Trademark filings and patent application count time series are structurally near-identical and cointegrated: Implications for studies in innovation
Iraj Daizadeh

TL;DR
This study demonstrates that trademark filings and patent applications are structurally similar, cointegrated, and exhibit synchronized long-term dynamics, implying a close relationship that supports their joint use in innovation research.
Contribution
It provides empirical evidence of the structural and cointegration relationship between trademarks and patents over 40 years, extending the understanding of their interconnectedness in innovation studies.
Findings
Trademark and patent time series are structurally similar.
They are cointegrated, indicating a long-term equilibrium.
Structural breaks occur simultaneously, suggesting common external influences.
Abstract
Through time series analysis, this paper empirically explores, confirms and extends the trademark/patent inter-relationship as proposed in the normative intellectual-property (IP)-oriented Innovation Agenda view of the science and technology (S&T) firm. Beyond simple correlation, it is shown that trademark-filing (Trademarks) and patent-application counts (Patents) have similar (if not, identical) structural attributes (including similar distribution characteristics and seasonal variation, cross-wavelet synchronicity/coherency (short-term cross-periodicity) and structural breaks) and are cointegrated (integration order of 1) over a period of approximately 40 years (given the monthly observations). The existence of cointegration strongly suggests a "long-run" equilibrium between the two indices; that is, there is (are) exogenous force(s) restraining the two indices from diverging from…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsIntellectual Property and Patents · Innovation Diffusion and Forecasting · scientometrics and bibliometrics research
