RJPP | Vol. 3, Iss. 1, Spring 2020

Volume 3, Issue 1 Spring 2020

rice university journal of public policy

Š 2020 by The Rice Journal of Public Policy This material may not be quoted or reproduced without prior permission, provided appropriate credit is given to the author and the James A. Baker III Institute for Public Policy.

This paper has been edited by students of The Rice Journal of Public Policy and, wherever feasible, by outside experts.

This journal is financed and supported by the James A. Baker III Institute for Public Policy. However, the research and views expressed in this paper are those of the individual student(s) and do not necessarily represent the views of the James A. Baker III Institute for Public Policy.

staff

Executive Team

Short Form Editors

JENNIFER FU

LIA MARTIN MOLLY WANCEWICZ ANTHONY D’SOUZA CLAIRE NOEL

Editor-in-Chief

GABRIELLE HUMPHREY Managing Editor

DALIA GULCA

Director of Design

ANIKA JAIN

Short Form Head

SOPHIE PEREIRA Long Form Head

Long Form Editors SU CHEN TEH LARA LIN MASON REECE ALEJANDRO ESCOBEDO

Design Team

MIMI BAKER

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Advisor

Sourcing Manager Publicity Manager

JOE BARNES

Bonner Means Baker Fellow at The Baker Institute for Public Policy

acknowledgements The Rice Journal for Public Policy would not have been possible without the support of the James A. Baker III Institute for Public Policy. Thank you to all the writers, editing team and design team for working together to publish our third edition amidst a worldchanging health crisis. Special thanks to Madison Grimes and all our colleagues at the Baker Institute Student Forum for their assistance. As always, we hope to continue working with our peers and students at Rice University to bring you future editions of the RJPP.

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rice university journal of public policy Note from the Editor Dear Reader,

Thank you for picking up a copy of the 2019-2020 edition of the Rice Journal for Public Policy. While many of the pieces in this journal were written before the global crisis that came to define this year, we believe its publication only serves to show the fortitude of our campus and our communities beyond. The publication of this journal strikes differently than any previous versions due to a huge disturbance in our workflow from the pandemic. The majority of the designing and fabrication of the journal was accomplished beyond our normal timeline by dedicated team members who persevered to finish the journal in the face of rapidly changing and extraordinary events. In particular, I want to thank the design team for their work in finishing the formatting of the journal past our usual term.

Our desire to bring you this journal shows that we believe its contents are incredibly important and relevant to our world now. Before the year is through we will have a witnessed and participated in another presidential election, this one perhaps even more unprecedented that the one in 2016. Policy will continue to play an incredibly large part in crafting our healing, our changes and laying a new path towards our collective future. The Rice Journal of Public Policy is dedicated to reducing the barriers for young voices to participate and educate themselves on these significant debates. We hope that you will join us in our work, either through writing, reading or providing feedback to your peers. If you have any comments or suggestions, you may reach us at ricejpp@gmail.com.

With gratitude, Jennifer Fu RJPP Editor-in-Chief 2019-2020 Rice University, Class of 2020

RJPP Vol. 3, Iss. 1 5

table of contents 8-43

BISF 2019 Competition Winners The Baker Institute Student Forum, the undergraduate student arm of the Baker Institute for Public Policy, hosts a public policy competition on different topics each year. For 2019, the theme of the competition was centered on health and technology policy. Rice undergraduate students were invited to submit a policy proposal on how to best address existing problems or new opportunities in issues surrounding domestic health and technology. The top three winners of the competition are spotlighted in our journal. To learn more about the annual BISF Policy Competition, visit their website at http://bisf.bakerinstitute.org/ policy-competition.

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Restoring Online Discourses: A Proposal for Increasing US Support for AI-Powered Bot Identification Systems ANNIE CHEN

Rice University 2021

22

Policy Initiatives Addressing Federal Science Research ESHAAN PATEL

Rice University 2020

34

Addressing Opioid Withdrawal and Treatment for Incarcerated and Formerly-Incarcerated Individuals in West Virginia ELIZA MARTIN & TERESA SMITH Rice University 2019

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Selected Papers These articles were selected from a pool of undergraduate students writing on an array of topics from Supreme Court politics to renewable energy. Our campus fosters a diverse background of interests and as such we find it pertinent to show various areas of the policy world.

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Healthcare Equity and Research Bill (HERB) CATELIN DAVIS

Rice University 2021

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Development Finance Policy for Universal Electricity Access TRISHA GUPTA & LISA LIN Rice University 2023

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Intellectual Property Rights Protection: An Examination of Causal Context in the People’s Republic of China JACOB J. KOELSCH Rice University 2022

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Increasing the Resilience of Puerto Rico’s Electricity Grid for Future Disasters ALICE LIU

Rice University 2020

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The Effects of a Proportional Wealth Tax to Subsidize College Education: A General Equilibrium Model CLAIRE SKINNER

Rice University 2020

88

An Analysis of Bias in the US Supreme Court SOPHIA G. PEREIRA Rice University 2021

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BISF 2019 Competition Winner

Restoring Online Discourses:

A Proposal for Increasing US Support for AI-Powered Bot-Identification Systems ANNIE CHEN

Rice University 2021 Abstract

In the days following the 2016 US Presidential Election, the prevalence of automated actors on social media known as “bots” became a salient issue with far-reaching consequences for both online discourse and the integrity of future elections.

The ensuing investigations found that bots manipulated trending discussion topics, boosted the follower numbers of public figures, and even started mock grassroots movements online, all of which had direct implications for the electoral process.1 However, the US government’s response to the threat of automated misinformation campaigns online has been lukewarm at best, leaving the problem mostly to social media companies and their security teams who are barely keeping the stream

of bots at bay. Moreover, the US has also been less than enthusiastic in its efforts to support the development of related AI technology that is needed for bot-identification.

Meanwhile, countries like Russia and China have made AI development a central part of their defensive and offensive strategies, taking advantage of the US’s lack of involvement in its private sector to bolster their own innovations. In this paper, we examine the present state of the social bot problem and the government’s current efforts to address it, propose that the US increase its investment in AI technology by increasing its engagement with relevant tech startups through Department of Defense initiatives, and discuss some of the most common societal and scientific concerns

Howard, Philip N. “How Political Campaigns Weaponize Social Media Bots.” IEEE Spectrum: Technology, Engineering, and Science News. October 18, 2018. Accessed January 29, 2019. https://spectrum.ieee.org/computing/software/how-political-campaigns-weaponize-social-media-bots.

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regarding the use of bot-identification systems. We conclude that the proposal will be capable of countering the effects of malicious political bots at minimal societal cost.

I. Introduction

The prevalence of bots on social media is becoming an increasingly salient issue for users, tech companies, and governments alike.

At a time where over 70 percent of US adults use Facebook, with three-fourths of that group using it daily, the presence of bots and the information they disseminate have a serious impact on society.2 This is not even taking into consideration the millions of users on Twitter and other social media platforms such as Youtube. These automated accounts and networks are now an inescapable part of online discourse, and they exercise an astounding degree of power over social media interactions. Some studies estimate that bot traffic made up over 50% of all online traffic in 2016 alone.3 Due to low entry barriers and general lack of accountability, social media is particularly susceptible to influence by automated actors.

This paper will focus mostly on the category of bots known as “social bots”, a term which describes “a user account that has been equipped with the features or software to automate interaction with

At a time where over 70 percent of US adults use Facebook, with threefourths of that group using it daily, the presence of bots and the information they disseminate have a serious impact on society. other user accounts (human or otherwise).”4 Note that the term “social bot” is distinct from the term “socialbot.” “Social bot” with the space is a broader term that includes any program which produces content through an automated process, interacts with humans on the social media platform, and is usually accompanied by some stipulation of mimicking human users, whereas “socialbot” without the space refers explicitly to automated networks of false identities that infiltrate real user networks.5 Within the social bot category, this paper is mostly focused on the discussion of political bots, or social bot networks deployed for political purposes.

II. Background Bot Activity on Social Media Negative Effects

A prime example of the impact of malicious automated social media occurred during the 2016 presidential election, where Russian ad campaigns reached more than 126 million Facebook user accounts and reached another 29 million with divisive political content posted by the Internet Research Agency, a secretive Russian company with suspected ties to the Kremlin.6 In addition to Facebook, foreign agents also targeted other popular social media

Ibid.

Horowitz, Michael, Paul Scharre, Gregory C. Allen, Kara Frederick, Anthony Cho, and Edoardo Saravalle. “Artificial Intelligence and International Security.” Center for a New American Security. July 10, 2018. Accessed January 29, 2019. https://www.cnas.org/ publications/reports/artificial-intelligence-and-international-security.

4 Howard, Philip N., Samuel Woolley, and Ryan Calo. “Algorithms, Bots, and Political Communication in the US 2016 Election: The Challenge of Automated Political Communication for Election Law and Administration.” Taylor and Francis Online. April 11, 2018.

Accessed January 29, 2019. https://www.tandfonline.com/doi/full/10.1080/19331681.2018.1448735.

5 Gorwa, Robert, and Douglas Guilbeault. “Unpacking the Social Media Bot: A Typology to Guide Research and Policy: Unpacking the Social Media Bot.” Research Gate. August 2018. Accessed January 24, 2019. https://www.researchgate.net/publication/326973601_Unpacking_the_Social_Media_Bot_A_Typology_to_Guide_Research_and_Policy_Unpacking_the_Social_Media_Bot. 6 Howard, Philip N., “How Political Campaigns Weaponize Social Media Bots.”

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platforms like Twitter and Google’s YouTube, posting more than 131,000 tweets and 1,100 YouTube videos at around the same time period.7 The entire effort was spearheaded by bots and botnets that engaged in political rumor-mongering, sharing links to Kremlin-sponsored news sources and spreading highly edited or false news.8 Research has already demonstrated that these kinds of social bots, deployed en masse, are capable of generating political impacts. Studies show that in 2016, bot activity accounted for more than 50 percent of total online traffic,9 a number that will almost certainly increase in the future as bot technology improves and becomes more easily accessible.

While the bots have not been demonstrably effective in changing people’s opinions, they are disturbingly helpful when used to discredit political leaders or journalists, particularly women. They also exhibit a tendency to boost the strength of negative messages.10 Due to sheer numbers, bots also have the capability to essentially “set the agenda” for online discourse by amplifying chosen content.11 Bots have also been used to boost the follower number of public fig-

ures, making them seem more popular than they actually are.12 Furthermore, social bots can be powerful tools for spreading misinformation online, and they are particularly egregious when deployed in social media spaces that have little to no fact checking or other external checks. As of now, researchers have identified and categorized some of the most common strategies exhibited by social media bots. Among these tactics are zombie electioneering, astroturf campaigns, hashtag hijacking (particular to Twitter), Retweet storms (a general tactic also applicable to platforms other than Twitter), and strategic flagging.13 Zombie electioneering attempts to create the appearance of broad support for an issue or candidate through a variety of tactics, including but not limited to automated commentary, sharing relevant stories, etc.14 Astroturf campaigning is similar, but its focus is on making the political campaign appear to be a grassroots movement.15 Hashtag hijacking entails co-opting the opponents’ hashtags to undermine support by injecting spam or negative discourse into the feed of the opponents’ supporters.16 Retweet storms involve the simultaneous reposting or retweeting of a

post by hundreds or thousands of bots.17 Finally, strategic flagging involves turning what little regulatory procedures a social media company may have against the target by flagging legitimate posts as containing inappropriate content, making the posts vulnerable to deletion.18 All of these tactics were deployed in the 2016 presidential election season, where the capability of such campaigns to undermine trust in democratic institutions became clear.

Positive Effects

Although social media bots have the potential to be manipulated for malicious purposes, many people do use them in benign fashions. Such online bots have a wide range of content and activities, and many even provide useful services and entertainment. Primarily commercial bots may be responsible for actions such as the promotion of products while political bots may express views on different current events. Still other bots serve a variety of purposes ranging from earthquake early warning systems to sending new followers automated thank-you notes.19 Some social bots are also used to distribute informative tweets and posts, thus increasing the dissemination of accurate

Ibid.

Howard, Philip N., “Algorithms, Bots, and Political Communication in the US 2016 Election.”

9 Horowitz, Michael, “Artificial Intelligence and International Security.”

10 Ibid.

11 Ibid.

12 Ibid.

13 Howard, Philip N., “How Political Campaigns Weaponize Social Media Bots.”

14 Ibid.

15 Ibid.

16 Ibid.

17 Ibid.

18 Ibid.

19 Lamo, Madeline, and Madeline Lamo. “Regulating Bots on Social Media Is Easier Said Than Done.” Slate Magazine. August 09, 2018. Accessed January 29, 2019. https://slate.com/technology/2018/08/to-regulate-bots-we-have-to-define-them.html.

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information and counteracting the spread of false messages.20 The complex nature of bot activity on social media makes it inherently difficult to implement regulations. For example, a blanket ban on these technologies would be an overly simplistic solution that does not take into account the nuances of online bots, and it would likely result in the shutdown of helpful bots upon which many businesses and individuals rely.21 For this reason, any future legislation regarding social bot regulation must be predicated on the existence of technologies that can distinguish benign bots from malicious bots.

The Role of AI in Social Bot Identification In 2017, Facebook alone admitted to having an estimated 270 million fake accounts, and researchers from Indiana University and the University of Southern California reported that approximately 9 to 15 percent of all Twitter accounts were bots.22 Due to the sheer scale of the problem, human efforts alone could never hope to achieve anything close to a comprehensive solution.

The yet-unexplored realms of artificial intelligence hold vast potential for tackling the issue of social media

bots, and many researchers are already beginning to turn their attention to the problem of bot-identification by bringing in AI technology, with the most popular approach thus far being supervised machine learning algorithms.23 Machine learning is a form of AI that enables systems to learn from data and improve over time, and the technology is well suited for bot-detection due to its adeptness at analyzing the differences between human users, benign bots, and malicious bots.24 Several promising research projects have already been conducted regarding the potential of AI and AI-related techniques to assist with social media bot identification.

For example, a study conducted in 2018 by scientists from Southern Methodist University created a machine learning system designed to detect bots on Twitter. The system incorporated a wide range of features, including “length of usernames, reposting rate, temporal patterns, sentiment expression, followers-to-friends ratio, and message variability,” for bot detection, achieving an overall 2.25% misclassification rate.25 The reported true positivity rating for spambots (i.e. the percentage of spambot accounts that were correctly classified

as spambots) was 97.13%, and follower bots were correctly classified in 100% of the cases presented.

These results indicate that the features selected for the algorithm were extremely well-adapted to identifying follower bots.26 Another example of AI bot identification concerns the upgrading of a popular bot-detection tool known as Botometer that has already been put into circulation by researchers at Indiana University.

The Botometer is a supervised machine learning system that was first made available in 2014 for Twitter, and it analyzes over 1,000 features from a given account to produce a bot classification score that informs the user of the likelihood that the analyzed account is automated.27 The 2019 study examined the necessity of updating detection tools with new training data and user feedback along with the need to evolve analyzed feature sets to capture the behavior of new bot classes.28 Additional updates were found to have increased Botometer’s overall accuracy from 0.95 to 0.97 AUC, a measurement which “quantifies the probability that a classifier will rank a randomly chosen bot higher than a randomly chosen human.”29 Despite such improvements, howev-

Oentaryo, Richard J., Arinto Murdopo, Philips K. Prasetyo, and Ee-Peng Lim. “On Profiling Bots in Social Media.” Lecture Notes in Computer Science Social Informatics, November 2016, 92-109, p. 92. Accessed January 29, 2019. doi:10.1007/978-3-319-47880-7_6.

21 Ibid., p. 93.

22 Morse, Jack, and Jack Morse. “Why Social Media Companies Won’t Kill off Bots.” Mashable. February 07, 2018. Accessed January 29, 2019. https://mashable.com/2018/02/06/facebook-instagram-twitter-bots/#KyYJMKaL2qqa.

23 Yang, Kai-Cheng, Onur Varol, Clayton A. Davis, Emilio Ferrara, Alessandro Flammini, and Filippo Menczer. “Arming the Public with AI to Counter Social Bots.” Research Gate. January 2019. Accessed January 29, 2019. https://www.researchgate.net/publication/330185799_Arming_the_public_with_AI_to_counter_social_bots.

24 “AI Can Help Battle Bots.” MeriTalk. March 13, 2018. Accessed January 29, 2019. https://www.meritalk.com/articles/ai-can-helpbattle-bots/.

25 Efthimion, Phillip G., Payne, Scott, and Proferes, Nicholas. “Supervised Machine Learning Bot Detection Techniques to Identify Social Twitter Bots,” SMU Data Science Review 1, No. 2 (2018): Article 5, p. 1.

26 Ibid., p. 16.

27 Yang, Kai-Cheng, “Arming the Public with AI to Counter Social Bots.”

28 Ibid.

29 Ibid.

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er, the overall US capability of AI bot identification and AI technology as a whole still leaves much to be desired.

US Information Security and Social Media Since the controversy of the 2016 election, the US has taken a number of steps to begin to counteract the problem of automated social media accounts. Following the public outcry, the federal government increased its efforts to pressure big tech companies like Facebook and Twitter to crack down on their automated accounts. Previously, tech companies had been reluctant to do so because they have financial incentives to maintain the status quo.

Unmonitored flows of information and viral stories attract clicks and advertising revenue regardless of their factualness, and any imposed limits on that kind of traffic would dent company revenues.30 Requiring social media companies to moderate the content posted on their sites would decrease the traffic rates they receive from bots, raise costs for security, and decrease their overall profits.31 As such, government involvement is necessary to incentivize such companies to begin to seriously self-regulate.

The financial disincentive of social media companies for bot account regulation has sparked many lawmakers’ interest in pro-

posing fines for companies that do not comply with Congressional demands. However, even these companies have started to admit that the scale of the problem may be too large for them to handle alone.

The testimonies of Twitter CEO Jack Dorsey and Facebook CEO Mike Zuckerburg before Congress last September both suggested that social media giants are struggling to keep up with the continuous stream of automated accounts and messag-

conjunction with the private sector to counteract the sheer scale and urgency of the problem.

Federal and state legislatures have also attempted to come up with their own solutions to the problem, resulting in a flurry of recent bills that attempt to regulate social media bot accounts in a variety of ways. Bot self-identification legislation has been proposed at the federal level, New Jersey, and California, where it has already passed the

As of now, the US is not equipped to handle the influx of automated social media accounts and the consequences they bring about. es that permeate both sites.32 At the point where the companies do not have the technological edge needed to identify and dispose of malicious bots quickly enough, simply fining them for their failure to remove the bots will not be sufficient to resolve the problem. Rather, such an admission opens the door for governmental intervention efforts that work in

state’s Senate and received governor approval in September 2018.33 However, such legislation has provoked significant concern from the scientific community and from legal observers who are, respectively, worried about the impact of the bills on future tech developments and free speech rights.34 Furthermore, the same limitations of bot-finding

Tusikov, Natasha. “Regulate Social Media Platforms before It’s Too Late.” The Conversation. December 30, 2018. Accessed January 29, 2019. https://theconversation.com/regulate-social-media-platforms-before-its-too-late-86984.

31 Howard, Philip N., “How Political Campaigns Weaponize Social Media Bots.”

32 Tangermann, Victor. “Social Media Giants Need Regulation from a Government That’s Unsure How to Help.” Futurism. September 05, 2018. Accessed January 29, 2019. https://futurism.com/social-media-congress-government-regulation.

33 Gevorkian, Ani, and Jadzia Pierce. “IoT and AI Update: California Legislature Passes Bills on Internet of Things, Artificial Intelligence, and Chatbots.” Inside Privacy. October 04, 2018. Accessed January 29, 2019. https://www.insideprivacy.com/uncategorized/ ot-and-ai-update-california-legislature-passes-bills-on-internet-of-things-artificial-intelligence-and-chatbots/.

34 Weaver, John. “Everything Is Not Terminator: We Need The California Bot Bill, But We Need It To Be Better - New Technology United.” McLane Middleton. September 25, 2018. Accessed January 29, 2019. http://www.mondaq.com/unitedstates/x/739116/ 30

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technologies that are troubling the social media companies also apply to these bills, for there would be no way to enforce compliance with the bills if bots could continue impersonating as people online without being identified. Therefore, we can see that successful bot-legislation in the US is contingent upon the establishment of reliable bot-detection technology, of which AI is an indispensable part.

Despite promising developments, current AI bot-detection technologies in the US are still outpaced by those that disseminate targeted propaganda and misinformation.35 The increasing inability to compete is a recurring issue with AI technology in the US as a whole due to the overall lack of federal investment in comparison to other countries.36 As of now, the US is not equipped to handle the influx of automated social media accounts and the consequences they bring about.

At the federal level, the lack of a clear strategic approach for combating online misinformation campaigns has made it difficult for the government to engage in regulatory practices, and existing technical limitations on bot-identification make any regulation difficult to enforce in the first place.37

The problem is also exacerbated by the US’s relative lack of investment in AI in comparison to many foreign countries, especially China. China’s total spending on AI technology in 2017 was estimated at around 12 billion, a number expected to increase to more than 70 billion by 2020, and they are also ranked first globally for the number of academic papers and citations on machine learning in addition to increasing their AI patent numbers by 200%.38 In addition, the US also has to account for the looming presence of Russia, which has made AI driven asymmetric warfare (ADAW) in the realm of digital information a central tenet of its strategy against the West.39 AI has the capability to supercharge Russia’s misinformation campaigns abroad in both Europe and the US, and their relative low cost allows the Russian government to wage “cost-effective and high-impact” information wars to great effect.40 The full cost of highly publicized Russian interference operation during the 2016 US election was estimated to be around 1 million dollars, and such campaigns will only increase in the future, acting as a continuous threat against US democratic institutions.41

Furthermore, these countries have taken advantage of the US’s lack of early-stage support for its tech startups and filled in the investment gap in the US commercial market to bolster their own innovations. Russian affiliates have engaged in nearly 300 funding rounds with US startups over the past seven years, and China has also made over 1,000 deals worth around 30 billion dollars total with US tech startups from 2010 to 2016.42 These investments by foreign actors have resulted in the unregulated transfer of cutting-edge US technology with military applications to rivals overseas, technology that can then be weaponized against the US in the form of more sophisticated bots and AI systems. The US must take immediate action to close early-stage startup funding gaps and increase its own investment in AI if it is to regain its comparative advantage in tech innovation.

III. Proposal

In order to mitigate foreign misinformation campaigns and preserve the foundations of US democracy, the country is in urgent need of artificial intelligence systems that are capable of identifying and label-

new technology/The content of this article is intended to provide a general guide.

35 Horowitz, Michael, “Artificial Intelligence and International Security.”

36 Andriole, Steve. “Artificial Intelligence, China And The U.S. - How The U.S. Is Losing The Technology War.” Forbes. November 09, 2018. Accessed January 29, 2019. https://www.forbes.com/sites/steveandriole/2018/11/09/artificial-intelligence-china-and-the-ushow-the-us-is-losing-the-technology-war/#6b63b7bc6195.

37 Kodner, Sofie. “Covert Bots: The Cyber-Nuisances Threatening Our Newsfeeds and Our Democracy.” Nuclear Stability in a Post-Arms Control World | Center for Strategic and International Studies. Accessed January 29, 2019. https://www.csis.org/npfp/ covert-bots-cyber-nuisances-threatening-our-newsfeeds-and-our-democracy.

38 Andriole, Steve. “Artificial Intelligence, China And The U.S.” 39 Polyakova, Alina. “Weapons of the Weak: Russia and AI-driven Asymmetric Warfare.” Brookings.edu. November 16, 2018. Accessed January 29, 2019. https://www.brookings.edu/research/weapons-of-the-weak-russia-and-ai-driven-asymmetric-warfare/.

40 Ibid.

41 Ibid.

42 Israel, Joshua. “Commercial Accelerators and the Defense Department: A Blueprint for Collaboration.” War on the Rocks. March 14, 2018. Accessed January 29, 2019. https://warontherocks.com/2018/03/commercial-accelerators-and-the-defense-department-a-blueprint-for-collaboration/.

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ing malicious social bots quickly and accurately. Additionally, if the US is to be able to compete in the international realm of AI technology, it must increase its investment in the field and ensure a continuous flow of innovation to prevent its technologies falling behind that of other countries in the AI arms race. The competition between malicious social bot creators and bot-detectors is an ongoing one, and tech measures to counteract social bot influence must have the US government’s full support.

To achieve these objectives, we recommend that the federal government increase its investment in AI bot-detection technology by increasing the Department of Defense’s engagement and partnership with relevant AI startups through the Defense Innovation Unit and similar ventures. This proposal is intended to build and develop a viable working relationship between cutting-edge technological start-ups and the Department of Defense as well as to independently encourage private sector innovation. In the short term, the proposal aims to increase investment in innovative AI social bot-detection techniques that reduce both false positives (classifying human users as bots) and false negatives (classifying bots as human users). Additionally, the proposal addresses the existing federal investment gap for startups.43 The

ultimate long-term goal of this proposal is to help reestablish the US’s technological advantage in the field of social bot AI. With social media companies and other domestic actors struggling to keep pace with foreign-based bot creators, the US federal government needs to adopt such a policy to support its own methods of countering misinformation and regain its technical edge.

of the DIU was launched in 2016 with a new branch office in Boston and measures to expedite the contracting process, managing to lower department contracting times from the previous 6-12 months to within 60 days.46 In August 2018, the DOD made the DIU a permanent part of the DOD, and it now has branch offices in Austin and Washington D.C. in addition to the Silicon Valley and Austin branches.47

Department of Defense and AI Startup Partnership In recent years, the Department of Defense (DoD) has created a number of initiatives to try and prioritize research and development efforts in AI. The Defense Innovation Unit (DIU), formerly known as the Defense Innovation Unit Experimental (DIUx), is one of the most important of these efforts, as it was the Department’s most high-profile outreach effort to tech startups.44 Founded in 2015, the DIU was originally stationed in California’s Silicon Valley to help the DoD acquire emerging technology with military applications more quickly. However, the first iteration of the program came under fire from Congress for its slow transaction speeds, singular geographical focus, and general failure to contract nontraditional startups.45 In response to these criticisms, a second version

The Defense Innovation Unit: A Closer Look

The main function of the DIU is to facilitate cooperation with promising tech startups by providing non-dilutive funding and an expedited contracting process in comparison to the actual DoD.48 Non-dilutive funding is a particular way to finance a company that does not compromise ownership of the company itself.49 Both the contract process and the non-dilutive funding are intended to attract startup partnerships. The DIU also offers a special kind of contract known as “Other Transaction (OT) agreements” or “pilot contracts” which provision negotiable payment terms and intellectual property rights.50 The DIU also offers more flexibility for companies in terms of relief from federal acquisition regulations, and they provide important opportunities for startups in terms of both direct customer feedback and

Yang, Kai-Cheng, “Arming the Public with AI to Counter Social Bots.”

Mitchell, Billy. “’No Longer an Experiment’ - DIUx Becomes DIU, Permanent Pentagon Unit.” Fedscoop. August 09, 2018. Accessed January 29, 2019. https://www.fedscoop.com/diu-permanent-no-longer-an-experiment/.

45 Ehlinger, Samantha. “Ash Carter on DIUx 1.0: Speed Was the Issue.” Fedscoop. September 13, 2016. Accessed January 29, 2019. https://www.fedscoop.com/ash-carter-on-first-diux-speed-was-the-problem/.

46 Ehlinger, Samantha. “Carter: DIUx Armed with New Method to Develop Tech Faster.” Fedscoop. July 26, 2016. Accessed January 29, 2019. https://www.fedscoop.com/diux-armed-with-new-method-to-develop-tech-faster/.

47 Mitchell, Billy. “’No Longer an Experiment.’”

48 “Work With Us.” Defense Innovation Unit. Accessed January 29, 2019. https://www.diu.mil/work-with-us/companies.

49 “Non-Dilutive: Everything You Need to Know.” UpCounsel. Accessed January 29, 2019. https://www.upcounsel.com/non-dilutive.

50 “Work With Us.” Defense Innovation Unit.

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product testing along with potential follow-on funding for successful pilot contract startups.51 This model of operations has already granted more than 100 million dollars worth of government contracts to 45 different startups as of 2017, and some of those acquired technologies are already in use.52 However, despite the commitment of the DIU to acquire developing technologies more efficiently, there is still a conspicuous lack of initiatives intended to combat targeted misinformation campaigns in online platforms. Out of the 41 startup companies listed under portfolio tab on the DIU website, none were targeted towards countering malicious, automated actors distributing information.53 Therefore, the proposal recommends for the DIU to increase its outreach efforts to startups and initiatives regarding AI social bot identification systems in all stages of the startup funding process.

The Startup Funding Process

The first four rounds of the startup funding process are respectively known as Seed, Series A, Series B, and Series C. The later the round of funding, the more mature the company, which decreases the risks of investment at the cost of

lower returns. At the seed round of funding, startups strive to prove that they have an idea that creates a marketable solution for an existing problem, a process known as the “product-solution” fit.54 Series A startups move to the “product-market” fit, where they try to demonstrate that their product and business are monetizable and have the potential to generate long-term profits.55 At this stage, companies attempt to expand its product’s user numbers as well as seek out customers who are willing to use incomplete versions of the product and provide the feedback needed for improvement. Series B startups focus on perfecting their marketing strategy, expanding their customer base and market reach, and growing the company in accordance with increasing demand.56 Series C startups are even further along in this process, with an emphasis on scalability and expansion to new markets.57 Increasing DoD Assistance in the Startup Funding Process

Due to the DoD’s overall focus on acquiring products rather than early investments, the current DIU has mostly been focused on helping late stage startup companies, usually Series C or beyond, with early startups comprising less than 5%

of their portfolio.58 We recommend that early stage startups should also be included in this outreach effort because early investment is critical to influencing the development direction of commercial technology.

A successful partnership strategy between the DoD and tech startups would allow the Defense Department to capture technological innovation earlier than any other actors, including foreign governments businesses, thus allowing the sector to regain its traditional technological advantage.59 Recognizing the stage that startups are in and understanding the obstacles that they face in each round of funding is critical to building successful DoD partnerships with emerging tech companies. The DoD is in an excellent position to help companies at all stages of the process, and the aforementioned DIU process embodies many of the ways that the federal government can benefit fledgling companies. For example, the non-dilutive funding that the DIU provides is attractive to startups, especially those at the Seed and Series A stages, because it results in an increase in the company’s valuation without impacting ownership.60 The process is also mutually beneficial for the DoD as it can focus on providing low to me-

Ibid.

Marcelo, Philp. “Experimental Defense Unit Funds New Tech but Faces Skeptics.” Phys.org - News and Articles on Science and Technology. August 10, 2017. Accessed January 29, 2019. https://phys.org/news/2017-08-experimental-defense-funds-tech-skeptics. html.

53 “Portfolio.” Defense Innovation Unit. Accessed January 29, 2019. https://www.diu.mil/portfolio.

54 Decker, Jeff. “Renewing Defense Innovation: Five Incentives for Forming Pentagon-Startup Partnerships.” War on the Rocks. May 07, 2018. Accessed January 29, 2019. https://warontherocks.com/2018/05/renewing-defense-innovation-five-incentives-for-forming-pentagon-startup-partnerships/.

55 Ibid.

56 Reiff, Nathan. “Series A, B, C Funding: How It Works.” Investopedia. December 21, 2018. Accessed January 29, 2019. https:// www.investopedia.com/articles/personal-finance/102015/series-b-c-funding-what-it-all-means-and-how-it-works.asp.

57 Ibid.

58 Decker, Jeff. “Renewing Defense Innovation.”

59 Ibid.

60 Ibid.

51 52

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According to the US Supreme Court, the first amendment protects freedom of speech regardless of the medium used, and that includes new forms of expression resultant from emerging technologies that could potentially include social bots. dium loan amounts for companies ranging from $100,000 to $500,000, which is a fairly minimal cost for acquiring new technologies.61 In addition, the product-testing the DIU process offers is also extremely valuable to Seed and Series A companies. Due to its budget size and longterm focus on national security, the department is also less sensitive to early product failures. Therefore, working with the DoD can provide many startups with product testing and feedback at a much larger scale than private investors can.62 Working with the DoD also allows expansion-oriented Series B and Series C startups to access one of the largest and most lucrative markets worldwide.63 All of these benefits could and should be extended to startups at all stages that aim to combat online misinformation. The applica-

tion of such benefits would greatly expand the US’s technical capability to target future misinformation campaigns.

Existing Startups

There are numerous existing startups that are engaging in innovative work to combat digital misinformation. To name a few of these companies, Distil Networks is a Series C startup valued at 21 million that uses AI-powered machine learning techniques in bot-detection and blocking.64 PerimeterX is a similar Series B startup that uses AI to analyze the behavior of website visitors, identifying patterns and blocking users that do not behave like humans.65 Another company called Userfeeds is a Seed-stage startup that aims to create auditable content trails to counteract bots that hijack social media ranking systems

by inflating upvote counts.66 In addition, a Seed stage company known as New Knowledge is focused on analyzing conversation content in social media platforms to look for signs of manipulation and locate the source of tampering.67 With more companies of similar motivations springing up in the US and around the world, the DoD has ample opportunities to start bringing some of these new innovations into the fold.

The Need for GovernmentCommercial Partnership

While many of the aforementioned startups were backed by venture capital (VC) funding, soliciting only VC funds is actually detrimental for startup companies for several reasons. Normally with venture capital (VC), investors expect the company they have invested in to exit at high values, usually millions of dol-

Israel, Joshua, “Commercial Accelerators and the Defense Department.”

Decker, Jeff. “Renewing Defense Innovation.”

63 Ibid.

64 “7 Startups Combating ‘Fake News’.” CB Insights Research. January 09, 2018. Accessed January 29, 2019. https://www.cbinsights. com/research/startups-combating-fake-news/.

65 Ibid.

66 Butcher, Mike. “Userfeeds Aims to Stop Fake News by Linking the Blockchain to Social Content.” TechCrunch. May 03, 2017.

Accessed January 29, 2019. https://techcrunch.com/2017/05/03/userfeeds-aims-to-stop-fake-news-by-linking-the-blockchain-to-social-content/.

67 Loizos, Connie. “A Young Startup with a Timely Offer: Fighting Propaganda Campaigns Online.” TechCrunch. January 26, 2018.

Accessed January 29, 2019. https://techcrunch.com/2018/01/26/a-young-startup-with-a-timely-offer-fighting-propaganda-campaigns-on-social-media/.

61 62

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lars or more, but the situation is different with AI startups where most successfully exited companies often sell for values below 50 million.68 Therefore, when several VCs invest in a single AI startup, that company can no longer consider the usual merger and acquisition offer of 50 to 100 million and must instead turn to increasing its scale of operations to try and aim for a much higher valuation later.69 Scaling the company has a high chance of alienating the AI startup’s core founders, which are usually a small group of technical experts inexperienced with running a large company.70 Furthermore, increasing the size of the company may actually devalue the business in the eyes of potential buyers who usually are interested only in the core technical team and the algorithm, as such buyers would be reluctant to pay to acquire extraneous personnel.71 In contrast, the mission and budget of the DoD allow it to invest in companies for the sake of their inventions and not so much for the long-term financial return, thereby avoiding most of the aforementioned problems.

ed to free speech implications, there are still some important concerns to address. According to the US Supreme Court, the first amendment protects freedom of speech regardless of the medium used, and that includes new forms of expression resultant from emerging technologies that could potentially include social bots.72 The way that most bot-identifier technology would conceivably be used as of now can be found in bot-identification legislation. This type of legislation typically requires all online bots to self-identify as such, thereby resulting in a form of compelled speech. Bots would be required to disclose information when they may not have been inclined to do so previously.73 This implication raises questions of whether an increase in the usage of bot-identification technologies would result in unconstitutionally compelled speech.

Historically, the Zauderer v. Office of Disciplinary Council Supreme Court case ruling suggests that governments are allowed to compel speech in certain cases, particularly when it concerns information about commercial products and services.74 However, such power does not translate to the government’s abiliAddressing Concerns ty to create unconditional disclosure Regarding Socialrequirements, especially at the point Bot Identification which the speaker is forced to adTechnology vocate for a view they do not agree Freedom of Speech with. An example of this limitation While increasing investment can be found in the case of Pacific in bot-identification AI technology Gas & Electric Co. v. Public Utilities does not seem to be directly relat- Commission of California, where the

Supreme Court ruled that a private electric utility company could not be compelled to make room in its own newsletter for organizations advocating for decreased electricity consumption since such a requirement would essentially force the company to endorse ideas that are detrimental to their own interests.75 We argue that the increasing use of bot-identification technologies to identify political bots does not require the bots to endorse ideas that are contrary to their own interest or the message they are endorsing, nor does it necessarily send an ideological or imperative message to the individuals who see the disclosure statement. Rather, we argue that disclosure of bot-ness for political bots is more similar to the process of placing warning labels on cigarette packs, where consumers can learn more about the product but still decide for themselves what to do with that information and whether or not to believe it.

Furthermore, we argue that using technology to identify and disclose political bots would increase the flow of information and discourse quality in online political discourse in positive ways, as it would force individuals to more critically evaluate the information that is presented by bots who can no longer disguise themselves as people. The identification of political bots would also be effective in preventing the individual from falling prey to malicious campaigning tactics such as zombie

Basta, Victor, and Magister Advisors. “For AI Startups, More Funding Is Often Not the Answer.” VentureBeat. July 01, 2017. Accessed January 29, 2019. https://venturebeat.com/2017/07/01/for-ai-startups-more-funding-is-often-not-the-answer/.

69 Ibid.

70 Ibid.

71 Ibid.

72 Lamo, Madeline, and Ryan Calo. “Regulating Bot Speech.” SSRN Electronic Journal, July 16, 2018. Accessed January 29, 2019. doi:10.2139/ssrn.3214572.

73 Ibid.

74 Ibid.

75 Ibid.

68

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electioneering or astroturfing, as requiring the bots to identify as such would dispel the illusion that there is real popular grassroots support for the movement.

In terms of general governmental free speech regulations, the courts have held that the government may regulate “the time, place, or manner of speech only as long as the regulation (1) is content-neutral; (2) is narrowly tailored to serve a significant governmental interest; and (3) leaves open ‘ample alternative channel’ to communicate the information.”76 These requirements are meant to prevent the slippery slope of governmental free speech regulations that could potentially occur.

Here, the requirement that government regulations on free speech be specifically tailored to “significant governmental interest” is of particular interest when it comes to regulating political social bots because of the blurred delineation between political bots and political individuals expressing individual views, which means the justification for political-bot disclosure must be specific and tailored by context.77 For example, political bot identification could potentially be justified in the context of electioneering, where the government’s interest in providing free and fair elections could be invoked to compel disclosure of bots engaged in election manipulation practices.78 This insight is significant because

it indicates that it is possible to use bot-identification technologies and disclosure in a way that respects the constitution.

Ethics and Data Bias in Machine Learning and AI

One of the most important parts of developing AI systems is in regard to the data used to train the machine in machine learning.

This question can be divided into two parts: 1) the ethics of the process for procuring training data and 2) whether or not the data is accurate and at morally acceptable standards. Concerns about training data are particularly important for AI because previous versions of AI training have ended in publicized disaster, such as in Microsoft’s infamous Tay experiment where Twitter trolls trained the interactive AI to use racist and transphobic language.79 From there, it becomes apparent that the quality of data practices has enormous implications on AI systems and on the outcome of the final product.

There are three key principles to keep in mind when one is going through the process of gathering training data: 1) informed consent of data providers, 2) doing no harm to participants, and 3) preserving the anonymity of participants.80 These three principles make up the basics of ethical data collection for AI training. We argue that these principles could be easily adhered to

when we are collecting social media data for training bot-identification technologies. For public platforms like Twitter where all tweets can be publicly accessed and read, it can be argued that explicit permission from the tweeters is not required.81 For more private platforms like Facebook, an opt-in system could be used to ensure that participants are giving explicit consent for researchers to use their data. Data collectors should also make an effort to reach as many people as possible to try and prevent sampling bias in the data. In both cases, anonymity and prevention of harm to participants can be achieved by not publishing any individual tweets or account information.82 To ensure the accuracy and representativeness of the data used in machine learning, data collectors must be cautious of replicating existing human biases in their machines, specifically in the data that is used to train them. A biased machine is one that is overly rigid and unable to adjust to variations in the data that is used to train it, and the machine is also less sensitive to the minute differences within datasets.83 One of the best ways to minimize such biases is to pay close attention to the way the machine’s training dataset is crafted—by taking multiple samples from the population that the machine is to analyze and testing the representativeness of

Ibid.

Ibid.

78 Ibid.

79 Korolov, Maria. “AI’s Biggest Risk Factor: Data Gone Wrong.” CIO. February 13, 2018. Accessed January 29, 2019. https://www. cio.com/article/3254693/artificial-intelligence/ais-biggest-risk-factor-data-gone-wrong.html.

80 Efthimion, Phillip G., “Supervised Machine Learning Bot Detection Techniques,” p. 18.

81 Ibid.

82 Ibid., p. 19.

83 Myers, Courtney. “Detecting and Preventing Bias in AI and ML at the Source | Articles | Chief Data Officer.” Articles | Innovation | Innovation Enterprise. August 30, 2018. Accessed January 29, 2019. https://channels.theinnovationenterprise.com/articles/steps-todetect-and-prevent-bias-in-ai-and-machine-learning-at-the-source.

76 77

18

those samples, AI developers can ensure that their training dataset mirrors the real population as closely as possible.84 By ensuring the representativeness of the training dataset, developers can also avoid the problem of their machines being biased towards certain trends in the data, with an example being a dataset that highlights the prevalence of men in the construction workforce.

A machine that was trained using such data may then develop a bias by “learning” that workers in the construction workforce are all men, a turn of events that obscures the role women in the field.85 In terms of social media data, gathering representative samples of data to teach bot-detection technologies would involve being as inclusive in the sampling process as possible, which would involve gathering account profiles and other relevant information on the broadest possible scope. Additionally, the training data must be checked for accuracy to ensure that the bots and human accounts within the data are properly labeled. As the DoD has access to comprehensive datasets that span long periods of time, preventing

machine learning bias in developing AI systems is another incentive to increase partnerships between startup AI companies and the DoD.86 Such data would provide valuable training bases for startups that are trying to develop new AI machines that avoid machine bias. As such, we see that while data bias in the use of bot-detection systems is a valid concern, there are also numerous procedural steps that could be followed to mitigate those risks.

IV. Implications

Automated actors on social media are now a near-ubiquitous aspect of life online. When maliciously used, these social bots can have severely detrimental effects on both online discourse and democratic institutions. The US’s overall lack of focus and investment in the area of countering automated online misinformation campaigns with AI has only exacerbated the problem. Social media companies and their security task forces alone are no longer capable of stemming the tide on their own. In the meantime, countries like China and Russia have

been increasing their own inputs into AI research, even taking advantage of the US’s startup investment gap to fund and appropriate the innovations of the US commercial sector for their own use. It is high time that the US take the threat of political bots on social media seriously and invests in its own tech startups accordingly. By increasing investment into AI-powered bot-detection technologies through the DoD and increasing engagement with the private sector, the US can both regain its traditional technological edge in defense capabilities as well as identify and counteract the harms of malicious social bots. Critics have voiced cautions for both bot-identification AI’s potential free speech implications and possible ethical problems in the machine learning process, but both concerns can be largely mitigated by adhering to the proper procedures of AI use and development. Therefore, we conclude that our proposal is a feasible way for the US to nullify online misinformation and preserve the integrity of its democratic institutions at little cost to the general public.

Ibid.

Ibid.

86 Decker, Jeff. “Renewing Defense Innovation.”

84 85

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BISF 2019 Competition Winner

Policy Initiatives Addressing Federal Science Research ESHAAN PATEL

Rice University 2020

Abstract

Scientific research in the United States has produced some of the most impactful and transformative innovations humanity has witnessed. It has allowed for continuous economic growth, improvements in health and medicine, and discoveries in the nature of the universe. However, in its current state, it has many flaws that impede on its efficiency and ability to innovate and produce knowledge. Although the issues in scientific research are multi-faceted, this paper will focus on two important issues with federal science policy: funding and grant disbursement.

I will recommend three proposals to improve the current situation. The first proposal is to index science funding to inflation and will be implemented by allowing each agency to develop or borrow a price index that tracks the purchasing power of grant money. Because this policy will help maintain grant purchasing

22

power and decrease funding volatility, institutions and Principal Investigators (PIs) can make long term commitments, which will help foster more innovative and risky measures that could produce a lasting impact.

The second proposal is a modified lottery system which will dramatically alter the way grants are disbursed in the current system. It will maintain the current peer review system up to a point but then shift to using a random lottery to allocate funding amongst the best grant proposals. This program will eliminate many of the perverse incentives that PIs, institutions, and grant reviewers have in the current system. It will also reduce racial and gender discrimination, while making the process overall more transparent, fair, and cost-effective. Finally, the blue skies research program will help allow federal funding agencies to harness the innovative nature of high risk, high impact science by increasing the funding given to individual

PIs or labs, while simultaneously allowing maximum freedom in research directions and choices. Thus, the program invests in the innovative ability of researchers. While the costs of the program are limited, the benefits could be dramatic. Implemented together, indexed funding, the modified lottery system, and blue skies research can improve scientific research by reducing the distortions that the current system creates.

applied research, and development.

Basic research is research done without any aim besides discovering new information about the environment.

Applied research is research done with a certain goal, say to develop a vaccine for a disease. Development is the process of using research to create an applicable product or design. This policy paper will focus on federal nondefense spending on basic and applied research. This is not to say that defense research and the “development� portion of R&D is not important, but rather that it I. Introduction to lies outside of the scope of what scientific research this paper is trying to address. Furpolicy thermore, there are numerous isThe United States federal sues in academic science itself from government has long been in the business of funding scientific research through a handful of agencies centered on a variety of disciplines. The federal government began formally funding scientific research after World War II, and non-defense scientific research took a priority as well with the creation of the National Science Foundation in 1950 by President Truman. Since the mid-twentieth century, scientific research and development (R&D) has been growing with the government playing an increasingly large role in the funding of this research.

This is primarily due to the belief that investing in scientific research compensation and treatment of is a way to grow the economy, imgraduate students and postdoctorprove lives, and create a more prosal fellows to the faulty peer review perous world. Indeed, scientific resystem. However, these issues are search has produced some of the not well addressed by federal policy greatest innovations in technology, and should be addressed instead by health, medicine, and engineering internal discussion within research over the last century, from penicillin institutions. to the internet. However, scientific This paper will primarily adresearch is not without issues which impede efficiency and a proper dis- dress issues related to two of the largest funders of scientific research. covery of truth.

Together, they constitute the maFederal R&D is broken into jority of the federal government’s three components: basic research,

budget towards basic and applied scientific research: the National Institutes of Health (NIH) and the National Science Foundation (NSF), with budgets of $37.3 billion and $6.65 billion, respectively. The NSF is primarily responsible for funding basic research in the physical sciences, engineering, and select social sciences, while the NIH is responsible for basic and applied biomedical research geared towards making discoveries about human biological conditions. The NIH spends over 80% of its budget on funding individual research grants through a competitive process, and it spends 10% of its budget on supporting researchers in its own laboratories.

Although the issues in scientific research are multi-faceted, this paper will focus on two important issues with federal science policy: funding and grant disbursement.

Similarly, the NSF spends over 80% of its budget on individual research grants in a variety of disciplines, and it spends approximately 11% of its budget on funding educational activities such as graduate student fellowships. Despite the focus on these two organizations, the policy prescriptions recommended by this paper can be easily applied to other major funders of scientific research, such as the Department of Energy, NASA, and the Department of Ag-

23

riculture. The three policy proposals that follow will focus on improving two important issues with federal science policy: funding and grant disbursement policy.

$6.65 billion, which was a decrease from the previous year. However, Congress provided NSF with $7.8 billion in funding--a difference of over a billion dollars. Unfortunately, this example of Congress overfunding scientific research is not II. Policy #1: Indexing commonplace--it more often underScience Funding to funds these agencies. This arbitrary Inflation funding mechanism has a significant A. Existing Policy and effect on the recipients of this fundInadequacies ing. Many research labs depend on Federal scientific research stable sources of funding to continfunding has long been subject to the ue their research, and a sudden lack whims of Congress and the Execu- of funding can put a halt to promistive Office. Consequently, the funding for science has been anything but predictable, with short bursts of increased funding followed by long periods of stagnation. Accounting for inflation, which has generally hovered around two percent in recent decades, this means that during periods of stagnation the effective budget of scientific research actually decreased. Additionally, research is becoming more expensive to carry out because of more expensive equipment needed to discover new ideas, a reminder that much of the ing research. Furthermore, variable low-hanging fruit in research may funding levels can make the job of a have already been harvested. grant-writer, usually the PI who preThe current process of funding sides over the lab that conducts the each research agency in the govern- research, very stressful. Grant-writment is a somewhat arbitrary, back- ers are often unable to make longand-forth procedure between the term plans and commitments beagency and Congress. The agency cause of the volatility of research requests a certain amount of money funding. This prevents good scienfor the following fiscal year, usually tific research from taking place, bedependent on both the organiza- cause science often requires deep, tion’s beliefs about its funding needs continuous study, which cannot be as well as policy priorities of the achieved in just a few years. executive branch. Then, Congress B. Design of indexing appropriates some level of funding federal science funding to for the agency; however, this level inflation of funding can be drastically differIndexing federal programs to ent than what the agency request- inflation is not a novel idea in the ed. For example, for the 2018 fiscal United States. Currently, entitleyear, the NSF requested a budget of ment programs such as Social Se-

curity are indexed to inflation using the Consumer Price Index (CPI), which measures the rate at which prices in a basket of ordinary consumer goods grows from one year to another. This allows for Social Security to automatically adjust upwards by the same rate as inflation, so that beneficiaries of the program can maintain the same purchasing power over the years. There have been numerous advocates of indexing other federal legislation to inflation, from minimum wage to pell grants. The logic is as follows: when

Federal scientific research funding has long been subject to the whims of Congress and the Executive Office.

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establishing a funding mechanism, the purchasing power of the beneficiaries should stay constant unless legislation is enacted to increase or decrease the level of funding. Thus, political will is only required to change the purchasing power and is not necessary to maintain the yearly budget.

This proposal recommends each agency to create a robust price index for itself and for said agencies and Congress to then use these price indexes to set the minimum level of funding for each agency in the following year. The funding will be issued as part of Congress’s annual budget. The reason a general inflation index, such as the CPI, is not recommended to index the

agency budget is because the spending of each agency is very specialized. For example, Social Security beneficiaries use benefits to buy a wide variety of goods ranging from food products to technology, but research institutions use funding to buy a narrow selection of goods specifically tailored to implementing research methods. Thus, a specific price index for each agency will best capture the true purchasing power of funding.

Price indexes for certain agencies already exist, and can be used to show how the level of funding would change from year to year. For example, the NIH uses a price index called the Biomedical Research and Development Price Index (BRDPI).

The figure below uses data from the Office of Budget of the NIH to show the hypothetical level of funding if one indexed it to BRDPI or the GDP price index (a general price index), as well as the actual level of funding that was enacted.

C. Analysis of indexing federal science funding to inflation

Indexing science funding to inflation will help reduce the volatility that is present in the current system.

This volatility is detrimental to science because it prevents research institutions from establishing long term commitments, it disincentivizes high potential research from being funded, and it engenders unnecessary stress on PIs, which detracts from their ability to produce research. Furthermore, stabilizing the funding for science could allow graduate students to better understand the job market, which can help to allocate resources and human capital to disciplines with the greatest demand. Finally, it would also help discourage research in-

stitutions from turning to private funding when faced with a lack of federal funding by creating a more predictable funding mechanism.

Opponents of this proposal might object on the grounds that indexing to inflation will cause science funding to increase automatically over the years. There are three aspects to the response to this objection. First, while the absolute level of funding will indeed rise, the overall economy will be growing as well, so the share of GDP and the federal budget dedicated to science funding will be more moderate than the absolute level of funding. Second, when Congress decides on a budget for a scientific research agency, they should be deciding on the amount of research they want to fund. The cost to produce this research rises with inflation in subsequent years, so the budget must rise accordingly.

If Congress decides that they want to fund more or less research, they can raise or lower the budget, but if there is no such political will, then the purchasing power of each agency should remain the same. Third, it is generally believed among economists, such as Paul Romer, that scientific research boosts innovation and grows the economy, so increased funding for scientific research may help boost the economy in the future, which will help it pay for itself.

Another critique that this proposal might have is that the narrow price indexes created for each agency can be subject to unappealing trends such as accelerating salaries of PIs. For example, raising PI salaries will increase the price index, which will then cause more funding to be allocated to the agencies, which will then allow for further increased salaries. While this trend can be deleterious, the overall price

index is quite large and captures many trends that cannot be subject to this sort of manipulation. We recommend dedicating teams to search for causes of the rise in price indexes and a careful monitoring of the costs of producing research, and if there are such discrepancies, they can be addressed with specific legislation. However, much of this work is already done by the agencies, and historically it has been successful at limiting the growth of the price index, so price manipulation should not be a limiting concern when implementing a price index.

III. Policy #2: Modified lottery for research grant funding A. Existing Policy and Inadequacies

A vast majority of scientific research is funded through individual grants in a competitive process within each agency such as the NIH or NSF. Currently, the NIH evaluates research ideas in order to determine whether they should give grant money to the institution/PI to perform research. They score the ideas by giving an “overall impact score to reflect their assessment of the likelihood for the project to exert a sustained, powerful influence on the research field(s) involved, in consideration of the following review criteria,” which are significance, investigator, innovation, approach, and environment. Additionally, the “NIH looks for grant proposals of high scientific caliber,” and cannot “pay for research that has already been done.” The NIH additionally prefers projects that can be completed in 2 years and no more than 4 years. These all show an obvious preference for new, exciting results, which ignores the fundamental na-

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ture of science: a slow, gritty process that must be replicated to reach some semblance of truth. In addition, the NIH spends a lot of time and resources on peer review of grant applications. For example, the annual budget of the NIH Center for Scientific Review (CSR) is $110 million, which pays for more than 24,000 scientists reviewing around 75,000 applications and attending around 2,500 panel meetings. By prioritizing certain goals for grant proposals and trying to discriminate between ‘good’ and ‘better’ proposals, the agencies reveal that they are trying to predict the productivity of certain proposals--a tricky endeavor that often leads to arbitrary decisions. Furthermore, this creates perverse incentives for the grant writers, who have to spend more and more time predicting the whims of their application reviewers instead of doing meaningful research.

On the researcher’s side, the first step towards obtaining funding is for a principal investigator to write grant proposals. PIs must be careful to write strong applications that they believe will maximize their chances of receiving funding, since the acceptance rate for grant applications is only 19%. This means that they try to shape their application in a way that would look appealing to the NIH. Consequently, PIs aim to orient their research under strict guidelines with measurable success in a way that follows the criteria that it will be judged on. However, because there are humans on both sides of this process, there is plenty of room for biases to creep in. Furthermore, with the low acceptance rate, the hesitation of any reviewer can result in an application being rejected. This creates a perverse incentive to orient an application in a

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way that will match the reviewers’ biases, at the expense of science.

These sacrifices and perverse incentives might be warranted if the current system was more productive than other competing mechanisms in allocating resources to proposals that produce the best scientific research and progress knowledge of the world. However, evidence shows that the current system is worse than random chance in being able to predict productivity of funded grants. More specifically, the current system does a reasonable job in separating good applications from those that are lacking in some major ways, but is incapable of discriminating between applications once they reach a certain percentile. This fact is revealed in a study of 400 NIH grant renewals that scored in the top 20 percentiles during the review process, and it finds no correlation between eventual productivity of research (measured by citations of papers) and percentile score of the grant during the review process.

Furthermore, an analysis on grant proposal data from the top 20 percentiles shows that an application in the top half of the group (measured by publications and citations) has only a 58% chance of being funded if judged by percentile score. This measure of success is only marginally better than random chance, and most of those gains are concentrated in the top 3 percentiles. If those percentiles are removed from consideration, then there is no case to be made for the current grant review process. Furthermore, while the current system and random chance may be equivalent in predicting capability, there is a distinct difference in the resources required and incentive structure between the two methods, as described earlier.

This failure in federal agencies to discriminate between the top fifth of grant proposals would not be an issue if there was enough funding to allow for nearly every decent proposal to receive funding. However, the lowest percentiles that the NIH funds “seldom exceed the 20th percentile and have hovered around the 10th percentile for some institutes in recent years,” which shows that these percentiles have consequential impact. A reviewer’s seemingly arbitrary and unenlightened decision to choose one application over another (among the top fifth 12 of applications) means that not only is promising research going unfunded, but also it encourages trying to game the system in order to get funded. Needless to say, the findings associated with the NIH are as easily apparent in other science funding agencies as well, such as in the NSF. B. Design of the modified lottery system

As shown above, the current system of allocating grants, especially once the proposal is in the top twentieth percentile, is inefficient and promotes perverse incentives for grantwriters. One method of improving the mechanism of allocating grants is the modified lottery system. This system uses existing peer review infrastructure to identify the promising scientific endeavors, let us call it ‘good science,’ from the mass of grant proposals but uses a lottery system to choose who receives grant funding from within the top group. The group of good science must necessarily be bigger than the payline--the percentage of total grants that can be funded--for this system to be effective; this proposal recommends for the good science category to be 2-3 times bigger than the payline. For example, if the

payline is 10%, then the peer review system must narrow the grant proposals to the top 20-30% before the random lottery selects which grants get funded. This allows for the peer reviewers to remove grants that are obviously flawed without having to navigate through the painstaking, frustrating, biased, and expensive task of choosing the best from the good.

The design of the proposed mechanism is as follows: the grants are all submitted and the peer re-

specific needs and issues, but the genuinely believe is good science, general mechanism should stay in- as opposed to trying to predict the biases of the reviewers and gamtact. ing the system. This is one of the C. Analysis of the modified biggest advantages of this system lottery system This system would be advanta- because it puts an end to the distorgeous in many different ways. First, tions in science, and helps prevent it would bring about tremendous racial, gender, and other forms of cost savings because peer reviewers discrimination. Finally, the modified can remotely assess grant proposals lottery system has many theoretical and will not have to meet in person and philosophical origins, has been to discuss the rankings of the best simulated through computer simulaproposals. Currently, the budget tions to ascertain efficiency, and has been implemented in institutions as

Critics of this system may hesitate to embrace randomness to fund science, and while this hesitation is understandable, one can see that the current system is not much better than random chance but does not have the benefits of an unbiased process. view process is used to separate good science from the rest of the applications. The applications not chosen are critiqued and sent back to grant writers for them to improve and resubmit in later rounds. The good science is then subjected to a lottery system that selects a 13 fraction of those proposals to be funded.

The unfunded good science is automatically re-submitted to the lottery to have a chance in the next round.

A figure that outlines this mechanism is shown below. This general mechanism should be implemented in each science funding agency; it is understandable for each agency to tailor the mechanism to meet their

of the NIH CSR is $110 million, which could go towards funding many more grants. Second, grant writers themselves invest much time and energy in writing grants that they believe will succeed in receiving funding instead of actually performing scientific research. Since unfunded meritorious proposals will automatically be resubmitted into the lottery, only flawed science will be subject to reconsideration and rewriting. This leads to the third advantage: this system works to eliminate biases of the reviewers in selecting which proposals get funded.

Furthermore, this also allows grant writers to write proposals that they

prominent as the Health Research Council of New Zealand. In other words, this proposal is not a fringe idea but rather one with theoretical and empirical underpinnings.

Critics of this system may hesitate to embrace randomness to fund science, and while this hesitation is understandable, one can see that the current system is not much better than random chance but does not have the benefits of an unbiased process. Other arguments claim that under this system, bad luck can stop good science from being actualized. While this claim is unfortunately true, one must realize that when there are more good propos-

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als than funding available, there will always be good science that goes unfunded. Furthermore, while in the proposed system bad luck can prevent good science from being funded, the current system does not have any systematic reason for failing to fund science--they instead use semi-arbitrary rankings to decide funding. Finally, there are methods of alleviating some of the burdens that are associated with random chance. One aspect of the proposed system that would address this is the immediate resubmission of unfunded meritorious applications to the lottery. Another method would be to set aside a small amount of funding to fund proposals in certain areas that, by some unlikely mystery of chance, never receive funding. In total, the proposed modified lottery system is a general improvement of the current system that permeates federal science funding agencies; however, each agency can and should adopt a version of this form that they believe is fair and that best suits their needs.

IV. Policy #3: Blue Skies Research A. Existing Policies and Inadequacies

In section III, the inefficiencies of the current process of discriminating between ‘good’ and ‘better’ science were introduced. These inefficiencies not only waste resources but also foster poor incentives that discourage proper scientific thought. However, even after addressing these inefficiencies by using a lottery to create a fairer and more transparent system, there still remain issues with the way scientific research is funded. One of the primary issues is that scientific research is funded on a proposal by propos-

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al basis. The history of science is one of serendipitous discoveries by researchers who were looking for something else altogether. Despite this, federal funding agencies “target research funding to perceived

can prevent the serendipity that is science from happening. This type of behavior is not useful for scientific progress. Government funding mechanisms that provide resources to tenured faculty at non-profit uni-

In modernity if scientists discover something that could potentially affect their prospects of publishing on their intended hypothesis, they are incentivized to ignore the results or quickly change to a project that is easier to publish. priority areas, while support for undirected investigator-initiated projects has declined sharply,” which goes against the nature of scientific progress. By outlining certain guidelines that grant proposals must match, science funding agencies are restricting the types of projects they fund in an attempt to predict what will produce novel discoveries. Researchers are quick to respond to such incentives. For example, Gary Bennett, a neuroscientist, claims that funding “‘affects what we study, what we publish, the risks we (frequently don’t) take, [and] nudges us to emphasize safe, predictable (read: fundable) science,’” which

versities are supposed to provide the financial and job security necessary to take risks and produce unconventional ideas and discoveries. While it is true that novel research does not always lead to enlightening discoveries, they occasionally lead to highly cited and high impact studies, which is characteristic of the variability of high risk, high return projects. This high risk research is what promotes scientific discovery, and having an incentive that encourages scientists to shy away from it is detrimental to science overall.

A more theoretical argument that outlines why the current system does not effectively capture value is

provided by Nassim Taleb, a statistician and philosopher, in his book Antifragile. Taleb recommends that governments should fund “non-teleological tinkering” instead of traditional research because this allows researchers to move freely and continue producing insights when innovations begin to drift, instead of being locked into a bureaucratic mold when projects shift direction. Furthermore, Taleb uses a mathematical argument to reason why governments should focus on funding as many qualified grants as possible, rather than trying to fund only the ones that they predict will be successful. This argument is called the “1/N” style, and the logic is as follows: when there are unlimited upsides and relatively low-cost downsides, one should focus on getting a little money in as many projects as possible, so that the small investment can increase exponentially if a handful of these ventures turn out to be successful. In other words, divide total funding by the number of qualified grants and disburse this level of funding to each applicant.

While crude in its method, this argument is powerful in that it reveals that resources are better allocated in funding quantity over predicted quality.

Another poor incentive that the current system creates is the need to produce positive results on the topic that the original hypothesis was about. Not only does this encourage deleterious exercises such as “p-hacking” (producing statistically significant results in an artificial manner), but this ignores how numerous scientific discoveries have been made in the past. Many scientists do not set out to find what they ultimately discovered. For example, Alexander Fleming discovered pen-

icillin by accident while researching something completely different: the influenza virus. In modernity if scientists discover something that could potentially affect their prospects of publishing on their intended hypothesis, they are incentivized to ignore the results or quickly change to a project that is easier to publish. Thus, grants should be more concerned with how good the study design and methods were, rather than whether the result was significant or surprising. Currently, there exist grants such as the NIH Director’s Pioneer Award that allocate $700,000 per year to 7 distinguished PIs to pursue undirected research for up to five years. While these are a step in the right direction, they pale in comparison to the total budget of funding agencies.

B. Design of Blue skies research

Blue skies research is a name for research done without a clear goal. Much of research throughout history has been conducted based primarily on the intellectual curiosities of men and women rather than for direct applications to the real world. While now scientific research has been institutionalized so that funding levels are much greater than they were in the past (a force for good), there has been a lack of undirected research. This proposal encourages scientific research agencies to allocate a portion of their funding to investigator led projects by funding individual labs or researchers for an extended period of time, instead of evaluating funding on the merits of individual grant proposals.

PIs should have to submit a short application--much shorter than current proposal applications--outlining the direction of

research that they wish to pursue.

Then, funding agencies should determine winners of the award through systematic, unbiased measures such as the modified lottery system detailed in Section II. Furthermore, the goal should not be to fund promising ideas or research directions (in the eyes of the reviewers), but instead to fund as many qualified PIs as possible. By giving opportunities to a variety of projects without regard to the content of the research, funding agencies can exploit the asymmetric nature of the payoffs of research: limited monetary losses and unlimited potential gains indicate that one should disburse funding as widely as possible.

Each agency has the discretion of discovering the exact method to implement this funding mechanism.

Because of the tremendous variation in the nature of each agency, a unilateral piece of legislation would not be an appropriate or effective way to bring about this change. For example, some agencies, such as the NIH, already have a program similar to this, albeit at a miniscule scale.

However, the proposal recommends that each agency set a baseline level of funding that they will commit to allocating towards this mechanism that is both achievable but significant. For example, the NIH currently allocates around 0.01% of its budget to the NIH Director’s Pioneer Award. This proposal would recommend that the NIH commit to increasing funding for this project by a factor of at least seven and possibly reducing the size of the awards so that more grants can be disbursed, with the goal of being able to be fund a majority of qualified applicants. While predicting the future levels of qualified applications is difficult and it may or may not be

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possible, commitments to increase funding, by capturing new funding or by replacing traditional grantbased funding, would allow funding agencies to unlock the high impact of innovative research.

C. Analysis of Blue Skies

fund a majority of the qualified PIs, so while there may be some inevitable favoritism, it should be small in comparison to the total grants funded. Furthermore, exaggerated claims are only an issue if the possibility of results are motivating grants applications to be funded, but this proposal recommends that applications be funded on qualifications of the PI and methodology. This proposal is not just a theoretical idea to improve science; blue sky research ideas have been accepted, successfully implemented, and shown to be highly effective in a number of institutions from Howard Hughes Medical Institute in the United States to the Australian Research Council.

In total, this method of funding 18 mechanisms has potential for bettering science and allowing PIs the creative freedom to produce innovations like those heralded in the 19th allow for science funding agencies to and 20th centuries. improve the funding mechanism for science, obtain better results, and V. Conclusion still maintain the general institution In conclusion, indexing science that is currently in place, thus pre- funding to inflation, implementing venting outsized costs of refitting a modified lottery system to deterthe old system to accommodate the mine how to select grant recipients, new one. and allocating an increased portion Critics argue that this system of funding for blue skies research will take resources away from di- will greatly improve the ability of rected initiatives and allocate them scientific research to produce innotowards research that has a high vation and discovery, and in turn, likelihood of failing to produce improve society. Indexing science meaningful results. The response to funding to inflation will be implethis criticism is twofold: the propos- mented by allowing each agency al allows each agency flexibility to to develop or borrow a price index determine how much to prioritize that tracks the purchasing power of the directed initiatives; high risk ne- grant money. This price index will cessitates high failure but also holds likely reflect the nationwide inflation the option for large successes. Some rate, but will also incorporate the other criticisms say that this propos- fluctuating cost of the narrow selecal is vulnerable to favoritism as well tion of goods and services needed as exaggerated claims. However, this to produce research. This measure proposal recommends scaling up will be funded through appropriathese blue sky initiatives so that they tions by Congress, and the budget and energy focusing on doing research. It reduces the application burden in two ways: having few requirements for details for the application and extending timelines to cover longer periods between applications. In total, this proposal would

The blue skies research program will help allow federal funding agencies to harness the innovative nature of high risk, high impact science.

Research

Movement towards a system that funds people not projects would be an important and significant improvement to the current scientific funding mechanism. One reason is that it would allow the current funding mechanism to resemble the true nature of science: a messy, unpredictable, serendipitous process. The current system with preliminary data, tight constraints, short timelines, and conditional acceptance does not encourage the search for truth but rather encourages manipulation, causes frustration, and wastes resources. Increasing funding for labs that have general research agendas but no clear idea on what the results may reveal helps bring back the trial and error nature of science. Another reason this process should be encouraged is because it reduces the application burden on PIs, so they can spend more time

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of each agency can be subject to change depending on political will.

However, absent of political desire to alter funding, funding will maintain its purchasing power, which will decrease its volatility. By decreasing this volatility, institutions and PIs can make long term commitments, which will help foster more innovative and risky measures that could produce lasting impact. This measure is a relatively 18 Crossley, Merlin. “Science Funding Should Go to People, Not Projects.� The Conversation, The Conversation US, 29 June 2015, theconversation. com/science-funding-should-goto-people-not-projects-44001. 22 minor tweak to current policy, with limited costs and disproportionate benefits to the scientific community and their ability to continue to innovate. A modified lottery system will dramatically alter the way grants are disbursed in the current system.

It will maintain the current peer re-

view system up to a point, but then shift to using a random lottery to allocate funding to grant proposals.

The peer review process will be used to discriminate between flawed proposals and promising research, but the lottery will choose which proposals from the promising research category receive funding. This program will eliminate many of the perverse incentives that PIs, institutions, and grant reviewers have in the current system. It will also reduce racial and gender discrimination, while making the process overall more transparent, fair, and cost-effective. Furthermore, the lottery system does not require a dramatic change in the structure of current funding mechanism, but rather a mere truncation of the procedure.

This system has been successfully implemented in New Zealand and promises to improve scientific research by eliminating the distortions caused by the poor predictive ability

of current grant-reviewers. Finally, the blue skies research program will help allow federal funding agencies to harness the innovative nature of high risk, high impact science. It will do so by increasing the funding given to individual PIs or labs, while simultaneously allowing maximum freedom in research directions and choices. Thus, the program removes funding agencies from the business of predicting scientific output and instead places the investment in the innovative ability of researchers.

Additionally, the costs of the program are limited, but the benefits may be dramatic; consequently, this program mimics the functioning of a pilot program. Implemented together, indexed funding, the modified lottery system, and blue skies research can dramatically improve 23 scientific research in the United States, helping society flourish through the use of enlightened and robust investments in science.

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BISF 2019 Competition Winner

Addressing Opioid Withdrawal and Treatment for Incarcerated and Formerly-Incarcerated Individuals in West Virginia ELIZA MARTIN & TERESA SMITH Rice University 2019 Abstract

In 2017, the United States Department of Health and Human Services declared the opioid epidemic a public health emergency.

There are nearly 100 deaths daily from opioids and some experts have estimated that this figure may swell to 250 deaths a day.1 Projections indicate that the opioid crisis is just beginning. However, the opioid crisis is not a monolith as some states are suffering from the crisis at greater rates than others. West Virginia has the highest opioid-drug overdose rate in the nation and one of the highest incarceration rates for opioid-dependent individuals. For those prisoners who are opioid-dependent, there is currently no policy in place to address opioid-withdrawal in West Virginia prison. Moreover, prisoners recently released from prison face the significant

Max Blau, “STAT forecast: Opioids could kill nearly 500,000 Americans in the next decade,” https:// www.statnews.com/2017/06/27/opioid-deaths-forecast/ (accessed January 28, 2019).

1

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likelihood that they will overdose in their first two weeks following prison release. The prevention of recidivism and reincarceration requires that individuals released from prison have access to medication-assisted treatment. However, access to opioid-dependency treatment is difficult in a state where the majority of individuals live in rural areas and there is a state moratorium on the creation of new medication-assisted therapy treatment clinics that administer methadone, a medication considered the “gold standard” of treatment. As such, we argue that West Virginia should implement medication-assisted therapy (MAT) and expand prescription abilities of physicians to prescribe MAT in order to address opioid-dependency in prison and decrease the rate of opioid-overdoses for individuals recently released from prison.

Introduction

In 2017, of the approximately 70,237 Americans who died from drug overdoses, 47,600 involved opioids.2 That’s approximately one-hundred and fifteen deaths every day. This figure represents not only an increase in overall deaths from drug overdoses from 2016, but also in the percentage of drug overdose deaths that involved an opioid, rising from 66.4% to 67.8%.

Even more alarming is that despite an increase in public awareness and policy responses to the public health opioid crisis, the age-adjusted rate of drug overdose deaths in 2017 was 9.6% higher than the rate in 2016.3 The death toll from drug overdoses is greater than those who have died from guns, car crashes, or HIV/ AIDS in a single year in the United States. An analysis from the New York Times demonstrated that drug overdose deaths have killed more Americans than the entire Vietnam and Iraq wars.4 A conglomeration of factors has led to the current crisis: economic and social upheaval for which opioids offer escape, a healthcare system that prioritizes minimizing pain, physicians who were instructed that pain medication was not addictive, extensive marketing of oxycodone for the treatment of non-malignant pain, and powerful

lobbying of government officials by pharmaceutical companies and advocacy organizations.5 Nonetheless, the opioid crisis is not a monolith.

Patterns of opioid consumption and distribution vary across states, socio-economic status, and gender identity. However, the policy response by the federal government as well as many state governments, appears to have largely focused on the opioid crisis in rural America, which predominantly affects non-Hispanic white Americans without a college

It is important to note that the opioid addiction crisis has also spread to urban areas, such as Washington D.C., that have dramatically affected minority communities.9 As opioid overdoses continue to increase, it is clear that policymakers are struggling to address one of the most important public health challenges that continues to constantly evolve.

Treatment with medication is the most effective option for individuals addicted to opioids. Medication-assisted treatment (MAT), or

The death toll from drug overdoses is greater than those who have died from guns, car crashes, or HIV/AIDS in a single year in the United States. degree.67 Unlike the heroin crisis of the 1970s that mainly affected urban minority populations, the current opioid overdose rates are highest in suburban and rural communities, especially in Appalachia, the Southwest, and New England.8

the use of the anti-craving medications, methadone, buprenorphine, or naltrexone, paired with behavioral counseling, decreased opioid use, overdose deaths, criminal activity, and infectious disease transmission.10 Of the three FDA approved

“Products - Data Briefs - Number 329 - November 2018,” https://www.cdc.gov/nchs/products/databriefs/ db329.html (accessed January 20, 2019).

3 Ibid.

4 German Lopez, “In 2016, Drug Overdoses Likely Killed More Americans than the Entire Wars in Vietnam and Iraq,” Vox, https:// www.vox.com/policy-and-politics/2017/7/7/15925488/opioid-epidemic-deaths-2016 (accessed January 10, 2019).

5 “Opioid Overdose Crisis,” National Institute on Drug Abuse, January 22, 2019, https://www.drugabuse.gov/drugsabuse/opioids/opioid-overdose-crisis (accessed December 28, 2019).

6 Brendan Saloner, Emma E. McGinty, Leo Beletsky, Ricky Bluthenthal, Chris Beyrer, Michael Botticelli, and Susan G. Sherman, 2018, “A Public Health Strategy for the Opioid Crisis,” Public Health Reports, https://doi.org/ 7 .1177/0033354918793627 (accessed 28 December, 2019).

8 Ibid.

9 Marisa Peñaloza, “The Opioid Crisis Is Surging In Black, Urban Communities,” NPR, March 8, 2018, https:// www.npr. org/2018/03/08/579193399/the-opioid-crisis-frightening-jump-to-black-urban-areas (accessed January 31, 2019).

10 “Effective Treatments for Opioid Addiction,” National Institute on Drug Abuse, November 2016, https:// www.drugabuse.gov/publica2

35

drugs, methadone and buprenorphine reduce opioid cravings and the effects of withdrawal by binding to the opioid receptor and alleviating the dependence. Naltrexone works differently in that it is not an opioid itself but blocks the receptor to block physical withdrawal symptoms yet requires the patient to be clean for approximately 10 days. It is more accepted in the criminal justice system because methadone and buprenorphine are thought as “replacement drugs” for the patient’s addiction even though naltrexone less well researched. However, none of these medications are widely used. In the United States, less than 33 percent of those enrolled in privately-funded substance use disorder treatment programs, receive medication-assisted treatment.11 Adding another layer of complexity to this policy issue is the criminal justice system. Individuals addicted to opioids are more likely to be involved with the criminal justice system. Many with substance-use disorder are convicted of nonviolent drug possession or distribution. For individuals with opioid dependency, they are 13 times more likely to be involved with the criminal justice system. Nearly 40 percent of heroin users are estimated

to have had criminal justice involvement.12 Lack of addiction treatment services in prisons across the United States has led to an increase in overdoses and reincarceration rates.

When an opioid-dependent individual is sentenced to prison, they experience withdrawal with no direct treatment, and their body’s tolerance to opioid reduces. Upon release, former inmates are 40 times more likely than the average citizen to die of opioid overdose in the two weeks immediately following their release.13 There is a critical need for state prisons, which house over 1.3 million individuals in the United States, to address opioid dependency and the incredible rate at which former inmates who were opioid-dependents, die upon release.

While the opioid crisis is a national health emergency, opioid dependency and overdoses vary drastically by state. West Virginia has the highest drug overdose death rate in the nation as over 700 individuals died from an opioid overdose in 2016.14 With over 433 pain pills per person entering West Virginia over the course of the year, it’s no surprise that in 2016, official estimates signaled that over 61,000 West Virginians used prescription pain med-

ications for non-medical purposes.15 That same year, over 42,000 individuals sought treatment for illegal drug use but failed to receive it.15 West Virginia is one of the states with the highest rate of poverty, rural-populations, and a dramatically growing rate of imprisonment, makes policy creation and implementation difficult.16 However, the characteristics and demographics of the state also provide the opportunity for policymakers and politicians to address the opioid crisis in one of the states most affected by the public health emergency. Furthermore, the successful implementation of policies to address opioid dependency and prevent overdoses upon release from prison in West Virginia, would serve as an implementable model across the country.

Statement of Current Policy

In September 2018, the Department of Health and Human Services announced the award of nearly $1 billion in opioid-specific grants to combat the opioid crisis.17 However, the current policy in inadequate in its lack of detail or direct policy changes to address expanding access to treatment. West Virginia

tions/effective-treatments-opioid-addiction/effective-treatments-opioid-addiction (accessed January 31, 2019).

11 “Treating Opioid Addiction in Criminal Justice Settings,” National Institute on Drug Abuse, December 2017, https://www.drugabuse. gov/publications/treating-opioid-addiction-in-criminal-justice-settings/treating-opioidaddiction-in-criminal-justice-settings, (accessed January 31, 2019).

12 Rhitu Chutterjee. “With More Opioid Use, People Are More Likely To Get Caught Up In The Justice System.” NPR, July 6, 2018. https://www.npr.org/sections/health-shots/2018/07/06/626176621/with-more-opioid-use-peopleare-more-likely-to-get-caught-upin-the-justice-syst (accessed January 22, 2019).

13 Scott Proescholdbell and Daniel Edwards, “Former Inmates at High Risk for Opioid Overdose Following Prison Release • UNC Gillings School of Global Public Health,” UNC Gillings School of Global Public Health, July 19th, 2018, https://sph.unc. edu/sph-news/former-inmates-at-high-risk-for-opioid-overdose-following-prison-release/ (accessed January 31, 2019).

14 “Prescription Drug Abuse Epidemic Fact Sheet,” Office of Joe Manchin, West Virginia Senator, https:// www.manchin.senate.gov/ imo/media/doc/Prescription%20Drug%20Abuse%20Fact%20Sheet.pdf ?cb (accessed January 31, 2019).

15 Ibid.

16 “West Virginia Profile,” Prison Policy Initiative, https://www.prisonpolicy.org/profiles/WV.html (accessed January 30, 2019).

17 “HHS Awards Over $1 Billion to Combat the Opioid Crisis,” U.S. Department of Health and Human Services, September 19th, 2018, https://www.hhs.gov/about/news/2018/09/19/hhs-awards-over-1-billion-combat-opioid-crisis.html (accessed January 30th, 2019).

36

is the state with the highest rate of opioid overdose deaths in the country. While West Virginia has worked to extend the availability of medication-assisted treatment by expanding Medicare to cover medication in addiction treatment programs, there are still significant policy gaps that must be addressed in order for the West Virginia opioid crisis to be mitigated.

West Virginia has policy barriers in place that prevent access to medication-assisted treatment.

West Virginia has enforced a moratorium on the creation of new methadone clinics. This is, in part, due to the cost of methadone treatment: treatment costs approximately $126 per week. Injectable and implantable buprenorphine is even more expensive, running at a cost of approximately $1,000 per treatment.18 Moreover, many physicians, whom are required to administer buprenorphine, are not willing to incur the high costs because of an uncertain waiting period for reimbursement. Additionally, there are concerns of drug diversion by certain organizations. Negative attitudes and misinformation surrounding MAT persist.

Access to medication-assisted therapy is critical in the treatment of opioid addiction. Methadone is considered the “gold standard” of treatment for opioid addiction. Currently, individuals in West Virginia

that are undergoing medication-assisted treatment, must receive their methadone dosages at a methadone clinic. Despite the obvious need to address the opioid crisis in West Virginia, only nine methadone clinics currently serve the entire state of West Virginia.19 The absence of addiction treatment services in West Virginia has led to an increase in not only reincarceration rates (and therefore an overall expanding prison population), but also an increase in overdose deaths.20 As former inmates are nearly forty times more likely than the average citizen to die of an opioid overdose in the two weeks immediately following their release, this represents a significant group of individuals at high risk for death.

With a state prison population of approximately 13,000, 58 percent of individuals in West Virginia prisons meet the criteria for substance abuse disorder, and approximately 25 percent abuse opioids.21 There is no current policy in place to address opioid treatment in West Virginia prisons nor the increased rate of death following prison release. State prisons do not dispense methadone or buprenorphine, which causes inmates to go through withdrawal with only symptom management as medical attention.

Moreover, individuals entering prison who were managing their treatment prior to their conviction with

methadone or buprenorphine, also experience withdrawal symptoms from the medication as they are not allowed access to methadone treatment in prison. Such an experience discourages individuals from seeking medication assisted therapy in the future.22 There are no current policies in place to address opioid withdrawal in West Virginia prisons.

While West Virginia does not currently have policies in place to address opioiddependency in prisons, the state has recently begun to address the phenomenon of opioidoverdoses for those prisoners immediately released who face increased rate of death. A few days prior to the release of a prisoner, state prisons have begun to administer naltrexone, a medication more commonly known as Vivitrol, to treat opioid addiction. Unlike methadone or buprenorphine, which prevents opioid cravings, Vivitrol acts as a drug that blocks the opioid receptors. Vivitrol requires that the patient be clean for ten days prior to injection. While the administration of Vivitrol presents a significant step in West Virginia’s recognition of the policy issue and the importance of medication-assisted therapy for prisoners, there are significant problems with naltrexone. Vivitrol is more costly than methadone and buprenorphine, and due to its recent development, there is scant data available regarding the effectiveness

Marina Shayevich, “‘Fear, Paranoia, and Pressure’: Challenges to Accessing Medication-Assisted Treatment for Opioid Addiction,” World of Psychology, September 19, 2018, https://psychcentral.com/blog/fear-paranoia-andpressure-challenges-to-accessing-medication-assisted-treatment-for-opioid-addiction/ (accessed January 30, 2019).

19 Linda Keslar, “The Methadone Blind Spot.” Proto Magazine, April 26, 2018, http://protomag.com/articles/ methadone-blind-spot (accessed 22 January, 2019).

20 Alison Shames and Ram Subramanian,“A Path to Recovery: Treating Opioid Use in West Virginia’s Criminal Justice System,” Vera Institute of Justice, October 2017, https://www.vera.org/publications/a-path-to-recovery-treating-opioid-use-west-virginia-criminal-justice-system (accessed 22, 2019).

21 “West Virginia Profile,” Prison Policy Initiative.

22 Mitchell, Shannon Gwin, Sharon M. Kelly, Barry S. Brown, Heather Schacht Reisinger, James A. Peterson, Adrienne Ruhf, Michael H. Agar, and Robert P, Schwartz, “Incarceration and Opioid Withdrawal: The Experiences of Methadone Patients and out-of-Treatment Heroin Users,” Journal of Psychoactive Drugs 41, 2 (2009): 145–52.

18

37

of the medication. The manufacturer of Vivitrol provides prisons with the first monthly injection of the medication free of charge. However, following the first injection, the inmate must either find a community program that is dispensing the medication or pay the $1,000 injection charge thereafter. However, the cost, limited access, and uncertainty of Vivitrol indicates that the current policy is insufficient.

Policy Proposal

The implementation of the following possible solutions in West Virginia prisons would play a critical role in mitigating opioid withdrawal in prisons and decreasing overdoses for individuals recently released from prisons.

Policy I: Implementation of Medication-Assisted Therapy in All Prisons and Expansion of Methadone Prescription Abilities to Physicians The West Virginia legislature should institute a law mandating medication-assisted therapy treatment to be made available in all state prisons. The current prison policy of symptom management to address opioid withdrawal has been declared “cruel and unusual punishment” by a judge in Massachusetts and many advocate that such a policy encourages the unfair treatment of prisoners.23 Not only is the implementation of MAT in West Virginia

prisons ethical and just treatment of prisoners, but is also critical in order for the success of incarcerated individuals upon their release.

Moreover, the Controlled Substances Act must be amended to allow primary care physicians to prescribe methadone in order to allow for those enrolled in MAT to continue.

The implementation of medication-therapy has been successfully implemented in Rhode Island. In 2016, Rhode Island Department of Corrections began expanding MAT access to all state prisons. The policy included access to the only three Federal Drug Administration approved addiction treatments, methadone, buprenorphine, and naltrexone. In Rhode Island, all incoming prisoners were screened for opioid dependency, and all those who were eligible, were offered treatment.

Upon release from prison, all participants were then referred to community addiction programs. The program has been incredibly successful in Rhode Island as the state noted a 12 percent decrease in overall overdose deaths and a 61 percent decrease in post-incarceration overdose deaths.24 While the implementation of MAT in West Virginia prisons is imperative to prevent opioid-withdrawal, the prevention of recidivism and reincarceration requires that individuals released from prison have access to medication-assisted treatment. Methadone in particular, is dispensed in liquid daily doses and

patients must be supervised while taking it. Urine tests are periodically required as they can distinguish methadone from substances of abuse. Patients must report daily to a clinic in order to receive methadone. Due to a state moratorium on the creation of new methadone clinics, nine existing clinics administer MAT in West Virginia. The structured nature of MAT clinics address the needs of some patients well. However, the need to obtain medication daily at a fixed site is an incredible burden as 51 percent of the population lives in a rural area without access to the urban MAT clinics.25 For these rural West Virginians, access to methadone on a daily basis imposes an incredible time and financial commitment due to distance.

Even if the moratorium on the creation of new MAT clinics was to be repealed and new clinics were created, it would be impractical for enough clinics established to meet demonstrated need. Instead, Congress should amend the Controlled Substances Act to allow primary care physicians who have undergone required training, to prescribe and dispense methadone and buprenorphine, while simultaneously counseling patients. General practitioners in the state, approximately 1,747, would therefore be able to prescribe methadone and buprenorphine for treatment, and patients could receive their daily doses at their local pharmacy.26

Kate Taylor, “Jail Ordered to Give Inmate Methadone for Opioid Addiction in Far-Reaching Ruling,” The New York Times, November 29, 2018, https://www.nytimes.com/2018/11/28/us/inmate-methadone-opioid-addictionruling.html.

24 Erick Trickey, “How the Smallest State Is Defeating America’s Biggest Addiction Crisis.” POLITICO Magazine, August 25, 2018, https://politi.co/2wbuwha (accessed January 31, 2019).

25 Jeffrey H. Samet, Michael Botticelli, and Monica Bharel, “Methadone in Primary Care — One Small Step for Congress, One Giant Leap for Addiction Treatment,” New England Journal of Medicine 379, 1 (July 5, 2018): 7–8. https://doi.org/10.1056/NEJMp1803982.

26 “West Virginia Physician Workforce Profile” in 2013 State Physician Workforce Data Book, AAMC Center for Workforce Studies 23

38

Instead of entering prisons, nonviolent opioiddependent drug offenders should enter communitybased treatment centers.

In the United States, there is only one study regarding the administration of methadone in a primary care setting as extensive efforts had to be made in order to meet all existing regulations. Physicians in the study, conducted over a ten-year period in Boston, administered medication prescriptions and care without any adverse incident.27 Internationally, the model has been successful. Australia, Great Britain, and Scotland have found that primary-care-based methadone programs are successful: whereas 15 percent of opioid users utilize MAT programs in the United States, in Scotland, approximately 60-80 percent of individuals with opioid-dependency are enrolled.

Nonetheless, there exists significant stigma in the criminal justice system MAT programs as some believe that one simply replaces their addiction with another. Although methadone and buprenorphine are opioids, their ability to restrain patients from cravings can prevent

overdose. A patient can also collaborate with their physician to taper their dosage over time.28 Moreover, were general practitioners in West Virginia able to prescribe methadone and buprenorphine for MAT, there would be an initial need to train physicians and pharmacists on opioid-dependency treatment and correct dosage. The risk of methadone or buprenorphine diversion is low should pharmacists and general practitioners receive thorough training and the implementation of proper supervision protocols, which would require that pharmacists inquire as to any medications taken over the previous twenty-four hours and prevent those who are intoxicated from being able to take a methadone dosage.29 Thorough training would require an initial monetary investment from the state. However, with the proper administration of the complete policy, West Virginia, like Rhode Island, would likely save significantly in the

longterm by lowering incarceration and recidivism rates, as well as the incidence of required emergency medical care following overdoses.30 In sum, the proposed policy provides immediate benefits for opioid-dependent incarcerated individuals while creating a more tenable framework for generations, as opioid-use disorder treatment would be expanded.

Policy II: Alternative Sentencing for Nonviolent Drug Possession Given the fact that the eradication of opioids is impossible and many individuals who are arrested for opioid possession or distribution and sentenced to harsh mandatory minimum sentences are opioid-dependent, West Virginia should offer nonviolent drug offenders community-based treatment as an alternative to probation or incarceration.

Instead of entering prisons, nonviolent opioid-dependent drug offenders should enter community-based treatment centers. Such a policy would expand upon the principles of West Virginia’s 2014 Justice Reinvestment Act, which sought to reduce incarceration rates and direct money towards evidence-based treatment and supervision programs.31 To date, the program has saved the state an estimated $287 million.32

(2013), https://www.aamc.org/download/152190/data/west_virginia.pdf.

27 Samet, Jeffrey H., Michael Botticelli, and Monica Bharel, “Methadone in Primary Care — One Small Step for Congress, One Giant Leap for Addiction Treatment,” New England Journal of Medicine.

28 “How to Get off Methadone,” American Addiction Centers, November 12, 2018, https:// americanaddictioncenters.org/withdrawal-timelines-treatments/methadone (accessed January 31, 2019).

29 Joseph Merrill, “Policy Progress for Physician Treatment of Opiate Addiction,” Journal of General Internal Medicine 17, 5 (2002): 361–68, https://doi.org/10.1046/j.1525-1497.2002.10628.x.

30 Erick Trickey, “How the Smallest State Is Defeating America’s Biggest Addiction Crisis,” POLITICO Magazine.

31 “West Virginia’s Justice Reinvestment: Strengthening Community Supervision, Increasing accountability, and Expanding Access to Substance Use Treatment,” Justice Center the Council of State Governments (June 2014).

32 Ibid.

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Drug offenders admitted into West Virginia prisons comprise approximately 25 percent of all new prison admissions.33 Of those individuals sentenced to prison, approximately half are classified as having a significant drug problem and a majority had no history of assault or violence.34 While a majority of drug offenders have a high overall risk of recidivism, they do not strong criminal histories and have no history of assault or violence. The average cost of incarcerating drug offenders in 2015 cost the state more than $22.4 million.35 By offering nonviolent drug offenders community-based treatment as an alternative to probation or incarceration, West Virginia will reduce its prison population while also offering individuals the treatment they need. California enacted a similar policy in 2000 and saw not only a significant reduction of its prison population, but also a 27.4 percent decline in the incarceration of drug offenders in the first five years of the program.35 However, the policy is not without its faults. Following the passage of California’s Substance Abuse and Crime Prevention Act of 2000, better known as Proposition 36, the

state saw an increase in recidivism rates for those who were offered and selected community-based treatment when compared to traditional drug courts.36 Moreover, some individuals maintain that community-based treatment as an alternative to probation or incarceration lowers the motivation for offenders to take treatment programs seriously.37

Recommendation

Both policy solutions are effective in addressing opioid withdrawal in West Virginia prisons and decreasing overdoses for individuals recently released from prisons. However, the implementation of medication-assisted therapy in all West Virginia prisons and the expansion of methadone prescription abilities to physicians should be implemented as it is the policy most effective and beneficial for all West Virginians.

While West Virginia should consider offering nonviolent drug offenders community-based treatment as an alternative to incarceration, we recognize that there are still questions remaining as to the long-term viability of the policy as diversion rates have not been shown to decrease significantly. Implementing MAT in all prisons and expanding meth-

adone prescription abilities utilizes infrastructure currently in place, the criminal justice system and pharmacies, and there is no need to create new methadone clinics. The policy expands MAT treatment in prisons which has proven to be effective in Rhode Island, which has witnessed 61 percent fewer overdose fatalities for former prisoners.38 Crucially, the policy also provides for individuals to continue their treatment after release through the state’s Medicaid program and methadone access at pharmacies.

While expanding MAT to pharmacies will be more onerous, especially as federal policy must change and the policy requires additional education for physicians and pharmacists, and the creation of additional regulatory groups in West Virginia, the policy will have a significant impact for the entire community, extending beyond those who have been released from prison. As such, we recommend that the State of West Virginia implement medication-assisted therapy in all prisons and expand MAT prescription abilities to physicians.

Maria Orsini and Douglas Spense, “Drug Offenders Incarcerated in West Virginia: Characteristics and Population Trends, 19982015,” Office of Research and Strategic Planning, January 2017.

34 Ibid. 35 Ibid.

35 Scott Ehlers and Jason Ziedenberg, “Proposition 36: Five Years Later,” Justice Policy Institute, April 2006.

36 Evans, Elizabeth, Libo Li, Darren Urada, and M. Douglas Anglin, “Comparative Effectiveness of California’s Proposition 36 and Drug Court Programs Before and After Propensity Score Matching,” Crime & Delinquency 60, 6 (2014): 909–38, https://doi. org/10.1177/0011128710382342.

37 Ibid.

38 Erick Trickey, “How the Smallest State Is Defeating America’s Biggest Addiction Crisis,” POLITICO Magazine.

33

40

41

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National Institute on Drug Abuse. “Effective Treatments for Opioid Addiction.” Accessed January 31, 2016. https://www. drugabuse.gov/publications/effective-treatments-opioid-addiction/effective-treatments-opioid-addiction.

National Institute on Drug Abuse. “Opioid Overdose Crisis,” January 2019. https://www.drugabuse.gov/drugs-abuse/ opioids/opioid-overdose-crisis.

National Institute on Drug Abuse. “Treating Opioid Addiction in Criminal Justice Settings.” December 2017. https://www. drugabuse.gov/publications/treating-opioid-addiction-in-criminal-justice-settings/treating-opioid-addiction-in-criminal-justice-settings. Assistant Secretary for Public Affairs (ASPA). “HHS Awards Over $1 Billion to Combat the Opioid Crisis.” US Department of Health and Human Services. September 19, 2018. https://www.hhs.gov/about/ news/2018/09/19/hhs-awards-over-1-billion-combat-opioid- crisis.html.

Shames, Alison and Subramanian, Ram. “A Path to Recovery Treating Opioid Use West Virginia Criminal Justice System.”

Vera Institute on Justice. October 2017.

Chutterjee, Rhitu. “With More Opioid Use, People Are More Likely To Get Caught Up In The Justice System.” NPR.org, July 6, 2018. https://www.npr.org/sections/health-shots/2018/07/06/626176621/with-more-opioid-use-peopleare-more-likely-to-get-caught-up- in-the-justice-syst.

Evans, Elizabeth, Libo Li, Darren Urada, and M. Douglas Anglin. “Comparative Effectiveness of California’s Proposition 36 and Drug Court Programs Before and After Propensity Score Matching.” Crime & Delinquency 60, no. 6 (September 1, 2014): 909–38. https://doi.org/10.1177/0011128710382342.

Shayevich Marina. “‘Fear, Paranoia, and Pressure’: Challenges to Accessing Medication-Assisted Treatment for Opioid Addiction.” World of Psychology, September 19, 2018. https://psychcentral.com/blog/fear-paranoia-and-pressure-challenges-to-accessing- medication-assisted-treatment-for-opioid-addiction/.

American Addiction Centers. “How to Get off Methadone.” American Addiction Centers.November 12, 2018 https:// americanaddictioncenters.org/withdrawal-timelines-treatments/methadone.

Prison Policy Initiative. “West Virginia Profile.” Prison Policy Initiative. Accessed January 31, 2019. https://www.prisonpolicy.org/profiles/WV.html.

Keslar, Linda. “The Methadone Blind Spot.” Proto Magazine, April 26, 2018. http://protomag.com/articles/methadone-blind-spot.

Lopez, German. “In 2016, Drug Overdoses Likely Killed More Americans than the Entire Wars in Vietnam and Iraq.” Vox, July 7, 2017. https://www.vox.com/policy-and-politics/ 2017/7/7/15925488/opioid-epidemic-deaths-2016.

Merrill, Joseph O. “Policy Progress for Physician Treatment of Opiate Addiction.” Journal of General Internal Medicine 17, no. 5 (May 2002): 361–68. https://doi.org/10.1046/j.1525-1497.2002.10628.x.

Mitchell, Shannon Gwin, Sharon M. Kelly, Barry S. Brown, Heather Schacht Reisinger, James A. Peterson, Adrienne Ruhf, Michael H. Agar, and Robert P. Schwartz. “Incarceration and Opioid Withdrawal: The Experiences of Methadon Patients and out-of-Treatment Heroin Users.” Journal of Psychoactive Drugs 41, no. 2 (June 2009): 145–52.

“Orsini - Drug Offenders Incarcerated in West Virginia Char.Pdf.” Accessed January 31, 2019. http://www.jrsa.org/member-spotlight/files/wv-drug-offenders-incarcerated-in-wv-1998-2015.pdf.

Orsini, Maria M, and Spense, Douglas H. “Drug Offenders Incarcerated in West Virginia: Characteristics and Population Trends, 1998-2015.” Office of Research and Strategic Planning, January 2017, 7.

Peñaloza, Marisa. “The Opioid Crisis Is Surging In Black, Urban Communities.” NPR.org, March 8, 2018. https://www. npr.org/2018/03/08/579193399/the-opioid-crisis-frightening-jump-to-black-urban-areas.

Office of Senator Manchin of West Virginia. “Prescription Drug Abuse Fact Sheet.Pdf.” Accessed January 31, 2019. https:// www.manchin.senate.gov/imo/media/doc/Prescription%20Drug%20Abuse%20Fact%20Sheet.pdf ?cb.

National Center for Health Statistics.“Drug Overdose Deaths in the US 1999-2017.” CDC. November 28, 2018. https:// www.cdc.gov/nchs/products/databriefs/db329.htm.

Proescholdbell, Scott, and Daniel Edwards. “Former Inmates at High Risk for Opioid Overdose Following Prison Release • UNC Gillings School of Global Public Health.” UNC Gillings School of Global Public Health. Accessed January 31, 2019. https://sph.unc.edu/sph-news/former-inmates-at-high-risk-for-opioid-overdose-following-prison-release/.

Ehlers, Scott and Ziedenberg, Jason. “Proposition 36: Five Years Later.” Justice Policy Institute. April 2006. http://www. justicepolicy.org/uploads/justicepolicy/documents/prop36.pdf.

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Saloner, Brendan, Emma E. McGinty, Leo Beletsky, Ricky Bluthenthal, Chris Beyrer, Michael Botticelli, and Susan G. Sherman. “A Public Health Strategy for the Opioid Crisis.” Public Health Reports 133, no. 1_suppl (November 2018): 24S-34S. https://doi.org/10.1177/0033354918793627.

Samet, Jeffrey H., Michael Botticelli, and Monica Bharel. “Methadone in Primary Care — One Small Step for Congress, One Giant Leap for Addiction Treatment.” New England Journal of Medicine 379, no. 1 (July 5, 2018): 7–8. https:// doi.org/10.1056/NEJMp1803982.

Ranapurwala, Shabbar et al. “Former Inmates at High Risk for Opioid Overdose Following Prison Release.” UNC Gillings School of Public Health. July 19, 2018. https://sph.unc.edu/sph-news/former-inmates-at-high-risk-for-opioid-overdose-following-prison- release/.

Taylor, Kate. “Jail Ordered to Give Inmate Methadone for Opioid Addiction in Far-Reaching Ruling.” The New York Times, November 29, 2018, sec. U.S. https://www.nytimes.com/2018/11/28/us/inmate-methadone-opioid-addiction-ruling.html.

Trickey, Erick. “How the Smallest State Is Defeating America’s Biggest Addiction Crisis.” POLITICO Magazine. Accessed January 31, 2019. https://politi.co/2wbuwha.

Justice Center - The Council of State Governments “West Virginia’s Justice Reinvestment: Strengthening Community Supervision, Increasing Accountability and Expanding Access to Substance Use Treatment.” June 2014. https://csgjusticecenter.org/wp-content/uploads/2014/06/West-Virginias-Justice-Reinvestment-Summary-Report.pdf.

43

Selected Paper

Healthcare Equity and Research Bill (HERB) CATELIN DAVIS

Rice University 2021 Executive Summary

In recent years, several states have passed legislation that allow citizens of age to consume marijuana legally in a variety of circumstances. The specifics of these laws vary from state to state. Some states allow marijuana to only be used medicinally under the close supervision of a healthcare professional, while others allow recreational marijuana consumption. However, the different state-level regulations on legal marijuana consumption directly contradict current federal regulations.

Federally, marijuana consumption, production, cultivation, and distribution are strictly prohibited. This stark contrast in marijuana policies leave citizens in a growing majority of states confused as smoking marijuana can be both an innocent act but also a serious federal infraction.

More specifically, disabled Americans whose medical treat-

44

ments would normally be protected by the Americans with Disabilities Act of 1990 (ADA) have no legal way to consume medical marijuana. This is despite the fact that these populations are those who could benefit the most from medical marijuana. Additionally, conducting the necessary, comprehensive medical research on the health effects of marijuana is made nearly impossible by numerous federally established roadblocks and bureaucratic barriers.

The Healthcare Equity and Research Bill (HERB) is designed to mitigate the effects of this policy incongruence surrounding medical marijuana laws while also encouraging medical research into the health benefits of marijuana usage. This bill would temporarily reschedule marijuana as a Schedule II substance, removing its distinction as an illegal substance in limit-

Conducting the necessary, comprehensive medical research on the health effects of marijuana is made nearly impossible by numerous federally established roadblocks and bureaucratic barriers. ed circumstances. After a period of 5 years, the Attorney General will be required to re-evaluate marijuana’s federal classification. During that 5-year period, the federal government will ease the seemingly punitive restrictions on marijuana research, giving marijuana researchers the freedom and flexibility to explore the drug’s health effects and benefits extensively. In effect, this will provide lawmakers the necessary scientific evidence to make a sound decision in this policy area.

Introduction

In 1996, California was the first state to legalize the production, distribution, and consumption of marijuana for medical use. In recent years, several other states have followed California’s lead. Now 33 states in the United States have some kind of legislation allowing for medical marijuana to be prescribed for the treatment of various maladies. However, the federal govern-

ment still regards marijuana as an illegal substance, most notably in the Controlled Substances Act of 1970 (CSA). In the CSA, various “controlled substances” are categorized into one of five schedules based on the substance’s potential for abuse, accepted medical value, and potential for addiction. Marijuana currently resides in Schedule I, along with some of the world’s most infamous illicit substances like heroin, LSD, and Ecstasy (DEA 2017).

Marijuana’s Schedule I classification has been a point of contention in this policy area, acting as one of the underlying issues that prevent substantial policy progress. It is specifically described by the DEA as the following: “Marijuana is a Schedule I substance under the Controlled Substances Act, meaning that it has a high potential for abuse, no currently accepted medical use in treatment in the United States, and a lack of accepted safety for use under medical supervision.” (DEA 2017)

Congress passed the landmark Americans with Disabilities Act (ADA) that prohibits discrimination of a “qualified individual” on the basis of disability. The ADA did a lot more than mandate the number of accessible parking spots a parking lot must have. It established several protections meant to prevent potential discrimination from the government, the public, and private employers. Title I of the ADA pertains to employment discrimination exclusively. It requires employers to accommodate an employee’s disability, medical condition, and medical treatment for said condition or disability (EEOC). So, if a patient needed to leave work to receive treatment or needed to take periodic breaks to take medication, the employer must allow the employee to do so, as long as it does not significantly affect productivity or quality of work (EEOC). Following that logic, if the same patient was to receive a medical marijuana prescription from their healthcare provider (in compliance with the state’s current medical marijuana regulations), the employee would believe that their marijuana use would also be protected by the ADA. Unfortunately, it is not.

As stated before, the federal government still regards marijuana (medical or recreational) as an illegal drug with no accepted medical use (Miller 2018). More specifically, as the ADA is concerned, “employees and applicants currently engaging in the illegal use of drugs are not covered by the ADA when an employer acts on the basis of such use” (EEOC). The confusion both employers and employees have about the issue of medical marijuana accommodations under the ADA has yet to be determined.

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Lowering some of the more frivolous barriers to marijuana research could allow researchers the resources and time needed to gather potentially life-saving medical knowledge about marijuana’s effects on the human body.

Additionally, access to medical marijuana is also an issue for patients because many health insurance plans are hesitant to extend coverage for medical marijuana (Bardea 2018). Some states have enacted state-level protection for medical marijuana patients. The ADA is a federal law, so its position on marijuana must be consistent with the federal definition of medical marijuana’s legality; actions taken at the state level fail to provide the protections to medical marijuana users that are missing from the ADA. Until this position is changed, disabled individuals who use medical marijuana do so with great risk and no legal protections.

Opponents of marijuana legalization often cite the lack of comprehensive clinical trials detailing the health effects of marijuana as reason enough to maintain the status quo. However, the status quo creates a situation that places stifling restriction on medical researchers, making it nearly impossible for them to conduct these much-needed comprehensive medical studies.

Marijuana's Schedule I status is often cited as the basis for these extensive restrictions. It is very difficult to initiate these kind of clin-

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ical trials because researchers who wish to conduct medical research on marijuana must first navigate through a series of regulatory red tape, bureaucratic hurdles, and rigorous approval processes with the various federal, state, and local governments, as well as with their home institutions and potential investors, before any kind of testing can be done (NASEM 2017). The complexity of the pre-trial approval process has been known to discourage potential researchers from conducting valuable research on marijuana.

Additionally, studies into different marijuana derivatives require different approval processes and restrictions.

If a study is able to receive the proper approval, researchers are limited in how and where they can source marijuana for the study. The only source of marijuana for medical studies approved by the federal government is at a single facility at the University of Mississippi. The strains available from this facility have not changed much since the 1980s, so these strains differ greatly from the strains known to today’s stoners (Owermohle 2019). The only alternative to using marijuana from University of Mississippi is to

require participants in the study to source and ‘‘administer’’ their own bud out of view of researchers; often times researchers are unsure of the exact dosage and chemical characteristics of subject-obtained marijuana because many facilities prohibit researchers from bringing samples onto the site for testing (Owermohle 2019).

However, the issues surrounding medical studies of medical marijuana have come to the attention of several members of Congress led by Representative Harley Rouda (DCA) and Senator Brian Schatz (DHI). Earlier this month, they sent a letter to the Justice Department “requesting a policy change allowing researchers to access marijuana from state-legal dispensaries to improve studies on the plant’s benefits and risks” (Jaeger 2019). In this letter, they recommended the DEA to make a number of policy changes in order to remove some of these barriers to marijuana research. Lowering some of the more frivolous barriers to marijuana research could allow researchers the resources and time needed to gather potentially life-saving medical knowledge about marijuana’s effects on the human body.

Policy Proposal and Justification

The Healthcare Equity and Research Bill (HERB) was created to address policy incongruence between state and federal marijuana legislations. The bill especially focuses on the effects to vulnerable populations like disabled Americans, to lower barriers for medical research into marijuana, and to encourage the discovery of important scientific information about marijuana that would benefit the general public. To achieve these goals, HERB will consist of the following elements: 1. An amendment to the CSA that would allow for the temporary rescheduling of marijuana to Schedule II for a period of 5 years.

This amendment will also allow any marijuana legalization or decriminalization state-level actions adopted before the passing of this bill to exist in their current state. States without significant existing marijuana regulations will treat marijuana as a Schedule II-controlled substance.

2. Legislation that temporarily reschedules marijuana to Schedule II for a period of 5 years. At which time, the Attorney General will review marijuana’s placement in the context of the ACS. The Attorney General at the time may choose to reschedule marijuana to another schedule, to deschedule marijuana (this will effectively legalize marijuana nationally), or to make its Schedule II classification permanent.

3.

Legislation that removes marijuana’s distinction as an “illegal substance” on the federal level.

4. An Order to the DEA to expediate reviews of all applications to cultivate and distribute marijuana for research purposes, including those filed by dispensaries and fa-

cilities that have already received adequate licensing for state-level marijuana distribution, cultivation, or other methods of processing.

5. Legislation establishing a public federal registry of the chemical characteristics (including levels of THC and CBD), strain, physical effects, recommended dosage, recommended usage, health warnings, and additional public health information regarding each unique strain of marijuana. This registry will be available online to the public as well as in all approved marijuana dispensaries. Researchers and growers will be able to add their unique strand to this registry upon verification of findings. Verification should be done by testing facilities approved by the National Institute of Health (NIH).

tion (Rich 2019).

HERB’s 5-year timeline is expected to result in both immediate and future benefits. Most notably, it is intended to allow adequate time for researchers to fully take advantage of new DEA policies on medical research into health benefits of medical marijuana. There could be an option to extend this timeline if there was a compelling enough reason to do so. The resulting scientific information is expected to provide the Attorney General the necessary information to make a definitive judgement on the federal government’s position on legal marijuana. Additionally, HERB will not place any undue restriction on the growing marijuana industry that many communities across the country have come to rely on. Allowing

HERB is intended to force the federal government to proactively re-evaluate its stance on marijuana.

6. An Order to the DEA will “amend... its current policies so as to allow researchers with [at least Schedule II] licenses to obtain cannabis-derived products from state authorized dispensaries for research purposes” as detailed in the aforementioned letter to the Justice Department (Schatz 2019).

7. An order will allow Congressional funds to be given to the Comptroller General of the United States to investigate effects of marijuana impairment on vehicle opera-

the marijuana industry to flourish in these communities can also serve as evidence of marijuana’s long-term effects on society.

Marijuana’s rescheduling to a Schedule II-controlled substance and reclassification as a substance legal under certain circumstances is expected to remove barriers that currently prevent certain populations from taking full advantage of state-level marijuana legislation because of their participation in feder-

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al programs. It will, in effect, allow for medical marijuana accommodations to be required under the ADA. The registry is meant to provide consumers of legal marijuana with the most up-to-date information. The collection of this data will also prove beneficial when the Attorney General re-evaluates marijuana’s placement.

Stakeholder Analysis

However, the 5-year timeline of HERB prevents any adequate analysis of possible political motivations or incentives of any of the stakeholders who will be involved in the decision-making and implementation of HERB’s later phases.

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Ultimately, the single most important stakeholder will remain the Attorney General. The Attorney General possesses near unilateral power in rescheduling and descheduling controlled substances in the context of the CSA (DEA 2017). The bureaucratic agencies that will be most influenced by HERB will be the NIH, DEA, and Food and Drug Administration (FDA). NIH will be responsible for administering the federal database and will play a role in lowering the barriers to marijuana research. The DEA will get the strongest hit from HERB due to the role the DEA plays in regulating both the recreational and scientific uses of marijuana (another role specified in the CSA). The FDA can

be expected to see an increase in the number of cannabis-derived products seeking FDA approval and the discovery of more medical application of medical marijuana.

Conclusion

HERB is intended to force the federal government to proactively re-evaluate its stance on marijuana. Ideally, HERB will be the first step in adopting federal drug polices of the 21st Century. HERB could open society’s eyes on the potential benefits marijuana could have, while also paving the way for more extensive revisions to potentially antiquated elements of policies like the ACS to be better in sync with societal values.

Works Cited

Bardes, Diana M. “From on High: A Discussion of Federal Law and State Court Decisions on Medical Marijuana and the Workplace.” Benefits Magazine, Vol. 55, No. 8 pages 14-18. Aug. 2018.

Jaeger, Kyle. “Bipartisan Lawmakers Tell DEA to Let Researchers Study Marijuana from Dispensaries.” Marijuana Moment.net. Dec. 6, 2019.

National Academies of Sciences, Engineering, and Medicine et al. “The Health Effects of Cannabis and Cannabinoids: The Current State of Evidence and Recommendations for Research.” The Health Effects of Marijuana: An Evidence Review and Research Agenda. Jan 12, 2015.

Rich, J.J. “The STATES Act Would Signal Progress but Could Also Create Many Problems.” Reason Foundation. May 3, 2019.

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Selected Paper

Development Finance Policy for Universal Electricity Access TRISHA GUPTA & LISA LIN Rice University 2023 Abstract

This paper examines the issue of limited global energy access and offers proposals to improve energy access and electrification across the globe, especially in less developed countries. Through the utilization of developmental finance tools, and the newly formed United States International Development Finance Corporation (USIDFC), this paper attempts to address the financing of global energy infrastructure. The current iteration of the USIDFC, recently constructed as an improvement upon the Overseas Private Investment Corporation (OPIC), fails to optimize its potential in relation to energy financing by restricting eligible partner businesses, providing indirect and inefficient approaches to supporting independent local economies, and failing to include comprehensive oversight measures.

In order to rectify these issues, this paper proposes the following policy alterations: the elimination of

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the US-Affiliation preference, the reevaluation of the equity finance benefits, the abolition of the small business requirement, the further involvement of local businesses, and the confirmation of transparency and accountability. The USIDFC, through the implementation of these policy changes, may promote global electrification and energy access in a much more efficient manner while avoiding the ethical and financial problems that plagued its predecessor. In conclusion, this paper offers improvements to the USIDFC in order to promote greater energy infrastructure and, in turn, provide greater energy access and security across the globe.

I. Introduction

As the world’s post-industrial countries seek greater automation and digitization, a jarring and vast disparity in energy infrastructure access widens the technological gap between developed and developing

countries, leaving the latter in severe energy poverty, stifling economic growth and suppressing access to modern basic needs such as internet and clean cooking fuels. Energy poverty is defined by Open Energy Information as being characterized by large numbers of people finding their well-being affected by a very low consumption of energy, use of dirty or polluting fuels, and lack of access to modern energy services.

Energy poverty impacts 840 million individuals worldwide and the key to addressing it lies in the latest evolution of US government foreign aid policy (IEA et al, 2019). Over the course of many decades, US foreign aid policy has transformed from grant- and subsidy-focused assistance to private sector partnerships. The transition from aid-based grants to development finance projects has been gradual, and not without basis. In fiscal year 2018, US-

of electricity with these funds while also netting $149 million in revenue (USIDFC, 2018). The rising movement to tap into the vast resources of the private sector is an attempt to both allocate greater funding for development projects and facilitate sustainable foreign development with the purpose of leading countries towards self-reliance.

II. Background

Electricity access, a modern luxury that is pervasive across post-industrial countries but largely absent in low-income developing countries, is responsible for a myriad of benefits for households and economies (Levi, 2015). Beginning with healthcare, the household problems caused by poor electrification are clearly visible. A lack of energy access tends to restrict families to homes saturated by toxic indoor air pollutants, such as sulfur dioxide

in villages lacking electricity as a means of cooking food and heating rooms (UNDESA, 2014). Greater electrification will serve to remove dependency on solid fuel sources, and therefore eliminate the release of toxic indoor air pollutants.

Energy access also impacts the availability of quality healthcare: electrification enables health clinics to not only utilize modern health technology and machinery at a much lower cost than diesel generators would allow for but also allows them to take advantage of refrigerated medicine storage and sterilization. Overall, it is clear that access to electricity can revolutionize the approach a developing country takes towards health. Electricity access also facilitates the provision of education at both educational institutions and in homes. In the most basic sense, electrification allows students to extend the hours

As the world’s post-industrial countries seek greater automation and digitization, a jarring and vast disparity in energy infrastructure access widens the technological gap between developed and developing countries, leaving the latter in severe energy poverty.

AID was appropriated a total $20 billion by Congress and contributed to the addition of 476MW of electricity worldwide; in the same year, OPIC was appropriated $60.8 million and generated over 500 MW

and mercury. These pollutants are responsible for 2.8 million premature deaths yearly as the burning of traditional solid fuel sources such as kerosene, firewood, and charcoal characterize energy consumption

they spend studying by providing artificial light at night. A more indepth look at the effect of electrification on schools reveals that the advantages are subtle yet innumerable. Students participating in a pi-

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lot program in the Philippines, India, and Morocco reported feeling more ‘excited’ and ‘happy’ to go to school, and the attendance numbers recorded by teachers tracked with this sentiment. Teachers also reported greater ease in providing printed materials , and teaching on rainy days when natural sunlight wasn’t sufficient. The most pervasive benefit of greater energy access would be its facilitation of the use of computers and the internet, which would give students and teachers alike access to a wealth of resources and information . This is key seeing as internet provision has been statistically correlated with higher rates of school completion, literacy, trade openness, and even income, making the internet one of the key tools in bridging a “digital divide” between rich and poor and facilitating civic participation and deliberative democracy (UNDESA, 2014).

Electricity also plays a crucial role in economic growth, and the associated processes of poverty alleviation and increased living standards.

As the OWiD reveals, there is a statistically strong correlation between

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energy use and GDP. The causal relationship between energy use and GDP in less developed countries reveals that “access to modern energy services improves productivity and enables local income generation by freeing up people’s money and time for more productive uses that can improve human welfare” (UNDP, 2017).

Energy development and access is such a fundamental objective that the United Nations has declared it a subclause of the 7th Sustainable Development Goal. The specific text of the goal reads by 2030, expand infrastructure and upgrade technology for supplying modern and sustainable energy services for all in developing countries, in particular least developed countries, small island developing States, and land-locked developing countries, in accordance with their respective programmes of support (UNDP, 2020).

The statistics that the UN provides regarding the current status of their progress towards achieving this goal reveal the impediments that lie ahead. According to the UN, 942 million members, or 13% of the world’s population, do not

meet the 250 megawatt per household threshold for adequate electricity access. In addition, 40% of the world’s population does not have access to clean fuels for cooking, and 31% of primary schools worldwide have no access to electricity. The sheer magnitude of the situation further underscores the necessity of a solution, and accentuates the vast disparity that characterizes global energy access (IEA et al, 2019).

Upon a thorough examination of the current nature of U.S. government funding for long-term infrastructure projects in developing nations and an assessment of the potential impact of the current structure that such projects take, it is clear that development finance can positively transform global utility access. Thus , this paper focuses on reforming the financing system that is currently utilized by American government agencies in order to support private institutions that look to institute infrastructure development projects across the globe.

What is a DFI?

Development finance institutions (DFIs) invest in projects for emerging markets in low income countries (LIC) and lower-middle income countries (LMIC) with the express purpose of stimulating sustainable economic growth and development (CSIS, 2019). DFIs were established by governments to mimic organic private investment; thus, DFIs operate much like commercial banks do with regards to the services they offer and their ability to turn a profit. This latter capability distinguishes DFIs from traditional grant agencies like USAID. DFIs are able to combine public and private investment by applying their own budget towards

projects and simultaneously encouraging investment from private businesses, i.e. private equity funds and commercial banks. Through an intensive screening process, projects are carefully evaluated to ensure sustainability and minimal adverse impact to society and the environment. Most importantly, if the project offers significant potential for a

with emerging markets and the most restricted energy access, providing about one-third of the capital required for these nations’ energy expansion projects (IRENA, 2019).

Moreover, between 2012 and 2016, bilateral DFIs alone committed over $10 billion to energy projects, making energy their largest sector investment (Kalow et al, 2018).

According to the UN, 942 million members, or 13% of the world’s population, do not meet the 250 megawatt per household threshold for adequate electricity access. positive impact, a DFI must consider if the project is likely to secure investment from the private sector without the assistance of the DFI or if the project is too high-risk for private businesses to invest in and will consequently require DFI support.

Importance of DFIs in Energy

Over the past decade, DFIs have grown at unprecedented rates and have both invested in and stimulated private investment in a multitude of sectors including agriculture, infrastructure, finance, and construction. In 2013 and 2014, DFIs were the largest contributors of energy finance in 20 countries

With such profound involvement in and dedication to the energy sector, DFIs have proven to be instrumental in supplying and mobilizing the massive capital needed for the expansion of energy infrastructure in the developing world.

Depending on whether ownership of the DFI belongs to a single government or a coalition of governments, DFIs are categorized as either bilateral (single government) or multilateral (multiple governments) and act to further their respective governments’ policies. The DFI owned by the US government is the United States International Development Finance Corporation (USIDFC), formerly the Overseas

Private Investment Corporation (OPIC). The USIDFC is the product of the 2018 BUILD Act which endowed this newly formed entity with expanded services. According to its website, the USIDFC currently offers four products: 1) political risk insurance, 2) equity finance (direct equity and equity funds), 3) debt finance (loans and guaranties), and 4) technical assistance. Previously, the OPIC was not permitted to engage in equity finance, which is considered a higher-risk and more volatile method of investment than debt finance (OPIC, 2019). However, its potential for greater profit than loans and guaranties has made equity finance a popular financial instrument among DFIs and a powerful addition to the services the USIDFC provides.

Current Policy

Before the BUILD Act, the OPIC’s impact was severely limited by the mandated maximum exposure cap of $29 billion. In comparison to other bilateral DFIs, the OPIC operated at a much lower budget with additional constraints, including the inability to make equity investments or provide technical assistance. Its staff was half the size of its closest competitor, the CDC of the UK, which generated roughly a quarter of the OPIC’s revenue. The USIDFC now has a maximum investment limit of $60 billion, which can be mobilized for the deployment of its newest product, equity finance, as well as for the augmentation of its existing services and administrative staff in support of additional projects.

Considering the potential of the USIDFC, it would be a shame not to streamline the agency with proper regulation and policy in order to ensure that it maximizes its

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investments and promotes further access to utilities across the globe.

The OPIC found itself embroiled in many problems, such as accountability issues, low rates of return, lack of equity financing, and a US-focused nexus. The USIDFC, as a newly formed agency, has the unique opportunity to circumvent these pitfalls and utilize the latest research and recommendations to optimize its funds and allocation. The policies proposed hereinafter look to define the ideal paths by which this agency can effectively maximize energy access worldwide.

III. Proposal Policy Options

There are two clear courses of action: either abolish the BUILD Act in order to revert to the OPIC, or modify the BUILD Act and the functionality of the USIDFC in order to ensure that it is effective and prompt in accomplishing all of its goals. The abolishment of the BUILD Act and reversion to the OPIC yields no clear benefits seeing as the OPIC was riddled with transparency and accountability issues, and suffered from a lack of sufficient tools to allow for collaboration with the DFIs of other developed nations. However, modification of the BUILD Act with the purpose of streamlining the USIDFC offers the best opportunity to fund global energy infrastructure and provide for universal electrification.

Eliminate US-Affiliation Preference

Although the OPIC’s nexus requirement, which largely restricted DFI support to US-affiliated businesses, has been replaced with a policy of preferential treatment for US-affiliated businesses, the nulli-

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fication of even a preference altogether could entirely remove barriers that prevent investment into key energy businesses, especially local ones whose participation in development carries profound influence on the sustainability of projects. Direct equity financing of local energy businesses or the use of local financial institutions to distribute funds to local businesses sets the foundation

ing, which is a powerful investment method newly authorized for the USIDFC’s disposal.

Although it may seem to be a practical idea to limit the benefits of the USIDFC or OPIC funding solely to U.S. businesses in order to maximize the boost delivered to the American economy, it is clear that this renders the agency more ineffectual than before and limits the

Direct equity financing of local energy businesses or the use of local financial institutions to distribute funds to local businesses sets the foundation for sustainable domestic investment that eases a state to self-reliance. for sustainable domestic investment that eases a state to self-reliance.

This directly coincides with USIDFC’s mission to utilize development finance to nourish emerging and recovering markets to self-reliance.

Furthermore, nullifying preference for US-related organizations opens the USIDFC to co-financing opportunities with other DFIs. Co-financing projects afford DFIs a safer method of employing equity finance in higher-risk countries (Kalow et al, 2018). However, it is necessary to remove barriers to equity financ-

promotion of free trade and its associated global economic benefits.

Reevaluation of Equity Finance Benefit

Many criticize equity financing as a high-risk endeavor, and therefore seek to limit or prevent its usage, especially given its capital-intensive nature. As a consequence, the USIDFC has been limited to a 30% cap on equity spending, in order to minimize the risk and potential for loss or no returns.

However, equity financing is a key tool for the USIDFC to utilize:

with equity authority, the USIDFC will have the ability to collaborate, on equal footing, with foreign DFIs that also rely on equity financing, an aspiration that the OPIC was unable to live up to as a senior lender providing debt financing. The effectiveness of equity financing in its past utilization is further supported by data from the Inter-American Development Bank, which reveals that “the incidence of ‘highly successful’ projects was much higher for equity than for loan investments—12% vs. 8%—demonstrating that [equity investment] can be associated with exceptionally high development results” (IDB, 2018). This is because equity projects tend to provide higher leverage, or potential for profit, while generating a positive development impact. With the utilities sector comprising 34% of USIDFC’s portfolio in 2016, diligent use of equity financing can maximize USIDFC’s efforts in developing global energy infrastructure (Kalow et al, 2018).

In addition to higher profit potentials, equity financing offers a large benefit over debt financing by eliminating immediate obligations to repay funds, allowing the U.S. to more authoritatively co-finance with other countries and offer larger sums of capital to local businesses. Given these immense benefits of equity funding, it is clear that barriers to equity need to be deconstructed immediately. Under BUILD, the USIDFC now has limited equity authority, up to 30 percent of the aggregate equity investment in any project and up to 35 percent of the total portfolio. As such, the fiscal year 2020 budget request incorporates only $150 million for equity investments, which translates to roughly only 4 percent of OPIC’s investments in the prior

year, demonstrating that the budget for equity financing must be greatly expanded in order to reap all the benefits detailed above. The Office of Management and Budget (OMB) has scored equity in a $1:$1 ratio against the budget. In essence, the “OMB is making the (wildly illogical) assumption that all equity investments by USIDFC will be immediate and total losses” (Center for Global Development, 2019).

Consequently, equity in companies is being regarded as an irretrievable grant rather than as a long-term investment, thus undermining the original intentions of expanding equity investments and weakening its benefits. From this, it is clear that the OMB must re-evaluate equity financing and apply a ratio against the budget that takes into account the potential for returns and profits that may bolster the BUILD Act and USIDFC. If done, USIDFC will have the authority to apply more equity finance towards energy projects--which are already well-appreciated for their relatively high profitability--prompting even greater development results.

Another critical benefit of equity finance is its ability to generate much-needed employment opportunities in areas of need. Increasing employment in the utilities sector and/or in financial institutions that fund energy projects provides a stronger base of human capital to actualize universal electrification.

This can be achieved by applying the higher potential for returns in equity finance, which are directly correlated with greater job creation, simultaneously advancing development objectives for these countries in need. The Inter-American Investment Corporation found that large businesses receiving equity finance generated 239,000 new jobs

in 2016. More importantly, they found that equity finance allows small businesses to expand by increasing employment and stimulating dramatic growth rates of about 18% (Kenton, 2020). Not only does equity finance create significant job opportunities in unstable markets, but it also supports small business growth, two major development goals held by DFIs (Kenton, 2020).

Thus, the benefits of deploying equity finance for energy expansion are higher potentials for returns, job growth, and support for small businesses. These advantages can be accessed by calling on the OMB to reevaluate the profitability of equity finance, relieving the USIDFC of the 30% equity limit, and allowing the USIDFC to exercise this powerful tool with greater liberty.

Abolish the Small Business Requirement

The USIDFC has incorporated a small-business involvement requirement of 50%, increasing the percentage from the 30% requirement of the OPIC. This requirement stipulates that half of all financed projects must originate from small local businesses. Intended to increase small business involvement in local markets and kindle local grassroots economic development, this policy is a pillar of sustained economic growth. Abolishing it could divert funds to large corporations that are less devoted to local economies. However, the focus on small businesses is a flawed and indirect attempt to engender local sustainability. Instead, USIDFC should increase local involvement by directly funding local businesses - large or small - as addressed in the next section.

The increase of the small business involvement rate from 30%

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to 50% is a change that should be immediately reversed. This requirement is part of a broader push in U.S. policy to support small businesses, known as the ‘set-aside’ policy. Unfortunately, set-aside policy has had a negative impact on the spending allocated to small businesses, concentrating funds in industry sectors where there are greater opportunities for such organizations, limiting free and open competition,

ture development that is necessary to foster electrification in low-income, rural communities, it is necessary to return to the 30% requirement that the OPIC operated utilizing. The unnatural mandate engendered by the 50% requirement fosters a disproportionate investment into small businesses where it might be unwise to allocate funding. A lower minimum would allow companies to wisely incorporate small businesses

can interest rates caused investment to suddenly flow out of Southeast Asia, leading to a sharp puncture in the credit bubble and causing a massive outflow of private investors in the region. This incident shattered Southeast and East Asian economies and led to a devastating Asian financial crisis. This example underlines the importance of encouraging DFIs to allocate funds to local energy and finance businesses in order

One of the major concerns regarding development finance is the possibility of crowding out private investment and distorting regional markets. and creating a series of unintended consequences for both government and small businesses--namely contracting and economic inefficiency, uneven and unsustainable growth, and barriers to entry in the federal contracting space (Lucyshyn and Rigilano, 2017). The primary sectors which small businesses occupy are ‘service-producing;’ these sectors include retail and wholesale trade, real estate, entertainment, and finance. Utilities, a sector that needs to be strongly emphasized in order to promote electrification and global energy access, falls under the category of ‘goods-producing’, a classification in which only 20% of small businesses lie. ‘Goods-producing’ small businesses tend to be concentrated in manufacturing or agriculture, additionally minimizing the number of small businesses that receive funding. In order to best stimulate the kind of energy infrastruc-

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into their portfolios while ensuring to prevent an outflight of foreign that the aforementioned pitfalls are investors from crippling regional economies. This policy would be avoided. effective in stimulating local econInvolvement of Local omies and the flow of financial inBusinesses In lieu of the small-business struments within a certain market, minimum, a requirement should thus promoting sustainable conmandate that 50% of all USIDFC struction of and support for energy funds must be allocated to business- infrastructure--goals not achievable es located in recipient developing through patchwork foreign financial countries. Additionally, local con- injections into regional economies. tent requirements and obligatory explanations for choosing to invest in companies not based in partner countries should be mandated.

Without the implementation of this policy, local economies may become dependent on foreign capital and thus susceptible to those companies’ business decisions and volatility in the international market. A prime example of this phenomenon occurred in Asia at the turn of the last century with the increase in U.S. interest rates. The increase in Ameri-

Ensure Transparency and Accountability

Fortunately, the USIDFC, as a newly formed agency, has the opportunity to avoid the human rights and environmental policy pitfalls that plagued its predecessor. An Inspector General has been appointed to overlook the agency internally; this is a major improvement upon the use of the USAID Inspector General to oversee the operations of the OPIC, which was reported to have violated environmental and so-

cial restrictions placed on it. According to some reports, the OPIC failed to compensate local and indigenous populations for their work and collaborated with local companies accused of workers’ rights abuses in Liberia and Bolivia (CIEL, 2007).

With an Inspector General specifically assigned to the USIDFC, it can be expected that such lapses in adherence to environmental and human rights policies will be avoided.

While the BUILD Act has already mandated more data transparency than the USIDFC’s predecessor, OPIC, there is still a paucity of disclosed impact and development data. Such statistics are necessary for public faith in the USIDFC’s ability to promote US policy and foreign development.

In order to promote transparency and accountability, the following measures must be implemented and enforced to legitimize the USIDFC’s proclaimed dedication to the ideals of disclosure and responsibility. The BUILD Act fails to include mechanisms to address community complaints from residents in target areas, to facilitate the continued improvement of policy, and to create a reserve fund to compensate adversely affected communities. The USIDFC must commit resources to risk mitigation and due diligence by implementing an internal incentive structure that rewards staff for positive development impacts, thereby fostering more resources for site visits, especially in areas highlighted by a 2015 U.S. government accessibility access report where monitoring needs to be strengthened. Additionally, the USIDFC must establish a process by which new and existing environmental, social, or development policies undergo a public

consultation process. It must also be stipulated that all investments have a robust consultation process in place to address issues raised by NGOs and community organizations in USIDFC operation areas. Practicing transparency and accountability crafts a durable model for the continued operation of the USIDFC, guaranteeing a stable institution for facilitating energy expansion in emerging markets.

IV. Policy Evaluation Crowding Out and Market Distortion

One of the major concerns regarding development finance is the possibility of crowding out private investment and distorting regional markets. Development finance institutions operate by providing the same financial services and products as a private investment or equity firm but at a lower cost to the client.

Thus, if development finance is employed in markets in which private lenders are already willing to invest, the DFI would crowd out private investment. This would stunt private investment efforts and go against the purpose of a DFI, which is to stimulate economic growth by working with the private sector.

To address this concern, the USIDFC, in addition to all other DFIs, has outlined an additionality requirement, which states that “USIDFC support must not compete with or supplant available sources of private-sector support or crowd-out private sector lending” (Machlin et al, 2019). The text of the bill that passed Congress and led to the formation of the USIDFC specifically states that the USIDFC is guaranteed to “operate according to internationally recognized best

practices and standards with respect to ensuring the avoidance of market distorting government subsidies and the crowding out of private sector lending” (HR 302, 2018).

USIDFC has realized this additionality stipulation by operating under certain conditions: focusing on low and lower-middle income countries and aligning with strict eligibility criteria for project proposals. Firstly, the USIDFC is primarily committed to investing in low and lower-middle income countries where private investment firms would typically choose not to operate due to the high-risk nature of diverting funds to such countries. Secondly, projects proposed to the USIDFC must meet strict criteria to be considered. To meet the additionality condition, USIDFC requires projects to prove that they have been unable to secure adequate funds from the private sector prior to applying for USIDFC support (Kenton, 2020). DFIs exist in part because of an acknowledgement that government spending and investment alone is insufficient to supply the funds necessary to achieve universal electrification.

Thus, a major role of USIDFC is to unlock private capital for projects in higher risk areas to cultivate market development and private sector involvement in industries such as utilities and electrical production.

By jointly investing in projects with private lenders, USIDFC shares the risk involved in development finance, attracting private investment in its efforts to expand global energy infrastructure. In fact, the OPIC (USIDFC’s predecessor) mobilized $3.8 billion from the private sector to fund development projects in 2018 alone, resulting in the generation of over 500 MW of electricity

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worldwide (USIDFC, 2019). Therefore, USIDFC’s practices safeguard against distorting markets and crowding out private investment.

Development in Host Country

Another common misconception regarding development finance originating from OECD (Organisation for Economic Co-operation and Development) countries is that it exists to promote development with the host country’s best interest in mind, rather than the recipient's best interest. However, data from past OPIC investments proves this claim to be categorically false.

The twenty-first century has seen the purview of DFIs, specifically the OPIC, grow to encompass a “diverse portfolio ranging from investments in the mobile telephone industry in Africa to renewable energy projects in South Asia” (CSIS, 2019). In 2017 alone, the OPIC was responsible for bringing 1,270 megawatts of electricity to homes in rural Africa and South Asia, building 22,000 new homes in South America and Eastern Europe, creating 13,000 jobs worldwide, helping 2.2 million low-income patients gain access to an in-person doctor consultation, and funding 790,000 micro-enterprises. Overall, the OPIC committed $10.6 billion in total capital investment to developing and emerging markets, generating $825.6 million in net tax and duty revenue and $1.84 million in export revenue across all recipient countries. Indeed, a 10% increase in financing from OPIC correlated with a 1.3% increase in growth in low-income countries over the course of one year (OPIC, 2017).

These statistics clearly demonstrate the benefits that recipient countries reap from DFI spending, indicating

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that DFI investment is not centered upon benefitting the host country, but rather on benefitting recipient countries and promoting positive externalities in host countries.

LDCs require the most funding for energy infrastructure projects and it is only by acknowledging the profitability of such projects that we will be able to make strong progress in ensuring that every household on Decrease in USIDFC Earth has access to at least 70 MW Returns Another misconception con- of electricity. cerning development finance is the Sustainable and SelfReliant Development notion that investment in LDCs has A problem that many have lower returns. As a matter of fact, the United Nations Conference on noted in relation to USAID grant Trade and Development conduct- assistance is the prevalence of ecoed research indicating that an LDC nomic injections, one-time funds is not always riskier than other lo- which have become a mainstay of cations, and frequently happens to American foreign aid. However, the be more profitable. When it comes USIDFC and its predecessor OPIC to profits, evidence suggests that have both acknowledged and manrates of return on foreign direct in- aged to circumvent the use of these vestment in LDCs are much higher patchwork funds by embracing a than on investment in developed, distinct form of growth, by which or even other developing, countries. short-term projects serve as catalysts UNCTAD figures show that returns for unilateral, abiding, progress. on investment for TNCs in Africa, Long-term independent and imwith 33 LDCs, are as high as 13% pactful growth is generated through (UNCTAD, World Investment Re- a type of fund allocation known as port 2008). This figure is in com- ‘impact investing.’ As stated by separison to an 8% average return on nior officials within the USIDFC, projects financed in higher-income impact investors will be key partners countries in Europe in the same for the new development finance year (OPIC, 2016). A key advan- agency, with a common allegiance tage of investing in an LDC is the to development impact and effecrelative lack of competition. LDCs tive proficiency deploying capital in have made substantial efforts to put challenging local contexts around into place tax incentives and mini- the world. “USIDFC will play a mal capital requirements for for- central role in accelerating the globeign investors. Incentives are usually al impact investing movement, unaimed at manufacturing, agriculture locking more capital for impact by and tourism with priority given to catalyzing new investors to align poorer areas. In certain cases, spe- their portfolios with global develcial zones are even being developed opment goals” (Cochrane, 2018). to provide quality infrastructure in a Impact investors played a large role in the OPIC, the former iteration concentrated area.

Overall, it is inaccurate to as- of the USIDFC, which claimed to sume that LDCs yield lower returns be a “leader in impact investing by on investments than more-devel- supporting private sector capital oped countries. This is important to and ingenuity that addresses denote, as LDCs suffer the most from velopment challenges and targets a lack of electricity or energy access. sustainable financial returns.” As a

matter of fact, the OPIC fostered a program focused specifically on engendering impact investing in its global portfolio, known as the Portfolio for Impact Program. This program was worth $70 million as of 2018, and has been transferred to the USIDFC as of 2019 in order to continue this legacy of impact investing (OPIC, 2018). These efforts guide recipient countries to self-reliance and facilitate the circulation of financial resources within local markets, providing a stable financial infrastructure to support enduring energy access and security.

IV. Conclusion

While this paper has spent much time detailing the advantages that developing countries would benefit from with the implementation of the proposed policy changes, it has not yet been emphasized how beneficial such changes would be to the United States.

It is important to note that the OPIC, the predecessor to the USIDFC, consistently yielded a net reve-

nue of profit for the United States government in its time. The OPIC, despite only being established in 1971, generated $5.7 billion in gains throughout its lifetime. This was all in spite of a $29 billion spending cap, which has been increased to $60 billion for the USIDFC (Center for Global Development, 2017).

Given that, with an investment cap of $29 billion, the OPIC was able to return $115.8 million to the United States Treasury at the end of 2018.

It is reasonable to assume that the USIDFC, after the completion of its first fiscal year, will be more than capable of generating even greater returns to the United States Treasury.

The international impact of development will be multifold because United States foreign investments are an investment in America’s national security. Through the allocation of greater funds and the supplementation of infrastructure, weakened states are stabilized, international anti-terrorism coalitions are strengthened, weapons proliferation is stemmed, and narcotics trafficking and global crime are halted,

all due to the economic benefits residents of these developing countries receive (U.S. Chamber of Commerce, 2019). Additionally, United States economic interests overseas are augmented by development finance investments. Trade opportunities arise, encouraging greater investment and more rapid economic growth (Office of U.S. Trade Representatives, 2014). United States business interests are also promoted throughout the world, as the USIDFC partners with American corporations in order to fund their initiatives in developing countries. The increased international trade and investment which results from development finance leads to American job creation (Coate, 2017).

Though the positive externalities of these policies to the United States may be more indirect and intangible, they are nonetheless highly valuable and should by no means be discounted when considering the benefits of this policy and its implications.  

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Modernizing Foreign Assistance Network News, August 8, 2019. http://modernizeaid.net/2019/08/opicusaid-coordination-report-shows-promise-strong-develo pment-ties-will-congress-deliver/ Natsios, A. and Postel E. 2018. “The Development Credit Authority needs to stay in USAID.” Devex, February 26, 2018. https://www.devex.com/news/opinion-the-development-credit-authority-needs-to-stay-in-usai d-92184

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Runde, D. 2019. Development Finance Institutions: Plateaued Growth, Increasing Need. Washington, D.C: Center for Strategic and International Studies. https://www.csis.org/analysis/development-finance-institutions-plateaued-growth-increasingneed Saldinger, A. 2019. “Development finance institutions grapple with their growing role.” Devex, March 19, 2019. https:// www.devex.com/news/development-finance-institutions-grapple-with-their-growing-r ole-94408 The Overseas Private Investment Corporation: Background and Legislative Issues. (2016, December 22). Retrieved from https://www.everycrsreport.com/reports/98-567.html UNCTAD. (n.d.). Investment opportunities in Least Developed Countries. Investment opportunities in Least Developed Countries.

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Devex, April 10, 2018. https://www.devex.com/news/former-dca-head-warns-of-perils-of-spinning-agency-intonewus-development-finance-corporation-92504

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Selected Paper

Intellectual Property Rights Protection: An

Examination of Causal Context in the People’s Republic of China JACOB J. KOELSCH Rice University 2022 Abstract

An element of the comparative unorthodoxy of the People’s Republic of China’s (PRC) economic, political, and organizational reform initiated in the late 1970’s is that it is not homogenous in character and degree of reorganization across all socio-political sectors and organizations. For example, a large degree of reorganization as it relates to China’s market ‘opening up’ to foreign investment and manufacture does not necessarily mean that the same degree of reform and is present all of the organizations that are meant to ensure the protection of foreign investors and all of the trade secrets and intellectual property (IP) they bring to the table. Contention regarding the comparatively underdeveloped Chinese IPR protection system presents the PRC as a uniformly developed nation across all sectors and as such, presents little normative explanation for lack of IPR protection, instead pointing to

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Chinese culture as the overarching causal factor. This paper challenges the accepted cultural blame mechanism in favor of a more normative blame mechanism, which instead offers a more hopeful outlook on the future of IPR protection in the PRC.

Introduction

The issue of piracy of foreign goods by firms in the People’s Republic of China remains central in analyses regarding the benefits and detriments of foreign investment in China. Research and development costs, costs central to pricing mechanisms that determine a good’s competitiveness in the market, are readily circumnavigated by producers in the PRC, effectively decreasing the competitiveness of foreign goods in the Chinesemarket. in comparison to pirated domestically produced goods. Publicization of the issue of lack of protection is worldwide, yet external pressure from firms

outside the PRC and transnational organizations that count China as a contributing member have been relatively unsuccessful in ushering a real commitment from the PRC to increase filing and protection mechanisms for IPR. Mainstream academic work regarding China’s comparatively under-enforced intellectual property system points to the influence of Confucianism, Mao-era efforts such as the Cultural Revolution, and Socialist ideology as the cause for the lack of enforceability of IPR in China, painting a rather grim picture with regards to the strengthening of IPR in the PRC. Rather, it is China’s herterogeneity of development across different economic sectors, especially in terms of the nation’s innovation capacity, a reality comparable to that of the United States as the worldwide leading violator of IPR in the nineteenth century, that is to blame for the lack of enforcement of both domestic and international IPR in the PRC. Pertaining to avenues of improvement to this system, it is incorrect to assume refinement

of the system will arise from external pressure. Instead, the system’s advance will occur as the PRC’s internal research and development sector develops, a development that will result in internal pressure from domestic developers to increase protection for native inventions.

The Economic Ramifications of IP Theft

The issue of intellectual property theft in the PRC continues to be discussed in international trade negotiations. Under the current Chinese IPR protective context, a difficult balancing act must be maintained by both the PRC, whose domestic firmsreceive pirating accusations, and the nations whose firms’ IPR are being infringed uponThe nation playing host to firms accused of piracy must also consider that the increased IPR protection that contributes to the nation’s legitimacy as a sphere for profitable foreign investment, investment that is necessary for a developing nation’s eco-

nomic growth, simultaneously with the reality that with an underdeveloped research and development capability, domestic firms rely heavily on spillover knowledge to continue to be competitive in international markers (Keupp et al., 2010). This difficult reality is one that faces leadership in the PRC as the nation’s legitimacy as an economic superpower comes into question in the wake of rampant IPR violation by Chinese domestic producers.

The balancing act that occurs in the camp of foreign firms seeking to invest in the PRC results in cost-benefit analysis regarding on one hand, the enormous prospects of producing in a nation with a heavily developed and attractive manufacturing capacity in terms of costs of manufacture, and the reality that comparatively poor protection of intellectual property often results in the closing off of pirated foreign goods from the Chinese market once plans are stolen and produced at a much lower cost by a Chinese firm. Research and development costs constitute an enormous por-

Mainstream academic work regarding China’s comparatively under-enforced intellectual property system points to the influence of Confucianism, Mao-era efforts such as the Cultural Revolution, and Socialist ideology as the cause for the lack of enforceability of IPR in China, painting a rather grim picture with regards to the strengthening of IPR in the PRC. 63

tion of the costs of production for firms, costs that when circumnavigated by PRC pirates, heavily increase the counterfeited product’s appeal in the Chinese market at the expense of the original product whose comparatively higher price makes the it wholly unattractive to Chinese consumers ((Navarro, 2012). Pharmaceutical companies such as Merck and Pfizer spend approximately 20% of their sales on research and development, while technology firms such as Microsoft and Intel spend around 15% of sales on research and development, significant costs that when circumnavigated by Chinese producers, results in a significant difference in price of the original and the counterfeit, effectively “[draining] a little bit more blood from [American] manufacturing veins” (Navarro, 2012, 57). What results is essentially a closed Chinese market for pirated goods whose brand recognition is not significant enough to overcome the large difference in price between the original good and the pirated Chinese good. Firms suffering from IPR infringement by domestic Chinese firms exert enormous amounts of pressure on their respective governments to, in turn, force the PRC to increase its protective measures for both domestic and foreign IPR in China.

Contention Over the Causes of Violations

by PRC Firms

Despite rampant publicization of what multinational firms characterize as rampant violations of both foreign and domestic IPR by Chinese firms, and notwithstanding membership in several transnational organizations and treaties

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specifically designed to police IPR violations (signed in to World Intellectual Property Organization in 1980, signed Paris Convention for Protection of Intellectual Property in 1985, signed Madrid agreement in 1989), violations still continue in the PRC (Can, 2017).

Chinese culture as a causal factor.

Examinations of intellectual property protection and violations in China both in academic work and in the mainstream media tend to take an Orientalist (Said, 1978) approach to uprooting the cause of such violations, pointing to certain determinants that they believe shape Chinese cultural ideology, determinants like Confucian boycott behavior and Socialist thought regarding communal property (Paradise, 2013). Economist Peter Navarro makes explicit the cause-andeffect relationship between Chinese cultural ideology and intellectual property abuse in a sweeping statement in his book Death by China (2011): The lack of remorse exists because over a billion mainland Chinese citizens have been raised in an ethics vacuum where property rights are meant to be trampled- and the sate owns everything. It’s an ethics skew that runs straight back to Chairman Mao and straight through the lunacy of the Cultural Revolution. This amoral skew created an attitude of, ‘Do whatever you can get away with to better your own situation’” (5859).

Dr. Navarro’s explicit sweeping statement blames overarching Chinese cultural ideology for the abuse of intellectual property rights, a grim assertion that eliminates the possibility for any internal moti-

vation for an increase in IPR protection. Subscribing to a view that places the blame of violation on an overarching Chinese cultural ideology, an idea that in and of itself is extremely unnuanced and oversimplified given the ethnic, cultural, and ideological diversity of the PRC, the motivation for increasing IPR protection must then come from foreign pressure. The Orientalist lens offers only one avenue for increasing IPR protection in China given the country’s depiction in this lens as an irrational actor: foreigna maintenance of the historically uneven power relationship between the PRC and diplomats from foreign nations such as the United States that seek an increase through coercive pressure.

However, this external pressure has persisted and steadily increased alongside China’s rise within the global economy without resulting in sizeable improvements to IPR protection in China.

Underdeveloped Research and Development as a causal factor.

Cultural blame fails to reconcile the fact that the PRC has not always been the leading global violator of IPR. In fact, in the nineteenth century, it was a nation in a similar stage of development of its respective research and development sectoras the PRC’s innovative capacity in the twenty-first century, a nation where ideologies such as socialist thought and Confucian boycott behavior are altogether absent and have been historically opposed. In the post-revolution era, American piracy of British textbooks and literature was rampant to the point that counterfeited books became accepted as the norm for American print media (Peng, 2013). Similarly to the PRC’s current IPR enforce-

ment mechanisms, the piracy of British literature occurred in spite of the presence of protective legislation such as the Copyright Act of 1790 and the Patent Act of 1793, although copyright infringement in the American case was formally encouraged by leading American officials such as Alexander Hamilton, which resulted in a much greater degree of infringement than that which occurs in the PRC today (Peng, 2013). In both the nineteenth century American context and in the PRC’s twenty first century context, opposition to infringement is wholly external and in both cases results in very little practical increase in IPR protection because of

the American IPR system and similarly, it is not the case of the Chinese “ethics vacuum”that causes the lack of enforceability of IPR in the PRC. Rather, it is the lack of a flourishing research and development sector in both cases thatresults in this lack of enforceability, a fault that, with growing pressure from indigenous researchers and developers, will become correct as the PRC graduates from the stage of a developing nation with an inordinate capacity for manufacturing (Navarro, 2011).

The Orientalist view of the cause of rampant violations in the PRC explicitly draws a connection between these Chinese cultural fac-

Cultural blame fails to reconcile the fact that the PRC has not always been the leading global violator of IPR. the lack of enforceability of the proposed sanctions for infringement.

External pressure in both cases proves to be an insufficient motivator for increasing IPR protection. In the United States in the nineteenth century, it was pressure from indigenous authors and firms that resulted in the motivation for increasing protection, asimilar reality to what will need to occur to spark a motivation among PRC leadership to take the necessary steps to increase IPR protection (Peng, 2013). Thus, it is truly not the case of American exceptionalism that resulted in the growth of

tors such as socialist thought, Confucian boycott behavior, and the influence of Maoist cultural-revolution-era ideals, resulting in a moral value judgement characterizing of the lack of IPR enforcement in the PRC. The view then contrasts this characterization with a comparison between this lack of enforcement in China and the developed American system, a contrast implying a link between American exceptionalism and the success of the American system (Peng, 2013). This view fails to address the historical violations of IPR by the United States

that occurred in a cultural context where the specific cultural ideologies (namely socialist thought, Confucian boycott behavior, and the influence of Maoist cultural-revolution-era ideals) that social scientists typically point to as the causes of rampant IPR violations in China were altogether absentThe cause must therefore be much more rationally motivated and quantifiably based in China’s status as a nation with a lack of uniformity of development, especially in terms of its capacity for innovation. As such, the grim picture regarding prospects of increased protection in China painted by advocates of the Chinese ideological blame mechanism becomes much more encouraging for domestic Chinese innovators and foreign investors alike. The twenty-first century PRC simultaneously demonstrates a strong imitation capability and a thriving capacity for manufacture but is caught in the developmental stage of its innovation sector.

The comparative lack of innovation and reliance on manufacture exemplary of a developing nation has resulted in a reliance on imported designs and knowledge spillover for some key industries that have been instrumental to solidifying the PRC’s position as a major player in the global economy. Increased IPR stifles innovation in industries where knowledge spillover is essential to the international competitiveness of Chinese firms handicapped on the international market by a poor national capacity for innovation (Chu et al, 2018). The PRC is currently the global leader in the manufacture of Penicillin, Vitamin C, Terramycin, Doxycycline, Hydrochloride, and Cephalosporins, however, in terms of pharmaceutical innovation, Chinese firms cannot compete head on with foreign transnational

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innovation-driven pharmaceutical companies (Cai et al, 2018). In a study done by Cai, Zhao, and Coyte (2018) on the relationship between the competitiveness of the knowledge-spillover-reliant Chinese pharmaceutical industry and degree of IPR protection found that “the strength of IPR protection is shown to be negatively related to the international competitiveness of China’s pharmaceutical manufacturing industry.” Firms such as domestic firms in the Chinese pharmaceutical industry have a collective comparatively large influence on central policy because of their centrality to the global competitiveness of the Chinese economy. There is comparatively less incentive to increase IPR protection, even for native inventors from firms in industries with a comparatively large capacity for lobbying, given the PRC’s trans-industrial comparative lack of a capacity for innovation.

Evidence of Efforts Towards Development of IP protection in the PRC

The orientalist argument for the cause of IPR violations in the PRC, a blame that implies that the Chinese-specific cultural factors make it impossible for IPR protection to increaseis somewhat challenged by recent trends pointing to the continued development of the Chinese IPR system and the development of a culture of patenting in China. This view pays little attention to the reality that the PRC has cemented itself as the most prolific patent filing nation globally continuing a trend of rapid increase in patenting over the past fifteen years, a change in national ideolo-

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gy that has resulted from decades of slow but gradual reform to an IPR system that has been present since the onset of market reform in the 1980’s (Fang et al, 2017). The characterization of Chinese IPR protection system as inadequate is based on a comparison of both Western IPR systems having been established over two centuries ago in the case of the American system, and the Chinese system, which itself is extremely young and immature, having only been in place for four decades. Since 1983, the PRC has been steadily adding depth to their IPR protection system, with the addition of laws and regulations such as the Trademark, Patent, and Copyright Laws, all put in place before the turn of the twentieth century, and legislative adjustments to the onset of digital invention, exemplified by the passing of the Measures for the Administrative Protection of Internet Copyright (MAPIC), signed into legislation in 2005 (Can, 2017). The Chinese system continues to be extremely dynamic, having been amended three times, with a fourth amendment having recently been proposed on January 4, 2019 by the National People’s Congress (NPC), an amendment that aims to increase damages by up to five times the original amount when willful violation occurs.

In terms of enforcing protective legislation, the PRC recently established three specialized IP courts in Beijing, Shanghai, and Guangzhou at the end of 2014 to enhance the effectiveness and efficiency of the judicial system of IPR protection, a recent development that directly contradicts the orientalist argument for the lack of IPR protection in China (Can, 2017, 45). A n element of concern for some scholars exam-

ining IPR abuse in China is a belief that there is no internal incentive for Chinese courts to police domestic violations of foreign Intellectual Property. For example, in a study regarding the means of IPR protection in weak appropriability regimes, authors Keupp, Beckenbauer, and Gaussman (2010) assert that there is a clear unlikelihood for foreign firms to win patent lawsuits against Chinese firms in Chinese courts because “the institutions of the law in China are plagued by nepotism and corruption, politicization of courts and judges, discrimination against foreign business, [and] ever-changing laws and local protectionism,” all assertions that dissuade foreign firms from direct investment and manufacture in China. However, these claims fail to recognize specific recent high profile court rulings that awarded unprecedented damages to foreign firms at the expense of domestic pirates, for example the ruling in favor of American social media titan, Facebook, at the expense of a Guangdong-based social media site, or the ruling in favor of American sportswear manufacturer, New Balance, at the expense of local Chinese shoemakers, rulings that resulted in over 1.5 million dollars in damages in each case (Bhandari, 2018). Authors making these assertions regarding continued stagnation in enforcement efforts fail to recognize significant recent developments in the Chinese IPR enforcement system that concretely point to the maturation of the Chinese IPR system.

Not only has there been a measurable change in the PRC regarding popular ideology of patent filing, but this change has additionally resulted in a need for corrective legislation regarding the abuse of

IPR on the side of the inventor rather than the pirate. Complementing the recent surge in patenting in the PRC over the past fifteen years has been the onset of a new issue exemplary of a young and developing IPR system: anti-competition abuses by over-filing domestic inventors (Wang, 2017). These anti-competition practices take the form of refusal to license patented designs, tying, predatory and excessive pricing, and price discrimination. In response, the Antimonopoly Commission under the State Council launched the drafting work of antimonopoly

idence of a change in overarching practices regarding IPR protection as a tool for the growth of a firm, and of the change in the overall culture of patenting in the PRC. To complement the development of Chinese domestic IPR legislation, China joined international treaties and transnational organizations that specifically govern IPR protection, both in terms of adding depth to a pre-existing domestic protection system, but also in terms ofestablishing a framework for the protection of international IPR in the PRC. Ascent into these treaties

ment Concerning the International Registration of Marks in 1989, the Berne Convention for the Protection of Literary and Artistic Works in 1992, the Convention for the Protection of Procedures of Phonograms Against Unauthorized Duplication of Their Phonograms in 1993, the Patent Cooperation Treaty in 1994, and the WIPO Copyright Treaty in 2007.

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China’s joining of these international treaties involved the acceptance of each treaty and organization’s rights and obligations, effectively forcing the adoption of internationally accepted legal IPR framework by the PRC. Those who fail to recognize these recent developments also tend to dismiss that the Chinese patent filing system is, in terms of its institutional framework, extremely similar to systems considered to be fully developed, systems not receiving such direct explicit institutional criticism as the PRC’s IPR system.

Comparing the modern Japanese system to the institutional framework currently in place in the PRC, the two patent filing systems are extremely similar, with the requirements for patenting being identical in both systems, except that the Chinese system actually offers more patentable categories than the Japanese system (Yaji, 2008). Thus, when examining the Chinese IPR system, criticism regarding the current abuse of IPR must be based more so ino the lack of enforcement of the and organization occurred rapidly legal framework, an issue that must and was extremely broad, according still be corrected by PRC legislators, to Can Huang (2017): rather than on the basis of a general lack of legal framework regarding China became a member of the violations. The seemingly contraWorld Intellectual Property Organidictory nature of increased legislazation in 1980, joined the Paris Contion regarding protection combined vention for the Protection of Industrial with stagnant enforcement is truly Property in 1985, the Madrid Agree-

Authors making these assertions regarding continued stagnation in enforcement efforts fail to recognize significant recent developments in the Chinese IPR enforcement system that concretely point to the maturation of the Chinese IPR system. guidelines in 2015, a drafting that aims to “help protect fair market competition, stimulate innovation, and prohibit undertakings from abusing intellectual property rights to eliminate or restrict competition” (Wang, 2017, 814). Simply stated, the challenge of fighting over-filing for anti-competition purposes is ev-

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exemplary of the dilemma of many emerging economies such as the PRC where “[developing] countries must manage the difficult problem of encouraging the inflow of foreign technological knowledge, to help domestic firms benefit from knowledge diffusion, while also reassuring foreign firms that their IPR will be protected” (Keupp, 2010, 112).

While there still exist institutional framework issues in the PRC’s IPR protection system such as issues of fragmented authority resulting inhorizontal and vertical rent-seeking competition among organizations designed to police IPR violations, the key issue resulting in these violations is the PRC’s lack of innovation capacity (Paradise, 2013, 324).

comparatively weak research and development capability. As the central government increases its commitment to grow the PRC’s innovation capability through massive structural overhauls, most notably the “Made in China 2025” plan proposed in 2015, an increased commitment to enforcing protection strategies brought about by internal pressure from native inventors in a growing research and development sector will also occur, as it did in the case of formally immature IPR systems such as that of the United States and Japan (Peng, 2013).

Growth of the PRC’s Innovation Capacity.

Top leaders in the PRC’s central government have been extremely vocal about the next step Prospects of Future of Chinese economic development Increase strategy, the creation of a Chinese The issue of the lack of en- innovation society. At the 17th naforcement of the existing Chinese tional congress, then president Hu and transnational legal frameworks Jintao stated that “innovation was regarding IPR protection can pri- to be at the ‘core’ of the country’s marily be traced back to the PRC’s development strategy”, a sentiment

echoed by current president Xi Jinping during a visit to the Chinese Academy of Sciences in 2013, and re-iterated by high level officials such as former Premier Wen Jiabao (Paradise, 2013, 317-318). As upper level officials continue to further their commitment to growing China’s innovation capacity by continuing the trend of increasing government subsidies to research and development, internal pressure from native inventors will also increase (Peng, 2013). It is this internal pressure fostered by an increased commitment to grow the PRC’s innovation capacity, and not external pressure from foreign nations, that will result in the most substantive increase in not only institutional protection for IPR, but more importantly, in the enforcement of existing framework. although the motivations that results in the greatest amount of measurable enforcement increase do not take the form of external pressure, rather a proactive commitment to continuing foreign investment in the PRC. Studies done

It is this internal pressure fostered by an increased commitment to grow the PRC’s innovation capacity, and not external pressure from foreign nations, that will result in the most substantive increase in not only institutional protection for IPR, but more importantly, in the enforcement of existing framework.

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by Chen and Puttitanun (2005) and

by Hu and Png (2013), both seeking to examine the effects of IPR on innovation found that reinforcing IPR enforcement itself can strengthens innovation in part by increasing the external financing ability of domestic firms, an increase brought about by the attractiveness of increased security of designs as a result of the lessened degree of piracy by these same domestic firms. Thus, IPR protection is necessary to continuing foreign investment in Chinese domestic firms, especially as the PRC graduates from the stage of a developing nation and no longer enjoys some of the benefits of such a categorization at the transnational level and is held more accountable for such violations.

Recommendations for Increase.

The strategy for increasing enforcement of IPR must be done incrementally and extremely carefully, as an overcorrection in protection could have an adverse effect on an already lacking Chinese innovation sector, and even on the competitiveness of domestic markets. First, an excessive increase in protection and enforcement mechanisms can result in over-filing practices that stifle competition in favor of inventors who, through the lack of a truly competitive market, enjoy the ability to price-discriminate, and price in a predatory and excessive manner (Wang, 2017). The creation of monopoly markets market caused by an overcorrection of enforcement mechanism could be truly detrimental to Chinese consumers, which will, in turn, likely result in opposition to the same excessive increase in IPR protection and enforcement that caused the lack of competition.

Second, degrees of increase cannot be trans-industrial: the degree of reliance of each individual industry on the spillover of knowledge and on the import of intermediate inputs rather than domestically produced intermediate inputs must be weighed when increasing protection and enforcement mechanisms. The positive outcomes of knowledge spillover from lack of IPR protection are only relevant until the PRC invests in its research and development to the point that Chinese firms can truly compete globally in terms of innovation and not simply manufacturing; the purposefully incremental and methodical increase of IPR protection for these sectors will end when this equal innovative competitiveness becomes a reality. For example, the strength of IPR protection in China since 1995 has increased yearly while the international competitiveness of the Chinese pharmaceutical manufacturing industry has consistently decreased (Cai et al, 2018), primarily as a result of this specific industry’s current reliance on the spillover of knowledge from international firms, a reliance that will continue as long as governmental investment in this specific industry’s research and development capabilitycontinues to be insufficient. Until the innovation capacity of a specific industry approaches the innovation capacity of foreign firms jockeying for position in the international market with these same Chinese firms, the PRC must be careful in the degree of increase of IPR protection and enforcement.

The degree of reliance of each specific industry on imported versus domestically produced inputs must also be carefully examined when assessing the preferable degree of increase of protection mechanisms.

A study done by Chu et al (2018) found that industries relying primarily on the import rather than the domestic production of intermediate inputs benefit the most from increased IPR protection, a combination that is positively correlated with an increase in innovation.

These findings reinforce that the degree of increase in protection and enforcement mechanisms cannot be blindly trans-industrial, as doing so could stifle innovation in some specific sectors, an effect directly contradicting of that which is the aim of increasing IPR for the benefit of an already lacking research and development sector.

De-Facto Protection Strategies When manufacturing in the PRC, both domestic foreign firms aware of China’s issues with protection and enforcement of IPR regulations have developed de-facto protection strategies in place of the enforcement that is traditionally guaranteed by the central government in more developed IPR systems. The most commonly used protection strategy is that of excessive technological specialization, or the “[creation and exploitation] of more difficult-to-replicate, non-tradable secrets” (Keupp et al, 2010, 115). an effort to make imitation so costly as to match the cost of innovation itself. (Keupp, Beckenbauer, & Gassman, 2010, p.115). domestic and foreign firms alike also take advantage of pervasive internal and external “guanxi” mechanisms, sometimes resulting in corrupt rent-seeking practices when a giving-and-receiving relationship is established between a firm and officials hired to oversee the protection of IPR (Keupp, 2010). These strategies exist as mechanisms designed to bridge the gaps created

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by institutional uncertainty and the weak appropriability of the Chinese regime. Until more funding from all levels of the Chinese government is appropriated to grow the PRC’s innovation capacity to a competitive level in international markets, these strategies will be necessary for firms to ensure that the damages caused by unchecked Rviolations to not exceed the benefits of manufacture in the PRC.

Conclusion

The lack of success of rampant external pressure on the PRC to increase the enforcement of established IPR protection regulations hasresulted in a great deal of examination of the Chinese IPR sys-

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tem by social scientists worldwide.

Some, choosing to follow an Orientalist narrative, place the burden of causation on an idea that adherence to these regulations is simply impossible given the influence of Taoism, Maoist socialism, and the Cultural Revolution (among others) on the overarching ideology of the Chinesegeneral population. This blame mechanism paints a grim reality for the prospects of growthof the Chinese IPR protection system, a grim reality that can only be dealt with by the continuous treatment of Chinese officials as irrational actors on the international sphere. The reality of the cause for such violations is much more rationally based and as such, reframes the narrative regard-

ing the prospects of the maturation of the Chinese IPR protection system,a reality that calls to mind the fact that the nation whose firms and diplomats currently lead the charge for putting external pressure on the PRC to increase enforcement is a nation who, in a similar state of infrastructural and economic development, practiced the same types of violationsas the PRC today, arguably at an even greater rate. The key to increasing enforcement of IPR in China rests in fostering enough internal pressure toresult in measurable change, pressure that will only rise if significant efforts are made by the Chinese government at all level to grow the nation’s capacity to innovate.

References

Bhandari, Bibek. 2018. “BBC Sues Chinese Company over Branding.” Sixth Tone, February 7, 2018. https://www.sixthtone.com/news/1001681/bbc-sues-chinese-company-over-branding Cai, J., Zhao, H., and Coyte, P. C. 2018. “The Effect of Intellectual Property Rights Protection on the International Competitiveness of the Pharmaceutical Manufacturing Industry in China.” Inzinerine Ekonomika-Engineering Economics, 29(1): 62–71. https://doi-org.ezproxy.rice.edu/10.5755/j01.ee.29.1.16878 Can, Huang. 2017. “Recent Development of the Intellectual Property Rights System in China and Challenges Ahead.” Management & Organization Review, 13(1): 39. https://doi.org/10.1017/mor.2017.2 Chu, A. C., Fan, H., et al. n.d. “Effects of international trade and intellectual property rights on innovation in China.” Journal Of Macroeconomics, 57: 110–121. https://doi-org.ezproxy.rice.edu/10.1016/j.jmacro.2018.05.003 Fang, L. H., Lerner, J., and Chaopeng Wu. 2017. “Intellectual Property Rights Protection, Ownership, and Innovation: Evidence from China.” Review of Financial Studies, 30(7): 2446. https://doi.org/10.1093/rfs/hhx023 Keupp, M., Beckenbauer, A., and Gassmann, O. 2010. “Enforcing Intellectual Property Rights in Weak Appropriability Regimes: The Case of de Facto Protection Strategies in China.” MIR: Management International Review, 50(1): 109130. http://www.jstor.org/stable/40658353 Maguire, J. 2012. “Progressive IP Reform in the Middle Kingdom: An Overview of the Past, Present, and Future of Chinese Intellectual Property Law.” The International Lawyer, 46(3): 893-912. http://www.jstor.org/stable/23827421 Navarro, P. 2011. Death by China. N.J: Pearson Education.

Paradise, J. 2013. “The New Intellectual Property Rights Environment in China: Impact of WTO Membership and China’s ‘Innovation Society’ Makeover.” Asian Journal of Social Science, 41(3/4): 312-332. http://www.jstor.org/stable/23654846 Peng, M. W. 2013. “An institution-based view of IPR protection.” Business Horizons, 56(2): 135–139. https://doi-org.ezproxy.rice.edu/10.1016/j.bushor.2012.10.002 Said, E. 1978. Orientalism. New York: Random House.

Suzuki, K. 2015. “Legal enforcement against illegal imitation in developing countries.” Journal of Economics, 116(3): 247270. http://www.jstor.org/stable/43918299 Wang, Xianlin. 2017. “Recent Developments in China’s Antimonopoly Regulations on Abuse of Intellectual Property Rights.” Antitrust Bulletin, 62(4): 806–814. http://ezproxy.rice.edu/login?url=http://search.ebscohost.com/login. aspx?direct=true&b=sph&AN=126235494&site=eds-live&scope=site Yaji, K. 2008. “A Study on the Patent Application Strategy for China from the Viewpoint of the Patent Application Procedure and Patent Application Conditions in China.” Hitotsubashi Journal of Commerce and Management, 42(1 (42)): 29-44. http://www.jstor.org/stable/43295014 Ying Liu, and Cheng Lian. 2018. “Tentative Analysis of Tea Beverage Enterprise Patent Protection Strategy.” AIP Conference Proceedings, 2040(1): 30007-1-130007–5. https://doi-org.ezproxy.rice.edu/10.1063/1.5079189

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Selected Paper

Increasing the Resilience of Puerto Rico’s Electricity Grid for Future Disasters

ALICE LIU

Rice University 2020

Abstract

Disaster resilient infrastructure is urgently needed to respond to the increasing frequency and intensity of extreme weather events brought about by climate change. Puerto Rico’s human rights crisis following the devastation of Hurricane Maria is one example of how failures in the electricity system can lead to cascading effects across other critical service sectors, including communications, water, and medical services.

A week after the hurricane, 95% of the island was without power, less than half the population had tap water, and 95% of the island had no cell phone service.1 An estimated 2,975 perished from hurricane-re-

lated problems in Puerto Rico in the five months after – many because power outages prevented those with treatable chronic illnesses from receiving medical care.2 Preexisting dysfunctionalities in Puerto Rico’s electricity grid, as well as a lack of native fossil fuel reserves, make Puerto Rico a valuable case study for the role of distributed technologies and renewable generation in creating a more reliable and resilient electricity system. This paper will first delineate the weaknesses in Puerto Rico’s electricity grid, then propose initiatives that might be taken to increase resilience while ensuring reliable and affordable electricity on a day to day basis for Puerto Rican residents.

“Energy Resilience Solutions for the Puerto Rico Grid.”

“Ascertainment of the Estimated Excess Mortality From Hurricane Maria in Puerto Rico.”

1 2

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Background

Historically, mutually reinforcing fiscal and geographic challenges have inhibited the establishment of an affordable, reliable, and resilient electricity system for Puerto Rico’s 3.2 million inhabitants3. Residents face electricity prices of 21.5 cents/ kWh, almost twice as expensive as the U.S. average of 13 cents/kWh.4 Customers suffer from power outages at five times the frequency of North American customers.5 A week after Hurricane Maria’s landfall, 95% of the island was without power. Three months after, only half of the power was restored, and full restoration was not achieved until almost a year later.6 Fiscal Pressures

In 2017, the vertically integrated Puerto Rico Energy and Power Authority (PREPA) controlled most of the island’s generation capacities, and all of the transmission and distribution lines. When PREPA filed for bankruptcy in July 2017, it was $9 billion in debt.7 The agency’s fiscal woes were partially due to structural issues, including “frequent turnover in leadership and management … [and] lack of regulatory oversight.”8 Puerto Rico’s decade-long economic recession had also resulted in a government plagued by chronic underfunding, underinvestment, and waning demand from population decline. Finally, PREPA’s insolvency was perpetuated by import dependence and

Puerto Rico’s human rights crisis following the devastation of Hurricane Maria is one example of how failures in the electricity system can lead to cascading effects across other critical service sectors, including communications, water, and medical services. oil, natural gas, and coal to supply its energy needs. In 2015, Puerto Rico imported 38,690 thousand barrels of petroleum products, 52 billion cubic feet of natural gas, and 1,485 thousand short tons of coal.10 In addition to typical usage in the transportation sector, petroleum products supplied 45% of the island’s electricity, a situation that makes little environmental or ecoImport Dependence: nomic sense.11 Burning oil emits Costly Fuel Oil As Puerto Rico has no proven only 25% less carbon dioxide than reserves of conventional fossil fuels, coal, the dirtiest energy source; natit is highly dependent on imported ural gas, the leading fuel for U.S. electricity generation, emits 50% infrastructural weaknesses, products of the island’s lack of domestic fuel reserves and mountainous terrain.

Yet these geographic challenges are not insurmountable, if not for severe financial limitations that had led to neglected generation facilities 28 years older than the industry average, inefficient, and prone to outages.9

“Puerto Rico Quick Facts.”

“Electric Generating Costs: A Primer.”

5 “Puerto Rico Electric Power Authority: Amended and Restated Fiscal Plan – Draft.”

6 “Energy Resilience Solutions for the Puerto Rico Grid.”

7 “Puerto Rico Electric Power Authority: Amended and Restated Fiscal Plan – Draft.”

8 Brown, Respaut, and Resnick-Ault. “The Bankrupt Utility Behind Puerto Rico’s Power Crisis.”

9 “Puerto Rico Electric Power Authority: Amended and Restated Fiscal Plan – Draft.”

10 “Puerto Rico - Territory Energy Profile Analysis.”

11 “Puerto Rico - Territory Energy Profile Analysis.”

3 4

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less carbon dioxide than coal.12 It is also the costliest method of electricity generation, making Puerto Rico susceptible to volatile global market prices. In 2011, near peak oil prices meant that petroleum-generated electricity cost 21.56 cents per kilowatt hour, compared to 3.23 cents using coal.13 Although PREPA recognizes this vulnerability, it lacks the funds and capacity for the new investments necessary to transition away from imported fossil fuels to domestic renewable resources. The disconnect between policy and execution is demonstrated by the failure of the Energy Public Policy Office’s 2010 renewable portfolio standard calling for 12% renewable energy by 2015.14 Renewables remain at only 3% in 2018.15

the transmission and distribution infrastructure. Two of PREPA’s critical generating facilities, Aguirre and Costa Sur, are located on the southern coast, as seen in Figure 1.

Meanwhile, 65% of the system’s energy demand is concentrated in and around San Juan in the northeast.16 Transmission lines connecting energy generation to demand must cross the sparsely populated mountain range extending across the center of the island, La Cordillera Central, with peak elevations of up to 4,300 feet.17 Not only does this make crucial maintenance against vegetation growth and aging infrastructure difficult, it also makes the grid extraordinarily vulnerable to localized failures. An interdependent system means that northern load centers, primarily the San Juan area, are at Transmission Difficulties: risk of failure because of failures up Generation Location and the power line. During Hurricane Mountainous Terrain Puerto Rico’s mountainous Maria, although most of the generterrain provides additional chal- ators remained intact, undamaged lenges in operating and maintaining generators could not supply power “How much carbon dioxide is produced when different fuels are burned?”

“Electric Generating Costs: A Primer.”

14 “Energy Transition Initiative – Puerto Rico Energy Snapshot.”

15 “Puerto Rico Electric Power Authority: Amended and Restated Fiscal Plan – Draft.”

16 “Build Back Better: Reimagining and Strengthening the Power Grid of Puerto Rico.”

17 “Build Back Better: Reimagining and Strengthening the Power Grid of Puerto Rico.”

18 “Build Back Better: Reimagining and Strengthening the Power Grid of Puerto Rico.”

19 “Puerto Rico - Territory Energy Profile Analysis.”

20 Weissenstein, “Puerto Rico Grid ‘teetering’ despite $3.8 Billion Repair Job.” 12 13

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until hard to access transmission lines along the extensively damaged north-south corridor were repaired.

In 2016, a fire at the southern Aguirre plant caused an island-wide blackout for six days.18 In the future, dependency on transmission across the mountain range will continue to be a critical weakness.

Current Conditions

Electricity was not fully restored to Puerto Rican residents until August 2018, almost a year after Hurricane Maria.19 Much of the repair work was makeshift, meant to provide only temporary relief while longer-term improvements were under development. For example, in the town of Cain Alto, power cables were woven through trees in violation of basic safety code.20 It is clear upon examining the historical weakness of Puerto Rico’s electricity system that merely repairing and rebuilding to pre-Maria conditions will be deeply unsatisfactory. As the rebuilding process continues,

Puerto Rico must seriously consider deep-reaching policy overhauls and innovative engineering solutions.

Given the reality of severe fiscal limitations, this calls for selective and strategic investment towards reconstructing an electricity grid able to satisfy the critical needs of Puerto Ricans, both in day to day living and in the case of another disaster.

mismanagement, as well as provide much needed capital for new investments.

However, it will be challenging to establish a privatization approach in which private owners could expect a reasonable return on equity.

Investors will be taking over poorly maintained assets that PREPA has been operating at a loss. Further-

It is clear upon examining the historical weakness of Puerto Rico’s electricity system that merely repairing and rebuilding to pre-Maria conditions will be deeply unsatisfactory.

Operational Landscape

In June 2018, Puerto Rico’s governor signed a bill to partially privatize PREPA’s assets. The initiative aims to sell its power generation units and contract out operation of its transmission and distribution system.21 Government officials have framed the move as an opportunity to diversify energy sources and shift towards microgrids. Privatization offers a chance to correct bureaucratic inefficiencies, corruption, and

more, PREPA forecasts further future declines in energy demand, in addition to its goal of lowering electricity rates.22 To profit, costs would have to be significantly cut by shifting towards cheaper natural gas and renewables, requiring investors to put money into new generation capabilities in an uncertain regulatory and economic environment.23 Additionally, in industries such as utilities services that tend

towards dominance by a single network, lack of competition means that profit-maximizing firms have no market-based incentive to provide cheap, quality services.24 In past experiments with crucial public services, privatization of Puerto Rico’s water and sewage systems and telecommunications industry in the 1990’s only led to further deterioration of water safety, and steadily increasing telephone service prices.25 Whereas in the U.S., limited water privatization has been successful because of the EPA’s ability to monitor and enforce the implementation of contracts, Puerto Rico lacks the same institutional capacity for regulation and oversight.26 Concessions and contracts to the private sector will not be a cure-all for currently existing structural weaknesses.

The underlying concern is that relinquishing control of the electricity system to foreign private companies will only further diminish the input Puerto Rican citizens have over issues critically impacting their livelihood. San Juan Mayor Carmen Yulín Cruz cautioned that “the privatization of PREPA puts the economic development of the country in private hands.”27 The central challenge for regulatory institutions such as the Puerto Rican Energy Commission (PERC) will be to ensure that the needs of Puerto Ricans remain at the forefront in the face of possibly conflicting investor interests. PERC should prioritize transparency throughout the transition, and be proactive in establish-

Coto, “Puerto Rico Gov Signs Bill to Privatize Power Company Assets.”

“Puerto Rico Electric Power Authority: Amended and Restated Fiscal Plan – Draft.”

23 Joffe and Stuart, “To Privatize PREPA, Puerto Rico Needs a Coherent Plan.”

24 Cortina De Cardenas, “Does Private Management…”

25 Newkirk, “The Peril of Privatizing Prepa.”

26 “Privatization of Water Services in the United States: An Assessment of Issues and Experience.”

27 Newkirk, “The Peril of Privatizing Prepa.”

21 22

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ing clear, detailed guidelines. Longterm agreements which include mandatory capital investments to update and improve infrastructure would be beneficial for both prospective investors and concerned residents. For example, Brazil’s ongoing power sector reforms have utilized investment obligations that include clearly defined amounts of annual investment, procedures for submission, approval and verification of programs. Additionally, after realizing investments yielding the most social benefits might be underprioritized by more profitable opportunities, Brazil established a public benefits fund to complement the utilities regulated investments.28

Improvements

Puerto Rico should have a modern, intelligent infrastructure that is affordable, reliable, and resilient, fueled by a diverse portfolio of centralized and distributed energy resources. This section will focus on how modern grid technology and distributed energy resources can directly and indirectly increase affordability, reliability and resiliency.

Segmentation

A key feature of disaster resiliency is the ability of individual segments of the system to function independently of one another, so that failures in certain sections does not adversely affect others. In order for each segment to be fully independent, each area must have enough individual generation capacity to match its energy demand.29 In the long term, generation centers need

minals and distribution infrastructure.30 Barring a waiver of the Jones Act that would enable the import of domestic LNG from the U.S., higher-priced gas imported from elsewhere in the Caribbean would automatically raise the cost of production by 2-3 cents/kWh.31 Hawaii, who shares Puerto Rico’s lack of native fossil fuel reserves Renewable Energy Although natural gas would and high utility prices, as well as an provide a cleaner, cheaper source abundant potential for renewable to be relocated closer to population centers. As this would involve either converting current generation systems or building new ones, relocation goals run parallel to the previously cited need to shift away from current fuel oil dependency.

It would also reduce long-distance transmission costs.

Puerto Rico should have a modern, intelligent infrastructure that is affordable, reliable, and resilient, fueled by a diverse portfolio of centralized and distributed energy resources. of electricity compared to fuel oil, caution should be taken that investment in costly Liquified Natural Gas (LNG) infrastructure does not crowd out investments in renewables. In 2012, the southern Costa Sur station was converted from fuel oil generation to be compatible with natural gas generation. LNG imports increased, but additional increases beyond that would require costly new LNG-specific import ter-

Jannuzzi, “Power Sector Reforms in Brazil.”

“Energy Resilience Solutions for the Puerto Rico Grid.”

30 “Puerto Rico - Territory Energy Profile Analysis.”

31 Sanzillo and Kunkel, “IEEFA Letter to Federal Oversight and Management Board.”

32 “State of Hawaii – Energy Policy Directives.”

28 29

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energy generation, has officially disavowed natural gas, fearful of “remaining locked in obsolete infrastructure”.32 Instead, the Hawaii Department of Energy has embarked on an ambitious program to shift to 100% renewable generation by 2045, as well as incorporate more smart grid technology. It has made impressive progress in less than a decade, achieving over 25% generation from renewables in 2018.

Perhaps recognizing similar problems and solutions, Puerto Rico recently increased its renewable portfolio standard to 50% by 2040 and 100% by 2050.33 The indebted government should explore creative models beyond privatization to incentivize investment towards this goal. For example, substantial portion of Hawaii’s renewables growth has been through consumer-side investments in solar PV generation at the scale of the individual household, which almost doubled between 2014 and 2019.34 Microgrids

Although residents had independently been installing solar panels in response to costly and unreliable electricity for years, it was only after Maria that the Puerto Rico Energy Commission adopted a regulation allowing homes and small businesses to build microgrids and networks to share that power with neighbors.35 Microgrids allow a community or an individual building to operate in isolation for an extended period of time using a combination of solar, battery storage, and backup generation. If just a small portion of

houses within a neighborhood had this capability, life-saving medicine could be refrigerated, and medical devices powered in the case of another disaster. Strategic government subsidies for a critical percentage of residences in a certain area would be a valuable and cost-effective initiative.36 Compared to Hawaii’s consumer-led investments, Puerto Rico’s substantially lower median household income might necessitate steeper rates of subsidy. Nonetheless, there remain numerous points for private involvement at different price levels, through the initial installment of individual generation, and a credit buyback system for customers to sell excess electricity back to the utility, similar to Hawaii’s “Smart Export” System.37 Where financially feasible, grid-tied microgrids should be used for critical infrastructure such as hospitals, emergency shelters, communications systems, water treatment plants, and industrial centers.

Remote microgrids, those that are entirely separate from the centralized grid, may be considered for remote communities for whom it may take months to return service to af-

ter a disaster. Smart grids and advanced feedback systems in tandem with local energy generation also creates a flexible supply source capable of rapidly ramping up/down in response to shifting demand.

Thus, in addition to increasing resiliency, distributed generation facilitates cost savings through demand response.

Conclusion

Grid modernization can facilitate a diversification of fuel sources, reducing overdependence on imported petroleum. This works in parallel with more distributed generation, mitigating the vulnerability of the overall system to localized failure points. The system must move towards diversification of generation location as well as diversification of generation method. Among competing interests of government officials, stakeholders, and private investors, it is crucial to never lose sight of the ultimate goal of empowering individual Puerto Rican citizens through reliable and dependent electricity.

Iulia Gheorghiu, “Puerto Rico passes 100% renewable energy bill as it aims for storm resilience.”

“Hawaii State Profile and Energy Estimates.”

35 Greenemeier and Dzierzak, “As Electricity Returns to Puerto Rico, Its People Want More Power - Scientific American.”

36 Greenemeier and Dzierzak.

37 “State of Hawaii – Energy Policy Directives.”

33 34

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“Privatization of Water Services in the United States: An Assessment of Issues and Experience.” National Research Council, 2002. https://doi.org/10.17226/10135.

“Puerto Rico - Territory Energy Profile Analysis.” US Energy Information Administration, 2019. https://www.eia.gov/ state/analysis.php?sid=RQ. “Puerto Rico Electric Power Authority: Amended and Restated Fiscal Plan – Draft,” 2018. http://www.aafaf.pr.gov/assets/ prepa-fiscal-plan-(v_april)-4.5.18.pdf.

“Puerto Rico Quick Facts.” U.S. Census Bureau, 2019. https://www.census.gov/quickfacts/PR Sanzillo, Tom, and Cathy Kunkel. “IEEFA Letter to Federal Oversight and Management Board,” 2018. http://ieefa.org/ wp-content/uploads/2018/09/IEEFA-Letter-to-Federal-Oversight-and-Management-Board_9.17.18.pdf.

“State of Hawaii – Energy Policy Directives.” Hawaii State Energy office, 2020. https://energy.hawaii.gov/energypolicy.

Weissenstein, Michael. “Puerto Rico Grid ‘teetering’ despite $3.8 Billion Repair Job.” Chicago Tribune, May 30, 2018. https://www.chicagotribune.com/nation-world/ct-puerto-rico-electricity-grid-20180530-story.html.

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Selected Paper

The Effects of a Proportional Wealth Tax to Subsidize College Education: A General Equilibrium Model CLAIRE SKINNER

Rice University 2020 Abstract

This project models a system where a wealth tax is used to subsidize two years of college education and analyzes the resulting effects on economic aggregates such as welfare, investment in education, consumption, and human capital.

I first created a model that given a cost of education 1) captures an agent’s tradeoff between consumption and investment in education, and 2) outputs the optimal values of savings and investment over the agent’s life. I then used this model to find the cost of education when the entire population invests two years in college education. Given this optimal education cost, I found the wealth tax rate that would result in a government budget deficit of zero.

Next, I used this partial equilibrium model to create a general equilibrium model in order to calculate the optimal interest rate that results in an aggregate savings of zero (savings equals consumption). Finally,

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I plugged the optimal interest rate back into the partial equilibrium model to calculate economic aggregates. I found that both aggregate welfare and aggregate consumption decreased when the wealth tax was implemented. This led to the conclusion that, despite the fact aggregate human capital did increase, implementing a wealth tax to subsidize college education is not beneficial, as people are overall worse off. However, changes to the model, such as reconsidering how to model utility and/or human capital accumulation and increasing the size of the state space (points at which the models were evaluated), could change this conclusion.

Introduction

In the lead up to the 2020 presidential election, many candidates have discussed plans in which the government would provide some level of free college education. In particular, Elizabeth Warren has

proposed funding her plan to pay for college by implementing a wealth tax. According to a CNBC article, her entire education plan calls for $800 billion in funding to make public college education tuition free, abolish student debt, and create a universal childcare program. “Her wealth tax, which rises to 3% on net worth of $1 billion and above, will raise $2.75 trillion over 10 years,” so, in theory, there is plenty of revenue to cover the costs (Dzhanova 2019). How would using a wealth tax to make college free affect individuals and the economy?

This project seeks to model a system where a wealth tax can be used to subsidize college education and to analyze the resulting effects on economic aggregates such as welfare, investment in education,

to be zero, I first needed to create a model to calculate the wealth tax rate necessary to subsidize two years of college education. I assumed the average American completes two years of college because according to a 2015 report by the Census Bureau, 42.3% of people over the age of 25 have at least an Associate’s degree (US Census Bureau 2016).

The first step was modeling an agent’s tradeoff between savings for the next period and investment in human capital. I used the following Bellman equation:

return on savings (assume 4% for now), and e is the cost of investing in it (see Table 1 for additional parameter values). In addition to survival probabilities, I calculated the population weight of each age using the following equation, where  is the growth rate:

I then normalized these population weights by dividing each one by the sum of all the weights (see Table 2 for survival probabilities and corresponding normalized population weights).

Next, I calculated the resulting Where V(at ,ht ) is the value aggregate investment for each cost function, a(t+1) is savings for the next of education. I discretized human

This project seeks to model a system where a wealth tax can be used to subsidize college education and to analyze the resulting effects on economic aggregates such as welfare, investment in education, consumption, and human capital. consumption, and human capital.

Additionally, it seeks to find a general equilibrium where the aggregate savings is zero (where consumption equals savings) in order to better determine the feasibility of such a system.

period, it is the investment in human capital (i.e. a year of college), ht is the current level of human capital, A and affect how human capital changes, ct is consumption, u(ct) is utility, is a utility parameter, s(t+1) is the probability of surviving to the next period, represents how much the agent discounts the next periModel In order to find the general od, V(a(t+1),h(t+1)) is the continuation equilibrium interest rate that causes value (the agent’s value from the aggregate savings of the economy next period), w is the wage, R is the

capital as ten points from 1 to 10 in log space, initial savings as eleven points from 0.01 to 10 in log space, and cost of education as six points from 0.1 to 0.7 in linear space. For each cost, I calculated the optimal savings and optimal investment in education for every year of an agent’s life, i.e. the optimal savings and investment profiles. This was done by finding the savings and investment values over the agent’s life

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that maximize the value function of the above Bellman equation for every combination of savings and human capital level from my discretizations. Then, assuming the initial human capital was 1.0, I interpolated over these values of savings and investment to calculate the optimal savings and investment the agent would choose every year, making sure to update the value function and human capital according to the Bellman equation. Finally, I calculated the aggregate investment in education for each of the six costs of education by summing the product of each normalized population weight and the corresponding optimal level of investment.

When aggregate investment is equal to the sum of the normalized population weights for period 1 and period 2 (0.02784 + 0.02744 = 0.05528), the entire population spends two years in college, so I found the optimal education cost where aggregate investment equals 0.05528 via interpolation.

The next step was to find the wealth tax rate that would clear the government budget constraint over a lifecycle with the optimal cost of education. I defined government expenditure in period t as the product of the normalized population weight, the cost of education, and the level of investment in education.

Thus, government expenditure over the agent’s lifecycle was calculated by taking the sum over all T periods.

I defined government revenue in period t as the product of the max of 0 and savings in period t and the tax rate , and government revenue over a lifecycle was found by taking the sum over all T periods.

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I created a discretization of ten tax rates from 0.001 to 0.1 in linear space. For each tax rate, I found the optimal savings and optimal investment profiles over the agent’s life and calculated government revenue, government expenditure, and the budget deficit. Using interpolation, I then found the tax rate that would result in a balanced budget, i.e. budget deficit = 0.

Next, using the optimal education cost and budget constraint clearing tax rate, I solved for the agent’s new optimal savings and optimal investment profiles. Then I was finally able to calculate aggregate savings, as well as aggregate welfare (the sum over the product of the normalized population weight and the value function in period t), expenditure, revenue, budget deficit, consumption, and human capital.

At this point I had a model to calculate the wealth tax rate necessary to subsidize 2 years of college education, but I had been assuming the interest rate was 4%. This caused the resulting aggregate savings to always be negative, meaning overall the population spends more than they save. This is not an ideal state for an economy.

Therefore, I decided to find the interest rate that would result in an aggregate savings of zero (where consumption equals savings), turning my model into a general equilibrium model. I created a discret-

ization of seven interest rates from 0.07 to 0.1 in linear space. It took some adjusting to find these bounds, as I needed enough points to interpolate over, but I also needed the right range to find where aggregate savings would be zero.

Using my partial equilibrium model, I found aggregate savings for every interest rate in my discretization. Interpolating over these values, I found the interest rate that resulted in zero aggregate savings. I then used my partial equilibrium model again with this optimal interest rate to find aggregate welfare, expenditure, revenue, budget deficit, investment in education, consumption, and human capital, as well as the optimal savings and optimal investment profiles. I calculated these metrics both with no wealth tax and with the budget clearing wealth tax in order to analyze the effect of subsidizing college education with a wealth tax.

Results

The results of using my partial equilibrium model to calculate aggregate savings over my discretization of interest rates can be found in Table 3. Interpolating over these results, I found that the optimal interest rate was 9.63%. Using this interest rate in my partial equilibrium model, the optimal cost of education was 0.442 and the budget clearing wealth tax rate was 5.04%.

Next, I found the optimal savings and investment profiles for an agent both with a wealth tax in place and without (Figures 1 & 2). Optimal savings without a wealth tax was considerably higher than optimal savings with a wealth tax, which I expected (Figure 3). However, I found it interesting that optimal sav-

ings without a wealth tax was never negative. The explanation for this is that an agent who does not have to pay a wealth tax waits until they have enough savings to invest in education. Moreover, they seem to do this in cycles (Figure 4). However, I think the spikes in the graph would likely be eliminated if the state space (discretization) contained more discrete points. The inclusion of a wealth tax causes the agent to invest more in education in earlier periods and less as they age. The agent does go into debt to do this, however, and that debt is not payed off until period 46.

To get a better idea of how the wealth tax affects the population as a whole, I calculated aggregates both with and without a wealth tax in place (Table 4). As a result of the wealth tax, aggregate welfare decreased by 18.07%, aggregate

investment increased by 20.56%, aggregate consumption decreased by 27.59%, and aggregate human capital increased by 4.92%.

Discussion

Since the inclusion of a wealth tax decreased aggregate welfare and consumption, I would argue that using a wealth tax to subsidize college education is, overall, a bad idea.

Human capital did increase because the wealth tax encouraged investing in education earlier in life. This meant the population was more educated overall. However, the resulting increase in welfare was not large enough to overpower the decrease in welfare from having to pay the wealth tax later in life. Additionally, the optimal interest rate was 9.63%, which we have not seen in the United States since 1989 (Macrotrends

2019). With interest rates as low as they are currently, aggregate savings would be negative, another reason this plan would not be beneficial.

With that said, I think some changes could be made to this model that might change the results. It would be interesting to see if increasing or decreasing the desired years of college education or even changing the way human capital accumulates (i.e. making a year in college result in a larger increase human capital) would make this system more feasible. Additionally, different ways of modeling an agent’s utility could also affect the results, as that directly affects welfare. And of course, given the appropriate computing power, increasing the number of points in the state space would improve the quality of the results.

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References

Dzhanova, Yelena. “Elizabeth Warren's education plan would massively increase funding and her wealth tax would pay for it.” CNBC, October 21, 2019. Accessed December 4, 2019. https://www.cnbc.com/2019/10/21/elizabeth-warrenswealth-tax-would-pay-for-massive-education-plan.html.

Jamerson, Joshua. “Warren Would Use Wealth Tax to Fund $800 Billion Education Plan.” The Wall Street Journal, October 21, 2019. Accessed December 4, 2019. https://www.wsj.com/articles/warren-would-use-wealth-tax-to-fund-800-billion-education-plan-11571662800.

Macrotrends. Federal Funds Rate - 62 Year Historical Chart. Accessed December 4, 2019. https://www.macrotrends. net/2015/fed-funds-rate-historical-chart.

NSC Research Center. “Time to Degree - 2016.” NSC Research Center, September 18, 2016. Accessed December 4, 2019. https://nscresearchcenter.org/signaturereport11/.

US Census Bureau. (2016, March 29). Educational Attainment in the United States: 2015, Ryan, Camille L., & Bauman, Kurt, March 29, 2016. Accessed December 4, 2019. https://www.census.gov/library/publications/2016/demo/p20578.html.

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Appendix Ρ

w

Parameter Value 0.96 Table 1. Parameter Values

1.0

0.08

0.9

0.5

0.012

Period

1

2

3

4

5

6

7

Survival Probability

0.99783

0.99768

0.99756

0.99748

0.99743

0.99738

0.99733

0.02784

0.02744

0.02705

0.02666

0.02628

0.02590

0.02552

Population Weight 8

9

10

11

12

13

14

15

16

0.99726

0.99716

0.99705

0.99692

0.99678

0.99664

0.99648

0.99632

0.99614

0.02515

0.02478

0.02442

0.02405

0.02369

0.02333

0.02297

0.02262

0.02226

17

18

19

20

21

22

23

24

25

0.99593

0.99568

0.99540

0.99508

0.99473

0.99434

0.99394

0.99352

0.99308

0.02191

0.02156

0.02120

0.02085

0.02049

0.02013

0.01978

0.01941

0.01905

26

27

28

29

30

31

32

33

34

0.99260

0.99206

0.99146

0.99077

0.99002

0.98918

0.98830

0.98737

0.98642

0.01869

0.01832

0.01795

0.01757

0.01719

0.01680

0.01641

0.01601

0.01560

35

36

37

38

39

40

41

42

43

0.98541

0.98431

0.98310

0.98183

0.98051

0.97910

0.97754

0.97579

0.97390

0.01519

0.01478

0.01435

0.01393

0.01349

0.01306

0.01261

0.01216

0.01170

44

45

46

47

48

49

50

51

52

0.97186

0.96962

0.96712

0.96433

0.96125

0.95785

0.95411

0.94997

0.94542

0.01124

0.01077

0.01029

0.00980

0.00931

0.00881

0.00831

0.00780

0.00729

53

54

55

56

57

58

59

60

61

0.94045

0.93506

0.92919

0.92292

0.91613

0.90862

0.90031

0.89132

0.88145

0.00677

0.00626

0.00575

0.00524

0.00474

0.00426

0.00379

0.00334

0.00291

62

63

64

65

66

67

68

69

70

0.87116

0.86111

0.85157

0.84206

0.83191

0.82052

0.80757

0.79295

0.77681

0.00250

0.00213

0.00179

0.00149

0.00123

0.00099

0.00079

0.00062

0.00048

71

72

73

74

75

76

77

78

79

0.75934

0.74079

0.72140

0.70139

0.68097

0.66000

0.63902

0.61910

0.59908

0.00036

0.00026

0.00019

0.00013

0.00009

0.00006

0.00004

0.00002

0.00001

80

81

0.57903

0.00000

0.00001 0.00000 Table 2. Survival Probabilities and Normalized Population Weights

85

Interest Rate

8%

8.67%

Aggregate Savings -0.0036 -0.0036 Table 3. Interest Rates and Corresponding Aggregate Savings

9.33%

10%

10.67%

11.33%

12%

-0.0032

-0.0030

0.0295

-0.0030

-0.0027

Figure 1. Optimal savings and investments over time with wealth tax of 5.044%

Figure 2. Optimal savings and investments over time with no wealth tax

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Figure 3. Optimal savings over time with 9.63% interest rate

Figure 4. Optimal investment over time with 9.63% interest rate

Aggregate

Welfare

Expenditure

Revenue

Budget Deficit

No Wealth Tax

42.2283

0.0241

-

-0.0241

5.04% Wealth Tax

34.5974

0.029

0.0195

-0.0095

Percent Change

-18.07%

20.56%

-

-60.3%

Investment

Savings

Consumption

Human Capital

0.0544

6.6144

133.6118

1.1587

0.0656

-0.0032

96.7497

1.2158

-27.59%

4.92%

20.56% -100.04% Table 4. Aggregates With and Without Wealth Tax

87

Selected Paper

An Analysis of Bias in the

US SUPREME COURT SOPHIA G. PEREIRA Rice University 2021

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I – Introduction And Literature Review The United States Court system features an independent judiciary branch that affords the judiciary the ability to avoid many of the external political constraints that prevent the United States executive and legislative branches from enacting policies according to their preferred goals. For example, unlike other government officials, justices make decisions without regard to the impact their decisions may have on their reappointment or electoral accountability, since they are appointed for life and thus are not accountable to the electorate. These structural features of the Supreme Court afford justices the ability to rule along their ideological preferences or policy goals, and not along political agendas or political constraints found in the executive and legislative branches.

Arguably, the most important component of the adjudication pro-

cess is the case outcome. As discussed in Bebchuk’s research on litigation settlement, there are many potential factors that affect the outcome of cases, such as financial constraints, equal access to representation, and legal rules (Bebchuk, 1984, 404).

Other factors, such as the particular legal issue in a case and case precedent, may also affect the direction of the final case decision. However, none of these influences account entirely for the outcome of adjudication processes, especially those in the Supreme Court. While acknowledging that each of these factors influences the outcome of cases to a certain extent, this paper argues that a large explanation of bias in Supreme Court decisions can be attributed to justice ideology and petitioner characteristics. However, the justices can only affect decisions in cases that are petitioned to the court. So, conceivably, petitioner characteristics will also play a large role in decision outcome. This pa-

per will analyze the influence of justices’ ideology and petitioners’ characteristics on Supreme Court cases and their ideological outcomes.

According to the Attitudinal Model of judicial voting, studied in the Segal and Spaeth research experiment, a justice’s ideology is one of the best predictors of case outcomes (Segal and Spaeth 2002).

This research finds that “the Supreme Court decides disputes in light of the facts of the case vis-à-vis the ideological attitudes and values of the justices” (Segal and Spaeth 2002, 86). In addition, the Supreme Court is uniquely likely, compared to lower courts, to have justices influenced by their ideological beliefs because justices are life-tenured, lack political accountability to constituents, and the Supreme Court controls its own docket (Segal and Spaeth 2002, 92).

Perhaps the most convincing evidence that Supreme Court bias is influenced by a justice’s ideology is Segal and Cover’s research on the effect of ideological values on Supreme Court justices’ votes in civil liberties cases from 1953 through 1988 (Segal and Cover, 1989, 561).

This research found that the correlation between the ideological values of the justices and their votes in civil liberties cases is eighty percent, emphasizing the strong statistical relationship between these values (Segal and Cover, 1989, 561). My research will expand on Segal and Cover’s research by analyzing decision bias across all case topics, instead of just civil liberties cases. In addition, my research will expand on Segal and Cover’s study by analyzing the effects of petitioner ideology in addition to justice ideology.

However, it is important to consider a differing perspective on

judicial voting. The Marksist Separation of Powers Model argues that, at times, the Court must consider its collective power above ideological beliefs (Segal and Spaeth 2002, 103). Therefore, to prevent overrides from other branches, the Court must have a unified voting majority, rather than a split ideological vote.

If this theory is correct, then the impact of justice ideology is mitigated.

It is for this reason that this paper will also analyze the impact of petitioner characteristics on Supreme Court bias.

In their research on litigant strategy, Eisenberg and Farber found that litigants are rational actors who understand that taking a case to trial is a costly matter (Eisenberg and Farber, 1997, 1). This research design finds that people are less litigious and less likely to advance a lawsuit where the litigation

may involve high potential costs.

These costs include both monetary and the emotional cost of protracted litigation (Eisenberg and Farber, 1997, 2). In further research on the topic, Eisenberg and Lanvers found that in cases where litigants feel that a court will rule in a specific manner, litigants have an incentive to settle their case pre-trial (Eisenberg and Lanvers, 2009). This research determined that if there were a predetermined signal about the potential outcome or direction of a case, litigants would have an incentive to engage in a pre-trial settlement or drop their case entirely. In fact, research shows that pre-trial settlement is the most common method where plaintiffs reach successful outcomes, even more common than plaintiffs’ successes at trial (Eisenberg and Lanvers, 2009, 112). However, in cases that lack any indica-

The Supreme Court is uniquely likely, compared to lower courts, to have justices influenced by their ideological beliefs because justices are life-tenured, lack political accountability to constituents, and the Supreme Court controls its own docket.

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tion as to the realistic direction of the case, litigants have an incentive to move forward to trial since there is a presumption and expectation that they may receive a more favorable decision.

Considering Eisenberg and Lanvers’ theory about how case settlement rate is affected by litigant strategy, it follows that if litigants develop trial strategy based on justice ideology and the characteristics of the petitioner, this would affect the actual number of cases appealed to the Supreme Court. Should the Court present conservative ideological signals, liberal litigants would have an incentive to settle pre-trial.

Conversely, should the Court present liberal ideological signals, conservative litigants would have an incentive to settle pre-trial.

The “50 Percent Rule” is the prediction that decisions in courts should be about 50 percent in favor of petitioners and 50 percent in favor of respondents, as this will encourage litigants to attend trial (Yates, Brace, and Boyea, 2012, 2).

This theory stems from the idea that litigants consider the perception of the Court’s ideology and make their decisions on whether to pursue their cases in a higher court based on their analysis of their winning probability, with consideration to the Court’s overall ideology. Therefore, theoretically, many of the cases that are appealed to higher courts should have low litigation costs and should be either ideologically vague or appealed because of litigants’ miscalculations of the judge’s ideological views (Eisenberg and Farber, 1997, 4 and McGuire, 2009, 1309).

However, it is important to note that research on the “50 Percent Rule” was developed at the trial level, and therefore has mixed

90

applicability at the appellate level.

In the case of research on the Supreme Court, the “50 Percent Rule” can still be applied from a theoretical perspective. Following this theory, it follows that should litigants perceive an advantage to appealing their case to the Supreme Court because of a bias in the decision direction of the Court, the Court might receive more petitions from candidates with cases that share the Court’s ideological views. Conversely, should litigants become aware of a bias in decision direction against their case type, the Court might receive less petitions from cases in that ideological leaning.

Another factor to note is that in the Supreme Court, justice discretion ultimately determines what cases are chosen to be included in the docket. This theory is known as the “Rule of Four,” and began in 1891 when Congress granted the Supreme Court discretionary appellate jurisdiction (Yingling, 2015, 479). Due to resource constraints, the Supreme Court cannot grant certiorari, which allows a higher court to review the decisions of a lower court, to every case petitioned before the Court. Therefore, the “Rule of Four” guidelines are utilized to determine which cases are granted certiorari. In fact, there are no known examples of justices not following this standard (Yingling, 2015, 481). According to the “Rule of Four,” the Supreme Court will only grant certiorari to a case if at least four justices, of the nine on the Court, vote to grant the case certiorari. Only a small percentage of petitions received by the Supreme Court, approximately one percent, are granted certiorari (Yingling, 2015, 479). In addition, cases are generally granted certiorari if mem-

bers of the Court question the validity of the lower court decision and thus, decide to review the case (McGuire, 2009, 1306). Therefore, although a litigant’s decision to pursue a case is based on a calculation that considers their chance for success, justice ideology, and their case position, ultimately it is the justices that determine which cases are put on the docket. This ties into one of the main questions this research will analyze: whether the Supreme Court is ideologically biased, and if so, what is the cause of this bias?

This paper is structured into four sections. Section I, above, is the Introduction. Section II will discuss the research design and hypothesis for this research, which sets forth five tests. The first test analyzes whether natural courts are ideologically biased based on justice ideology. The second test analyzes the dependent variable in this research design, whether Supreme Court decisions are biased. The third test will examine the effect of justice ideology on bias in Court decisions. The fourth test will analyze the effect of petitioner characteristics on bias in Court decisions. Finally, the last test will analyze the effect of both justice ideology and petitioner characteristics on bias in Court decisions, to account for the effects of each variable while controlling for the effects of either. Following this, Section III will provide analysis of the data on these variables. The final section of this paper will discuss the results of this research design and offer inferences as to the substantive implications of these findings on the Supreme Court.

Ii - Research Design And Hypotheses Are Natural Courts Ideologically Biased Based on the Justices?

To consider the question of whether the Supreme Court justices are ideologically biased, this research will examine the Martin-Quinn Scores, focusing on two variables to measure justice bias, justice ideology (mqScore) and natural courts (naturalCourt) (Martin and Quinn, 2002).

To determine whether there was bias in the natural courts, I will calculate the mean ideology score for all the justices in each natural court. From this mean score, the overall bias of the specific natural court can be assessed. Natural courts with a negative mqScore value indicate liberal leaning Courts, while natural courts with a positive mqScore value indicate conservative leaning Courts.

I expect that each natural court will be biased in a liberal or conservative manner; however, this will differ between natural courts depending on the justices present.

Justices that are extremely biased in one partisan direction will affect the mean score for the natural court more than justices that are relatively ideologically neutral.

Are Supreme Court Decision Directions Biased?

Next, this research will consider the question of whether the Supreme Court decision directions are ideologically biased. To analyze bias in decision outcomes, this research will examine the Spaeth Justice centered data, utilizing the decision direction variable (decisionDirection) for each natural court (Martin, Segal, Ruger, and Benesh, 2017).

The decision direction variable in the Spaeth Data is coded to measure three categories. If the justices rule in a conservative manner, the variable will be coded as 1.

If the justices rule in a liberal manner, the variable will be coded as 2. And, if the partisan ideology of the ruling is unspecifiable, it will be coded as 3. A decision is coded as liberal leaning for issues pertaining to criminal procedure, civil rights, First Amendment, due process, privacy, attorneys, unions, economic activity, judicial power, and federalism. For examples, cases would be coded as liberally-leaning if they ruled in favor of a person accused of a crime, a person denied jury trial, pro-civil liberties, pro-civil rights, pro-juvenile, pro-affirmative action, pro-neutrality in establishment clause cases, pro-female in abortion cases, pro-government, anti-business, pro-consumer, pro-judicial review of administrative action, pro-federal power, and anti-state, among other factors (Martin, Segal, Ruger, and Benesh, 2017). A decision is coded as conservative leaning if the decision is the opposite of a liberally coded decision. Cases are coded as unspecifiable if there is no clear ideological leaning, including cases such as boundary disputes between states, estate issues, and other issues that are not ideologically divisive. However, in this research design, cases coded as unspecifiable will be excluded from data analysis, as they will not contribute to analysis of the Court’s ideological leaning.

To improve the data analysis in this research, I recalibrated the decision direction variable utilizing a new scale. This new variable will be coded as Decision Bias (DecBias) and is calculated through the following formula:

DecBias = decisionDirection -1, if decisionDirection < 2 In this new scale, the DecBias data will fall into the range of 0 to 1, with conservative decisions equal to 0, and the liberal decisions equal to 1. Then, I will take an average of the DecBias scores to see the overall decision direction bias of the Supreme Court. Under this scale, if the Supreme Court was unbiased, the scores would balance out, and the DecBias score should be 0.5.

I hypothesize that overall the Supreme Court decision directions will be biased to some extent leaning in a certain direction; however, whether the Court leans in a liberal or conservative direction will be based on the specific natural court and their case decisions.

Does the Ideological Composition of the Supreme Court Cause Bias in Decision Direction?

If the statistical analysis above indicates that there is an ideological bias based on the justices in each natural court, and that there is in fact a bias in decision directions from the Court, then this research design will analyze the relationship between the average court ideology and average case direction for each natural court.

To analyze the relationship between justice ideology and decision direction, the experiment will analyze the statistical relationship between the independent variable, the mean ideology for each natural court (mqScore), the dependent variable, and the distribution of outcomes in either a conservative or liberal direction for each natural court (DecBias) (Martin, Segal, Ruger, and Benesh, 2017) and (Martin and Quinn, 2002).

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This data considers that there will be a variation in ideology depending on the justices present on the Court at any specific time.

Therefore, this research will account for the composition of the Court by utilizing natural courts as the control variable.

Ultimately, this research design will test whether the mean justice ideology for each natural court predicts the decision direction, and if it does, how well it predicts the decision direction. Considering this, as ideological bias of the natural courts changes the decision direction bias should also change. As such, the alternative hypothesis is as follows: H1: Decisions of the Supreme Court are influenced by the ideological liberalism and conservatism of the Court.

Ultimately, if the “50 Percent” theory is correct, we would expect that 50 percent of decision outcomes are liberal leaning, while the other 50 percent of decision outcomes are conservative leaning.

However, if it is true that justice ideology affects decision direction, then the decision directions should be reflective of this bias.

Does Petitioner Ideology Account for Supreme Court Bias?

In addition to assessing the results of justice ideology, this research will also analyze petitioner characteristics, another variable that could affect bias in Supreme Court decisions. The question this research design will attempt to answer is whether petitioner characteristics are related to a change in Supreme Court decision bias once justice ideology is controlled for.

As described above, “The Rule of Four” contends that because jus-

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tices pick cases for certiorari, this will shape the decision bias. However, the characteristics of the petitioners may play a role in whether a case is granted certiorari. The expectation in this research design is that once justice ideology is controlled for, petitioner characteristics will affect Supreme Court decision bias. As such: H2: Controlling for the ideological preferences of the Court, it is further expected that litigant char-

ers that are businesses; petitioners that are organizations; the federal government as the petitioner; the state government as the petitioner; the local government as the petitioner; the petitioner as a government body that cannot be defined as local, state, or federal; the petitioner as a non-profit organization; and lastly, the petitioner as unspecifiable.

I then coded each of the 78,851 petitioner variables on Microsoft Excel as fitting into one of

Approximately twenty of the natural courts analyzed were liberally biased. Meanwhile, approximately fifteen of the natural courts analyzed were conservatively biased.

Therefore, there seems to be a stronger liberal bias in the Courts as compared to a conservative bias. acteristics will influence the direction of Supreme Court outcomes.

Therefore, an analysis of petitioner characteristics is useful in analyzing the overall bias of the Supreme Court.

To consider the question of whether the characteristics of the petitioners affect bias in decision direction, this research will examine the Spaeth Justice centered data, analyzing the petitioner variable (petitioner) for each natural court (Martin, Segal, Ruger, and Benesh, 2017).

From this, I created nine new variables, which include the following: individual petitioners; petition-

these categories. The petitioner was labeled as 1 if it belonged to a particular category, and 0 if it did not belong to a particular category.

According to the coding scheme, petitioners such as a “person accused of a crime” were classified as an individual petitioner.

Petitioners such as an “airline” company or a “bank” were classified as businesses. Petitioners such as “professional organizations” were classified as organizations. Petitioners such as the “Attorney General,” and the “United States” were classified under the federal government. Petitioners such as a “state department or agency” were classified under the state government. Petitioners such

as the “county government” and “local school district” were classified under the local government.

Petitioners such as “nonprofit organizations” and “religious organizations” were classified as non-profit petitioners. Petitioners that fit under multiple categories, such as “a bankrupt person or business” were classified as unspecifiable. Lastly, petitioners such as “government officials” where their identities were not known, but they were government entities, were classified as unspecifiable government petitioners.

Following this I can measure decision bias as a function of both justice ideology and petitioner characteristics. More specifically, I can test whether petitioner characteristics change the effect of justice ideology on Supreme Court bias.

Iii – Data Analysis Are Natural Courts Ideologically Biased Based on the Justices?

The analysis in this paper presents the mean ideology of the Supreme Court justices, as calculated for each of the 31 natural courts.

This is calculated utilizing data from the Martin-Quinn Scores (Martin and Quinn, 2002). The primary concern in this data is whether the natural courts are ideologically biased or neutral in their partisan nature.

The statistical measure of analyzing the ideological bias of justices is a scatterplot. On Graph 1 (appendix), points on the left side of the scatterplot represent natural courts with more liberal ideologies.

Conversely, points on the right side of the scatterplot represent natural courts with more conservative ideologies.

As indicated by the results in Graph 1, the natural courts are ideologically biased. Most notably, approximately twenty of the natural courts analyzed were liberally biased. Meanwhile, approximately fifteen of the natural courts analyzed were conservatively biased. Therefore, there seems to be a stronger liberal bias in the Courts as compared to a conservative bias.

Are Supreme Court Decision Directions Biased?

The second data analysis in this paper presents the mean decision bias in Supreme Court case direction, as calculated for each of the 31 natural courts.

The statistical measure of analyzing the bias in decision direction is a scatterplot. On Graph 2 (appendix), points on the horizontal axis at value 0.5 represent unbiased cases.

Points less than the 0.5 horizontal axis line represent courts that are conservatively biased. Points greater than the 0.5 horizontal axis line represent courts that are liberally biased.

As indicated by the results in Graph 2, the Supreme Court is biased in its decision directions. Only one natural court lies on the line of no bias. This unbiased natural court, as calculated by averaging the Martin-Quinn ideology scores for each justice in the natural court, is Chief Justice Robert’s third natural court. Every other mean calculation for the decision bias in natural courts is biased in either a conservative or liberal direction.

According to the results, approximately fifteen natural courts have a conservative bias in their decision directions. Conversely, approximately sixteen courts have a liberal bias in their decision direc-

tions as calculated using the Spaeth Justice centered data (Martin, Segal, Ruger, and Benesh, 2017).

Does the Ideological Composition of the Supreme Court Cause Bias in Decision Direction?

Following the conclusion above, that natural courts are influenced by justice ideology and that natural courts are biased in their decision direction, this research will now analyze the extent to which justice ideology affects decision bias.

Preliminary evidence suggests that the Attitudinal Model correctly hypothesized the strong influence of justice ideology on decision bias. As indicated by the results in Graph 3 (appendix), the ideological composition of the Supreme Court strongly affects decision direction. Though there are four outliers, the first, second, third, and fourth Rehnquist natural courts, every other natural court from Vinson through Roberts finds that when the Court has a liberally-leaning ideology score, the decision bias leans liberally, and when the Court has a conservatively-leaning ideology score, the decision bias leans conservatively. In Graph 3, the horizontal axis at 0.5 represents the line of no bias. Everything to the left of this 0.5 line represents liberally biased ideology, while everything to the right of the 0.5 line represents conservatively biased ideology. Throughout the data, we find that there are more cases that represent liberally biased ideology and decision outcomes, as compared to conservatively biased ideology and decision outcomes.

When considering the data as analyzed for each natural court, there is a strong statistical relationship between justice ideology and decision bias. As indicated in Graph

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3, the R2 statistic for this data is approximately 0.3450. From this statistical information, we know that over a third of the variation in bias of the natural courts is accounted for by the ideological bias of the natural courts.

The intercept of Graph 3 represents the point where the ideological score is zero. Decisions at the 0.5 horizontal line represent when the mean Supreme Court ideology score is at zero, and therefore unbiased. However, in this Graph, the intercept is above the 0.5 horizontal decision bias line and is closer to the 0.6 horizontal line. This data shows that the Supreme Court has an overall slight liberal bias and tendency to rule cases in a liberal manner.

The directional hypothesis for this data is that as the Courtâ&#x20AC;&#x2122;s ideology becomes more conservative, liberal bias decreases. The data in Graph 3 confirms this directional hypothesis. The standard error for justice ideology is .028323 (Table 3, appendix). This data has a relatively small standard error, which indicates that the data is not extremely spread out. Because the data is less spread out, it raises the likelihood that the sample mean that is being statistically interpreted is closer to the actual population mean. The t-statistic for justice ideology indicates the probability that the relationship between decision bias and judge ideology could have occurred by chance. Therefore, a t-statistic greater than the threshold value of 1.645 would indicate that the relationship is less likely to have occurred by chance. The t-statistic for this data is approximately -3.94. As the absolute value of the t-statistic increases in value, the probability of the null hypothesis, that the slope is equal to 0, decreases. Therefore,

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this high t-statistic value indicates that there is a small chance that the relationship between these two variables occurred by chance, confirming the hypothesis that there is a relationship between these two variables. The P>|t| value for justice ideology indicates the statistical significance of our data. A P>|t| value less than 0.5 is statistically significant. The P>|t| value in this data set is 0.001, which is less than 0.5, indicating that there is a strong statistical significance in the data set.

Does Petitioner Ideology Account for Supreme Court Bias?

The question this research design will attempt to answer is whether petitioner characteristics are related to a change in Supreme Court decision bias once justice ideology is controlled for.

First, I analyzed whether justice ideology affects the winning party in case outcomes. I utilized the Spaeth Justice centered data partyWinning variable, which analyzes whether the petitioning party emerged as victorious in the case decision (Martin, Segal, Ruger, and Benesh, 2017). I compared this to the Justice ideology variable (mqScore) to determine whether justice ideology relates to the probability of a petitioner winning.

The results in Table 4 (appendix) show that as average Court ideology becomes more conservative, liberal petitioners are less likely to win. This data has a low standard error, .0035078, and is statistically significant as it has a P>|z| score of 0.033.

Next, I analyzed the effect of specific petitioner characteristics on the overall bias in decision directions. The expectation in this

research design is that once justice ideology is controlled for, petitioner characteristics will affect Supreme Court decision bias.

From a natural court level analysis, petitioners that are individuals, businesses, organizations, the federal government, the state government, local government, unspecifiable government, and non-profit organizations all have liberal bias.

This is visible in the coefficient estimates for these variables in Table 5 (appendix), which are all positive.

In addition, the hypothesis, that litigant characteristics will influence the direction of Supreme Court outcomes, was also confirmed by the results. Statistically, bias in the decision direction of the Supreme Court outcomes varies depending on the characteristics of the petitioner. The pseudo R2 statistic for this data, as seen in Table 5, is approximately 0.0231. From this statistical information, we know that over 2.3% of the variation in bias of the natural courts is accounted for by the characteristics of petitioners.

The standard deviation for these nine variables is very small, with the largest standard deviation being .0199051 for unspecifiable government petitioners (Table 5).

The small standard error indicates that the data is not extremely spread out.

The t-statistic indicates the probability that the relationship between the two variables could have occurred by chance. Therefore, a bigger t-value would indicate that the relationship is less likely to have occurred by chance. The t-statistic for the nine petitioner characteristics varies between 5.76 and 20.45 (Table 5). As all of these t-statistics are high values that are above the threshold of 1.645, they indicate

that there is a small chance that the relationship between these two variables occurred by chance, confirming the hypothesis that there is a relationship between petitioner characteristics and bias in Supreme Court decisions.

The P>|t| value indicates the statistical significance of our data. A P>|t| value less than 0.5 is statistically significant. The P>|t| values for all nine of the petitioner characteristics is below 0.5, which indicates that there is strong statistical significance in the data set (Table 5).

In fact, every P>|t| value is 0.000, with the exception of non-profit petitioners for which the P>|t| value is 0.047.

The Effects of Justice Ideology and Petitioner Characteristics on Supreme Court Bias Finally, to analyze the effect of both justice ideology and petitioner characteristics on Supreme Court bias, this research design conducted a multivariate analysis examination of the variables. To do this, a binary logistic regression test was performed on the Stata database.

Following this, I can measure decision bias as a function of both justice ideology and litigant characteristics. More specifically, I can test whether petitioner characteristics change the effect of justice ideology on Supreme Court bias.

The findings of this binary logistic regression test indicate that both petitioner characteristics and justice ideology affect decision direction bias in the Supreme Court (Table 6, appendix). However, these two variables have different effects on bias. Justice ideology has an inverse relationship with bias, which can be seen by its coefficient value of -0.0318115. This value indicates

that as the Supreme Court decision bias becomes more conservative, the liberal bias in justice ideology decreases by the slope value of -0.0318115. Conversely, the positive coefficient values for the different petitioner characteristic types indicates more liberal bias. Therefore, the most liberal bias occurs when the petitioner is the State government as this coefficient value is the largest.

Iv - Summary And Conclusion

The purpose of this research design was to present several questions on variables that could affect judicial outcomes, and to analyze these variables to determine which variable affects judicial outcome most significantly. The findings of this research design are threefold: the decision directions of the court are biased; the ideological composition of the court accounts for approximately 35% of that bias; and that the petitionersâ&#x20AC;&#x2122; characteristics account for approximately 2.3% of that bias.

As hypothesized, statistical evidence from this research design confirms that Supreme Court decisions are biased in one ideological direction. In fact, evidence from this research shows that without even accounting for the effects of ideology, the Supreme Court has a liberally leaning tilt in its decision directions.

The overall liberal bias of the Court was determined by calculating the percentage of decision directions for each ideological direction, and determining which ideological direction was strongest per each natural court.

To determine the variables that contribute to this bias, this research analyzed the effect of justice ideolo-

gy and petitioner characteristics on the overall bias of Supreme Court decisions. The results are as follows: both justice ideology and petitioner characteristics account for bias in the Supreme Court decisions; however, justice ideology affects the bias in decision directions to a much larger degree.

Therefore, as hypothesized, statistical evidence from this research design confirms that the ideological composition of the court affects the bias in decision direction.

Except for the first four Rehnquist courts, every natural court that was ideological biased in one direction, as calculated through the Martin-Quinn ideology scores, was also ideologically biased in decision directions, as calculated through the Spaeth Justice-centered data in that same partisan manner. This finding is consistent with the Attitudinal Model of judicial voting presented at the beginning of this research project, which contends that justice ideology is one of the best predictors of case outcomes. In addition, like the overall liberal bias in the ideology of the court, the intercept of the graph analyzing the ideological composition of the Court confirmed that there is a liberal bias in decision directions as well.

Lastly, as hypothesized, statistical evidence from this research design confirms that petitioner characteristics affect bias in Supreme Court decision directions. There seems to be more liberal bias than conservative bias throughout the different petitioner types. This is consistent with the findings on bias in the Supreme Court, in which the statistical evidence noted that there is an overall liberal bias in the Court (Graph 1).

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In this research design, my interest was to determine whether petitioner characteristics promote liberal outcomes on top of the ideological predisposition of the justices.

Based on the results of this research project, I find that this is true. However, while petitioner characteristics create a liberal bias in the court, justice ideology plays a larger role in determining the case outcome.

While the court has some control over their ideology and in which cases they choose to grant certiorari, they do not have control over the petitioners.

When examining the data accounting for the effect of both independent variables, the pseudo R2 statistic for this data is approximately 0.0185, indicating that 1.8% of bias in decision directions is accounted for by both justice ideology and petitioner characteristics.

Therefore, the amalgamation of justice ideology, petitioner ideology, and decision bias provides a more complete understanding of Supreme Court bias than looking at any single variable alone. However, as a complex variable, Supreme Court bias is not solely shaped by two variables. Rather, this research design can be expanded in future studies by analyzing the effect of other potential independent variables such as the characteristics of the respondents or the composition of the Supreme Court docket.

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Appendix

Table 1: Ideological Composition and Decision Bias Natural Court Level Means

Appendix Continued

Table 2: Mean Ideological Composition and Decision Bias Case Level Analysis

Table 3: Ideological Composition and Decision Bias Natural Court Level Analysis

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Table 4: Justice Ideology and the Effect on the Winning Party

Table 5: Petitioner Characteristics and Decision Bias Linear Analysis

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Table 6: Effects of Justice Ideology and Petitioner Characteristics on Supreme Court Bias

Graph 1: Ideology Ranges in the Supreme Court Natural Courts

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Graph 2: Decision Bias in the Supreme Court Natural Courts

Graph 3: Ideological Composition and Decision Bias of Natural Courts

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