Seasonal adjustment of hybrid time series: An application to U.S. regional jobs data

Article type: Research Article

Authors: Phillips, Keith R.^* | Wang, Jianguo

Affiliations: Federal Reserve Bank of Dallas, Dallas, TX, USA

Correspondence: [*] Corresponding author: Keith R. Phillips, Federal Reserve Bank of Dallas, 2200 N Pearl St., Dallas 75201, TX, USA. Tel.: +1 210 978 1409; E-mail:[email protected]

Abstract: Hybrid time series data often require special care in estimating seasonal factors. Series such as the state and metro area Current Employment Statistics produced by the U.S. Bureau of Labor Statistics (BLS) are composed of two different source series that often have two different seasonal patterns. In this paper we address the process to test for differing seasonal patterns within the hybrid series. We also discuss how to apply differing seasonal factors to the separate parts of the hybrid series. Currently, for state employment data, the BLS simply juxtaposes the two different sets of seasonal factors at the transition point between the benchmark part of the data and the survey part. We argue that the seasonal factors should be extrapolated at the transition point or that an adjustment should be made to the level of the unadjusted data to correct for a bias in the survey part of the data caused by differing seasonal factors at the transition month.

Keywords: Current employment statistics, seasonal adjustment, hybrid time series

DOI: 10.3233/JEM-160428

Journal: Journal of Economic and Social Measurement, vol. 41, no. 2, pp. 191-202, 2016