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Consistent Estimation of Regression Coefficients in Replicated Data with Non-Normal Measurement Errors

Author

Listed:
  • Aman Ullah

    (Department of Economics, University of California)

  • Shalabh

    (Department of Statistics, Panjab University)

  • Debasri Mukherjee

    (Department of Economics, University of California)

Abstract

In this paper we consider a weighted harmonic mean of two inconsistent estimators to propose a new estimator of the coefficient of a linear regression model with measurement errors. The proposed estimator is simple and it does not depend on any unknown quantity. The approximate bias and MSE of the estimator are derived. Further, an empirical application is also presented.

Suggested Citation

  • Aman Ullah & Shalabh & Debasri Mukherjee, 2001. "Consistent Estimation of Regression Coefficients in Replicated Data with Non-Normal Measurement Errors," Annals of Economics and Finance, Society for AEF, vol. 2(1), pages 249-264, May.
    • Handle: RePEc:cuf:journl:y:2001:v:2:i:1:p:249-264
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    References listed on IDEAS

    as
    1. Rose, Andrew K., 1991. "The role of exchange rates in a popular model of international trade : Does the 'Marshall-Lerner' condition hold?," Journal of International Economics, Elsevier, vol. 30(3-4), pages 301-316, May.
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    Cited by:

    1. Singh, Sukhbir & Jain, Kanchan & Sharma, Suresh, 2012. "Using stochastic prior information in consistent estimation of regression coefficients in replicated measurement error model," Journal of Multivariate Analysis, Elsevier, vol. 111(C), pages 198-212.
    2. Galea, Manuel & de Castro, Mário, 2017. "Robust inference in a linear functional model with replications using the t distribution," Journal of Multivariate Analysis, Elsevier, vol. 160(C), pages 134-145.
    3. Sukhbir Singh & Kanchan Jain & Suresh Sharma, 2014. "Replicated measurement error model under exact linear restrictions," Statistical Papers, Springer, vol. 55(2), pages 253-274, May.

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    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General

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