Accessible Published by De Gruyter Oldenbourg February 13, 2016

Editorial Announcement

Peter Winker

This first issue of volume 236 of the Jahrbücher für Nationalökonomie und Statistik / Journal of Economics and Statistics marks the start of a new special section entitled Data Observer. Contributions to this series describe data that can be used in empirical research in economics, and in the social sciences in general. While most of these data sets are micro data at the level of individuals, households, or firms (including linked employer-employee data sets), cross section and time series data at an aggregate level are covered as well. The contributions to this section describe the information that is available in the data sets, give examples of topics investigated with the data, and inform readers how to access these data for their own research. The authors are experts who often were in charge of collecting or building the data sets. Furthermore, papers in the series portray the research data centers and data service centers of data producing institutions that allow academic researchers to work with (mostly confidential) micro data for individuals and firms. All articles published in the Data Observer section are made available free of charge from the website of the Journal (http://www.jbnst.de/en).

The first paper in the new section “The German Time Series Dataset 1834–2012” by Thomas Rahlf presents a comprehensive set of historical macrodata. It is assumed to fill a gap as Germany has been often neglected in comparative analyses covering longer time periods due to the lack of available reference statistics.

Adding the section Data Observer is one element of the editors’ effort to make research data available – including those related to the research papers published in the Journal. In fact, the Journal of Economics and Statistics maintains a data archive providing data and code for all empirical papers published in recent years. If data cannot be published in the data archive due to data protection rules etc., detailed information on data access is provided instead. According to Duvendack et al. (2015: 173), the Journal of Economics and Statistics belongs to the group of only 27 journals with the 333 journal listed in Web of Science in the field of economics with such a data archiving policy. Only 10 out of these 333 journals also have an explicit policy on replication studies, and again, the Journal of Economics and Statistics belongs to this group aiming at fostering replication studies as a mean to improve the quality of empirical studies and our trust in published results. Ludsteck and Seth (2014) is a recent replication study in the Journal of Economics and Statistics, which can serve as a role model for this type of contribution. More replication studies are welcome.

The data archive will see a major progress since the Journal serves as a pilot for EDaWaX’s application (http://www.edawax.de/about/) for data archives provided by economic journals. This will allow both a more structured deposit of research data and additional information on published articles using standardized metadata and an automated doi-assignment to research data. In parallel, also each article published in the Journal will be attributed a doi.

References

Ludsteck, Johannes, Stefan Seth (2014), Comment on: “Unemployment Compensation and Wages: Evidence from the German Hartz Reforms” by Stefan Arent and Wolfgang Nagl. Journal of Economics and Statistics 234(5): 635–644. Search in Google Scholar

Duvendack, Maren, Richard W. Palmer-Jones, W. Robert Reed (2015), Replications in Economics: A Progress Report. Econ Journal Watch 12(2): 164–191. Search in Google Scholar

Published Online: 2016-2-13
Published in Print: 2016-2-1

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