J. Huston McCulloch
452 Arps Hall
1945 N. High St.
Areas of Expertise
- Term Structure of Interest Rates
- Stable Probability Distributions
- Money and Banking
- Adaptive Learning
- California Institute of Technology B.S. in Economics with Honors, June 1967
- Ph.D., University of Chicago Department of Economics, June 1973
J. Huston McCulloch is Professor of Economics at the Ohio State University, where he also holds an appointment with the Department of Finance. He was formerly at Boston College, has been a Faculty Research Fellow at the National Bureau of Economics Research, and served as Editor of the Journal of Money, Credit and Banking from 1983-1991.
Dr. McCulloch’s primary research interests center on money, banking and macroeconomic fluctuations, and extend to related financial and econometric issues. He is an internationally recognized authority on the term structure of interest rates, heavy-tailed stable probability distributions, and Austrian utility theory. He is the author of the book Money and Inflation: A Monetarist Approach and has published articles in the American Economic Review, the Journal of Political Economy, the Quarterly Journal of Economics, the Journal of Monetary Economics, the Journal of Finance, Computation in Statistics, the Bulletin of the London Mathematical Society, the Zeitschrift fÃ¼r NationalÃ¶konomie, andTennessee Anthropologist. His diverse research has received over 1000 indexed citations.
Dr. McCulloch’s recently published research include a survey of financial applications of stable distributions in the Handbook of Statistics, a critique (with Min-Teh Wu) of the Diamond-Dybvig deposit insurance model, and two papers on statistical aspects of global warming. His ongoing research, often with doctoral students, involves testing his 1981 Misintermediation hypothesis of macroeconomic fluctuations with newly available real term structure data from Treasury Inflation-Protection Securities (with Kevin Guo), an extended Neyman Goodness-of-Fit test (with E. Richard Percy), option pricing with log-stable distributions (with Seung-Hwan Lee), skew-Student probability distributions (with Young-Il Kim), Moment Ratio estimation of autoregressive processes, an empirical implementation of Adaptive Learning (with Mark Longbrake), and a Bayesian approach to the calibration problem.