A growing literature estimates the macroeconomic effect of weather using variations in annual country-level averages of temperature and precipitation. However, averages may not reveal the effects of extreme events that occur at a higher time frequency or higher spatial resolution. To address...

Differentiation is arguably the most important business strategy, but optimal investment in differentiation requires understanding the magnitudes of its implications. We consider the extent and dimensions of differentiation in omnichannel grocery by examining the impacts of entry events on...

This research focuses on the analysis of the submarine geomorphology in the Mariana Trench located in west Pacific Ocean. The research question is to identify variations in the geomorphic form and bathymetry in different segments of the trench. Technically, the paper applies Python and R...

The study area is focused on the Philippine Trench, a hadal trench located in the axe of the collision of the Philippine Sea Plate and Sunda Plate, west Pacific Ocean. The research is aimed at the analysis of the trench geomorphology by a correlation between changes in slope steepness and...

We measure the effectiveness of policies in a mixed frequency spatial VAR (MF-SVAR) modeling framework, conditional on the spillover and diffusion effects of the global pandemic and unemployment. Specifically, we examine two aspects of policy effectiveness from a spatio-temporal perspective,...

In this paper we propose a hierarchical shrinkage approach for multi-country VAR models. In implementation, we consider three different scale mixtures of Normals priors — specifically, Horseshoe, Normal- Gamma, and Normal-Gamma-Gamma priors. We provide new theoretical results for the...

In the context of latent factor models that are widely used in economics, a common assumption made is one of factor pervasiveness, which implies that all available predictor or informative variables in a dataset, with the possible exception of a negligible number of them, load significantly on...

We survey the nascent literature on machine learning in the study of financial markets. We highlight the best examples of what this line of research has to offer and recommend promising directions for future research. This survey is designed for both financial economists interested in grasping...

We survey the nascent literature on machine learning in the study of financial markets. We highlight the best examples of what this line of research has to offer and recommend promising directions for future research. This survey is designed for both financial economists interested in grasping...