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Online Estimation of DSGE Models
Sarfati, Reca; Matlin, Ethan; Herbst, Edward; Cai, Michael; Schorfheide, Frank; Del Negro, Marco (2019-08-01)
This paper illustrates the usefulness of sequential Monte Carlo (SMC) methods in approximating DSGE model posterior distributions. We show how the tempering schedule can be chosen adaptively, explore the benefits of an SMC variant we call generalized tempering for ?online? estimation, and provide examples of multimodal posteriors that are well captured by SMC methods. We then use the online estimation of the DSGE model to compute pseudo-out-of-sample density forecasts of DSGE models with and without financial frictions and document the benefits of conditioning DSGE model forecasts on nowcasts ...
Staff Reports , Paper 893

Report
Priors for the long run
Giannone, Domenico; Lenza, Michele; Primiceri, Giorgio E. (2017-11-01)
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

Report
Forecasting in large macroeconomic panels using Bayesian Model Averaging
Koop, Gary; Potter, Simon M. (2003-03-01)
This paper considers the problem of forecasting in large macroeconomic panels using Bayesian model averaging. Practical methods for implementing Bayesian model averaging with factor models are described. These methods involve algorithms that simulate from the space defined by all possible models. We explain how these simulation algorithms can also be used to select the model with the highest marginal likelihood (or highest value of an information criterion) in an efficient manner. We apply these methods to the problem of forecasting GDP and inflation using quarterly U.S. data on 162 time ...
Staff Reports , Paper 163

Report
Forecasting Macroeconomic Risks
Boyarchenko, Nina; Adams, Patrick A.; Adrian, Tobias; Giannone, Domenico (2020-02-01)
We construct risks around consensus forecasts of real GDP growth, unemployment, and inflation. We find that risks are time-varying, asymmetric, and partly predictable. Tight financial conditions forecast downside growth risk, upside unemployment risk, and increased uncertainty around the inflation forecast. Growth vulnerability arises as the conditional mean and conditional variance of GDP growth are negatively correlated: downside risks are driven by lower mean and higher variance when financial conditions tighten. Similarly, employment vulnerability arises as the conditional mean and ...
Staff Reports , Paper 914

Working Paper
Bargaining Shocks and Aggregate Fluctuations
Drautzburg, Thorsten; Fernandez-Villaverde, Jesus; Guerron-Quintana, Pablo (2020-03-12)
We argue that social and political risk causes signiﬁcant aggregate ﬂuctuations by changing bargaining power. To that end, we document signiﬁcant changes in the capital share after large political events, such as political realignments, modiﬁcations in collective bargaining rules, or the end of dictatorships, in a sample of developed and emerging economies. These policy changes are associated with signiﬁcant ﬂuctuations in output. Using a Bayesian proxy-VAR estimated with U.S. data, we show how distribution shocks cause movements in output and unemployment. To quantify the ...
Working Papers , Paper 20-11

Working Paper
Political Distribution Risk and Aggregate Fluctuations
Guerron-Quintana, Pablo; Fernandez-Villaverde, Jesus; Drautzburg, Thorsten (2017-08-21)
We argue that political distribution risk is an important driver of aggregate fluctuations. To that end, we document significant changes in the capital share after large political events, such as political realignments, modifications in collective bargaining rules, or the end of dictatorships, in a sample of developed and emerging economies. These policy changes are associated with significant fluctuations in output and asset prices. Using a Bayesian proxy-VAR estimated with U.S. data, we show how distribution shocks cause movements in output, unemployment, and sectoral asset prices. To ...
Working Papers , Paper 17-25

Working Paper
Do Phillips Curves Conditionally Help to Forecast Inflation?
Stark, Tom; Dotsey, Michael; Fujita, Shigeru (2017-08-21)
This paper reexamines the forecasting ability of Phillips curves from both an unconditional and conditional perspective by applying the method developed by Giacomini and White (2006). We find that forecasts from our Phillips curve models tend to be unconditionally inferior to those from our univariate forecasting models. Significantly, we also find conditional inferiority, with some exceptions. When we do find improvement, it is asymmetric - Phillips curve forecasts tend to be more accurate when the economy is weak and less accurate when the economy is strong. Any improvement we find, ...
Working Papers , Paper 17-26

Working Paper
Do Phillips curves conditionally help to forecast inflation?
Dotsey, Michael; Fujita, Shigeru; Stark, Tom (2015-03-25)
This paper reexamines the forecasting ability of Phillips curves from both an unconditional and conditional perspective by applying the method developed by Giacomini and White (2006). We find that forecasts from our Phillips curve models tend to be unconditionally inferior to those from our univariate forecasting models. We also find, however, that conditioning on the state of the economy sometimes does improve the performance of the Phillips curve model in a statistically significant manner. When we do find improvement, it is asymmetric -- Phillips curve forecasts tend to be more accurate ...
Working Papers , Paper 15-16

Working Paper
Assessing Macroeconomic Tail Risk
Loria, Francesca; Matthes, Christian; Zhang, Donghai (2019-04-19)
What drives macroeconomic tail risk? To answer this question, we borrow a definition of macroeconomic risk from Adrian et al. (2019) by studying (left-tail) percentiles of the forecast distribution of GDP growth. We use local projections (Jord, 2005) to assess how this measure of risk moves in response to economic shocks to the level of technology, monetary policy, and financial conditions. Furthermore, by studying various percentiles jointly, we study how the overall economic outlook?as characterized by the entire forecast distribution of GDP growth?shifts in response to shocks. We find that ...
Working Paper , Paper 19-10

Working Paper
Core and 'Crust': Consumer Prices and the Term Structure of Interest Rates
Ajello, Andrea; Benzoni, Luca; Chyruk, Olena (2012-12-19)
We propose a no-arbitrage model that jointly explains the dynamics of consumer prices as well as the nominal and real term structures of risk-free rates. In our framework, distinct core, food, and energy price series combine into a measure of total inflation to price nominal Treasuries. This approach captures different frequencies in inflation fluctuations: Shocks to core are more persistent and less volatile than shocks to food and, especially, energy (the 'crust'). We find that a common structure of latent factors determines and predicts the term structure of yields and inflation. The model ...
Working Paper Series , Paper WP-2014-11

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