Econometric Analysis of Panel Data PD6.ppt

1、Econometric Analysis of Panel Data,Random Regressors Pooled (Constant Effects) Model Instrumental Variables Fixed Effects Model Random Effects Model Hausman-Taylor Estimator,Random Regressors,Pooled (Constant Effects) Model Other classical assumptions remained. OLS is biased; Instrumental variables

2、estimation should be used. IV estimator is consistent.,Constant Effects Model,Instrumental Variables Estimation,Constant Effects Model,Instrumental Variables Estimation Instrumental Variables: Zi Included Instruments: X1i # Zi # Wi,Constant Effects Model,Instrumental Variables Estimation,Constant Ef

3、fects Model,Instrumental Variables Estimation HAC Variance-Covariance Matrix,Constant Effects Model,Hypothesis Testing of Instrumental Variables Test for Endogeneity Test for Overidentification Test for Weak Instruments,Random Regressors,Fixed Effects Model Other classical assumptions remained. Can

4、not estimate the parameters of time-invariant regressors, even if they are correlated with model error. The random regressors x2 has to be time-varying.,Fixed Effects Model,The Model Instrumental Variables #Zi #Xi (Zi must be time variant),Fixed Effects Model,Within Estimator Panel-Robust Variance-C

5、ovariance Matrix,Example: Returns to Schooling,Cornwell and Rupert Model (1988) Data (575 individuals over 7 ears) Dependent Variable yit: LWAGE = log of wage Explanatory Variables xit: Time-Variant Variables x1it: EXP = work experience (+EXP2) exogenous WKS = weeks worked endogenous OCC = occupatio

6、n, 1 if blue collar IVIND = 1 if manufacturing industry IV SOUTH = 1 if resides in south IV SMSA = 1 if resides in a city (SMSA) IV MS = 1 if married IV UNION = 1 if wage set by union contract IV Time-Invariant Variables x2i: ED = years of education endogenous FEM = 1 if femaleBLK = 1 if individual

7、is black,Random Regressors,Random Effects Model Other classical assumptions remained. Mundlak approach may be used when Instrumental variables must be used if,Random Effects Model,The Model,Random Effects Model,(Partial) Within Estimator Panel-Robust Variance-Covariance Matrix,Example: Returns to Sc

8、hooling,Cornwell and Rupert Model (1988) Data (575 individuals over 7 years) Dependent Variable yit: LWAGE = log of wage Explanatory Variables xit: Time-Variant Variables x1it: EXP = work experience (+EXP2) exogenous WKS = weeks worked endogenous OCC = occupation, 1 if blue collar IVIND = 1 if manuf

9、acturing industry IV SOUTH = 1 if resides in south IV SMSA = 1 if resides in a city (SMSA) IV MS = 1 if married IV UNION = 1 if wage set by union contract IV Time-Invariant Variables x2i: ED = years of education endogenous FEM = 1 if female IV BLK = 1 if individual is black IV,Hausman-Taylor Estimat

10、or,The Model Time-variant Variables: x1it, x2it Time-invariant Variables:x3i, x4i Fixed effects model can not estimate b3 and b4; Random effects model has random regressors: x2 and x4 correlated with u.,Hausman-Taylor Estimator,Fixed Effects Model,Hausman-Taylor Estimator,Fixed Effects Model Within

11、Residuals,Hausman-Taylor Estimator,Random Effects Model,Hausman-Taylor Estimator,Instrumental Variables Hausman-Taylor (1981) Amemiya-Macurdy (1986),Hausman-Taylor Estimator,Instrumental Variable Estimation,Example: Returns to Schooling,Cornwell and Rupert Model (1988) Data (575 individuals over 7 e

12、ars) Dependent Variable yit: LWAGE = log of wage Explanatory Variables xit: Time-Variant Variables x1it: EXP = work experience endogenous (+EXP2)WKS = weeks worked endogenous OCC = occupation, 1 if blue collar, IND = 1 if manufacturing industrySOUTH = 1 if resides in southSMSA = 1 if resides in a city (SMSA)MS