I have been thinking about this one and here is an idea.   1) Time and cross-sectionally demean your data.  How to do this is shown here. SAS/ETS(R) 14.1 User's Guide You will likely want to use some form of PROC TIMESERIES or some PROC MEANS calls to do this.  2) Now that the data are "demeaned" a simple OLS estimate would give you your "Two-way FE" estimates.  From here you could then extend this regression by using PROC REG or perhaps better, PROC GLMSELECT SAS/STAT(R) 14.1 User's Guide and use whatever variable selection method you prefer.   In essence, it would force FE into your model, with whatever final specification the algorithm chooses. *would love to see some of your results.  Good luck-Ken ... View more

You are correct that PROC QLIM is the most efficient, accurate and simplest way to accomplish Heckman's 2-step estimator. You will need to correct your standard errors in your second stage.  See the QLIM documentation. SAS/ETS(R) 13.2 User's Guide You might just want to use PROC REG with some HCCME= options to correct your standard errors. SAS/STAT(R) 9.2 User's Guide, Second Edition But you are close as is.  ... View more