Timeline for Practical issues with dynamic panel data modeling
Current License: CC BY-SA 4.0
9 events
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| Jun 11, 2020 at 14:32 | history | edited | CommunityBot |
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| S Aug 26, 2019 at 22:32 | history | suggested | ptrj | CC BY-SA 4.0 |
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| Aug 26, 2019 at 21:38 | review | Suggested edits | |||
| S Aug 26, 2019 at 22:32 | |||||
| Jul 20, 2014 at 5:01 | vote | accept | generic_user | ||
| Jul 20, 2014 at 3:55 | comment | added | jayk | I don't have much experience with the bias corrected estimators. The Blundell-Bond estimator will be easy to apply if your data is already formatted for Arellano-Bover. I mostly suggested the Behr paper because I think it's a pretty clear presentation of the Arellano-Bover and Blundell-Bond estimators, rather than because I thought bias corrected estimators were a particularly compelling alternative. | |
| Jul 20, 2014 at 3:42 | comment | added | jayk | Hey ACD I've changed the answer to reflect these two questions. The gist? You can use the same number of lags for the instrument (dated t-2 and back) even if you have a large number of lags in your regression equation - because the important thing is the number of lags of the error term, which is always going to be first-differenced. I also suggested two alternative estimators that use a larger set of moment conditions. | |
| Jul 20, 2014 at 3:37 | history | edited | jayk | CC BY-SA 3.0 |
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| Jul 20, 2014 at 2:58 | comment | added | generic_user | Thanks a lot for the answer. I'm still stuck on one question however -- with 3 lags, say, of the the dv, I suppose that I can only instrument with the 4th and backwards? This means that my instruments for the first lag (the most important) will be quite weak. Right? I've also been looking at bias estimators/corrections of those proposed by originally by Kiviet, but those seem to rely on a consistent first-step gmm estimate, which I don't have is Sargan and AR2 tests fail | |
| Jul 19, 2014 at 7:07 | history | answered | jayk | CC BY-SA 3.0 |