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1 janvier 2015
- handle: 10670/1.cb3jwd
info:eu-repo/semantics/openAccess
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Armando Sánchez Vargas et al., « On the econometric modeling of nonlinear relationships: the gumbel regression model », Revista mexicana de economía y finanzas, ID : 10670/1.cb3jwd
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Résumé
Nonlinear relationships among random variables often come out in all fields of economics. The academic debate on how to deal with nonlinearities, from a statistical point of view, has been centered in developing new estimation methods or modifying the specification of the classic linear econometric models. Here, we propose to face this issue by deriving population regression models from conditional distributions with genuine nonlinear conditional means. Such a mathematical procedure guarantees not only a consistent derivation of the conditional mean that gives rise to a nonlinear econometric model, but also a proper analysis of the causal effects among the involved economic variables (i.e., partial effects). Finally, we exemplify the workings of this approach by specifying a nonlinear and heteroskedastic econometric model based on the Gumbel distribution.