Center for Economic Policy Analysis (CEPA)
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We analyze workers’ risk preferences and training investments. Our conceptual framework differentiates between the investment risk and insurance mechanisms underpinning training decisions. Investment risk leads risk-averse workers to train less; they undertake more training if it insures them against future losses. We use the German Socio-Economic Panel (SOEP) to demonstrate that risk affinity is associated with more training, implying that, on average, investment risks dominate the insurance benefits of training. Crucially, this relationship is evident only for general training; there is no relationship between risk attitudes and specific training. Thus, as expected, risk preferences matter more when skills are transferable – and workers have a vested interest in training outcomes – than when they are not. Finally, we provide evidence that the insurance benefits of training are concentrated among workers with uncertain employment relationships or limited access to public insurance schemes.
Interest in evaluating the effects of continuous treatments has been on the rise recently. To facilitate the estimation of causal effects in this setting, the present paper introduces entropy balancing for continuous treatments (EBCT) by extending the original entropy balancing methodology of Hainmüller (2012). In order to estimate balancing weights, the proposed approach solves a globally convex constrained optimization problem, allowing for much more computationally efficient implementation compared to other available methods. EBCT weights reliably eradicate Pearson correlations between covariates and the continuous treatment variable. This is the case even when other methods based on the generalized propensity score tend to yield insufficient balance due to strong selection into different treatment intensities. Moreover, the optimization procedure is more successful in avoiding extreme weights attached to a single unit. Extensive Monte-Carlo simulations show that treatment effect estimates using EBCT display similar or lower bias and uniformly lower root mean squared error. These properties make EBCT an attractive method for the evaluation of continuous treatments. Software implementation is available for Stata and R.
Labor market policy tools such as training and sanctions are commonly used to help bring workers back to work. By analogy to medical treatments, the individual exposure to these tools may have side effects. We study effects on health using individual-level population registers on labor market events outcomes, drug prescriptions and sickness absence, comparing outcomes before and after exposure to training and sanctions. We find that training improves cardiovascular and mental health and lowers sickness absence. The results suggest that this is not due to improved employment prospects but rather to instantaneous features of participation such as, perhaps, the adoption of a more rigorous daily routine. Unemployment benefits sanctions cause a short-run deterioration of mental health, possibly due higher stress levels, but this tapers out quickly.
Stochastic uncertainty can cause difficult coordination problems that may hinder mutually beneficial cooperation. We propose a mechanism of ex-post voluntary transfers designed to circumvent these coordination problems and ask whether it can do so. To test this, we implement a controlled laboratory experiment based on a repeatedly played Ultimatum Game with a stochastic endowment. Contrary to our hypothesis, we find that allowing voluntary transfers does not entail an efficiency increase. We suggest and analyze two main reasons for this finding: First, the stochastic uncertainty forces proposers to accept high strategic uncertainty if they intend to cooperate by claiming a low amount (which many proposers do not). Second, many responders behave only incompletely conditionally cooperative by transferring too little (which hinders cooperation in future periods).
Numerous studies investigate which sanctioning institutions prevent cartel formation but little is known as to how these sanctions work. We contribute to understanding the inner workings of cartels by studying experimentally the effect of sanctioning institutions on firms’ communication. Using machine learning to organize the chat communication into topics, we find that firms are significantly less likely to communicate explicitly about price fixing when sanctioning institutions are present. At the same time, average prices are lower when communication is less explicit. A mediation analysis suggests that sanctions are effective in hindering cartel formation not only because they introduce a risk of being fined but also by reducing the prevalence of explicit price communication.
Drinking is Different!
(2020)
Unhealthy behavior can be extremely costly from a micro- and macroeconomic perspective and exploring the determinants of such behavior is highly important from an economist’s point of view. We examine whether locus of control (LOC) can explain alcohol consumption as an important domain of health behavior. LOC measures how much an individual believes that she is in control of the consequences of her own actions for her life’s future outcomes. While earlier literature showed that an increasing internal LOC is associated with increased health-conscious behavior in domains such as smoking, exercise or diets, we find that drinking seems to be different. Using German panel data from the Socio-Economic Panel (SOEP) we find a significant positive effect of having an internal LOC on the probability of moderate and regular drinking. We suggest and discuss two likely mechanisms for this relationship and find interesting gender differences. While social investments play an important role for both men and women, risk perceptions are especially relevant for men.
Envy is an unpleasant emotion. If individuals anticipate that comparing their payoff with the (potentially higher) payoff of others will make them envious, they may want to actively avoid information about other people’s payoffs. Given the opportunity to reduce another person’s payoff, an individual’s envy may trigger behavior that is detrimental to welfare. In this case, if individuals anticipate that they will react in a welfare-reducing way, they may also avoid information about other people’s payoffs from the outset. We investigated these two hypotheses using three experiments. We found that 13% of our potentially envious subjects avoided information when they did not have the opportunity to reduce another participant’s payoff. Psychological scales do not explain this behavior. We also found that voluntarily uninformed subjects did neither deduct less of the payoff nor less frequently than subjects who could not avoid the information.