Could Noise Spectra of Strange Attractors Better Explained Wealth and Income Inequalities? Evidence from the S&P-500 Index
C-Rene Dominique ()
MPRA Paper from University Library of Munich, Germany
SUMMARY: Inequity in wealth and income distributions is ubiquitous and persistent in markets economies. Economists have long suspected that this might be due to the workings of a power law. But studies in financial economics have focused mainly on tail exponent while attempting to recover the Pareto and Zipf’s laws. The estimation of tail exponents from log-log plots, as in stock market returns, produces biased estimators and has little impact on policy. This paper argues that economic time series are output signals of a multifractal process driven by strange attractors. Consequently, estimating noise spectra thrown-up by strange attractors stands to produce a much richer set of information, including the lower and upper bounds of unequal income distribution.
Keywords: noise spectra; singularity spectrum; correlation dimension; income distribution; fractal attractor; scale exponent. (search for similar items in EconPapers)
JEL-codes: G1 G14 (search for similar items in EconPapers)
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