Silviase/jgov_v1.4_full_ann huggingface dataset:
## Abstract

This paper examines the value of Japanese biomedical patents filed for 1991–2002, both before and after the introduction of the TLO Act in 1998 and the Japanese Bayh-Dole Act in 1999. We use forward citations to measure the value of the patents. Adjusting the heterogeneity of propensity to cite by subsequent patents in 19 major biomedical fields per year, we employ panel regressions controlling a fixed effect of the first assignee. Our main findings are as follows: (1) patents filed by a corporation and joint applications by corporations are highly valued; (2) if a corporation is the first assignee, a patent with a government co-assignee is highly valued; (3) although the value of government patents is not very impressive, it has risen since the pro-patent policies; and (4) there is no significant change in the value of university patents before and after the Japanese Bayh-Dole Act.

Key words: biomedical research, patent value, pro-patent policy, government research institute, university

JEL Classification No: L65, O34, O38

Kenta Nakamura (Corresponding author)

Graduate School of Commerce and Management, Hitotsubashi University

Naka, 2-1 Kunitachi, Tokyo 186-8601, JAPAN

and Japan Society for the Promotion of Science

Phone: 81-(0)42-580-8182 Fax: 81-(0)42-580-8184

k-nakamura@sage.ocn.ne.jp

Yosuke Okada

Graduate School of Economics, Hitotsubashi University

Naka, 2-1 Kunitachi, Tokyo 186-8601, JAPAN

yookada@econ.hit-u.ac.jp

Akira Tohei

Fair Trade Commission of Japan

6-B building, Chuo Godo Chosha, 1-1-1 Kasumigaseki,

Chiyodaku, Tokyo 100-8987, JAPAN

Akira_Tohei@jftc.go.jp
### 1. Introduction

The amount of money that the Japanese government spends on biomedical research has dramatically increased since the latter half of the 1990s, reflecting the growing prevalence of opinions emphasizing the role of the public sector in research $ ^{1} $ . At the same time, the Japanese government has actively promoted pro-patent policies with the intention of advancing research collaboration among industries, universities, and governments and facilitating the commercialization of their research outcomes. Regrettably, however, primarily due to data constraints, very few solid empirical studies have been conducted on the research performance of the Japanese public sector per se $ ^{2} $ .

The present study is focused on exploring the following two questions: (i) Did Japanese pro-patent policy measures that were introduced in the latter half of the 1990s encourage the public sector to file valuable patents? (ii) Are the values of corporate patents positively associated with the presence of co-assignees, especially when the co-assignees belong to the public sector, such as government research institutes and universities? We examine these policy questions by utilizing patent statistics on biomedical research $ ^{3} $ . Since there is a close association between producing scientific knowledge in biomedical research and implementing the knowledge in commercialization, and because patenting is one of the most effective tools for securing privately appropriable knowledge of biotechnologies, patent statistics would prove to be a beneficial source of information on the role of the public sector and its research collaboration with the private sector in the commercialization of the research outcome.

After the enactment of the Basic Law on Science and Technology in 1995, there was a wave of legislations that encouraged collaborative research among industries, governments, and universities. Table 1 provides a list of the policy initiatives. Several legislative measures in this list are emulated from relevant U.S. policies, such as the Bayh-Dole Act and the Small Business
Innovation Research (SBIR) program. From among the policy initiatives mentioned in Table 1, the following two legislative measures are deserving of attention in this study because it is expected that they have a wide and profound effect on patenting activity and technology transactions in the public sector.

## [INSERT TABLE 1 AROUND HERE]

First, the Law on the Promotion of Technology Licensing by Universities etc. (hereafter, “the TLO Act”), enacted in 1998, states that the government should support technology licensing organizations (TLOs) of universities and government research institutes. In addition, these institutes should obtain the partial remission of patent fees, and the licensees from the approved TLOs by the government may be given government investment under certain conditions.

Second, the Law on the Special Measures for Revitalizing Industrial Activities (hereafter, “the Japanese Bayh-Dole Act”) was enacted in 1999; this act specifies Bayh-Dole provisions in Sections 30–33, such as permission to retain patents to inventions derived from publicly funded research as well as exclusive licensing of state-owned patents $ ^{4} $ . These provisions generated considerable interest among Japanese policy makers in emulating the Bayh-Dole Act of 1980 in the U.S., which is widely credited with stimulating significant growth in industry-university-government technology transfer and research collaboration.

At first glance, the TLO Act and the Japanese Bayh-Dole Act appear to have had significant effects on the way in which public sector researchers produce privately appropriable research outcomes. As will be discussed in detail in the following sections, patenting by both government research institutes and universities has exploded since the introduction of these two policy measures $ ^{5} $ . In addition, the number of patent applications that were jointly filed by both private and public sector researchers also significantly increased from 1998.

However, the incentive to patent by public sector researchers would be arguably very different from that by private sector researchers. As Argyres and Liebeskind (1998) indicate, the commercialization of government/university research would be hampered because of the historic commitment to create and sustain “intellectual commons” for the public at large. The informal, free flow of knowledge between public and private sectors may be an important
source of social benefit. Patenting may thereby inhibit the diffusion of scientific knowledge, which has been christened by Heller and Eisenberg (1998) as the “the tragedy of anticommons.”

The effect of pro-patent policies on both public and private R&D has been the focus of recent empirical studies (Henderson et al., 1998; Mowery et al., 2001; Hall and Ziedonis, 2001; Agrawal and Henderson, 2002; Mowery et al., 2002; Thursby and Thursby, 2002; Mowery and Ziedonis, 2002; Owen-Smith and Powell, 2002; Owen et al., 2002; Lanjouw and Schankerman, 2004a; Mowery and Sampat, 2005; Hall, 2005; Murray and Stern, 2005; and others). These studies provoke, to a greater or lesser extent, a cautious view toward pro-patent policies and toward the Bayh-Dole-like measure in particular.

For example, Mowery and Sampat (2005) convincingly argue that efforts at emulating the Bayh-Dole policy are likely to have a modest success rate at best, without greater attention being paid to the underlying structural differences among the higher education systems. Mowery and Sampat (2005, p.123) also suggest that the emulated Bayh-Dole policies by OECD countries, including Japan, “ignore one of the central justifications for Bayh-Dole, i.e., that government ownership of publicly funded inventions impedes their commercialization.”

In a related vein, Cohen et al. (1998), Cohen et al. (2002a, b), Agrawal and Henderson (2002), Walsh and Cohen (2004), and Murray and Stern (2005), among others, suggest that in the U.S., the channels of open science, such as publications, conferences, informal communications, and consulting, are the primary and important methods of transmitting scientific knowledge, as compared to patents and licenses. These studies emphasize that the informal flow of knowledge between universities and industries is essential and that patenting may play other roles such as defending against infringement litigation and obtaining bargaining chips in licensing negotiations.

Almost all Japanese universities and government research institutes are predominantly funded by the government and are tightly controlled by vertically divided bureaucracy $ ^{6} $ . Contrary to the case in the U.S., Japanese public sector researchers have to abide by strict office regulations that are virtually similar to those for civil servants. In addition, academic culture such as open science and priority-first sentiments seems to be endemic among public sector researchers. Concomitantly, it was very unlikely for Japanese public sector researchers to file patents until very recently (Odagiri and Goto, 1993; Odagiri, 1999; Kneller, 2003; Walsh and Cohen, 2004). Therefore, not only the number of patents but also the value of these patents filed by the public sector researchers, especially those patents that had been increasingly applied for since the introduction of the pro-patent policy, would deserve to be closely examined as a proxy
for the effectiveness of the policy initiatives, translating their work into privately appropriable knowledge.

We use citation counts by subsequent patents (i.e., forward citations) as the patent value measure. Following Jaffe and Lerner (2001) and Hall, Jaffe, and Trajtenberg (2002), we adjust the heterogeneity concerning propensity to cite by subsequent patents in 19 major biomedical fields per year. In other words, we construct a weighted citation count (normalized forward citation intensity) that is defined by the difference between the actual number of citations received per patent and the reference citation intensity in each technology field, every year.

We employ several panel regressions, controlling for the individual effect of the first assignee of a patent and using the normalized citation counts as the dependent variable. Our main findings are as follows: (1) patents filed by a corporation as well as jointly filed patents by no less than two corporations are highly valued on average; (2) if a corporation is the first assignee, a patent with a government co-assignee is highly valued on average; (3) although the value of government patents is not very impressive, this value has risen since the introduction of the pro-patent policy; and (4) there is no significant change in the value of university patents before and after the Japanese Bayh-Dole Act. These findings may reflect the fact that the pro-patent policy in Japan is only now beginning to have some impact on the patenting activity of government research institutes. On the other hand, the findings do not appear to dictate the patenting behavior of university researchers. We are of the opinion that the institutional and organizational features of government research institutes and universities are keys to elucidate the salient responses between these institutes. Japanese universities may not yet accommodate themselves to patenting biomedical research outcomes despite the introduction of several facilitating policy measures in the late 1990s.

The rest of the paper is structured as follows. Section 2 describes data sources, technology classification, and assignee name matching. Section 3 lays out the empirical formulation. Section 4 provides a brief summary of our patent data in terms of technology class, assignee type, and industry classification. Section 5 explains the variable constructions. Section 6 provides summary statistics for selected variables; Section 7 presents empirical findings, and Section 8 concludes the paper.

### 2. Data Construction

#### 2.1. Retrieval of Patent Data

We utilized several patent databases. First, we retrieved biomedical patents from the Derwent Innovation Index (DII) and the Derwent World Patent Index (DWPI) (Thomson ISI) by using 19 search equations that are defined by the Japan Patent Office (JPO) (2003). The search equations
define 19 biomedical fields non-exclusively, by using a combination of International Patent Classifications (IPC) and key technical terms of the relevant technological categories $ ^{7} $ . Table 2 shows summary descriptions of these 19 biotechnology fields. We believe that these categories cover a broad range of technology fields associated with biomedical research.

## [INSERT TABLE 2 AROUND HERE]

The patent retrieval procedure is as follows: the date of the search is March 1, 2004; the priority country is Japan; the priority date is from 1 January 1991 to the date of the search. Then, using several kind codes $ ^{8} $ , we matched the patents with the IIP Patent Database (the Institute of Intellectual Property). The IIP Patent Database provides accurate information on the Japanese assignees because it is based on the original digitized database (Seiri-Hyojunka Database) compiled by the JPO. Moreover, patent documents from the IIP Patent Database are described in Japanese, which greatly alleviated our efforts in identifying assignee names, as will be explained in detail in the following section.

By using the above-mentioned search procedure, we retrieved 30 938 patents with the following items: application number, application date, designated state, IPC, assignee name, patent country, kind code, patent number, priority country, priority date, publication date, forward citations, backward citations, and equivalent patents (i.e., “Derwent family”) $ ^{9} $ . Then, we re-examined the priority information, assignee names, and priority country of each patent and excluded irrelevant or erroneous data. The dataset that remained comprised 30 350 patents. In addition, if an assignee belonged to a particular industry, we checked whether or not that assignee was a listed company by using the Japan Development Bank (JDB) Database and the Japan Bioindustry Association (JBA) Annual Report.

#### 2.2. Assignee Name Matching

Assignee names in the Derwent patent data were provided in English, and unfortunately, were not accurate enough to infer the relevant Japanese assignee names (in some cases, the data were quite erroneous and misleading). Thus, we had to match the English assignee names with their corresponding Japanese names. First, we matched the first assignee with, if any, other co-assignees. Second, we retrieved the Japanese assignee names (written in Japanese) from the
IIP Patent Database and matched them with the DII/DWPI patent data by using several types of patent numbers and kind codes. We then supplemented the remaining missing assignee names by using the Intellectual Property Digital Library (IPDL) offered by the JPO. After time-consuming exploration, we identified 5 352 distinct assignees of the 30 350 patents in which the number of the first assignee was 3 577. We adopted original assignee names at the date of patent filing to avoid arbitrary aggregation or disaggregation of assignee names because there were many applicants that had undergone M&A, a company split, or a change in assignee name or institutional affiliation.

#### 2.3. Classification of Assignee Types

Pro-patent policies, including the Japanese Bayh-Dole Act in 1999 and the TLO Act in 1998, are mainly intended for the public sector, which includes government research institutes and universities. The main aim of the present study is to detect the effect of these policy measures; therefore, we need to clearly distinguish private sector patents (mainly corporate patents) from public sector patents (i.e., government patents and university patents).

We classified all the assignees into one of the following types: corporations (corp), government research institutes (gov), universities (univ), individuals, and other types of assignees such as private foundations and public associations. If individual assignees have their own institutional affiliations, their true affiliations are often suppressed in patent documents under the Japanese patent filing routine. Thus, we had to search for the original affiliations of all the individual assignees by using the Yahoo! and Google search engines. Subsequently, we reclassified the patents that were filed by individual patentees into the above-mentioned three types of assignees to the greatest possible extent.

Moreover, we classified the combinations of co-assignees if they amounted to two or more. As will be explained in the next section, we distinguished between the first assignee and other co-assignees of a patent in order to control for a possible first-assignee fixed effect on patent values in regressions. First, if no less than two co-assignees are corporations and there are no other co-assignees belonging to universities and government research institutes, the patents filed for by those co-assignees were denoted as $ corp\_corp $ . Second, we denote an industry-government patent as $ corp1\_gov $ if a corporation is the first assignee of a patent and at least one co-assignee is a government research institute and there are no other co-assignees belonging to universities. Similarly, we denote a patent as $ gov1\_corp $ if a government research institute is the first assignee and at least one co-assignee is a corporation and there are no other co-assignees belonging to universities. Finally, we denote an industry-university patent as $ corp1\_univ $ if a corporation is the first assignee and at least one co-assignee is a university and there are no other co-assignees belonging to government research institutes. Similarly, we
denote a patent as $ univ1\_corp $ if a university is the first assignee and at least one co-assignee is a corporation and there are no other co-assignees belonging to government research institutes $ ^{10} $ .

After time-consuming data exploration, we exclusively identified all the first assignees and co-assignees of 30 350 patents as follows: corp (21 664 patents), gov (1 611), univ (995), corp_corp (1 420), corp1_gov (323), gov1_corp (536), corp1_univ (636), univ1_corp (460), individuals (727), private foundations and public associations (1 350), and others (628).

### 3. Empirical Formulation: “Fixed Effect” Approach

We treat a first-assignee individual effect that is possibly associated with patent values. The first assignee of a patent may be the main inventor or solely the main contributor to the research fund. There may not be a significant reason for the sequence of co-assignees, and we have no additional information regarding the reasons for the order of these co-assignees. However, there are also no reasons for negating the fact that the first assignee would be the principal co-assignee. Therefore, we control for a possible “unobservable” fixed effect for the first assignee in regressions. In other words, our basic model for estimation is

$$ Y_{i(t),j}=c_{j}+X_{i(t),j}\alpha+D_{i(t)}^{C}\beta+D_{i(t)}^{G}\gamma+D_{i(t)}^{U}\delta+D99_{i(t)}\times(D_{i(t)}^{G}\varsigma+D_{i(t)}^{U}\xi)+u_{i(t),j}, $$

where $ Y_{i(t),j} $ is a “normalized” forward citation intensity of a patent i filed in year t by the first assignee j. The column vector $ X_{i(t),j} $ represents the impact of individual patent characteristics on patent values. $ D99_{i(t)} $ is an indicator variable that takes on the value of unity if the priority year of patent i is 1999 or later, otherwise zero. $ u_{i(t),j} $ is an error term. This specification essentially exploits cross-sectional variations of the pooled observations of patents that are filed by the first assignee of a patent across the years. The inclusion of individual effect $ c_{j} $ controls for all the “unobserved” individual characteristics of the first assignee. In other words, $ c_{j} $ captures all the attributes of the first assignee that do not vary across patents, such as innovative capacity and institutional capability of an in-house legal section $ ^{11} $ . Estimates of the parameters of interest are based entirely on the cross-sectional variation between $ Y_{ijt} $ and assignee type dummies $ D_{i(t)} $ s.
$ D_{i(t)} $ s represent row vectors of assignee type dummies of patent i in year t. A superscript of $ D_{i(t)} $ represents a particular assignee type. Therefore, if a patent is filed by at least one corporation and there are no other co-assignees belonging to the public sector, we denote the row vector of the indicator variables as $ D_{i(t)}^{C} $ . On the other hand, if a patent is filed by at least one government research institute and there are no other co-assignees belonging to universities, we denote the row vector of the indicator variables as $ D_{i(t)}^{G} $ . In a similar manner, if a patent is filed by at least one university and there are no other co-assignees belonging to a government research institute, we denote the row vector of the indicator variables as $ D_{i(t)}^{U} $ . To be more precise, we define them as follows:

$$ D_{i(t)}^{C}=(corp_{i(t)},corp_{-}corp_{i(t)}) $$

$$ D_{i(t)}^{G}=(gov_{i(t)},gov1_{-}corp_{i(t)},corp1_{-}gov_{i(t)}) $$

$$ D_{i(t)}^{U}=(u n i v_{i(t)},u n i v1\_{c} o r p_{i(t)},c o r p1\_{u} n i v_{i(t)}). $$

By using these indicator variables, we examine the effect of a particular assignee type on the patent value. Under a fixed effect specification of the first assignee, a coefficient of the dummy variables in fact evaluates the impact of the relevant assignee type on the patent values compared to the “average” value of all the patents with the same first assignee type. For example, a coefficient of $ corp_{i(t)} $ indicates the impact of a corporate assignee without co-assignees from either governments or universities, compared with the average patent value of all corporate patents. In a similar manner, a coefficient of $ gov1\_corp_{i(t)} $ indicates the impact of the first assignee of a government with a corporation as a co-assignee, compared with the average patent value of all government patents. Thus, the first assignee type of a patent is an essential factor of our empirical specification.

We explore the impact of the pro-patent policy for the public sector on patent values by using several cross terms between a year dummy $ (D99_{i(t)}) $ and assignee type dummies for the public sector. In other words, we include the cross terms of a year dummy $ D99_{i(t)} $ with both $ D_{i(t)}^{G} $ and $ D_{i(t)}^{U} $ .

### 4. Basic Facts about Japanese Biomedical Patents

In this section, we summarize some basic facts about Japanese biomedical patents, which would