The PANEL Procedure
- Overview
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Getting Started
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Syntax
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Details
Missing Values Computational Resources Restricted Estimates Notation The One-Way Fixed-Effects Model The Two-Way Fixed-Effects Model Balanced Panels Unbalanced Panels Between Estimators Pooled Estimator The One-Way Random-Effects Model The Two-Way Random-Effects Model Parks Method (Autoregressive Model) Da Silva Method (Variance-Component Moving Average Model) Dynamic Panel Estimator Linear Hypothesis Testing Heteroscedasticity-Corrected Covariance Matrices R Square Specification Tests Troubleshooting ODS Graphics The OUTPUT OUT= Data Set The OUTEST= Data Set The OUTTRANS= Data Set Printed Output ODS Table Names
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Examples
- References
| Missing Values |
Any observation in the input data set with a missing value for one or more of the regressors is ignored by PROC PANEL and is not used in the model fit.
If there are observations in the input data set with missing dependent variable values but with nonmissing regressors, PROC PANEL can compute predicted values and store them in an output data set by using the OUTPUT statement. Note that the presence of such observations with missing dependent variable values does not affect the model fit because these observations are excluded from the calculation.
If either some regressors or the dependent variable values are missing, the model is estimated as unbalanced where the number of time series observations across different cross sections does not have to be equal. The Parks and Da Silva methods cannot be used with unbalanced data.