In this article, we combine machine learning techniques with statistical moments of the gasoline price distribution. By doing so, we aim to detect and predict cartels in the Brazilian retail market. In addition to the traditional variance screen, we evaluate how the standard deviation,...

In this article, we combine machine learning techniques with statistical moments of the gasoline price distribution. By doing so, we aim to detect and predict cartels in the Brazilian retail market. In addition to the traditional variance screen, we evaluate how the standard deviation,...

Using an agent-based model, we investigate how monetary policy affects banks' risk-taking in terms of the profile of their lending to real sector firms.Our agent-based model considers five types of agents: banks, depositors, the Central Bank, firms, and the clearinghouse. While banks and...

Using an agent-based model, we investigate how monetary policy affects banks' risk-taking in terms of the profile of their lending to real sector firms. Our agent-based model considers five types of agents: banks, depositors, the Central Bank, firms, and the clearinghouse. While banks and...

In this article, we propose a Snowdrift Game with costly punishment in a spatial-structured two-population arrangement. In order to generate the results, we use the Agent Based Simulation (ABS) model. The numerical simulations as well as the dynamics observed in the ABS are analyzed and...

This paper combines evolutionary game theory and input–output analysis to assess firms' strategic location choice. To evaluate the model, firms competed in the automotive sector of Mercosur. To decide where to locate, the following exogenous factors were considered: potential market; local...