Correcting the bias in the estimation of a dynamic ordered probit with fixed effects of self-assessed health status
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 as unobserved health status, and another one in the cut points, interpreted as heterogeneity in reporting behavior. The contributions of this paper are twofold. Firstly this paper contributes to the recent literature on bias correction in nonlinear panel data models by applying 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.
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Fernández-Val, Iván, 2009.
"Fixed effects estimation of structural parameters and marginal effects in panel probit models,"
Journal of Econometrics,
Elsevier, vol. 150(1), pages 71-85, May.
- Ivan Fernandez-Val, 2007. "Fixed Effects Estimation of Structural Parameters and Marginal Effects in Panel Probit Models," Boston University - Department of Economics - Working Papers Series WP2007-009, Boston University - Department of Economics.
- Jeffrey M. Wooldridge, 2005. "Simple solutions to the initial conditions problem in dynamic, nonlinear panel data models with unobserved heterogeneity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(1), pages 39-54.
- Jeffrey M. Wooldridge, 2002. "Simple solutions to the initial conditions problem in dynamic, nonlinear panel data models with unobserved heterogeneity," CeMMAP working papers CWP18/02, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Paul Contoyannis & Andrew M. Jones & Nigel Rice, 2004. "The dynamics of health in the British Household Panel Survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 19(4), pages 473-503.
- William H. Greene & David A. Hensher, 2008. "Modeling Ordered Choices: A Primer and Recent Developments," Working Papers 08-26, New York University, Leonard N. Stern School of Business, Department of Economics.
- Carro, Jesus M., 2007. "Estimating dynamic panel data discrete choice models with fixed effects," Journal of Econometrics, Elsevier, vol. 140(2), pages 503-528, October.
- Mundlak, Yair, 1978. "On the Pooling of Time Series and Cross Section Data," Econometrica, Econometric Society, vol. 46(1), pages 69-85, January.
- Jinyong Hahn & Whitney Newey, 2004. "Jackknife and Analytical Bias Reduction for Nonlinear Panel Models," Econometrica, Econometric Society, vol. 72(4), pages 1295-1319, 07.
- Jinyong Hahn & Whitney K. Newey, 2003. "Jackknife and analytical bias reduction for nonlinear panel models," CeMMAP working papers CWP17/03, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Hahn, Jinyong & Kuersteiner, Guido, 2011. "Bias Reduction For Dynamic Nonlinear Panel Models With Fixed Effects," Econometric Theory, Cambridge University Press, vol. 27(06), pages 1152-1191, December.
- Bester, C. Alan & Hansen, Christian, 2009. "A Penalty Function Approach to Bias Reduction in Nonlinear Panel Models with Fixed Effects," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(2), pages 131-148. Full references (including those not matched with items on IDEAS)