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Keywords:forecasting 

Working Paper
Variable Selection and Forecasting in High Dimensional Linear Regressions with Structural Breaks

This paper is concerned with the problem of variable selection and forecasting in the presence of parameter instability. There are a number of approaches proposed for forecasting in the presence of breaks, including the use of rolling windows and exponential down-weighting. However, these studies start with a given model specification and do not consider the problem of variable selection, which is complicated by time variations in the effects of signal variables. In this study we investigate whether or not we should use weighted observations at the variable selection stage in the presence of ...
Globalization Institute Working Papers , Paper 394

Working Paper
Variable Selection and Forecasting in High Dimensional Linear Regressions with Structural Breaks

This paper is concerned with the problem of variable selection and forecasting in the presence of parameter instability. There are a number of approaches proposed for forecasting in the presence of breaks, including the use of rolling windows or exponential down-weighting. However, these studies start with a given model specification and do not consider the problem of variable selection. It is clear that, in the absence of breaks, researchers should weigh the observations equally at both the variable selection and forecasting stages. In this study, we investigate whether or not we should use ...
Globalization Institute Working Papers , Paper 394

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

Journal Article
Flexible Average Inflation Targeting and Inflation Expectations: A Look at the Reaction by Professional Forecasters

This Commentary examines the response of longer-run inflation expectations to the FOMC’s August 2020 announced switch to a flexible average inflation-targeting (FAIT) regime. The data indicate an upward shift in the lower end (below 2 percent) of the distribution of inflation expectations and a stronger anchoring of expectations around the 2 percent inflation objective following the announcement, evidence that is consistent with intended effects of the change in the monetary policy framework. To provide context, we also include a retrospective assessment of the response of inflation ...
Economic Commentary , Volume 2021 , Issue 09 , Pages 7

Working Paper
Forecasting GDP Growth with NIPA Aggregates

Beyond GDP, which is measured using expenditure data, the U.S. national income and product accounts (NIPAs) provide an income-based measure of the economy (gross domestic income, or GDI), a measure that averages GDP and GDI, and various aggregates that include combinations of GDP components. This paper compiles real-time data on a variety of NIPA aggregates and uses these in simple time-series models to construct out-of-sample forecasts for GDP growth. Over short forecast horizons, NIPA aggregates?particularly consumption and GDP less inventories and trade?together with these simple ...
Working Papers (Old Series) , Paper 1708

Working Paper
Capturing Macroeconomic Tail Risks with Bayesian Vector Autoregressions

A rapidly growing body of research has examined tail risks in macroeconomic outcomes. Most of this work has focused on the risks of significant declines in GDP, and it has relied on quantile regression methods to estimate tail risks. Although much of this work discusses asymmetries in conditional predictive distributions, the analysis often focuses on evidence of downside risk varying more than upside risk. We note that this pattern in risk estimates over time could obtain with conditional distributions that are symmetric but subject to simultaneous shifts in conditional means (down) and ...
Working Papers , Paper 20-02R

Working Paper
Does Realized Volatility Help Bond Yield Density Prediction?

We suggest using "realized volatility" as a volatility proxy to aid in model-based multivariate bond yield density forecasting. To do so, we develop a general estimation approach to incorporate volatility proxy information into dynamic factor models with stochastic volatility. The resulting model parameter estimates are highly efficient, which one hopes would translate into superior predictive performance. We explore this conjecture in the context of density prediction of U.S. bond yields by incorporating realized volatility into a dynamic Nelson-Siegel (DNS) model with stochastic ...
Finance and Economics Discussion Series , Paper 2015-115

Working Paper
FISCAL SURPRISES AT THE FOMC

This paper provides a detailed examination of a new set of fiscal forecasts for the U.S. assembled by Croushore and van Norden (2017) from FOMC briefing books. The data are of particular interest because (1) they afford a look at fiscal forecasts over six complete business cycles and several fiscal policy regimes, covering both peacetime and several wars, (2) the forecasts were precisely those presented to monetary policymakers, (3) they include frequently updated estimates of both actual and cyclically adjusted deficits, (4) unlike most other U.S. fiscal forecasts, they were neither partisan ...
Working Papers , Paper 17-13

Report
Priors for the long run

We propose a class of prior distributions that discipline the long-run predictions of vector autoregressions (VARs). These priors can be naturally elicited using economic theory, which provides guidance on the joint dynamics of macroeconomic time series in the long run. Our priors for the long run are conjugate, and can thus be easily implemented using dummy observations and combined with other popular priors. In VARs with standard macroeconomic variables, a prior based on the long-run predictions of a wide class of theoretical models yields substantial improvements in the forecasting ...
Staff Reports , Paper 832

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

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Clark, Todd E. 7 items

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