11-03-2016 09:28 AM
I have panel data such that two cross sections of a firm are analyzed over time, and the response variable takes on non-negative integer values (i.e. count data.). I'd like to estimate this model using Poisson Regression:
The data looks like this:
data model_data; input date counts x1 x2 x3; datalines; January-01 14 0 6.5 .45 January-01 21 1 6.5 .45
March-04 24 0 4.5 .55
March-04 26 1 4.5 .55
ln(counts) = B0 + B1 x1 + B2 x2 + B3 x3 ...
I've estimated this model in SAS with the following code:
proc genmod data = model_data; class x1 / param=glm; model counts = x1 x2 x3 / dist=poisson link=log scale=pearson type1 type3 ; output put=poisson_out;
Where x1 is the cross section of the data analyzed over time, and x2 and x3 are continuous predictor variables, using a pearson correction for overdispersion. Is PROC GENMOD able to analyze this type of data? I have found plenty of examples for purely cross sectional data, but there is an absence of discussion about using this for panel data. If PROC GENMOD is not capable of analyzing panel data, is PROC TCOUNTREG a viable alternative?