Vector error-correction models (VECM) are increasingly being used to capture dynamic relationships between financial variables. Estimation and interpretation of such models can be enhanced if zero restrictions are allowed in the coefficient matrices. Specifically, in tests of indirect causality...

The aim of this paper is to investigate the ability of the Dynamic Variance Gamma model, recently proposed by Bellini and Mercuri (2010), to evaluate option prices on the S&P500 index. We also provide a simple relation between the Dynamic Variance Gamma model and the Vix index. We use this...

There is wide debate over the impact of uncertainty on firm behavior, due to the difficulty both of measuring uncertainty and of identifying causality. This paper takes three steps that attempt to address these challenges. First, we develop an instrumental variables strategy that exploits firms'...

Using equations that arise in quantum mechanics, this paper describes a way to more accurately and efficiently represent non-Gaussian return distributions than the standard method of invoking skewness and kurtosis. Then, it provides a new single intuitive number, defined here as the “crash...

To what extent do mass media outlets influence viewers' trust in scientific evidence and compliance with behavior recommended by scientific experts? Exploiting the US lock-down period of the COVID-19 pandemic in early 2020, we analyze a large longitudinal database that combines daily...

We test for and measure the effects of cable news in the US on regional differences in compliance with recommendations by health experts to practice social distancing during the early stages of the COVID-19 pandemic. We use a quasi-experimental design to estimate the causal effect of Fox News...

The contribution of this paper is twofold. First, we introduce a daily vector autoregression (VAR) model for the US economy that allows discerning between lockdown shocks and a real business cycle shocks. With this methodology at hand, we then evaluate the impact of lockdown measures on economic...

We build a publicly available platform that tracks economic activity at a granular level in real time using anonymized data from private companies. We report daily statistics on consumer spending, business revenues, employment rates, and other key indicators disaggregated by county, industry,...

We test for and measure the effects of cable news in the US on regional differences in compliance with recommendations by health experts to practice social distancing during the early stages of the COVID-19 pandemic. We use a quasi-experimental design to estimate the causal effect of Fox News...