1. psid3.do Panel study of income dynamics Longitudinal data of 5000 households started in 1969 HH members followed annually since This example has 5-years worth of data for 789 continuously employed full time male workers 5*789 = 3945 obs

2. 1 st exercise, ignore panel nature of data and estimate human capital earnings function Regress log hourly wage on –Education –Tenure and tenure2 –Experiene and experience 2 –Race –Union status

3. *generate new variables; gen exp=age-educ-5; gen exp2=exp*exp; gen wage=laborinc/hours; gen wagel=log(wage); gen tenure2=tenure*tenure;

5. * get OLS estimates; reg wagel exp exp2 tenure tenure2 union educ black;

6. Notice R 2 and compare to FE in next regression

7. Areg constructs within Panel means rather than Estimate LSDV model ID is the variable That identifies Groups for Fixed-effects Data must Be sorted by ID Number of groups (N in class notation) Big jump in R 2

8. . * now estimate a model with fixed effects;. * the xi command is used to construct a series of;. * dummy variables. suppose you have a variable ;. * x2 that has four values, 1,2,3,4. i.x2 will;. * construct a set of 3 dummy variables, one for;. * x2=1, x2=3 and x2=4. > > * notice that in the within group model, you;. * must delete variables without any within-panel;. * variation. in this case, educ and black;. xi: reg wagel exp exp2 tenure tenure2 union i.id;

10. Summary of Results (X’s) VariableOLSFixed Exp0.0336 (0.0040) 0.055 (0.006) Exp 2 -4.2E-4 (1.0E-4) -6.5E-4 (1.6E-4) Tenure0.0307 (0.0029) 0.0178 (0.0032) Tenure 2 -7.5E-4 (1.1E-4) -5.0E-4 (1.4E-4) Union0.129 (0.017) 0.052 (0.024)

11. Rate of return to tenure Y it =β 0 + E it β 1 + E it 2 β 2 + T it β 3 + T it 2 β 4 + Union it β 5 + EDUC i γ 1 + Black i γ 2 + ε it dY/dT = β 3 + 2 T it β 4 Return to tenure OLS FE 5 years 0.0232 0.0128 10 years 0.0157 0.0078 20 years 0.0007 -0.0022