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On data transformations and evidence of nonlinearity

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  • de Bruin, P.
  • Franses, Ph.H.B.F.

Abstract

In this paper we examine the interaction between data transformation and the empirical evidence obtained when testing for (non-)linearity. For this purpose we examine nonlinear features in 64 monthly and 53 quarterly US macroeconomic variables for a range of Box-Cox data transformations. Our general finding is that evidence of nonlinearity is not independent of the data transformation. Results of simulation experiments substantiate this finding.

Suggested Citation

  • de Bruin, P. & Franses, Ph.H.B.F., 1998. "On data transformations and evidence of nonlinearity," Econometric Institute Research Papers EI 9823, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    • Handle: RePEc:ems:eureir:1548
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    Cited by:

    1. Paul De Bruin & Philip Hans Franses, 1999. "Forecasting power-transformed time series data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 26(7), pages 807-815.
    2. Rossen Anja, 2016. "On the Predictive Content of Nonlinear Transformations of Lagged Autoregression Residuals and Time Series Observations," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 236(3), pages 389-409, May.
    3. Franses, Philip Hans & de Bruin, Paul, 2002. "On data transformations and evidence of nonlinearity," Computational Statistics & Data Analysis, Elsevier, vol. 40(3), pages 621-632, September.

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