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Censored Probit Estimation with Correlation near the Boundary: A Useful Reparameteriztion

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  • Terza, Joseph V.
  • Tsai, Wei-Der

Abstract

The conventional computational algorithms for full information maximum likelihood (FIML) estimation of the censored probit model (see Farber, 1983), will sometimes fail to converge when the estimated value of the correlation coefficient (ñ) approaches ±1; even when the true value of ñ is not at a boundary. We show that a simple reparametrization of the censored probit model may afford straightforward Newton-Raphson convergence to the true FIML estimate for cases in which likelihood maximization under the conventional censored probit parameterization would have failed. Moreover, our method avoids the computational and inferential complications that arise in alternative methods that, based on a specified criterion, suggest fixing the estimated value of ñ at -1 or +1. For the purpose of illustration the method is used to estimate the determinants of elderly parents’ receipt of informal care from their children.

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Bibliographic Info

Article provided by Review of Applied Economics in its journal Review of Applied Economics.

Volume (Year): 2 (2006)
Issue (Month): 1 ()
Pages:

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Handle: RePEc:ags:reapec:50278

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Web page: http://www.lincoln.ac.nz/story11874.html

Related research

Keywords: sample selection; endogenous treatment effects; endogenous switching; qualitative dependent variables; informal elderly care; Research Methods/ Statistical Methods; I12; C24; C63;

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References

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  1. Joseph Terza, 2009. "Parametric Nonlinear Regression with Endogenous Switching," Econometric Reviews, Taylor & Francis Journals, vol. 28(6), pages 555-580.
  2. Kenkel, D., 1988. "The Demand For Preventive Medical Care," Papers 3-88-4, Pennsylvania State - Department of Economics.
  3. Butler, J. S., 1997. "Censored probit models do not fail randomly: A Monte Carlo study," Economics Letters, Elsevier, vol. 57(1), pages 33-37, November.
  4. Richard P. Chaykowski & J. S. Butler & George Slotsve, 1992. "A simultaneous analysis of grievance activity and outcome decisions," Industrial and Labor Relations Review, ILR Review, Cornell University, ILR School, vol. 45(4), pages 724-737, July.
  5. Rivers, Douglas & Vuong, Quang H., 1988. "Limited information estimators and exogeneity tests for simultaneous probit models," Journal of Econometrics, Elsevier, vol. 39(3), pages 347-366, November.
  6. Henry S. Farber & Michelle J. White, 1990. "Medical Malpractice: An Empirical Examination of the Litigation Process," NBER Working Papers 3428, National Bureau of Economic Research, Inc.
  7. Meng, Chun-Lo & Schmidt, Peter, 1985. "On the Cost of Partial Observability in the Bivariate Probit Model," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 26(1), pages 71-85, February.
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Cited by:
  1. Terza, Joseph V. & Basu, Anirban & Rathouz, Paul J., 2008. "Two-stage residual inclusion estimation: Addressing endogeneity in health econometric modeling," Journal of Health Economics, Elsevier, vol. 27(3), pages 531-543, May.

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