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Data Transformation and Forecasting in Models with Unit Roots and Cointegration

  • John C. Chao

    (University of Maryland)

  • Valentina Corradi

    (University of Exeter)

  • Norman R. Swanson

    ()

    (Department of Economics, Texas A&M University)

We perform a series of Monte Carlo experiments in order to evaluate the impact of data transformation on forecasting models, and find that vector error-corrections dominate differenced data vector autoregressions when the correct data transformation is used, but not when data are incorrectly tansformed, even if the true model contains cointegrating restrictions. We argue that one reason for this is the failure of standard unit root and cointegration tests under incorrect data transformation.

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Article provided by Society for AEF in its journal Annals of Economics and Finance.

Volume (Year): 2 (2001)
Issue (Month): 1 (May)
Pages: 59-76

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Handle: RePEc:cuf:journl:y:2001:v:2:i:1:p:59-76
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