  Objective: An understanding of when one or more external factors may
influence the evolution of innovation tracking indices (such as US patent and
trademark applications (PTA)) is an important aspect of examining economic
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)
to explore the LRD using overlapping time windows to quantify long-memory
dynamics in the monthly PTA time-series spanning 1977 to 2016.
Results/Discussion: The CHE is found to increase in a clear S-curve pattern,
achieving persistence (H~1) from non-persistence (H~0.5). For patents, the
inflection occurred over a span of 10 years (1980-1990), while it was much
sharper (3 years) for trademarks (1977-1980). Conclusions/Originality/Value:
This analysis suggests (in part) that the rapid augmentation in R&D expenditure
and the introduction of the various patent directed policy acts (e.g.,
Bayh-Dole, Stevenson-Wydler) are the key impetuses behind persistency, latent
in PTA. The post-1990s exogenic factors seem to be simply maintaining the high
degree and consistency of the persistency metric. These findings suggest
investigators should consider latent persistency when using these data and the
CHE may be an important tool to investigate the impact of substantive exogenous
variables on growth dynamics.
