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Probit model for panel data with heterogeneity and endogenous explanatory variables : ウィキペディア英語版 | Probit model for panel data with heterogeneity and endogenous explanatory variables In many cases, there is an unobservable heterogeneity in the probit model. For instance, when modelling the consumption choice of a certain brand, consumers’ personal preference is unobserved but needs to be considered in the model 〔 Pradeep K. Chintagunta, Dipak C. Jain and Naufel J. Vilcassim (1991), “Investigating Heterogeneity in Brand Preferences in Logit Models for Panel Data”, Journal of Marketing Research, Vol. 28, pp. 417-428.〕 . Owing to omitted variable or measurement error, endogeneity issue also could arise〔 Wooldridge, J. (2002): Econometric Analysis of Cross Section and Panel Data, MIT Press, Cambridge, Mass, pp 473.〕 . A probit model including both of these two issues can be represented as:
where is the unobservable heterogeneity effect and . If and are independent, this model will degenerate to a probit model with unobservable heterogeneity. In this case, we can just integrate against the density of conditional on , then can be obtained 〔 Wooldridge, J. (2002): Econometric Analysis of Cross Section and Panel Data, MIT Press, Cambridge, Mass, pp 494.〕 and the objective for the conditional Maximum Likelihood Estimation is
If and are correlated, under the normality assumption, it can be assumed that = 〔 For more details, refer to Whitney K. Newey (1987), “Efficient Estimation of Limited Dependent Variable Models with Endogenous Explanatory Variables”, Journal of Econometrics 36, pp. 231-250.〕 , where and is independent with and . Then the model can be rewritten as:
where and Based on this, following the same Maximum Likelihood Estimation procedure and the scaled parameter can be consistently estimated, then the APE 〔 Wooldridge, J. (2002): Econometric Analysis of Cross Section and Panel Data, MIT Press, Cambridge, Mass, pp 22.〕 can be consistently estimated correspondingly.
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