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Author: Miguel Henry

Articles by: Miguel Henry
Dr. Henry is an Economist at Greylock McKinnon Associates and specializes in econometrics and industrial organization. After receiving his PhD in Economics from Washington State University - School of Economic Sciences, Dr. Henry has worked on issues related to workers compensation, health insurance and employment. He currently works on econometric issues related to market power and product market definition in Pharmaceutical Antitrust private litigation cases. Dr. Henry also worked at the Economic Research Service – USDA enhancing the analytical usefulness of the Nielsen Homescan panel data and conducting economic research investigating household purchase dynamics for dietary fiber. He has taught undergraduate and graduate econometrics at the University of Oklahoma and Washington State University. Dr. Henry also holds a MS in Statistics from Washington State University - Math Department.
Dec 11 by Miguel Henry Posted in Econometrics, Time Series

Permutation Entropy
Permutation Entropy (PE) is a robust time series tool which provides a quantification measure of the complexity of a dynamic system by capturing the order relations between values of a time series and extracting a probability distribution of the ordinal patterns (see Henry and Judge, 2019). Today, we will learn about the PE methodology and will demonstrate its use through a toy example.

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