<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

Pubblicato online: 01 mar 2018

Pagine: 265 - 301

Ricevuto: 01 ago 2015

Accettato: 01 ott 2017

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

Parole chiave
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

Pubblicato online: 01 mar 2018

Pagine: 265 - 301

Ricevuto: 01 ago 2015

Accettato: 01 ott 2017

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

Parole chiaveUnobserved 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.

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