Unemployment is notoriously difficult to predict. In previous studies, once country fixed effects are added to panel estimates, few variables predict changes in unemployment rates. Using panel data for 29 European countries over 439 months between 1985 and 2021 in an unbalanced country*month...

We provide a framework for evaluating and improving multivariate density forecasts. Among other things, the multivariate framework lets us evaluate the adequacy of density forecasts involving cross-variable interactions, such as time-varying conditional correlations. We also provide conditions...

Using research designs patterned after randomized experiments, many recent economic studies examine outcome measures for treatment groups and comparison groups that are not randomly assigned. By using variation in explanatory variables generated by changes in state laws, government draft...

This paper presents and implements statistical tests of stock market forecastability and volatility that are immune from the severe statistical problems of earlier tests. Although the null hypothesis of strict market efficiency is rejected, the evidence against the hypothesis is not...

We argue that comprehensive out-of-sample (OOS) evaluation using statistical decision theory (SDT) should replace the current practice of K-fold and Common Task Framework validation in machine learning (ML) research. SDT provides a formal framework for performing comprehensive OOS evaluation...

In this paper we focus on alternative procedures for calculating and interpreting quality-adjusted price indexes for microcomputers, based on a variety of estimated hedonic price equations. Our data set comprises an unbalanced panel for 1265 model observations from 1982 to 1988, and includes...

Social media data presents challenges for forecasters since one must convert text into data and deal with issues related to these measures being collected at different frequencies and volumes than traditional financial data. In this paper, we use a deep learning algorithm to measure sentiment...

We explore the in- and out- of sample robustness of tests for consumer choice inconsistencies based on parameter restrictions in parametric models, with a focus on tests proposed by Ketcham, Kuminoff and Powers (2015). We start by arguing that non-parametric alternatives are inherently...

Consumer choices are constrained in many markets due to either supply-side rationing or information frictions. Examples include matching markets for schools and colleges; entry-level labor markets; limited brand awareness and inattention in consumer markets; and selective admissions to...

We investigate the relationship between (a) official information on COVID-19 infection and death case counts; (b) beliefs about such case counts, at present and in the future; (c) beliefs about average infection chance--in principle, directly calculable from (b); and (d) self-reported...