Rethinking Occupational Entry Regulations (OER)

Rethinking Occupational Entry Regulations (OER) Cross-country measurement and firm-level productivity consequences Giuseppe Nicoletti and Christina von Rueden Co-authored by Indre Bambalaite

Web-based launch in cooperation with PIIE, 31 March 2020, OECD OER webpage: https://bit.ly/2w4MR2X

The main rationale for OER is information asymmetry

Q: Is this still a valid rationale in times of digital platforms making information about the quality of services more accessible ?

The share of workers holding an occupational license is high and on the rise United States

European Union

Healthcare practitioners

35.0%

Legal

Union

Licensed

Licensed (Gallup) 2006

30.0%

Education, training, and library Healthcare support

25.0%

Protective service

20.0%

Community and social services

15.0%

Personal care and service

10.0%

Life, physical, and social science

5.0%

Total Architecture and engineering

0.0%

Business and financial operations 0

20

40

60

80

1950s

1970s

1990s

2004

Source: Kleiner and Krueger (2010)

Percentage of workers with occupational license by sector

Research assessing the impacts of OER on economic outcomes – and notably firm-level productivity – have so far been hampered by the absence of comprehensive cross-country data sources measuring the burden imposed by these regulations, especially for personal services.

post-2004

A new cross-country and crossoccupational measure of occupational entry regulations (OER)

The new indicator measures both scope and intensity of entry requirements based on granular information Step 1: Collecting and summing individual information

Step 2: Discounting the overall value

100% OER

• Protected title • Reserved activities

70%

Qualification requirements

Administrative burdens

License

Only the supervisor needs the license

• Reserved activities • Protected title Mobility restrictions

50%

Certification

• Protected title Territorial limits

Limitation to number of authorizations

Mandatory local exam

0%

Mandatory state exam Requirement of compulsory practice

Nationality

Unregulated

The OER covers both advanced and emerging countries for a selected set of occupations Included in empirical analysis

Not included in empirical analysis

Countries

Occupations Non-European United States (state-level) Canada (provincelevel) India (Delhi)

Personal Aesthetician

Nurse

Professional Architect

Baker

Taxi driver

Civil Engineer

Germany

Israel

Driving instructor

Hungary

South Africa

Electrician

European Belgium Spain Finland

Sweden

France

United Kingdom

Italy Portugal Slovenia

Iceland Poland Switzerland

Butcher

Hairdresser Painter-decorator Plumber

Lawyer

Accountant Real-estate agent

Entry requirements vary both across and within countries OECD OER Indicator (0 – absence of regulations, 6 – fully regulated occupation) 5

Q1-Q3

Min

Max

Average

4

Personal services

3 2 1

Professional services

0 Canada

Europe

United States

Main findings 1: • Stringency varies widely across countries and states (even within occupations) • Suggests the need for better integration of these services in all three economic areas

The requirement mix varies, with qualifications taking the lion’s share OECD OER Indicator (0 – absence of regulations, 6 – fully regulated occupation) Personal services

3 2.5

Mobility restrictions Qualification requirements Administrative burdens Average

3.5 3 2.5 2

1.5

1.5

1

1

0.5

0.5

0

0

SWE CHE FIN GBR ESP IND ISR SVN ZAF ITA HUN PRT BEL USA POL CAN FRA DEU ISL AUT

2

CHE FIN SWE USA GBR ESP POL DEU ISR ISL CAN FRA SVN PRT HUN BEL IND AUT ITA ZAF

3.5

Professional services

Main findings 2: • The stringency of regulatory requirements mostly stem from qualification requirements • Professional services tend to be more regulated than personal services

The most restrictive requirements prevail everywhere Percentage of occupations by country group 100%

CAN

Europe

USA

80%

60% 40% 20% 0%

License

Supervisor

Certification

Personal services Personal services

License

Supervisor

Certification

Professional services Professional services

Main findings 3: • Occupational regulations typically take the form of licensing requirements. • More diverse (and less restrictive) arrangements are more common in the EU/Canada than in the US

The productivity and other consequences of ill-designed licensing requirements

Existing evidence points to harmful effects of strict licensing requirements Economic outcome

Empirical evidence

No clear quality improvement

Most research fails to demonstrate quality improvements from higher regulations (Koumenta et al., 2019; Kleiner, 2017)

Weaker business dynamism

Exemption from requirements increased number of market entrants (Rostam Afschar, 2015) and increases churn rates (Canton et al., 2014)

Higher wages and prices

Ample evidence of decline in wages and prices associated with easing of regulations (e.g. Athanassiou et al., 2015; Larsen et al., 2019)

Lower employment

Licensing reduces equilibrium labour supply by 17%-27% (Blair and Chung, 2018) and employment (Koumenta and Humphris, 2015)

Productivity ?

This paper

Strict OER can curb firm-level productivity Firms subject to stricter licensing requirements tend to lag behind those at the global productivity frontier

Average distance to frontier (log productivity)

6

OER affect the ability and incentives of firms to improve productivity by

5 Each dot represents the productivity gap in one country-sector cell (e.g. architectural activities in Spain)

4

• limiting the supply of skilled workers • lowering competitive pressures

3 2 1

0 0

1

2

3

OER stringency

4

5

Estimating the link between OER and productivity We use cross-country firm-level data at the occupation level (11 EU countries, 11 occupations, 2014-16) to look at the productivity consequences of strict OER In our specification (Aghion-Howitt, 1997), productivity is driven by • progress at the global frontier, • catch up by laggards and • other firm-specific factors (age, size), controlling for country-wide shocks and sector characteristics

Q Is productivity growth also affected by OER and if so, how?

Easing OER can boost productivity Productivity gains from reducing regulation from most to least regulated country in each occupation (by firm productivity quartile and size class) p.p.

3

p.p.

5

2.5

4

2

Quartile 4 (high)

3

1.5 2

1 0.5

1

0

0

Quartile 2

Quartile3

Quartile 4 (high)

Mobility restrictions

Qualification requirements

Administrative burden

Main findings: • Bold reforms easing OER could boost productivity growth, especially for the most productive firms • Reforms targeting qualification requirements would be especially productivity-enhancing

Strict OER can stifle job reallocation States with a high share of licensed workers have lower hiring and separation rates Job hire rate (%) United States 2012-18 15

OER hinder the most productive firms from attracting the best workers because

AK

14

WY ND ID UT

13

MTCO

TXOK LA GA TNFL NM MS IN KY AR SD OR WA KS MO AL USA NC MN MI CA DE WV DC ME VANE VT OH IAMD NH IL HI WI NJ PA RI MA NY AZ SC NV

12

11 10

CT

9 8 10

15

Source: Hermansen (2019), based on data from CareerOneStop and BLS Statistics

20

25 30 Licensed employment, %

• Qualification requirements prevent workers from switching professions (or just upskill) • Geographic restrictions prevent workers from moving across firms

Estimating the link between OER and efficient job reallocation A canonical reallocation model (Foster, Decker, Haltiwanger) in which the ability of a firm to grow in size depends on: • past productivity levels, • other firm features (age, size), • unobservable factors affecting the country, sector or period in which the firm operates

Q

Does the presence of strict OER thwart this basic mechanism of efficient firm growth?

We measure the differential employment growth of high relative to low productive firms

Easing OER can improve the ability of firms to attract the workers they need to gain market shares Gains to efficiency of labour reallocation from reducing OER from most to least regulated country in each occupation (difference in employment growth between the average firm at the 1st and 4th productivity quartile) p.p

0.6

p.p.

0.35

By sub-indicator

0.51

0.5 0.4

0.3 0.25

0.32

0.32

0.3

0.2 0.24

0.2

0.15 0.1

0.1 0

By country

0.05 Full Indicator

Administrative Qualification burdens requirements

Mobility restrictions

0

DEU

ITA

SVN HUN FRA

PRT

BEL

ESP

Main findings: • OER reforms could contribute to a better reallocation of resources across firms (e.g. by easing mobility constraints, or allowing to switch more easily between occupations) • Effects are strongest for reforms targeting qualification requirements (for sample based on EU countries)

GBR

FIN

SWE

Some policy implications

Some policy implications International evidence together with our empirical results suggests that there is wide scope for:

 replacing strict licensing systems with lighter schemes based on certification or targeting of supervisors only, where appropriate  making qualification and other requirements proportionate to public policy aims  reducing market segmentation via effective mutual recognition regimes More generally regulations need to be reviewed in the light of changing public interests and technological developments:  The focus of regulations could shift from inputs to outputs, wherever possible

 The increasing role of online consumer reviews and service quality comparison platforms should be considered and encouraged to alleviate information asymmetry concerns Reviewing and streamlining OER could have a number of economic benefits, including help sustain productivity growth of services in the current slowdown

Selected policy reforms (United States) State

Year

Reform

Florida

2011

Reduction/exemption of licensing fees for military veterans and low-income

Michigan

2013-2014

Out of 87 occupations reviewed, 6 became unlicensed

Arizona

2016

Out of 102 occupations reviewed, 5 became unlicensed

2019

First US State to recognize all out-of-state licensures

Nebraska

2016

Exception of license for natural hair braiders

Utah

2017

Reduction of entry regulations for electricians, plumbers and contractors

Wisconsin 2017

Reduction of entry regulations for barbers, cosmetologists, aestheticians, electrologists, and manicurists

In times of #Covid-19, easing the movement of #licensed medical staff becomes even more important

Visit our dedicated webpage to find all background documents, the database and more! https://bit.ly/2w4MR2X Christina.VonRueden@oecd.org Giuseppe.Nicoletti@oecd.org

Indre.Bambalaite@oecd.org

Technical background information

References Aghion P and P. Howitt (1997), “A Schumpeterian Perspective on Growth and Competition. In: Kreps DM, Wallis KF Advances in Economics and Econometrics: Theory and Applications”, Cambridge University Press, Vol. 2, pp. 279-317, https://doi.org/10.1007/978-1-349-26270-0_2.

Athanassiou, E., N. Kanellopoulos, R. Karagiannis and A. Kotsi (2015), “The Effects of Liberalization of Professional Requirements in Greece”, Centre for Planning and Economic Research (KEPE), www.ec.europa.eu/DocsRoom/documents/13363/attachments/1/translations/en/renditions/native.

Blair, P. Q., and B. W. Chung (2018b), “Job Market Signalling through Occupational Licensing”, NBER Working Paper Series, No. 24791, https://doi.org/10.3386/w24791.

Canton et al., 2014) Hermansen, M. (2019), "Occupational licensing and job mobility in the United States", OECD Economics Department Working Papers, No. 1585, OECD Publishing, Paris, https://doi.org/10.1787/4cc19056-en.

Kleiner M. M. and A. B. Krueger (2010), "The Prevalence and Effects of Occupational Licensing," British Journal of Industrial Relations, London School of Economics, Vol. 48(4), pp.676-687, https://doi.org/10.1111/j.1467-8543.2010.00807.x.

Kleiner, M. M. (2017), “The influence of occupational licensing and regulation”, IZA World of Labor, No. 392, https://doi.org/10.15185/izawol.392.

Koumenta M. and A. Humphris (2015), “The Effects of Occupational Licensing on Employment, Skills and Quality: A Case Study of Two Occupations in the UK”. Queen Marry University of London, http://ec.europa.eu/DocsRoom/documents/13364/attachments/1/translations/en/renditions/native.

Koumenta, M., M. Pagliero and D. Rostam-Afschar (2019), “Effects of regulation on service quality. Evidence from six European cases”, European Commission, https://doi.org/10.2873/910094.

Larsen, B., E. Brynjolfsson, C. Farronato and A. Fradkin (2019), “Consumer Protection in an Online World: When Does Occupational Licensing Matter?”.

Rostam-Afschar, D. (2015), “Regulatory Effects of the Amendment to the HwO in 2004 in German Craftsmanship”, European Commission.

Heterogeneity of occupational regulations across United States Panel A: Personal services 4

Q1-Q3

Min

Max

Average

3.5

3 2.5 2

1.5 1

0

CO TX IA ME CT MT OR AK GA WY MA IL WI AL UT ID NH FL IN VA RI MD AZ DE ND VT NE NJ NY WV KY WA OH CA TN NM MI DC SC SD AR NC KS MN OK HI MO LA MS NV PA

0.5

Heterogeneity of occupational regulations across United States Panel B: Professional services 4

Q1-Q3

Min

Max

Average

3.5

3 2.5 2

1.5 1

0

MD MA IA MN NY CT PA GA WV NC IL VT WY NH MS ND TN AR KS NJ MI AK NE ID CO UT OH KY ME AL DC WI DE FL SC OR TX IN MT MO VA HI AZ NM WA SD LA RI OK CA NV

0.5

Average OER levels by occupation in the US 4 3.5

Administrative burdens

Qualification requirements

Mobility restrictions

Average all countries

3 2.5 2 1.5 1

Personal services

Professional services

Real-estate agent

Lawyer

Civil Engineer

Architect

Accountant

Taxi driver

Plumber

Painter-decorator

Hairdresser

Electrician

Driving Instructor

Butcher

Baker

0

Aesthetician

0.5

Estimating the link between OER and productivity Firm-level productivity growth a function of 1.

Productivity growth of firms at the productivity frontier

2.

Distance to the productivity level of frontier firms (the further it is, the faster it should grow)

3.

Characteristics of the firm (e.g. size, age)

4.

Unobservable country-wide shocks and sector characteristics

5.

The level of OER in a given country-sectors cell (average level, by subindicator) ∆đ?‘łđ?‘ˇđ?’‡đ?’”đ?’„đ?’• = đ?œˇđ?&#x;? ∆đ?‘łđ?‘ˇđ?‘łđ?’†đ?’‚đ?’…đ?’†đ?’“ + đ?œˇđ?&#x;? đ?‘Žđ?’‚đ?’‘đ?’‡đ?’”đ?’„đ?’•âˆ’đ?&#x;? + đ?‘żđ?’‡đ?’„đ?’”đ?’• + đ?œˇđ?&#x;“ đ?‘šđ?’†đ?’ˆđ?’–đ?’?đ?’‚đ?’•đ?’Šđ?’?đ?’?đ?’„đ?’” + đ?œšđ?’„đ?’• + đ?œšđ?’” + đ?œş đ?’”đ?’•

Labour productivity growth

Growth of global leader

Gap to Age, size the global leader

OER Indicator

Fixed effects

Refinements: • Accounting for heterogeneity: non-linearity, productivity quartiles, size classes • Sub-indicators of the OER • National instead of global leader • Sector-time FE, sector-country controls • Reverse causality test

Estimating the link between OER and productivity Firm-level employment growth a function of 1.

2.

3.

4.

Lagged labour productivity of the same firm Characteristics of the firm (e.g. size, age) Unobservable country-sector-time characteristics An interaction of #1 with the level of OER in a given country-sector cell (average level, by subindicator)

Following Decker et al. (2016)

∆đ?‘Źđ?’Žđ?’‘đ?’?đ?’‡đ?’”đ?’„đ?’• = đ?œˇđ?&#x;? đ?‘łđ?‘ˇđ?’‡đ?’”đ?’„đ?’•âˆ’đ?&#x;? + đ?œˇđ?&#x;? đ?‘łđ?‘ˇđ?’‡đ?’”đ?’„đ?’•âˆ’đ?&#x;? ∗ đ?‘šđ?’†đ?’ˆđ?’–đ?’?đ?’‚đ?’•đ?’Šđ?’?đ?’?đ?’„đ?’” + đ?‘żđ?’Šđ?’„đ?’”đ?’• + đ?œšđ?’„đ?’”đ?’• + đ?œş Employment growth

Labour productivity

OER indicator

Age, size Fixed effects

Refinements: • Subindicators of the OER • Including firms transitioning from self-employed to employer status