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| Miranda, Alfonso; Rabe-Hesketh, Sophia. |
| Studying behavior in economics, sociology, and statistics often involves fitting models in which the response variable depends on a dummy variable—also known as a regime-switch variable—or in which the response variable is observed only if a particular selection condition is met. In either case, standard regression techniques deliver inconsistent estimators if unobserved factors that affect the response are correlated with unobserved factors that affect the switching or selection variable. Consistent estimators can be obtained by maximum likelihood estimation of a joint model of the outcome and switching or selection variable. This article describes a “wrapper” program, ssm, that calls gllamm (Rabe-Hesketh, Skrondal, and Pickles, GLLAMM Manual [University... |
| Tipo: Journal Article |
Palavras-chave: Endogenous switching; Sample selection; Binary variable; Count data; Ordinal variable; Probit; Poisson regression; Adaptive quadrature; Gllamm; Wrapper; Ssm; Research Methods/ Statistical Methods. |
| Ano: 2006 |
URL: http://purl.umn.edu/117582 |
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| Miranda, Alfonso. |
| This paper presents code for fitting a FIML endogenous switching Poisson count model for cross-sectional data in Stata 7: the espoisson command. The Poisson process depends on an unobserved heterogeneity term, ε; a set of explanatory variables, x; and an endogenous dummy, d. The endogenous dummy depends on an unobserved random term, v. Correlation between ε and v is allowed. If a model with exogenous d is fitted instead, correlation between ε and v will result in simultaneous equation bias. The endogenous switching model corrects this problem. After describing the underlying econometric theory behind the command, an example is discussed. |
| Tipo: Journal Article |
Palavras-chave: Count models; Endogenous switch; Sample selection; Research Methods/ Statistical Methods. |
| Ano: 2004 |
URL: http://purl.umn.edu/116208 |
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