A regression error specification test (RESET) for the truncated regression model

  • Authors

    • Sunil Sapra Department of Economics and Statistics, California State University, 5151 State University Drive, Los Angeles, CA 90032
    2018-06-14
    https://doi.org/10.14419/ijaes.v6i2.13478
  • Truncated Regression, RESET, TRESET, Empirical Size, Empirical Power.

  • Abstract

    While a variety of specification tests are routinely employed to test for misspecification in linear regression model, such tests and their applications to the truncated and censored regression models are uncommon. This paper develops a regression error specification test (RESET) for the truncated regression model as an extension of the popular RESET for the linear regression model (Ramsey (1969)). The two proposed extensions TRESET1 and TRESET2 developed in the paper are applied to labor force participation data from Mroz (1987). The paper studies the empirical size and power properties of the proposed tests via Monte Carlo experiments. Our simulation results suggest that both TRESET tests have reasonably good size and power properties for the truncated regression model in medium to large samples. However, TRESET2 consistently outperforms TRESET1 both in terms of empirical size and power in our experiments.

     

     

    Author Biography

    • Sunil Sapra, Department of Economics and Statistics, California State University, 5151 State University Drive, Los Angeles, CA 90032

      Profesor, Department of Economics and Statistics, California State University, Los Angeles, USA

      Sunil Sapra, earned both his M.Phil. and Ph.D. in Econometrics at Columbia University, New York. He is currently a Professor of Economics and Statistics at CaliforniaStateUniversity, Los Angeles. Prior to joining Cal. State, LA, he taught at State University of New York, Buffalo and held the prestigious ASA/NSF/Census Research Fellowship (1989-90) at the Bureau of the Census, Washington, D. C. He is an expert in Business Statistics at the Westlaw Roundtable Group. He has published more than 70 articles in some of the most prestigious statistics and econometrics journals. His research on semi-parametric econometrics, missing data problems, nonlinear statistical and econometric models, robust statistical procedures, limited dependent variables and duration data analysis has been published in Econometric Theory, The American Statistician, International Journal of Advanced Statistics and Probability, Statistica Neerlandica, Statistical Papers, Sankhya, Economics e-journal, Bulletin of Economic Research, Economics Letters, Applied Economics Letters, and Empirical Economics Letters. He serves on the editorial boards of several statistics and economics journals. His research has been cited in statistics and econometrics textbooks and journals as well as a widely-used volume on statistical distributions. He received the Outstanding Professor Award from California State University, Los Angeles in 2003 for excellence in teaching and research. He has been listed in Who’s Who among American Teachers and Educators (11th Edition, 2007).

  • References

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      [4] Horowitz JL (1994) Bootstrap-based critical values for the Information Matrix Test, Journal of Econometrics 38, 375-386. https://doi.org/10.1016/0304-4076(94)90092-2.

      [5] Horowitz JL & Neumann GR (1989) Specification Testing in censored regression models: parametric and semi-parametric methods, Journal of Applied Econometrics 4, S61-S86. https://doi.org/10.1002/jae.3950040505.

      [6] Maddala GS (1983) Limited Dependent and qualitative variables in Econometrics. Cambridge University Press, New York. https://doi.org/10.1017/CBO9780511810176.

      [7] Mroz T (1987) the sensitivity of an empirical model of married women's hours of work to economic and statistical assumptions. Econometrica 55, 765-799. https://doi.org/10.2307/1911029.

      [8] Peters S (2000) on the use of the RESET tests in Microeconometric Models, Applied Economics Letters 7, 361-365. https://doi.org/10.1080/135048500351285.

      [9] Ramsey JB (1969) Tests for specification errors in classical least-squares regression analysis, Journal of the Royal Statistical Society, Series B 31, 350-71.

      [10] Sapra S (2005) A Regression Error Specification (RESET) Test for Generalized Linear Models, Economics Bulletin 3, AccessEcon, 1-6.

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  • How to Cite

    Sapra, S. (2018). A regression error specification test (RESET) for the truncated regression model. International Journal of Accounting and Economics Studies, 6(2), 53-55. https://doi.org/10.14419/ijaes.v6i2.13478

    Received date: 2018-05-29

    Accepted date: 2018-06-04

    Published date: 2018-06-14