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Keywords:DSGE models 

Discussion Paper
What’s Up with the Phillips Curve?

U.S. inflation used to rise during economic booms, as businesses charged higher prices to cope with increases in wages and other costs. When the economy cooled and joblessness rose, inflation declined. This pattern changed around 1990. Since then, U.S. inflation has been remarkably stable, even though economic activity and unemployment have continued to fluctuate. For example, during the Great Recession unemployment reached 10 percent, but inflation barely dipped below 1 percent. More recently, even with unemployment as low as 3.5 percent, inflation remained stuck under 2 percent. What ...
Liberty Street Economics , Paper 20200918a

Working Paper
Financial Business Cycles

Using Bayesian methods, I estimate a DSGE model where a recession is initiated by losses suffered by banks and exacerbated by their inability to extend credit to the real sector. The event triggering the recession has the workings of a redistribution shock: a small sector of the economy -- borrowers who use their home as collateral -- defaults on their loans. When banks hold little equity in excess of regulatory requirements, the losses require them to react immediately, either by recapitalizing or by deleveraging. By deleveraging, banks transform the initial shock into a credit crunch, and, ...
International Finance Discussion Papers , Paper 1116

Report
Exploiting the monthly data flow in structural forecasting

This paper develops a framework that allows us to combine the tools provided by structural models for economic interpretation and policy analysis with those of reduced-form models designed for nowcasting. We show how to map a quarterly dynamic stochastic general equilibrium (DSGE) model into a higher frequency (monthly) version that maintains the same economic restrictions. Moreover, we show how to augment the monthly DSGE with auxiliary data that can enhance the analysis and the predictive accuracy in now-casting and forecasting. Our empirical results show that both the monthly version of ...
Staff Reports , Paper 751

Report
Forming priors for DSGE models (and how it affects the assessment of nominal rigidities)

This paper discusses prior elicitation for the parameters of dynamic stochastic general equilibrium (DSGE) models and provides a method for constructing prior distributions for a subset of these parameters from beliefs about the moments of the endogenous variables. The empirical application studies the role of price and wage rigidities in a New Keynesian DSGE model and finds that standard macro time series cannot discriminate among theories that differ in the quantitative importance of nominal frictions.
Staff Reports , Paper 320

Working Paper
Selecting Primal Innovations in DSGE models

DSGE models are typically estimated assuming the existence of certain primal shocks that drive macroeconomic fluctuations. We analyze the consequences of estimating shocks that are "non-existent" and propose a method to select the primal shocks driving macroeconomic uncertainty. Forcing these non-existing shocks in estimation produces a downward bias in the estimated internal persistence of the model. We show how these distortions can be reduced by using priors for standard deviations whose support includes zero. The method allows us to accurately select primal shocks and estimate model ...
Working Paper Series , Paper WP-2017-20

Working Paper
OccBin: A Toolkit for Solving Dynamic Models With Occasionally Binding Constraints Easily

We describe how to adapt a first-order perturbation approach and apply it in a piecewise fashion to handle occasionally binding constraints in dynamic models. Our examples include a real business cycle model with a constraint on the level of investment and a New Keynesian model subject to the zero lower bound on nominal interest rates. We compare the piecewise linear perturbation solution with a high-quality numerical solution that can be taken to be virtually exact. The piecewise linear perturbation method can adequately capture key properties of the models we consider. A key advantage of ...
Finance and Economics Discussion Series , Paper 2014-47

Report
Dynamic prediction pools: an investigation of financial frictions and forecasting performance

We provide a novel methodology for estimating time-varying weights in linear prediction pools, which we call dynamic pools, and use it to investigate the relative forecasting performance of dynamic stochastic general equilibrium (DSGE) models, with and without financial frictions, for output growth and inflation in the period 1992 to 2011. We find strong evidence of time variation in the pool?s weights, reflecting the fact that the DSGE model with financial frictions produces superior forecasts in periods of financial distress but doesn?t perform as well in tranquil periods. The dynamic ...
Staff Reports , Paper 695

Discussion Paper
Forecasting the Great Recession: DSGE vs. Blue Chip

Dynamic stochastic general equilibrium (DSGE) models have been trashed, bashed, and abused during the Great Recession and after. One of the many reasons for the bashing was the models’ alleged inability to forecast the recession itself. Oddly enough, there’s little evidence on the forecasting performance of DSGE models during this turbulent period. In the paper “DSGE Model-Based Forecasting,” prepared for Elsevier’s Handbook of Economic Forecasting, two of us (Del Negro and Schorfheide), with the help of the third (Herbst), provide some of this evidence. This post shares some of our ...
Liberty Street Economics , Paper 20120416

Report
Rare shocks, great recessions

We estimate a DSGE model where rare large shocks can occur, by replacing the commonly used Gaussian assumption with a Student?s t distribution. Results from the Smets and Wouters (2007) model estimated on the usual set of macroeconomic time series over the 1964-2011 period indicate that 1) the Student?s t specification is strongly favored by the data even when we allow for low-frequency variation in the volatility of the shocks and 2) the estimated degrees of freedom are quite low for several shocks that drive U.S. business cycles, implying an important role for rare large shocks. This result ...
Staff Reports , Paper 585

Report
Safety, liquidity, and the natural rate of interest

Why are interest rates so low in the Unites States? We find that they are low primarily because the premium for safety and liquidity has increased since the late 1990s, and to a lesser extent because economic growth has slowed. We reach this conclusion using two complementary perspectives: a flexible time-series model of trends in Treasury and corporate yields, inflation, and long-term survey expectations, and a medium-scale dynamic stochastic general equilibrium (DSGE) model. We discuss the implications of this finding for the natural rate of interest.
Staff Reports , Paper 812

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