Katherine Terrell

FOURTH IZA-WORLD BANK CONFERENCE ON
EMPLOYMENT AND DEVELOPMENT
Bonn, May 5-6, 2009
Informality, Minimum Wages and
Enforcement in Brazil
Brooke Helppie, University of Michigan
Katherine Terrell, University of Michigan and IZA
Research Questions, Motivation, Contribution
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To what extent is informality due to more rigid labor market
regulation?
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But de jure regulation may not have an effect if not
enforced… Hence, we ask to what extent is informality
affected by greater enforcement of labor regulations (and
Minimum Wages in particular)?
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Brazil is a good case study since highly regulated and much
informality
Brazil - Enforcement of labor legislation varies across states
Large literature on MWs in Brazil and one new paper on
enforcement (Almeida and Carneiro, 2008) but no paper
there (or elsewhere) combines the two
Î enforcement often used as a residual explanation
Research Questions, Motivation, Contribution
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Majority of MW literature identifies impact on
employment in formal and informal sector without
individual panel data Æ shortcoming as measure it
indirectly/net effect
We ask to what extent do higher MWs and greater
enforcement:
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Increase flows out of the formal (informal) sector (layoffs?
change in status?)
Reduce flows (hiring) into the formal (or informal) sector
Does the structure of MWs make a difference?
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Brazil recently reinstated new higher state minimum wages
(MWs) in several states
What do we mean by Informality?
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In Brazil workers who have a “signed work card”
enjoy
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A minimum of 25 days of vacation;
Maximum work week of 44 hours;
Overtime premium of 50%;
13th month pay;
4 months of maternity leave; 5 days paternity leave
MW set a level necessary to pay for necessities of a
worker and his or her family (including housing, food,
education. Leisure, clothing, hygiene, transportation and
social security)
One month notice for firing
Some UI, Fund for Unemployment
What to expect in terms of informality?
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We might expect
Increase in MW, holding Enforcement constant
Îdecline in EF (increase in flows out of EF; decrease in flows in )
Î Increase in EINF , if this sector does not pay the MW
Î decline in EINF , if this sector pays the MW
Increase in Enforcement, holding MW constant
Î increase or decrease in EF
Î decline in EINF
What do we know about impact of MW?
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Informal Sector:
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Found to have a spike at the MW, But not clear whether
E responds to changes in MW
Elasticity of E w.r.t. MW
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<0 (Faynzylber, 2001; Lemos 2004)
>0 (Carneiro, 2000; Carneiro et al. , 2001)
Formal Sector:
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Found to have a spike at the MW
Elasticity of W w.r.t. MW ranges from 0 to large:
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0.4-0.6 (Veloso, 1990); N.S. (Soares, 2002)
Elasticity of E w.r.t. MW typically small neg. or not. signif.
:
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-0.001 -0.0024 in long run (Carneiro et al. , 2001; Lemos,
2004)
All Full-Time Workers : Formal v.
Informal
Minimum Wages
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Today some states have one MW while others have
multiple MWs
Return to State level MWs
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1988-2000: One National MW
2000-present: State “wage floors” allowed*
` 2000 – Rio de Janeiro (3-tiered occupation-specific MW)
` 2001 – Rio Grande do Sul (4-tiered Industry-specific MW)
` 2006 – Parana
` 2007 – Sao Paulo
*Constitution only allows one MW but Article 7, para. 5 mandates
“wage floors” commensurate with the level and difficulty of a job.
Table 3: Rio Grande do Sul (Porto Alegre) - Industrial Categories
Covered by Each Minimum Wage Level (2002-2008)
Wage Level 1
a) na agricultura e na pecuária;
b) nas indústrias extrativas;
c) em empresas de pesca;
d) empregados domésticos;
e) em turismo e hospitalidade;
f) nas indústrias da construção civil;
g) nas indústrias de instrumentos musicais e brinquedos;
h) em estabelecimentos hípicos.
Wage Level 2
a) nas indústrias do vestuário e do calçado;
b) nas indústrias de fiação e tecelagem;
c) nas indústrias de artefatos de couro;
d) nas indústrias do papel, papelão e cortiça;
e) em empresas distribuidoras e vendedoras de jornais e revistas e empregados
em bancas, vendedores ambulantes de jornais e revistas;
f) empregados da administração das empresas proprietárias de jornais e revistas;
g) empregados em estabelecimentos de serviços de saúde.
Wage Level 3
a) nas indústrias do mobiliário;
b) nas indústrias químicas e farmacêuticas;
c) nas indústrias cinematográficas;
d) nas indústrias da alimentação;
e) empregados no comércio em geral;
f) empregados de agentes autônomos do comércio.
Wage Level 4
a) nas indústrias metalúrgicas, mecânicas e de material elétrico;
b) nas indústrias gráficas;
c) nas indústrias de vidros, cristais, espelhos, cerâmica de louça e porcelana;
d) nas indústrias de artefatos de borracha;
e) em empresas de seguros privados e capitalização e de agentes autônomos de
seguros privados e de crédito;
f) em edifícios e condomínios residenciais, comerciais e similares;
g) nas indústrias de joalheria e lapidação de pedras preciosas;
h) auxiliares em administração escolar (empregados de estabelecimentos de
ensino).
Rio de Janeiro MW Classification is by Occupations
(movement from one wage level to another)
Nominal Minimum Wage Increases
(% Change from previous minimum wage)
Year
Month
2002 May
2003 March
May
2004 January
May
June
2005 January
May
June
2006 January
May
June
2007 January
May
2008 January
April
Federal Minimum
11.11%
20.00%
1
Rio Grande do Sul
2
3
4
1
2
Rio de Janeiro
3
4
5
6
13.04% 13.19% 13.33% 13.20%
10.42%
15.00%
14.40% 13.85% 13.33% 12.86%
9.43%
10.51%
10.49% 10.47% 10.46% 10.44%
6.90%
6.89%
13.33%
13.33%
13.33% 13.33% 13.33% 13.33%
15.00%
15.00%
15.00% 15.00% 15.00% 15.00%
10.70%
10.70%
10.70% 10.70% 10.70% 10.70%
20.00% 20.00% 20.00% 20.00%
8.33%
8.33%
8.33%
8.33%
8.33%
6.96%
7.03%
7.10%
6.88%
10.85% 10.85% 10.85% 10.85%
15.38%
8.35%
8.35%
8.35%
8.35%
16.67%
8.57%
9.21%
5.98%
5.98%
5.98%
5.98%
Enforcement
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1943 CLT (Consolidação das Leis do Trabalho)
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Gave system of labor courts a pre-eminent role in
enforcement of contracts and dispute resolution.
Three tiers: local (varas), regional, and superior
Varas are the courts where individual workers or unions
file their cases – employer notified and invited to provide
documents proving innocence.
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Employer bears full burden of proof.
Biased toward workers. (80% of cases in Minas Gerais decided
in favor of the worker – Camargo, 2000)
Lengthy process (average time 700 days from time of filing to
resolution)
Costly to employer (average - R$1,000 plus 2% for court;
employees pay nothing)
Pesquisa Mensal de Emprego (PME)
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January 2002 – April 2008 (“new methodology data”)
Six largest metropolitan areas
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Random sample within each but relative size is
proportional to population
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Bahia (Salvador)
Rio de Janeiro
Pernambuco (Recife)
Sao Paulo (Sao Paulo)
Minas Gerais (Belo Horizonte)
Between 12,000 to 20,000 observations per city in a given
month
Rotating panel
Impact of Minimum Wages
and Enforcement
Begin by seeing if an effect on wages…
Estimation Strategy
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Analytical sample:
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Men, ages 15-70, first two observation
Estimate wage effects
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On those who stay in the same job in t=0 and t=1
Separate estimates for those in formal and informal jobs
Separate estimates for all, less educated, more educated
Nominal wages and minimum wages, holding city specific
inflation constant
Base Regressions:
∆WiS = α∆MWS + β∆Enf S + φ (∆MWS * ∆Enf S ) + λ∆Inf S + µiS
∆WiS = α1∆OMWS + α 2 ∆MMWS + β ∆Enf S + φ1 (∆OMWS * ∆Enf S )
+ φ2 (∆MMWS * ∆Enf S ) + λ∆Inf S + µiS
Preliminary findings using only Federal MW
Individual First Difference Wage regression for workers who have a formal sector job at time t=0.
without Enforcement
All
More Educ Less Educ
∆ln(MW)
0.224
[0.012]***
∆Enforcement
∆Enforcement x ∆ln(MW)
Observations
Number of individuals
-
0.210
[0.015]***
-
0.267
[0.019]***
-
All
with Enforcement
More Educ
Less Educ
-0.141
-0.116
-0.187
[0.059]**
[0.075]
[0.092]**
-0.122
-0.175
-0.061
[0.063]*
[0.081]**
[0.102]
0.555
0.495
0.687
[0.089]***
[0.115]***
[0.139]***
494429
335177
159252
494429
335177
159252
201894
143525
72000
201894
143525
72000
Note: Panel data on individuals includes only first two observations for each individual. *significant at 10%; ** significant
at 5%; *** significant at 1%.
Marginal Effects with Enforcement:
∆ W/ ∆ MW - at mean Enforcement
∆ W/∆ Enforcement - at mean MW
0.234
0.042
0.219
-0.029
0.278
0.142
Estimation Strategy
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Flow Analysis
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1.
2.
Effect of MW and Enforcement on flows
From formal jobs to other labor market states (firing)
From other labor market states into formal (hiring)
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Other states: informal, self-employed, unemployed, out of the
labor force
Things to consider:
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Need to control for business cycles, age, education , tenure,
city specific effects
Use nominal or real MW?
Use lagged change in MW given inflexibility in firing
Use OLS and not Probit
Table 7 ‐ Monthly Transition Matrix
T=1 Employment Status
IE
SE
UE
246,017
8,035
2,645
2,120
3,811
3,339
841
266,808
(FE)
92.21%
3.01%
0.99%
0.79%
1.43%
1.25%
0.32%
100.00%
Info rmal Employees
(IE)
10,020
10.43%
67,276
70.06%
8,138
8.47%
3,311
3.45%
5,202
5.42%
982
1.02%
1,099
1.14%
96,028
100.00%
Self‐Employed
(SE)
2,849
2.29%
8,562
6.89%
99,516
80.06%
2,449
1.97%
5,077
4.08%
389
0.31%
5,467
4.40%
124,309
100.00%
Unemployed
(UE)
2,229
3.80%
4,435
7.56%
2,940
5.01%
34,236
58.32%
14,463
24.64%
237
0.40%
160
0.27%
58,700
100.00%
Out of Labor Force
(OLF)
2,947
1.33%
5,906
2.66%
5,477
2.46%
15,346
6.90%
191,436
86.10%
797
0.36%
443
0.20%
222,352
100.00%
Public
(PB)
3,556
6.25%
986
1.73%
321
0.56%
221
0.39%
777
1.37%
50,920
89.49%
117
0.21%
56,898
100.00%
Employer
(EM)
898
2.53%
1,205
3.40%
5,429
15.32%
158
0.45%
434
1.23%
123 27,180
0.35% 76.72%
35,427
100.00%
268,516
31.20%
96,405
11.20%
124,466
14.46%
57,841
6.72%
221,200
25.71%
56,787 35,307
6.60% 4.10%
860,522
100.00%
T=0 Employment Statu
Fo rmal Employees
Total
FE
OLF
PB
EM
Total
VERY Preliminary findings using FEDMW
only
Flows from Formal Employment into Other
States (Probit Analysis)
-1
ln(hourly MW)_t-1
From Formal Employment at time t-1 into the following states in time t:
-2
-3
-4
-5
-6
-7
Unemployed
(U)
Self-Employed
(SE)
Out of the Labor
Force (OLF)
-0.162
[0.240]
-0.44
[0.407]
-0.497
[0.386]
0.443
[0.302]
0.241
[0.496]
0.15
[0.399]
-0.593
[0.638]
-1.606
[0.682]
0.652
[1.095]
-0.279
[0.858]
-1.107
[0.635]*
0.836
[0.787]
-1.083
[0.995]
0.985
[0.781]
0.358
[0.621]
-0.778
[0.507]
190188
183700
183832
186563
190188
183700
183832
186563
Enforcement_t-1
[Enforcement x ln(MW)_]t-1
Observations
-8
Informal
Employees
(IE)
Informal
Unemployed Self-Employed Out of the Labor
Employees (IE)
(U)
(SE)
Force (OLF)
Flows into Formal Employment - New Hires (Probit Analysis)
From the following states in time t-1 into formal employment at time t:
ln(MW)_t-1
Informal
Employees
(IE)
-0.121
[0.254]
Unemployed
(U)
Self-Employed
(SE)
Out of the Labor
Force (OLF)
0.174
[0.505]
0.141
[0.405]
-0.906
[0.300]***
Enforcement_t-1
[Enforce x ln(MW)] _t-1
Informal
Unemployed Self-Employed Out of the Labor
Employees (IE)
(U)
(SE)
Force (OLF)
1.458
[0.527]***
1.471
[0.418]***
1.306
[1.395]
-1.654
[0.813]*
2.026
[0.841]***
-4.39
[1.069]***
0.392
[0.492]***
1.38
[0.776]**
-2.316
1.374
3.187
-1.854
[0.681]***
[1.068]
[0.671]***
[0.614]
Standard errors in bracket, * significant at 10%; ** significant at 5%; *** significant at 1%
Notes: Regression includes, Exper and Exper2, dummies for completed years of education, city, year and month fixed effects. The hourly minimum wage is the
National minimum in 1997 Reais. Recife is the base city and "no education" the base for the education variables.
Preliminary Findings and Next Steps
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Findings:
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Next Steps:
Implement what we propose:
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MWs increase Ws in formal, especially less educated
Higher enforcement raises W of less educated; no effect on W
of more educated
MW alone has no effect on flows out of or into formal; When
interacted with enforcement may dampen flows into formal
Estimate flows for informal
Debug the Rio de Janeiro data so as to estimate MMW
Incorporate leads and lags of MWs
Collect more enforcement data
Consider instruments for MWs (political variables) to
explain endogeneity of MMW choice