Since the global financial crisis, the Federal Reserve has relied on two main rates to implement monetary policy—the rate paid on reserve balances (IORB rate) and the rate offered at the overnight reverse repo facility (ON RRP rate). In this post, we explore how these tools steer the federal funds rate within the Federal Reserve’s target range and how effective they have been at supporting rate control.
This post discusses the evolution of the short-run natural rate of interest, or short-run r*, over the past year and a half according to the New York Fed DSGE model, and the implications of this evolution for inflation and output projections. We show that, from the model’s perspective, short-run r* has increased notably over the past year, to some extent outpacing the large increase in the policy rate. One implication of these findings is that the drag on the economy from recent monetary policy tightening may have been limited, rationalizing why economic conditions have remained relatively buoyant so far despite the elevated level of interest rates.
Stablecoins are digital assets whose value is pegged to that of fiat currencies, usually the U.S. dollar, with a typical exchange rate of one dollar per unit. Their market capitalization has grown exponentially over the last couple of years, from $5 billion in 2019 to around $180 billion in 2022. Notwithstanding their name, however, stablecoins can be very unstable: between May 1 and May 16, 2022, there was a run on stablecoins, with their circulation decreasing by 15.58 billion and their market capitalization dropping by $25.63 billion (see charts below.) In this post, we describe the different types of stablecoins and how they keep their peg, compare them with money market funds—a similar but much older and more regulated financial product, and discuss the stablecoin run of May 2022.
Daily investment at the Federal Reserve’s Overnight Reverse Repo (ON RRP) facility increased from a few billion dollars in March 2021 to more than $2.3 trillion in June 2022 and has stayed above $2 trillion since then. In this post, which is based on a recent staff report, we discuss two channels—a deposit channel and a wholesale short-term debt channel—through which banks’ balance-sheet costs have increased investment by money market mutual funds (MMFs) in the ON RRP facility.
The size of the money market fund (MMF) industry co-moves with the monetary policy cycle. In a post published in 2019, we showed that this co-movement is likely due to the stronger response of MMF yields to monetary policy tightening relative to bank deposit rates, combined with MMF shares and bank deposits being close substitutes from an investor’s perspective. In this post, we update the analysis and zoom in to the current monetary policy tightening by the Federal Reserve.
Over the past fifteen years, reserves in the banking system have grown from tens of billions of dollars to several trillion dollars. This extraordinary rise poses a natural question: Are the rates paid in the market for reserves still sensitive to changes in the quantity of reserves when aggregate reserve holdings are so large? In today’s post, we answer this question by estimating the slope of the reserve demand curve from 2010 to 2022, when reserves ranged from $1 trillion to $4 trillion.
In March 2020, U.S. prime money market funds (MMFs) suffered heavy outflows following the liquidity shock triggered by the COVID-19 crisis. In a previous post, we characterized the run on the prime MMF industry as a whole and the role of the liquidity facility established by the Federal Reserve (the Money Market Mutual Fund Liquidity Facility) in stemming the run. In this post, based on a recent Staff Report, we contrast the behaviors of retail and institutional investors during the run and explain the different reasons behind the run.
Changes in the distribution of banks’ reserve balances are important since they may impact conditions in the federal funds market and alter trading dynamics in money markets more generally. In this post, we propose using the Lorenz curve and Gini coefficient as a new approach to measuring reserve concentration. Since 2013, concentration, as captured by the Lorenz curve and the Gini coefficient, has co-moved with aggregate reserves, decreasing as aggregate reserves declined (such as in 2015-18) and increasing as aggregate reserves increased (such as at the onset of the COVID-19 pandemic).
Aggregate reserves declined from nearly $3 trillion in August 2014 to $1.4 trillion in mid-September 2019, as the Federal Reserve normalized its balance sheet. This decline came to a halt in September 2019 when the Federal Reserve responded to turmoil in short-term money markets, with reserves fluctuating around $1.6 trillion in the early months of 2020. Then, in response to the COVID-19 pandemic, the Federal Reserve dramatically expanded its balance sheet, both directly, through outright purchases and repurchase agreements, and indirectly, as a consequence of the facilities to support market functioning and the flow of credit to the real economy. In this post, we characterize the increase in reserves between March and June 2020, describing changes to the distribution and concentration of reserves.
In March, with the outbreak of the COVID-19 pandemic in the United States, the market for municipal securities was severely stressed: mutual fund redemptions sparked unprecedented selling of municipal securities, yields increased sharply, and issuance dried up. In this post, we describe the evolution of municipal bond market conditions since the onset of the COVID-19 crisis. We show that conditions in municipal markets have improved significantly, in part a result of the announcement and implementation of several Federal Reserve facilities. Yields have decreased substantially, mutual funds have received significant inflows, and issuance has rebounded. These improvements in municipal market conditions help ensure that state and local governments have better access to funding for critical capital investments.