State Dependence and Heterogeneity in Health Using a Bias Corrected Fixed Effects Estimator
AbstractThis paper considers the estimation of a dynamic ordered probit of self-assessed health status with two fixed effects: one in the linear index equation and one in the cut points. The two fixed effects allow us to robustly control for heterogeneity in unobserved health status and in reporting behaviour, even though we can not separate both sources of heterogeneity. The contributions of this paper are twofold. First it contributes to the literature that studies the determinants and dynamics of Self-Assessed Health measures. Second, this paper contributes to the recent literature on bias correction in nonlinear panel data models with fixed effects by applying and studying the finite sample properties of two of the existing proposals to our model. The most direct and easily applicable correction to our model is not the best one, and has important biases in our sample sizes.
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Bibliographic InfoPaper provided by Instituto de Economia. Pontificia Universidad Católica de Chile. in its series Documentos de Trabajo with number 402.
Date of creation: 2011
Date of revision:
Dynamic ordered probit; fixed effects; self-assessed health; reporting bias; panel data; unobserved heterogeneity; incidental parameters; bias correction;
Other versions of this item:
- Jesús M. Carro & Alejandra Traferri, 2011. "State dependence and heterogeneity in health using a bias corrected fixed effects estimator," Economics Working Papers we1118, Universidad Carlos III, Departamento de Economía.
- C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
- C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
- I19 - Health, Education, and Welfare - - Health - - - Other
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