The PANEL Procedure

(View the complete code for this example.)

The following DATA step creates the data set Electricity from the cost function data in Greene (1990). The variable Production is the log of output in millions of kilowatt-hours, and the variable Cost is the log of cost in millions of dollars.

data Electricity;
   input firm year production cost @@;
datalines;
1 1955   5.36598   1.14867  1 1960   6.03787   1.45185
1 1965   6.37673   1.52257  1 1970   6.93245   1.76627
2 1955   6.54535   1.35041  2 1960   6.69827   1.71109
2 1965   7.40245   2.09519  2 1970   7.82644   2.39480
3 1955   8.07153   2.94628  3 1960   8.47679   3.25967
3 1965   8.66923   3.47952  3 1970   9.13508   3.71795
4 1955   8.64259   3.56187  4 1960   8.93748   3.93400
4 1965   9.23073   4.11161  4 1970   9.52530   4.35523
5 1955   8.69951   3.50116  5 1960   9.01457   3.68998
5 1965   9.04594   3.76410  5 1970   9.21074   4.05573
6 1955   9.37552   4.29114  6 1960   9.65188   4.59356
6 1965  10.21163   4.93361  6 1970  10.34039   5.25520
;

Consider the model

where represents cost, represents production, is the cross-sectional error component, and is the error variance component.

The first step is to make sure the data are sorted by firms and years within firms:

proc sort data = Electricity;
   by firm year;
run;

If you assume that the cross-sectional effects are random, four possible estimators are available for the variance components. The VCOMP=FB option in the following statements uses the Fuller and Battese (1974) estimator to fit the model:

proc panel data = Electricity;
   id firm year;
   model cost = production / ranone vcomp = fb;
run;

The output of these statements is shown in Figure 26.1.

Printed first is a report that provides the estimation method and various data counts. Fit statistics and variance components estimates are printed next. A Hausman specification test compares this model to its fixed-effects counterpart. Finally, the table of regression parameter estimates shows the estimates, standard errors, and t tests.