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Forecasting Economic Time Series in the Presence of Variance Instability and Outliers
Bank of Greece, Department of Statistics, Athens, Greece
Department of Statistics and Actuarial-Financial Mathematics, University of the Aegean, Karlovassi, Greece
- 1 Bank of Greece, Department of Statistics, Athens, Greece
- 2 Department of Statistics and Actuarial-Financial Mathematics, University of the Aegean, Karlovassi, Greece
Theoretical Economics Letters·Volume 09 (2019)·Pages 2940–2964·Published 22 November 2019·DOI10.4236/tel.2019.98182
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Abstract
This work examines the impact of data transformation (for variance stabilization) and outlier adjustment (“linearization”) on the quality of univariate time series forecasts, considering each one separately, as well as in combination. Twenty of the most important time series of the Greek economy were used for this purpose. Empirical findings show a significant improvement in forecasts’ confidence intervals, but no substantial improvement in point forecasts. Furthermore, the combined transformation-linearization procedure improves substantially the non-normality problem encountered in many macroeconomic time series.
KeywordsApplied Time Series AnalysisTime Series “Linearization”Time Series Trans-formationOutliersForecasting of Macroeconomic Time SeriesGreek Macroeconomic Time Series
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