How to analyze Panel data using SAS

Step 1: Sort the data properly
eg:
proc sort data=a;
by state date;
run;
Step 2: invoke the TSCSREG procedure and specify the cross section and time series variables in an ID statement. And specify the linear regression model with a MODEL statement: the dependent variable is listed first, followed by an equal sign, followed by the list of regressor variables

eg:
proc tscsreg data=a;
id state date;
model y = x1 x2;
run;

In order to aid in model specification within this class of models, the procedure provides two specification test statistics Rejection of the null hypothesis might suggest that the fixed effects model is more appropriate.
a) F statistic that tests the null hypothesis that the fixed effects parameters are all zero.
b) a Hausman m-statistic that provides information about the appropriateness of the random effects specification

Fixed effects: the models are essentially regression models with dummy variables corresponding to the specified effects

Random effects:
We include a classical error term with zero mean and a homoscedastic covariance matrix
One-Way model: we also include error term with the index of cross section
Two-Way model: We include also error term with the time change

Usually you cannot explicitly specify all the explanatory variables that affect the dependent variable. The omitted or unobservable variables are summarized in the error disturbances. The TSCSREG procedure used with the Fuller-Battese method adds the individual and time-specific random effects to the error disturbances, and the parameters are efficiently estimated using the GLS method

Step 3: The following statements are used with the TSCSREG procedure.
PROC TSCSREG options;
BY variables;
ID cross-section-id-variable time-series-id-variable;
MODEL dependent = regressor-variables / options;
label: TEST equation [,equation... ];