Learning, capital-embodied technology and aggregate fluctuations

Görtz, C. and Tsoukalas, J. (2013) Learning, capital-embodied technology and aggregate fluctuations. Review of Economic Dynamics, 16(4), pp. 708-723. (doi:10.1016/j.red.2012.04.003)

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Publisher's URL: http://dx.doi.org/10.1016/j.red.2012.04.003

Abstract

Recent cyclical episodes in the U.S. and G-7 economies are asymmetric: recoveries and expansions tend to be long and gradual and busts tend to be short and sharp. A large body of work views the two recent cyclical U.S. episodes, namely, the “new economy” boom in the late 1990s, and the 2000s housing boom-bust as episodes where over-optimistic beliefs have played a significant role. These episodes have revived interest in expectations driven business cycles models. However, previous work in this area has not addressed the important asymmetry feature of business cycles. This paper takes a step towards addressing this limitation of expectations driven business cycle models. We propose a generalization of the Greenwood et al. (1988) model with vintage capital and learning about capital embodied productivity and show it can deliver fluctuations that are asymmetric as in the U.S. data. Learning, calibrated to match the procyclical forecast precision from the Survey of Professional Forecasters, is crucial for the modelʼs ability to generate asymmetries. Forecast errors generated by the model are shown to trigger recessions that mimic in magnitude, duration and depth the typical post WW II U.S. recession.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Tsoukalas, Professor John
Authors: Görtz, C., and Tsoukalas, J.
College/School:College of Social Sciences > Adam Smith Business School > Economics
Journal Name:Review of Economic Dynamics
ISSN:1094-2025
Published Online:04 May 2012

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