We estimate the impact of the COVID-19 crisis on business failures among small and medium size enterprises (SMEs) in seventeen countries using a large representative firm-level database. We use a simple model of firm cost-minimization and measure each firm's liquidity shortfall during and after...

This paper assesses the prospects of a 2021 time bomb in SME failures triggered by the generous support policies enacted during the 2020 COVID-19 crisis. Policies implemented in 2020, on their own, do not create a 2021 "time-bomb" for SMEs. Rather, business failures and policy costs remain...

How will countries handle idiosyncratic national macroeconomic shocks under the European single currency? The ways in which European countries now react to internally asymmetric shocks provide a better forecast than do the regional response pattern of the United States. In this paper we compare...

Many households hold little wealth, especially liquid wealth. In precautionary savings models, absent preference heterogeneity, these households should display not only higher marginal propensities to consume (MPCs), but also lower average propensities to consume (APCs) and higher future...

Using original data from two waves of a survey conducted in March and April 2020 in eight OECD countries (N = 21,649), we show that women are more likely to see COVID-19 as a very serious health problem, to agree with restraining public policy measures adopted in response to it, and to comply...

This note lays out the basic Susceptible-Infected-Recovered (SIR) epidemiological model of contagion, with a target audience of economists who want a framework for understanding the effects of social distancing and containment policies on the evolution of contagion and interactions with the...

Financial crises cause economic, social and political havoc. Macroprudential policies are gaining traction but are still severely under-researched compared to monetary policy and fiscal policy. We use the general framework of sequential predictions also called online machine learning to forecast...