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From | <Marianne.LEFEBVRE@ec.europa.eu> |
To | <statalist@hsphsun2.harvard.edu> |
Subject | st: interpretation reciprocal causation ivprobit cdsimeq |
Date | Tue, 30 Oct 2012 08:26:37 +0000 |
Dear Stata list As I am new here, I would like to understand how to improve my question sent ten days ago in order to get your feedback. It is about the interpretation of the results of two estimations procedures ivprobit. Do not hesitate to let me know if this is not the good place to ask such questions or good question format. Thanks a lot Best, Marianne Lefebvre -----Original Message----- From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Marianne.LEFEBVRE@ec.europa.eu Sent: Friday, October 19, 2012 2:30 PM To: statalist@hsphsun2.harvard.edu Subject: st: interpretation reciprocal causation ivprobit cdsimeq Dear Stata listers I have run the following regressions using ivprobit and cdsimeq and I am not too sure about the interpretation. please see my question in capital letters below. Thanks a lot for your help. In order to account for the potential endogeneity between insurance decision (binary variable) and economic performance (continuous), we adopt a 2SLS estimation technique where total gross margin is instrumented. We use Newey's (1987) minimum-chi-squared estimator (ivprobit twostep option). We find that economic performance, as defined by the total gross margin, significantly explains insurance adoption (table 1). Post-estimation tests: We ran the joint significance test of the instruments in the first stage regression (F-statistic>10). The Amemiya-Lee-Newey test of overidentifying restrictions is not significant (chi2=2.025, p-value= 0.1547). The Wald test of exogeneity for IVprobit estimations allows to reject the null hypothesis of exogeneity of the instruments (chi2=7.45, p-value= 0.0064). Then, we verify whether there is reciprocal causation between insurance use and economic performance (total gross margin). To obtain this result, we rely on the two-stage probit least squares estimation method described in (Maddala 1983) for simultaneous equations models in which one of the endogenous variables is continuous (total gross margin) and the other endogenous variable is dichotomous (insurance use) (cdsimeq command in Stata http://www.stata-journal.com/article.html?article=st0038). We find that economic performance (total gross margin) significantly explains insurance adoption but the reverse effect is not significant (table 2). IS IT CORRECT TO CONCLUDE AS FOLLOWS? The result suggests that the endogeneity bias between insurance decision and economic performance is due to omitted variables, and not reciprocal causation. It therefore justifies the use of the ivprobit model where economic performance is instrumented to explain insurance decision, rather than the (Maddala 1983) estimation procedure (cdsimeq). Table 1: 2SLS Probability to adopt insurance, with instrumentation of gross margin First step Number of obs = 144 R-squared = 0.2453 Adj R-squared = 0.1946 grossmargin Coef. Std. Err. t P>t [95% Conf. Interval] q3_individual farms -228188.2*** 112400.5 -2.03 0.044 -450496.7 -5879.677 q4_totaluaa_sq .1313854 *** .0329142 3.99 0.000 .0662869 .1964839 nuts2_32 51374.23 95259.15 0.54 0.591 -137031.8 239780.2 nuts2_33 16731.56 100579.9 0.17 0.868 -182198 215661.2 nuts2_34 10620.46 100359.5 0.11 0.916 -187873.1 209114 nuts2_41 7942.025 127155.7 0.06 0.950 -243549.8 259433.8 nuts2_42 93651.27 99561.3 0.94 0.349 -103263.6 290566.2 q4_ratiorent -33656.87 82139.63 -0.41 0.683 -196114.8 128801 q21_noninsuranmeasures -56509.8 68454.26 -0.83 0.411 -191900.4 78880.8 _cons 292010.1 154708.1 1.89 0.061 -13975.68 597995.8 Second step Number of obs = 144 Wald chi2(8) = 29.93 Prob > chi2 = 0.0002 insurance2011 Coef. Std. Err. z P>z [95% Conf. Interval] I_grossmargin 3.88e-06*** 1.43e-06 2.72 0.006 1.09e-06 6.68e-06 nuts2_32 -1.805997 .5538496 -3.26 0.001 -2.891522 -.7204715 nuts2_33 -1.224679 .5420211 -2.26 0.024 -2.287021 -.1623367 nuts2_34 -.9044687 .5287984 -1.71 0.087 -1.940894 .131957 nuts2_41 -2.162879 .7412688 -2.92 0.004 -3.615739 -.7100187 nuts2_42 -3.11869 .7796749 -4.00 0.000 -4.646824 -1.590555 q4_ratiorent 1.127435 .4558475 2.47 0.013 .2339906 2.02088 q21_noninsuranmeasures -.7945278 .3990442 -1.99 0.046 -1.57664 -.0124156 _cons .4889867 .4838786 1.01 0.312 -.459398 1.437371 Wald test of exogeneity: chi2(1) = 7.45 Prob > chi2 = 0.0064 Test of overidentifying restrictions: Amemiya-Lee-Newey minimum chi-sq statistic Chi-sq(1)= 2.025 P-value = 0.1547 Table 2: two-stage probit least squares estimation (cdsimeq) – SECOND STAGE REGRESSIONS WITH CORRECTED STANDARD ERRORS ------------------------------------------------------------------------------ grossmargin | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- I_insur~2011 | -15809.74 28736.81 -0.55 0.583 -72623.96 41004.48 q3_individ~s | -239284.4 113697.5 -2.10 0.037 -464070.5 -14498.42 q4_totalua~q | .1351443 .0322533 4.19 0.000 .0713778 .1989108 _cons | 264916.4 104230.9 2.54 0.012 58846.34 470986.5 ------------------------------------------------------------------------------ ------------------------------------------------------------------------------ insuran~2011 | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- I_grossmar~n | 2.67e-06*** 1.07e-06 2.50 0.012 5.77e-07 4.77e-06 nuts2_32 | -1.634341 .5218917 -3.13 0.002 -2.65723 -.6114523 nuts2_33 | -1.201044 .5233067 -2.30 0.022 -2.226706 -.1753817 nuts2_34 | -.8801489 .5140605 -1.71 0.087 -1.887689 .1273911 nuts2_41 | -2.143736 .7280761 -2.94 0.003 -3.570739 -.7167331 nuts2_42 | -2.832533 .6944463 -4.08 0.000 -4.193622 -1.471443 q4_ratiorent | 1.11448 .445112 2.50 0.012 .2420765 1.986884 q21_nonins~s | -.755226 .381161 -1.98 0.048 -1.502288 -.0081642 _cons | .483358 .4681395 1.03 0.302 -.4341785 1.400894 ------------------------------------------------------------------------------ Marianne Lefebvre Joint Research Centre: The European Commission's in-house science service Institute for Prospective Technological Studies Agriculture and Life Science in the Economy <file://C:\Documents and Settings\lefebme\Application Data\Microsoft\Signatures\Marianne_files\image001.gif> Edificio EXPO, C/ Inca Garcilaso no 3 41092 Seville, Spain Tel: +34 954 48 8314 Fax: +34 954 48 8434 marianne.lefebvre@ec.europa.eu <blocked::mailto:marianne.lefebvre@ec.europa.eu> * * 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/ * * 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/