Division of the Humanities and Social Sciences California Institute of Technology Pasadena, California 91125 T Esting Dividend Signalling Models
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چکیده
This paper derives a key monotonicity property common to all dividend signalling models: the greater the rate that dividend income is taxed relative to capital gains income, the greater the value of information revealed by a given dividend, and hence the greater the associated excess return. This monotonicity condition is tested with robust non-parametric techniques. No evidence is found to support dividend signalling models. The same results are inconsistent with tax-based CAPM arguments. "'We are very grateful to Ray Farrow for his extensive help on the first three sections of the paper and for the very generous provision of his time to this project. \iVe also appreciate Jeff Strnad's comments and suggestions. The first author acknowledges support from the SSHRC. All errors remain our own. TESTING DIVIDEND SIGNALLING MODELS Dan Bernhardt and J. Fiona Robertson
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Peter Sokol-Hessner, Colin F. Camerer, and Elizabeth A. Phelps Division of the Humanities and Social Sciences (HSS), California Institute of Technology, Division of the Humanities and Social Sciences (HSS) and Computational and Neural Systems (CNS), California Institute of Technology, 1200 E. California Blvd., Pasadena, CA 91125, USA, and Department of Psychology, New York University, 6 Washing...
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