nep-ipr New Economics Papers
on Intellectual Property Rights
Issue of 2020‒10‒26
two papers chosen by
Giovanni Ramello
Università degli Studi del Piemonte Orientale “Amedeo Avogadro”

  1. Linguistic Metrics for Patent Disclosure: Evidence from University versus Corporate Patents By Nancy Kong; Uwe Dulleck; Adam Jaffe; Shupeng Sun; Sowmya Vajjala
  2. Examining Patent Examiners: Present Bias, Procrastination and Task Performance By Ryo Nakajima; Michitaka Sasaki; Ryuichi Tamura

  1. By: Nancy Kong; Uwe Dulleck; Adam Jaffe; Shupeng Sun; Sowmya Vajjala
    Abstract: Encouraging inventors to disclose new inventions is an important economic justification for the patent system, yet the technical information contained in patent applications is often inadequate and unclear. This paper proposes a novel approach to measure disclosure in patent applications using algorithms from computation allinguistics. Borrowing methods from the literature on second language acquisition, we analyze core linguistic features of 40,949 U.S. applications in three patent categories related to nanotechnology, batteries, and electricity from 2000 to 2019. Relying on the expectation that universities have more incentives to disclose their inventions than corporations for either incentive reasons or for different source documents that patent attorneys can draw on, we confirm the relevance and usefulness of the linguistic measures by showing that university patents are more readable. Combining the multiple measures using principal component analysis, we find that the gap in disclosure is 0.4 SD, with a wider gap between top applicants. Our results do not change after accounting for the heterogeneity of inventions by controlling for cited-patent fixed effects. We also explore whether one pathway by which corporate patents become less readable is use of multiple examples to mask the “best mode” of inventions. By confirming that computational linguistic measures are useful indicators of readability of patents, we suggest that the disclosure function of patents can be explored empirically in a way that has not previously been feasible.
    Keywords: patent disclosure, computational linguistic analysis, readability
    JEL: K11 O31 O34
    Date: 2020
  2. By: Ryo Nakajima (Faculty of Economics, Keio University); Michitaka Sasaki (Organization for Research Initiative and Promotion, Tottori University); Ryuichi Tamura (Faculty of International Studies and Regional Development, University of Niigata)
    Abstract: This paper explores the unproductive procrastination behavior of patent examiners, probes whether such behavior is caused by present-biased preferences, and estimates the magnitude. We set out a quasihyperbolic discounting model where a patent examiner is assigned a biweekly quota of patent application reviews and determines the level of effort by the deadline. We estimate the present-bias factor of each patent examiner based on patent prosecution data in the U.S. and find that the proportion of present-biased individuals exceeds the majority. We demonstrate that the job separation rate is higher for less present-biased patent examiners, and a fragmented work quota can improve patent examination quality and timeliness.
    Keywords: patent examination, procrastination, present bias, quasihyperbolic discounting
    JEL: D03 J01 K29 O34
    Date: 2020–09–19

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