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| From | David Torres <writeon4truth2@msn.com> |
| To | "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu> |
| Subject | st: First-stage F from -xtivreg- versus AP F |
| Date | Tue, 21 Jan 2014 09:28:56 -0500 |
Statalisters, I'm using -xtivreg- to estimate a 2SLS random effects model in Stata 13.0. I'm needing help getting the first stage F statistic in addition to the Angrist-Pischke F I can get from the postestimation command -xtoverid- (more on this below). . which xtivreg /Applications/Stata/ado/base/x/xtivreg.ado *! version 1.6.2 14apr2011 . which xtoverid /Users/diego/Library/Application Support/Stata/ado/plus/x/xtoverid.ado *! xtoverid version 2.1.6 2Nov2011 *! Authors Mark Schaffer and Steve Stillman *! Derived from overidxt and overid Here is the most basic conditional model in which I am regressing vertically scaled reading scores on year and year-squared. The endogenous regressor, diffsch, denotes whether a student attended an out-of-zone magnet school. It is instrumented with the log difference in distance between the zoned school and the nearest magnet school and the log distance to the enrolled school: . xtivreg srsc year yearsq (diffsch=diffdist dist_enrld), re first First-stage G2SLS regression Number of obs = 27830 Wald chi(4) = 7182 Prob> chi2 = 0.0000 ------------------------------------------------------------------------------ diffsch | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- year | .0010897 .0023365 0.47 0.641 -.0034898 .0056692 yearsq | .0009441 .0005764 1.64 0.101 -.0001858 .0020739 diffdist | .004433 .001686 2.63 0.009 .0011284 .0077376 dist_enrld | .162999 .0019443 83.84 0.000 .1591883 .1668097 _cons | .1364031 .0035329 38.61 0.000 .1294787 .1433274 ------------------------------------------------------------------------------ G2SLS random-effects IV regression Number of obs = 27830 Group variable: short_id Number of groups = 6168 R-sq: within = 0.8770 Obs per group: min = 3 between = 0.2215 avg = 4.5 overall = 0.6533 max = 5 Wald chi2(3) = 154192.94 corr(u_i, X) = 0 (assumed) Prob> chi2 = 0.0000 ------------------------------------------------------------------------------ srsc | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- diffsch | 9.999284 1.941415 5.15 0.000 6.19418 13.80439 year | 74.19692 .3811099 194.69 0.000 73.44996 74.94389 yearsq | -7.926549 .0940278 -84.30 0.000 -8.11084 -7.742258 _cons | 475.1334 .6555358 724.80 0.000 473.8486 476.4182 -------------+---------------------------------------------------------------- sigma_u | 37.264026 sigma_e | 25.567877 rho | .67991546 (fraction of variance due to u_i) ------------------------------------------------------------------------------ Instrumented: diffsch Instruments: year yearsq diffdist dist_enrld ------------------------------------------------------------------------------ Now I would like to get the first stage F-statistic, but the first option above does not appear to give it. If I use the postestimation command -xtoverid- with the noisily option, as shown below, I do get the Angrist-Pischke F, but in my write-up I'd like to show the regular F-stat to test joint significance of the instruments. . xtoverid, nois First-stage regressions ----------------------- First-stage regression of __00000I: OLS estimation -------------- Estimates efficient for homoskedasticity only Statistics consistent for homoskedasticity only Number of obs = 27830 F( 5, 27825) = 2097.56 Prob> F = 0.0000 Total (centered) SS = 875.5555503 Centered R2 = 0.2037 Total (uncentered) SS = 960.0415225 Uncentered R2 = 0.2737 Residual SS = 697.2383726 Root MSE = .1583 ------------------------------------------------------------------------------ __00000I | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- __00000R | .0010897 .0023365 0.47 0.641 -.00349 .0056694 __00000U | .0009441 .0005764 1.64 0.101 -.0001858 .0020739 __00000E | .1364031 .0035329 38.61 0.000 .1294784 .1433277 __00000L | .004433 .001686 2.63 0.009 .0011283 .0077377 __00000O | .162999 .0019443 83.84 0.000 .1591881 .1668098 ------------------------------------------------------------------------------ Included instruments: __00000R __00000U __00000E __00000L __00000O ------------------------------------------------------------------------------ F test of excluded instruments: F( 2, 27825) = 3528.57 Prob> F = 0.0000 Angrist-Pischke multivariate F test of excluded instruments: F( 2, 27825) = 3528.57 Prob> F = 0.0000 Summary results for first-stage regressions ------------------------------------------- (Underid) (Weak id) Variable | F( 2, 27825) P-val | AP Chi-sq( 2) P-val | AP F( 2, 27825) __00000I | 3528.57 0.0000 | 7058.41 0.0000 | 3528.57 Stock-Yogo weak ID test critical values for single endogenous regressor: 10% maximal IV size 19.93 15% maximal IV size 11.59 20% maximal IV size 8.75 25% maximal IV size 7.25 Source: Stock-Yogo (2005). Reproduced by permission. Underidentification test Ho: matrix of reduced form coefficients has rank=K1-1 (underidentified) Ha: matrix has rank=K1 (identified) Anderson canon. corr. LM statistic Chi-sq(2)=5630.40 P-val=0.0000 Weak identification test Ho: equation is weakly identified Cragg-Donald Wald F statistic 3528.57 Stock-Yogo weak ID test critical values for K1=1 and L1=2: 10% maximal IV size 19.93 15% maximal IV size 11.59 20% maximal IV size 8.75 25% maximal IV size 7.25 Source: Stock-Yogo (2005). Reproduced by permission. Weak-instrument-robust inference Tests of joint significance of endogenous regressors B1 in main equation Ho: B1=0 and orthogonality conditions are valid Anderson-Rubin Wald test F(2,27825)= 13.53 P-val=0.0000 Anderson-Rubin Wald test Chi-sq(2)= 27.06 P-val=0.0000 Stock-Wright LM S statistic Chi-sq(2)= 27.03 P-val=0.0000 Number of observations N = 27830 Number of regressors K = 4 Number of endogenous regressors K1 = 1 Number of instruments L = 5 Number of excluded instruments L1 = 2 IV (2SLS) estimation -------------------- Estimates efficient for homoskedasticity only Statistics consistent for homoskedasticity only Number of obs = 27830 F( 4, 27826) = 3.6e+05 Prob> F = 0.0000 Total (centered) SS = 122387579.2 Centered R2 = 0.8485 Total (uncentered) SS = 976762125.4 Uncentered R2 = 0.9810 Residual SS = 18546537.84 Root MSE = 25.82 ------------------------------------------------------------------------------ __00000G | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- __00000I | 9.999284 1.941276 5.15 0.000 6.194454 13.80412 __00000R | 74.19692 .3810826 194.70 0.000 73.45002 74.94383 __00000U | -7.926549 .094021 -84.31 0.000 -8.110827 -7.742271 __00000E | 475.1334 .6554887 724.85 0.000 473.8487 476.4181 ------------------------------------------------------------------------------ Underidentification test (Anderson canon. corr. LM statistic): 5630.398 Chi-sq(2) P-val = 0.0000 ------------------------------------------------------------------------------ Weak identification test (Cragg-Donald Wald F statistic): 3528.573 Stock-Yogo weak ID test critical values: 10% maximal IV size 19.93 15% maximal IV size 11.59 20% maximal IV size 8.75 25% maximal IV size 7.25 Source: Stock-Yogo (2005). Reproduced by permission. ------------------------------------------------------------------------------ Sargan statistic (overidentification test of all instruments): 0.577 Chi-sq(1) P-val = 0.4474 ------------------------------------------------------------------------------ Instrumented: __00000I Included instruments: __00000R __00000U __00000E Excluded instruments: __00000L __00000O ------------------------------------------------------------------------------ Test of overidentifying restrictions: Cross-section time-series model: xtivreg g2sls Sargan-Hansen statistic 0.577 Chi-sq(1) P-value = 0.4474 Can anyone tell me how to get what I want, the regular first stage F-stat, from all this? I'd very much appreciate your help. Thanks for your consideration, folks, Diego Torres * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/faqs/resources/statalist-faq/ * http://www.ats.ucla.edu/stat/stata/