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Today, the Federal Reserve Bank of New York (FRBNY) is hosting the spring meeting of its Economic Advisory Panel (EAP). As has become the custom at this meeting, the FRBNY staff is presenting its forecast for U.S. growth, inflation, and the unemployment rate. Following the presentation, members of the EAP, which consists of leading economists in academia and the private sector, are asked to critique the staff forecast. Such feedback helps the staff evaluate the assumptions and reasoning underlying its forecast as well as the forecast’s key risks. The feedback is also an important part of the forecasting process because it informs the staff’s discussions with New York Fed President William Dudley about economic conditions. In that same spirit, we are sharing a short summary of the staff forecast in this post; for more detail, see the FRBNY Staff Outlook Presentation from the EAP meeting on our website.
Grant Aarons, Daniele Caratelli, Matthew Cocci, Domenico Giannone, Argia Sbordone, and Andrea Tambalotti
What is the weather today? You don’t need to be a meteorologist to answer this question. Just take a look outside the window. Macroeconomists do not have this luxury. The first official estimate of GDP this quarter will not be published until the end of July. In fact, we don’t even know what GDP was last quarter yet! But while we wait for these crucial data, we float in a sea of information on all aspects of the economy: employment, production, sales, inventories, you name it. . . . Processing this information to figure out if it is rainy or sunny out there in the economy is the bread and butter of economists on trading desks, at central banks, and in the media. Thankfully, recent advances in computational and statistical methods have led to the development of automated real-time solutions to this challenging big data problem, with an approach commonly referred to as nowcasting. This post describes how we apply these techniques here at the New York Fed to produce the FRBNY Nowcast, and what we can learn from it. It also serves as an introduction to our Nowcasting Report, which we will update weekly on our website starting this Friday, April 15.
Bonni Brodsky, Marco Del Negro, Joseph Fiorica, Eric LeSueur, Ari Morse, and Anthony Rodrigues
In our previous post, we showed that the gap between the market-implied path for the federal funds rate and the survey-implied mean expectations for the federal funds rate from the Survey of Primary Dealers (SPD) and the Survey of Market Participants (SMP) narrowed from the December survey to the January survey. In particular, we provided explanations for this narrowing as well as for the subsequent widening from January to March. This post continues the discussion by presenting a novel approach called “tilting” that yields insights by measuring how much the survey probability distributions have to be altered to match the market-implied path of the federal funds rate. We interpret any discrepancy between the original and tilted distributions as arising from either risk premia or dispersion in beliefs.
Bonni Brodsky, Marco Del Negro, Joseph Fiorica, Eric LeSueur, Ari Morse, and Anthony Rodrigues
Over the past year, market pricing on interest rate derivatives linked to the federal funds rate has suggested a significantly lower expected path of the policy rate than responses to the New York Fed’s Survey of Primary Dealers (SPD) and Survey of Market Participants (SMP). However, this gap narrowed considerably from December 2015 to January 2016, before widening slightly at longer horizons in March. This post argues that the narrowing between December and January was mostly the result of survey respondents placing greater weight on lower rate outcomes, while the subsequent widening between January and March likely reflects an increased demand for insurance against states of the world where the policy rate remains at very low levels.
Correction: In the original version of this post, the chart “Average Daily Fedwire Payments Are Higher at Quarter-End” contained incorrect data. The chart has now been updated. We regret the error.
The federal funds market is an important source of short-term funding for U.S. banks. In this market, banks borrow reserves on an unsecured basis from other banks and from government-sponsored enterprises, typically overnight. Before the financial crisis, the Federal Reserve implemented monetary policy by targeting the overnight fed funds rate and then adjusting the supply of bank reserves every day to keep the rate close to the target. Before the crisis, reserves were generally in scarce supply, which periodically caused temporary spikes in the fed funds rate during times of high demand, typically at the end of each quarter. In this post, we show that the Fed actively responded to quarter-end volatility by injecting reserves into the banking system around these dates.
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.
The 2007-09 financial crisis, and the monetary policy response to it, have greatly increased the size of central bank balance sheets around the world. These changes were not always well understood and some were controversial. We discuss these crisis-induced changes, following yesterday’s post on the composition of central bank balance sheets in normal times, and explain the policy intentions behind some of them.
There has been unusually high activity on central banks’ balance sheets in recent years. This activity, which has expanded beyond the core operations and collateral of the central bank, has been called “unconventional,” “nonstandard,” “nontraditional,” and “active.” But what constitutes a normal central bank balance sheet? How does central bank asset and liability composition vary across countries and how did the crisis change this composition? In this post, we focus on the main characteristics of central bank balance sheets before the crisis. In our next piece, we describe how this composition has changed in response to the crisis.
What types of counterparties can borrow from or lend to a central bank, and what kind of collateral must they possess in order to receive a loan? These are two key aspects of a central bank’s monetary policy implementation framework. Since at least the nineteenth century, it has been understood that an important role of central banks is to lend to solvent but illiquid institutions, particularly during a crisis, as this provides liquidity insurance to the financial system. They also provide liquidity to markets during normal times as a means to implement monetary policy. Central banks that rely on scarcity of reserves need to adjust the supply of liquidity in the market, as described in our previous post. In this post, we focus on liquidity provision related to the conduct of monetary policy.
In the minutes of the July 2015 Federal Open Market Committee (FOMC) meeting, the chair indicated that Federal Reserve staff would undertake an extended effort to evaluate potential long-run monetary policy implementation frameworks. But what is a central bank’s monetary policy implementation framework? In a series of four posts, we provide an overview of the key elements that typically constitute such a framework.
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