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Smoothed Maximum Score Estimation of Discrete Duration Models

Author

Listed:
  • Sadat Reza

    () (Nanyang Business School, Nanyang Technological University, Singapore 639798, Singapore)

  • Paul Rilstone

    () (Department of Economics, York University, Toronto, ON M3J 1P3, Canada)

Abstract

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.

Suggested Citation

  • Sadat Reza & Paul Rilstone, 2019. "Smoothed Maximum Score Estimation of Discrete Duration Models," Journal of Risk and Financial Management, MDPI, Open Access Journal, vol. 12(2), pages 1-16, April.
  • Handle: RePEc:gam:jjrfmx:v:12:y:2019:i:2:p:64-:d:222990
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Thanasis Stengos, 2019. "Nonparametric Econometric Methods and Applications," Journal of Risk and Financial Management, MDPI, Open Access Journal, vol. 12(4), pages 1-3, November.

    More about this item

    Keywords

    maximum score estimator; discrete duration models; efficient semiparamteric estimation;

    JEL classification:

    • C - Mathematical and Quantitative Methods
    • E - Macroeconomics and Monetary Economics
    • F2 - International Economics - - International Factor Movements and International Business
    • F3 - International Economics - - International Finance
    • G - Financial Economics

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