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Nonparametric Hypothesis Testing with Parametric Rates of Convergence

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  • Rilstone, Paul

Abstract

Nonparametric estimators are frequently criticized for their poor performance in small samples. In this paper, the author considers using kernel methods for the estimation of the expected derivatives of a regression function. The proposed estimators are shown to be asymptotically normal and n-consistent. As a consequence, their standard errors are comparable to parametric estimates. An empirical example demonstrates the facility of the approach. Copyright 1991 by Economics Department of the University of Pennsylvania and the Osaka University Institute of Social and Economic Research Association.

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  • Rilstone, Paul, 1991. "Nonparametric Hypothesis Testing with Parametric Rates of Convergence," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 32(1), pages 209-227, February.
    • Handle: RePEc:ier:iecrev:v:32:y:1991:i:1:p:209-27
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    1. Jang-Ting Guo & Rong-Chang Wu, 1998. "Financial Liberalization and the Exchange-Rate Exposure of the Taiwanese Firms: A Nonparametric Analysis of Taiwan," Multinational Finance Journal, Multinational Finance Journal, vol. 2(1), pages 37-61, March.
    2. Bayer, Christian, 2006. "Investment dynamics with fixed capital adjustment cost and capital market imperfections," Journal of Monetary Economics, Elsevier, vol. 53(8), pages 1909-1947, November.
    3. Rodríguez, Francisco & Shelton, Cameron A., 2013. "Cleaning up the kitchen sink: Specification tests and average derivative estimators for growth econometrics," Journal of Macroeconomics, Elsevier, vol. 38(PB), pages 260-273.
    4. Lu, Xuewen & Burke, M.D., 2005. "Censored multiple regression by the method of average derivatives," Journal of Multivariate Analysis, Elsevier, vol. 95(1), pages 182-205, July.
    5. Aysun, Uluc & Guldi, Melanie, 2011. "Exchange rate exposure: A nonparametric approach," Emerging Markets Review, Elsevier, vol. 12(4), pages 321-337.
    6. Hallam, Arne, 1992. "A Brief Overview Of Nonparametric Methods In Economics," Northeastern Journal of Agricultural and Resource Economics, Northeastern Agricultural and Resource Economics Association, vol. 21(2), pages 1-15, October.
    7. Li, Cong & Wang, Yanfei, 2016. "Gradient-based bandwidth selection for estimating average derivatives," Economics Letters, Elsevier, vol. 140(C), pages 19-22.
    8. Lewbel, Arthur, 1995. "Consistent nonparametric hypothesis tests with an application to Slutsky symmetry," Journal of Econometrics, Elsevier, vol. 67(2), pages 379-401, June.
    9. Bayer, Christian, 2008. "On the interaction of financial frictions and fixed capital adjustment costs: Evidence from a panel of German firms," Journal of Economic Dynamics and Control, Elsevier, vol. 32(11), pages 3538-3559, November.
    10. Rob Euwals & Bertrand Melenberg & Arthur van Soest, 1998. "Testing the predictive value of subjective labour supply data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 13(5), pages 567-585.
    11. Lei Jiang & Esfandiar Maasoumi & Jiening Pan & Ke Wu, 2018. "A test of general asymmetric dependence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(7), pages 1026-1043, November.
    12. Junsoo Lee & Seung-Jun Kwak & John List, 2000. "Average Derivative Estimation of Hedonic Price Models," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 16(1), pages 81-91, May.
    13. Christian Bayer, 2001. "Aggregate investment dynamics when firms face fixed investment cost and capital market imperfections," Discussion Papers in Economics 01_13, University of Dortmund, Department of Economics.
    14. C. W. Granger & Esfandiar Maasoumi, 2000. "A Dependence Metric for Nonlinear Time Series," Econometric Society World Congress 2000 Contributed Papers 0421, Econometric Society.
    15. Shouhong Wang, 1996. "Nonparametric econometric modelling: A neural network approach," European Journal of Operational Research, Elsevier, vol. 89(3), pages 581-592, March.
    16. Lee, Myoung-jae & Kim, Young-sook, 2007. "Multinomial choice and nonparametric average derivatives," Transportation Research Part B: Methodological, Elsevier, vol. 41(1), pages 63-81, January.
    17. Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, volume 1, number 8355.
    18. Edna Schechtman & Shlomo Yitzhaki & Taina Pudalov, 2011. "Gini’s multiple regressions: two approaches and their interaction," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(1), pages 67-99.
    19. König, Anja, 1997. "Schätzen und Testen in semiparametrischen partiell linearen Modellen für die Paneldatenanalyse," Hannover Economic Papers (HEP) dp-208, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    20. Henderson Daniel J. & Parmeter Christopher F., 2017. "Root-n Consistent Kernel Density Estimation in Practice," Journal of Econometric Methods, De Gruyter, vol. 6(1), pages 1-10, January.
    21. Livanis, Grigorios T. & Salois, Matthew J. & Moss, Charles B., 2009. "A Nonparametric Kernel Representation of the Agricultural Production Function: Implications for Economic Measures of Technology," 83rd Annual Conference, March 30 - April 1, 2009, Dublin, Ireland 51063, Agricultural Economics Society.

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