Labor Supply of New York City Cabdriver: One Day at a Time

1. Labor Supply of New York City Cabdriver: One Day at a Time

2. Outline Introduction Empirical Analysis Interpretation Discussion and Conclusion

3. Introduction Empirical Analysis Interpretation Discussion and Conclusion Introduction Relationship between Work Hours and Wages Economic Theory: Positive Relationship High wage  Working more Low wage  Leisure more In Fact: Negative Relationship?

4. Introduction Empirical Analysis Interpretation Discussion and Conclusion Introduction Objective Exploring the relationship between wages and work hours Sample New York City Cabdrivers • Daily fluctuate wage • Choose work hour themselves • Data recording by trip sheet and meter

5. Introduction Empirical Analysis Interpretation Discussion and Conclusion Empirical Analysis • Data • Wage Variability within Days and between Days • Wage Elasticities • How do elasticities vary with experience? • Could drivers earn more by driving differently?

6. Introduction Empirical Analysis Interpretation Discussion and Conclusion Empirical Analysis Data Reference - Trip Sheet + Meter - Phone Survey of 14 owners and managers at fleet company Main Variables - Daily Work Hours - Average Daily Wage

7. Introduction Empirical Analysis Interpretation Discussion and Conclusion Empirical Analysis Data Types of Cabdrivers Daily Fleet Drivers Lease-Drivers Owner-Drivers Data Set TRIP TLC1 TLC2

8. Introduction Empirical Analysis Interpretation Discussion and Conclusion Empirical Analysis Data

9. Introduction Empirical Analysis Interpretation Discussion and Conclusion Empirical Analysis • Data • Wage Variability within Days and between Days • Wage Elasticities • How do elasticities vary with experience? • Could drivers earn more by driving differently? 

10. Introduction Empirical Analysis Interpretation Discussion and Conclusion Empirical Analysis Wage Variability within Days and between Days Within days Regress median hourly wage on previous hour’s median wage • 1st to 4th order autocorrelation are positive and significant • Autocorrelation between two halves of the day is positive and significant Positive or Zero Autocorrelation within days

11. Introduction Empirical Analysis Interpretation Discussion and Conclusion Empirical Analysis Wage Variability within Days and between Days Between days Regress median hourly wage of day t on previous hour’s median wage of day t-1 • Negative and Insignificant No Autocorrelation between days

12. Introduction Empirical Analysis Interpretation Discussion and Conclusion Empirical Analysis Wage Elasticities Methodology • OLS and IV regression • Add dummy variable (high temperature, shift during week, rain, night shift dummy, day shift dummy) • IV = the distribution of hourly wages of other drivers that drove on the same day and shift • Fixed Effect Model

13. Introduction Empirical Analysis Interpretation Discussion and Conclusion Empirical Analysis Wage Elasticities Simple Correlation between log hours and log wages

14. Introduction Empirical Analysis Interpretation Discussion and Conclusion Empirical Analysis Wage Elasticities IV log hours worked equations

15. Introduction Empirical Analysis Interpretation Discussion and Conclusion Empirical Analysis Wage Elasticities IV log hours worked equations (continue)

16. Introduction Empirical Analysis Interpretation Discussion and Conclusion Empirical Analysis Wage Elasicities • Negative wage elasticity on work hours • TLC1 and TLC2 are more strongly negative than TRIP

17. Introduction Empirical Analysis Interpretation Discussion and Conclusion Empirical Analysis • Data • Wage Variability within Days and between Days • Wage Elasticities • How do elasticities vary with experience? • Could drivers earn more by driving differently?   

18. Introduction Empirical Analysis Interpretation Discussion and Conclusion Empirical Analysis How do elasticities vary with experience? • Low experience elasticity is more strongly negative in TRIP and TLC2

19. Introduction Empirical Analysis Interpretation Discussion and Conclusion Empirical Analysis How do elasticity vary with payment structure? • Elasticity in fleet drivers is less negative than others.

20. Introduction Empirical Analysis Interpretation Discussion and Conclusion Empirical Analysis Could drivers earn more by driving differently? Actual total wage earning = Fixed-hours earning = Compare this two earnings • FHE > actual earning • Net earning is increased by 5% on average if they drove the same number of hours everyday.

21. IntroductionEmpirical Analysis Interpretation Discussion and Conclusion Interpretation • Daily Income Targeting • Liquidity Constraint • Breaks • Increase Disutility of Effort • Participation Marginal Utility

22. IntroductionEmpirical Analysis Interpretation Discussion and Conclusion Interpretation Daily Income Targeting • Cabdrivers set target and quit when they reach it. • Drivers use their daily lease fee as a reference point. • Marginal utility of income decline substantially around the average daily income level Daily Targeting Wage Marginal Utility

23. IntroductionEmpirical Analysis Interpretation Discussion and Conclusion Interpretation Liquidity Constraint • Most of lease drivers pay their weekly or monthly fee in advance, so they don’t need to drive long hours on low wage day to pay for their shift. • People with no liquidity constraint should not have negative elasticity. Elasticity Owner Driver > Lease Driver > Fleet Driver

24. IntroductionEmpirical Analysis Interpretation Discussion and Conclusion Interpretation  • Daily Income Targeting • Liquidity Constraint • Breaks • Increase Disutility of Effort • Participation  Marginal Utility

25. IntroductionEmpirical Analysis Interpretation Discussion and Conclusion Interpretation Breaks Problem The trip sheets do not distinguish between idle time and leisure time. Explanation There are 3reasons show that breaks do not significantly affect negative elasticities.

26. IntroductionEmpirical Analysis Interpretation Discussion and Conclusion Interpretation Breaks Explanation 1. Breaks of more than 30 minutes were removed from calculating. The results were not significantly different from the report 2. The measured elasticity is negative 3. Assumption that the length of breaks responses less strongly to wages than for inexperienced drivers

27. IntroductionEmpirical Analysis Interpretation Discussion and Conclusion Interpretation Increase Disutility of Effort • “Earning – Money - Tiring” Hypothesis • Cannot explain experience effect

28. IntroductionEmpirical Analysis Interpretation Discussion and Conclusion Interpretation  • Daily Income Targeting • Liquidity Constraint • Breaks • Increase Disutility of Effort • Participation    Marginal Utility

29. IntroductionEmpirical Analysis Interpretation Discussion and Conclusion Interpretation Participation The wage elasticity would be biased if unobservable affected drivers’ decisions (or participation). Explanation There is not that much unobserved factors that affect participation. 1. The fixed effects mitigates the omitted variable problem. 2. The drivers usually have a regular schedule of shift.

30. IntroductionEmpirical Analysis Interpretation Discussion and Conclusion Discussion and Conclusion • The elasticity contradicts to the theoretical prediction. • Wage and work hour are highly correlated within days, but weakly correlated between days • The cabdrivers are not representative of working population • The further analysis should be conducted with other data set.