Publications

Reconciling Hayek's and Keynes' Views of Recessions (2016)

with Paul Beaudry and Franck Portier    (forthcoming, Review of Economic Studies)

Abstract: Recessions often happen after periods of rapid accumulation of houses, consumer durables and business capital. This observation has led some economists, most notably Friedrich Hayek, to conclude that recessions often reflect periods of needed liquidation resulting from past over-investment. According to the main proponents of this view, government spending or any other form of aggregate demand policy should not be used to mitigate such a liquidation process, as doing so would simply result in a needed adjustment being postponed. In contrast, ever since the work of Keynes, many economists have viewed recessions as periods of deficient demand that should be countered by activist fiscal policy. In this paper we reexamine the liquidation perspective of recessions in a setup where prices are flexible but where not all trades are coordinated by centralized markets. The model illustrates why liquidations likely cause recessions characterized by deficient aggregate demand and accordingly suggests that Keynes' and Hayek's views of recessions may be closely linked. In our framework, interventions aimed at stimulating aggregate demand face a trade-off whereby current stimulus postpones the adjustment process and therefore prolongs the recessions, but where some stimulative policies may nevertheless remain desirable.

Is the Macroeconomy Locally Unstable and Why Should We Care?

with Paul Beaudry and Franck Portier  ,  NBER Macroeconomics Annual 31 (2016)

Abstract: In most modern macroeconomic models, the steady state (or balanced growth path) of the system is a local attractor, in the sense that, in the absence of shocks, the economy would converge to the steady state. In this paper, we examine whether the time series behavior of macroeconomic aggregates (especially labor market aggregates) is in fact supportive of this local-stability view of macroeconomic dynamics, or if it instead favors an alternative interpretation in which the macroeconomy may be better characterized as being locally unstable, with nonlinear deterministic forces capable of producing endogenous cyclical behavior. To do this, we extend a standard AR representation of the data to allow for smooth nonlinearities. Our main finding is that, even using a procedure that may have low power to detect local instability, the data provide intriguing support for the view that the macroeconomy may be locally unstable and involve limit-cycle forces. An interesting finding is that the degree of nonlinearity we detect in the data is small, but nevertheless enough to alter the description of macroeconomic behavior. We complete the paper with a discussion of the extent to which these two different views about the inherent dynamics of the macroeconomy may matter for policy.


Working Papers

Putting the Cycle Back into Business Cycle Analysis (2017)

with Paul Beaudry and Franck Portier

Abstract: Are business cycles mainly a response to persistent exogenous shocks, or are they the consequence of strong endogenous mechanism which produces recurrent boom-bust phenomena? We present new evidence in favor of the second interpretation, and find support for the somewhat extreme notion that business cycles may be generated by stochastic limit cycle forces. The three elements that tend to favor this interpretation of business cycles are: (i) slightly extending the frequency window one associates with business cycle, (ii) allowing for strategic complementarities across agents arising from financial frictions, (iii) allowing for a locally unstable steady state in estimation.

Misspecification and the Causes of Business Cycles (2015)

Abstract: Modern dynamic stochastic general equilibrium (DSGE) macroeconomics models generally feature several different exogenous shock processes. A standard tool in the quantitative macroeconomics toolbox for evaluating the individual importance of these shocks is a variance decomposition. The reliability of this tool depends importantly on having accurate estimates of the variances of the innovations to the exogenous shock processes. Using a novel framework, I show that when the DSGE model is misspecified and the shock variances are estimated using a likelihood-based approach, the resulting estimates are biased upward. Next, using the same framework, I propose a simple procedure to identify and partially correct for the effects of model misspecification on these variance estimates. As an example of its usefulness, I apply this procedure to a recent paper and find that it reduces the estimated variances of the shocks in the model by as much as a third of their respective naive estimates.

Can a Limit-Cycle Model Explain Business Cycle Fluctuations? (2014)

Abstract: In conventional models of the business cycle, all fluctuations are ultimately caused by the arrival of random shocks. As a result, individual booms and busts are largely unrelated phenomena. An alternative to this viewpoint is that booms and busts are inherently related, which suggests that fluctuations are at least in part driven by deterministic cyclical forces.This paper shows (1) how a purely deterministic general-equilibrium model can give rise to limit-cycle fluctuations, and (2) that this model can replicate business cycle features once it includes a small amount of exogenous variation. The deterministic limit cycle arises through a simple micro-founded mechanism in a rational-expectations environment, and does not rely on the existence of multiple equilibria or dynamic indeterminacy. Since these cycles would indefinitely repeat themselves in the absence of shocks, a TFP shock is introduced in order to create irregularities. The model is estimated to match US hours data, and is shown to be able to match the data closely. The TFP shock in the model is of a reasonable persistence and relatively small size, accounting for only around a fifth of the standard deviation of hours in the model. This highlights that models capable of generating deterministic fluctuations do not require the addition of large, persistent shocks in order to match patterns in the data, which is a common criticism of conventional models.