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Factor Structural Time Series Models for Official Statistics with an Application to Hours Worked in Germany

Author

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  • Weigand Roland

    (Institute for Employment Research (IAB) Regensburger Strasse 104, 90478 Nuremberg, Germany)

  • Wanger Susanne
  • Zapf Ines

    (Institute for Employment Research (IAB) Regensburger Strasse 104, 90478 Nuremberg, Germany)

Abstract

We introduce a high-dimensional structural time series model, where co-movement between the components is due to common factors. A two-step estimation strategy is presented, which is based on principal components in differences in a first step and state space methods in a second step. The methods add to the toolbox of official statisticians, constructing timely regular statistics from different data sources. In this context, we discuss typical measurement features such as survey errors, statistical breaks, different sampling frequencies and irregular observation patterns, and describe their statistical treatment. The methods are applied to the estimation of paid and unpaid overtime work as well as flows on working-time accounts in Germany, which enter the statistics on hours worked in the national accounts.

Suggested Citation

  • Weigand Roland & Wanger Susanne & Zapf Ines, 2018. "Factor Structural Time Series Models for Official Statistics with an Application to Hours Worked in Germany," Journal of Official Statistics, Sciendo, vol. 34(1), pages 265-301, March.
    • Handle: RePEc:vrs:offsta:v:34:y:2018:i:1:p:265-301:n:12
    DOI: 10.1515/jos-2018-0012
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    Cited by:

    1. Susanne Wanger & Roland Weigand & Ines Zapf, 2016. "Measuring hours worked in Germany – Contents, data and methodological essentials of the IAB working time measurement concept [Die Berechnung der geleisteten Arbeitsstunden in Deutschland – Inhalte,," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), vol. 49(3), pages 213-238, November.
    2. Johann Fuchs & Enzo Weber, 2017. "Long-term unemployment and labour force participation: a decomposition of unemployment to test for the discouragement and added worker hypotheses," Applied Economics, Taylor & Francis Journals, vol. 49(60), pages 5971-5982, December.
    3. Mendolicchio, C. & Pietra, T., 2016. "Endowment redistribution and Pareto improvements in GEI economies," Journal of Mathematical Economics, Elsevier, vol. 67(C), pages 181-190.
    4. Klinger, Sabine & Weber, Enzo, 2016. "Detecting unemployment hysteresis: A simultaneous unobserved components model with Markov switching," Economics Letters, Elsevier, vol. 144(C), pages 115-118.
    5. Wanger, Susanne & Weigand, Roland & Zapf, Ines, 2016. "Measuring hours worked in Germany : contents, data and methodological essentials of the IAB working time measurement concept (Die Berechnung der geleisteten Arbeitsstunden in Deutschland : Inhalte, Da," Journal for Labour Market Research, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], vol. 49(3), pages 213-238.
    6. Eckman, Stephanie & Kreuter, Frauke, 2015. "Misreporting to looping questions in surveys : recall, motivation and burden," IAB-Discussion Paper 201529, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    7. Wanger, Susanne & Weigand, Roland & Zapf, Ines, 2016. "Measuring hours worked in Germany : contents, data and methodological essentials of the IAB working time measurement concept (Die Berechnung der geleisteten Arbeitsstunden in Deutschland : Inhalte, Da," Journal for Labour Market Research, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], vol. 49(3), pages 213-238.

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    More about this item

    Keywords

    Unobserved components model; state space model; national accounts; overtime work; working-time accounts;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics

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