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Econometric Analysis of Panel Data. Panel Data Analysis Fixed Effects Dummy Variable Estimator Between and Within Estimator First-Difference Estimator Panel-Robust Variance-Covariance Matrix Heteroscedasticity and Autocorrelation Cross Section Correlation Hypothesis Testing
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Econometric Analysis of Panel Data • Panel Data Analysis • Fixed Effects • Dummy Variable Estimator • Between and Within Estimator • First-Difference Estimator • Panel-Robust Variance-Covariance Matrix • Heteroscedasticity and Autocorrelation • Cross Section Correlation • Hypothesis Testing • To pool or Not to pool
Panel Data Analysis • Fixed Effects Model • ui is fixed, independent of eit, and may be correlated with xit.
Fixed Effects Model • Classical Assumptions • Strict Exogeneity • Homoschedasticity • No cross section and time series correlation
Fixed Effects Model • Extensions • Weak Exogeneity
Fixed Effects Model • Extensions • Heteroschedasticity
Fixed Effects Model • Extensions • Time Series Correlation (with cross section independence for short panels)
Fixed Effects Model • Extensions • Cross Section Correlation (with time series independence for long panels)
Dummy Variable Model • Dummy Variable Representation • Note: X does not include constant term, otherwise one less number of dummy variables should be used.
Dummy Variable Model • Dummy Variable Estimator (LSDV) • Heteroscedasticity and Autocorrelation
Dummy Variable Model Panel-Robust Variance-Covariance Matrix
Within Model Within Model Representation
Within Model Model Assumptions
Within Model • Within Estimator: FE-OLS
Within Model • Within Estimator: GLS • GLS = FE-OLS • Note:
Within Model • Normality Assumption
Within Model Log-Likelihood Function ML Estimator
Within Model ML Estimator of e2 is downward biased even for large N: For balanced panel (T=Ti: ), e2 should be estimated as:
Within Model • Estimated Fixed Effects • For , is consistent but is inconsistentunless .
Within Model • Panel-Robust Variance-Covariance Matrix • Consistent statistical inference for general heteroscedasticity, time series and cross section correlation.
First-Difference Model • First-Difference Representation • Model Assumptions
First-Difference Model • First-Difference Estimator: FD-OLS • Consistent statistical inference for general heteroscedasticity, time series and cross section correlation should be based on panel-robust variance-covariance matrix.
First-Difference Model • First-Difference Estimator: GLS
Hypothesis Testing • To Pool or Not to Pool? • F-Test based on dummy variable model: constant or zero coefficients for D w.r.t F(N-1,NT-N-K) • F-test based on fixed effects (unrestricted) model vs. pooled (restricted) model
Hypothesis Testing • Heteroscedasticity • Serial Correlation • Spatial Correlation
Example: Investment Demand • Grunfeld and Griliches [1960] • i = 10 firms: GM, CH, GE, WE, US, AF, DM, GY, UN, IBM; t = 20 years: 1935-1954 • Iit = Gross investment • Fit = Market value • Cit = Value of the stock of plant and equipment