Part II Second-Generation Studies of Labor Supply 1) Introduction 2) Wage equation 3) Analysis of labor force participation decision 4) Comparing conditional OLS and Tobit estimates of labor supply 5) Heckman two-stage method

1) Introduction Major shortcoming of first-generation studies of labor supply: neglecting the selectivity bias (focus on working cohort only) Data: US, 1975, women

Variables WHRS…...labor supply….. hours worked per year in 1975 WA………..age WE………...education in years WW………..wage………….hourly wage rate KL6………number of children less than 6 years old K618 ……..number of children more than 6 years old and less than 18 years old LWW = ln(WW) LWHRS = ln(WHRS) WA2=(WA^2)/100 AX……….labor market experience in years CIT……….dummy variable, =1 if live in large city

2) Wage equation Ln(wage)=0+1WA+2(WA)2+3WE+4AX+5CIT

2) Wage equation Ln(wage)=0+1WA+2(WA)2+3WE+4AX

Wages of workers vs. non-workers

3) Analysis of labor force participation decision: OLS

3) Analysis of labor force participation decision: OLS

Problem with OLS: values of LFP outside the range [0,1]

3) Analysis of labor force participation decision: PROBIT

3) Analysis of labor force participation decision: PROBIT predicted values = probability to work

3) Analysis of labor force participation decision: PROBIT Marginal effects = change in probability to work due to a marginal increase in explanatory variables

3) Analysis of labor force participation decision: LOGIT

LOGIT marginal effects

4) Comparing conditional OLS and Tobit estimates of labor supply Avg.hours(US)<Avg.hours(CZ) Higher corr(wage,edu) in the US (see next slides)

OLS for working women

OLS for the whole sample (constructed wages)

TOBIT (censored point = 0)

5) Heckman two-stage method

5) Heckman two-stage method