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mmolina@uniroma3.it |

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statalist@hsphsun2.harvard.edu |

Subject |
st: [Fwd: Endogeneity in Bivariate Probit] |

Date |
Sun, 9 Aug 2009 18:07:46 +0200 (CEST) |

Thank you Cameron. Mi model is: y1* = alpha1 + betaY2* + e1 y2* = alpha2 + betaX + e2 where y1 (0,1) is innovation in product and y2 (0,1) is innovation in process. I supossed that both inlfuence each other and put them in a system. X represent other factors such as foreign ownership, quality certification and also two dummies (for 3) different sizes. For two of the selected countries I received low Prob > chi(2) and for the third, these results. Likelihood-ratio test of rho = 0 : chi2(1) = 2,1962 Prob > chi(2) = 0,1383 I was wondering if these results imply endogenity. Best, Alejandra Hi Alejandra, So if I understand your model specification correctly, it is along the lines of some mediational model (let's say the underlying response variate y2* is the mediator between some IV X and the ultimate outcome y1*): y1* = alpha1 + betaX + betaY2* + e1 y2* = alpha2 + betaX + e2 Then you are asking if a test of cov(e1,e2) = 0 under the 'biprobit' is equivalent to a Hausman test of endogeneity. Indeed, the Knapp and Seakes (1998) paper is oft-cited in the bivariate probit context for this purpose, but I am not 100% sure if it can be invoked in this case. (I could be wrong). Mediational models bring in a number of issues about the proper direction of causal flow among the variables in the system. Of course, cov(e1,e2) = 0 is necessary for getting good overall empirical model fit (implying, for example, that no common causes of y1* and y2* have been omitted), and thus unbiased estimates, but I don'[t know if this automatically implies endogeneity in the sense that cov(y2*,e1) = 0 (unless X is being regarded as an instrument here), and I believe that more is involved for convincingly demonstrating the properness of the postulated causal chain. I would suggest having a look at: James, L.R., Mulaik, S.A., & Brett, J.M. (2006). A tale of two methods. Organizational Research Methods, 9(2), 233-244. Further, quantifying the degree of mediation in probit (and logit) models is more complicated than in the linear case: MacKinnon, D.P., Lockwood, C.M., Brown C.H., Wang W., & Hoffman M. (2007). The intermediate endpoint effect in logistic and probit regression. Clinical Trials, 4(5), 499-513. For more general readings on mediation see: MacKinnon, D.P. (2008). Introduction to statistical mediation analysis. Mahwah, NJ: Erlbaum. MacKinnon, D. P., & Fairchild, A. J. (2009). Current directions in mediation analysis. Current Directions in Psychological Science, 18, 16-20. Hope this is helpful, and that I have understood the situation correctly. Cam -------------------------- Messaggio originale --------------------------- Oggetto: Endogeneity in Bivariate Probit Da: mmolina@uniroma3.it Data: Dom, 9 Agosto 2009 1:51 am A: statalist@hsphsun2.harvard.edu -------------------------------------------------------------------------- Dear Statalist, I found on the Statist archive that Knapp and Seaks argue that a likelihood-ratio test of the correlation coefficient of the residuals (rho) can be used as an endogeneity test. On the other hand I read that if "the second dependent variable, y2, appears on the right-hand side of the first equation, this is a recursive, simultaneous-equations model. Surprisingly, the endogenous nature of one of the variables on the right-hand side of the first equation can be ignored in formulating the log-likelihood" (Greene, 2002, pp.715). I run my model for three countries and only in one case I obtained these results: Likelihood-ratio test of rho = 0 : chi2(1) = 2,1962 Prob > chi(2) = 0,1383 Should I consider that y2 variable have passed the endogeneity test? Thanks in advance and regards, Alejandra Molina * * 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/

**Follow-Ups**:**FW: st: [Fwd: Endogeneity in Bivariate Probit]***From:*Cameron McIntosh <cnm100@hotmail.com>

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