Could Noise Spectra of Strange Attractors Better Explain Wealth and Income Inequalities? Evidence from the S&P-500 Index ()
ABSTRACT
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.
Share and Cite:
Dominique, C. (2018) Could Noise Spectra of Strange Attractors Better Explain Wealth and Income Inequalities? Evidence from the S&P-500 Index.
Modern Economy,
9, 449-462. doi:
10.4236/me.2018.93030.
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