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Labor income and predictable stock returns

Author: Tano Santos; Pietro Veronesi; National Bureau of Economic Research.
Publisher: Cambridge, MA. : National Bureau of Economic Research, ©2001.
Series: Working paper series (National Bureau of Economic Research), no. 8309.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Database:WorldCat
Summary:
Abstract: We propose and test a novel economic mechanism that generates stock return predictability on both the time series and the cross section. In our model, investors' income has two sources, wages and dividends, that grow stochastically over time. As a consequence, the fraction of total income produced by wages changes over time de-pending on economic conditions. We show that as this fraction fluctuates, the  Read more...
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Details

Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Tano Santos; Pietro Veronesi; National Bureau of Economic Research.
OCLC Number: 47244203
Notes: "May 2001."
Description: 1 online resource (51, [6] pages) : illustrations.
Series Title: Working paper series (National Bureau of Economic Research), no. 8309.
Responsibility: Tano Santos, Pietro Veronesi.

Abstract:

Abstract: We propose and test a novel economic mechanism that generates stock return predictability on both the time series and the cross section. In our model, investors' income has two sources, wages and dividends, that grow stochastically over time. As a consequence, the fraction of total income produced by wages changes over time de-pending on economic conditions. We show that as this fraction fluctuates, the risk premium that investors require to hold stocks varies as well. We test the main implications of the model and find substantial support for it. A regression of stock returns on lagged values of the labor income to consumption ratio produces statistically significant coefficients and adjusted R2 's that are larger than those generated when using the dividend price ratio. Tests of the cross sectional implication find considerable improvements on the performance of both the conditional CAPM and CCAPM when compared to their unconditional counterparts.

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