This project analyzes how a principal can motivate an agent to conserve rather than exploit a depletable resource. This dynamic problem is relevant for tropical deforestation as well as for other environmental problems. It is shown that the smaller is the agent's discount factor (e.g., because...

This paper sheds new light on the role of communication for cartel formation. Using machine learning to evaluate free-form chat communication among firms in a laboratory experiment, we identify typical communication patterns for both explicit cartel formation and indirect attempts to collude...

We discuss public pension systems in a multi-period overlapping generations model with gerontologically founded human aging and a special focus on occupation-specific morbidity and mortality. We examine how distinct replacement rates for white-collar and blue-collar workers and early retirement...

We study the interplay between intragenerational and intergenerational equity in an economy with two countries producing and consuming from national capital stocks. We characterize the sustainable development path that a social planner would implement to achieve intertemporal egalitarianism. If...

Continuous longevity improvements and population ageing have led countries to modify national public pension schemes by increasing the standard and early retirement ages in a discretionary, scheduled, or automatic way, and by making it harder for people to retire prematurely. To this end,...

How do banks facilitate creative destruction and shape firm turnover? We develop a dynamic general equilibrium model of bank credit reallocation with endogenous firm entry and exit that allows for both theoretical and quantitative analysis. By restructuring loans to firms with poor prospects and...

Based on administrative data of unemployed in Belgium, we estimate the labour market effects of three training programmes at various aggregation levels using Modified Causal Forests, a causal machine learning estimator. While all programmes have positive effects after the lock-in period, we find...

To successfully reduce student attrition, it is imperative to understand what the underlying determinants of attrition are and which students are at risk of dropping out. We develop an early detection system (EDS) using administrative student data from a state and a private university to predict...

Artificial intelligence (AI) is starting to pervade the economic and social life rendering strategic interactions with artificial agents more and more common. At the same time, experimental economic research has increasingly employed computer players to advance our understanding of strategic...

While traditional empirical models using determinants like size and trade costs are able to predict RTA formation reasonably well, we demonstrate that allowing for machine detected non-linear patterns helps to improve the predictive power of RTA formation substantially. We employ machine...