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...

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...

We propose the relaxation algorithm as a simple and powerful method for simulating the transition process in growth models. This method has a number of important advantages: (1) It can easily deal with a wide range of dynamic systems including stiff differential equations and systems giving rise...

The transition paths from plan to market have varied markedly across countries. Central and Eastern European and the Baltic countries, which opted for a fast and profound transformation of their institutions including business climates, rapidly narrowed the productivity gap with advanced...

Common integrated assessment models produce the counterintuitive result that higher risk aversion does not lead to stronger near-term abatement. This paper re-examines this result with a DICE model that is fully coupled with a thermohaline circulation model. It also features Epstein-Zin utility...

In this paper we use the property that certainty equivalence, as implied by a first-order approximation to the solution of stochastic discrete-time models, breaks in its equivalent continuous-time version. We study the extent to which a first-order approximated solution built by perturbation...

We argue that deep learning provides a promising avenue for taming the curse of dimensionality in quantitative economics. We begin by exploring the unique challenges posed by solving dynamic equilibrium models, especially the feedback loop between individual agents' decisions and the aggregate...

In this paper we use the property that certainty equivalence, as implied by a first-order approximation to the solution of stochastic discrete-time models, breaks in its equivalent continuous-time version. We study the extent to which a first-order approximated solution built by perturbation...

Repeated interactions provide a prominent but paradoxical hypothesis for human cooperation in one-shot interactions. Intergroup competitions provide a different hypothesis that is intuitively appealing but heterodox. We show that neither mechanism reliably supports the evolution of cooperation...

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...