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
You need to follow some guidelines when you use PROC PANEL for analysis. For each cross section, PROC PANEL requires at least two time series observations that have nonmissing values for all model variables. There should be at least two cross sections for each time point in the data. If these two conditions are not met, then an error message is printed in the log that states that there is only one cross section or time series observation and further computations will be terminated. You must provide adequate data for an estimation method to produce results, and you should check the log for any errors that are related to data.
If PROC PANEL uses the Parks method and the number of cross sections is greater than the number of time series observations
per cross section, then PROC PANEL produces an error message that states that the 
matrix is singular. This is analogous to seemingly unrelated regression that has fewer observations than equations in the
model. To avoid the problem, reduce the number of cross sections.
Your data set could have multiple observations for each time ID within a particular cross section. However, you can use PROC PANEL only in cases where you have only a single observation for each time ID within each cross section. In such a case, after you have sorted the data, an error warning is printed in the log that states that the data have not been sorted in ascending sequence with respect to time series ID.
The cause of the error is due to multiple observations for each time ID for a given cross section. PROC PANEL allows only one observation for each time ID within each cross section.
The following data set shown in Figure 20.2 illustrates the preceding instance with the correct representation.
In this case, you can observe that there are no multiple observations with respect to a given time series ID within a cross section. This is the correct representation of a data set where PROC PANEL is applicable.
If for state ID 1 you have two observations for the year=1955, then PROC PANEL produces the following error message:
"The data set is not sorted in ascending sequence with respect to time series ID. The current time period has year=1955 and the previous time period has year=1955 in cross section firm=1."
A data set similar to the previous example with multiple observations for the YEAR=1955 is shown in Figure 20.3; this data set results in an error message due to multiple observations while using PROC PANEL.
In order to use PROC PANEL, you need to aggregate the data so that you have unique time ID values within each cross section. One possible way to do this is to run a PROC MEANS on the input data set and compute the mean of all the variables by FIRM and YEAR, and then use the output data set.