Various approaches used in Agent-based Computational Economics (ACE) to model endogenously determined interactions between agents are discussed. This concerns models in which agents not only (learn how to) play some (market or other) game, but also (learn to) decide with whom to do that (or not).

We study the relationship between the risk of default and Environmental, Social and Governance (ESG) factors using Supervised Machine Learning (SML) techniques on a cross-section of European listed companies. Our proxy for credit risk is the z-score originally proposed by Altman (1968). We...

This paper analyzes the response of the soybean sown area of Argentina to changes in price incentives and other variables which are relevant for agricultural production. To this effect, VEC models are estimated for some of the main producing provinces and for the country’s total in the period...

Italy makes for a very interesting case study of the impact of social variables on economic performance. Across its provinces, differences in social and cultural attitudes seem associated to large differences in economic development. We analyze the importance of some social variables on...

This paper analyzes the role of uncertainty in a multi-sector housing model with financial frictions. We include time varying uncertainty (i.e. risk shocks) in the technology shocks that affect housing production. The analysis demonstrates that risk shocks to the housing production sector are a...

This paper examines spatial variations in exposure to toxic air pollution from industrial facilities in urban areas of the United States, using geographic microdata from the U.S. Environmental Protection Agency's Risk-Screening Environmental Indicators project. We find that average exposure in...

Existing studies in finance have documented the comovement of stock returns of companies headquartered in the same location. The interpretation is that local investors have a “local bias†due to an information advantage on local companies. This paper argues that localized agglomeration...

The standard approach to modelling consumption/saving problems is to assume that the decisionmaker is solving a dynamic stochastic optimization problem However under realistic descriptions of utility and uncertainty the optimal consumption/saving decision is so difficult that only recently...

This paper introduces a method for solving numerical dynamic stochastic optimization problems that avoids rootfinding operations. The idea is applicable to many microeconomic and macroeconomic problems, including life cycle, buffer-stock, and stochastic growth problems. Software is provided.

Economists working with numerical solutions to the optimal consumption/saving problem under uncertainty have long known that there are quantitatively important interactions between liquidity constraints and precautionary saving behavior This paper provides the analytical basis for those...