Analysing establishment survey non-response using administrative data and machine learning

Küfner, Benjamin; Sakshaug, Joseph W. und Zins, Stefan (2022): Analysing establishment survey non-response using administrative data and machine learning. In: Journal of the Royal Statistical Society / Series A (Statistics in Society), Bd. 185, Nr. SUPPL 2: S310-S342

Abstract

Declining participation in voluntary establishment surveys poses a risk of increasing non-response bias over time. In this paper, response rates and non-response bias are examined for the 2010-2019 IAB Job Vacancy Survey. Using comprehensive administrative data, we formulate and test several theory-driven hypotheses on survey participation and evaluate the potential of various machine learning algorithms for non-response bias adjustment. The analysis revealed that while the response rate decreased during the decade, no concomitant increase in aggregate non-response bias was observed. Several hypotheses of participation were at least partially supported. Lastly, the expanded use of administrative data reduced non-response bias over the standard weighting variables, but only limited evidence was found for further non-response bias reduction through the use of machine learning methods.

• Dokumententyp: Zeitschriftenartikel
• Fakultät: Mathematik, Informatik und Statistik > Statistik
• Themengebiete: 500 Naturwissenschaften und Mathematik > 510 Mathematik
• ISSN: 0964-1998
• Sprache: Englisch