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Can Economists Predict Recessions?

An analysis of 55 years of data from the Survey of Professional Forecasters suggests that quarter-ahead recession forecasts are fairly accurate but still have a great deal of uncertainty.
On the Economy

Working Paper
How Persistent Are Unconventional Monetary Policy Effects?

This paper argues that one cannot precisely estimate the persistence of unconventional monetary policy (UMP) effects, especially with short samples and few observations. To make this point, we illustrate that the most influential model on the topic exhibits structural instability, and sensitivity to specification and outliers that render the conclusions unreliable. Restricted models that respect more plausible asset return predictability are more stable and imply that UMP shocks were persistent. Estimates of the dynamic effects of shocks should respect the limited predictability in asset ...
Working Papers , Paper 2014-04

Discussion Paper
How Easy Is It to Forecast Commodity Prices?

Over the last decade, unprecedented spikes and drops in commodity prices have been a recurrent source of concern to both policymakers and the general public. Given all the recent attention, have economists and analysts made any progress in their ability to predict movements in commodity prices? In this post, we find there is no easy answer. We consider different strategies to forecast near-term commodity price inflation, but find that no particular approach is systematically more accurate and robust. Additionally, the results warn against interpreting current forecasts of commodity prices ...
Liberty Street Economics , Paper 20110627

Working Paper
High-Dimensional Copula-Based Distributions with Mixed Frequency Data

This paper proposes a new model for high-dimensional distributions of asset returns that utilizes mixed frequency data and copulas. The dependence between returns is decomposed into linear and nonlinear components, enabling the use of high frequency data to accurately forecast linear dependence, and a new class of copulas designed to capture nonlinear dependence among the resulting uncorrelated, low frequency, residuals. Estimation of the new class of copulas is conducted using composite likelihood, facilitating applications involving hundreds of variables. In- and out-of-sample tests confirm ...
Finance and Economics Discussion Series , Paper 2015-50

Working Paper
Nowcasting U.S. Headline and Core Inflation

Forecasting future inflation and nowcasting contemporaneous inflation are difficult. We propose a new and parsimonious model for nowcasting headline and core inflation in the U.S. price index for personal consumption expenditures (PCE) and the consumer price index (CPI). The model relies on relatively few variables and is tested using real-time data. The model?s nowcasting accuracy improves as information accumulates over the course of a month or quarter, and it easily outperforms a variety of statistical benchmarks. In head-to-head comparisons, the model?s nowcasts of CPI infl ation ...
Working Papers (Old Series) , Paper 1403

Working Paper
Forecasting Consumption Spending Using Credit Bureau Data

This paper considers whether the inclusion of information contained in consumer credit reports might improve the predictive accuracy of forecasting models for consumption spending. To investigate the usefulness of aggregate consumer credit information in forecasting consumption spending, this paper sets up a baseline forecasting model. Based on this model, a simulated real-time, out-of-sample exercise is conducted to forecast one-quarter ahead consumption spending. The exercise is run again after the addition of credit bureau variables to the model. Finally, a comparison is made to test ...
Working Papers , Paper 20-22

Forecasting in large macroeconomic panels using Bayesian Model Averaging

This paper considers the problem of forecasting in large macroeconomic panels using Bayesian model averaging. Practical methods for implementing Bayesian model averaging with factor models are described. These methods involve algorithms that simulate from the space defined by all possible models. We explain how these simulation algorithms can also be used to select the model with the highest marginal likelihood (or highest value of an information criterion) in an efficient manner. We apply these methods to the problem of forecasting GDP and inflation using quarterly U.S. data on 162 time ...
Staff Reports , Paper 163

Working Paper
FRED-MD: A Monthly Database for Macroeconomic Research

This paper describes a large, monthly frequency, macroeconomic database with the goal of establishing a convenient starting point for empirical analysis that requires "big data." The dataset mimics the coverage of those already used in the literature but has three appealing features. First, it is designed to be updated monthly using the FRED database. Second, it will be publicly accessible, facilitating comparison of related research and replication of empirical work. Third, it will relieve researchers from having to manage data changes and revisions. We show that factors extracted from our ...
Working Papers , Paper 2015-12

How long is the soft-landing runway for the labor market?

A normalized labor market likely entails a more-usual relationship between layoffs and labor market tightness indicators, and sooner or later, a higher unemployment rate.
Dallas Fed Economics

Housing demand and community choice: an empirical analysis

Housing demand reflects the household's simultaneous choice of neighborhood, whether to own or rent the dwelling, and the quantity of housing services demanded. Existing literature emphasizes the final two factors, but overlooks the choice of community. This paper develops an econometric model that incorporates all three components, and then estimates this model using a sample of households in Tampa, Florida. Incorporating community choice increases the price elasticity of demand and reduces the differential between white and comparable nonwhite households. The results are robust to the ...
Staff Reports , Paper 16


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