How forward-looking is optimal monetary policy?
We calculate optimal monetary policy rules for several variants of a simple optimizing model of the monetary transmission mechanism with sticky prices and/or wages. We show that robustly optimal rules can be represented by interest-rate feedback rules that generalize the celebrated proposal of Taylor (1993). Optimal rules, however, require that the current interest rate operating target depend positively on the recent past level of the operating target, and its recent rate of increase, in a way that is characteristic of estimated central bank reaction functions, but not of Taylor's proposal.
Assessing changes in the monetary transmission mechanism: a VAR approach
Paper for a conference sponsored by the Federal Reserve Bank of New York entitled Financial Innovation and Monetary Transmission
The Macroeconomic Effects of Forward Guidance
In this post, we quantify the macroeconomic effects of central bank announcements about future federal funds rates, or forward guidance. We estimate that a commitment to lowering future rates below market expectations can have fairly strong effects on real economic activity with only small effects on inflation.
Why Didn’t Inflation Collapse in the Great Recession?
GDP contracted 4 percent from 2008:Q2 to 2009:Q2, and the unemployment rate peaked at 10 percent in October 2010. Traditional backward-looking Phillips curve models of inflation, which relate inflation to measures of “slack” in activity and past measures of inflation, would have predicted a substantial drop in inflation. However, core inflation declined by only one percentage point, from 2.2 percent in 2007 to 1.2 percent in 2009, giving rise to the “missing deflation” puzzle. Based on this evidence, some authors have argued that slack must have been smaller than suggested by ...
Forecasting with the FRBNY DSGE Model
The Federal Reserve Bank of New York (FRBNY) has built a DSGE model as part of its efforts to forecast the U.S. economy. On Liberty Street Economics, we are publishing a weeklong series to provide some background on the model and its use for policy analysis and forecasting, as well as its forecasting performance. In this post, we briefly discuss what DSGE models are, explain their usefulness as a forecasting tool, and preview the forthcoming pieces in this series.
An Assessment of the FRBNY DSGE Model's Real-Time Forecasts, 2010-2013
The previous post in this series showed how the Federal Reserve Bank of New York?s DSGE model can be used to provide an interpretation of the Great Recession and the slow recovery. In this post, we look at the role of the model as a forecasting tool and evaluate its forecasting performance since 2010. This analysis will give context for the last post, which will present the model?s current forecast for the U.S. economy.
The FRBNY DSGE Model Forecast
The U.S. economy has been in a gradual but slow recovery. Will the future be more of the same? This post presents the current forecasts from the Federal Reserve Bank of New York?s (FRBNY) DSGE model, described in our earlier ?Bird?s Eye View? post, and discusses the driving forces behind the forecasts. Find the code used for estimating the model and producing all the charts in this blog series here. (We should reiterate that these are not the official New York Fed staff forecasts, but only an input to the overall forecasting process at the Bank.)
Why Are Interest Rates So Low?
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 ...
The FRBNY DSGE Model Meets Julia
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.
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.