Palgrave Handbook of Econometrics: Applied Econometrics

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11 Discrete Choice Modeling William Greene Abstract We detail the basic theory for models of discrete choice. This encompasses m ...

474 Discrete Choice Modeling 11.4.3 Sample selection in a bivariate probit model 512 11.4.4 Multivariate binary choice and the p ...

William Greene 475 We emphasize that we have chosen to focus on models for discretechoice, rather than models for discretedepend ...

476 Discrete Choice Modeling constraint,x′d≤y, wherexis a vector of prices andyis income (or total expen- diture). Assuming the ...

William Greene 477 most of what follows, we will not need this level of generality, but the models to be developed will accommod ...

478 Discrete Choice Modeling choices. The termbinary choiceis often used interchangeably with the former. A bivariate choiceormu ...

William Greene 479 even in this form, it will generally bear little resemblance to the linear regression model. As in other nonl ...

480 Discrete Choice Modeling Health Care data (our appelation) was used in Riphahn, Wambach and Million (2003) to analyze utiliz ...

William Greene 481 earlier that the individual makes exactly one choice. Second, it is evident that, in describing the choice of ...

482 Discrete Choice Modeling We can approach the specification in equation (11.2) from a different viewpoint. The random utility ...

William Greene 483 proper probability models for the implied regressions. The logit and probit mod- els described in the next se ...

484 Discrete Choice Modeling The log-likelihood function for the observed data is: lnL= ∑n i= 1 lnProb(di|xi,zi) = ∑ di= 1 ln Pr ...

William Greene 485 the assumptions of the model (distribution, omitted variables, heteroskedasticity, and correlation across obs ...

486 Discrete Choice Modeling 11.3.2.3 Marginal effects Partial effects in the binary choice model are computed for continuous va ...

William Greene 487 An empirical conundrum can arise when doing inference about partial effects rather than coefficients. For any ...

488 Discrete Choice Modeling mentioned earlier. UsingVBHHHproduces a particularly convenient computation, as well as an interest ...

William Greene 489 complication arises in interpretation of the model. The partial effects in this augmented model are: δi= ∂Pro ...

490 Discrete Choice Modeling constant. It is tempting to suggest that this measure measures the “contribution” of the variables ...

William Greene 491 To obtain the posterior mean (Bayesian estimator), we assume a non-informative, flat (improper) prior forθ: p ...