Decomposing Excess Returns in Stochastic Linear Models
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.
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References listed on IDEAS
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- Yun, Myeong-Su, 2003.
"Decomposing Differences in the First Moment,"
IZA Discussion Papers
877, Institute for the Study of Labor (IZA).
- Schwert, G William, 1981. "Using Financial Data to Measure Effects of Regulation," Journal of Law and Economics, University of Chicago Press, vol. 24(1), pages 121-158, April.
- Lin, Carl, 2011.
"Give Me Your Wired and Your Highly Skilled: Measuring the Impact of Immigration Policy on Employers and Shareholders,"
IZA Discussion Papers
5754, Institute for the Study of Labor (IZA).
- Carl Lin, 2011. "Give me your wired and your highly skilled: measuring the impact of immigration policy on employers and shareholders," Working Papers 2011/17, Institut d'Economia de Barcelona (IEB).
- Gerald G. Brown & Herbert C. Rutemiller, 1977. "Means and Variances of Stochastic Vector Products with Applications to Random Linear Models," Management Science, INFORMS, vol. 24(2), pages 210-216, October.
- Daniel A. Powers & Hirotoshi Yoshioka & Myeong-Su Yun, 2011. "mvdcmp: Multivariate decomposition for nonlinear response models," Stata Journal, StataCorp LP, vol. 11(4), pages 556-576, December.
- repec:uwp:jhriss:v:8:y:1973:i:4:p:436-455 is not listed on IDEAS
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