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From |
Tirthankar Chakravarty <tirthankar.chakravarty@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: help for xtlsdvc / Bias corrected FE |

Date |
Sat, 2 May 2009 16:28:38 +0100 |

The Kiviet estimator is not a very good strategy (his own caveat) because it assumes that everything other than the lagged dep. var. (which is included by default) is strictly exogenous. See also: ftp://ftp.unibocconi.it/pub/RePEc/cri/papers/WP165Bruno.pdf To run the -xtlsdvc- with -xtreg, fe- estimates, do the following: /* Begin */ webuse nlswork, clear xtset idcode year // ssc install xtlsdvc, replace g lag_lnw = L.ln_w // inconsistent fixed effects estimator xtreg ln_w lag_lnw age ttl_exp tenure not_smsa south, fe mat my = e(b) // note that 1000 bs reps could take days xtlsdvc ln_w age ttl_exp tenure not_smsa south, initial(my) bias(3) vcov(1000) /* End */ T On Sat, May 2, 2009 at 1:59 PM, olfa alouini <olfasgb@hotmail.com> wrote: > Dear all, > > I have a panel of 15 countries, 40 years of data. I want to estimate the effect of a number of variables on growth rates. > > After running xtserial I believe I have an autocorrelation problem. I have pasted the output in case I interpreted this wrongly: > xtserial GDPgrowth_copr Population Open Output_thkm Delta_inf Deltadef > Wooldridge test for autocorrelation in panel data > H0: no first-order autocorrelation > F( 1, 10) = 141.386 > Prob> F = 0.0000 > > > > To address this issue, I want to run a dynamic. However including a lagged endogenous variable (in this case growth [ i t-1] makes the FE estimator I'd like to use inefficient. I know Kiviet (1995) proposed a way to correct the bias induced by the inclusion of the lagged variable. How can I implement this correction with Stata? > > I tried with the -xtlsdvc- command, but the initial estimation has to be either ah, xtabond or xtabond2, not xtreg,fe. I tried to retrieve my results from xtreg, fe and put them in the "my" matrix form but did not succeed. Any help would be greatly appreciated. > > In addition to that, I was wondering if I had to change my estimation strategy if I estimated my model for only ten years of data (in this case N>T), or is the bias corrected FE estimator still valid and more efficient than GMM for instance? > > Also how many dependent variables can be included in xtlsdvc? and is the lagged variable automatically included? > > Thanks in advance, > > Olfa > > _________________________________________________________________ > Hotmail® has a new way to see what's up with your friends. > http://windowslive.com/Tutorial/Hotmail/WhatsNew?ocid=TXT_TAGLM_WL_HM_Tutorial_WhatsNew1_052009 > > > * > * 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/ > -- To every ω-consistent recursive class κ of formulae there correspond recursive class signs r, such that neither v Gen r nor Neg(v Gen r) belongs to Flg(κ) (where v is the free variable of r). * * 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: help for xtlsdvc / Bias corrected FE***From:*olfa alouini <olfasgb@hotmail.com>

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