The Spurious Relation between Inflation Uncertainty and Stock Returns: Evidence from the U.S
AbstractThe purpose of this paper is to reconsider the empirical evidence on the relation between inflation, inflation uncertainty, and stock returns. Two unprecedented proxies for inflation uncertainty are used. First, the power of inflation and inflation uncertainty to explain stock returns is compared. Both variables are separately negatively related to stock returns. However, when both are included together in the regressions, the inflation variable becomes redundant, meaning that its coefficient becomes statistically insignificantly different from zero. This means that inflation uncertainty dominates and supplants the effect of inflation. Second, this paper provides strong evidence that inflation uncertainty itself becomes redundant, and fails to explain stock returns, when two fundamental variables are included in the regressions. The two fundamental variables are the change in the cost of equity, and the growth rate of earnings. The first variable is roughly measured by the change in the baa and in the aaa corporate bond yields, while the second one is taken to be the rate of change of industrial production. The main conclusion of the paper is that both inflation and inflation uncertainty are not significantly related to stock returns when the two aforementioned fundamental variables are accounted for.
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Bibliographic InfoArticle provided by Better Advances Press, Canada in its journal Review of Economics & Finance.
Volume (Year): 3 (2013)
Issue (Month): (November)
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Find related papers by JEL classification:
- G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
- G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
- E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
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