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A simple adjustment for measurement errors in some limited dependent variable models

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  • Wang, Liqun

Abstract

This paper proposes a simple method to adjust for measurement errors in estimations of many popular limited dependent variable models, e.g., the binary response model, the censored and the truncated regression models. The procedure is based on a simple correction of the estimators for the corresponding "error-free" models and is easy to be incorporated into the existing statistical computer packages. The extra computing cost is minimal.

Suggested Citation

  • Wang, Liqun, 2002. "A simple adjustment for measurement errors in some limited dependent variable models," Statistics & Probability Letters, Elsevier, vol. 58(4), pages 427-433, July.
  • Handle: RePEc:eee:stapro:v:58:y:2002:i:4:p:427-433
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    References listed on IDEAS

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    1. Sepanski, J. H. & Carroll, R. J., 1993. "Semiparametric quasilikelihood and variance function estimation in measurement error models," Journal of Econometrics, Elsevier, vol. 58(1-2), pages 223-256, July.
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    Cited by:

    1. Wang, Liqun & Hsiao, Cheng, 2011. "Method of moments estimation and identifiability of semiparametric nonlinear errors-in-variables models," Journal of Econometrics, Elsevier, vol. 165(1), pages 30-44.
    2. Gibson, Fiona L. & Burton, Michael P., 2009. "Biased estimates in discrete choice models: the appropriate inclusion of psychometric data into the valuation of recycled wastewater," 2009 Conference (53rd), February 11-13, 2009, Cairns, Australia 47943, Australian Agricultural and Resource Economics Society.
    3. Gustavo Rocha & Reinaldo Arellano-Valle & Rosangela Loschi, 2015. "Maximum likelihood methods in a robust censored errors-in-variables model," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 24(4), pages 857-877, December.

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