Data Transformation and Forecasting in Models With Unit Roots and Cointegration¤
نویسندگان
چکیده
We perform a series of Monte Carlo experiments in order to evaluate the impact of data transformation on forecasting models, and ̄nd that vector error-corrections dominate di®erenced 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. JEL classi ̄cation: C22, C51.
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