Search Results
Working Paper
Real-Time Forecasting and Scenario Analysis using a Large Mixed-Frequency Bayesian VAR
We use a mixed-frequency vector autoregression to obtain intraquarter point and density forecasts as new, high frequency information becomes available. This model, delineated in Ghysels (2016), is specified at the lowest sampling frequency; high frequency observations are treated as different economic series occurring at the low frequency. As this type of data stacking results in a high-dimensional system, we rely on Bayesian shrinkage to mitigate parameter proliferation. We obtain high-frequency updates to forecasts by treating new data releases as conditioning information. The same ...
Journal Article
Should food be excluded from core CPI?
The greater a component?s SNR, the more useful the component should be in forecasting headline CPI.
Journal Article
Factor-based prediction of industry-wide bank stress
This article investigates the use of factor-based methods for predicting industry-wide bank stress. Specifically, using the variables detailed in the Federal Reserve Board of Governors? bank stress scenarios, the authors construct a small collection of distinct factors. We then investigate the predictive content of these factors for net charge-offs and net interest margins at the bank industry level. The authors find that the factors do have significant predictive content, both in and out of sample, for net interest margins but significantly less predictive content for net charge-offs. ...
Core Inflation Revisited: Forecast Accuracy across Horizons
How far out can you forecast inflation? This analysis examines the accuracy of core inflation in predicting headline inflation for periods ranging from three to 24 months in the future.
Price Volatility and Headline Inflation
Movements in “sticky prices”—items that show low price volatility—may indicate that recent swings in U.S. headline inflation are only temporary.
Working Paper
Tests of equal forecast accuracy for overlapping models
This paper examines the asymptotic and finite-sample properties of tests of equal forecast accuracy when the models being compared are overlapping in the sense of Vuong (1989). Two models are overlapping when the true model contains just a subset of variables common to the larger sets of variables included in the competing forecasting models. We consider an out-of-sample version of the two-step testing procedure recommended by Vuong but also show that an exact one-step procedure is sometimes applicable. When the models are overlapping, we provide a simple-to-use fixed regressor wild bootstrap ...
Working Paper
Evaluating long-horizon forecasts
This paper examines the asymptotic and finite-sample properties of tests of equal forecast accuracy and encompassing applied to predictions from nested long-horizon regression models. We first derive the asymptotic distributions of a set of tests of equal forecast accuracy and encompassing, showing that the tests have non-standard distributions that depend on the parameters of the data-generating process. Using a simple parametric bootstrap for inference, we then conduct Monte Carlo simulations of a range of data-generating processes to examine the finite-sample size and power of the tests. ...
Working Paper
Real-time forecast averaging with ALFRED
This paper presents empirical evidence on the efficacy of forecast averaging using the ALFRED real-time database. We consider averages taken over a variety of different bivariate VAR models that are distinguished from one another based upon at least one of the following: which variables are used as predictors, the number of lags, using all available data or data after the Great Moderation, the observation window used to estimate the model parameters and construct averaging weights, and for forecast horizons greater than one, whether or not iterated- or direct-multistep methods are used. A ...
Journal Article
Tracking the U.S. Economy with Nowcasts
The Federal Open Market Committee wants its interest-rate decisions to be data-dependent. But until the past several years, much of the statistical information available?not just to the FOMC, but anyone?had come from reports that looked backward at conditions from the previous month or even quarter. New models developed by economists allow for forecasting of conditions in the current quarter as reports arrive on a day-to-day basis?as in now. Hence, ?nowcasts.?
Journal Article
Uncertainty about when the Fed will raise interest rates
It's hard to make a firm prediction as to when the Fed will raise interest rates.