Forecasts of the Lost Recovery
The years following the Great Recession were challenging for forecasters for a variety of reasons, including an unprecedented policy environment. This post, based on our recently released working paper, documents the real-time forecasting performance of the New York Fed dynamic stochastic general equilibrium (DSGE) model in the wake of the Great Recession. We show that the model’s predictive accuracy was on par with that of private forecasters and proved to be quite a bit better, at least in terms of GDP growth, than that of the median forecasts from the Federal Open Market Committee’s (FOMC) Summary of Economic Projections (SEP).
The New York Fed DSGE Model Forecast–March 2018
This post presents a quarterly update of the economic forecast generated by the Federal Reserve Bank of New York’s dynamic stochastic general equilibrium (DSGE) model. We describe our forecast very briefly and highlight its change since November 2017.
A DSGE Perspective on Safety, Liquidity, and Low Interest Rates
Marco Del Negro, Domenico Giannone, Marc Giannoni, Abhi Gupta, Pearl Li, and Andrea Tambalotti Third of three posts The preceding two posts in this series documented that interest rates on safe and liquid assets, such as U.S. Treasury securities, have declined significantly in the past twenty years. Of course, short-term interest rates in the United […]
The New York Fed DSGE Model Forecast–November 2017
This post presents our quarterly update of the economic forecasts generated by the Federal Reserve Bank of New York’s dynamic stochastic general equilibrium (DSGE) model. We describe very briefly our forecast and its change since August 2017.
The New York Fed DSGE Model Forecast—August 2017
This post presents our quarterly update of the economic forecasts generated by the Federal Reserve Bank of New York’s dynamic stochastic general equilibrium (DSGE) model. We describe very briefly our forecast and its change since May 2017.
The New York Fed DSGE Model Forecast—May 2017
This post presents our quarterly update of the economic forecasts generated by the Federal Reserve Bank of New York’s dynamic stochastic general equilibrium (DSGE) model. We describe very briefly our forecast and its change since February 2017. As usual, we wish to remind our readers that the DSGE model forecast is not an official New York Fed forecast, but only an input to the Research staff’s overall forecasting process. For more information about the model and variables discussed here, see our DSGE Model Q & A .
Forecasting with Julia
A little more than a year ago, in this post, we announced DSGE.jl—a package for working with dynamic stochastic general equilibrium (DSGE) models using Julia, the open-source computing language. At that time, DSGE.jl contained only the code required to specify, solve, and estimate such models using Bayesian methods. Now, we have extended the package to provide the additional code needed to produce economic forecasts, counterfactual simulations, and inference on unobservable variables, such as the natural rate of interest or the output gap. The old, pre-Julia version of the code, which was written in MATLAB and is posted here on Github, a public repository hosting service, also performed some of these functions, but not quite as fast.
The FRBNY DSGE Model Forecast—February 2017
This post presents the latest update of the economic forecasts generated by the Federal Reserve Bank of New York’s (FRBNY) dynamic stochastic general equilibrium (DSGE) model. We introduced this model in a series of blog posts in September 2014 and published forecasts twice a year thereafter. With this post, we move to a quarterly release schedule, and highlight how our forecasts have changed since November 2016.
Readers should keep in mind that the DSGE model forecast is not an official New York Fed forecast, but only an input to the Research staff’s overall forecasting process. For more information about the model and the variables discussed here, see our DSGE Model Q & A.
The FRBNY DSGE Model Forecast—November 2016
This post presents the latest update of the economic forecasts generated by the Federal Reserve Bank of New York’s (FRBNY) dynamic stochastic general equilibrium (DSGE) model.
The Macro Effects of the Recent Swing in Financial Conditions
Credit conditions tightened considerably in the second half of 2015 and U.S. growth slowed. We estimate the extent to which tighter credit conditions last year were responsible for the slowdown using the FRBNY DSGE model. We find that growth would have slowed substantially more had the Federal Reserve not delayed liftoff in the federal funds rate.