Pablo Azar



During the COVID-19 pandemic, many industries adapted to new social distancing guidelines by adopting new technologies, providing protective equipment for their employees, and digitizing their methods of production. These changes in industries’ supply chains, together with monetary and fiscal stimulus, contributed to dampening the economic impact of COVID-19 over time. In this post, I discuss a new framework that analyzes how changes in supply chains can drive economic growth in the long run and mitigate recessions in the short run.

Florin Bilbiie, Gauti Eggertsson, Giorgio Primiceri, and Andrea Tambalotti



How will the U.S. economy emerge from the ongoing COVID-19 pandemic? Will it struggle to return to prior levels of employment and activity, or will it come roaring back as soon as vaccinations are widespread and Americans feel comfortable travelling and eating out? Part of the answer to these questions hinges on what will happen to the large amount of “excess savings” that U.S. households have accumulated since last March. According to most estimates, these savings are around $1.6 trillion and counting. Some economists have expressed the concern that, if a considerable fraction of these accumulated funds is spent as soon as the economy re-opens, the ensuing rush of demand might be destabilizing. This post argues that these savings are not that excessive, when considered against the backdrop of the unprecedented government interventions adopted over the past year in support of households and that they are unlikely to generate a surge in demand post-pandemic.

William Chen, Marco Del Negro, Shlok Goyal, Alissa Johnson, and Andrea Tambalotti

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. The model projects solid growth over the next two years, with core inflation slowly rising toward 2 percent. Uncertainty for both output and inflation forecasts remains large.

Jonathan McCarthy



The coronavirus pandemic and the various measures to address it have led to unprecedented convulsions to the U.S. and global economies. In this post, I examine those extraordinary impacts through the lens of personal consumption expenditures on discretionary and nondiscretionary services, a framework I developed in a 2011 post (and subsequently employed in 2012, 2014, and 2017). In particular, I show that there were exceptional declines in both services categories during the spring; their recoveries, however, have displayed notably different patterns in recent months, with nondiscretionary services expenditures nearly back to their prior level and discretionary services expenditures seemingly stalled well below their pre-pandemic peak.

William Chen, Marco Del Negro, 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 September 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.

Hunter L. Clark, Jeffrey B. Dawson, and Maxim Pinkovskiy



China’s economy was the first to be hit by the COVID-19 outbreak, the first to be locked down, and the first to begin an economic recovery. We examine the impact of the COVID-19 crisis on China’s GDP growth using a set of alternative growth indicators. Our analysis finds that China’s official GDP growth figures over the first three quarters of this year have been broadly in line with alternative indicators and that growth presently is staging a strong rebound and providing a boost to the global economy. However, this rebound faces potential headwinds in the forms of high levels of debt, declining return to capital accumulation, and a shrinking working-age population in China.

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.

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.

William Chen, Marco Del Negro, Michele Lenza, Giorgio Primiceri, and Andrea Tambalotti

U.S. inflation used to rise during economic booms, as businesses charged higher prices to cope with increases in wages and other costs. When the economy cooled and joblessness rose, inflation declined. This pattern changed around 1990. Since then, U.S. inflation has been remarkably stable, even though economic activity and unemployment have continued to fluctuate. For example, during the Great Recession unemployment reached 10 percent, but inflation barely dipped below 1 percent. More recently, even with unemployment as low as 3.5 percent, inflation remained stuck under 2 percent. What explains the emergence of this disconnect between inflation and unemployment? This is the question we address in “What’s Up with the Phillips Curve?,” published recently in Brookings Papers on Economic Activity.