Targeted Wage Subsidies and Firm Performance

Joint work with Oskar Nordström Skans and Johan Vikström

Labour Economics, 2018, 53, pp. 33-45

This paper studies how targeted wage subsidies affect the performance of the recruiting firms. Using Swedish matched employer-employee administrative data from the period 1998–2008, we show that treated firms substantially outperform other recruiting firms after hiring through subsidies, despite identical pre-treatment performance levels and trends in a wide set of key dimensions. The pattern is less clear from 2007 onwards, after a reform removed the involvement of caseworkers from the subsidy approval process. Overall, our results suggest that targeted employment subsidies can have large positive effects on post-match outcomes of the hiring firms, at least if the policy environment allows for pre-screening by caseworkers.

Working papers

Threat Effects of Monitoring and Unemployment Insurance Sanctions: Evidence from Two Reforms

The paper provides among the first quasi-experimental estimates of the threat of unemployment insurance (UI) benefit sanctions on job-exit rates. Using a difference-in-differences design, I exploit two reforms of the Swedish UI system that made monitoring and sanctions considerably stricter at different points in time for (i) UI claimants and (ii) job-seekers who exhausted their UI benefits and therefore receive alternative “activity support” benefits instead. Results show that men (in particular if long-term unemployed) respond to monitoring and the threat of sanctions by finding jobs faster. By contrast, the existing literature has almost exclusively focused on estimating how job-finding rates respond for those actually receiving a sanction. I estimate such “sanction-imposition effects” and find that they are similar in size for men and women. I further show that properly aggregated sanction-imposition effects explain very little of the overall reform effects for males, and that they are sufficiently small to be consistent with the small and insignificant reform effects found for women. A direct policy implication is that the total impact of monitoring and sanctions may be severely underestimated when focusing only on the sanction imposition effects as is typically done in the literature.

Empirical Monte Carlo Evidence on Estimation of Timing-of-Events Models

Joint work with Gerard J. van den Berg and Johan Vikström

This paper uses an Empirical Monte Carlo simulation approach to study estimation of Timing-of-Events (ToE) models. We exploit rich Swedish data of jobseekers with information on participation in a training program to simulate placebo treatment durations. We first use these simulations to examine which covariates are major confounding variables to be included in selection models. We then show that the joint inclusion of specific types of short-term employment history variables (notably, the share of time spent in employment), together with baseline socio-economic characteristics, regional and inflow timing information, is able to remove selection bias. Next, we omit sets of variables and estimate ToE models with discrete distributions for the ensuing systematic unobserved heterogeneity. In many cases the ToE approach provides accurate effect estimates, especially if calendar-time variation in the unemployment rate of the local labor market is taken into account. However, assuming too many or too few support points for the unobserved heterogeneity may lead to large biases. Information criteria, in particular those penalizing parameter abundance, are useful to select the number of support points.

Comparing Sequence Data Models: Prediction and Dissimilarities

Joint work with Raffaella Piccarreta and Marco Bonetti

We propose different methods for comparing the ability of competing non-nested event history models to generate trajectories that are similar to the observed ones. We first introduce alternative distance-based criteria to compare pairwise dissimilarities between observed and simulated sequences. Next, we estimate two alternative semi-Markov multi-state models using data on family formation and childbearing decisions from the Dutch Fertility and Family Survey. We use the estimated models to simulate event histories and to illustrate the proposed comparison criteria.