Big question in this lecture

Stockholm Doctoral Course Program in Economics

Development Economics II

Lecture 4 (2nd half)

Regulations

Masayuki Kudamatsu IIES, Stockholm University

Big question in this lecture

What is the impact

of regulations on

development?

Methodology focus in this lecture

How to identify the impact of policies where randomization is infeasible

• Limitations of cross-country regression

Outline

Entry Regulations

Labor Regulations

1. Entry Regulations

• Djankov, La Porta, Lopez de

Silanes, and Shleifer (2002, QJE) • Precursor to World Bank’s Doing

1-1 Research questions

• What the regulation of entry across countries is like?

1-2 Measuring entry regulations

# of procedures (interactions with

outside entities) required by law to set up a standardized firm:

• industrial or commercial activities • in largest city

1-2 Measuring entry regulations:

descriptive stats

Type of Mean # of

regulations procedures

all 10.48

safety & health 0.34

environment 0.14

taxes 2.04

labor & social security 1.94

“screening” 6.04

1-2 Measuring entry regulations:

descriptive stats (cont.)

• Fewer procedures in richer countries (Table III, Panel B)

Quartile of Mean # of GDP per capita procedures

1st 6.77

2nd 11.10

3rd 12.33

1-3 Estimating Impacts

By using cross-country data, estimate

yc = α + βRc + γ log(

GDPc

POPc

) + εc

• R_c: # of procedures

1-3 Results (Tables IV and V)

More entry regulations • associated w/:

• Less compliance w/ international

quality standards

• More deaths from intenstinal

infections

• _{Larger unofficial economy} • More corruption

• not associated w/ • water pollution

1-3 Interpretations

Public choice theory vindicated? No, because

• Benevolent govt: regulate entry when market failure severe

⇒ Could still end up with worse

outcomes if market failure so severe • Corruption and red-tape can be

1-4 Estimating causes

By using cross-country data, estimate

Rc = α +βXc + γ log(

GDPc

POPc

) + εc

• X_c: measure of how benevolent govt is

• GDP: proxy for severity of market failure

1-4 Results (Tables VII)

More entry regulations associated w/: • Less constrained executive

• Less effective legislature

• More autocratic political institutions • French legal origin

1-4 Interpretations

Public choice theory vindicated? No, because

• Democracy and regulations:

simultaneously determined by, say, history

• More democratic governments: not necessarily better reflect preference of the public

1-5 Taking stock

• Regulations (and other policies): endogenous

⇒ Cross-sectional regression results: hard to be conclusive

cf. Rodrik (2005)

• Correlates of entry regulations: corruption, unofficial economy, democracy

2. Labor Regulations

• Besley and Burgess (2004, QJE) • Use subnational panel data to

2-1 Research question

Is labor regulation really bad for manufacturing growth?

• Manufacturing: driver of economic growth

2-2 India as a testing ground

• 1947: labor regulations legislated at federal level

• Since then, each state

independently amends them in either pro-worker (+1) or

pro-employer (-1) directions

2-2 India as a testing ground

(cont.)

• Other industrial policies are

implemented at the federal level

⇒ State-level labor regulations won’t proxy for other policies

• Labor regulations apply to

registered manufacturing sectors (firms w/ many employees) only

2-3 Empirical strategy

Using state panel (1958-92) data yst = αs + βt + µrs,t−1 +x�stξ +εst

• r_s,t−1: degree of labor regulations • α_s: state fixed effect

• β_t: year fixed effect

• x_{st: time-varying exogenous} covariates

Digression: s.e. clustering

• Always report # of clusters used for s.e. calculation

⇐ If small (<50), s.e. is underestimated (Bertrand et al. 2004)

• With few clusters, use “wild

bootstrap-t” procedure by Cameron, Gelbach, & Miller (2008)

• _{Create a distribution of t-values by:} • Obtain residuals by imposingβ ₌0 • Multiply -1 w the residuals for randomly

chosen half of clusters • Obtain t-value

• Repeat this 999 times

2-4 Results 1 (Table II)

Pro-worker labor regulations ⇒

• More workdays per worker lost to strikes

• More workdays per worker lost to lockouts

2-4 Results 2

Impact of pro-worker labor regulations on outputs per capita: (Table III)

• Negative for registered manufacturing

• Zero for all sectors combined or for construction sector

2-4 Results 3 (Table V)

For registered manufacturing,

pro-worker labor regulations also lead to

• Less employment

• Less intense use of labor • Less fixed capital investment • Less factories

• Lower labor productivity

2-4 Results 4 (Table VIII)

• Pro-worker labor regulations also lead to higher urban poverty

2-5 Robustness

• Negative impact on registered

manufacturing: robust to a bunch of controls and to dropping West

Bengal (Table IV, ft. 22, columns 4 & 7 of Table VIII)

• Not robust to state-specific time trends (column 4 of Table IV, ft. 21, column 5 of Table VIII)

2-6 Taking stock

• More convincing than simple

cross-country regression analysis

• Unobserved time-invarient

characteristics of jurisdiction

• Other concurrent policies

3. Interactions of entry and

labor regulations

• Aghion, Burgess, Redding, Zilibotti (2008, AER)

3-1 Research questions

• What are the consequences of deregulation on entry and

production activities in manufacturing sector?

3-2 India as a testing ground

• 1951: License Raj introduced

• A license issued by govt required for

setting up a new factory, expanding capacity, starting a new product line, or changing locations

3-2 India as a testing ground

(cont.)

• Deregulation staggered across industries

⇒ Industries deregulated later: control group

• 2 big waves (1985 & 1991: Figure A1) unexpectedly initiated by new prime minister

3-2 India as a testing ground

(cont.)

When deregulation happened,

• Each state had different levels of pro-worker labor regulations

3-3 Empirical strategy

yist = αis + ηit + βst + θdit ∗rst + εist • i: industry in registered

3-3 Empirical strategy (cont.)

yist = αis + ηit + βst + θdit ∗rst + εist • d_it: delicensing dummy

• r_st: labor regulation index

• standard error: clustered at state (16) by delicensing-year (8) level

• _{Serial correlation in dit} ∗rst & εist at

industry-state level

• _{Year of delicensing: same for many}

industries (1985 and 1991) ⇒

Correlation indit ∗rst & εist within each

3-4 Result (Table 3 column 1)

• Significantly negative θ (coefficient on dit ∗ rst)

⇒ After delicensing, increases in an industry’s output larger for

pro-employer states than for pro-worker states

3-4 Result (cont.)

To gauge economic significance... • Obtain fitted values and

counterfactuals (θ = 0: if no heterogenous effects of delicensing)

• Sum across industries within state Compared to counterfactuals, state output in 1997

3-5 Robustness 1 (Table 3)

• Drop one state at a time • Replace r_st with r_s,1980 (labor

regulation when no industry was delicensed)

• r_st may be a response to industrial

development after delicensing

• Controlling for interactions of d_it and state dummies

• Unobserved state characteristics

(instead of labor regulations) at the time of deregulation may drive results

3-5 Robustness 2 (Table 4)

• The 1991 liberalization came as a package including trade and FDI liberalization

• Results survive if controlling for • Interaction of r_st & log tariff rate by

industry

• Interaction of r_st & fraction of products

open to automatic approval of FDI within each industry

3-5 Robustness 3 (Table 5)

• Labor regulations proxy for some other state policies?

• Results survive if controlling for interactions of delicensing and

• _{Development expenditures}

• Financial development (Burgess &

Pande 2005, cf. Lec 8 in Q1)

• Technological level of industries by

state

• _{Political history}

3-5 Final concerns

• Industries may have been chosen for delicensing because of their expected future growth

• No significant correlation between

year of delicensing and output growth between 1980-1984

• The choice of industries is unlikely to

have depended on their expected future growth in pro-employer states

3-6 Taking stock

• Impact of entry deregulation is heterogenous

• Complementary institutions seem to matter

cf. Kaplan-Piedra-Seira (2011):

Simplifying bureaucratic procedures to set up a firm in Mexico ⇒ # of new firms per month ↑ only by 5% (and the effect dies out by 15th

3-6 Taking stock (cont.)

Methodologically...

• Exploiting three-dimensional

4. Causes of heavy regulations?

• Low trust (Aghion, Algan, Cahuc, & Shleifer 2010)

• Those who will lose from deregulation block the reform (Caselli and Gennaioli 2008) • Political institutions (cf. Lecture 5

References for the lecture on regulations

Acemoglu, Daron. 2008. “Oligarchic versus Democratic Societies.”

Journal of the European Economic Association 6(1): 1-44. _!

Acemoglu, Daron, and Thierry Verdier. 2000. “The Choice between Market Failures and Corruption.” American Economic Review 90(1): 194-211.

Aghion, Philippe et al. 2010. “Regulation and Distrust.” The Quarterly Journal of Economics 125(3): 1015 -1049.

Aghion, Philippe et al. 2008. “The Unequal Effects of Liberalization: Evidence from Dismantling the License Raj in India.” American Economic Review 98(4): 1397-1412. !

Banerjee, Abhijit V. 1997. “A Theory of Misgovernance.” Quarterly Journal of Economics 112(4): 1289-1332. _!

Bertrand, Marianne, Esther Duflo, and Sendhil Mullainathan. 2004. “How Much Should We Trust Differences-in-differences Estimates?.”

Quarterly Journal of Economics 119: 249-275. _!

Besley, Timothy, and Robin Burgess. 2004. “Can Labor Regulation Hinder Economic Performance? Evidence from India.” Quarterly Journal of Economics 119: 91-134. _!

Cameron, A. Colin, Jonah B. Gelbach, and Douglas L. Miller. 2008. “Bootstrap-based Improvements for Inference with Clustered Errors.” Review of Economics & Statistics 90(3): 414-427.

Caselli, Francesco, and Nicola Gennaioli. 2008. “Economics and Politics of Alternative Institutional Reforms.” Quarterly Journal of Economics 123(3): 1197-1250.

Publications. !

Djankov, Simeon et al. 2002. “The Regulation of Entry.” Quarterly Journal of Economics 117(1): 1-37. _!

Kaplan, David S., Eduardo Piedra, and Enrique Seira. 2011. “Entry regulation and business start-ups: Evidence from Mexico.” Journal of Public Economics 95(11-12): 1501-1515.

La Porta, Rafael, Florencio Lopez-de-Silanes, and Andrei Shleifer. 2008. “The Economic Consequences of Legal Origins.” Journal of Economic Literature 46(2): 285-332. !