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Industrial Electricity Usage and Stock Returns

Published online by Cambridge University Press:  08 February 2017

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Abstract

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The growth rate of industrial electricity usage predicts future stock returns up to 1 year with an R2 of 9%. High industrial electricity usage today predicts low stock returns in the future, consistent with a countercyclical risk premium. Industrial electricity usage tracks the output of the most cyclical sectors. Our findings bridge a gap between the asset pricing literature and the business cycle literature, which uses industrial electricity usage to gauge production and output in real time. Industrial electricity growth compares favorably with traditional financial variables, and it outperforms Cooper and Priestley’s output gap measure in real time.

Type
Research Article
Copyright
Copyright © Michael G. Foster School of Business, University of Washington 2017 

Footnotes

1 We thank Hendrik Bessembinder (the editor), Tom Cosimano, Bjorn Eraker, Wayne Ferson, Ravi Jagannathan, Bill McDonald, Stavros Panageas, Jesper Rangvid, Marco Rossi, Raman Uppal, Annette Vissing-Jorgensen, Jason Wei, Xiaoyan Zhang, and an anonymous referee for helpful comments. We thank Manisha Goswami, Steve Hayes, Dongyoup Lee, and Liang Tan for data support. Any errors are our own.

References

Baker, M., and Wurgler, J.. “Investor Sentiment and the Cross-Section of Stock Returns.” Journal of Finance, 51 (2006), 16451680.Google Scholar
Bansal, R., and Yaron, A.. “Risks for the Long Run: A Potential Resolution of Asset Pricing Puzzles.” Journal of Finance, 59 (2004), 14811509.CrossRefGoogle Scholar
Belo, F., and Yu, J.. “Government Investment and the Stock Market.” Journal of Monetary Economics, 60 (2013), 325339.Google Scholar
Boudoukh, J.; Richardson, M.; and Whitelaw, R.. “The Myth of Long-Horizon Predictability.” Review of Financial Studies, 21 (2008), 15771605.CrossRefGoogle Scholar
Burnside, C.; Eichenbaum, M.; and Rebelo, S.. “Capacity Utilization and Returns to Scale.” NBER Macroeconomics Annual, 1995 (1995), 67110.Google Scholar
Burnside, C.; Eichenbaum, M.; and Rebelo, S.. “Sectoral Solow Residuals.” European Economic Review, 40 (1996), 861869.Google Scholar
Campbell, J. Y.Consumption-Based Asset Pricing.” In Handbook of the Economics of Finance, Vol. IB, Constantinides, G., Harris, M., and Stulz, R., eds. Amsterdam, Netherlands: North-Holland (2003), 803887.Google Scholar
Campbell, J. Y., and Cochrane, J. H.. “By Force of Habit: A Consumption-Based Explanation of Aggregate Stock Market Behavior.” Journal of Political Economy, 107 (1999), 205251.CrossRefGoogle Scholar
Campbell, J. Y., and Thompson, S.. “Predicting the Equity Premium Out of Sample: Can Anything Beat the Historical Average?Review of Financial Studies, 21 (2008), 15091531.CrossRefGoogle Scholar
Charoenrook, A.“Does Sentiment Matter?” Working Paper, Vanderbilt University (2003).Google Scholar
Cochrane, J. H.Production-Based Asset Pricing and the Link between Stock Returns and Economic Fluctuations.” Journal of Finance, 46 (1991), 209237.Google Scholar
Cochrane, J. H.The Dog That Did Not Bark: A Defense of Return Predictability.” Review of Financial Studies, 21 (2008), 15331575.Google Scholar
Comin, D., and Gertler, M.. “Medium-Term Business Cycles.” American Economic Review, 96 (2006), 523551.Google Scholar
Cooper, I., and Priestley, R.. “Time-Varying Risk Premiums and the Output Gap.” Review of Financial Studies, 22 (2009), 28012833.Google Scholar
Da, Z.; Yang, W.; and Yun, H.. “Household Production and Asset Prices.” Management Science, 62 (2016), 387409.CrossRefGoogle Scholar
Fama, E., and French, K.. “Business Conditions and Expected Returns on Stocks and Bonds.” Journal of Financial Economics, 25 (1989), 2349.CrossRefGoogle Scholar
Ferreira, M. A., and Santa-Clara, P.. “Forecasting Stock Market Returns: The Sum of the Parts Is More than the Whole.” Journal of Financial Economics, 100 (2011), 514537.Google Scholar
Ferson, W., and Lin, J.. “Alpha and Performance Measurement: The Effects of Investor Heterogeneity.” Journal of Finance, 69 (2014), 15651596.Google Scholar
Fisher, K., and Statman, M.. “Consumer Confidence and Stock Returns.” Journal of Portfolio Management, 30 (2003), 115127.CrossRefGoogle Scholar
Hodrick, R. J.Dividend Yields and Expected Stock Returns: Alternative Procedures for Inference and Measurement.” Review of Financial Studies, 5 (1992), 357386.Google Scholar
Jorgenson, D. W., and Griliches, Z.. “The Explanation of Productivity Change.” Review of Economic Studies, 34 (1967), 249283.Google Scholar
King, R. G., and Rebello, S.. “Resuscitating Real Business Cycles.” In Handbook of Macroeconomics, Taylor, J. and Woodford, M., eds. Amsterdam, Netherlands: North-Holland (2000), 9271007.Google Scholar
Lamont, O.Investment Plans and Stock Returns.” Journal of Finance, 55 (2000), 27192745.CrossRefGoogle Scholar
Lettau, M., and Ludvigson, S.. “Consumption, Aggregate Wealth, and Expected Returns.” Journal of Finance, 55 (2001), 815849.CrossRefGoogle Scholar
Lettau, M., and Ludvigson, S.. “Euler Equation Errors.” Review of Economic Dynamics, 12 (2009), 255283.CrossRefGoogle Scholar
Lettau, M., and Ludvigson, S.. “Measuring and Modeling Variation in the Risk-Return Trade-Off.” In Handbook of Financial Econometrics, Ait-Sahalia, Y. and Hansen, L., eds. Amsterdam, Netherlands: North-Holland (2010), 617690.CrossRefGoogle Scholar
Li, E. X. N.; Livdan, D.; and Zhang, L.. “Anomalies.” Review of Financial Studies, 22 (2009), 43014334.Google Scholar
Li, Y.; Ng, D. T.; and Swaminathan, B.. “Predicting Market Returns Using Aggregate Implied Cost of Capital.” Journal of Financial Economics, 110 (2013), 419436.CrossRefGoogle Scholar
Lin, X., and Zhang, L.. “The Investment Manifesto.” Journal of Monetary Economics, 60 (2013), 351366.Google Scholar
Liu, L. X.; Whited, T. M.; and Zhang, L.. “Investment-Based Expected Stock Returns.” Journal of Political Economy, 117 (2009), 11051139.Google Scholar
Ludvigson, S.Consumer Confidence and Consumer Spending.” Journal of Economic Perspectives, 18 (2004), 2950.Google Scholar
Lustig, H., and van Nieuwerburgh, S.. “Housing Collateral, Consumption Insurance, and Risk Premia: An Empirical Perspective.” Journal of Finance, 60 (2005), 11671219.Google Scholar
McGrattan, E., and Schmitz, J.. “Maintenance and Repair: Too Big to Ignore.” Federal Reserve Bank of Minneapolis Quarterly Review, 23 (1999), 213.Google Scholar
Moller, S. V., and Rangvid, J.. “End-of-the-Year Economic Growth and Time-Varying Expected Returns.” Journal of Financial Economics, 115 (2015), 136154.Google Scholar
Newey, W. K., and West, K. D.. “A Simple, Positive Semi-Definite, Heteroskedasticity and Autocorrelation Consistent Covariance Matrix.” Econometrica, 55 (1987), 703708.Google Scholar
Pena, I. J.; Restoy, F.; and Rodriguez, R.. “Can Output Explain the Predictability and Volatility of Stock Returns?Journal of International Money and Finance, 21 (2002), 163182.Google Scholar
Rangvid, J.Output and Expected Returns.” Journal of Financial Economics, 81 (2006), 595624.Google Scholar
Rapach, D., and Zhou, G.. “Forecasting Stock Returns.” In Handbook of Economic Forecasting, Elliott, G. and Timmermann, A., eds. Amsterdam, Netherlands: North-Holland (2013), 328383.Google Scholar
Santos, T., and Veronesi, P.. “Labor Income and Predictable Stock Returns.” Review of Financial Studies, 19 (2006), 144.Google Scholar
Stambaugh, R. F.Predictive Regressions.” Journal of Financial Economics, 54 (1999), 375421.CrossRefGoogle Scholar
Welch, I., and Goyal, A.. “A Comprehensive Look at the Empirical Performance of Equity Premium Prediction.” Review of Financial Studies, 21 (2008), 14551508.CrossRefGoogle Scholar
Zhang, L.The Value Premium.” Journal of Finance, 60 (2005), 67103.Google Scholar