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Working Paper
Time-varying Uncertainty of the Federal Reserve’s Output Gap Estimate
Berge, Travis J. (2020-02-03)
What is the output gap and when do we know it? A factor stochastic volatility model estimates the common component to forecasts of the output gap produced by the staff of the Federal Reserve, its time-varying volatility, and time-varying, horizon-specific forecast uncertainty. The common factor to these forecasts is highly procyclical, and unexpected increases to the common factor are associated with persistent responses in other macroeconomic variables. However, output gap estimates are very uncertain, even well after the fact. Output gap uncertainty increases around business cycle turning ...
Finance and Economics Discussion Series , Paper 2020-012

Working Paper
Machine Learning, the Treasury Yield Curve and Recession Forecasting
Puglia, Michael; Tucker, Adam (2020-05-20)
We use machine learning methods to examine the power of Treasury term spreads and other financial market and macroeconomic variables to forecast US recessions, vis-à-vis probit regression. In particular we propose a novel strategy for conducting cross-validation on classifiers trained with macro/financial panel data of low frequency and compare the results to those obtained from standard k-folds cross-validation. Consistent with the existing literature we find that, in the time series setting, forecast accuracy estimates derived from k-folds are biased optimistically, and cross-validation ...
Finance and Economics Discussion Series , Paper 2020-038

Working Paper
Reconsidering the Fed’s Forecasting Advantage
Owyang, Michael T.; McCracken, Michael W.; Guisinger, Amy Y. (2022-01-02)
Previous studies show the Fed has a forecast advantage over the private sector, either because it devotes more resources to forecasting or because it has an informational advantage in knowing the path of future monetary policy. We evaluate the Fed’s forecast advantage to determine how much of it results from the Fed’s knowledge of the conditioning path. We develop two tests—an instrumental variable encompassing test and a path-dependent encompassing test—to equalize the Fed’s information set with the private sector’s. We find that, generally, the Fed does not encompass the private ...
Working Papers , Paper 2022-001

Working Paper
Tests of Conditional Predictive Ability: Existence, Size, and Power
McCracken, Michael W. (2020-12-18)
We investigate a test of conditional predictive ability described in Giacomini and White (2006; Econometrica). Our main goal is simply to demonstrate existence of the null hypothesis and, in doing so, clarify just how unlikely it is for this hypothesis to hold. We do so using a simple example of point forecasting under quadratic loss. We then provide simulation evidence on the size and power of the test. While the test can be accurately sized we find that power is typically low.
Working Papers , Paper 2020-050

Working Paper
The Accuracy of Forecasts Prepared for the Federal Open Market Committee
Hanson, Tyler J.; Chang, Andrew C. (2015-07-09)
We analyze forecasts of consumption, nonresidential investment, residential investment, government spending, exports, imports, inventories, gross domestic product, inflation, and unemployment prepared by the staff of the Board of Governors of the Federal Reserve System for meetings of the Federal Open Market Committee from 1997 to 2008, called the Greenbooks. We compare the root mean squared error, mean absolute error, and the proportion of directional errors of Greenbook forecasts of these macroeconomic indicators to the errors from three forecasting benchmarks: a random walk, a first-order ...
Finance and Economics Discussion Series , Paper 2015-62

Working Paper
Back to the Present: Learning about the Euro Area through a Now-casting Model
Modugno, Michele; Cascaldi-Garcia, Danilo; Ferreira, Thiago Revil T.; Giannone, Domenico (2021-03-30)
We build a model for simultaneously now-casting economic conditions in the euro area and its three largest member countries--Germany, France, and Italy. The model formalizes how market participants and policymakers monitor the euro area by incorporating all market moving indicators in real time. We find that area wide and country-specific data provide informative signals to now-cast the economic conditions in the euro area and member countries. The model provides accurate predictions of economic conditions in real time over a period that covers the past three recessions.
International Finance Discussion Papers , Paper 1313

Working Paper
Evaluating Conditional Forecasts from Vector Autoregressions
McCracken, Michael W.; Clark, Todd E. (2014-10-02)
Many forecasts are conditional in nature. For example, a number of central banks routinely report forecasts conditional on particular paths of policy instruments. Even though conditional forecasting is common, there has been little work on methods for evaluating conditional forecasts. This paper provides analytical,Monte Carlo, and empirical evidence on tests of predictive ability for conditional forecasts from estimated models. In the empirical analysis, we consider forecasts of growth, unemployment, and inflation from a VAR, based on conditions on the short-term interest rate. Throughout ...
Working Papers (Old Series) , Paper 1413

Working Paper
Constructing Fan Charts from the Ragged Edge of SPF Forecasts
Clark, Todd E.; Ganics, Gergely; Mertens, Elmar (2022-11-23)
We develop a model that permits the estimation of a term structure of both expectations and forecast uncertainty for application to professional forecasts such as the Survey of Professional Forecasters (SPF). Our approach exactly replicates a given data set of predictions from the SPF (or a similar forecast source) without measurement error. Our model captures fixed horizon and fixed-event forecasts, and can accommodate changes in the maximal forecast horizon available from the SPF. The model casts a decomposition of multi-period forecast errors into a sequence of forecast updates that may be ...
Working Papers , Paper 22-36

Working Paper
Large Vector Autoregressions with Stochastic Volatility and Flexible Priors
Clark, Todd E.; Carriero, Andrea; Marcellino, Massimiliano (2016-06-30)
Recent research has shown that a reliable vector autoregressive model (VAR) for forecasting and structural analysis of macroeconomic data requires a large set of variables and modeling time variation in their volatilities. Yet, there are no papers jointly allowing for stochastic volatilities and large datasets, due to computational complexity. Moreover, homoskedastic VAR models for large datasets so far restrict substantially the allowed prior distributions on the parameters. In this paper we propose a new Bayesian estimation procedure for (possibly very large) VARs featuring time varying ...
Working Papers (Old Series) , Paper 1617

Working Paper
Censored Density Forecasts: Production and Evaluation
Weale, Martin; Mitchell, James (2022-08-16)
This paper develops methods for the production and evaluation of censored density forecasts. The focus is on censored density forecasts that quantify forecast risks in a middle region of the density covering a specified probability, and ignore the magnitude but not the frequency of outlying observations. We propose a fixed-point algorithm that fits a potentially skewed and fat-tailed density to the inner observations, acknowledging that the outlying observations may be drawn from a different but unknown distribution. We also introduce a new test for calibration of censored density forecasts. ...
Working Papers , Paper 21-12R

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