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Extremum sieve estimation in k -out-of- n systems

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  • Tatiana V. Komarova

Abstract

This paper considers nonparametric estimation of absolutely continuous distribution functions of lifetimes of non-identical components in k-out-of-n systems from the observed 'autopsy' data. In economics, ascending 'button' or 'clock' auctions with n heterogeneous bidders present 2-out-of-n systems. Classical competing risk models are examples of k-out-of-n systems. Under weak conditions on the underlying distributions the estimation problem is shown to be well-posed and the suggested extremum sieve estimator is proven to be consistent. The paper illustrates the suggested estimation method by using sieve spaces of Bernstein polynomials which allow an easy implementation of constraints on the monotonicity of estimated distribution functions.

Suggested Citation

  • Tatiana V. Komarova, 2013. "Extremum sieve estimation in k -out-of- n systems," CeMMAP working papers 47/13, Institute for Fiscal Studies.
  • Handle: RePEc:azt:cemmap:47/13
    DOI: 10.1920/wp.cem.2013.4713
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    References listed on IDEAS

    as
    1. Chen, Xiaohong, 2007. "Large Sample Sieve Estimation of Semi-Nonparametric Models," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 76, Elsevier.
    2. Whitney K. Newey & James L. Powell, 2003. "Instrumental Variable Estimation of Nonparametric Models," Econometrica, Econometric Society, vol. 71(5), pages 1565-1578, September.
    3. Tatiana V. Komarova, 2009. "Nonparametric identification in asymmetric second-price auctions: a new approach," CeMMAP working papers CWP31/09, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
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