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Triadic citations, country biases and patent value: the case of pharmaceuticals

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Abstract

Triadic patents minimise home bias effects in studies that focus on patent counts as a measure of innovative activity. Yet, biases in qualitative patent indicators have been largely neglected. This article advocates that forward patent citations, and triadic citations in particular, can illuminate further on home bias, self citations, and the speed of knowledge flows for drug patents published by the USPTO for the period 1980–2008. The evidence shows that triadic citations help to minimize the home bias in citations as well as to make patent quality more transparent. Also, it indicates that self citations and the age distribution of citations are important factors to consider when explaining cross-country differences in pharmaceutical citations.

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Notes

  1. See Lanjouw and Schankerman (2004) and Hall et al. (2005) but also Sampat and Ziedonis (2004).

  2. For detailed reviews, see Jaffe and Trajtenberg (1999); Sampat and Ziedonis (2004); Maurseth and Verspagen (2002); Blind and Cremers (2009) and Li (2009).

  3. See Hall et al. (2001).

  4. For more details on the OECD database, see Dernis and Kahn (2004).

  5. Wang (2007), however, warns that triadic threshold does not always identify relatively high realised patent value.

  6. This is in terms of triadic counts with the set of countries also including Argentina, Austria, Belgium, Brazil, Czech Republic, Spain, Finland, Greece, Hungary, Ireland, Island, South Korea, Luxemburg, Mexico, Norway, New Zealand, Poland, Portugal, Slovakia, Turkey, India, China, Hong-Kong, Taiwan, Russia, the Soviet Union and South Africa. The total of 39 countries included added to 97% of all patents counts for pharmaceuticals.

  7. Estimates in all Figures are 2-year moving averages.

  8. The early period prior to 1985 was ignored for it was a transitional period when European patents were increasingly filed with the EPO away from national patents offices. On the other end of the timescale, citations analysis excludes patents granted since 2000 to limit the bias associated with the introduction of publication of patents applications prior to grant date (Hinze and Schmoch 2004).

  9. All continuous explanatory variables were centred prior to estimation which was by maximum likelihood using robust standard errors to address the impact of misspecification on dispersion. In contrast to the standard Poisson model, we employ an auxiliary logit regression that jointly estimates excess zeros. This regression uses backward 5-year citations, the triadic dummy variable and claims as explanatory factors. For details on the ZINB model, see Long (1997).

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Acknowledgment

I am grateful to Jason Nielsen for his valuable research assistance.

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  1. Centre for Strategic Economic Studies, Victoria University, Melbourne, Australia

    George Messinis

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  1. George Messinis
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Messinis, G. Triadic citations, country biases and patent value: the case of pharmaceuticals. Scientometrics 89, 813–833 (2011). https://doi.org/10.1007/s11192-011-0473-z

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