Practicum Final Report

Gentrification Susceptibility Toolkit

2016

Sean Angst Sandy Lo Edward Muna Difan Xiao

Gentrification Toolkit TABLE OF CONTENTS

Spring 2016

Executive Summary Background & Overview Methodology Analysis Results Neighborhood Case Studies Limitations Conclusion Appendix

The mission of the Housing + Community Investment Department is to create viable urban communities by advocating for safe and livable neighborhoods through the promotion, development and preservation of decent, safe affordable housing and by expanding economic opportunities and public services, principally for lowand moderate income persons.

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EXECUTIVE SUMMARY This report is carried out on behalf of the Housing and Community Investment Department of Los Angeles (HCIDLA) who works to ensure decent housing and economic opportunity for residents of Los Angeles.

Recent HCIDLA efforts’ have been stymied due to decreasing funds for affordable development, rising housing demand, and increases in land value. In addition, the city is experiencing gentrification, or changes in the socioeconomic composition of its low income neighborhoods marked by the arrival of affluent populations and new investment in surrounding markets.

As affluent populations invest in these traditionally distressed neighborhoods, housing prices have risen leading to amplified displacement in many areas throughout the city.

This report explores the gentrification and displacement affecting low-income residents in the City of Los Angeles. These phenomena are often linked and occur in tandem; however, they are analyzed as separate processes in order to identify their unique drivers.

Analyzing gentrification and displacement as distinct enabled the assessment to determine whether these processes had similar geographic distributions. Three major components comprise our study: the creation of indices to rank relative gentrification risk in Los Angeles, an evaluation of displacement risk, and the development of neighborhood case studies.

To create the gentrification susceptibility index, census tracts were sorted into those experiencing gentrification or not in two periods—1990 to 2000 and 2000 to 2012. This categorization was based on whether the tracts were economically vulnerable in 1990 or 2000, and whether they experienced increases in home values and demographic changes over the period of study. Then, regression analysis was utilized to identify the indicators that were most strongly correlated with the occurrence of gentrification. From this analysis, indicators of significance were determined and used to create scoring metrics for the susceptibility index. Next, tracts were evaluated in regards to their vulnerability for the displacement of low-income residents. This was done by assessing housing vulnerability in 1990 and 2000, and whether the tract lost low-income residents over the time period of study. Finally, neighborhood studies are supplied to more closely describe the contextual events that may be shaping gentrification Los Angeles neighborhoods.

This report adopts the research design from Karen Chapple’s Mapping Susceptibility to Gentrification: The Early Warning Toolkit (2009). Based on examination of the data, 53% (375) census tracts out of 700 were identified as moderately susceptible to gentrification. In addition 16% (114) census tracts are have a high degree of susceptibility to gentrification. These areas are concentrated along the eastern portions of the city as well as Downtown Los Angeles and Mid City. Moreover, 296 low to moderate-income census tracts experienced displacement from 1990-2012, and 212 low to moderate-income census tracts currently remain at risk. Finally, landscape analysis of five neighborhood case studies indicate that nuanced differences exist at the neighborhood level regarding both resident characteristics and the effects of gentrification.

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BACKGROUND & OVERVIEW

Current Affordable Housing Assesment

uneven understanding of how serious the problem is or what should be done about it.”

The City of Los Angeles’ Housing and Community Investment Department (HCIDLA) has expressed two Funding Challenges primary goals for the upcoming fiscal year (Housing From 2008 to 2014, the total amount of Affordable and Community Investment Department of the City Housing Trust Funds (AHTF) allocated yearly dropped of Los Angeles, 2015): significantly from $108 million to just $26 million1. Provide decent housing and a suitable living -illustrated in Figure 2. This decline was the result environment to the city’s residents. of the demise of redevelopment agencies (RDA’s), 2. Expand economic opportunities for low- and lack of permanent financial sources at the state and moderate-income individuals. local levels, and shrinking funds from the federal Their strategic plan outlines several key challenges in government (Enterprise Community Partners 2014). achieving these goals that stem from the increasingly high demand for affordable units. In 2010, more than half of renters were considered rent burdened— paying more than 30 percent of income on housing— an increase of more than 31 percent over the past 10 years. The gap between rent and income continues to widen, as shown in Figure 1 (Garcetti, 2015a).

Moreover, one-third of the affordable housing stock is set to expire in the next decade (see Appendix A – Figure 1 for the expiration trend from 2006 - 2011).

Specifically, the two primary sources of federal funding for housing and community investment—the Community Development Block Grant (CDBG) fund and the HOME Investment Partnerships Program— have faced consistent pressure over the past 8 years (The City of Los Angeles Fiscal Budgets, 2008-2016).

As a result, both the CDBG and HOME programs have experienced significant declines in funding from 2008 to 2014 with only slight recoveries in recent years (detailed break down found in Appendix A – Table 1).

As a result, Mayor Eric Garcetti announced a goal of Figure 1: Change in Median Income & Rent, U.S. & L.A. building 10,000 affordable housing units by 2021 to provide relief to the rising demand of available housing stock (Tim L. & Tiffany H., 2014). Experts widely agree that the production and preservation of housing has not kept pace with growing populations, driving up housing costs. Affordable housing advocates have realized the magnitude of this issue as well. Cynthia Strathmann—the Executive Director of Strategic Actions for a Just Economy (SAJE)—explained, “The city understands there is a problem but there is a very Source: Impacts of the Widening Divide: Los Angeles at the Forefront of the Rent Burden Crisis 4

Figure 2: Affordable Housing Funding in Los Angeles (Source: LA Times)

To tackle these challenges, the City is taking measures to ensure stable financial streams and enact legislative enforcements around affordable housing development and preservation. This year, Mayor Garcetti signed an Executive Directive No.13, which directed the Departments of City Planning, Building and Safety, and Housing and Community Investment to ensure that more than 20 percent of housing within departmental programs were set-aside as affordable (Litman, 2015). In addition, AB 2 was passed to establish Community Revitalization and Investment Authorities (CRIAs) throughout the state, which will have powers similar to redevelopment agencies to collect tax increment financing after approval. The funds collected from the value-added tax collection have a mandated 25% affordable housing set aside (Garcetti, 2015b). This tool is still in its infancy and has yet to be used by a municipality in the state due to increased restrictions and the heightened approval process.

than $25,000 annually (Reconnecting America, 2012).

Despite its benefits, transit oriented development has also been linked to increases in housing prices in residential and commercial areas. A survey of current literature on transit oriented development reveals the lack of consensus among scholars, however, findings suggest increases in housing premiums ranging from 6 percent to 45 percent (Wyly & Hammel, 2004).

In addition to increasing transit access, the City of Los Angeles is invested in creating more sustainable communities. The mayor’s office launched the Great Streets Initiative to enhance walkability in Los Angeles and identified 15 streets for revitalization (Listokin & Wyly, 2000). These improvements are often connected with benefits such as reductions in noise and air pollution, congestion, improved aesthetics, livability, and economic activity (Guerrieri et al., 2013).

A study of walkable communities in Washington D.C. found that a 20-point increase in walkability, on a scale of 94, leads to a $301.76/square foot premium in residential rents, and a $81.54/square foot premium in Political Context housing values (Housing and Community Investment Recent programs and initiatives at the city level have Department of the City of Los Angeles, 2013). affected issues surrounding affordable housing and speculation such as transit oriented developments To compliment this effort, in April 2015 the Mayor of (TODs), the Great Streets Initiative, and the Los Angeles revealed a new sustainability plan for the mayor’s long-term sustainability plan. HCIDLA have city. This plan laid out strategies for the sustainable committed their efforts around affordable housing in growth with an emphasis on environmental areas experiencing transit-oriented investments. The stewardship and equity focusing especially on the City of Los Angeles is in the midst of expanding transit areas of housing and transportation (HCIDLA, 2012). throughout the city through the passage of Measure Recognizing the potential impacts of revitalization R, which will add 42 transit stations by the year 2030 on gentrification, the mayor appointed an innovation (Strauss, 2015). New transit stations will create many committee with the responsibility of quantifying benefits for low-income communities. Around 70% of displacement effects from these programs and commuters who use transit in Los Angeles make less developing recommendations for mitigation.

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Figure 3: Causes of Affordable Housing Funds Shortage

Defining Gentrification The term gentrification has been defined in many ways specific to ideas surrounding race, class, and economic development. The most often cited gentrification scholar, Lance Freeman, defines gentrification in two parts. First, the characteristics of neighborhoods with the potential to gentrify are considered such as proximity to the central city, population of low-income households, and disinvestment. Next, the process of gentrification itself is incorporated by measuring the influx of affluence and increases in investment that occur due to the arrival of high-income individuals (Freeman, 2005).

While Freeman does not incorporate displacement specifically, sociologist Ruth Glass takes a more direct approach and choosing to define gentrification as a process by which a neighborhood’s “original working-class occupiers are displaced by an influx of higher-income newcomers” (Semuels, 2015).

More broadly speaking, Glass’ definition refers to a process of neighborhood changes that result from the migration of wealthier residents into poorer neighborhoods and increased economic investment.

Additional resources ranging from academic papers and community organization briefs to governmental reports were further considered to reflect the diverse interpretations of the phenomenon (Phillips, Flores, & Henderson 2014; Dastrup, et al., 2014, Marcuse, 2009; Newman & Wyly 2006). We have chosen to keep the processes of displacement and gentrification separate in our analysis, but ultimately consider both as interdependent forces. Academic scholars continue to debate both the precise meaning and effects of gentrification on society—particularly whether the process harms or benefits the original residents of gentrifying neighborhoods (for a full summary of the critical literature review see Appendix B).

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Our final definition of gentrification leverages the methodology developed by Karen Chapple’s Mapping Susceptibility to Gentrification: The Early Warning Toolkit (2009). This definition incorporates Freeman’s two-step process, but provides additional nuance by examining race, class, and tenure compositions.

Furthermore, it is specifically geared so that it may be used to examine gentrification pressures that lead to susceptibility in the future, rather than solely what has already occurred. First, an area’s initial vulnerability was assessed by considering the proportion of renters, low-income, college-education, and nonwhite residents present. Then, the influx of affluence was measured through changes in educational attainment and income compositions as well as changes in investment proxied through property values.

Gentrification in Los Angeles Gentrification further compounds the issue of affordable housing by increasing rent prices and home values in neighborhoods where housing was previously affordable, placing additional burden on many of the original residents. This phenomenon is especially pertinent given Los Angeles’ transportation goals and HCIDLA’s commitment to areas within close proximity of mass transit, which are especially vulnerable. Gentrification in Los Angeles is among the highest in the nation with 15.1 percent of census tracts gentrifying from 2000 – 2010, up from just 2.9 percent in the previous decade (Reconnecting America, n.d.). Gentrification in the city has been characterized as a “weak-center” pattern due to its divergence from the more common centralized processes experienced in the Northeast and Midwest.

In Los Angeles, gentrification has occurred in various pockets throughout the city without a singular center of outgrowth (Reese, Deverteuil, & Thach, 2010).

Sample Improvements Made to Reseda Great Streets (Source: Great Streets Flickr) The discussion regarding gentrification often focuses around its’ effect on poverty. Proponents argue that gentrification allows for the revitalization of disinvested communities and furthers integration goals. On the other hand, opponents contend that gentrification shifts poverty to other portions of the city and amplify its’ concentration through the displacement of neighborhoods’ most vulnerable residents. As rent prices and home values increase as a result of renewed investments and affluent in-movers, original residents often must also take on additional housing burden. In addition, resident’s right to the city is often invoked as they have spent decades contributing and building their neighborhoods only to be displaced and unable to fully capture the new benefits. It is crucial to consider equity when discussing gentrification.

The areas most heavily impacted by the process are historically communities of color, which have witnessed past and present marginalization.

as renewed interest in “new markets” traditionally excluded by middle-income individuals (Shaw, 2005). Escalating housing prices and the resulting demand shocks drove higher income residents into lower-income neighborhoods that border wealthier areas. Moreover, during city-wide housing booms, neighborhoods with low initial home values experienced larger and faster rates of appreciation.

The increase in demand and appreciation of property has led to higher housing costs resulting in the displacement of original residents and gentrification (Shill & Nathan, 1983). This appreciation of value may be positive for the local community through increased tax revenues and investment, yet it hinges on the ability of residents to remain in the neighborhood and capitalize on new benefits.

Mayor Garcetti Signing the LA Sustainability Plan

The Causes of Gentrification and Effect on Affordable Housing The causes of gentrification have been widely studied, yet continue to be disputed. This is due to the highly localized and variable nature of recent gentrification.

In California, the rise of gentrification may be traced to neo-liberal policies that have emphasized partnerships between local government and private capital spurring market-oriented redevelopment.

The strengthening of ties between lower-income neighborhoods and loosening capital markets attracted a wave of high-risk mortgages as well

Source: Office of the Mayor

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Figure 4: The Process of Gentrification and Displacement

Impact of Gentrification on Renters

The Dynamics of Neighborhood Change

The impact of gentrification on renters can be significant, though this may not always be recognized by residents themselves. The neighborhood of Boyle Heights provides an interesting example of this dichotomy as 75 percent of the neighborhood currently rents their homes compared to 61 percent in the City of Los Angeles at large. Moreover, 51 percent of occupied housing units are currently overcrowded and 40 percent of renter-occupied units are considered severely overcrowded (AvilaHernandez, n.d.). The neighborhood is consistently associated with gentrification, and has experienced rent increases leading to overcrowding and rising displacement pressures in turn. Resident anxiety or satisfaction with their neighborhood, however, is often complicated as a result of the aesthetic improvements that may be facilitated through these changes. In the beginning, residents often view redevelopment, and the accompanying increases in property values and possible influx White-migration, with reserved optimism due to the potential improvements in amenities and services associated. As the process of change continues and destabilizing pressures build, renters become split with some hoping to capture the new benefits and others assuming that incoming resources and institutions are contingent upon their displacement.

The effects of gentrification have been explored to a far lesser extent due to methodological challenges. In recent years, scholarship has begun focus more attention on the underlying mechanisms at work especially in relation to displacement (see Appendix C). While some initial studies discounted the magnitude of displacement, others stressed the need to distinguish between naturally occurring turnover and involuntary migration (Davidson, 2008; Newman & Wyly, 2006; Clark & Ledwith, 2006). More nuanced analysis at both the neighborhood and national level suggests that the displacement of residents is indeed a significant effect of gentrification, especially for a neighborhood’s most vulnerable citizens although they do not always name it as such (Verteuil, 2010; Ellen & O’Regan, 2011; Lester & Hartley, 2013; Sharkey, 2013). Further, discontinuity introduced to traditional neighborhood structures may lead to voluntary moves as well. This is evidenced in the Los Angeles Family and Neighborhood Study, which found that social cohesion acts as a significant predictor of future moves (Formoso et al., 2010). Furthermore, low-income residents undergoing moves, both voluntary and involuntary, are far more likely to end up in isolated neighborhoods of economic and racial concentration (Huynh & Maroko, 2013). Displacement has not been limited to residents alone; evidence of both social service and industry migration resulting from gentrification has been noted as well (Barrett et al., 2010; Lee, 2010).

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A logic model illustrating neighborhood change processes is found in Figure 4. Key drivers range from macro level changes in society and the economy as well as the marginalization of vulnerable communities to neo-liberal that facilitate the process. Once the influx of affluence and demographic change begins, amenities and services within the community shift to meet the emerging needs of new residents accelerating the disorganization of networks and community ties.

As new resources flow into the community, demand and speculation for housing rises causing rent prices and home values to increase sharply. In turn, original residents face heightened housing burden leading to the displacement and relocation previously discussed.

As a result, the residents whom remain are unable to fully capture emerging community benefits due to increased stressors, lack of ownership, and new scarcity of needed services, while those outwardly mobile are simply not around to leverage the renewed investments.

The observed social effects of gentrification have been highly variable dependent upon local context.

A generalized theory of change has been developed that outlines the balance between disorder and stress, and the influx of institutional resources and intergenerational closure. Education presents the clearest example of the dual effects of gentrification.

On the surface, exchanges in social capital and demands for higher quality education may result from the influx of higher income individuals allowing for positive benefits to be secured by original residents.

This may be offset, though, as many in-movers have no children or choose alternatives to public school causing reductions in resources assigned to local schools. Further, the stress associated with increased living expenses and social discontinuity may lead to additional negative effects on educational outcomes (Verteuil, 2010). Similar theories of social change have been applied to public health outcomes as

well, (Lester & Hartley, 2013; Formoso et al., 2010).

Additionally, a study utilizing the exogenous shock of Los Angeles’ Northridge Earthquake in 1994 found that crime increased in the short term as a result of the gentrification that followed—it should be noted that the linkage between crime and neighborhood change is also debated (Huynh & Maroko, 2013; Barrett et al., 2008; Lee, 2010).

Research Questions This analysis focuses on developing a better understanding of the process of gentrification in the City of Los Angeles. Moreover, it seeks to determine the key indicators of gentrification so that susceptibility to the phenomenon may be assessed by neighborhood. Thus, our research aims to answer the following questions: 1. What is the current (and past) state of gentrification and displacement in Los Angeles?

2. What are the most significant indicators of gentrification in Los Angeles? How do these factors vary in influence by geographic location?

3. What is the predicted susceptability of gentrification and vulnerability of displacement in Los Angeles?

4. How are the processes of gentrification and displacement evidenced in the five HCIDLAidentified neighborhoods?

Data Variables were collected for the 702 census tracts comprising the City of Los Angeles. Data from secondary sources included demographics, family composition, housing characteristics, employment, and economic status. This information was collected from the 2010-14 American Community Survey (rolling average stated from hereafter as 2012), and 1990 and 2000 Decennial Census.

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LA Skyline & Traffic (Source: Creative Commons Flickr) Additional data was supplied by HCIDLA on building In addition, each tract’s proximity to low-diversity, quality and housing stock. Shape files for census affluent tracts and previously gentrified tracts was tracts, neighborhood amenities, roads, and natural considered. Economic variables cover employment features were obtained through the L.A. County GIS status, income, commuting behavior, and job density Portal. In addition, 3rd grade reading proficiency rates within a given tract. Low-income households were were gathered from the California Department of designated as those falling below 80% of the citywide Education and information on job density assembled median income (AMI) in the base year. Housing from the Longitudinal Employer Household Dynamics variables include characteristics of the neighborhood (LODES) survey. In order to align census tracts across housing stock such as tenure, total units per years, areal interpolation was used to standardize building, median rent price, median home value, each observation in 2010 census boundaries using construction year, vacancy, cost burden, Systematic evaluation tools provided by the U.S. 2010 Project. Code Enforcement Program (SCEP) eligible, at-risk Monetary data points were each converted into 2012 affordable housing units, reliable information system dollars using CPI-adjusted inflation rates as well. evaluation (RISE) and Ellis Act removals.

Indicators

Neighborhood Case Studies

In an effort to understand the factors shaping gentrification and displacement in Los Angeles, variables were culled from the critical literature review explored previously and expert interviews conducted with local government, developer, community organization, and nonprofit representatives (interview details and protocol found in Appendix D & E).

Through this process, 41 variables were identified to capture neighborhood change and public investment (see Appendix F). These indicators may be thought of as representing four related factors to the processes of gentrification and displacement: amenities, demographics, economics, and housing. Amenities describe a series of variables that denote access or proximity to public investment, parks, public housing, high-quality schools, and rail stations. Demographic variables include commonly documented population, race, age, household composition, and education.

The predictive, quantitative tool utilizes statistical data analysis to assess gentrification and displacement from a top-down approach. To supplement this analysis, neighborhood case studies have been supplied to leverage qualitative and descriptive information not captured in the previous analysis. Research has shown that census-based strategies neglect the distinctly visible changes to the urban landscape produced by changes in the built environment that are inherent to gentrification (Hwang & Sampson, 2014). Moreover, traditional data sources do not usually account for the political and economic forces, such as large-scale private developers, city capital investments, public housing policies, and communitybased organizations that are facilitating or stalling the effects of gentrification (Hwang & Sampson, 2014).

Our five neighborhood case studies aim to provide a unique perspective on gentrification via a deeper discussion of the demographic and historical context.

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Methodology While studies focusing on single neighborhoods provide more detailed evaluation of qualitative changes, they are unable to draw quantitative inferences over time and across neighborhoods.

Conversely, large quantitative studies, which typically rely on census data, face difficulties distinguishing gentrification from other forms of neighborhood change and do not typically discuss the social implications of reinvestment. We attempt to capture these less pronounced cues by exploring the varying degrees of gentrification occurring across different neighborhoods in Los Angeles. The neighborhoods chosen for case studies include Historic South Central, Glassell Park, Jefferson Park, Boyle Heights, and San Pedro.

weighted. Model specification and results are found in Appendix H. Each of these models has specific benefits and reveals different information about the variables influencing gentrification. In order to account for the binary nature of the outcome variable, assigned 0 if the census tract did not gentrify over the period of study and 1 if it underwent gentrification, models used a logit specification when possible.

Moreover, the models were executed in exploratory iterations adding variables one at a time to assess their influence and ensure that multi-collinearity was minimized. This process was further confirmed using the exploratory regression tool in ArcGIS to assess the viability of all 41 variables and their combinations.

Cross-sectional analysis was employed first in order to determine the indicators most strongly correlated to Methodology gentrification in each time period independently. Due This study utilizes a methodology developed by to limitations in data availability for public investment Chapple in Mapping Susceptibility to Gentrification: going back in time, full specification was only possible The Early Warning Toolkit (2009) and Miriam Zuk in for the 2000 to 2012 cross section. As displayed, the Regional Early Warning System for Displacement: variables influencing gentrification and the direction Typologies Final Project Report (2015). For full details of their effects differed greatly for each period. see Appendices F-I. Subsequently, a fixed effect regression was utilized Measuring Gentrification Census tracts were scored as gentrified or not based on a four-step process examining baseline characteristics and changes across the 1990 to 2000 and 2000 to 2012 time periods (see Appendix G). First, tracts were evaluated for being sufficiently populated—more than 500 residents. Second, initial vulnerability was assessed by determining whether the proportion of low income residents, renters, or non-white households for a given tract were more than the city median at baseline, or whether the proportion of college-educated was less than the city median. Third, changes in demographics and influx of affluence were measured through increases in college-educated individuals or median household income as compared to the city median. Fourth, significant increases in housing values were identified by growth in median owner-occupied home values greater than the city median. Census tracts that met the requirements at each stage were qualified as gentrified.

to check the robustness of these models and assess their sensitivity. Fixed effect models represent a valuable method of analysis for non-randomized data available over time. These models remove a portion of the bias present in traditional evaluation allowing for more accurate estimates. This is done by controlling for macro-level changes in each period and using the differences in indicators over time to determine the magnitude of their effects. The sample was set-up as a panel in order to carry this method out; however, to achieve a balanced dataset public investment indicators were unable to be included. While several of the estimated coefficients matched the 2000 to 2012 cross-section, differences in magnitude and significance suggested that the results were unreliable. This stemmed from the fixed effect model’s exclusion of roughly half the observations because their gentrification status remained constant over consecutive periods as well as bias emerging from omitted variables. Ultimately, the model’s benefits were outweighed by its failure to capture the most Next, three sets of regression analysis were performed: recent iteration of gentrification accurately.

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vides local coefficient estimates specific to each census tract, which may then be mapped and assessed visually. The model utilized a linear probability specification and an adaptive kernel type that allowed for the spatial context—the number of neighboring census tracts considered in each local analysis—to adjust according to their relative density. Additionally, geographically weighted regressions help account for spatial autocorrelation—the clustering of similar features in geographic space—which may cause bias in more general, averaged estimates. This is especially pertinent as spatial autocorrelation was detected in the dataset using the Moran’s I statistic. Despite the smaller number of explanatory variables, the GWR Cummings Block, Mariachi Plaza (Source: CCFlickr) model had a relatively similar level of fitness as comAs a result, the 2000 – 2012 cross sectional results pared to the 2000 to 2012 cross-section due to its were selected to construct the gentrification sus- consideration of spatial variation. ceptibility index. This decision reflected the model’s ability to better capture the theory of change around public investment and greater relevance to current drivers. Variables of significance included: proportion of the population identifying as non-White (positive correlation), proportion of households that were single-female headed families (negative correlation), proportion of households renting (positive correlation), proportion of residential buildings built pre-war (positive correlation), proportion of residential units vacant (negative correlation), proximity to previously gentrified tracts (positive correlation), and access to rail stations (positive correlation).

The exploratory regression tool in ArcGIS substantiated these results by confirming that the five variables represented the optimal combination for model fitness. Each variable of significance provided a onepoint indicator used to form the susceptibility index.

Points were distributed in relation to the citywide median and summed. Indicators with a positive sign were scored if the tract’s measure was greater than the city median in 2012, while those with a negative correlation were scored for being less than the citywide statistic. Consequently, the index ranged from 0 to 7 and was split into four categories: no susceptibility (0 points), low susceptibility (1 – 2 points), moderate (3 – 4 points), and high susceptibility (5 – 7 points).

Historic Felix Sign in near Historic South LA (Source: Creative Commons Flickr)

Measuring Displacement Displacement categories were created using a fourstage process dividing census tracts among seven categories (see Appendix I). Tracts were initially screened for having populations greater than 500.

Then, these areas were split into low-income, moderate-income, and exclusionary tracts based on the proportion of households designated as low-income in comparison to the city overall. Low-income tracts were categorized as those with a greater number of Last, geographically weighted regression (GWR) low-income households than the city median, while analysis was executed in order to determine how the exclusionary tracts fell within the lowest 10th percenfive variables of significance varied in influence by tile regarding low-income households or those with geographical location. GWR is useful because it prothe least in the city overall. The remainder of census 12 tracts were regarded as moderate.

Sixth Street Bridge in Boyle Heights (Source: Creative Commons Flickr)

Next, past displacement was assessed by determining whether the tract had lost low-income households over the period of study. Finally, future vulnerability was evaluated based on the number of rail stations, amount of pre-1950 or pre-1970 buildings, employment density, rent increases, and property value growth as compared to the city median in the second year under consideration. These criteria were used to further apportion tracts as low risk, at risk, or undergoing displacement. Low-risk and exclusionary tracts did not show signs of vulnerability or loss of low-income households. At-risk areas were those that met vulnerability requirements without signs of displacement, while those undergoing displacement showed evidence of vulnerability and had experienced the loss of low-income households.

Defining Neighborhood Boundaries Freeman’s definition of gentrification relies on marking the arrival of new, affluent populations to a neighborhood traditionally defined by its lack of investment and high concentration of low-income households. These traits are important for our analysis; however, it is also crucial to acknowledge the subjective nature of neighborhood definition and its potential impact on our analysis. Traditional policy research has relied on census boundaries or politically established borders in order to formulate the neighborhood as a unit of analysis.

Yet, many researchers have noted that there is often a difference between the way governments and institutions define neighborhoods as opposed

to the community (Coulton, 2012). One study of neighborhood perception in Los Angeles shows that populations that are socially marginalized and geographically immobile view their neighborhoods as smaller. In contrast, those living in large census tracts or areas with higher vacancy rates often view their neighborhoods as larger (Pebley & Sastry, 2009).

This variability calls researchers to assess their neighborhood boundaries against community perception via surveying and in-person inspection of neighborhoods. Given our limited capacity, surveying the population was not feasible. To adjust, we modified a mixed methods approach piloted by Weiss et al. (2007) for urban health studies in order to delineate neighborhoods. This method includes: 1) using neighborhood council boundaries, community planning areas, and neighborhood areas defined by the Los Angeles Times to outline the overlapping areas as a starting point for neighborhoods; 2) development of maps using ArcGIS that indicates census block boundaries within these loosely defined neighborhoods; 3) examination of land use plans and census data to identify those census blocks with residential land uses and with high concentrations of renters. Final determination of the boundaries was made based on presence of residents (if boundaries bisect census blocks), homogeneity of income status, and connectivity to other census blocks.

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Analysis Results

Figure 5: Past Gentrification in Los Angeles tracts that gentrified were concentrated in portions Analysis Results of eastern Los Angeles near downtown. The 1990Susceptibility to gentrification and vulnerability to 2000 period of gentrification however was more displacement has increased significantly from the widely distributed over the city with the the 20001990-2000 period to 2000-2012. These phenomena 2012 time period retrenching around the Downtown have not only become more widespread, but also Los Angeles area and into portions of Mid City. more highly concentrated in low-income areas most Notably these areas aligned with areas identified in susceptible to their negative effects. Moreover, the literature and anecdotally with gentrification such susceptibility to gentrification remains high in much as Downtown Los Angeles, Northeast Los Angeles to of South and Eastern Los Angeles. include Silverlake, Echo Park, Los Feliz. There was Past Gentrification in Los Angeles also instances of gentrification during this period Based on our gentrification criteria adapted from the occurring in Westlake and Pico Union Neighborhoods Chapple methodology it is clear that many census that border Downtown Los Angeles. Relative to other tracts have experienced gentrification over the two census tracts that qualify as vulnerable the census periods. During the 1990-2000 period 82 census tracts tracts that crossed over into gentrified experienced experienced gentrification while in the 2000-2012 higher levels of investment (increases in median home period 104 census tracts experienced gentrification value) and demographic change (increases in college of whom 13 census tracts experienced gentrification educated persons and median income). These results in both periods. For both periods census are visually depicted in Figure 5.

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Figure 6: Gentrification Susceptibility in Los Angeles Current Susceptibility Results – Gentrification The results from the regression analysis categorizations may be found in Figure 6 above. Census tracts of high susceptibility are clustered heavily in Eastern Los Angeles around Boyle Heights as well as in Downtown and Historic South Central. This observation matches to the recent efforts focused on revitalizing the “historic core” and “arts district” as well as the river development project. In addition, Jefferson Park and University Park show signs of high susceptibility in conjunction with their proximity to the Expo line. Neighborhoods in East Hollywood, Silver Lake, and Echo Park are also exposed to the phenomenon aligning with current community anxieties. Moreover, the majority of South Los Angeles and Eastern Los Angeles show at least a moderate degree of susceptibility substantiating the worries expressed by residents and community groups through our interview process. It is important to explicate what this index means more deeply. That is, the same factors most strongly correlated with gentrification in the past are heavily present in these communities currently. Often, claims are made that community concerns are overblown, but the illustration Figure 6 shows that these fears align to the pressures already operating in their neighborhoods.

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Table 1: Gentrification Susceptibility in Los Angeles Gentrfication Susceptibility 2010-2014 Index

Census Tracts (Count)

No Susceptibility

5

Low Susceptibility

184

Moderate Susceptibility

375

High Susceptibility

114

Geographically Weighted Regression Results Gentrification Coefficient estimates from the geographically weighted regression analysis were mapped next. Natural breaks in the data were used to assign groupings. This allowed for the choropleth maps to be shaded in seven hues with roughly the same amount of census tract observations in each range.

Figure 7: Proportion non-White The proportion of a census tract’s population identifying as non-white had the strongest correlation to gentrification in the North Eastern portion of Los Angeles as well as Downtown (see Figure 7). These areas have large Hispanic populations and have also been the subject of much attention due to their proximity to the Los Angeles River revitalization, “historic core”, and “arts district” redevelopment efforts. This indicator has little influence on the West-side of the city where the non-white population has continued to shrink in recent years. The effect was positive citywide with areas composed of larger non-White populations experiencing higher likelihoods of gentrification.

Figure 8: Proportion Single Female Head of Household The coefficient estimates related to the proportion of households whom were single-female headed families were largest in magnitude on the East side and Downtown (illustrated in Figure 8). The majority of Los Angeles exhibited a negative correlation to this indicator with greater proportions of single-female families decreasing the likelihood of gentrification.

This may represent the differences in neighborhood poverty level or types of housing stock available to single mothers who are required to balance multiple responsibilities and expenses. Further, the gentrifying class is often childless and therefore requires different sets of amenities and services. As a result, these areas may be less attractive to those individuals. Additionally, the variable had little to no influence throughout the Western portion of Central Los Angeles.

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Figure 9: Proportion of Buildings Pre-War In regards to the proportion of buildings built before 1950, Eastern and Historic South Los Angeles exhibited the largest positive association (evidenced in Figure 9). These are known for their well built single-family homes and traditional architecture that has been attractive in the past to new buyers.

Again, a reversal of signs is noted for the Western portion of the city and Long Beach where the effect is negative most likely due to greater prevalence of new development and updated housing stock.

Figure 10: Proportion of Units Vacant The proportion of units vacant revealed a strong negative impact on a tract’s likelihood to gentrify.

This was especially true in Leimert Park, Jefferson Park, and University Park (see Figure 10). In addition, negative correlations were also noted for Eastern Los Angeles. These neighborhoods represent some of the last areas with significant vacancy rates in Los Angeles, thus it is interesting to note that the effect is noticeable. It may also allude to the higher poverty rates and related negative social impacts that often accompany this occurrence.

17

Figure 11: Proportion of Households Renting The association related to proportion of households renting was positive for the majority of the city (displayed in Figure 11). This influence was most prominent in South Central and Historic South Los Angeles along the Blue rail line. This is important to note considering renters heightened vulnerability to displacement and the additional developments planned along the river in the near future. This indicator was not as influential in North Eastern Los Angeles, however.

Figure 12: Proximity to Previously Gentrified Tracts A census tract’s proximity to rail stations exhibited positive correlations throughout the majority neighborhoods (presented in Figure 12). This was especially pronounced in Hollywood, Silver Lake, and Echo Park where transit orientated development along the red and purple line has increasingly been produced. University Park and Jefferson Park show a strong positive correlation between rail proximity and gentrification as well. This indicator displays notable influence radiating outward North to South from Downtown where the current rail hubs exist.

This is especially pertinent as it relates directly to government intervention.

18

Figure 13: Proximity to Previously Gentrified Tract The last variable examined was proximity to other previously gentrified tracts. Gentrification often spreads gradually over time throughout a neighborhood, which is composed of multiple tracts.

This indicator demonstrated a positive association to gentrification confirming these results in part (exhibited in Figure 13). North East Los Angeles, Central Los Angeles, and Baldwin Hills presented the strongest correlations. Interestingly, this variable was less influential in Hollywood, Silver Lake, and Echo Park where gentrification has been centered in the most recent decade perhaps related to their relatively new emergence. Long Beach was the only community exhibited a negative association for this indicator.

As evidenced by the variation in coefficient magnitudes and signs discussed above, geographically weighted regression analysis proves useful in distinguishing the factors influencing gentrification in a more nuanced way. As the city and community groups attempt to grasp the factors driving gentrification in the future, it is advisable to assess neighborhoods independently to determine the indicators most strongly associated with the process unique to the specific community in question.

19

Figure 14: Displacement Index

Current Vulnerability Results – Displacement The City of Los Angeles underwent significant change in regards to displacement over the two periods of study. The 1990-2000 sample exhibited less than half the number of census tracts undergoing displacement as compared to 2000-2012 for both low- and moderate-income tracts (for reference see Table 2). Furthermore, transitions from low-risk to at-risk and at-risk to undergoing displacement are evident. This was especially true in Venice, Jefferson Park, Hollywood, Echo Park, Silver Lake, Boyle Heights, Historic South Los Angeles, and Glassell Park. While the number of at-risk census tracts appeared to decrease over this time period, this is due to the fact that such large number of these areas experienced decreases in low-income households.

This becomes more apparent when the sharp decline in low-risk tracts is noted as well. Consequently, the displacement of low-income residents became much more widespread throughout the city over this period.

Table 2: Total Census Tracts per Category Period of Study

Low Risk

At Risk

Undergoing Displacement

Low Risk

At Risk

Undergoing Displacement

1990-2000

135

163

66

155

44

24

69

2000-2012

121

110

153

75

19

143

69

20

Low Income

Moderate Income

Advanced Exclusion

Neighborhood Case Studies Neighborhood Case Studies: Landscape Analysis To further bolster our analysis, HCIDLA has identified five neighborhoods that are currently undergoing varying levels of gentrification. Our neighborhood landscape analyses will provide gentrification patterns and trends that will emerge when we examine its demographic make-up, historical context, and recent news of gentrification or anti-gentrification activity. Additionally, it is important to note that because of the City’s large surface area, it would not be wise to produce blanket policies to address gentrification and its effect on affordable housing. Instead, we understand that a majority of the city’s makeup is comprised of neighborhoods and we will use the following five neighborhood’s diverse characteristics to provide a more representative baseline for the City in terms of gentrifying forces present and pushback from the community.

For instance, our baseline analysis tells us that there is much development occurring in Historic South Los Angeles with the multi-million-dollar Reef Mega Development and the planned Sears Town Center Development in Boyle Heights (as seen in Figure 16), that will be the largest development in the City’s history (Avila-Hernandez, n.d.). Both the San Fernando Valley and the San Pedro/Wilmington Area are experiencing revitalization with their respective beautification projects meant to increase the walkability of their downtown core and draw in new businesses and housing development. Lastly, Jefferson Park and Glassell Park are neighborhoods that have seen a recent increase of housing values over the last few years. The new homeowners are usually younger and spill-over from the already-gentrified cities of Highland Park and Silverlake, make Jefferson Park and Glassell Park ripe for continued gentrification.

Figure 15: Neighborhood Boundaries

21

Figure 16 & 17: Renderings of LA Reef Project (Source: LA Curbed)

Historic South Los Angeles (LA)

residents (Los Angeles Times, 2015). Moreover, the median household income in 2008 dollars was Historic South Los Angeles is a small, approximately $30,882 (Los Angeles Times, 2015.); this is considered 2.25-mile area that flanks Downtown Los Angeles to low for both the city and county. Furthermore, renters the northeast, Central-Alameda on the east, South occupied approximately 79.6 percent of the housing Park to the south and Vermont Square, Exposition units in the neighborhood (Los Angeles Times, 2015).

Park and University Park on the west. It is bounded by Washington Boulevard on the north, Central Avenue Within the last few years, Historic South LA has been to the east, East Vernon Avenue on the south, and embroiled in controversy over the planned Reef mega the 110 Harbor Freeway to the west. Historically, the development. The Reef project is a $1.2 billion, 1.66 neighborhood has been known to be demographically million square-foot project that would rise on the site of two parking lots in the heart of Historic South Los high-density with many low-income renters.

Angeles, at the intersection of Washington Boulevard According to the 2000 Census, approximately 49,728 and Broadway Avenue (Wattenhofer, 2015). The people live in the Historic South LA neighborhood, mega development would boast a 208-room hotel averaging about 19,474 people per square mile--one with two condominium high-rises that overlook a of the highest population densities in all of Los Angeles pedestrian shopping center and include 2733 offCounty (Los Angeles Times, 2015). Latinos make up street parking spots. While the Reef project will bring approximately 87.2 percent of the population while about 2,700 temporary construction jobs to the African-Americans make up 10.1 percent. Mexico neighborhood, long-time residents worry about the and El Salvador were the most common place of long term impacts of the development, particularly birth representing 56.3 percent of the foreign-born displacement.

Table 3: Rent-burdened households in proximity to the Reef Development Source: Strategic Actions for a Just Economy (SAJE) Likelihood of Property Value Increase

Reef Tracts in Buffer

All Cost Burdened Renter Households

All People in Cost Burdened Households

Risk Level for Financial Strain and/or Displacement

Total People per Risk Category

Very high

1/4 mile

403

1,294

Very High

1,294

High

1/4- -1/2 mile

976

3,151

High

3,151

Moderate

1/2 -1 mile

3,469

12,799

Moderate

Moderate

1-2 mile

6,172

26,512

Moderate

Total

22

39,311 43, 756

Table 4: Quantitative Table of Historic South Los Angeles Indicator

Historic South Los Angeles Total

Percentage

City of Los Angeles Total

Percentage

Total Population

59,776

1.13%

5,302,920

-

Median Income (Average)

28,205

26.66%

105,795

-

5%

-

28%

-

Tracts Undergoing Gentrification

1

6.67%

104

14.81%

Tracts Undergoing Displacement

5

33.33%

290

42.65%

High-Susceptible Census Tracts

8

53.33%

114

16.76%

Change in % Non-White

-

1.81%

-

-0.19%

Change in % college-educated

-

0.004%

-

-0.01%

Change in % Low-income Residents

-

2.07%

-

-2.61%

Change in % Renters

-

1.31%

5,803

27.25%

14,432

40.97%

427

85.08%

511

76.80%

Educational Attainment: Proportion college or more (Average)

Change in Median Income Change in Median Rent Change in % rent-burdened Change in Home Price

0.68%

27.35%

17.15%

72,291

36.79%

-381

0.09%

Total At-Risk Units (Expiring by 2020)

11

0.08%

14,584

-

Total Ellis Act-Removals (as of 2014)

5

0.70%

717

-

-50,304

-

Change in Units Scoring 6 or Below on RISE

Displacement becomes a pressing issue when 77 percent of people living south of Downtown Los Angeles, like the residents of South Historic LA, are renters (Strathmann, 2015). Not only are there a disproportionate number of renters in Historic South LA, but these renters are living in the most overcrowded neighborhood in all of the United States (Strathmann, 2015). A study, released by Strategic Actions for a Just Economy (SAJE), show that the Reef Project would put nearly 1,300 south historic LA residents at-risk of displacement. Furthermore, there are an additional 43,000 residents who are at moderate-risk of displacement (Table 2). Results from our own quantitative analysis, as seen in Table 3, and the zoomed in susceptibility map for Historic South Los Angeles (Figure 1 in Appendix J) not only corroborate this, but emphasize these neighborhood concerns. Over 50 percent of the South Historic LA census tracts are highly-susceptible to gentrify while regional percentages for change in median rent, change in percentage of rent-burdened, and change in home price, are higher than the overall city medians. Our zoomed-in displacement map (Figure 1 in Appendix J) shows a significant proportion of the neighborhood’s census tracts are low-income and atrisk of displacement as well.

-615

Glassell Park Glassell Park was originally part of the Rancho San Rafael area when attorney Andrew Glassell received part of Rancho San Rafael in 1871 as the result of a lawsuit. The development of Glassell Park officially began in the early 20th century and in 1912, the city of Los Angeles annexed much of the neighborhood to its boundaries today.

Today, the 2.75 square mile, asymmetrically-shaped, neighborhood lies to the East of the 5 Freeway and Los Angeles River and is bisected by the 2 (Glendale) Freeway. According to the 2000 U.S. Census, Glassell Park has a total population of approximately 23,467 and its residents are majority Latino with 66.1 percent of the total population in this demographic category (Los Angeles Times, 2015). Likewise, 49.4 percent of the city’s residents are Mexican and 51.5 percent of the residents are foreign-born, which is considered high for the City (Los Angeles Times Mapping Project, n.d.). Moreover, the median household income is $50,098, which is considered average for the City, but low for the entire County (Los Angeles Times, 2015).

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Table 5: Quantitative Table of Glassell Park Indicator

Glassel Park

City of Los Angeles

Total

Percentage

Total

Percentage

Total Population

30,579

0.58%

5,302,920

-

Median Income (Average)

53,512

50.58%

105,795

-

28%

-

Educational Attainment: Proportion college or more (Average)

30%

Tracts Undergoing Gentrification

1

12.50%

104

14.81%

Tracts Undergoing Displacement

0

0.00%

290

42.65%

High-Susceptible Census Tracts

0

0.00%

114

16.76%

Change in % Non-White

-

-6.73%

-

-0.19%

Change in % college-educated

-

-0.010%

-

-0.01%

Change in % Low-income Residents

-

0.06%

-

-2.61%

Change in % Renters

-

-0.48%

13,602

33.96%

14,432

40.97%

498

72.19%

511

76.80%

-

21.32%

-148,211

79.70%

-381

0.09%

Total At-Risk Units (Expiring by 2020)

0

0.00%

14,584

-

Total Ellis Act-Removals (as of 2014)

2

0.28%

717

-

-50,304

-

Change in Median Income Change in Median Rent Change in % rent-burdened Change in Home Price

Change in Units Scoring 6 or Below on RISE

-117

0.68%

17.15%

In recent years, the neighborhood has been undergoing rapid gentrification as young professionals from the already-gentrified neighborhoods of Los Feliz and Silverlake, move into Glassell Park (White & Donahoo, n.d.), as evidenced in Table 5. Our quantitative results show that there has been a 30.39 percent increase of college-educated residents, much higher as compared to the city during the same period. Likewise, there has been an influx of middle-class families moving into the neighborhood, often attracted by the Craftsman style homes and the relatively low housing prices. Glassell Park is also in close proximity to the Burbank Airport, the L.A. Zoo, Universal Studios, and Pasadena. While our analysis shows that only 12.5 percent of Glassell Park has undergone gentrification, our other indicators help to paint a more complete picture of a changing neighborhood. For instance, the change in percentage of rent-burdened is higher for the neighborhood than for the City. Similarly, this pattern was also observed in the increases of home prices. During our study time period, home prices for Glassell Park increased 79.7 percent versus the City’s 0.09 percent. Finally, the zoomed-in displacement map (Figure 2 in Appendix J) indicates that parts of Glassell Park are low-income and at-risk of displacement.

24

Figure 18 & 19: Park Terrace Project and Jefferson Square Project (Source: Caria Pineda, 2014)

Table 6: Quantitative Table of Jefferson Park Indicator

Jefferson Park

City of Los Angeles

Total

Percentage

Total

Percentage

Total Population

30,850

0.58%

5,302,920

-

Median Income (Average)

37,741

35.67%

105,795

-

Educational Attainment: Proportion college or more (Average)

17.13%

28%

-

Tracts Undergoing Gentrification

1

11.11%

104

14.81%

Tracts Undergoing Displacement

4

44.44%

290

42.65%

High-Susceptible Census Tracts

1

11.11%

114

16.76%

Change in % Non-White

-

-2.14%

-

-0.19%

Change in % college-educated

-

-0.01%

-

-0.01%

Change in % Low-income Residents

-

-2.38%

-

-2.61%

Change in % Renters

-

-1.72%

Change in Median Income

12,753

49.01%

14,432

40.97%

Change in Median Rent

1,248

247.10%

511

76.80%

Change in % rent-burdened Change in Home Price Total At-Risk Units (Expiring by 2020) Total Ellis Act-Removals (as of 2014) Change in Units Scoring 6 or Below on RISE

Jefferson Park Located West of USC, Jefferson Park is encompassed by the 10 Freeway in the north, Exposition Blvd in the south, Crenshaw Blvd in the west and Western Ave in the east. It is known for its ethnic and cultural diversities in the City of Los Angeles (City of Los Angeles, 2015). Additionally, it is designated as a Historic Preservation Overlay Zone (HPOZ) to protect the neighborhood’s architectural and cultural resources by way of “providing review of proposed exterior alterations and additions to historic properties within designated districts” (City of Los Angeles, 2015).

With approximately 23,130 people living in the 1.42-square-mile neighborhood in 2000, Jefferson park is considered to be one of the highest-density neighborhoods in the City. Black and Latino residents comprise the majority of the population. Moreover, the median household income in 2008 was $32,654 (Los Angeles Times, 2015), which is relatively low compared with both the city of Los Angeles and the county. Among all residents, renters reside in roughly 69.5% of the housing units. As a result, approximately one-third of the area is considered low-income as well as at least moderately at-risk of displacement and gentrification, according to Appendix J, Figure 3.

Jefferson Park has faced soaring home prices with the

0.68%

24.53%

17.15%

147,019

71.08%

-381

0.09%

233

1.60%

14,584

-

2

0.28%

717

-

-50,304

-

-302

median home price rising to $450,000, an increase of 40.6% from 2013 to 2014 (Khouri, A., 2014). This spike is largely due to surging house flipping and the establishment of Expo line, which made the neighborhood more accessible to new residents. Two affordable housing projects are also now open and have become models of collaboration between the public and private sectors.

These two projects are the Jefferson Park Terrace Project and Jefferson Square Project. Jefferson Park Terrace, located on the South Western Avenue and 30th Street, is an apartment building with 60 units, which was completed in 2014. Jefferson Square Project is an apartment complex with 40 units and completed in 2013, which is located on West Jefferson Blvd. The two projects are expected to provide new affordable housing units to the Jefferson Park community (Caria Pineda, 2014) and aim to provide low-income families safe, affordable, and quality housing. These endeavors will surely relieve some pressure in the context of high housing prices and housing shortages. Meanwhile, many market rate housing projects are also undergoing in the community. Since 2013, the neighborhood has experienced an “infill boom” ranging from townhomes to apartment buildings (DenverInfill, 2014).

25

Table 6 shows the basic information of Jefferson Park, as well as the changes from 2000-2012. While having the similarly numerical status of susceptibility and gentrification with the city, the median rent in the area has doubled in 14 years, which is more than three times larger than the city level. Meanwhile, changes in the percentage of rent-burdened residents and home prices have increased significantly.

San Pedro Our research area of San Pedro is enclosed to the North by 19th Street, South of Summerland, West of Figure 20. San Pedro Waterfront Projects (Source: The Port of Los Angeles, 2015)

Ports O’ Call Promenade and Parking

Sampson Way & 7th St. Intersection Improvements

Harbor Blvd., and East of Mayler. According to the Los Angeles Times Mapping Project and the 2000 decennial census, San Pedro has a population of 80,065. Specifically, White and Latino people make up the majority of the population representing 44.2 percent and 40.8 percent respectively. Moreover, residents had a median household income of $57,508 in 2008, sitting above the city and county median.

Additionally, 56.1 percent of the neighborhood’s residents are renters.

After decades of developing efforts in San Pedro, the results are not promising. Property values declined from $616,000 in 2006 to $374,000 in 2012 (Zillow, 2015) and the homeless population has continued to rise in recent years (Donna L., 2015). According to a report in 2012 prepared for the Mayor’s Office on social vulnerability, San Pedro has a high proportion of residents who live the poverty line with low levels of education as well (Susanne Moser Research & Consulting, 2015).

Many on-going projects, however, are beginning to revitalize the area such as the Los Angeles Waterfront Project. Residents, developers, consultants and the government are involved to advocate, assess and plan for this project. The L.A. Waterfront Project is expected to become a catalyst for regional development, which includes the AltaSea Marine Research Center and the redevelopment of the Ports O’ Call village as well as the established USS Iowa battleship museum and the Crafted marketplace. The City is also considering building hotels, resorts, family residences, townhomes and condominiums to serve various income levels. Finally, a San Pedro Waterfront Market Feasibility Study has been undertaken to assess how the City can utilize public-owned sites to promote residential and hospitality development.

According to our quantitative table, the San Pedro area has less susceptibility to gentrification compared with other study areas. More than half of the area continues to fall in the low-income bracket leaving them vulnerable to a multitude of issues though, especially as development move in. In addition, roughly half the region is moderately susceptible to gentrification and has experienced increases in the proportion of its’ population whom are non-White and renters.

Town Square at 6th Street 26

Table 7: Quantitative Table of San Pedro Indicator

San Pedro

City of Los Angeles

Total

Percentage

Total

Percentage

Total Population

80,395

1.52%

5,302,920

-

Median Income (Average)

58,434

55.23%

105,795

-

Educational Attainment: Proportion college or more (Average)

24.02%

28%

-

Tracts Undergoing Gentrification

1

4.55%

104

14.81%

Tracts Undergoing Displacement

8

36.36%

290

42.65%

High-Susceptible Census Tracts

0

0.00%

114

16.76%

Change in % Non-White

-

6.41%

-

-0.19%

Change in % college-educated

-

-0.02%

-

-0.01%

Change in % Low-income Residents

-

-1.59%

-

-2.61%

Change in % Renters

-

3.62%

13,303

32.01%

14,432

40.97%

481

63.11%

511

76.80%

Change in Median Income Change in Median Rent Change in % rent-burdened Change in Home Price

0.68%

18.09%

17.15%

127,021

43.61%

-381

0.09%

Total At-Risk Units (Expiring by 2020)

4

0.03%

14,584

-

Total Ellis Act-Removals (as of 2014)

4

0.56%

717

-

-50,304

-

Change in Units Scoring 6 or Below on RISE

-195

Boyle Heights

Among all residents, 75.9 percent were renters and the median age of 25 years old making it one of the The study area for Boyle Heights lies within the youngest neighborhoods within the city. boundaries of the 5 Freeway to the north, East Washington Blvd in the south, South Lorena Street in the Before Boyle Heights became a predominantly Latino east, and Soto Street to the west. According to the neighborhood, Boyle Heights was a Jewish communi2000 decennial census and the Los Angeles Times, ty during the post-World War II period. In the 1950s, Boyle Heights had a population of 92,756 in 2000, it became racially and ethnically heterogeneous. Parwith the Latino population composing a dominant ticularly, collaborations between Jewish and Latino share of residents at 94 percent. As a working-class residents shaped the politics in Boyle Heights during neighborhood (Los Angeles Times, 2015), the medi- this time. Decline in the Jewish population occurred an household income of Boyle Heights was $33,235 in the 1960’s and 1970’s due to suburbanization and in 2008, which was lower than the city and county. the development of freeways as well as redlining according to the sociologist Bruce Phillips (Tobar, 2011).

Figure 21. Proposed sites/ Metro-owned It is noteworthy that the Los Angeles Metro Authority properties - Boyle Heights (Source: Metro 2012) has played an important role in developing affordable housing units in the area. At the end of 2014, Metro started to approve affordable housing projects on Metro-owned properties along the Gold Transit Line and granted Exclusive Negotiated Agreements (ENAs) for Abode Communities, East L.A. Community Corporation (ELACC), Bridge Housing Corporation, and A Community of Friends (ACOF), which “allowed the developers a three-month or 18-month window to conduct intensive community outreach and incorporate feedback into site plans” (Sahra Sulaiman, 2015).

27

The agreement between the Metro and the developers resulted in the following affordable housing projects (Figure 21 displays the map of the proposed sites): 1. Cesar Chavez and Soto Site: developed by Abode Communities, will provide 77 affordable housing units; 2. 1st and Soto Site: developed by Bridge housing and ELACC, will provide 65 affordable housing units; 3. 1st and Lorena: developed by A Community of Friends, will establish 49 affordable housing units and units for the homeless and the disabled veterans; 4. Cesar Chavez and Fickett: unlike the former three projects, this project, developed by McCormack Baron Salazar, was rescinded by Metro for the ENA grant, meaning further developments may take more time 5. 1st and Boyle: developed by McCormack Baron Salazar, has been under construction and will deliver 80 units of affordable housing with around 4,000 square feet floor for commerce (The Metro, 2015) 6. Mariachi Plaza Station: currently pending in the design phase (The Metro, 2015) Besides Metro-related projects, ELACC has been working on a $25-million-dollar affordable housing complex, called Cielito Lindo. This project is a collaboration between ELACC and Union de Vecinos. ELACC, has been accused of developing at the expense of 15 families whom currently live there despite its’ status as a leader in anti-displacement advocacy (Los Angeles Times, 2015). In December 2015, however, renters and the organization came to an agreement, which will guarantee original tenant’s the right to move into the project (David Zahniser, 2015).

According to Table 8, Boyle Heights faces many gentrification pressures, with more than half of the census tracts considered high susceptibility. The overall percentage for the neighborhood is more than three times larger than the City’s. In addition, the increase in median income experienced is lower than the City, while the growth in home prices is substantially larger. As shown in Appendix J Figure 5, the entirety of the study area is comprised of low-income census tracts, the majority of which are at-risk of displacement.

Table 8: Quantitative Table of Boyle Heights Indicator

Boyle Heights

City of Los Angeles

Total

Percentage

Total

Percentage

Total Population

90,898

1.71%

5,302,920

-

Median Income (Average)

32,624

30.84%

105,795

-

Educational Attainment: Proportion college or more (Average)

7.43%

28%

-

Tracts Undergoing Gentrification

4

16.00%

104

14.81%

Tracts Undergoing Displacement

12

48.00%

290

42.65%

High-Susceptible Census Tracts

13

52.00%

114

16.76%

0.05%

-

-0.19%

Change in % college-educated

0.02%

-

-0.01%

Change in % Low-income Residents

-0.28%

-

-2.61%

Change in % Renters

0.57%

Change in % Non-White

Change in Median Income Change in Median Rent

7,248

29.10%

14,432

40.97%

395

69.67%

511

76.80%

Change in % rent-burdened Change in Home Price

0.68%

21.61%

17.15%

73,528

38.50%

-381

0.09%

Total At-Risk Units (Expiring by 2020)

155

1.06%

14,584

-

Total Ellis Act-Removals (as of 2014)

4

0.56%

717

-

-50,304

-

Change in Units Scoring 6 or Below on RISE

28

-1,007

Limitations & Conclusions Limitations This report faces several limitations due to data and time constraints that may be improved upon for future research. First, increased standard errors due to the normalization of census tract boundaries present a risk for bias. Also, access and proximity measures may be over-estimated as they assume the entirety of census tracts are within a given boundary. In future research, this may be remediated using more advanced spatial interpolation techniques. An additional possibility for further iterations may be to use census block groups that are more disaggregated to avoid these issues. Next, the use of the City of Los Angeles rather than the County as a whole creates a relatively small sample size and edge effects for the census tracts with very few neighbors. As a result of this and the non-experimental methods used, it is also impossible to attribute causality. Consequently, this project is able to determine susceptibility given a set of indicators, but not make truly quantitative predictions regarding which neighborhoods are most likely gentrify. It would be advisable to use the entirety of the County of Los Angeles in subsequent research projects to help alleviate some of these issues.

Data constraints also posed an issue regarding private investment information not publicly available. Data was unable to be obtained regarding new commercial and market-rate residential construction as well as specific price increases for land that would have been valuable for analysis. Lacking this data and the visual signs of investment or neighborhood change lead to simplified capture of gentrification that may not capture the full breadth of the process. Furthermore, land use data was not able to be obtained regarding residential, commercial, and special zoning that influence where and how development is able to proceed. In addition our definition of investment relies solely on the measure of median home value. This measure broadly captures speculation as opposed to investment and although some investments like public infrastructure, amenities, and schools are capitalized into the cost of a home, other types of investments like retail development may be left out. A more strict definition of investment that requires both increases in median home value as well as measures that reflect increases in public or private investment would potentially alter the number of census tracts experiencing gentrification. More robust measures of public investment would also be desirable for future research. The terms of public investment and gentrification have a range of definitions, thus it may be interesting to explore how changing the ways these phenomenon are quantified may shift results in future sensitivity analysis. In addition, the ten-year study periods do not allow for nuanced understanding of the smaller changes occurring from year to year, which shape gentrification and displacement. Last, the data supplied by HCIDLA could only be used qualitatively due to its lack of alignment to the years of observation from secondary sources.

Conclusions This project focused on identifying past gentrification, determining the indicators most strongly correlated to the process, and investigating displacement within the City of Los Angeles. These results were used to predict gentrification susceptibility across the city and finally to examine how these effects are seen at the neighborhood level.

Our findings show that 296 low to moderate-income census tracts experienced displacement from 19902012. Moreover by the conclusion of 2012, 212 low- to moderate-income census tracts remained at risk for displacement. Furthre, during the 1990-2012 period 171 census tracts experienced gentrification. Seven primary indicators were revealed to be driving this process. The resulting model found that 53% (375 out of 700) of census tracts within Los Angeles have mild susceptibility to gentrification and that 16% (114 out of 700) census tracts have high susceptibility to gentrification. These areas are concentrated along eastern Los Angeles, Downtown, and Mid City. Finally, by examining certain communities at the neighborhood level nuanced differences in their experiences with development and gentrification were evidenced.

29

Echoing the Mayor’s emphasis on creating sustainable development that equitably distributes costs and benefits, the city must ensure that undue hardship is not placed on existing low-income residents. A course must be charted so that increased investment may be experienced in traditionally marginalized neighborhoods without displacement. This will allow those residents who have spent their lives contributing to these areas to fully benefit from new resources they have been anxiously denied in the past. Furthermore, our methodology’s shortcomings create an impetus for the expansion of data collection in order to solidify a better understanding of gentrification.

To that end our team recommends that HCIDLA consider the following in its work moving forward: 1. Gentrification is occurring in areas with low vacancy rates, high proportions of prewar housing and high proportions of renters. Given that prewar housing lacks density this finding aligns with previous literature arguing that high demand and decreased supply in these areas exacerbate housing speculation. HCIDLA should explore avenues for preserving existing stock and the in-fill development of affordable housing in these areas.

2. Populations such as renters and communities of color often reside in areas with large gentrification risk. Plans to develop in and invest in these areas should consider communities of color as major stakeholders in conversations about neighborhood development.

3. In addition, plans for development should consider the need for increased rental housing as part of project approvals.

4. Influential factors for gentrification differ throughout various areas of the city of Los Angeles, in part because of the city’s multiple socioeconomic centers and degree of sprawl relative to other cities.

Further study should be conducted to identify neighborhood specific indicators of gentrification.

This may help the city craft more effective policies that fit local contexts.

30

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Appendix Appendix A: Affordable Housing and Funding

Figure 1: At-Risk Affordable Units

Table 1: City’s Fiscal Year Budgets, 2008-2016

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Appendix B: Critical Literature Review Author/ Research Question Organization, Year

Definition of Gentrification

Targeted Areas

Methodology

Results/Findings

Allyson Marie Bates, 2012

Vigdor (2001) Smith (1998) Kennedy, Leonard (2001)

Washington, DC, Metropolitan Area

Probit Regression Model

The process of gentrification and displacement can have both positive and negative effects on low-status households in the Washington, D.D. metropolitan area.

Low-status household with no more than a high school diploma have a high probability of being displaced regardless of whether they live in a gentrified or a non-gentrified area.

Whether gentrification and displacement cause low-status households to exit their homes at faster rates depending on whether they live in gentrified versus non- gentrified areas.

Logan, J., The role of rental & Vachon, management agenM., 2008 cies (RMA) in regard to what is been considered as the beginning of gentrification in West Broadway. And the process and impact on rental properties.

Gentrification is a West Broadway part of the larger Neighborhood in process of neighbor- Winnipeg hood renewal, and can be described as a process whereby a low rent neighborhood changes to a high rent neighborhood through redevelopment.

Stakeholder Analysis/ Analysis of Rent Costs/Changes

The average of rent per accommodation type demonstrates that RMAs are playing a large role in the rate of rent increase in the West Broadway.

Tierney, S., & Petty, C., 2015

Gentrification generated sociological and geographical changes as previously disinvested areas become ‘younger, smarter, and richer,’ resulting in the displacement of most (or all) of the original working-class residents (Beauregard, 1990; Freeman & Braconi, 2004).

GIS Analyze variables’ values over time

The full gentrification of Bricktown may ultimately be judged on the eventual density of its residential growth.

While urban renewal and gentrification may engender regional economic benefits, these benefits do not alleviate poverty. Rather, poverty tends to shift to other sections of the city.

Whether gentrification can occur in an adolescent, mid-sized American city with a limited cultural or historical affinity for density--The impacts of the Metropolitan Area Projects (MAPs) on Bricktown and its surrounding metropolitan areas

Oklahoma City

Author/Organization, Year

Research Question

Institute for Children and Poverty, 2006

What are the impacts of gentrification?

Will it create a new influx of homeless families from these neighborhoods?

What changes are occurring there and what, if anything, can be deduced from them?

Portland Bureau of Planning and Sustainability, 2012

Center for Community Innovation at the Institute of Urban and Regional Development, 2009

To create an early warning toolkit to help communities identify whether their neighborhood is susceptible to gentrification as reinvestment occurs

Definition of Gentrification

Targeted Areas

Methodology

Results/Findings

Park Slope in Brooklyn, Central Harlem, East Harlem, West Harlem, and Washington Heights in upper Manhattan

Case Study

Findings confirmed that certain neighborhoods (West Harlem & Washington Heights) were more prone to gentrification/more vulnerable than the other cities.

NYC Department of Homeless Services (DHS)-> partnered with CBOs in six highest-risk neighborhoods to prevent new cases of homelessness

Public goal of imPortland proving neighborhoods for current residents often results in making neighborhoods more attractive, which can lead to rising rents and values and involuntary displacement

Case Study

Policy Strategies: Facilitate equitable revitalization and mitigate harmful effects Tools to access potential harms from future projects

A process of neigh- The Bay Area borhood change that encompasses economic change in the form of increases in both real estate investment and household income, as well as demographic change in the form of increases in educational attainment.

GIS Policy Strategies: Susceptibility Index Housing policies: rent control, preservation of affordable rental units, and rental assistance programs to ease the rent burden.

Value capture policies: from assessment districts to tax increment financing to development impact fees

Author/ Organization, Year

Research Question

Definition of Gentrification

Targeted Areas

Methodology Results/Findings

Grube-Cavers, A., & Patterson, Z., 2015

When the variables within a specified area are growing at an accelerated rate relative to the surrounding area.

Sees gentrification as an event

Canadian urban centers: Montreal, Toronto and Vancouver

Survival Analysis

According to the model, if a subway station is built 550 meters away from a CT which previously had no access to transit, that census tract would be five times more likely to gentrify as a result.

Jed Kolko, 2009

Previously average household income increases with distance from a central business district, however in recent years average household income has increased in downtown areas near central business districts. This paper defines gentrification as that increase in average household income in CBD proximate downtown neighborhoods.

Use Average Neighborhood Job Pay to see if there is a positive direction with average neighborhood income

Found positive relationship between average neighborhood pay and average neighborhood incomes.

Found that this effect reached 2 miles out Tastes or commuting costs may have changed such that people want to live closer to their employment

Difference and Difference Analysis

The findings of this analysis provide two important implications for policy-makers and urban planners. As the economic effects of mega retail-led regeneration schemes have arguably not been definite in terms of actual beneficiaries, it seems that the dimension of their neighborhood effect needs to be emphasized more in practice.

Considering that mega-retail-led regeneration schemes may price out neighborhood residents who cannot afford inflated rents, such schemes’ negative effects on surrounding neighborhoods need to be regarded as an important factor in the implementation process, just as other economic effects are.

Jae How Does Kwang Westfield Lee, 2013 London Shopping Centre Affect Gentrification of Deprived Neighborhoods in White City, London

White City, London

Appendix C: Neighborhood Impacts of Gentrification

Appendix D: Interview Protocol & Guidelines Goals: 1. Gather sector specific perspectives on the state of gentrification and the affordable housing shortage in Los Angeles.

2. Collect stories, examples and illustrations of gentrification and affordable housing efforts and needs.

3. Refine common themes across sectors.

4. Identify helpful tools to help shape HCIDLA deliverable Project Description The mission of the Housing + Community Investment Department is to create viable urban communities by advocating for safe and livable neighborhoods through the promotion, development and preservation of decent, safe affordable housing and by expanding economic opportunities and public services, principally for low- and moderate income persons.

HCIDLA’s Public Policy & Research (PP&R) unit engages in proactive research and analysis to support new policies, legislation and programs. We work to identify funding sources, policy constraints, land use policy tools, and solutions to address affordable housing and neighborhood change issues. Our work is driven by the following core strengths: public policy development, research, data and geospatial analysis, preserving and monitoring of at-risk housing, and federal and state legislation and regulations.

As Los Angeles continues to develop it is important to identify ways to mitigate the displacement of long term residents. The PP&R units is currently interested in exploring policy and land use issues that may require data and geospatial analysis to potentially create new policy proposals to address gentrification and displacement.

Goals: 1. Describe the landscape of gentrification in Los Angeles, identify common and contrasting themes across sectors, develop a tool assessing current and potential need 2. Identify challenges and opportunities in the prevention of displacement and gentrification 3. Identify potential indicators of gentrification

Methods 1. To accomplish the aforementioned goals we will produce the following deliverables.

2. Conduct a literature review on indicators of gentrification supported by scholars 3. Produce case studies on neighborhoods of interest identified by HCIDLA 4. Produce a mapping tool which identifies neighborhoods at risk for gentrification and displacement

Do you have any questions? Great. Also for the purpose of accuracy we would like to record this interview.

Recordings will only be used internally. Is it ok if we record?

Interview Questions Organizational 1. What stance do you or your organization have on neighborhood change and/or gentrification?

2. Do you believe your organization has a role is in process of gentrification—either mitigating, regulating, or encouraging?

3. What approaches, initiatives, programs or methods does your organization utilize to reinvest in distressed neighborhood? How does this relate to gentrification, affordable housing, and displacement?

4. What strategies does your organization employ (or believe would be effective) when providing resources and investment to neighborhoods that have suffered from disinvestment in the past so that original residents may remain and experience the renewed opportunities? In other words, how do we provide investment in a responsible while preventing displacement and allowing neighborhood culture and climate to continue to flourish?

Collaborative 5. How does your organization interact with HCIDLA? How does this relate to their mission of providing affordable housing and preventing displacement—especially within areas of reinvestment and rapid neighborhood change?

6. How is your organization collaborating with other partners in a similar capacity?

Landscape 7. How would you describe the city’s current efforts as related to reinvestment, displacement, and gentrification?

8. Describe the challenges and benefits you see related to gentrification?

9. What factors do you believe contribute to gentrification?

10. What structures in the City of Los Angeles are conducive to assuring neighborhoods undergoing rapid reinvestment and compositional changes continue to preserve the rights of original residents?

11. What structures inhibit the city from providing affordable housing and preventing displacement in the city?

Best Practices and Opportunities 12. What are the gaps in knowledge around the issue of gentrification?

13. What tools would be most useful for your organization in organizing efforts related to gentrification, displacement, and affordable housing?

14. Have you seen any novel approaches or tools produced by other cities, states or organizations related to these issues?

15. Where do you think HCIDLA and the City of Los Angeles should focus its efforts on?

Appendix E: Interviewee Table

Interviewee

Sector

Jan Breidenbach, Adjunct Professor (USC) Esperanza Community Housing CD Tech Pacoima Beautiful East Los Angeles Community Corporation (ELACC) LA Thrives Alliance for Community Transit - Los Angeles (ACT - LA) Tunua Thrash, Local Initiatives Support Corporation (LISC - LA) McCormick Baron Salazar

Academia

Community Based Organization/ Non Profit

Affordable Housing Developer

Appendix F – Regression and Scoring Variables Variables

Description

Indcluded (Y/N)

Proportion Black

Total non-Hispanic Black individuals divided by total population

Y

Proportion Latino

Total Hispanic individuals divided by total population

Y

Proportion Asian Pacific-Islander

Total non-Hispanic Asian and Pacific Islander individuals divided by total population

Y

Proportion Native American

Total non-Hispanic Native American individuals divided by total population

Y

Proportion Other

Total non-Hispanic individuals identifying as Other or more than one race divided by total population

Y

Proportion Non-White

Sum of all race/ethnicity categories except non-Hispanic White divided by total population

Y

Proportion age 65 and older

Total individuals over the age of 65 divided by total population

Y

Population age under 18

Total individuals under the age of 65 divided by total population

N

Proportion college or more educational attainment

Total individuals age 25 and older with 4-year college degree or more divided by total population age 25 and older

N

Proportion of households married couples with children

Total married couple households with children divided by total households

Y

Proportion of households single-female headed with children

Total single-female headed households with children divided by total house- Y holds

Median household income

Median total income of individuals age 15 and older per household regardless of relation

N

Proportion low income households

Households earning below 80% of the City of Los Angeles’ area median income calculated in the base year of analysis (1990 or 2000) Total households earning below 80% of AMI divided by total households

N

Median owner-occupied home price

Median price of single family homes with owner living in the unit

N

Median gross rent

Monthly amount of rent plus the estimated average monthly cost of utilities and fuel

Y

Proportion Renters

Total renter-occupied households divided by total households

Y

Proportion of households with 3 or more cars

Total households with 3 or more cars divided by total households

Y

Proportion unemployed

Total individuals age 16 and older that do not have a job and have actively looked for work in the prior 4 weeks divided by total labor force

Y

Proportion of workers taking public transit

Total workers age 16 and older identifying public transportation as primary commute method divided by total workers age 16 and older

Y

Proportion of buildings with 3 or 4 units

Total buildings with 3 or 4 units for either rent or ownership divided by total residential buildings

Y

Proportion of buildings with 5 or more units

Total buildings with 5 or more units for either rent or ownership divided by total residential buildings

Y

Proportion of units vacant

Total units not occupied either by renters or owners divided by total residen- Y tial units

Proportion pre-war homes

Total buildings constructed prior to 1950 divided by total buildings

Y

Proportion pre-1970 homes

The City of Los Angeles’ Rent Stabilization Ordinance (RSO) covers rental properties constructed before this year Total buildings constructed in before 1970 divided by total buildings

Y

Proportion rent-burdened

Total renter and owner households paying in excess of 30% of income on housing costs divided by total households

Y

Housing + Community Investment Department Los Angeles Dataset Variable

Year

Details

Included in Regression (Y/N)

Total number of SCEP eligible units

2013

N

Total number of RISE units scoring 6 or below

2010 - 2014

Total number of Ellis Act removals Total Number of At-Risk Affordable Housing

2006 - 2014

Systematic Code Enforcement Program (SCEP) requires that multi-family rental properties with two or more occupied units be inspected on a scheduled basis Index that ranks buildings’ code compliance based on various factors, such as number of violations, duration of non-compliance and how far cases advanced up the chain of command before resolution 6 or under considered unacceptable by HCIDLA Conversions from rental units to condominiums Publicly funded affordable housing units either past expiration or undergoing expiration in the next 5 years

2008 - 2020

N

Y N

Additional Sources and GIS Interpolated Variables Variable

Year Source

Details

Included (Y/N)

Job Density

LODES 2003 & 2012

Total jobs divided by total workforce

Y

High Quality Grade School Access

Utilizing 3rd Grade Reading Scores, median proficiency rate determined for City of Los Angeles by dividing students scoring proficient or above by total enrollment Schools exceeding City median considered high quality Buffer of ½-mile drawn around each school meeting high-quality measure, census tracts intersecting this buffer considered having access Spatial join used to count total number of school buffers intersecting each census tract

Y

California Department of Education GIS Interpolation

Access to Parks

Buffer of ½-mile drawn around each park, census tracts intersecting this buffer considered having access Spatial join used to count total number of park buffers intersecting each census tract

Access to Museums and Stadiums

Buffer of ½-mile drawn around each museum and stadium, census tracts intersecting this buffer considered having access Spatial join used to count total number of museum buffers intersecting each census tract

Access to Public Recreation Facilities

Buffer of ½-mile drawn around each public recreational facility, census tracts intersecting this buffer considered having access Spatial join used to count total number of recreation facility buffers intersecting each census tract

Access to Public Libraries

L.A. County Open GIS Portal – Current GIS Interpolation

Buffer of ½-mile drawn around each public library, census tracts intersecting this buffer considered having access Spatial join used to count total number of library buffers intersecting each census tract

Y

Y

Y

Y

Y

Access to Rail Station

Buffer of ½-mile drawn around each rail station, census tracts intersecting this buffer considered having access Spatial join used to count total number of rail station buffers intersecting each census tract

Access to Public Housing

Buffer of ½-mile drawn around each public housing project, census tracts intersecting this buffer considered having access Spatial join used to count total number of public housing buffers intersecting each

Y

Stata utilized to compute distances from each census tract’s centroid to every other census tract centroid Sum function used to count number of census tracts that had gentrified in the previous period falling within a 1-mile radius from the original tract’s centroid

Y

Proximity to previously gentrified tract

Proximity to low-diversity, White dominant tract

Stata utilized to compute distances from each census tract’s centroid to every other census tract centroid Tracts with more than 80% of population identifying as non-Hispanic White considered White-dominant Sum function used to count number of census tracts considered White-dominant falling within a 1-mile radius from the original tract’s centroid

Proximity to high-income dominant tract

Proximity to college-educated dominant tract

1990 & 2000 Decennial Census 2010-14 American Community Survey GIS Interpolation

Stata utilized to compute distances from each census tract’s centroid to every other census tract centroid Tracts with median income in top 20th percentile for City of Los Angeles considered high income-dominant Sum function used to count number of census tracts considered high income-dominant falling within a 1-mile radius from the original tract’s centroid Stata utilized to compute distances from each census tract’s centroid to every other census tract centroid Tracts with more than 80% of population with 4-year college degree or more considered college educated-dominant Sum function used to count number of census tracts considered college educated-dominant falling within a 1-mile radius from the original tract’s centroid

Y

N

Y

Appendix G – Gentrification Categories Gentrifying Census Tracts 1990-2012 In order to identify indicators of gentrification we need to make clear distinctions between census tracts that we identify as gentrified and those that are not. In order for a census tract to be identified as gentrified they need to meet the following baseline criter • • • •

Have at least 500 people in the baseline year Identified as vulnerable in year 1 Experience demographic change Experience significant housing value increase between year 1 and 2

A census tract can be classified as vulnerable if it meets three of four conditions. It must have a percentage of low-income households, renters or nonwhite population greater than the regional median or it must have a college-educated population lower than the regional median.

Demographic change is measured as a growth in the percent of college educated individuals and a growth in the median household income greater than the regional median.

Significant housing value increase measured as growth in owner-occupied home value greater than the regional median.

Appendix H – Model Specifications and Regression Results Gentrified (Pr:1|0)=ß0+ ß1Ai + ß2Di + ß3Ei + ß4Hi + ei •Logit • Gentrified coded 0 for no change and 1 for census tracts that underwent gentrification from 1990 to 2000 or 2000 to 2012 • Ai= amenity variables, Di= demographic variables, Ei= economic variables, and Hi= housing variables Three Sets of Analysis • Fixed Effects and Random Effects utilizing Panel Data • 1990 – 2000 and 2000 – 2012 Cross Sectional Data • Geographically Weighted Regression (Linear Probability Model) Statistically Significant Variables Influencing Gentrification 2000 – 2012 Cross Section • Proportion of non-White residents (+) • Proportion of households renting (+) • Proportion of households single-female headed families (-) • Pre-war housing stock (+) • Vacant Units (-) • Within 1 - mile of previously gentrified tract (+) • Within ¼ - mile of rail station (+) Fixed Effects • Proportion of population non-White (-) • Proportion of households renting (+) • Proportion of buildings built pre-war (+) • Proportion of units vacant (+) • Proportion of population age 65 and older (+) • Proportion of households married couples with children (-) • Proportion of workers taking public transit (+)

Appendix I - Displacement Categories

Appendix J – Zoom-in Maps of Gentrification Susceptibility & Displacement Vulnerability Figure 1: Historic South Los Angeles

Figure 2: Glassel Park

Figure 3: Jefferson Park

Figure 4: San Pedro

Figure 5: Boyle Heights