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Dynamic evaluation of job search assistance

Bibliographic Data

ID21653300
AuthorsStephen Kastoryano (Department of Economics University of Reading Reading UK, corresponding author), Bas Van Der Klaauw (0000-0003-0476-9397, Department of Economics VU University Amsterdam Amsterdam The Netherlands)
Year2022
Volume37
Issue2
Pages227-241
Publication date2022-03-01
Open AccessYes
TypeARTICLE
VenueJournal of Applied Econometrics (JOURNAL)
Journal identifiersISSN: 1099-1255 • E-ISSN: 0883-7252
PublisherWiley (PUBLISHER • GB)
DOI10.1002/jae.2866
OpenAlexW2161675681
LanguageEN
Citations received4
References cited37

This paper evaluates a job search assistance program for unemployed teachers where the assignment to the program is dynamic. We discuss the methodology of estimating dynamic treatment effects and identification conditions. In the empirical analysis, we use administrative data from a unique institutional environment in which we observe all variables determining assignment to the job search assistance program. This allows us to compare results from a dynamic discrete‐time evaluation model and a continuous‐time duration model. All approaches show that participation in the job search assistance program reduces exit rates from unemployment, in particular when starting the program early during the spell of unemployment. The discrete‐time approach makes less strict parametric assumptions, but the results are sensitive to the choice of control group and the unit of time

Discrete choice · Discrete time and continuous time · Econometrics · Economic growth · Economics · Machine learning · Operations research · Parametric statistics · Spell · Statistics · Unemployment · Advanced Causal Inference Techniques · Computer Science · Labor market dynamics and wage inequality · Mathematics

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Citations per year0.33
Citation span2014 - 2025 (12)
Highly citedNo

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