We aim to evaluate two different econometric screens for identifying anti-competitive behavior in the fuel retail market: (i) The Markov-Switching GARCH (MS-GARCH) Models; (ii) The Local Gaussian Correlation (LGC) approach. Using the gasoline cartel judged and condemned in Brasília as a...

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,...

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...