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 dynamic programming method when the one-stage deviation principle in the sense of mechanism design literature doesn’t hold. The commonly used dynamic programming method is valid only if the one-stage deviation principle in the sense of mechanism design literature is...

Robust decision making implies welfare costs or robustness premia when the approximating model is the true data generating process. To examine the importance of these premia at the aggregate level we employ a simple two-sector dynamic general equilibrium model with human capital and introduce an...

This paper extends the transformed maximum likelihood approach for estimation of dynamic panel data models by Hsiao, Pesaran, and Tahmiscioglu (2002) to the case where the errors are cross-sectionally heteroskedastic. This extension is not trivial due to the incidental parameters problem that...

Quarterly GDP figures usually are published with a delay of some weeks. A common way to generate GDP series of higher frequency, i.e. to nowcast GDP, is to use available indicators to calculate a single index by means of a common factor derived from a dynamic factor model (DFM). This paper deals...

To synthesize the literature on determinants of the shadow economy, this paper uses three cross-national shadow economy measures and employs numerous determinants over hundreds of model combinations to identify robust determinants of the shadow economy and address modeling uncertainty. We find...

In this paper, we study a two-country dynamic setup with environmental externalities and potential model misspecification in relation to this public good. Under model uncertainty, robust policies help to correct the inefficiencies associated with free riding on public good provision, implying...

We introduce a novel approach to solving dynamic programming problems, such as those in many economic models, on a quantum annealer, a specialized device that performs combinatorial optimization. Quantum annealers attempt to solve an NP-hard problem by starting in a quantum superposition of all...

This paper explores cost-effective low-carbon R&D and capital investment portfolios for the electricity generation sector through 2060. We present a novel method for long-term planning by combining an economic model of endogenous non-linear technical change and a generation capacity planning...