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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.
Marco Del Negro, Marc Giannoni, Erica Moszkowski, Sara Shahanaghi, and Micah Smith
This post presents an update of the economic forecasts implied by the Federal Reserve Bank of New York’s (FRBNY) dynamic stochastic general equilibrium (DSGE) model, which we first introduced in a series of blog posts in September 2014. The model continues to predict a gradual recovery in economic activity, but one that will proceed at a slightly slower pace than was forecast in our April update. It also predicts a slow return of inflation toward the Federal Open Market Committee’s (FOMC) long-run target of 2 percent. This forecast remains surrounded by significant uncertainty. Please note that the DSGE model forecasts are not the official New York Fed staff forecasts, but only an input to the overall forecasting process at the Bank.
Inflation dynamics are often described by some form of the Phillips curve. Named after A. W. Phillips, the British economist whose study of U.K. wage and unemployment data laid the groundwork, the Phillips curve denotes an inverse relationship between inflation and some measure of economic slack. A much-discussed issue in the literature is how forward-looking this relationship is. In this post, we address this question using a flexible version of the New KeynesianPhillips curve (NKPC) to illustrate the key role that expectations play in inflation dynamics.
Marco Del Negro, Marc Giannoni, Matthew Cocci, Sara Shahanaghi, and Micah Smith
Second post in the series
In a recent series of blog posts, the former Chairman of the Federal Reserve System, Ben Bernanke, has asked the question: “Why are interest rates so low?” (See part 1, part 2, and part 3.) He refers, of course, to the fact that the U.S. government is able to borrow at an annualized rate of around 2 percent for ten years, or around 3 percent for thirty years. If you expect that inflation is going to be on average 2 percent over the next ten or thirty years, this implies that the U.S. government can borrow at real rates of interest between 0 and 1 percent at the ten- and thirty-year maturities. This phenomenon is by no means limited to the United States. Governments in Japan and Germany are able to borrow for ten years at nominal rates below 1 percent, and the ten-year yield on Swiss government debt is slightly negative. Why is that?
Marco Del Negro, Marc Giannoni, Matthew Cocci, Sara Shahanaghi, and Micah Smith
First in a two-part series
There are various types of economic forecasts, such as judgmental forecasts or model-based forecasts. In this post, we provide an update of the economic forecasts implied by the Federal Reserve Bank of New York’s (FRBNY) dynamic stochastic general equilibrium (DSGE) model, which we introduced in a series of five blog posts in September 2014 here. It continues to predict a gradual recovery in economic activity with a progressive but slow return of inflation toward the Federal Open Market Committee’s (FOMC) long-run target of 2 percent. This forecast remains surrounded by significant uncertainty. Please note that the DSGE model forecasts are not the official New York Fed staff forecasts, but only an input to the overall forecasting process at the Bank.
Marco Del Negro, Raiden Hasegawa, and Frank Schorfheide
Second in a two-part series
As an economist, you make policy recommendations at any point in time that depend on what model of the economy you have in mind and on your assessment of the state of the economy. One can see these points play out in the current discussion about the timing of interest rate liftoff and the speed of the subsequent renormalization. If you think nominal rigidities are not all that important, you are likely to conclude that accommodative policies won’t do much for growth but will generate inflation. Similarly, if you are convinced that the economy is already firing on all cylinders, you may see little need for prolonged accommodation. The problem is, you are not quite sure about the state of the economy or what the right model is. If you are a Bayesian, you may want to try to put probabilities on different models/states of the world and take it from there. The first post in this series, “Combining Models for Forecasting and Policy Analysis,” introduced a procedure called dynamic pools that shows how to do just that. In this post, we apply that procedure to a policy exercise. We can’t publicly discuss current policies, so we will instead apply our method to consider alternative monetary policies at the onset of the Great Recession.
Liberty Street Economics features insight and analysis from New York Fed economists working at the intersection of research and policy. Launched in 2011, the blog takes its name from the Bank’s headquarters at 33 Liberty Street in Manhattan’s Financial District.
The editors are Michael Fleming, Andrew Haughwout, Thomas Klitgaard, Donald Morgan, and Asani Sarkar, all economists in the Bank’s Research Group.
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