The PANEL Procedure
- Overview
- Getting Started
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Syntax
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DetailsSpecifying the Input DataSpecifying the Regression ModelUnbalanced DataMissing ValuesComputational ResourcesRestricted EstimatesNotationOne-Way Fixed-Effects ModelTwo-Way Fixed-Effects ModelBalanced PanelsUnbalanced PanelsFirst-Differenced Methods for One-Way and Two-Way ModelsBetween EstimatorsPooled EstimatorOne-Way Random-Effects ModelTwo-Way Random-Effects ModelParks Method (Autoregressive Model)Da Silva Method (Variance-Component Moving Average Model)Dynamic Panel EstimatorLinear Hypothesis TestingHeteroscedasticity-Corrected Covariance MatricesHeteroscedasticity- and Autocorrelation-Consistent Covariance MatricesR-SquareSpecification TestsPanel Data Poolability TestPanel Data Cross-Sectional Dependence TestPanel Data Unit Root TestsLagrange Multiplier (LM) Tests for Cross-Sectional and Time EffectsTests for Serial Correlation and Cross-Sectional EffectsTroubleshootingCreating ODS GraphicsOUTPUT OUT= Data SetOUTEST= Data SetOUTTRANS= Data SetPrinted OutputODS Table Names
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Example
- References
PROC PANEL writes the transformed series to an output data set. That is, if the user selects FIXONE, FIXONETIME, or RANONE and supplies the OUTTRANS = option, the transformed dependent variable and independent variables are written out to a SAS data set; other variables in the input data set are copied unchanged.
Say that your data set contains variables y, x1, x2, x3, and z2. The following statements result in a SAS data set:
proc panel data=datain outtrans=dataout;
id cs ts;
model y = x1 x2 x3 / fixone;
run;
First, z2 is copied over. Then _Int, x1, x2, y, and x3, are replaced with their mean deviates (from cross sections). Furthermore, two new variables are created.
- _MODELL_
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is the model’s label (if it exists).
- _METHOD_
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is the model’s transformation type. In the FIXONE case, this is _FIXONE_ or _FIXONETIME_. If the model RANONE model is selected, the _METHOD_ variable is either _Ran1FB_, _Ran1WK_, _Ran1WH_, or _Ran1NL_, depending on the variance component estimators chosen.