Decomposing Excess Returns in Stochastic Linear Models

15 Pages Posted: 31 Dec 2011

See all articles by Carl Lin

Carl Lin

Bucknell University; IZA Institute of Labor Economics

Abstract

We present a theorem helpful in estimating the mean and variance of a linear function with arbitrary multivariate randomness in its coefficients and variables. We derive a generalized decomposition result from two random linear functions in which the result can be applied to most models using event study analysis. Taking the 1989 minimum wage hike as an example, we found that the apparent lack of an effect is a consequence of two off-setting forces: 1) a negative effect arising from firm-specific traits and 2) a positive effect arising from market performance. In sum, we bring to the analysis a method that helps provide additional insights and can be applied to much of the work using event study.

Keywords: excess returns, minimum wage, decomposition, event study

JEL Classification: G14, J31, J38

Suggested Citation

Lin, Carl, Decomposing Excess Returns in Stochastic Linear Models. IZA Discussion Paper No. 6237, Available at SSRN: https://ssrn.com/abstract=1977823 or http://dx.doi.org/10.2139/ssrn.1977823

Carl Lin (Contact Author)

Bucknell University ( email )

1 Dent Drive
Lewisburg, PA 17837
United States

IZA Institute of Labor Economics ( email )

P.O. Box 7240
Bonn, D-53072
Germany

HOME PAGE: http://www.iza.org/profile?key=6255

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