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From |
"Rodrigo A. Alfaro" <raalfaroa@gmail.com> |

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

Subject |
Re: st: Panel with low within variance and -xtfmb- |

Date |
Thu, 15 Nov 2007 21:40:35 -0300 |

Late, but not too late. FEVD procedure is different than taking FE "by hand". You have a difficult problem, which is small within variation in your x's. Probably you should try to deal with the endogeneity using IV variables once you take an average of your data (sort of BE estimator). With some within variation, you could also work with the Hausman-Taylor estimator (xthtaylor). Good luck, RA.

----- Original Message ----- From: "Ivan Etzo" <ivanetzo@hotmail.com>

To: <statalist@hsphsun2.harvard.edu>; <nicola.baldini2@unibo.it>

Sent: Tuesday, October 09, 2007 5:10 PM

Subject: Re: st: Panel with low within variance and -xtfmb-

Thank you Nicola,

I read the paper and used the command -xtfevd-. I then runned a fixed effect

estimation using -regress- with -xi:- to generate groups dummies, which

allows for the estimation of time invariant variables, but I found quite

different coefficient for the time invariant (while time variant are the

same). I'm now wondering which is the difference of using the two different

techinques..

Moreover, estimates of time variant variables from -xtfevd- are the same as

those obtained with -xtreg- ( fe opt). I understand that -xtreg- is a within

estimation which takes into account only variation across time (years)

within each individual, the point is that my time variant variables are

almost time invariant", that is their within variation is very small

compared to the between one.

Ivan

-------Original Message-------

From: nicola.baldini2@unibo.it

Date: 10/06/07 13:12:03

To: statalist@hsphsun2.harvard.edu

Cc: ivanetzo@hotmail.com

Subject: Re: st: Panel with low within variance and -xtfmb-

Package -xtfevd- from http://www.polsci.org/pluemper may help. It is a

module to estimate time-invariant and rarely changing variables in panel

data models with fixed effects.

Nicola

At 02.33 05/10/2007 -0400, "Ivan Etzo" wrote:

Hi, I'd like to test a basic form of my model (panel T=3D7 N=3D380) with= one

regressor that is time invariant and two regressors that have low wi= thin variance with the following percentage

Y: 15% X1: 0.6% X2:0.6% X3:0 hausman test rejects the RE model (using -xtreg-) so I cannot estima= te

the model with the time invariant regressor that for me it's very impo= rtant.

I tried the -xtfmb- which is an implementation of the Fama and MacBe= th

(1973) two step procedure, I report the very clear description of the = command from the help

-xtfmb- "is an implementation of the Fama and MacBeth (1973) two ste= p

procedure. The procedure is

as follows: In the fi= rst step, for each single time period a

cross-sectional regression is

= performed. Then, in the second step, the final coeffic= ient

estimates are obtained as the

average of the f= irst step coefficient estimates." The coefficient I obtain from this procedure are practically the sam= e

with the RE model.. I attached the results below. I wonder whethe= r the -xtfmb- produces inconsistent estimates as well.. any help would be= very appreciated.

Ivan Random-effects GLS regression = ;Number of obs =3D 2660 Group varia= ble (i): region Number of groups =3D 380 R-sq: within =3D 0.0097 Obs per group: min =3D = 7 between =3D 0.8153 avg =3D 7.0 overall =3D 0.= 7953 max =3D 7 Random effects u_i ~ Gaussian Wald chi2(3) &nbs= p; =3D 1665.29 corr(u_i, X) =3D 0 (assumed= ) Prob > chi2 =3D = 0.0000 lnmig | Coef. Std. Err. = z P>|z| [95% Conf. Inte= rval] lndpop | .9560363 .033868= 9 28.23 0.000 .8896544 1.02= 2418 lnopop | 1.023108 .0338689 30.21 = ; 0.000 .9567262 1.08949 lndist | -.= 3231335 .0587596 -5.50 0.000 &nbs= p; -.4383002 -.2079668 _cons | -21.17337 .= 799259 -26.49 0.000 -22.73989 -19= =2E60685 sigma_u | .68680964 sigma_e |&n= bsp;.27499318 rho | .86183578 (fraction of varia= nce due to u_i) Fama-MacBeth (1973) Two-Step procedure&nbs= p;Number of obs =3D 2660 Num.= time periods =3D 7 F( 3, &nbs= p; 6) =3D 11189.96 Prob > = F =3D 0.0000 avg. R-squared =3D 0.7962 &= nbsp; | &nb= sp; Fama-MacBeth lnmig | = ; Coef. Std. Err. t P>|= t| [95% Conf. Interval] = ; lndpop | .9552167 .0101939 &= nbsp; 93.70 0.000 .9302731 .9801604 = lnopop | 1.017995 .0061794 164.7= 4 0.000 1.002874 1.033115 lndist&nbs= p;| -.3232731 .0117134 -27.60 0.000&nb= sp; -.3519349 -.2946114 _cons | -21.08686&= nbsp; .1716352 -122.86 0.000 -21.50683= -20.66688

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