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Working Paper
Estimating Hysteresis Effects
Furlanetto, Francesco; Lepetit, Antoine; Robstad, Ørjan; Rubio-Ramirez, Juan F.; Ulvedal, Pål (2021-11-09)
In this paper, we identify demand shocks that can have a permanent effect on output through hysteresis effects. We call these shocks permanent demand shocks. They are found to be quantitatively important in the United States, in particular when the sample includes the Great Recession. Recessions driven by permanent demand shocks lead to a permanent decline in employment and investment, although output per worker is largely unaffected. We find strong evidence that hysteresis transmits through a rise in long-term unemployment and a decline in labor force participation and disproportionately ...
FRB Atlanta Working Paper , Paper 2021-24

Report
A Bayesian Approach to Inference on Probabilistic Surveys
Del Negro, Marco; Casarin, Roberto; Bassetti, Federico (2022-07-01)
We propose a nonparametric Bayesian approach for conducting inference on probabilistic surveys. We use this approach to study whether U.S. Survey of Professional Forecasters density projections for output growth and inflation are consistent with the noisy rational expectations hypothesis. We find that in contrast to theory, for horizons close to two years, there is no relationship whatsoever between subjective uncertainty and forecast accuracy for output growth density projections, both across forecasters and over time, and only a mild relationship for inflation projections. As the horizon ...
Staff Reports , Paper 1025

Working Paper
The Role of the Prior in Estimating VAR Models with Sign Restrictions
Inoue, Atsushi; Kilian, Lutz (2020-12-03)
Several recent studies have expressed concern that the Haar prior typically imposed in estimating sign-identified VAR models may be unintentionally informative about the implied prior for the structural impulse responses. This question is indeed important, but we show that the tools that have been used in the literature to illustrate this potential problem are invalid. Specifically, we show that it does not make sense from a Bayesian point of view to characterize the impulse response prior based on the distribution of the impulse responses conditional on the maximum likelihood estimator of ...
Working Papers , Paper 2030

Working Paper
Assessing Abenomics: Evidence from Inflation-Indexed Japanese Government Bonds
Christensen, Jens H. E.; Spiegel, Mark M. (2019-10-15)
We assess the impact of news concerning the reforms associated with ?Abenomics? using an arbitrage-free term structure model of nominal and real yields. Our model explicitly accounts for the deflation protection enhancement embedded in Japanese inflation-indexed bonds issued since 2013, which pay their original nominal principal when deflation has occurred from issue to maturity. The value of this enhancement is sizable and time-varying, with substantive impacts on estimates of expected inflation compensation. After properly accounting for deflation protection, our results suggest that ...
Working Paper Series , Paper 2019-15

Working Paper
Forecast Combination for Euro Area Inflation - A Cure in Times of Crisis?
Hubrich, Kirstin; Skudelny, Frauke (2016-08)
The period of extraordinary volatility in euro area headline inflation starting in 2007 raised the question whether forecast combination methods can be used to hedge against bad forecast performance of single models during such periods and provide more robust forecasts. We investigate this issue for forecasts from a range of short-term forecasting models. Our analysis shows that there is considerable variation of the relative performance of the different models over time. To take that into account we suggest employing performance-based forecast combination methods, in particular one with more ...
Finance and Economics Discussion Series , Paper 2016-104

Working Paper
Dividend Momentum and Stock Return Predictability: A Bayesian Approach
Antolin-Diaz, Juan; Petrella, Ivan; Rubio-Ramirez, Juan F. (2021-11-10)
A long tradition in macro finance studies the joint dynamics of aggregate stock returns and dividends using vector autoregressions (VARs), imposing the cross-equation restrictions implied by the Campbell-Shiller (CS) identity to sharpen inference. We take a Bayesian perspective and develop methods to draw from any posterior distribution of a VAR that encodes a priori skepticism about large amounts of return predictability while imposing the CS restrictions. In doing so, we show how a common empirical practice of omitting dividend growth from the system amounts to imposing the extra ...
FRB Atlanta Working Paper , Paper 2021-25

Working Paper
Real exchange rate forecasting and ppp: this time the random walk loses
Rubaszek, Michal; Muck, Jakub; Ca' Zorzi, Michele (2015-03-01)
This paper brings four new insights into the Purchasing Power Parity (PPP) debate. First, we show that a half-life PPP (HL) model is able to forecast real exchange rates better than the random walk (RW) model at both short and long-term horizons. Second, we find that this result holds if the speed of adjustment to the sample mean is calibrated at reasonable values rather than estimated. Third, we find that it is preferable to calibrate, rather than to elicit as a prior, the parameter determining the speed of adjustment to PPP. Fourth, for most currencies in our sample, the HL model ...
Globalization Institute Working Papers , Paper 229

Working Paper
Growth-at-Risk is Investment-at-Risk
Amburgey, Aaron; McCracken, Michael W. (2023-08-21)
We investigate the role financial conditions play in the composition of U.S. growth-at-risk. We document that, by a wide margin, growth-at-risk is investment-at-risk. That is, if financial conditions indicate U.S. real GDP growth will be in the lower tail of its conditional distribution, we know that the main contributor is a decline in investment. Consumption contributes under extreme financial stress. Government spending and net exports do not play a role.
Working Papers , Paper 2023-020

Working Paper
High-Dimensional Copula-Based Distributions with Mixed Frequency Data
Patton, Andrew J.; Oh, Dong Hwan (2015-05-19)
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

Working Paper
Nowcasting Business Cycles: a Bayesian Approach to Dynamic Heterogeneous Factor Models
D'Agostino, Antonello; Giannone, Domenico; Lenza, Michele; Modugno, Michele (2015-08-06)
We develop a framework for measuring and monitoring business cycles in real time. Following a long tradition in macroeconometrics, inference is based on a variety of indicators of economic activity, treated as imperfect measures of an underlying index of business cycle conditions. We extend existing approaches by permitting for heterogenous lead-lag patterns of the various indicators along the business cycles. The framework is well suited for high-frequency monitoring of current economic conditions in real time - nowcasting - since inference can be conducted in presence of mixed frequency ...
Finance and Economics Discussion Series , Paper 2015-66

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