Search Results
Working Paper
Combining forecasts from nested models
Motivated by the common finding that linear autoregressive models forecast better than models that incorporate additional information, this paper presents analytical, Monte Carlo, and empirical evidence on the effectiveness of combining forecasts from nested models. In our analytics, the unrestricted model is true, but as the sample size grows, the DGP converges to the restricted model. This approach captures the practical reality that the predictive content of variables of interest is often low. We derive MSE-minimizing weights for combining the restricted and unrestricted forecasts. In the ...
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 ...
What Do Components of Key Inflation Measures Say about Future Inflation?
A new analysis suggests that the food expenditures category of the consumer price index could be a useful signal of future headline inflation.
Working Paper
Advances in forecast evaluation
This paper surveys recent developments in the evaluation of point forecasts. Taking West?s (2006) survey as a starting point, we briefly cover the state of the literature as of the time of West?s writing. We then focus on recent developments, including advancements in the evaluation of forecasts at the population level (based on true, unknown model coefficients), the evaluation of forecasts in the finite sample (based on estimated model coefficients), and the evaluation of conditional versus unconditional forecasts. We present original results in a few subject areas: the optimization of power ...
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
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. ...
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.?