Total hits 17.168
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Übergänge von jungen Menschen mit Behinderungen an der ersten Schwelle. Potentiale und Herausforderungen der BA-BIBB-IAB Bewerberbefragung 2024 (im Erscheinen)
Reims, N. & Weller, S. (2025): Übergänge von jungen Menschen mit Behinderungen an der ersten Schwelle. Potentiale und Herausforderungen der BA-BIBB-IAB Bewerberbefragung 2024 (im Erscheinen). In: Gemeinsam leben.
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Effects of Replacing Telephone with Web, Mail, and Mixed-Mode Data Collection in an Establishment Follow-Up Survey (im Erscheinen)
Globisch, C., Küfner, B., Sakshaug, J. & Zins, S. (2025): Effects of Replacing Telephone with Web, Mail, and Mixed-Mode Data Collection in an Establishment Follow-Up Survey (im Erscheinen). In: Survey research methods.
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Do minimum wages increase job satisfaction?
Bossler, M. & Broszeit, S. (2017): Do minimum wages increase job satisfaction? Micro data evidence from the new German minimum wage. In: Labour, Vol. 31, No. 4, p. 480-493. DOI:10.1111/labr.12117
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The scars of youth
Schmillen, A. & Umkehrer, M. (2018): The scars of youth. Effects of early-career unemployment on future unemployment experience. In: International Labour Review, Vol. 156, No. 3/4, p. 465-494. DOI:10.1111/ilr.12079
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Labour Mobility in German Establishments during the COVID-19 Crisis: Panel Data Analyses with Special Reference to Short-Time Work and Working from Home
Bellmann, L., Bellmann, L. & Hübler, O. (2023): Labour Mobility in German Establishments during the COVID-19 Crisis: Panel Data Analyses with Special Reference to Short-Time Work and Working from Home. (IZA discussion paper / Forschungsinstitut zur Zukunft der Arbeit 15935), Bonn, 23 p.
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Auswirkungen des gesetzlichen Mindestlohns aus ökonomischer Perspektive
Bossler, M. (2019): Auswirkungen des gesetzlichen Mindestlohns aus ökonomischer Perspektive. In: C. Arnold & P. Fischinger (Hrsg.) (2019): Mindestlohn: interdisziplinäre Betrachtungen, Tübingen, Mohr Siebeck p. 43-65.
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Combining Scientific and Non-scientific Surveys to Improve Estimation and Reduce Costs
Sakshaug, J., Wiśniowski, A., Perez-Ruiz, D. & Blom, A. (2021): Combining Scientific and Non-scientific Surveys to Improve Estimation and Reduce Costs. In: T. Rudas & G. Péli (eds.) (2021): Pathways between social science and computational social science, Springer p. 71-93. DOI:10.1007/978-3-030-54936-7_4
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Methods to Estimate Causal Effects
Collischon, M. (2022): Methods to Estimate Causal Effects. An Overview on IV, DiD and RDD and a Guide on How to Apply them in Practice. In: Soziale Welt, Vol. 73, No. 4, p. 713 -735. DOI:10.5771/0038-6073-2022-4-713