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A new approach to bootstrap inference in functional coefficient models

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  • Herwartz, H.
  • Xu, F.
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Abstract

To infer on functional dependence of regression parameters, a new, factor based bootstrap approach is introduced, that is robust under various forms of heteroskedastic error terms. Modeling the functional coefficient parametrically, the bootstrap approximation of an F-statistic is shown to hold asymptotically. In simulation studies with both parametric and nonparametric functional coefficients, factor based bootstrap inference outperforms the wild bootstrap and pairs bootstrap approach, according to its rejection frequencies under the null hypothesis. Applying the functional coefficient model to a cross sectional investment regression on savings, the saving retention coefficient is found to depend on third variables as the population growth rate and the openness ratio.

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Bibliographic Info

Article provided by Elsevier in its journal Computational Statistics & Data Analysis.

Volume (Year): 53 (2009)
Issue (Month): 6 (April)
Pages: 2155-2167

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Handle: RePEc:eee:csdana:v:53:y:2009:i:6:p:2155-2167

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  1. Russell Davidson & Emmanuel Flachaire, 2000. "The Wild Bootstrap, Tamed at Last," Econometric Society World Congress 2000 Contributed Papers 1413, Econometric Society.
  2. Feldstein, Martin & Horioka, Charles, 1980. "Domestic Saving and International Capital Flows," Economic Journal, Royal Economic Society, vol. 90(358), pages 314-29, June.
  3. White, Halbert, 1980. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica, Econometric Society, vol. 48(4), pages 817-38, May.
  4. Horowitz, J. & Hardle, W., 1992. "Testing a Parametric Model Against a Semiparametric Alternative," Discussion Paper 1992-19, Tilburg University, Center for Economic Research.
  5. Aneiros-Perez, G. & Vilar-Fernandez, J.M., 2008. "Local polynomial estimation in partial linear regression models under dependence," Computational Statistics & Data Analysis, Elsevier, vol. 52(5), pages 2757-2777, January.
  6. Horowitz, J.L., 1992. "Testing a Parametric Model Against a Semiparametric Alternative," Papers 9219, Tilburg - Center for Economic Research.
  7. Zongwu Cai & Jianqing Fan & Qiwei Yao, 2000. "Functional-coefficient regression models for nonlinear time series," LSE Research Online Documents on Economics 6314, London School of Economics and Political Science, LSE Library.
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Cited by:
  1. Herwartz, Helmut & Walle, Yabibal M., 2014. "Determinants of the link between financial and economic development: Evidence from a functional coefficient model," Economic Modelling, Elsevier, vol. 37(C), pages 417-427.
  2. Herwartz, H. & Xu, F., 2010. "A functional coefficient model view of the Feldstein-Horioka puzzle," Journal of International Money and Finance, Elsevier, vol. 29(1), pages 37-54, February.
  3. Helmut Herwartz & Israel Waichman, 2010. "A comparison of bootstrap and Monte-Carlo testing approaches to value-at-risk diagnosis," Computational Statistics, Springer, vol. 25(4), pages 725-732, December.
  4. Steffen Ahrens & Matthias Hartmann, 2014. "State-dependence vs. Time-dependence: An Empirical Multi-Country Investigation of Price Sluggishness," Kiel Working Papers 1907, Kiel Institute for the World Economy.

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