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A Simple Framework for Non-Parametric Specification Testing

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  • Ellison, G.
  • Ellison, F.

Abstract

This paper presents a simple framework for testing the specification of parametric conditional means. The test statistics are based on quadratic forms in the residuals of the null model. Under general assumptions the test statistics are asymptotically normal under the null. With an appropriate choice of the weight matrix, the tests are shown to be consistent and to have good local power. Specific implementations involving matrices of bin and kernel weights are discussed. Finite sample properties are explored in simulations and an application to some parametric models of gasoline demand is presented.
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(This abstract was borrowed from another version of this item.)
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Ellison, G. & Ellison, F., 1993. "A Simple Framework for Non-Parametric Specification Testing," Harvard Institute of Economic Research Working Papers 1662, Harvard - Institute of Economic Research.
  • Handle: RePEc:fth:harver:1662
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    References listed on IDEAS

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    1. Mikosch, T., 1991. "Functional limit theorems for random quadratic forms," Stochastic Processes and their Applications, Elsevier, vol. 37(1), pages 81-98, February.
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    8. repec:cup:etheor:v:9:y:1993:i:3:p:451-77 is not listed on IDEAS
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    Citations

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    Cited by:

    1. Chevalier, Judith & Ellison, Glenn, 1997. "Risk Taking by Mutual Funds as a Response to Incentives," Journal of Political Economy, University of Chicago Press, vol. 105(6), pages 1167-1200, December.
    2. Andrea Vaona, 2008. "The sensitivity of nonparametric misspecification tests to disturbance autocorrelation," Quaderni della facoltà di Scienze economiche dell'Università di Lugano 0803, USI Università della Svizzera italiana.
    3. E Fe-Rodriguez & C D Orme, 2005. "The Asymptotic Equivalence of Kernel-based Nonparametric Conditional Moment Test Statistics," The School of Economics Discussion Paper Series 0504, Economics, The University of Manchester.
    4. Glenn Ellison & Sara Fisher Ellison, 2011. "Strategic Entry Deterrence and the Behavior of Pharmaceutical Incumbents Prior to Patent Expiration," American Economic Journal: Microeconomics, American Economic Association, vol. 3(1), pages 1-36, February.
    5. Andrea Vaona & Guido Ascari, 2012. "Regional Inflation Persistence: Evidence from Italy," Regional Studies, Taylor & Francis Journals, vol. 46(4), pages 509-523, June.
    6. Lawrence Dacuycuy, 2006. "Explaining male wage inequality in the Philippines: non-parametric and semiparametric approaches," Applied Economics, Taylor & Francis Journals, vol. 38(21), pages 2497-2511.
    7. Helene Couprie & Eugenio Peluso & Alain Trannoy, 2007. "From Household to Individual Welfare Comparisons: A Double Concavity Test," IDEP Working Papers 0701, Institut d'economie publique (IDEP), Marseille, France, revised 01 2007.
    8. Ellison, Glenn & Ellison, Sara Fisher, 2000. "A simple framework for nonparametric specification testing," Journal of Econometrics, Elsevier, vol. 96(1), pages 1-23, May.
    9. Zapata, Hector O. & Sulgham, Anil K., 2006. "A Semiparametric Approach to Estimate Engel curves using the US Micro Data," 2006 Annual meeting, July 23-26, Long Beach, CA 21092, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    10. Hall, Peter & Yatchew, Adonis, 2005. "Unified approach to testing functional hypotheses in semiparametric contexts," Journal of Econometrics, Elsevier, vol. 127(2), pages 225-252, August.
    11. Emmanuel Guerre & Pascal Lavergne, 2001. "Rate-optimal data-driven specification testing in regression models," Econometrics 0107001, EconWPA.
    12. Couprie, Hélène & Peluso, Eugenio & Trannoy, Alain, 2010. "Is power more evenly balanced in poor households?," Journal of Public Economics, Elsevier, vol. 94(7-8), pages 493-507, August.
    13. Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, number 8355, June.
    14. Lawrence Dacuycuy, 2006. "On the finite sampling properties of the Zheng test for omitted and irrelevant variable problems," Applied Economics Letters, Taylor & Francis Journals, vol. 13(11), pages 681-684.
    15. repec:eee:econom:v:200:y:2017:i:1:p:1-16 is not listed on IDEAS
    16. Li, Qi & Hsiao, Cheng & Zinn, Joel, 2003. "Consistent specification tests for semiparametric/nonparametric models based on series estimation methods," Journal of Econometrics, Elsevier, vol. 112(2), pages 295-325, February.
    17. Ait-Sahalia, Yacine & Bickel, Peter J. & Stoker, Thomas M., 2001. "Goodness-of-fit tests for kernel regression with an application to option implied volatilities," Journal of Econometrics, Elsevier, vol. 105(2), pages 363-412, December.
    18. Aït-Sahalia, Yacine. & Bickel, Peter J. & Stoker, Thomas M., 1994. "Goodness-of-fit tests for regression using kernel methods," Working papers 3747-94., Massachusetts Institute of Technology (MIT), Sloan School of Management.
    19. Marilena Furno, 2010. "A robust test of specification based on order statistics," Computational Statistics, Springer, vol. 25(4), pages 707-723, December.
    20. Zheng, Xu, 2008. "Testing for discrete choice models," Economics Letters, Elsevier, vol. 98(2), pages 176-184, February.
    21. Miles, Daniel & Mora, Juan, 2003. "On the performance of nonparametric specification tests in regression models," Computational Statistics & Data Analysis, Elsevier, pages 477-490.
    22. repec:ebl:ecbull:v:3:y:2005:i:21:p:1-6 is not listed on IDEAS
    23. Victor Chernozhukov & Sokbae Lee & Adam M. Rosen, 2013. "Intersection Bounds: Estimation and Inference," Econometrica, Econometric Society, pages 667-737.
    24. Lin, Zhongjian & Li, Qi & Sun, Yiguo, 2014. "A consistent nonparametric test of parametric regression functional form in fixed effects panel data models," Journal of Econometrics, Elsevier, vol. 178(P1), pages 167-179.

    More about this item

    Keywords

    economic models ; tests ; econometrics;

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General

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