We analyze link between mortgage-related regulatory penalties levied on banks and the level of systemic risk in the U.S. banking industry. We employ a frequency decomposition of volatility spillovers (connectedness) to assess system-wide risk transmission with short-, medium-, and long-term...

Several developing economies witnessed a large number of systemic financial and currency crises since the 1980s which resulted in severe economic, social, and political problems. The devastating impact of the 1982 and 1994-95 Mexican crises, the 1997-98 Asian financial crisis, the 1998 Russian...

This paper proposes a macro-prudential financial soundness analysis that can be used by most developing and transformation countries with or without crisis experience as well as by developed countries with limited data. The objective is to detect economic and financial sector vulnerability,...

This paper analyzes the effect of the removal of government guarantees on bank risk taking. We exploit the removal of guarantees for German Landesbanken which results in lower credit ratings, higher funding costs, and a loss in franchise value. This removal was announced in 2001, but...

Comparative quantitative research into the causes, responses to, and effects of banking crisis uses two series of crisis data: Reinhart and Rogoff (2009, 2010) and Laeven and Valencia (2013, and their predecessors). While these data sets provide broad coverage, the measures they code have...

We assess the robustness of previous findings on the determinants of terrorism. Using extreme bound analysis, the three most comprehensive terrorism datasets, and focusing on the three most commonly analyzed aspects of terrorist activity, i.e., location, victim, and perpetrator, we re-assess the...

We introduce archetypal analysis as a tool to describe and categorize scientists. This approach identifies typical characteristics of extreme ('archetypal') values in a multivariate data set. These positive or negative contextual attributes can be allocated to each scientists under...

We analyze a coordination game with information-constrained players. The players' actions are based on a noisy compressed representation of the game's payoffs in a particular case, where the compressed representation is a latent state learned by a variational autoencoder (VAE). Our generalized...

We postulate a nonlinear DSGE model with a financial sector and heterogeneous households. In our model, the interaction between the supply of bonds by the financial sector and the precautionary demand for bonds by households produces significant endogenous aggregate risk. This risk induces an...

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,...