A Plucking Model of Business Cycles

May 29, 2020

By Stéphane Dupraz, Emi Nakamura and Jón Steinsson


In standard models, economic activity fluctuates symmetrically around a “natural rate” and stabilization policies can dampen these fluctuations but do not affect the average level of activity. An alternative view–labeled the “plucking model” by Milton Friedman–is that economic fluctuations are drops below the economy’s full potential ceiling. If this view is correct, stabilization policy, by dampening these fluctuations, can raise the average level of activity. We show that the dynamics of the unemployment rate in the US display a striking asymmetry that strongly favors the plucking model: increases in unemployment are followed by decreases of similar amplitude, while the amplitude of the increase is not related to the amplitude of the previous decrease. We develop a microfounded plucking model of the business cycle. The source of asymmetry in our model is downward nominal wage rigidity, which we embed in an explicit search model of the labor market. Our search framework implies that downward nominal wage rigidity is consistent with optimizing behavior and equilibrium. In our plucking model, stabilization policy lowers average unemployment and thereby yields sizable welfare gains.

Interesting take at business cycle asymmetries, and one that makes a much better use of “potential GDP” than other models.


Can Pandemic-Induced Job Uncertainty Stimulate Automation?

May 27, 2020

By Sylvain Leduc and Zheng Liu


The COVID-19 pandemic has raised concerns about the future of work. The pandemic may become recurrent, necessitating repeated adoptions of social distancing measures (voluntary or mandatory), creating substantial uncertainty about worker productivity. But robots are not susceptible to the virus. Thus, pandemic-induced job uncertainty may boost the incentive for automation. However, elevated uncertainty also reduces aggregate demand and reduces the value of new investment in automation. We assess the importance of automation in driving business cycle dynamics following an increase in job uncertainty in a quantitative New Keynesian DSGE framework. We find that, all else being equal, job uncertainty does stimulate automation, and increased automation helps mitigate the negative impact of uncertainty on aggregate demand.

Are the robots going to take over? It all depends how you define a robot, at least in this kind of modelling. Leduc and Liu view them as perfect substitutes for labor without its imperfections, such as catching a virus. However, robots can also catch a virus, be poorly qualified for particular jobs, or be difficult to move to another location. In other words, they face the same kind of frictions that are valid for the human workforce. With this in mind, they are not a miracle solution, and there is substantial uncertainty from investing in them.

Dynamic Beveridge Curve Accounting

May 11, 2020

By Hie Joo Ahn and Leland Crane


We develop a dynamic decomposition of the empirical Beveridge curve, i.e., the level of vacancies conditional on unemployment. Using a standard model, we show that three factors can shift the Beveridge curve: reduced-form matching efficiency, changes in the job separation rate, and out-of-steady-state dynamics. We find that the shift in the Beveridge curve during and after the Great Recession was due to all three factors, and each factor taken separately had a large effect. Comparing the pre-2010 period to the post-2010 period, a fall in matching efficiency and out-of-steady-state dynamics both pushed the curve upward, while the changes in the separations rate pushed the curve downward. The net effect was the observed upward shift in vacancies given unemployment. In previous recessions changes in matching efficiency were relatively unimportant, while dynamics and the separations rate had more impact. Thus, the unusual feature of the Great Recession was the deterioration in matching efficiency, while separations and dynamics have played significant, partially offsetting roles in most downturns. The importance of these latter two margins contrasts with much of the literature, which abstracts from one or both of them. We show that these factors affect the slope of the empirical Beveridge curve, an important quantity in recent welfare analyses estimating the natural rate of unemployment.

This is a pretty clever use of a standard model to decompose the Beveridge Curve, i.e., the dynamics of unemployment and vacancies. I would not have thought that matching efficiency would be have been an issue in the Great Recession, given that the underlying issue was financial.

Dollar invoicing, global value chains, and the business cycle dynamics of international trade

May 6, 2020

By David Cook and Nikhil Patel


Recent literature has highlighted that international trade is mostly priced in a few key vehicle currencies, and is increasingly dominated by intermediate goods and global value chains (GVCs). Taking these features into account, this paper reexamines the business cycle dynamics of international trade and its relationship with monetary policy and exchange rates. Using a three country dynamic stochastic general equilibrium (DSGE) framework, it finds key differences between the response of final goods and GVC trade to both internal and external shocks. In particular, the model shows that in response to a dollar appreciation triggered by a US interest rate increase, direct bilateral trade between non-US countries contracts more than global value chain oriented trade which feeds US final demand. We use granular data on GVC at the sector level to document empirical evidence in favor of this prediction.

Few people may appreciate that, but this papers brings back memories from my dissertation and shortly thereafter. Back then, I was working on international real business cycles and wrote separate papers on asymmetries (with a three-country model), exchange rate fluctuations, and the importance of intermediate goods. How things have evolved since, now papers integrate all three without difficulty! Nice!