*
*  Example 7.7
*  J. Wooldridge, Econometrics of Cross Section and Panel Data
*
*  Note: The sample data files include all required data transformations.
*        However, in many cases we show how these data transformations would
*        be created in RATS from the basic data, as this is something you will
*        need to know how to do in practice.
*
cal(panelobs=3) 1987
all 157//3
open data jtrain1.raw
data(format=free,org=columns) / year fcode employ sales	avgsal scrap rework $
 tothrs union grant d89 d88 totrain hrsemp lscrap lemploy lsales lrework lhrsemp $
 lscrap_1 grant_1 clscrap cgrant clemploy clsales lavgsal clavgsal cgrant_1 chrsemp clhrsemp
*
* These aren't really necessary, as they're included in the complete data set, but
* these show how they would be generated in RATS from the basic data.
*
set allthree = %valid(scrap(%indiv(t)//1)+scrap(%indiv(t)//2)+scrap(%indiv(t)//3))
set d89 = %period(t)==3
set d88 = %period(t)==2
set lscrap = log(scrap)
*
* If you use the RATS lag notation for the lag of grant, it will knock out all
* 1987 data points, since grant{1} will be pre-sample. However, the value of that
* lag is known to be zero for all data points, so we create a separate value
* which is 0 for all 1987 data points, and the lag of grant otherwise.
*
set grant_1 = %if(%period(t)==1,0,grant{1})
*
linreg lscrap
# constant d88 d89 grant grant_1