Machine learning (ML) techniques are used to construct a financial conditions index (FCI). The components of the ML-FCI are selected based on their ability to predict the unemployment rate one-year ahead. Three lessons for macroeconomics and variable selection/dimension reduction with large...

We examine the role of U.S. monetary policy in global financial stability by using a cross-country database spanning the period from 1870-2010 across 69 countries. U.S. monetary policy tightening increases the probability of banking crises for those countries with direct linkages to the U.S.,...

The recent financial crisis and ensuing recession appear to have put the productive capacity of the economy on a lower and shallower trajectory than the one that seemed to be in place prior to 2007. Using a version of an unobserved components model introduced by Fleischman and Roberts (2011), we...

This paper develops a new-Keynesian model with nominal depreciation allowances to consider the effects of temporary tax-based investment incentives on capital spending and real activity. In particular, we investigate the effects of a temporary expensing allowance on investment in partial and...

No, not really, since spectral estimators suffer from small sample and misspecification biases just as VARs do. Spectral estimators are no panacea for implementing long-run restrictions. In addition, when combining VAR coefficients with non-parametric estimates of the spectral density, care...

I show that the probability that the Board of Governors of the Federal Reserve System staff's forecasts (the "Greenbooks'") overpredicted quarterly real gross domestic product (GDP) growth depends on both the forecast horizon and also whether the forecasted quarter was above or below trend real...

Since the onset of the Great Recession, the U.S. economy has experienced low real GDP growth and low real interest rates, including for long maturities. We show that these developments were largely predictable by calibrating an overlapping-generation model with a rich demographic structure to...

Factor models are widely used in summarizing large datasets with few underlying latent factors and in building time series forecasting models for economic variables. In these models, the reduction of the predictors and the modeling and forecasting of the response y are carried out in two...

We apply textual analysis tools to measure the degree of optimism versus pessimism of the text that describes Federal Reserve Board forecasts published in the Greenbook. The resulting measure of Greenbook text sentiment, “Tonality,� is found to be strongly correlated, in the...

We apply textual analysis tools to the narratives that accompany Federal Reserve Board economic forecasts to measure the degree of optimism versus pessimism expressed in those narratives. Text sentiment is strongly correlated with the accompanying economic point forecasts, positively for GDP...