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Jel Classification:C32 

Report
Online Estimation of DSGE Models

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
DSGE forecasts of the lost recovery

The years following the Great Recession were challenging for forecasters. Unlike other deep downturns, this recession was not followed by a swift recovery, but generated a sizable and persistent output gap that was not accompanied by deflation as a traditional Phillips curve relationship would have predicted. Moreover, the zero lower bound and unconventional monetary policy generated an unprecedented policy environment. We document the real real-time forecasting performance of the New York Fed dynamic stochastic general equilibrium (DSGE) model during this period and explain the results using ...
Staff Reports , Paper 844

Report
Money, credit, monetary policy, and the business cycle in the euro area: what has changed since the crisis?

This paper studies the relationship between the business cycle and financial intermediation in the euro area. We establish stylized facts and study their stability during the global financial crisis and the European sovereign debt crisis. Long-term interest rates have been exceptionally high and long-term loans and deposits exceptionally low since the Lehman collapse. Instead, short-term interest rates and short-term loans and deposits did not show abnormal dynamics in the course of the financial and sovereign debt crisis.
Staff Reports , Paper 885

Report
Fitting observed inflation expectations

This paper provides evidence on the extent to which inflation expectations generated by a standard Christiano et al. (2005)/Smets and Wouters (2003)?type DSGE model are in line with what is observed in the data. We consider three variants of this model that differ in terms of the behavior of, and the public?s information on, the central banks? inflation target, allegedly a key determinant of inflation expectations. We find that: 1) time-variation in the inflation target is needed to capture the evolution of expectations during the post-Volcker period; 2) the variant where agents have ...
Staff Reports , Paper 476

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

Report
Dynamic effects of credit shocks in a data-rich environment

We examine the dynamic effects of credit shocks using a large data set of U.S. economic and financial indicators in a structural factor model. An identified credit shock resulting in an unanticipated increase in credit spreads causes a large and persistent downturn in indicators of real economic activity, labor market conditions, expectations of future economic conditions, a gradual decline in aggregate price indices, and a decrease in short- and longer-term riskless interest rates. Our identification procedure, which imposes restrictions on the response of a small number of economic ...
Staff Reports , Paper 615

Report
Tracking the new economy: using growth theory to detect changes in trend productivity

The acceleration of productivity since 1995 has prompted a debate over whether the economy's underlying growth rate will remain high. In this paper, we propose a methodology for estimating trend growth that draws on growth theory to identify variables other than productivity namely consumption and labor compensation to help estimate trend productivity growth. We treat that trend as a common factor with two "regimes," high-growth and low-growth. Our analysis picks up striking evidence of a switch in the mid-1990s to a higher long-term growth regime, as well as a switch in the early 1970s in ...
Staff Reports , Paper 159

Report
Macroeconomic nowcasting and forecasting with big data

Data, data, data . . . Economists know it well, especially when it comes to monitoring macroeconomic conditions?the basis for making informed economic and policy decisions. Handling large and complex data sets was a challenge that macroeconomists engaged in real-time analysis faced long before ?big data? became pervasive in other disciplines. We review how methods for tracking economic conditions using big data have evolved over time and explain how econometric techniques have advanced to mimic and automate the best practices of forecasters on trading desks, at central banks, and in other ...
Staff Reports , Paper 830

Working Paper
Asymmetry, Complementarities, and State Dependence in Federal Reserve Forecasts

Forecasts are a central component of policy making; the Federal Reserve''s forecasts are published in a document called the Greenbook. Previous studies of the Greenbook''s inflation forecasts have found them to be rationalizable but asymmetric if considering particular sub-periods, e.g., before and after the Volcker appointment. In these papers, forecasts are analyzed in isolation, assuming policymakers value them independently. We analyze the Greenbook fore- casts in a framework in which the forecast errors are allowed to interact. We find that allowing the losses to interact makes the ...
Working Papers , Paper 2013-012

Working Paper
Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors

We develop uncertainty measures for point forecasts from surveys such as the Survey of Professional Forecasters, Blue Chip, or the Federal Open Market Committee's Summary of Economic Projections. At a given point of time, these surveys provide forecasts for macroeconomic variables at multiple horizons. To track time-varying uncertainty in the associated forecast errors, we derive a multiple-horizon specification of stochastic volatility. Compared to constant-variance approaches, our stochastic-volatility model improves the accuracy of uncertainty measures for survey forecasts.
Working Papers , Paper 2017-026

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