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Operating Leverage,Stock Market Cyclicality,and the Cross-Section of Returns

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  • François Gourio

    () (Department of Economics, Boston University)

Abstract

I use a putty-clay technology to explain several asset market facts. The key mechanism is as follows: a one percent increase in revenues leads to a more-than-one percent increase in profits, since labor costs don’t move one-for-one. This amplification is greater for plants with low productivity for which the average profit margin (revenue minus costs) is small. This “operating leverage” effect implies that low productivity plants benefit disproportionately from business cycle booms. These plants have thus higher systematic risk and higher average returns. This model can help explain the empirical findings of Fama and French (1992), and more generally the sources of differences in market betas across firms. I obtain supporting evidence for the mechanism using firm- and industry-level data. The aggregate effect follows from trend growth: low-productivity plants outnumber high-productivity plants, making the aggregate stock market procyclical. I examine these aggregate implications and find that this model generates a volatile stock market return that predicts the business cycle.

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Bibliographic Info

Paper provided by Boston University - Department of Economics in its series Boston University - Department of Economics - Working Papers Series with number WP2005-002.

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Length: 48 pages
Date of creation: Jan 2005
Date of revision:
Handle: RePEc:bos:wpaper:wp2005-002

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Cited by:
  1. John Cochrane, 2005. "Financial Markets and the Real Economy," NBER Working Papers 11193, National Bureau of Economic Research, Inc.
  2. Jo�o F. Gomes & Leonid Kogan & Motohiro Yogo, 2009. "Durability of Output and Expected Stock Returns," Journal of Political Economy, University of Chicago Press, vol. 117(5), pages 941 - 986.
  3. Erica X. N. Li & Dmitry Livdan & Lu Zhang, 2009. "Anomalies," Review of Financial Studies, Society for Financial Studies, vol. 22(11), pages 4301-4334, November.

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