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From |
Stephen Armah <armah.stephen@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: 2SLS with random effects correcting for autocorrelation |

Date |
Thu, 26 Mar 2009 08:17:57 -0500 |

Dear all, How does one test for the different kinds of endogeneity and what is the order of testing in STATA? The two possible kinds of endogeneity I am dealing with are (i) simultaneity or omitted variable endogeneity (I know I should use the C test) (ii) country-specific endogeneity (I know I should use the Hausman) My dependent variable is growth. I have a cross-section with 31 countries and 6 four-year periods. With regards to (i) above, I have 10 exogenous included RHS variables and many exogenous excluded instruments. Also should I first for auto-correlation and heteroskedasticity in STATA before testing for endogeneity or is is better to do the reverse? Thanks On 3/26/09, Helene Ehrhart <Helene.Ehrhart@u-clermont1.fr> wrote: > Thank you Nicola for these helpful suggestions. > I'll try them! > > Hélène. > > Quoting nicola.baldini2@unibo.it: > >> No suggestions that 100% fit your problem. >> Among second best solutions, you may leave the random effects. In >> such a case, an uncommon choice is to try the -fmivreg- from >> http://www.antonisureda.com/other/stuff/files/ which uses the Fama >> and MacBeth (1973) two step procedure, with instrumental variables >> and Newey-West standard errors. In the first step, for each single >> time period a cross-sectional regression is performed. Then, in the >> second step, the final coefficient estimates are obtained as the >> average of the first step coefficient estimates. >> Fama, Eugene F., and James D. MacBeth, 1973. Risk, Return, and >> Equilibrium: Empirical tests, Journal of Political Economy 81, >> 607-636. >> Other options (not involving the fixed effects) are first >> differencing (-xitvreg2- and -xtabond2-) or cross-sectional commands >> (-ivreg2-, -newey2-), all of them are available from SSC. >> Nicola >> >> P.S. I'll NOT receive/read any email but the Digest. >> >> At 02.33 21/03/2009 -0400, Helene Ehrhart wrote: >>> Dear all, >>> >>> I would like to estimate an equation with instrumental variables using >>> random effects and correcting for autocorrelation. >>> I already tried many ways to do that in stata but no command was able >>> to meet all the three requirements : >>> >>> - - xtivreg , re does not allow for autocorrelation correction >>> - - xtivreg2 does not allow for random effects >>> - - xtdata to transform data so that it corresponds to random effects >>> and then estimation with ivreg28 but then the option bw(1) is not >>> possible since the data are transformed >>> - - estimating the first stage with xtreg ,re ; taking the predicted >>> dependant value and using it as regressors for the 2nd stage using >>> xtregar ,re which corrects for autocorrelation. This works but the >>> standard errors should then be corrected by bootstrapping to correct >>> the bias of using a predicted value as regressor. Unfortunately, >>> traditional bootstrap using a random sample does not maintain the >>> autocorrelation structure. So this method should also be eliminated. >>> >>> If anyone already faced this problem, estimating in 2SLS with random >>> effects correcting for autocorrelation, I would really appreciate to >>> know what is the proper way to do that in Stata. >>> >>> Thanks, >>> >>> Hélène Ehrhart. >> >> >> > > > > > * > * 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**:**Re: st: 2SLS with random effects correcting for autocorrelation***From:*nicola.baldini2@unibo.it

**Re: st: 2SLS with random effects correcting for autocorrelation***From:*Helene Ehrhart <Helene.Ehrhart@u-clermont1.fr>

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