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Time Series Properties of the German Production Index


  • Gebhard Flaig*



The production index is an important indicator for assessing the cyclical state of the economy. Unfortunately, the monthly time series is contaminated by many noisy components like seasonal variations, calendar and vacation effects. Only part of those nuisance components are explicitly considered in the seasonal adjustment procedures used by statistical agencies. In this paper, we propose a more flexible specification for the seasonal and working day effects and introduce an indicator for the summer vacations effect. We allow for time-varying parameters and show that the resulting Unobserved Components Model delivers more reliable results for the trend and cycle components of the production index.
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Suggested Citation

  • Gebhard Flaig*, 2005. "Time Series Properties of the German Production Index," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 89(4), pages 419-434, November.
  • Handle: RePEc:spr:alstar:v:89:y:2005:i:4:p:419-434 DOI: 10.1007/s10182-005-0213-x

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    References listed on IDEAS

    1. Regina Riphahn & Oliver Serfling, 2005. "Item non-response on income and wealth questions," Empirical Economics, Springer, vol. 30(2), pages 521-538, September.
    2. Joachim R. Frick & Markus M. Grabka, 2003. "Missing Income Data in the German SOEP: Incidence, Imputation and its Impact on the Income Distribution," Discussion Papers of DIW Berlin 376, DIW Berlin, German Institute for Economic Research.
    3. Horton N. J. & Lipsitz S. R., 2001. "Multiple Imputation in Practice: Comparison of Software Packages for Regression Models With Missing Variables," The American Statistician, American Statistical Association, vol. 55, pages 244-254, August.
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    Cited by:

    1. Monika Ruschinski, 2006. "Investigating the Cyclical Properties of World Trade," ifo Working Paper Series 30, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    2. Posch, Olaf, 2009. "Structural estimation of jump-diffusion processes in macroeconomics," Journal of Econometrics, Elsevier, vol. 153(2), pages 196-210, December.
    3. Löschel Andreas & Oberndorfer Ulrich, 2009. "Oil and Unemployment in Germany," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 229(2-3), pages 146-162, April.
    4. Bloechl, Andreas, 2014. "Penalized Splines, Mixed Models and the Wiener-Kolmogorov Filter," Discussion Papers in Economics 21406, University of Munich, Department of Economics.

    More about this item


    Production index; seasonal adjustment; working day effect; business cycles; unobserved components models; JEL C22; E32;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles


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