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.

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.

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.

William Chen, Marco Del Negro, Ethan Matlin, and Reca Sarfati

Editor’s note: The release of the March 2020 DSGE forecast was postponed as New York Fed economists shifted their focus to the COVID-19 pandemic. In conjunction with the release of the June 2020 forecast, we’ve decided to post the March 2020 forecast for the record as well.

Ozge Akinci, William Chen, Marco Del Negro, Ethan Matlin, and Reca Sarfati

Editor’s note: The release of the March 2020 DSGE forecast was postponed as New York Fed economists shifted their focus to the COVID-19 pandemic. With the June 2020 forecast now out, we’ve decided to post this forecast for the record as well.


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 December 2019. 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.

William Chen, Marco Del Negro, Ethan Matlin, Reca Sarfati, 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. We describe very briefly our forecast and its change since September 2019. 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.

Ozge Akinci, William Chen, Marco Del Negro, Ethan Matlin, and Reca Sarfati

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 2019. 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.

Michael Cai, Marco Del Negro, Edward Herbst, Ethan Matlin, Reca Sarfati, and Frank Schorfheide

The estimation of dynamic stochastic general equilibrium (DSGE) models is a computationally demanding task. As these models change to address new challenges (such as household and firm heterogeneity, the lower bound on nominal interest rates, and occasionally binding financial constraints), they become even more complex and difficult to estimate—so much so that current estimation procedures are no longer up to the task. This post discusses a new technique for estimating these models which belongs to the class of sequential Monte Carlo (SMC) algorithms, an approach we employ to estimate the New York Fed DSGE model. To learn more, check out this paper of ours.

Sushant Acharya, Michael Cai, Marco Del Negro, Ethan Matlin, and Reca Sarfati

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 January 2019. 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.

Michael Cai, Marco Del Negro, Ethan Matlin, and Reca Sarfati

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 October 2018. 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.