Asani Sarkar



Once a bank grows beyond a certain size or becomes too complex and interconnected, investors often perceive that it is “too big to fail” (TBTF), meaning that if the bank were to fail, the government would likely bail it out. Following the global financial crisis (GFC) of 2008, the G20 countries agreed on a set of reforms to eliminate the perception of TBTF, as part of a broader package to enhance financial stability. In June 2020, the Financial Stability Board (FSB), a sixty-eight-member international advisory body set up in 2009, published the results of a year-long evaluation of the effectiveness of TBTF reforms. In this post, we discuss the main conclusions of the report—in particular, the finding that implicit funding subsidies to global banks have decreased since the implementation of reforms but remain at levels comparable to the pre-crisis period.

William Chen, Marco Del Negro, Keshav Dogra, Shlok Goyal, and Alissa Johnson

This post presents an update of the economic forecasts generated by the Federal Reserve Bank of New York’s dynamic stochastic general equilibrium (DSGE) model. We describe very briefly our forecast and its change since June 2020.

As usual, we wish to remind our readers that the DSGE model forecast is not an official New York Fed forecast, but only an input to the Research staff’s overall forecasting process. For more information about the model and variables discussed here, see our DSGE model Q & A. Note that interactive charts are now available for DSGE model forecasts.

In response to the pandemic, the New York Fed’s DSGE model has been modified because the economic disruptions caused by COVID-19 are likely different from standard business cycles. The model now includes additional shocks designed to reflect phenomena like lockdowns and social distancing (the model description on the GitHub page describes these changes in some detail). To incorporate the substantial uncertainty surrounding future economic activity, we construct three possible scenarios, described below, that differ in the projected severity of the pandemic and its effects on economic behavior. Our final forecast combines these individual scenarios by weighting them according to our a priori views on how likely each scenario is. The weights on the three scenarios are 80, 10, and 10 percent, respectively. We partly inform these views using the most recent (August) Survey of Professional Forecasters (SPF) probabilistic survey for year-over-year 2020 GDP growth.

Gizem Koşar, Rachel Pomerantz, and Wilbert van der Klaauw



The New York Fed’s Center for Microeconomic Data released results today from its August 2020 SCE Household Spending Survey and SCE Public Policy Survey. The former provides information on consumers' experiences and expectations regarding household spending, while the latter provides information on consumers' expectations regarding future changes for a wide range of fiscal and social policies and the potential impact of these changes on their households. These data have been collected every four months since December 2014 for the SCE Household Spending Survey and October 2015 for the SCE Public Policy Survey as part of the Survey of Consumer Expectations (SCE).

Rod Garratt, Michael Lee, and Aaron Plesset



Today, the majority of retail payments in the United States are digital. Practically all digital payments are tracked, collected, and aggregated by financial institutions, payment providers, and vendors. This trend has accelerated during the COVID-19 pandemic as payments that require physical contact, such as cash, have been discouraged. As cash gradually becomes obsolete, consumers are left with fewer alternatives for making private transactions. In this post, we outline some evidence on the impact of COVID-19 on consumer payment behavior and follow up in the second post in this Liberty Street Economics series with a look at the implications of cash obsolescence for privacy.

Rajashri Chakrabarti, Maxim Pinkovskiy, Will Nober, and Lindsay Meyerson



Does health insurance improve health? This question, while apparently a tautology, has been the subject of considerable economic debate. In light of the COVID-19 pandemic, it has acquired a greater urgency as the lack of universal health insurance has been cited as a cause of the profound racial gap in coronavirus cases, and as a cause of U.S. difficulties in managing the pandemic more generally. However, estimating the effect of health insurance is difficult because it is (generally) not assigned at random. In this post, we approach this question in a novel way by exploiting a natural experiment—the adoption of the Affordable Care Act (ACA) Medicaid expansion by some states but not others—to tease out the causal effect of a type of health insurance on COVID-19 intensity.

Anna Kovner and Antoine Martin




Any time the Federal Reserve or the official sector more broadly provides support to the economy during a crisis, the intervention raises concerns related to moral hazard. Moral hazard can occur when market participants do not bear the negative consequences of the risks they take. This lack of consequences can encourage even greater risks, due to the expectation of future government help. In this post, we consider the potential for moral hazard stemming from the official sector’s response to the coronavirus pandemic and explain why moral hazard concerns were likely more severe in 2008.

Anna Kovner and Antoine Martin




In the United States and other free market economies, the official sector typically has minimal involvement in market activities absent a clear rationale to justify intervention, such as a market failure. In this post, we consider arguments for official sector intervention, focusing on the market failure arising from externalities related to business closures. These externalities are likely to be particularly high for closures arising from pandemic-related economic disruptions. We discuss how the official sector, including institutions such as Congress and the Treasury, can increase social welfare by acting to minimize the fixed costs of business start-up and failure, including the costs associated with unemployment, beyond the level set by private markets alone.

Anna Kovner and Antoine Martin




The Federal Reserve’s response to the coronavirus pandemic has been unprecedented in its size and scope. In a matter of months, the Fed has, among other things, cut the federal funds rate to the zero lower bound, purchased a large amount of Treasury securities and agency mortgage‑backed securities (MBS) and, together with the U.S. Treasury, introduced several lending facilities. Some of these facilities are very similar to ones introduced during the 2007-09 financial crisis while others are completely new. In this post, we argue that the new facilities, while unprecedented, are a natural extension of the Fed’s toolkit, as they operate through similar economic mechanisms to prevent self-reinforcing bad outcomes. We also explain why these new facilities are particularly useful as part of the response to the pandemic, which is an economic shock very different from a financial crisis.

Rajashri Chakrabarti, Sebastian Heise, Davide Melcangi, Maxim Pinkovskiy, and Giorgio Topa



In our previous post, we looked at the effects that the reopening of state economies across the United States has had on consumer spending. We found a significant effect of reopening, especially regarding spending in restaurants and bars as well as in the healthcare sector. In this companion post, we focus specifically on small businesses, using two different sources of high-frequency data, and we employ a methodology similar to that of our previous post to study the effects of reopening on small business activity along various dimensions. Our results indicate that, much like for consumer spending, reopenings had positive and significant effects in the short term on small business revenues, the number of active merchants, and the number of employees working in small businesses. It is important to stress that we are not expressing any views in this post on the normative question of whether, when, or how states should loosen or tighten restrictions aimed at controlling the COVID-19 pandemic.

Rajashri Chakrabarti, Sebastian Heise, Davide Melcangi, Maxim Pinkovskiy, and Giorgio Topa

Editor’s note:  We have clarified the description of data used for the analysis since this post was first published (September 23, 5:27 p.m.)



The spread of COVID-19 in the United States has had a profound impact on economic activity. Beginning in March, most states imposed severe restrictions on households and businesses to slow the spread of the virus. This was followed by a gradual loosening of restrictions (“reopening”) starting in April. As the virus has re-emerged, a number of states have taken steps to reverse the reopening of their economies. For example, Texas and Florida closed bars again in June, and Arizona additionally paused operations of gyms and movie theatres. Taken together, these measures raise the question of how closures and reopenings affect consumer spending. In this post, we investigate how much consumer spending increased after the reopenings. It is important to stress that we are not expressing any views on the normative question of whether, when, or how states should loosen or tighten restrictions aimed at controlling the COVID-19 pandemic.