<abstract xmlns="http://www.w3.org/1999/xhtml"><p> 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.</p></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.

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

Journal of Official Statistics

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

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...

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

Published Online: Mar 01, 2018

Page range: 265 - 301

Received: Aug 01, 2015

Accepted: Oct 01, 2017

DOI: https://doi.org/10.1515/jos-2018-0012

Keywords
Unobserved components model, state space model, national accounts, overtime work, working-time accounts

© by Roland Weigand

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

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

Published Online: Mar 01, 2018

Page range: 265 - 301

Received: Aug 01, 2015

Accepted: Oct 01, 2017

DOI: https://doi.org/10.1515/jos-2018-0012

KeywordsUnobserved components model, state space model, national accounts, overtime work, working-time accounts

© by Roland Weigand

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Keywords
Unobserved components model, state space model, national accounts, overtime work, working-time accounts