RT Generic
T1 Correcting the bias in the estimation of a dynamic ordered probit with fixed effects of self-assessed health status
A1 Carro, Jesús M.
A1 Traferri, Alejandra
A2 Universidad Carlos III de Madrid. Departamento de Economía, 
AB This paper considers the estimation of a dynamic ordered probit with fixed effects, with an application to self-assessed health status. The estimation of nonlinear panel data models with fixed effects by MLE is known to be biased when T is not very large. The problem is specially severe in our model because of the dynamics and because it contains two fixed effects: one in the linear index equation, interpreted asunobserved health status, and another one in the cut points, interpreted as heterogeneityin reporting behavior. The contributions of this paper are twofold. Firstly this papercontributes to the recent literature on bias correction in nonlinear panel data models byapplying and studying the finite sample properties of two of the existing proposals to the ordered probit case. The most direct and easily applicable correction to our model is not the best one and still has important biases in our sample sizes. Secondly, we contribute to the literature that study the determinants of Self-Assesed Health measures by applying the previous analysis on estimation methods to the British Household Panel Survey.
SN 2340-5031
YR 2009
FD 2009-06
LK https://hdl.handle.net/10016/5210
UL https://hdl.handle.net/10016/5210
LA eng
DS e-Archivo
RD 21 jul. 2024