We study the dynamic impact of Covid-19, economic mobility, and containment policy shocks. We use Bayesian panel structural vector autoregressions with daily data for 44 countries, identified through sign and zero restrictions. Incidence and mobility shocks raise cases and deaths significantly...

I show that the irreversibility of dying coupled with gradual information acquisition over time on the likely arrival and eventual effectiveness of vaccines confers a real option value to lockdown strategies that delay the incidence of a pandemic.The case for lockdown strategies becomes stronger...

We develop a new targeted maximum likelihood estimation method that provides improved forecasting for misspecified linear autoregressive models. The method weighs data points in the observed sample and is useful in the presence of data generating processes featuring structural breaks, complex...

This paper develops a discrete-time epidemiological model for the spread of crises across sectors in the United States for the period 1952-2015. It is the first to use an epidemiological approach with macroeconomic (Flow of Funds) data. An extension of the usual one-period Markov model to a...

A sizeable proportion of enterprises, especially SMEs, in receipt of financial assistance from the government, will fail to repay. In this paper we asked whether, and to what extent, it may be beneficial to apply a screening mechanism to deter those mostly likely to fail to repay from seeking...

We propose the dynamic network effect (DNE) model for the study of high-dimensional multivariate time series data. Cross-sectional dependencies between units are captured via one or multiple observed networks and a low-dimensional vector of latent stochastic network effects. The...