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The New York Fed engages with individuals, households and businesses in the Second District and maintains an active dialogue in the region. The Bank gathers and shares regional economic intelligence to inform our community and policy makers, and promotes sound financial and economic decisions through community development and education programs.
Abhi Gupta, Pearl Li, Erica Moszkowski, Marco Del Negro, and Marc Giannoni
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 global financial crisis has put financial stability risks—and the potential role of macroprudential policies in addressing them—at the forefront of policy debates. The challenge for macroeconomists is to develop new models that are consistent with the data while being able to capture the highly nonlinear nature of crisis episodes. In this post, we evaluate the impact of a macroprudential policy that has the government tilt incentives for banks to encourage them to build up their equity positions. The government has a role since individual banks do not internalize the systemic benefit of having more bank equity. Our model allows for an evaluation of the tradeoff between the size of such incentives and the probability of a future financial crisis.
Marco Del Negro, Marc Giannoni, Abhi Gupta, Pearl Li, and Erica Moszkowski
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 have since published forecasts twice a year. Here we describe our current forecast and highlight how it has changed since May 2016.
In recent months, there have been some high-profile assessments of how far the Federal Reserve has come in terms of communicating about monetary policy since its “secrets of the temple” days. While observers say the transition to greater transparency “still seems to be a work in progress,” they note the range of steps the Fed has taken over the years to shed light on its strategy, including issuing statements to announce and explain policy changes following Federal Open Market Committee (FOMC) meetings, post-meeting press conferences and minutes, FOMC-member speeches and testimony, and “forward guidance” in all its variants.
As Director of Research for the New York Fed for the past seven years, Jamie McAndrews has been responsible for the Bank’s financial and economic policy research, as well as the collection of data and statistics from financial institutions. On the eve of his retirement on June 30, Jamie shared his perspective on how the Research and Statistics Group has changed with Andrew Haughwout, a senior vice president in the Group.
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.
Stefano Eusepi, Erica Moszkowski, and Argia Sbordone
The May 2016 forecast of the Federal Reserve Bank of New York’s (FRBNY) dynamic stochastic general equilibrium (DSGE) model remains broadly in line with those of our two previous semiannual reports (see our May 2015 and December 2015 posts). In the past year, the headwinds that contributed to slower growth in the aftermath of the financial crisis finally began to abate. However, the widening of credit spreads associated with swings in financial markets in the second half of 2015 and the first few months of this year have had a negative impact on economic activity. Despite this setback, the model expects a rebound in growth in the second half of the year, so that the medium-term forecast remains, as in the December post, one of steady, gradual economic expansion. The model also continues to predict gradual progress in the inflation rate toward the Federal Open Market Committee’s (FOMC) long-run target of 2 percent.
When we launched our research blog five years ago this week, we didn’t expect to set any internet traffic records while writing about economics. Still, we saw that a blog would be a good way to build familiarity with our research and policy analysis, and to share the expertise of our staff when it’s relevant to issues in the public eye. As I said back at the birth, our goal was to deliver “lively, clear, and analytically sound” posts and, in that, I think we have succeeded.
In recent speeches, the Federal Reserve’s Janet Yellen and Lael Brainerd explained how policymakers are likely to take a cautious approach to normalizing monetary policy given historically low estimates for the natural rate of interest and expectations that the rate will rise only gradually over time.
Marco Del Negro, Marc Giannoni, Pearl Li, Erica Moszkowski, and Micah Smith
We have implemented the FRBNY DSGE model in a free and open-source language called Julia. The code is posted here on GitHub, a public repository hosting service. This effort is the result of a collaboration between New York Fed staff and folks from the QuantEcon project, whose aim is to coordinate development of high performance open-source code for quantitative economic modeling.
Liberty Street Economics features insight and analysis from economists working at the intersection of research and policy. The editors are Michael Fleming, Andrew Haughwout, Thomas Klitgaard, and Donald Morgan.
The views expressed are those of the authors, and do not necessarily reflect the position of the New York Fed or the Federal Reserve System.
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