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Testing for Nonlinearity in Mean in the Presence of Heteroskedasticity

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  • Stan Hurn

    ()
    (Economics, School of Social Sciences, University of Manchester, United Kingdom)

  • Ralf Becker

    (School of Economics and Finance, Queensland University of Technology, Brisbane, 4001)

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

Article provided by Queensland University of Technology (QUT), School of Economics and Finance in its journal Economic Analysis and Policy (EAP).

Volume (Year): 39 (2009)
Issue (Month): 2 (September)
Pages: 311-326

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Handle: RePEc:eap:articl:v39:y:2009:i:2:p:311-326

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Postal: GPO Box 2434, BRISBANE QLD 4001
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Keywords: nonlinearity in mean; heteroskedasticity; wild bootstrap; empirical size and power;

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Cited by:
  1. Andrea Fracasso & Giuseppe Vittucci Marzetti, 2014. "International R&D Spillovers, Absorptive Capacity and Relative Backwardness: A Panel Smooth Transition Regression Model," International Economic Journal, Taylor & Francis Journals, vol. 28(1), pages 137-160, March.
  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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