1. Panel Data Analysis Using GAUSS4
Kuan-Pin Lin Portland State University

2. Panel Data Analysis Hypothesis Testing
Panel Data Model Specification
Pool or Not To Pool
Random Effects vs. Fixed Effects
Heterscedasticity
Time Serial Correlation
Spatial Correlation

3. Fixed Effects vs. Random Effects
Hypothesis Testing
Estimator
Random Effects
E(ui|Xi) = 0
Fixed Effects
E(ui|Xi) =/= 0
GLS or RE-LS
(Random Effects)
Consistent and Efficient
Inconsistent
LSDV or FE-LS
(Fixed Effects)
Consistent
Inefficient
Possibly Efficient

4. Random Effects vs. Fixed Effects
Fixed effects estimator is consistent under H0 and H1; Random effects estimator is efficient under H0, but it is inconsistent under H1.
Hausman Test Statistic

5. Random Effects vs. Fixed Effects
Alternative Hausman Test (Mundlak Approach)
Estimate the random effects model with the group means of time variant regressors:
F Test that g = 0

6. Hypothesis Testing
Fixed Effects Model
Random Effects Model

7. Heteroscedasticity The Null Hypothesis
Based on the auxiliary regression
LM test statistic is NR2 ~ 2(K), N is total number of observation (i,t)s.

8. Cross Sectional Correlation
The Null Hypothesis
Based on the estimated correlation coefficients
Breusch-Pagan LM Test (Breusch, 1980)
As T  ∞ (N fixed)

9. Cross Sectional Correlation
Bias adjusted Breusch-Pagan LM Test (Pesaran, et.al. 2008)

10. Time Serial Correlation
The Model and Null Hypothesis
LM Test Statistic

11. Joint Hypothesis Testing Random Effects and Time Serial Correlation
The Model
Joint Test for AR(1) and Random Effects

12. Joint Hypothesis Testing Random Effects and Time Serial Correlation
Based on OLS residuals :

13. Joint Hypothesis Testing Random Effects and Time Serial Correlation
Marginal Tests for AR(1) & Random Effects
Robust Test for AR(1) & Random Effects
Joint Test Equivalence

14. Panel Data Analysis Extensions
Seeming Unrelated Regression
Allowing Cross-Equation Dependence
Fixed Coefficients Model
Dynamic Panel Data Analysis
Using FD Specification
IV and GMM Methods
Spatial Panel Data Analysis
Using Spatial Weights Matrix
Spatial Lag and Spatial Error Models

15. References
Baltagi, B., Li, Q. (1995) Testing AR(1) against MA(1) disturbances in an error component model. Journal of Econometrics, 68,
Baltagi, B., Bresson, G., Pirotte, A. (2006) Joint LM test for homoscedasticity in a one-way error component model. Journal of Econometrics, 134,
Bera, A.K., W. Sosa-Escudero and M. Yoon (2001), Tests for the error component model in the presence of local misspecification, Journal of Econometrics 101, 1–23.
Breusch, T.S. and A.R. Pagan (1980), The Lagrange multiplier test and its applications to model specification in econometrics, Review of Economic Studies 47, 239–253.
Pesaran, M.H. (2004), General diagnostic tests for cross-section dependence in panels, Working Paper, Trinity College, Cambridge.
Pesaran, M.H., Ullah, A. and Yamagata, T. (2008), A bias-adjusted LM test of error cross-section independence, The Econometrics Journal,11, 105–127.