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 ` To what extent is informality due to more rigid labor market regulation? ` ` 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)? ` ` 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 ` ` 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: ` ` ` 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? ` Brazil recently reinstated new higher state minimum wages (MWs) in several states What do we mean by Informality? ` In Brazil workers who have a “signed work card” enjoy ` ` ` ` ` ` ` ` 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? ` 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? ` Informal Sector: ` ` 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 ` ` ` <0 (Faynzylber, 2001; Lemos 2004) >0 (Carneiro, 2000; Carneiro et al. , 2001) Formal Sector: ` ` Found to have a spike at the MW Elasticity of W w.r.t. MW ranges from 0 to large: ` ` 0.4-0.6 (Veloso, 1990); N.S. (Soares, 2002) Elasticity of E w.r.t. MW typically small neg. or not. signif. : ` -0.001 -0.0024 in long run (Carneiro et al. , 2001; Lemos, 2004) All Full-Time Workers : Formal v. Informal Minimum Wages ` ` Today some states have one MW while others have multiple MWs Return to State level MWs ` ` 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 ` 1943 CLT (Consolidação das Leis do Trabalho) ` ` ` 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. ` ` ` ` 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) ` ` January 2002 – April 2008 (“new methodology data”) Six largest metropolitan areas ` ` ` ` ` ` Random sample within each but relative size is proportional to population ` ` 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 ` Analytical sample: ` ` Men, ages 15-70, first two observation Estimate wage effects ` ` ` ` ` ` 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 ` Flow Analysis ` 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) ` ` Other states: informal, self-employed, unemployed, out of the labor force Things to consider: ` ` ` ` 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 ` Findings: ` ` ` ` ` Next Steps: Implement what we propose: ` ` ` ` ` 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