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

Weigand Roland (), Wanger Susanne () and Zapf Ines ()
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Weigand Roland: Institute for Employment Research (IAB) Regensburger Strasse 104, 90478 Nuremberg, Germany
Wanger Susanne: Institute for Employment Research (IAB) Regensburger Strasse 104, 90478 Nuremberg, Germany
Zapf Ines: Institute for Employment Research (IAB) Regensburger Strasse 104, 90478 Nuremberg, Germany
Authors registered in the RePEc Author Service: Roland Jucknewitz

Journal of Official Statistics, 2018, vol. 34, issue 1, 265-301

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.

Keywords: Unobserved components model; state space model; national accounts; overtime work; working-time accounts (search for similar items in EconPapers)
Date: 2018
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https://doi.org/10.1515/jos-2018-0012 (text/html)

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Working Paper: Factor structural time series models for official statistics with an application to hours worked in Germany (2015)
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:offsta:v:34:y:2018:i:1:p:265-301:n:12

DOI: 10.1515/jos-2018-0012

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