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Shift Restrictions and Semiparametric Estimation in Ordered Response Models

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  • Roger W. Klein

    ()
    (Dept. of Economics, New Jersey Hall, 75 Hamilton St., Rutgers University, New Brunswick, NJ 08901, U.S.A.)

  • Robert P. Sherman

    ()
    (Div. of Humanities and Social Sciences 227-88, California Institute of Technology, Pasadena, CA 91125, U.S.A.)

Abstract

We develop a √"n"-consistent and asymptotically normal estimator of the parameters (regression coefficients and threshold points) of a semiparametric ordered response model under the assumption of independence of errors and regressors. The independence assumption implies shift restrictions allowing identification of threshold points up to location and scale. The estimator is useful in various applications, particularly in new product demand forecasting from survey data subject to systematic misreporting. We apply the estimator to assess exaggeration bias in survey data on demand for a new telecommunications service. Copyright The Econometric Society 2002.

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Bibliographic Info

Article provided by Econometric Society in its journal Econometrica.

Volume (Year): 70 (2002)
Issue (Month): 2 (March)
Pages: 663-691

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Handle: RePEc:ecm:emetrp:v:70:y:2002:i:2:p:663-691

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Cited by:
  1. Giuseppe De Luca & Valeria Perotti, 2010. "Estimation of ordered response models with sample selection," CEIS Research Paper 168, Tor Vergata University, CEIS, revised 03 Jun 2010.
  2. Christian N. Brinch, 2008. "Non-parametric Identification of the Mixed Hazards Model with Interval-Censored Durations," Discussion Papers 539, Research Department of Statistics Norway.
  3. James E. Prieger, 2004. "An Empirical Investigation of Biased Survey Data and an Attempted Cure," Working Papers 44, University of California, Davis, Department of Economics.
  4. Melanie Lührmann & Jürgen Maurer, 2008. "Who wears the trousers? A semiparametric analysis of decision power in couples," MEA discussion paper series 08168, Munich Center for the Economics of Aging (MEA) at the Max Planck Institute for Social Law and Social Policy.
  5. Bo E. Honore & Aureo de Paula, 2007. "Interdependent Durations, Second Version," PIER Working Paper Archive 08-044, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 01 Nov 2008.
  6. Arthur Lewbel, 2002. "Ordered Response Threshold Estimation," Boston College Working Papers in Economics 535, Boston College Department of Economics, revised 29 Oct 2003.
  7. Stefan Boes, 2013. "Nonparametric analysis of treatment effects in ordered response models," Empirical Economics, Springer, vol. 44(1), pages 81-109, February.
  8. Bo E. Honor & �ureo De Paula, 2010. "Interdependent Durations," Review of Economic Studies, Oxford University Press, vol. 77(3), pages 1138-1163.
  9. Jürgen Maurer, 2007. "Socioeconomic and Health Determinants of Health Care Utilization Among Elderly Europeans: A Semiparametric Assessment of Equity, Intensity and Responsiveness for Ten European Countries," MEA discussion paper series 07144, Munich Center for the Economics of Aging (MEA) at the Max Planck Institute for Social Law and Social Policy.
  10. Juan Mora & Ana I. Moro, 2006. "Consistent Specification Test For Ordered Discrete Choice Models," Working Papers. Serie AD 2006-17, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
  11. Bo E. Honoré & Aureo de Paula, 2009. ""Interdependent Durations" Third Version," PIER Working Paper Archive 09-039, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 01 Feb 2008.
  12. William H. Greene & David A. Hensher, 2008. "Modeling Ordered Choices: A Primer and Recent Developments," Working Papers 08-26, New York University, Leonard N. Stern School of Business, Department of Economics.

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