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Cited by 817

The DOI matches its Crossref record.

Patents as Options: Some Estimates of the Value of Holding European Patent Stocks

Pakes, Ariel·1986·Econometrica

Abstract

In many countries holders of patents must pay an annual renewal fee in order to keep their patents in force. This paper uses data on the proportion of patents renewed, and the renewal fees faced by, post World War II cohorts of patents in France, the United Kingdom, and Germany, in conjunction with a model of patent holders' renewal decisions, to estimate the returns earned from holding patents in these countries. Since patents are often applied for at a nearly stage in the innovation process, the model allows agents to be uncertain about the sequence of returns that will be earned if the patent is kept inforce. Formally, then, the paper presents and solves a discrete choice optimal stochastic control model, derives the implications of the model on aggregate behaviour, and then estimates the parameters of the model from aggregate data. The estimates enable a detailed description of the evolution of the distribution of returns earned from holding patents over their life spans,and calculations of both; the annual returns earned from holding the patents still in force (or the patent stocks) in the alternative countries, and the distribution of the discounted value of returns earned from holding the patents in a cohort.

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Metadata

Authors
Pakes, A.
Venue
Econometrica
Publisher
JSTOR
Published
1986-07
Volume
54
Issue
4
Pages
755
ISSN
0012-9682 (ISSN-L)
OpenAlex
W1984509612
Cited by
817
References
0
FWCI
11.02
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Patents as Options: Some Estimates of the Value of Holding European Patent Stocks. https://app.cochat.ai/papers/10.2307/1912835
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Pakes, A. (1986). Patents as Options: Some Estimates of the Value of Holding European Patent Stocks. Econometrica. https://doi.org/10.2307/1912835

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.