Bottom-up economic forecasting of regional unemployment in Germany

Kern, Christoph ; Lin, Cinny ; Ganesh, Vighnesh Natarajan ; Rathi, Prakhar ; Sasson, Amit

Document Type: Book chapter
Year of publication: 2022
Book title: Neue Dimensionen in Data Science : Interdisziplinäre Ansätze und Anwendungen aus Wissenschaft und Wirtschaft
Page range: 299-311
Publisher: Wawrzyniak, Barbara ; Herter, Michael
Place of publication: Berlin
Publishing house: Wichmann Verlag
ISBN: 978-3-87907-721-2 , 3-87907-721-5 , 978-3-87907-722-9
Related URLs:
Publication language: English
Institution: School of Social Sciences > Social Data Science and Methodology (Keusch 2022-)
Subject: 330 Economics
Abstract: In this chapter, we present and compare various approaches to grouping counties to optimize forecasts of regional unemployment rates. As a reference, we first group counties based on their administrative structures, i.e., each county's state. This approach is compared to a set of data-driven techniques that utilize unsupervised machine learning. We show that grouping counties based on arbitrary historic borders may not be the best approach, while clustering the counties based on their economic similarities may improve forecasting results.

Dieser Eintrag ist Teil der Universitätsbibliographie.

Metadata export


+ Search Authors in

+ Page Views

Hits per month over past year

Detailed information

You have found an error? Please let us know about your desired correction here: E-Mail

Actions (login required)

Show item Show item