Re: [Gretl-users] Gretl-users Digest, Vol 111, Issue 13 Hausman Test in IV estimation

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Instrumental variables and Hausman test (Javier Garc?a) ---------------------------------------------------------------------- Message: 1 Date: Wed, 13 Apr 2016 02:28:36 +0200 From: Javier Garc?a <javier.garcia(a)ehu.eus&gt; To: <gretl-users(a)lists.wfu.edu&gt; Subject: [Gretl-users] Instrumental variables and Hausman test Message-ID: <570d92ba.e567c20a.767b.fffffbe5SMTPIN_ADDED_BROKEN(a)mx.google.com&gt; Content-Type: text/plain; charset="utf-8" Hello everybody, I am trying to perform the Hausman test within a instrumental variables context. Using the smoke.gdt data from the Wooldridge's book, I regress the variable called lincome on a constant, cigs, educ, age and agesq. In order to do this I apply "instrumental variables->2sls", providing one instrument (in particular the variable called restaurn) for cigs, a variable that we suspect that could be correlated with the perturbation. As it can be seen below, the asymptotic test statistic is 5.00976. However, if I do it manually (or using another program like Stata), that value is totally different, getting 2.76 aproximately (the square of the estimates differences, (0.00173057-(-0.0413845))^2, over the variances differences, 0.0260279^2-0.00171372^2). What am I doing wrong? It could be a Gretl bug? Thanks a lot in advance. Javi Model 1: OLS, using observations 1-807 Dependent variable: lincome coefficient std. error t-ratio p-value ----------------------------------------------------------- const 7.79544 0.170427 45.74 1.05e-225 *** cigs 0.00173057 0.00171372 1.010 0.3129 educ 0.0603605 0.00789834 7.642 6.10e-014 *** age 0.0576907 0.00764359 7.548 1.21e-013 *** agesq ?0.000630589 8.33822e-05 ?7.563 1.08e-013 *** Mean dependent var 9.687315 S.D. dependent var 0.712695 Sum squared resid 341.8539 S.E. of regression 0.652880 R-squared 0.164978 Adjusted R-squared 0.160813 F(4, 802) 39.61341 P-value(F) 2.68e-30 Log-likelihood ?798.5010 Akaike criterion 1607.002 Schwarz criterion 1630.469 Hannan-Quinn 1616.013 Model 2: TSLS, using observations 1-807 Dependent variable: lincome Instrumented: cigs Instruments: const restaurn educ age agesq coefficient std. error z p-value --------------------------------------------------------- const 7.78114 0.228129 34.11 5.52e-255 *** cigs ?0.0413845 0.0260279 ?1.590 0.1118 educ 0.0400241 0.0161607 2.477 0.0133 ** age 0.0932076 0.0236787 3.936 8.27e-05 *** agesq ?0.00104373 0.000272324 ?3.833 0.0001 *** Mean dependent var 9.687315 S.D. dependent var 0.712695 Sum squared resid 611.6565 S.E. of regression 0.873306 R-squared 0.024886 Adjusted R-squared 0.020022 F(4, 802) 22.62942 P-value(F) 9.92e-18 Log-likelihood ?7885.899 Akaike criterion 15781.80 Schwarz criterion 15805.26 Hannan-Quinn 15790.81 Log-likelihood for income = ?8614.4 Hausman test - Null hypothesis: OLS estimates are consistent Asymptotic test statistic: Chi-square(1) = 5.00976 with p-value = 0.0252048 JAVIER GARC?A Departamento de Econom?a Aplicada III (Econometr?a y Estad?stica) Facultad de Econom?a y Empresa (Secci?n Sarriko) Avda. 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