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From |
Cameron McIntosh <cnm100@hotmail.com> |

To |
STATA LIST <statalist@hsphsun2.harvard.edu> |

Subject |
RE: st: Endogeneity and Panel Data : treatreg, ivregress or .. ? Any suggestion would be really appreciated ! |

Date |
Mon, 14 Nov 2011 08:11:59 -0500 |

John, Thanks for clarifying. I think you still need to account for dependencies/serial correlation, but note that with 70 data points, I think you are now in the realm of large N, large T panel models. I don't think you can rely on the asymptotics that were developed for just the large N fixed (small) T case, and you would need specialized resampling methods as well, if you want to go that route (other types of robust SE estimators might be preferable): Kapetanios, G. (2008). A Bootstrap Procedure for Panel Data Sets with Many Cross-Sectional Units. Econometrics Journal, 11(2), 377-395. Hansen, C.B. (2007). Asymptotic properties of a robust variance matrix estimator for panel data when T is large. Journal of Econometrics, 141, 597–620. http://www.utdallas.edu/~d.sul/Econo2/Hansen-2007-JoE-PanelHAC.pdf http://faculty.chicagobooth.edu/christian.hansen/research/techapp_panel_cov_t.pdf http://faculty.chicagobooth.edu/christian.hansen/research/stock_watson_note.pdf Cam > From: cariboupad@gmx.fr > Date: Mon, 14 Nov 2011 12:02:12 +0100 > Subject: Re: st: Endogeneity and Panel Data : treatreg, ivregress or .. ? Any suggestion would be really appreciated ! > To: statalist@hsphsun2.harvard.edu > > Dear Cameron, > > Thanks for you answer. > Let me precise thus the following > > The average number of points per individual is about 70. There is no > doubt that choices of the endogenous variable whithin an individual > are correlated : some will always choose 2 particular values, some > will choose other values, etc. > The endonegous variable is not naturally ordered. > > When I run treatreg as described before, without any correction for > clustering, t stats are great > Of course when I add the option vce(bootstrap cluster(id) reps(400) ) > every significance vanish (maybe my instrument is not as good as > expected?)... but do I really need to correct for clustering here? > I mean, treatreg is not really designed for panel data right ? > > Thx > > On 14 November 2011 06:08, Cameron McIntosh <cnm100@hotmail.com> wrote: > > John, > > I strongly suggest that you take a look at the following (as for clustered observations and missing data, you haven't really described the dataset enough to be able to comment -- how many time points are there?): > > Greene, W.H., & Hensher, D.A. (2010). Modeling Ordered Choices: A Primer. Cambridge, UK: Cambridge University Press. > > Chesher, A., & Smolinski, K. (2012). IV models of ordered choice. Journal of Econometrics, 166(1), 33-48. > > Carrasco, R. (2001). Binary Choice With Binary Endogenous Regressors in Panel Data. Journal of Businessand Economic Statistics, 19(4), 385-394. > > Chesher, A., Rosen, A., & Smolinski, K. (February 11, 2011). An instrumental variable model of multiple discrete choice. cemmap working paper CWP06/11. The Institute for Fiscal Studies Department of Economics, UCL. http://www.ihs.ac.at/vienna/resources/Economics/Papers/20111117_Paper_Rosen.pdf > > Mullahy, J. (2001). [Estimation of Limited Dependent Variable Models with Dummy Endogenous Regressors: Simple Strategies for Empirical Practice]: Comment. Journal of Business & Economic Statistics, 19(1), 23-25. > > Altonji, J.G., & Matzkin, R.L. (2005). Cross Section And Panel Data Estimators For Nonseparable Models With Endogenous Regressors. Econometrica, 73(4), 1053-1101.http://down.cenet.org.cn/upfile/94/2005711152046101.pdf > > Dong, Y., & Lewbel, A. (April 2011). Simple Estimators for Binary Choice Models With Endogenous Regressors.http://fmwww.bc.edu/ec-p/wp604.pdf > > Lewbel, A. (March 2011). Binary Choice With Endogenous Or Mismeasured Regressors.http://www.indiana.edu/~caepr/visitors/2011/downloads/LewbelBinaryChoice.pdf > > Cam > > > > ---------------------------------------- > >> From: cariboupad@gmx.fr > >> Date: Sun, 13 Nov 2011 15:41:46 +0100 > >> Subject: st: Endogeneity and Panel Data : treatreg, ivregress or .. ? Any suggestion would be really appreciated ! > >> To: statalist@hsphsun2.harvard.edu > >> > >> Dear Stata List, > >> Dear Mark Schaffer (I guess ;-) ) > >> > >> I have a econometric question related to endogenous variables and > >> panel data, and I believe that it can be interesting for anyone who > >> uses longitudinal data. > >> > >> Here's the context : > >> > >> I have a panel dataset of individuals who, at any time t, could > >> endogenously chose the value of a variable E (for endogenous). E is > >> not ordered and could take few values (in my case, 6 possible > >> choices). > >> > >> I am particularly interested in the effect of one of these choices on > >> a fully continuous outcome variable Y. > >> > >> That is, at any time and for any individual I would like to estimate > >> > >> Yit=a+bXit+cZit+eit > >> > >> where for example, Z is a binary variable that is equals to 1 if > >> individual i chooses E="the value of interest" at time t, and zero > >> otherwise. variables in X are assumed to be exogenous. > >> I believe I have a good instrument for Z, along for other control > >> demographic variables, and therefore I guess I have basically two > >> choices in order to take into account the panel nature of my dataset > >> > >> 1) using ivregress2 with the option cluster(id) and correcting for the > >> endogenous part with (Z= instrument + age + location of birth). > >> However Z is a dummy variable... I know this should not be a problem > >> but... > >> 2) using treatreg with the option vce(bootstrap, cluster(id) > >> reps(400)) and modeling the choice of E=2 (that is Z=1) with treat(Z= > >> instrument + age + location of birth) > >> 3) I tried to use xtivreg 2 with fixed effects, but location of birth > >> is time invariant (and I believe very important in order to understand > >> Z) so it cannot be estimated. > >> > >> Is my approach correct ? Do you have eventually other ways to tacke > >> this multiple choice endogenous problem ? > >> > >> Moreover, in the context of panel data, do I always need to use > >> clustering on id in order to have correct standard errors ? > >> My dataset is large, but I have much more time variation than > >> clusters. About 200 000 individuals and 10 million observations for > >> the whole dataset. > >> The period where the instrument is available reduces the dataset > >> considerably : 1 million observations and about 20 000 individuals. > >> An important remark : the panel is NOT balanced. So individuals could > >> come in and out of the dataset during the 10 year period covered by my > >> dataset. Some have thus very few observations, and some have hundreds > >> of rows. > >> > >> > >> > >> Many thanks in advance for your suggestions, > >> > >> Best, > >> * > >> * For searches and help try: > >> * http://www.stata.com/help.cgi?search > >> * http://www.stata.com/support/statalist/faq > >> * http://www.ats.ucla.edu/stat/stata/ > > > > * > > * For searches and help try: > > * http://www.stata.com/help.cgi?search > > * http://www.stata.com/support/statalist/faq > > * http://www.ats.ucla.edu/stat/stata/ > > > > * > * For searches and help try: > * http://www.stata.com/help.cgi?search > * http://www.stata.com/support/statalist/faq > * http://www.ats.ucla.edu/stat/stata/ * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**References**:**st: Endogeneity and Panel Data : treatreg, ivregress or .. ? Any suggestion would be really appreciated !***From:*John Litfiba <cariboupad@gmx.fr>

**RE: st: Endogeneity and Panel Data : treatreg, ivregress or .. ? Any suggestion would be really appreciated !***From:*Cameron McIntosh <cnm100@hotmail.com>

**Re: st: Endogeneity and Panel Data : treatreg, ivregress or .. ? Any suggestion would be really appreciated !***From:*John Litfiba <cariboupad@gmx.fr>

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