• Graduate program
    • Why Tinbergen Institute?
    • Program Structure
    • Courses
    • Course Registration
    • Recent PhD Placements
    • Admissions
    • Facilities
  • Research
  • News
  • Events
    • Events Calendar
    • Tinbergen Institute Lectures
    • Annual Tinbergen Institute Conference
    • Events Archive
    • Summer School
      • Crash Course in Experimental Economics
      • Behavioral Macro and Complexity
      • Introduction in Genome-Wide Data Analysis
      • Econometric Methods for Forecasting and Data Science
  • Times

Harvey, A., Koopman, S.J. and Riani, M. (1997). The modeling and seasonal adjustment of weekly observations Journal of Business and Economic Statistics, 15(3):354--368.

  • Journal
    Journal of Business and Economic Statistics

Several important economic time series are recorded on a particular day every week. Seasonal adjustment of such series is difficult because the number of weeks varies between 52 and 53 and the position of the recording day changes from year to year. In addition certain festivals, most notably Easter, take place at different times according to the year. This article presents a solution to problems of this kind by setting up a structural time series model that allows the seasonal pattern to evolve over time and enables trend extraction and seasonal adjustment to be carried out by means of state-space filtering and smoothing algorithms. The method is illustrated with a Bank of England series on the money supply.