Is neglected heterogeneity really an issue in binary and fractional regression models? A simulation exercise for logit, probit and loglog models

DOI10.1016/J.CSDA.2009.10.012zbMath1464.62146OpenAlexW2152811129MaRDI QIDQ962351

Esmeralda A. Ramalho, Joaquim J. S. Ramalho

Publication date: 6 April 2010

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2009.10.012

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Computational methods for problems pertaining to statistics (62-08)

Related Items (3)

Exponential regression of fractional-response fixed-effects models with an application to firm capital structure ⋮ Misspecified discrete choice models and Huber-White standard errors ⋮ Moment-based estimation of nonlinear regression models with boundary outcomes and endogeneity, with applications to nonnegative and fractional responses

Cites Work

• Unnamed Item
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• Improved estimators for a general class of beta regression models
• Specification error in multinomial logit models. Analysis of the omitted variable bias
• Properties of Proportional-Hazards Score Tests under Misspecified Regression Models
• Consistent Estimation of Scaled Coefficients
• A geometric approach to assess bias due to omitted covariates in generalized linear models
• Logit Models from Economics and Other Fields
• Econometrics of Qualitative Dependent Variables
• A Mirror Image Invariance for M-Estimators

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