We propose a new method for solving high-dimensional dynamic programming problems and recursive competitive equilibria with a large (but finite) number of heterogeneous agents using deep learning. The "curse of dimensionality" is avoided due to four complementary techniques: (1) exploiting...

This paper develops a new equilibrium model of two-sided search where agents have multiple attributes and general payoff functions. The model can be applied to several substantive issues. Here we use it to provide a novel understanding of the separate effects of equal opportunities for women in...

This paper combines the standard incomplete markets model of uninsurable idiosyncratic risks and borrowing constraints with the Arrow/Romer approach to endogenous growth to analyze the interaction of risk, growth, and inequality, the latter also endogenously determined in equilibrium. We derive...

Climate change is predicted to substantially alter forest growth. Optimally, forest owners should take these future changes into account when making rotation decisions today. However, the fundamental uncertainty surrounding climate change makes predicting these shifts hard. Hence, this paper...

Labour income follows a deterministic growth trend and fluctuates between two values. Interest rates are drawn initially, fluctuate between two values and can differ in their arrival rates. Low interest rates imply a stationary long-run wealth distribution, high interest rates imply exploding...

This paper addresses the steep learning curve in Machine Learning faced by non-computer scientists, particularly social scientists, stemming from the absence of a primer on its fundamental principles. I adopt a pedagogical strategy inspired by the adage ”once you understand OLS, you can work...

Ride-hailing applications create new challenges for governments providing transit services, but also create new opportunities to raise tax revenue. To shed light on the effect of taxing or subsidizing ride-hailing applications, we extend a pseudo-monocentric city model to include multiple...

We analyze optimal compensation schedules for the directors of two plants belonging to the same owner and producing the same good but serving geographically differentiated markets. Since the outcome of each director depends on his own effort and on a random variable representing market...

We develop a simple model of managing a system subject to pollution damage under risk of an abrupt and random jump in the damage coefficient. The model allows the full dynamic characterization of the optimal emission policies under uncertainty. The results, that imply prudent behavior due to...