We document that the US dollar exchange rate drives global trade prices and volumes.
Using a newly constructed data set of bilateral price and volume indices for more than 2,500 …

We selectively review recent advancements in research on predictive models of earnings
and returns. We discuss why applying statistical, econometric, and machine learning …

We use a dynamic panel data model to generate density forecasts for daily active Covid-19
infections for a panel of countries/regions. Our specification that assumes the growth rate of …

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 …

We show empirically that the variation across country pairs in exchange rate pass-through
and trade elasticity is meaningfully explained by the dollar's dominance as invoicing …

This paper provides a new multi-dimensional clustering approach for unobserved
heterogeneity in panel data models. Each unit is associated with multiple clusters. For …

Average partial effects (APEs) are generally not point-identified in binary response panel
models with unrestricted unobserved heterogeneity. We show their point-identification under …

We use a dynamic panel Tobit model with heteroskedasticity to generate forecasts for a
large cross‐section of short time series of censored observations. Our fully Bayesian …

We use a decision-theoretic framework to study the problem of forecasting discrete
outcomes when the forecaster is unable to discriminate among a set of plausible forecast …

This paper develops an efficient Stein-like shrinkage estimator for estimating slope
parameters under structural breaks in seemingly unrelated regression models, which is then …