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Keywords:real-time data OR Real-time data OR Real-Time Data 

Working Paper
Growth-at-Risk is Investment-at-Risk

We investigate the role financial conditions play in the composition of U.S. growth-at-risk. We document that, by a wide margin, growth-at-risk is investment-at-risk. That is, if financial conditions indicate U.S. real GDP growth will be in the lower tail of its conditional distribution, we know that the main contributor is a decline in investment. Consumption contributes under extreme financial stress. Government spending and net exports do not play a role. We show that leverage plays a key role in determining both consumption- and investment-at-risk, which provides support to the financial ...
Working Papers , Paper 2023-020

Working Paper
Which Output Gap Estimates Are Stable in Real Time and Why?

Output gaps that are estimated in real time can differ substantially from those estimated after the fact. We aim to understand the real-time instability of output gap estimates by comparing a suite of reduced-form models. We propose a new statistical decomposition and find that including a Okun’s law relationship improves real-time stability by alleviating the end-point problem. Models that include the unemployment rate also produce output gaps with relevant economic content. However, we find that no model of the output gap is clearly superior to the others along each metric we consider.
Finance and Economics Discussion Series , Paper 2020-102

Working Paper
The continuing power of the yield spread in forecasting recessions

In this paper, we replicate the main results of Rudebusch and Williams (2009), who show that the use of the yield spread in a probit model can predict recessions better than the Survey of Professional Forecasters. We investigate the robustness of their results in several ways: extending the sample to include the 2007-09 recession, changing the starting date of the sample, changing the ending date of the sample, using rolling windows of data instead of just an expanding sample, and using alternative measures of the actual" value of real output. Our results show that the Rudebusch-Williams ...
Working Papers , Paper 14-5

Working Paper
Time-varying Uncertainty of the Federal Reserve’s Output Gap Estimate

A factor stochastic volatility model estimates the common component to estimates of the output gap produced by the staff of the Federal Reserve, its time-varying volatility, and time-varying, horizon-specific forecast uncertainty. Output gap estimates are very uncertain, even well after the fact, especially at business cycle turning points. However, the common component of the output gap estimates is clearly procyclical, and innovations to the common factor produce persistent positive effects on economic activity. Output gaps estimated by the Congressional Budget Office have very similar ...
Finance and Economics Discussion Series , Paper 2020-012r1

Working Paper
Forecasting Economic Activity with Mixed Frequency Bayesian VARs

Mixed frequency Bayesian vector autoregressions (MF-BVARs) allow forecasters to incorporate a large number of mixed frequency indicators into forecasts of economic activity. This paper evaluates the forecast performance of MF-BVARs relative to surveys of professional forecasters and investigates the influence of certain specification choices on this performance. We leverage a novel real-time dataset to conduct an out-of-sample forecasting exercise for U.S. real gross domestic product (GDP). MF-BVARs are shown to provide an attractive alternative to surveys of professional forecasters for ...
Working Paper Series , Paper WP-2016-5

Working Paper
Measurement Error in Macroeconomic Data and Economics Research: Data Revisions, Gross Domestic Product, and Gross Domestic Income

We analyze the effect of measurement error in macroeconomic data on economics research using two features of the estimates of latent US output produced by the Bureau of Economic Analysis (BEA). First, we use the fact that the BEA publishes two theoretically identical estimates of latent US output that only differ due to measurement error: the more well-known gross domestic product (GDP), which the BEA constructs using expenditure data, and gross domestic income (GDI), which the BEA constructs using income data. Second, we use BEA revisions to previously published releases of GDP and GDI. ...
Finance and Economics Discussion Series , Paper 2015-102

Working Paper
Incorporating Short Data into Large Mixed-Frequency VARs for Regional Nowcasting

Interest in regional economic issues coupled with advances in administrative data is driving the creation of new regional economic data. Many of these data series could be useful for nowcasting regional economic activity, but they suffer from a short (albeit constantly expanding) time series which makes incorporating them into nowcasting models problematic. Regional nowcasting is already challenging because the release delay on regional data tends to be greater than that at the national level, and "short" data imply a "ragged edge" at both the beginning and the end of regional data sets, ...
Working Papers , Paper 23-09

Working Paper
Growth-at-Risk is Investment-at-Risk

We investigate the role financial conditions play in the composition of U.S. growth-at-risk. We document that, by a wide margin, growth-at-risk is investment-at-risk. That is, if financial conditions indicate U.S. real GDP growth will be in the lower tail of its conditional distribution, we know that the main contributor is a decline in investment. Consumption contributes under extreme financial stress. Government spending and net exports do not play a role.
Working Papers , Paper 2023-020

Working Paper
Forecasting with small macroeconomic VARs in the presence of instabilities

Small-scale VARs are widely used in macroeconomics for forecasting U.S. output, prices, and interest rates. However, recent work suggests these models may exhibit instabilities. As such, a variety of estimation or forecasting methods might be used to improve their forecast accuracy. These include using different observation windows for estimation, intercept correction, time-varying parameters, break dating, Bayesian shrinkage, model averaging, etc. This paper compares the effectiveness of such methods in real time forecasting. We use forecasts from univariate time series models, the Survey of ...
Finance and Economics Discussion Series , Paper 2007-41

Working Paper
On the Real-Time Predictive Content of Financial Conditions Indices for Growth

We provide evidence on the real-time predictive content of the National Financial Conditions Index (NFCI), for conditional quantiles of U.S. real GDP growth. Our work is distinct from the literature in two specific ways. First, we construct (unofficial) real-time vintages of the NFCI. This allows us to conduct out-of-sample analysis without introducing the kind of look-ahead biases that are naturally introduced when using a single current vintage. We then develop methods for conducting asymptotic inference on tests of equal tick loss between nested quantile regression models when the data are ...
Working Papers , Paper 2022-003

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