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Testing for nonlinearity in mean in the presence of heteroskedasticity

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  • Stan Hurn
  • Ralf Becker

Abstract

This paper considers an important practical problem in testing time-series data for nonlinearity in mean, namely, the distortion in the size of the test encountered if the the data are heteroskedastic. It is shown that using a heteroskedastic consistent auxiliary regression together with the wild bootstrap is an e®ective way of dealing with the problem. Simulation results indicate that signi¯cant improvements in empirical size are obtained, particularly in small samples.

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Bibliographic Info

Paper provided by School of Economics and Finance, Queensland University of Technology in its series Stan Hurn Discussion Papers with number 2006-02.

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Date of creation: 15 Jun 2006
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Handle: RePEc:qut:sthurn:2006-02

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  3. Sílvia Gonçalves & Halbert White, 2001. "The Bootstrap of the Mean for Dependent Heterogeneous Arrays," CIRANO Working Papers 2001s-19, CIRANO.
  4. Emmanuel Flachaire, 1999. "A better way to bootstrap pairs," Post-Print halshs-00175892, HAL.
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Cited by:
  1. Andrea Fracasso & Giuseppe Vittucci Marzetti, 2012. "International R&D spillovers, absorptive capacity and relative backwardness: a panel smooth transition regression model," Department of Economics Working Papers 1203, Department of Economics, University of Trento, Italia.
  2. Carlo Altavilla & Paul De Grauwe, 2005. "Non-Linearities in the Relation between the Exchange Rate and its Fundamentals," CESifo Working Paper Series 1561, CESifo Group Munich.
  3. Giulio Cainelli & Andrea Fracasso & Giuseppe Vittucci Marzetti, 2012. "Spatial agglomeration and productivity in Italy: a panel smooth transition regression approach," Openloc Working Papers 1204, Public policies and local development.

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