[I-S] A Fractal Comparison of Real and Austrian Business Cycle Models

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http://paws.wcu.edu/mulligan/www/FractalRBC.htm

A Fractal Comparison of Real and Austrian Business Cycle Models

 

Robert F. Mulligan, Ph.D.

Department of Business Computer Information Systems & Economics

Western Carolina University

College of Business

Cullowhee, North Carolina 28723

Phone: 828-227-3329

Fax: 828-227-7414

Email: mulligan@wcu.edu

 

Acknowledgements

Robert F. Mulligan is associate professor of economics in the Department of Business Computer Information Systems and Economics at Western Carolina University College of Business and a research associate of the State University of New York at Binghamton.  Thanks are due to Patrick Hays of the Department of Accounting, Finance, and Entrepreneurship for the program performing Lo's modified R/S test for stochastic dependence.  Helpful comments from Patrick Hays, Steve Henson, Steven Miller, and Michael Smith, are gratefully acknowledged.  The author retains responsibility for any errors or omissions.

 

Abstract

This paper examines macromonetary data for fractal character and stochastic dependence.  Lo's modified R/S test for stochastic dependence is used to explore the data's fractal properties along with five fractal analysis techniques for estimating the Hurst exponent, Mandelbrot-Lévy characteristic exponent, and fractal dimension.  Techniques employed are rescaled-range analysis, power-spectral density analysis, roughness-length analysis, the variogram or structure function method, and wavelet analysis.  Monthly data is analyzed over the 1959-2006 range and a quarterly dataset extending from 1947-2006 is also examined.  Strong evidence is found for stochastic dependence in the monetary aggregates, which suggests an activist monetary policy, and for nominal consumption expenditures, supporting Austrian business cycle theory.  No evidence for stochastic dependence in investment productivity is found, and this finding is invariant to whether productivity ratios are adjusted to account for credit expansion.

 

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