This paper investigates the predictive power of the shadow rate for the inflation rate in countries with a zero lower bound (the US, the UK and Canada) and in those with negative rates (Japan, the Euro Area and Switzerland). Using shadow rates obtained from two different models (the Wu-Xia...

We derive exact conditions relating the distributions of firm productivity, sales, output, and markups to the form of demand in monopolistic competition. Applications include a new “CREMR” demand function (Constant Revenue Elasticity of Marginal Revenue): it is necessary and sufficient for...

Estimates of the trade elasticity based on actual trade policy changes are scarce, and the few that exist are all over the place. This paper offers a setting where an exogenous increase in a border tax can be used to estimate the trade elasticity. It shows theoretically and empirically that if...

This paper analyzes the stability and distribution of ambiguity attitudes using a broad population sample. Using high-powered incentives, we collected six waves of data on ambiguity attitudes about financial markets—our main application—and climate change. Estimating a structural stochastic...

This paper introduces a new test of the predictive performance and market timing for categorical forecasts based on contingency tables when the user has non-categorical loss functions. For example, a user might be interested in the return of an underlying variable instead of just the direction....

Using a novel dataset that contains qualitative firm survey data on sales forecasts as well as balance-sheet data on realized sales, we document that only major forecast errors are predictable and display autocorrelation. This result is a particular violation of the Full Information Rational...

This paper provides a detailed assessment of the real-time forecast accuracy of a wide range of vector autoregressive models (VAR) that allow for both structural change and indicators sampled at different frequencies. We extend the literature by evaluating a mixed-frequency time-varying...

Climate change is predicted to substantially alter forest growth. Optimally, forest owners should take these future changes into account when making rotation decisions today. However, the fundamental uncertainty surrounding climate change makes predicting these shifts hard. Hence, this paper...

We propose two novel methods to "bring ABMs to the data". First, we put forward a new Bayesian procedure to estimate the numerical values of ABM parameters that takes into account the time structure of simulated and observed time series. Second, we propose a method to forecast aggregate time...

We have argued that from the standpoint of a policy maker who has access to a number of expert forecasts, the uncertainty of a combined forecast should be interpreted as that of a typical forecaster randomly drawn from the pool. With a standard factor decomposition of a panel of forecasts, we...