Counts With An Endogenous Binary Regressor: A Series Expansion Approach
AbstractWe propose an estimator for count data regression models where a binary regressor is endogenously determined. This estimator departs from previous approaches by using a flexible form for the conditional probability function of the counts. Using a Monte Carlo experiment we show that our estimator improves the fit and provides a more reliable estimate of the impact of regressors on the count when compared to alternatives which do restrict the mean to be linear-exponential. In an application to the number of trips by households in the US, we find that the estimate of the treatment effect obtained is considerably different from the one obtained under a linear-exponential mean specification.
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Bibliographic InfoPaper provided by Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie) in its series Working Papers. Serie AD with number 2004-36.
Length: 30 pages
Date of creation: Sep 2004
Date of revision:
Publication status: Published by Ivie
Count data; Polynominal Poisson Expansions; Flexible Functional Form.;
Other versions of this item:
- Andrés Romeu & Marcos Vera-Hern�ndez, 2005. "Counts with an endogenous binary regressor: A series expansion approach," Econometrics Journal, Royal Economic Society, vol. 8(1), pages 1-22, 03.
- C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
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