To better understand the tight post-pandemic labor market in the US, we decompose the decline in aggregate hours worked into the extensive (fewer people working) and the intensive margin changes (workers working fewer hours). Although the pre-existing trend of lower labor force participation...

We use a dynamic panel Tobit model with heteroskedasticity to generate point, set, and density forecasts for a large cross-section of short time series of censored observations. Our fully Bayesian approach allows us to flexibly estimate the cross-sectional distribution of heterogeneous...

Policymakers can take actions to prevent local conflict before it begins, if such violence can be accurately predicted. We examine the two countries with the richest available sub-national data: Colombia and Indonesia. We assemble two decades of fine-grained violence data by type, alongside...

This paper considers the problem of forecasting a collection of short time series using cross sectional information in panel data. We construct point predictors using Tweedie's formula for the posterior mean of heterogeneous coefficients under a correlated random effects distribution. This...

Existing research has shown that job displacement leads to large and persistent earnings losses for men, but evidence for women is scarce. Using administrative data from Germany, we apply an event study design in combination with propensity score matching and a reweighting technique to directly...

We provide a comprehensive analysis of income inequality and income dynamics for Germany over the last two decades. Combining personal income tax and social security data allows us - for the first time - to offer a complete picture of the distribution of annual earnings in Germany. We find that...

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...

We use dynamic panel data models to generate density forecasts for daily Covid-19 infections for a panel of countries/regions. At the core of our model is a specification that assumes that the growth rate of active infections can be represented by autoregressive fluctuations around a downward...