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On the Sensitivity of Unit Root Inference to Nonlinear Data Transformations

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Author Info
Franses, P.H.
Koop, G.

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Abstract

In this paper we analyze the sensitivity of unit root inference to nonlinear transformations through Bayesian techniques. We make joint inference about the Box-Cox transformation, which includes the cases yt and log(yt), and the unit root. When we apply our method to the fourteen Nelson-Plosser series, we find that unit root inference can be very sensitive to the transformation chosen and that the usual practice of taking logs is not always warranted.

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Publisher Info
Paper provided by Erasmus University of Rotterdam - Econometric Institute in its series Papers with number 9648/a.

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Length: 8 pages
Date of creation: 1996
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Handle: RePEc:fth:erroem:9648/a

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Related research
Keywords: UNIT ROOTS ; ECONOMETRICS;

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Find related papers by JEL classification:
C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Bayesian Analysis
C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General

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  1. Valentina Corradi & Norman R. Swanson, 2003. "The Effect of Data Transformation on Common Cycle, Cointegration and Unit Root Tests: Monte Carlo Results and a Simple Test," Departmental Working Papers 200322, Rutgers University, Department of Economics. [Downloadable!]
    Other versions:
  2. Deleersnyder, B. & Geyskens, I. & Gielens, K. & Dekimpe, M.G., 2002. "How Cannibalistic is the Internet Channel?," Research Paper ERS-2002-22-MKT Revision_, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus Uni. [Downloadable!]
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This page was last updated on 2009-12-16.

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