Seasonality, Forecast Extensions and Business Cycle Uncertainty

15 Pages Posted: 7 Aug 2012

See all articles by Tommaso Proietti

Tommaso Proietti

University of Rome II - Department of Economics and Finance

Date Written: September 2012

Abstract

Seasonality is one of the most important features of economic time series. The possibility to abstract from seasonality for the assessment of economic conditions is a widely debated issue. In this paper we propose a strategy for assessing the role of seasonal adjustment (SA) on business cycle measurement. In particular, we provide a method for quantifying the contribution to the unreliability of the estimated cycles extracted by popular filters, such as Baxter and King and Hodrick–Prescott (HP). The main conclusion is that the contribution is larger around the turning points of the series and at the extremes of the sample period; moreover, it much more sizeable for highpass filters, like the HP filter, which retain to a great extent the high‐frequency fluctuations in a time series, the latter being the ones that are more affected by SA. If a bandpass component is considered, the effect has reduced size. Finally, we discuss the role of forecast extensions and the prediction of the cycle. For the time series of industrial production considered in the illustration, it is not possible to provide a reliable estimate of the cycle at the end of the sample.

Keywords: Linear filters, Reliability, Seasonal adjustment, Unobserved components

Suggested Citation

Proietti, Tommaso, Seasonality, Forecast Extensions and Business Cycle Uncertainty (September 2012). Journal of Economic Surveys, Vol. 26, Issue 4, pp. 555-569, 2012. Available at SSRN: https://ssrn.com/abstract=2125669 or http://dx.doi.org/10.1111/j.1467-6419.2010.00660.x

Tommaso Proietti (Contact Author)

University of Rome II - Department of Economics and Finance ( email )

Via Columbia, 2
Rome, 00133
Italy

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