Search Results

(refine search)

SORT BY: PREVIOUS / NEXT

All:
Title:
Author:
Abstract:
Keywords:

+ Add Search Parameter

Working Paper
Assessing the Role of Global Demand and Supply Shocks in the Recent US Inflation Experience Using a Cross-Country Panel Dataset of Professional Forecasts
Higgins, Patrick C. (2025-10-06)
Although there have been a range of studies investigating the role and importance of global supply and demand shocks in US inflation developments during and since the pandemic, this study uses a heretofore unused dataset for this purpose: a quarterly panel of professional forecasts from Consensus Economics. We use real-time data with daily vintage snapshots since 2005 from the Federal Reserve Board of Governors FAME database to disentangle forecast errors from revisions and to exploit the monthly frequency and partial availability of CPI inflation and industrial production. Our measures of ...
FRB Atlanta Working Paper , Paper 2025-10

Working Paper
Risk, Return, and Volatility Feedback: A Bayesian Nonparametric Analysis
Maheu, John M.; Jensen, Mark J. (2014-06-01)
The relationship between risk and return is one of the most studied topics in finance. The majority of the literature is based on a linear, parametric relationship between expected returns and conditional volatility. This paper models the contemporaneous relationship between market excess returns and contemporaneous log-realized variances nonparametrically with an infinite mixture representation of their joint distribution. The conditional distribution of excess returns given log-realized variance will also have an infinite mixture representation but with probabilities and arguments depending ...
FRB Atlanta Working Paper , Paper 2014-6

Working Paper
Forecasts of inflation and interest rates in no-arbitrage affine models
Gospodinov, Nikolay; Wei, Bin (2016-02-01)
In this paper, we examine the forecasting ability of an affine term structure framework that jointly models the markets for Treasuries, inflation-protected securities, inflation derivatives, and oil future prices based on no-arbitrage restrictions across these markets. On the methodological side, we propose a novel way of incorporating information from these markets into an affine model. On the empirical side, two main findings emerge from our analysis. First, incorporating information from inflation options can often produce more accurate inflation forecasts than those based on the Survey of ...
FRB Atlanta Working Paper , Paper 2016-3

Working Paper
Narrative Sign Restrictions for SVARs
Antolin-Diaz, Juan; Rubio-Ramirez, Juan F. (2016-12-01)
We identify structural vector autoregressions using narrative sign restrictions. Narrative sign restrictions constrain the structural shocks and/or the historical decomposition around key historical events, ensuring that they agree with the established narrative account of these episodes. Using models of the oil market and monetary policy, we show that narrative sign restrictions tend to be highly informative. Even a single narrative sign restriction may dramatically sharpen and even change the inference of SVARs originally identified via traditional sign restrictions. Our approach combines ...
FRB Atlanta Working Paper , Paper 2016-16

Working Paper
Inference in Bayesian Proxy-SVARs
Rubio-Ramirez, Juan F.; Waggoner, Daniel F.; Arias, Jonas E. (2018-12-01)
Motivated by the increasing use of external instruments to identify structural vector autoregressions (SVARs), we develop algorithms for exact finite sample inference in this class of time series models, commonly known as proxy-SVARs. Our algorithms make independent draws from the normal-generalized-normal family of conjugate posterior distributions over the structural parameterization of a proxy-SVAR. Importantly, our techniques can handle the case of set identification and hence they can be used to relax the additional exclusion restrictions unrelated to the external instruments often ...
FRB Atlanta Working Paper , Paper 2018-16

Working Paper
The Response of Stock Market Volatility to Futures-Based Measures of Monetary Policy Shocks
Gospodinov, Nikolay; Jamali, Ibrahim (2014-08-01)
In this paper, we investigate the dynamic response of stock market volatility to changes in monetary policy. Using a vector autoregressive model, our findings reveal a significant and asymmetric response of stock returns and volatility to monetary policy shocks. Although the increase in the volatility risk premium, futures-trading volume, and leverage appear to contribute to a short-term increase in volatility, the longer-term dynamics of volatility are dominated by monetary policy's effect on fundamentals. The estimation results from a bivariate VAR-GARCH model suggest that the Fed does not ...
FRB Atlanta Working Paper , Paper 2014-14

Working Paper
Inference Based on SVARs Identified with Sign and Zero Restrictions: Theory and Applications
Rubio-Ramirez, Juan F.; Waggoner, Daniel F.; Arias, Jonas E. (2014-02-01)
In this paper, we develop algorithms to independently draw from a family of conjugate posterior distributions over the structural parameterization when sign and zero restrictions are used to identify SVARs. We call this family of conjugate posterior distributions normal-generalized-normal. Our algorithms draw from a conjugate uniform-normal-inverse-Wishart posterior over the orthogonal reduced-form parameterization and transform the draws into the structural parameterization; this transformation induces a normal-generalized-normal posterior distribution over the structural parameterization. ...
FRB Atlanta Working Paper , Paper 2014-1

Working Paper
A moment-matching method for approximating vector autoregressive processes by finite-state Markov chains
Gospodinov, Nikolay; Lkhagvasuren, Damba (2013-09-01)
This paper proposes a moment-matching method for approximating vector autoregressions by finite-state Markov chains. The Markov chain is constructed by targeting the conditional moments of the underlying continuous process. The proposed method is more robust to the number of discrete values and tends to outperform the existing methods for approximating multivariate processes over a wide range of the parameter space, especially for highly persistent vector autoregressions with roots near the unit circle.
FRB Atlanta Working Paper , Paper 2013-05

Working Paper
The Dynamic Striated Metropolis-Hastings Sampler for High-Dimensional Models
Waggoner, Daniel F.; Wu, Hongwei; Zha, Tao (2014-11-01)
Having efficient and accurate samplers for simulating the posterior distribution is crucial for Bayesian analysis. We develop a generic posterior simulator called the "dynamic striated Metropolis-Hastings (DSMH)" sampler. Grounded in the Metropolis-Hastings algorithm, it draws its strengths from both the equi-energy sampler and the sequential Monte Carlo sampler by avoiding the weaknesses of the straight Metropolis-Hastings algorithm as well as those of importance sampling. In particular, the DSMH sampler possesses the capacity to cope with incredibly irregular distributions that are full ...
FRB Atlanta Working Paper , Paper 2014-21

Working Paper
Multivariate return decomposition: theory and implications
Gospodinov, Nikolay; Anatolyev, Stanislav (2015-08-01)
In this paper, we propose a model based on multivariate decomposition of multiplicative?absolute values and signs?components of several returns. In the m-variate case, the marginals for the m absolute values and the binary marginals for the m directions are linked through a 2m-dimensional copula. The approach is detailed in the case of a bivariate decomposition. We outline the construction of the likelihood function and the computation of different conditional measures. The finite-sample properties of the maximum likelihood estimator are assessed by simulation. An application to predicting ...
FRB Atlanta Working Paper , Paper 2015-7

show more (118)

PREVIOUS / NEXT

Fed in Print

Search Results

FILTER BY YEAR

FILTER BY BANK

FILTER BY SERIES

FILTER BY CONTENT TYPE

FILTER BY AUTHOR

FILTER BY JEL CLASSIFICATION