Limited-Dependent and Qualitative Variables in EconometricsCambridge University Press, 27 juni 1986 This book presents the econometric analysis of single-equation and simultaneous-equation models in which the jointly dependent variables can be continuous, categorical, or truncated. Despite the traditional emphasis on continuous variables in econometrics, many of the economic variables encountered in practice are categorical (those for which a suitable category can be found but where no actual measurement exists) or truncated (those that can be observed only in certain ranges). Such variables are involved, for example, in models of occupational choice, choice of tenure in housing, and choice of type of schooling. Models with regulated prices and rationing, and models for program evaluation, also represent areas of application for the techniques presented by the author. |
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Limited-Dependent and Qualitative Variables in Econometrics G. S. Maddala Begränsad förhandsgranskning - 1983 |
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alternative Amemiya analysis assume assumption bivariate censored regression model Chapter choice coefficients condition consistent estimates corresponding covariance matrix defined demand denote density function dependent variable diagonal dichotomous variables discussed disequilibrium models distribution function dummy variable Econometric Economic endogenous estimation method example exogenous variables explanatory variables follows formulation given by equations Heckman Hence heteroscedasticity images individual inthe iterative joint density latent variables leastsquares likelihood function linear probability model logit model loglikelihood function loglinear Maddala maximized McFadden ML estimates ML method model considered multinomial logit multinomial probit multivariate Note number of observations obtained ofthe parameters preceding section predictions probit method probit model problem procedure reducedform residuals sample selfselection simultaneousequations models specification suggested term thatthe themodel tobit tothe truncated normal distribution truncated regression model twostage estimation twostage method values variance vector wage wecan weshall zero