The Singularity of the Information Matrix of the Mixed Proportional Hazard Model
AbstractElbers and Ridder (1982) identify the Mixed Proportional Hazard model by assuming that the heterogeneity has finite mean. Under this assumption, the information matrix of the MPH model may be singular. Moreover, the finite mean assumption cannot be tested. This paper proposes a new identification condition that ensures non-singularity of the information bound. This implies that there can exist estimators that converge at rate root N. As an illustration, we apply our identifying assumption to the Transformation model of Horowitz (1996). In particular, we assume that the baseline hazard is constant near t=0 but make no no parametric assumptions are imposed for other values of t. We then derive an estimator for the scale normalization that converges at rate root N.
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Bibliographic InfoPaper provided by University of Western Ontario, Department of Economics in its series UWO Department of Economics Working Papers with number 20026.
Date of creation: Jul 2002
Date of revision:
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Postal: Department of Economics, Reference Centre, Social Science Centre, University of Western Ontario, London, Ontario, Canada N6A 5C2
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Web page: http://economics.uwo.ca/research/research_papers/department_working_papers.html
Other versions of this item:
- Geert Ridder & Tiemen M. Woutersen, 2003. "The Singularity of the Information Matrix of the Mixed Proportional Hazard Model," Econometrica, Econometric Society, vol. 71(5), pages 1579-1589, 09.
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- Jerry Hausman & Tiemen M. Woutersen, 2005.
"Estimating a semi-parametric duration model without specifying heterogeneity,"
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CWP11/05, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Tiemen Woutersen & Jerry Hausman, 2005. "Estimating a Semi-Parametric Duration Model without Specifying Heterogeneity," Economics Working Paper Archive 525, The Johns Hopkins University,Department of Economics.
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- Hausman, Jerry A. & Woutersen, Tiemen, 2014. "Estimating a semi-parametric duration model without specifying heterogeneity," Journal of Econometrics, Elsevier, vol. 178(P1), pages 114-131.
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