Before revision: Understanding the dynamics of patents and trademarks is a key aspect of tracking innovative progress/ egress. This paper empirically explores the chronological Hurst exponent (CHE) , an approach that calculates the Hurst exponent over an increasing duration of time windows to quantify long-memory dynamics , in the monthly numbers of United States patent and trademark applications from 1977 to 2016.
After revision: Understanding the dynamics of patents and trademarks is a key aspect of tracking innovative progress/ regress. Using exploratory statistics, the analysis uses a novel tool to leverage the long-range dependency (LRD) intrinsic to PTA to resolve when such factor(s) may have caused significant disruptions in the evolution of the indices, and thus give insight into substantive economic growth dynamics. Approach: This paper explores the use of the Chronological Hurst Exponent (CHE) , an approach that calculates the Hurst exponent over an increasing duration of time windows to quantify long-memory dynamics , in the monthly numbers of United States patent and trademark applications from 1977 to 2016.