Separating seasonal components from other sources of economic fluctuations is crucial for both economic modeling and policy making. Practitioners treat seasonality as noise to be removed before estimating models and tend to apply deseasonalizing methods in a rather mechanic manner. Removing seasonal components is, nevertheless, not a trivial task. This technical note shows that the most popular deseasonalizing methods distort the time series properties of the variables and, thus, cannot be considered harmless procedures. Modern time-series techniques for non stationary processes are applied to the study of the seasonal components of the 15 main macroeconomic variables of the Chilean economy. The main result is that the presence of seasonal unit roots render standard deseasonalizing techniques inadequate and models based on seasonally-adjusted data unreliable.
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Article provided by Instituto de Economía. Pontificia Universidad Católica de Chile. in its journal Cuadernos de Economía.
Find related papers by JEL classification: C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Hypothesis Testing C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Estimation C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions
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Rómulo A.Chumacero & Francisco A.Gallego, 2002.
"Trends and cycles in real-time,"
Estudios de Economia,
University of Chile, Department of Economics, vol. 29(2 Year 20), pages 211-229, December.
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