Rational Expectations and the Puzzling No-Effect of the Minimum WAge Sara Pinoli Bocconi University December 12th, 2008

EMPLOYMENT EFFECT OF MW Introduction Model Empirical Analysis Conclusion EMPLOYMENT EFFECT OF MW Competitive labor market  disemployment effect Controversial empirical evidence  puzzle characteristics of labor market monopsony efficiency wage endogenous search effort characteristics of MW policy expected unexpected

Introduction Model Empirical Analysis Conclusion CONTRIBUTION Changes in the minimum wage are often PREDICTABLE  rational agents discount future variations in the minimum wage  expected changes in the minimum wage have different observed employment effect than unexpected changes

Introduction Model Empirical Analysis Conclusion MAIN FINDINGS Model: agents adjust their behavior in advance expected ΔMW has lower observed effect than unexpected ΔMW  harder to identify Empirical Evidence (Spain 2004:3): unexpected ΔMW has higher positive effect on job separations; unexpected ΔMW has negative effect on ex-post Δu expected ΔMW has negative effect on ex-ante Δu

OUTLINE Model Empirical Analysis Conclusion

Introduction Model Empirical Analysis Conclusion MODEL: FRAMEWORK LOW WAGE WORKERS’ LABOR MARKET: matching frictions: m(v,u) heterogeneous stochastic matches: productivity productivity shocks at rate λ firing cost F minimum wage increases with probability state 0: state 1: state 2:

Introduction Model Empirical Analysis Conclusion FLOWS DYNAMICS

UNEMPLOYMENT DYNAMICS Introduction Model Empirical Analysis Conclusion UNEMPLOYMENT DYNAMICS

Introduction Model Empirical Analysis Conclusion MODEL: SUMMARY Expectations affect the TIMING of the MW effects Ex-post effects expected MW vs. unexpected MW lower disemployment lower increase in job destruction lower decrease in job creation  harder to find empirical evidence of disemployment effect of expected changes in the minimum wage

EMPIRICAL ANALYSIS: SPAIN Introduction Model Empirical Analysis Conclusion EMPIRICAL ANALYSIS: SPAIN Why Spain? Expected vs. unexpected Δ+MW: Aznar vs. Zapatero  Data EPA 2000-2006: rotating quarterly survey on population living in Spain. 150,000 individuals aged 16+ 6 consecutive quarters working status, personal characteristics

ECONOMETRIC SPECIFICATION Introduction Model Empirical Analysis Conclusion ECONOMETRIC SPECIFICATION Probit model employment prob. job destruction rate job finding rate Difference in difference Young (16-24) vs. adult (25-54),

Introduction Model Empirical Analysis Conclusion ROBUSTNESS Expected Δ+MW CK(95): only substantial ΔMW can be used to estimate the employment effect  ZMW Treatment and control groups not all the young workers are paid MW  young female vs. adult female young female low edu vs. adult female low edu Timing expectations affect the timing of employment effects 

RESULTS: EMPLOYMENT PROBABILITY Introduction Model Empirical Analysis Conclusion RESULTS: EMPLOYMENT PROBABILITY Y vs. A YF vs. AF YFL vs. AFL young*UMW1 0.003 0.002 0.001 -0.000 (0.001)*** (0.001)** (0.001) (0.003) young*ZMW2 -0.002 -0.003 -0.010 -0.012 (0.002) (0.005)* (0.005)** young*UMW_pre3 -0.001 young*UMW_post4 -0.004 (0.003)*** young*ZMW_pre3 -0.006 (0.004)* young*ZMW_post4 (0.004)*** Pseudo-R2 0.237 0.147 0.033 Observations 1889412 952728 199349 Standard errors in parenthesis Controls: gender, education, attended courses the last month, time (quarterly) effect, linear trend, region of residence

RESULTS: FLOWS OUT OF EMPLOYMENT Introduction Model Empirical Analysis Conclusion RESULTS: FLOWS OUT OF EMPLOYMENT Y vs. A YF vs. AF YFL vs. AFL young*UMW1 0.002 0.004 0.008 (0.000)*** (0.001)*** (0.003)*** young*ZMW2 0.001 (0.000) (0.001) (0.005) young 0.018 0.017 0.006 female 0.020 temporary 0.085 0.106 0.145 part-time 0.013 0.011 -0.001 (0.003) Pseudo-R2 0.161 0.156 0.162 Observations 956432 396856 48789 Standard errors in parenthesis Controls: gender, education, attended courses the last month, time (quarterly) effect, linear trend, region of residence, contract type, working day, industry, occupation, sector

RESULTS: FLOWS INTO EMPLOYMENT Introduction Model Empirical Analysis Conclusion RESULTS: FLOWS INTO EMPLOYMENT Y vs. A YF vs. AF YFL vs. AFL young*UMW1 0.002 0.001 0.009 (0.002) (0.005)* young*ZMW2 0.004 0.005 0.012 (0.003)* (0.003) (0.008) young 0.040 0.047 0.034 (0.003)*** (0.009)*** female -0.066 (0.002)*** active search 0.021 0.016 (0.006)*** Pseudo-R2 0.104 0.110 0.107 Observations 186191 112978 21081 Standard errors in parenthesis Controls: gender, education, attended courses the last month, time (quarterly) effect, linear trend, region of residence, first job, search method

Introduction Model Empirical Analysis Conclusion changes in MW are often predictable; expected changes in MW are partly anticipated; ex-post unemployment effect is lower in case of expected changes in MW;  better to focus on unexpected ΔMW MW increases separations but may increase participation  non significant employment effect

Introduction Model Empirical Analysis Conclusion

Introduction Model Empirical Analysis Conclusion Wage Structure 2002 wages MW edu