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Non-Linearities and Unit Roots in G7 Macroeconomic Variables

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  • Aksoy Yunus

    ()
    (Birkbeck College, University of London)

  • Leon-Ledesma Miguel A.

    ()
    (University of Kent)

Abstract

We carry out a meta-analysis on the frequency of unit-roots in macroeconomic time series with a dataset covering 249 variables for the G7 countries. We use linear tests and the three popular non-linear tests (TAR, ESTAR and Markov Switching). In general, the evidence in favour of the random walk hypothesis is weaker than in previous studies. This evidence against unit roots is stronger for real and nominal asset prices. Our results show that rejection of the null of a unit root in the macro dataset is substantially higher for non-linear than linear models. Finally, the results from a Monte Carlo experiment show that rejection frequencies are very close to the nominal size of the test when the DGP is a linear unit root process. This leads us to reject the hypothesis that overfitting deterministic components explains the higher rejection frequencies of nonlinear tests.

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Bibliographic Info

Article provided by De Gruyter in its journal The B.E. Journal of Macroeconomics.

Volume (Year): 8 (2008)
Issue (Month): 1 (February)
Pages: 1-44

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Handle: RePEc:bpj:bejmac:v:8:y:2008:i:1:n:5

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Cited by:
  1. Christopoulos, Dimitris & León-Ledesma, Miguel A., 2010. "Current account sustainability in the US: What did we really know about it?," Journal of International Money and Finance, Elsevier, vol. 29(3), pages 442-459, April.
  2. Stefano Puddu, 2013. "Real Sector and Banking System: Real and Feedback Effects. A Non-Linear VAR Approach," IRENE Working Papers 13-01, IRENE Institute of Economic Research.
  3. Lee, Chien-Chiang & Lee, Jun-De, 2009. "Income and CO2 emissions: Evidence from panel unit root and cointegration tests," Energy Policy, Elsevier, vol. 37(2), pages 413-423, February.
  4. Yavuz, Nilgün Çil & Yilanci, Veli, 2012. "Testing For Nonlinearity In G7 Macroeconomic Time Series," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 69-79, September.

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