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In recent years there has been a lot of interest in the effect of income inequality (heterogeneity) on the economy, from both academics and policymakers. Researchers have developed Heterogeneous Agent New Keynesian (HANK) models that incorporate heterogeneity and uninsurable idiosyncratic risk into the New Keynesian models that have become a cornerstone of monetary policy analysis. This research has argued that heterogeneity and idiosyncratic risk change many features of New Keynesian models – the
transmission of conventional monetary policy, the forward guidance puzzle, fiscal multipliers, the efficacy of targeted transfers and automatic stabilizers, among others. However, the source of the difference between HANK and representative agent New Keynesian (RANK) models remains unclear. This is because HANK models are typically not analytically tractable, leaving it unclear what exactly is driving the results. To shed light on the macroeconomic consequences of heterogeneity, we develop a stylized HANK model that contains key features present in more complicated HANK models.
Large firms play an integral role in aggregate economic activity owing to their size and production linkages. Events specific to these large firms can thus have significant effects on the macroeconomy. Quantifying these effects is tricky, however, given the complexity of the production process and the difficulty in identifying firm-level events. The recent pause in Boeing’s 737 MAX production is a striking example of such an event or “shock” to a large firm. This post applies a basic framework that is grounded in economic theory to provide a back-of-the envelope calculation of how the “737 MAX shock” could impact U.S. GDP growth in the first quarter of 2020.
In our previous post, we presented evidence suggesting that labor market indicators provide the most reliable information for dating the U.S. business cycle. In this post, we further develop the case. In fact, the unemployment rate has provided an almost perfect record of distinguishing the beginning of recessions in the post-war U.S. economy. We also show that using more granular labor market data, such as by region or industry, also provides valuable information about the state of the business cycle.
The study of the business cycle—fluctuations in aggregate economic activity between times of widespread expansion and contraction—is one of the foremost pursuits in macroeconomics. But even distinguishing periods of expansion and recession can be challenging. In this post, we discuss different conceptual approaches to dating the business cycle, study their past performance for the U.S. economy, and highlight the informativeness of labor market indicators.
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.
Matthew Higgins, Thomas Klitgaard, and Michael Nattinger
Tariffs are a form of taxation. Indeed, before the 1920s, tariffs (or customs duties) were typically the largest source of funding for the U.S. government. Of little interest for decades, tariffs are again becoming relevant, given the substantial increase in the rates charged on imports from China. U.S. businesses and consumers are shielded from the higher tariffs to the extent that Chinese firms lower the dollar prices they charge. U.S. import price data, however, indicate that prices on goods from China have so far not fallen. As a result, U.S. wholesalers, retailers, manufacturers, and consumers are left paying the tax.
Richard K. Crump, David O. Lucca, and Casey McQuillan
Inventory investment plays a central role in business cycle fluctuations. This post examines whether inventory investment amplifies or dampens economic fluctuations following a tightening in financial conditions. We find evidence supporting an amplification mechanism. This analysis suggests that inventory accumulation will be a drag on economic activity this year but provide a boost in 2020.
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.
Liberty Street Economics features insight and analysis from New York Fed economists working at the intersection of research and policy. Launched in 2011, the blog takes its name from the Bank’s headquarters at 33 Liberty Street in Manhattan’s Financial District.
The editors are Michael Fleming, Andrew Haughwout, Thomas Klitgaard, and Asani Sarkar, all economists in the Bank’s Research Group.
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