文档介绍：© 2005 The Trustees of Indiana University (12/10/2005) Linear Regression Model for Panel Data: 1
Linear Regression Models for Panel Data Using SAS,
STATA, LIMDEP, and SPSS
Hun Myoung Park
This document summarizes linear regression models for panel data and illustrates how to
estimate each model using SAS , STATA , LIMDEP , and SPSS . This document
does not address nonlinear models (., logit and probit models), but focuses on linear
regression models.
1. Introduction
2. Least Squares Dummy Variable Regression
3. Panel Data Models
4. The Fixed Group Effect Model
5. The Fixed Time Effect Model
6. The Fixed Group and Time Effect Model
7. Random Effect Models
8. The Poolability Test
9. Conclusion
1. Introduction
Panel data are cross sectional and longitudinal (time series). Some examples are the cumulative
General Social Survey (GSS) and Current Population Survey (CPS) data. Panel data may have
group effects, time effects, or the both. These effects are analyzed by fixed effect and random
effect models.
Data Arrangement
A panel data set contains observations on n individuals (., firms and states), each measured
at T points in time. In other word, each individual (1 through n subject) includes T observations
(1 through t time period). Thus, the total number of observations is nT. Figure 1 illustrates the
data arrangement of a panel data set.
Figure 1. Data Arrangement of Panel Data
Group Time Variable1 Variable2 Variable3 …
1 1 …………
1 2 …………
………………
1 T …………
2 1 …………
2 2 …………
... ……………
2 T …………
………………
/~statmath
© 2005 The Trustees of Indiana University (12/10/2005) Linear Regression Model for Panel Data: 2
………………
n 1 …………
n 2 …………
………………
n T …………
Fixed Effect versus Random Effect Models
Panel data models estimate fixed and/or random effects models using dummy variables. The
core difference between fixed and