DISCUSSION:
My expectation was that the coefficients estimates from PE.results would be (essentially) the same as the estimates from PE.results_shift but shifted by a year. So PE.results at t+1, t+2,... would equal PE.results_shift at t+0, t+1,... But the estimates are dramatically different (in the first case the wrong sign).
On a quick visual scan, the matched sets are the same in PM.results and PM.results_shift.
y and y1 have similar distributions
> summary(test[,.(y,y1)])
y y1
Min. : 405.7 Min. : 405.7
1st Qu.: 620.9 1st Qu.: 621.4
Median : 740.7 Median : 741.6
Mean : 748.3 Mean : 748.9
3rd Qu.: 867.0 3rd Qu.: 867.4
Max. :1094.0 Max. :1094.0
NA's :2241 NA's :2334
1) Run PanelMatch code from README
2) Create a lead version of y
3) Run PanelMatch code from README but with outcome.var="y1" instead of ="y" (also change dataset to "test")
DISCUSSION: My expectation was that the coefficients estimates from PE.results would be (essentially) the same as the estimates from PE.results_shift but shifted by a year. So PE.results at t+1, t+2,... would equal PE.results_shift at t+0, t+1,... But the estimates are dramatically different (in the first case the wrong sign).
On a quick visual scan, the matched sets are the same in PM.results and PM.results_shift.
y and y1 have similar distributions
Any idea why the coefficients are so different?