CPANEL Procedure
PROC CPANEL Features
The CPANEL procedure fits panel-data regression models by using various techniques, and does the following:
provides an ID statement for specifying the cross section and time variables
provides flexible model-building syntax that supports continuous regressors, classification (CLASS) variables, interactions, and nested effects
fits one-way and two-way fixed-effects models
fits one-way and two-way random-effects models
fits Hausman and Taylor (1981) models
fits Amemiya and MaCurdy (1986) models
fits instrumental variables (IV) regression models
fits dynamic panel models
enables you to fit multiple models by using multiple estimators, all within one procedure call
provides a COMPARE statement for producing customizable comparisons of various models and estimators
provides a TEST statement for performing linear tests of hypotheses
provides a RESTRICT statement for imposing linear parameter constraints
provides an OUTPUT statement for producing a data table that contains predictions and residuals
Because the CPANEL procedure runs on SAS Cloud Analytic Services (CAS), it also does the following:
enables you to run on a cluster of machines that distribute the data and the computations
enables you to run in single-machine mode on CAS
exploits all the available cores and concurrent threads. For information about how PROC CPANEL uses threads, see the section Multithreading in Chapter 4, Shared Concepts.