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Article

Smoothed Maximum Score Estimation of Discrete Duration Models

by 1 and 2,*
1
Nanyang Business School, Nanyang Technological University, Singapore 639798, Singapore
2
Department of Economics, York University, Toronto, ON M3J 1P3, Canada
*
Author to whom correspondence should be addressed.
J. Risk Financial Manag. 2019, 12(2), 64; https://doi.org/10.3390/jrfm12020064
Received: 7 March 2019 / Revised: 8 April 2019 / Accepted: 9 April 2019 / Published: 15 April 2019
(This article belongs to the Special Issue Nonparametric Econometric Methods and Application)
This paper extends Horowitz’s smoothed maximum score estimator to discrete-time duration models. The estimator’s consistency and asymptotic distribution are derived. Monte Carlo simulations using various data generating processes with varying error distributions and shapes of the hazard rate are conducted to examine the finite sample properties of the estimator. The bias-corrected estimator performs reasonably well for the models considered with moderately-sized samples. View Full-Text
Keywords: maximum score estimator; discrete duration models; efficient semiparamteric estimation maximum score estimator; discrete duration models; efficient semiparamteric estimation
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MDPI and ACS Style

Reza, S.; Rilstone, P. Smoothed Maximum Score Estimation of Discrete Duration Models. J. Risk Financial Manag. 2019, 12, 64. https://doi.org/10.3390/jrfm12020064

AMA Style

Reza S, Rilstone P. Smoothed Maximum Score Estimation of Discrete Duration Models. Journal of Risk and Financial Management. 2019; 12(2):64. https://doi.org/10.3390/jrfm12020064

Chicago/Turabian Style

Reza, Sadat, and Paul Rilstone. 2019. "Smoothed Maximum Score Estimation of Discrete Duration Models" Journal of Risk and Financial Management 12, no. 2: 64. https://doi.org/10.3390/jrfm12020064

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