The HPPANEL Procedure
- Overview
- Getting Started
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Syntax
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DetailsSpecifying the Input DataSpecifying the Regression ModelSpecifying the Number of Nodes and Number of ThreadsUnbalanced DataOne-Way Fixed-Effects ModelTwo-Way Fixed-Effects ModelBalanced PanelsUnbalanced PanelsOne-Way Random-Effects ModelTwo-Way Random-Effects ModelBetween EstimatorsPooled EstimatorLinear Hypothesis TestingSpecification TestsOUTPUT OUT= Data SetOUTEST= Data SetPrinted OutputODS Table Names
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Example
- References
Unbalanced Data
The HPPANEL procedure can process data that have different numbers of time series observations across different cross sections. The missing time series observations are recognized by the absence of time series ID variable values in some of the cross sections in the input data set. Moreover, if an observation that has a particular time series ID value and cross-sectional ID value is present in the input data set but one or more of the model variables are missing, that time series point is treated as missing for that cross section.