Tracking Reserve Ampleness in Real Time Using Reserve Demand Elasticity
As central banks shrink their balance sheets to restore price stability and phase out expansionary programs, gauging the ampleness of reserves has become a central topic to policymakers and academics alike. The reason is that the ampleness of reserves informs when to slow and then stop quantitative tightening (QT). The Federal Reserve, for example, implements monetary policy in a regime of ample reserves, whereby the quantity of reserves in the banking system needs to be large enough such that everyday changes in reserves do not cause large variations in short-term rates. The goal is therefore to implement QT while ensuring that reserves remain sufficiently ample. In this post, we review how to gauge the ampleness of reserves using the new Reserve Demand Elasticity (RDE) measure, which will be published monthly on the public website of the Federal Reserve Bank of New York as a standalone product.
The Central Banking Beauty Contest
Expectations can play a significant role in driving economic outcomes, with central banks factoring market sentiment into policy decisions and market participants forming their own assumptions about monetary policy. But how well do central banks understand the expectations of market participants—and vice versa? Our model, developed in a recent paper, features a dynamic game between (i) a monetary authority that cannot commit to an inflation target and (ii) a set of market participants that understand the incentives created by that credibility problem. In this post, we describe the game, a type of Keynesian beauty contest: its main novelty is that each side attempts, with varying degrees of accuracy, to forecast the other’s beliefs, resulting in new findings regarding the levels and trajectories of inflation.
A New Set of Indicators of Reserve Ampleness
The Federal Reserve (Fed) implements monetary policy in a regime of ample reserves, where short-term interest rates are controlled mainly through the setting of administered rates, and active management of the reserve supply is not required. In yesterday’s post, we proposed a methodology to evaluate the ampleness of reserves in real time based on the slope of the reserve demand curve—the elasticity of the federal (fed) funds rate to reserve shocks. In this post, we propose a suite of complementary indicators of reserve ampleness that, jointly with our elasticity measure, can help policymakers ensure that reserves remain ample as the Fed shrinks its balance sheet.
When Are Central Bank Reserves Ample?
The Federal Reserve (Fed) implements monetary policy in a regime of ample reserves, whereby short-term interest rates are controlled mainly through the setting of administered rates. To do so, the quantity of reserves in the banking system needs to be large enough that everyday changes in reserves do not cause large variations in the policy rate, the so-called federal funds rate. As the Fed shrinks its balance sheet following the plan laid out by the Federal Open Market Committee (FOMC) in 2022, how can it assess when to stop so that the supply of reserves remains ample? In the first post of a two-part series, based on the methodology developed in our recent Staff Report, we propose to assess the ampleness of reserves in real time by estimating the slope of the reserve demand curve.
On the Distributional Consequences of Responding Aggressively to Inflation
This post discusses the distributional consequences of an aggressive policy response to inflation using a Heterogeneous Agent New Keynesian (HANK) model. We find that, when facing demand shocks, stabilizing inflation and real activity go hand in hand, with very large benefits for households at the bottom of the wealth distribution. The converse is true however when facing supply shocks: stabilizing inflation makes real outcomes more volatile, especially for poorer households. We conclude that distributional considerations make it much more important for policy to take into account the tradeoffs between stabilizing inflation and economic activity. This is because the optimal policy response depends very strongly on whether these tradeoffs are present (that is, when the economy is facing supply shocks) or absent (when the economy is facing demand shocks).
On the Distributional Effects of Inflation and Inflation Stabilization
This post and the next discuss the distributional effects of inflation and inflation stabilization through the lenses of a theoretical model—a Heterogeneous Agent New Keynesian (HANK) model. This model combines the features of New Keynesian models that have been the workhorse for monetary policy analysis since the work of Woodford (2003) with inequality in wealth and income at the household level following the seminal contribution of Kaplan, Moll, and Violante (2018). We find that while inflation hurts everyone, it hurts the poor in particular. When the source of inflation is a supply shock, fighting inflation aggressively hurts the poor even more, however, while the opposite is true for demand shocks, as discussed in the companion post.
Can Discount Window Stigma Be Cured?
One of the core responsibilities of central banks is to act as “lender of last resort” to the financial system. In the U.S., the Federal Reserve has been operating as a lender of last resort through its “discount window” (DW) for more than a century. Historically, however, the DW has been plagued by stigma—banks’ reluctance to use the DW, even for benign reasons, out of concerns that it could be interpreted as a sign of financial weakness. In this post, we report on new research showing that once a DW facility is stigmatized, removing that stigma is difficult.
Dropping Like a Stone: ON RRP Take‑up in the Second Half of 2023
Take-up at the Overnight Reverse Repo Facility (ON RRP) has halved over the past six months, declining by more than $1 trillion since June 2023. This steady decrease follows a rapid increase from close to zero in early 2021 to $2.2 trillion in December 2022, and a period of relatively stable balances during the first half of 2023. In this post, we interpret the recent drop in ON RRP take-up through the lens of the channels that we identify in our recent Staff Report as driving its initial increase.
The New York Fed DSGE Model Perspective on the Lagged Effect of Monetary Policy
This post uses the New York Fed DSGE model to ask the question: What would have happened to interest rates, output, and inflation had the Federal Reserve been following an average inflation targeting (AIT)-type reaction function since 2021:Q2, when inflation began to rise—as opposed to keeping the federal funds rate at the zero lower bound (ZLB) until March 2022, and then raising it aggressively thereafter? We show that actual policy was more accommodative in 2021 than implied by the AIT reaction function and then more contractionary in 2022 and beyond. On net, the lagged effect of monetary policy on the level of GDP, when measured relative to the counterfactual, has been positive throughout the forecast horizon, due to the initial boost associated with keeping the fed funds rate near zero in 2021.
A Bayesian VAR Model Perspective on the Lagged Effect of Monetary Policy
Over the last few years, the U.S. economy has experienced unusually high inflation and an unprecedented pace of monetary policy tightening. While inflation has fallen recently, it remains above target, and the economy continues to expand at a robust pace. Does the resilience of the U.S. economy imply that monetary policy has been ineffectual? Or does it reflect that policy acts with “long and variable lags” and so we haven’t yet observed the full effect of the monetary tightening that has already taken place? Using a Bayesian vector autoregressive (BVAR) model, we show that economic activity has, indeed, been substantially stronger than would have been anticipated considering the rapid policy tightening. Still, the model expects a significant slowdown in 2024-25, even though short-term interest rates are forecasted to fall.