Analysing Establishment Survey Non-Response Using Administrative Data and Machine Learning

Author:

Küfner Benjamin1,Sakshaug Joseph W.,Zins Stefan1

Affiliation:

1. Institute for Employment Research (IAB) , Nuremberg , Germany

Abstract

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.

Funder

Institute for Employment Research

Publisher

Oxford University Press (OUP)

Subject

Statistics, Probability and Uncertainty,Economics and Econometrics,Social Sciences (miscellaneous),Statistics and Probability

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