Hitotsubashi University
Institute of Innovation Research

The Screening Function of International Search
Authorities under the Patent Cooperation Treaty:
Evidence from the Japanese Government s Policy
Change in 1999

Okada, Yoshimi
IIR Working Paper WP#20-13

July 2020

Institute of Innovation Research
Hitotsubashi University
Tokyo, Japan
http://www.iir.hit-u.ac.jp

The Screening Function of International Search Authorities under the Patent
Cooperation Treaty: Evidence from the Japanese Government’s Policy Change in
1999
Yoshimi OkadaaaHitotsubashi University, Institute of Innovation Research, 2-1 Naka, Kunitachi, Tokyo
186-8601, Japan.
July 20, 2020
Abstract
This article examines the screening function of the International Searchauthorities, which produce International Search Reports (ISRs) forinternational patent applications filed under the Patent Cooperation Treaty. It
first reveals that the patent examination policy change from quantity-oriented
to quality-oriented by the Patent Office of the Japanese government in 1999
increased the number of references cited in ISRs significantly. It uses thisunexpected drastic policy change as an instrument for the quality of ISRs
and finds that the effect of improving the quality of ISRs on the applicant’s
decision to enter the national/regional phase procedure is significant,resulting in decrease in the entrance rates, by four percent for the UnitedStates national phase procedure and six percent for European regional phaseprocedure. Thus, the examination policy change made the information
provided by ISRs on prior art become significantly more useful to applicants(e.g., more findings of unexpected prior art) and thus enhanced the screening
function of ISRs significantly. The estimated coefficients of improving thequality of ISRs are more than ten times larger than those estimated by using
the ordinary least squares method (OLS), showing that the endogeneity of
examiner’s citations with respect to the patenting value is so significant thatit leads to substantial underestimations by using the OLS.
Keywords: Screening; International Search Report; Patent Cooperation Treaty; prior art
search; quality of patent examination; patent examination policy change
JEL classification: O34, O38, K29

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Highlights
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Japan’s patent examination policy became quality-oriented in 1999.
Quality-oriented patent examination caused a significant rise in search quality.
Significant effect of quality improvement in prior art search on applicants.
A rise in International Search Report quality enhanced the screening function.
Japan’s policy change contributed to an efficient global patent examination system.

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1. Introduction
There are two alternative ways in which to obtain a foreign patent. The first way is to
file a patent application directly to a foreign patent authority. The second way is to filean international patent application to the patent authority of the applicant’s own country
under the Patent Cooperation Treaty (PCT) and designate the countries or regions inwhich he/she wants to obtain patents as the “designated countries.” Under the first
approach, a patent applicant must file a patent application, written in the foreign
language, to the foreign patent authority within 12 months of the original patentapplication date if he/she wants to hold the priority right. By contrast, under the PCTinternational patent filing system, an applicant can postpone the due date of submitting
the translation to the foreign patent authorities as late as 30 months after the priority
date 1. Further, the applicant is provided with an International Search Report (ISR) by an
International Search Authority (ISA) 2, which enables him/her to estimate the possible
scope of the patent right as well as the possibility of acquiring a patent, assess whether
to bear the additional cost including the cost of translating the application documents
into the foreign language(s), and screen out applications of little value. This study
focuses on this screening function of an ISA and ISRs.
From the viewpoint of global patent examination authorities, the PCT system
offers two advantages for increasing the efficiency of global patent examination. The
first is that patent examination authorities can use the prior art information cited in ISRs
to examine PCT patent applications under their respective subsequent examination
procedures, which they call “national phase” or “regional phase.” The Trilateral Patent
Offices (i.e., the European Patent Office (EPO), the Japan Patent Office (JPO), and theUnited States Patent and Trademark Office (USPTO)) have investigated the utility of
ISRs, confirming that they are beneficial to patent authorities that examine PCT patentapplications entering the national/regional phase, although the details are not publicly
available (Trilateral Patent Offices, 2001, 2002). The second advantage is that thescreening function of the ISAs and the ISRs reduces the number of patent applications
that each patent authority must examine since applicants do not submit the translation(s)of some PCT applications and those applications do not enter the national/regional
phases.
According to WIPO (WIPO, 2020 and WIPO, 2015a), the number of PCT
applications filed globally in 2019 was around 266,000, about triple the 93,000
1There was a legal change in the PCT system in 2003. Before 2004, the due date was 20 months
from the priority date.
2 The objective of the international search is “to discover relevant prior art” and the ISA “endeavors
to discover as much of the relevant prior art as its facilities permit” (15.01 of (WIPO, 2015b)).
3

applications filed in 2000 and more than 10 times the 20,000 applications filed in 1990.
In 2019, Japanese residents filed 52,700 PCT applications, more than five times the
9,600 applications filed in 2000 and more than 30 times the 1,700 applications filed in
1990. Thus, the use of the PCT system has been increasing significantly in the past three
decades to become the main route for obtaining foreign patents. This trend has meantthat it is now increasingly important to enhance the screening function of ISA’s and
ISR’s to maximize the efficiency of the global patent examination system.
Despite the importance of an ISA’s and an ISR’s screening function, no priorstudy, to the best of my knowledge, has addressed this matter. Based on this gap in the
body of knowledge on this topic, this article reveals the significance of the information
provided by ISRs to applicants and investigates whether improving the quality of ISRs
affects applicants’ decision to enter the national/regional procedure. However,investigating the effects of the quality of ISRs on applicants’ decision is challenging fortwo main reasons.
The first difficulty is that there is no established way of measuring the qualityof ISRs. In 1999, the examination policy of the JPO veered suddenly fromquantity-oriented to quality-oriented 3, which led to a dramatic rise in the number ofcitations in the ISRs that deny the patentability of filed inventions. Based on this finding,the quality of ISRs is quantified by measuring the number of cited documents that deny
the novelty or inventive step of at least one of the claims. 4
The second difficulty is the problem of endogeneity. My hypothesis is that the
number of citations made by an examiner in an ISR to deny the patentability of the filed
inventions, which serves as a proxy for the quality of an ISR, affects negatively theapplicant’s decision to enter the national/regional phase procedure. However, because
the number of the examiner’s backward citations is positively correlated with theeconomic value of the patent (Allison et al., 2003; Harhoff et al., 2003) and theeconomic value affects positively the applicant’s decision to enter the national/regional
phase procedure in designated countries, the coefficient of the number of examiner
citations estimated by using the ordinary least squares (OLS) method is likely to bepositively biased (that is, smaller in absolute values). In addition, other factors are
assumed to affect the applicant’s decision, such as the possible obsolescence of theinvention and an applicant’s ex-post discovery of prior art after filing a PCT application,
both of which might be correlated positively with the number of the examiner’s

3

Because the policy was not well publicized, the precise date is unknown.
The scope of exclusive right is defined in “claims” of patent application documents. An
application usually contains two or more claims.

4

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backward citations and negatively affect the decision to enter the national/regional
phase.
Fortunately to perform an empirical study, the policy change made by the JPO
in 1999 was not announced in advance and was not well publicized even afterward. Thechange, therefore, did not affect the quality of patent applications immediately after thechange, but rather provided an exogenous shock to the citations in the ISRs. This article,
hence, exploits this exogenous shock as an instrumental variable for the quality of ISRs
to investigate the research question posed above.
In the past decade, governments in major countries have been emphasizing on
the importance of the quality of patents in order to promote innovation. In 2013, theEconomic and Scientific Advisory Board of the EPO, for instance, recommended
improving the patent system and highlighted the importance of patent quality inboosting innovation. In Japan, the Cabinet decided in July 2014 to aim to achieve thehighest quality patent examination in the world through several measures including the
introduction of an objective quality management system. In 2015, the USPTO launched
its “Enhanced Patent Quality Initiative,” which consists of comprehensive measures toimprove patent examination. In 2016, the United States Government Accountability
Office (USGAO) recommended that the USPTO define quality and strengthen searchcapabilities (USGAO, 2016a, 2016b). Thus, it has been one of the top priority tasks forthese patent offices to provide high quality patent examinations.
One of the most important factors that affect patent examination quality is theextent of the comprehensiveness of prior art search (Federal Trade Commission, 2003;
Jaffe & Lerner, 2004; Merrill et al., 2004; USGAO, 2013, 2016a). To the best of myknowledge, no empirical study, however, has thus far provided evidence for the tangible
effect of improving the quality of prior art search on the outcome of patentexaminations.
The major findings of this study can be summarized as follows. The JPO’s
drastic examination policy change from quantity-oriented to quality-oriented in August
1999 led to a dramatic rise in the number of several types of documents cited in ISRs.
After the JPO’s policy change, the rate of the entrance of the national/regional phaseprocedure decreased by 4% for US and by 6% for Europe. This study uses theunexpected policy change as an instrument for the quality of ISRs and finds that theeffects of improving the quality of ISRs on the applicant’s decision to enter thenational/regional phase procedure are statistically significant with large values: a 10%
increase in quality causes a 4% decrease in entering the US national phase procedure
and a 6% decrease in entering the European regional phase procedure. The information5

provided by ISRs on prior art thus became significantly more useful to patent applicants.
Further, the estimated effects of this quality improvement in ISRs were far more than 10times those estimated by using the OLS method, suggesting that the value of patenting
overseas is strongly correlated with the number of the examiner’s backward citations
and the OLS estimation substantially underestimates the screening function of the ISRs.
The information revealed by ISRs seems to be significantly unanticipated to theapplicants to affect greatly their decision to enter the national/regional phase. The 1999
quality-oriented policy change by the JPO hence improved the quality of prior art search,
thereby enhancing the screening function of the ISA and ISR’s and raising theefficiency of the global patent examination system.
The remainder of this paper is organized as follows. Section 2 describes theinstitutional background and prior literature and formulates the hypotheses; Section 3
describes the data construction, variables, and estimation models; Section 4 presents theresults and discussion; and Section 5 concludes.
2. Institutional background, prior literature, and hypotheses development
2.1. Prior art information in ISRs under the PCT system
Under the PCT system, an applicant living in Japan can file a patent application written
in Japanese to the JPO or the International Bureau and the JPO prepares an ISR as the
ISA 5. An ISR is usually prepared within three months of receiving the application if theapplication claims priority based on earlier patent application(s) 6.
An ISR contains a list of references with citation category information thatindicates the examiner’s patentability assessment of each claim. The major citation
categories are “X,” “Y,” “A,” “P,” and “E.” The symbol “X” is indicated when theclaimed invention cannot be considered to be novel or to involve an inventive step when
the prior art is taken alone. The symbol “Y” is given if the claimed invention cannot be
considered to involve an inventive step because the claimed invention is the
combination of two or more pieces of prior art and such a combination is obvious to aperson skilled in the art. The symbol “A” means that the document is not considered todeny the novelty or inventive step of the claimed invention. The symbol “E” is given toan earlier application or patent published on or after the international filing date of the
focal PCT application. The symbol “P” denotes that the document was published before
5

If an application is written in English, the applicant can designate the JPO or EPO as the ISA. This
study only deals with PCT applications written in Japanese.
6 Rule 42 of the Regulations under the PCT stipulates that the time limit for establishing the ISR
shall be three months from the receipt of the search copy by the ISA or nine months from the priority
date, whichever time limit expires later.
6the international filing date but later than the priority date claimed by the focal PCT
application. The document category “E” and “P” is given in combination with a symbol
indicating the relevance of the document (e.g., “P, X”, “P, Y” or “P, A”). In this study,references to categories of both “P” and “E” are ignored for simplicity because thesekinds of documents are treated as prior art only when they had been filed in thejurisdiction in question7, and the legal effects of these references differ by jurisdiction 8.
Because one application usually contains two or more claims, two or morecategories may be assigned to one reference as in the case in which a document is
assigned to category X in light of claim 1 and to category Y in light of claim 2. In thisstudy, for simplicity, the references are categorized as follows: “X document” if “X” isassigned in light of at least one claim; “Y document” if “Y” is assigned in light of atleast one claim and no “X” is assigned; and “A document” if “A” is assigned in light ofat least one claim and no “X” or “Y” is assigned. “X documents” and “Y documents”
are hereinafter collectively called “XY documents.”
Although the references in ISRs are beneficial for reducing the workload
needed to process the application by other offices in the national/regional phase(Trilateral Patent Offices, 2001, 2002), a significant amount of prior art documents areadded through the national/regional phase examination process in each designatedcountry; hence, there seems to be room for improvement in the quality of ISRs (JPO,
2013).
The screening function will not be boosted, however, by improving the qualityof ISRs if the prior art information provided by an ISR is practically useless to theapplicant because of such factors as wide differences in legal systems and in thestandards of patent grants, as suggested by Jensen et al. (2005) and Webster et al.
(2007) 9. Further, the amendment of claims in a patent examination procedure may besignificant compared with the denial of the patentability of the initial claims 10. It istherefore an important empirical issue to examine whether improving the prior art
information provided by an ISR affects the applicant’s decision to enter the7

A prior application of “E, X” or “E, Y” filed only to Japan cannot be considered to be a prior art
under US patent law or the EPC.
8 In the United States, the combination of “EY” category documents can deny the inventive step of
the filed invention; however, the combination of “EY” category documents is not allowed under theEuropean and Japanese patent systems.
9 Jensen et al. (2005) and Webster et al. (2007) investigated patent applications filed to the EPO,
JPO, and USPTO between 1990 and 1995 and concluded that the examination outcome isinconsistent among these offices. However, this research did not take account of the difference in thequality of prior art search among the corresponding patent applications.
10 Applicants can narrow the scope of exclusive right by amending the initial claims in therespective patent examination procedure in each national/regional phase.
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national/regional phase.
2.2. Prior literature
The JPO (2011, 2013) investigated the types and number of prior art documents cited bynational/regional patent offices by using sample of 3,597 PCT applications for which
ISRs are prepared by the JPO and 5,311 PCT applications for which ISRs are preparedby the USPTO, both with a filing date in 2004–2005. It revealed that a significant
amount of prior art documents is added through the national/regional examination
process in each designated country.
Wada (2016) scrutinized a large sample of PCT applications with filing dates in
2002–2005 of which ISRs were produced by the EPO, the JPO, or the USPTO andentered the three national/regional examination processes to investigate whether
geographical distance affects the probability of finding prior art at the time of preparing
an ISR. It revealed that geographical distance as well as the technological complexity of
the filed inventions negatively affect the probability of finding prior art patentdocuments.
Wada (2014) is a pioneering study that used a quantified quality indicator of an
ISR. The indicator is based on the measurement of the ratio of the number of citations
cited in the ISR to the total number of citations cited by the ISR, the EPO, the JPO, or
the USPTO. The quality of an ISR, however, cannot be measured by the proposed
indicator if the application did not enter the national/regional phase procedure and there
are not US or European corresponding patent applications. Thus, improving the qualityof ISRs may not necessarily increase the average value of the proposed indicator if
applications with high quality ISR’s tend not to enter the national/regional phaseprocedure and drop from the sample. It is therefore necessary to investigate whether andto what extent improving the quality of an ISR affects the applicant’s decision to enter
the national/regional procedure in each designated country to reveal the efficacy of the
proposed indicator.
Lemley (2001) estimated the cost incurred by patent holders including
litigation cost, assuming that the number of patents reduces by 10% if the USPTO
doubles the amount of time examiners spend reviewing a patent from the current 18
hours to 36 hours. He found that it is not cost effective to improve examination quality.
Further, he emphasized that very few patents were ever the subject of litigation, or evenlicensing, and that 95% of the patents issued were either never used or were used incircumstances that did not crucially rely on the determination of validity, suggestingrational ignorance on the part of the USPTO. He concluded that little money should be8

spent in the examination process at the USPTO and comments on the need to strengthen
the validity inquiry by trial courts.
Cockburn et al. (2002) investigated 182 US patents, the validity of which the
Court of Appeals for the Federal Circuit (CAFC) ruled on in 1997–2000. For eachpatent, they identified the USPTO primary examiner and collected historical statistics
such as each examiner’s average “approval time” (i.e., the average time between initial
application and patent issue) and “three-month volume of patents” (i.e., the count ofissued patents in the three months before the issue date of the focal patent). By using
these two parameters, they found no evidence that workload affects the probability of
the CAFC finding a patent invalid. They stated that efforts to improve the visible
aspects of the examination process can create long-lasting and subtle changes on theless easily measured aspects of the examination process. This study had a fundamental
problem, however, in that a long “approval time” and low “three-month volume ofpatents” do not necessarily always mean that the examiner had a larger allocation oftime and low workload, rather, these factors may mean that the patent applications arepotentially controversial and require examiners more processes and more time for themto examine points at issue carefully.
De Saint-Georges and Van Pottelsberghe de la Potterie (2013) presented aquality index for patent systems composed of nine operational design components thatshape the transparency and stringency of patent systems and affect the extent to which
they comply with patentability conditions. Seven components are related to rules andregulations (e.g., grace period, opposition process, and continuation-in-parts), while twocomponents measure patent offices’ resource allocation policy (i.e., workload per
examiner and incentives). They investigated 32 national patent systems, and throughcross-sectional quantitative analyses, showed that demand for patent rights is lower inpatent systems with a higher quality index, controlling for research efforts, patent fees,
and the strength of enforcement mechanisms. This study, however, is not an empirical
study based on micro-level data.
Yamauchi and Nagaoka (2015) has investigated the effects of outsourcing ofprior art search on the patent examination, using a large scale Japanese patentexamination data controlling for the endogeneity of outsourcing decision as well as thechanges in the time resources available for an examiner to find that the outsourcing ofprior art search significantly decreases the frequency of appeals against both examiners’
rejections and grant decisions and reduces the length of examination duration.
Nagaoka and Yamauchi (2017) has examined how initiation timing of patentexamination affects the quality of patent examination by exploiting the law change in
9Japan, which shortened the maximum allowed time for examination request from sevento three years in 2001, and thus accelerated the timing of examination. It has found that
acceleration of the timing of patent examination increased significantly both the grant
rate and the frequency of appeals against the rejections of the patent office. These
results reveal that more information constraint increases both type I and type II errors(wrong grants and wrong rejections), but the increase in wrong grants is dominant.
These effects become stronger in technology sectors which have both short technology
cycles and early examination requests. It concludes that the findings suggest that thepatent office is under prior-art-information constraint.
Kim and Oh (2017) has empirically investigated effects of examination
workloads at the Korean Patent Office on the patent examination outcome and validityof patents, using Korean patent micro-level data to find that examiner decisions to grant
patents are systematically biased as workload increases, with examiners being more
likely to grant a patent than to reject it., and the likelihood of grant decision reversal byinvalidation trial boards significantly increases as workload increases. It concludes thatthese results imply that an examiner who lacks sufficient time for a prior art searchtends to grant a patent and, consequently, a large workload decreases the quality of
examinations by resulting in unqualified patents.
Frakes and Wasserman (2017) has addressed the question whether the time
allocated for reviewing patent applications to each examiner affects patent grant
decisions using application-level data to trace the behavior of individual examiners in
the USPTO over the course of a series of promotions that carry with them reductions in
examination time allocations. It has found that such promotions are associated withincreases in granting tendencies, decreases in the share of total prior art citations listed
in the final patent that derive from the examiner as opposed to the applicant, anddecreases in the likelihood of allowance at the EPO or the JPO.
These above four studies, however, has not investigated direct influences ofincrease in quality or intensiveness of prior search on the outcome of patentexamination. In summary, despite the importance of the screening function of the ISA’s
and ISR’s, no prior study has thus far addressed this matter or showed the direct effects
of improving the quality of prior art search empirically.
2.3. Drastic change in the JPO’s patent examination policy in 1999
As discussed previously, this study hypothesize that an exogenous shock in the qualityof ISR’s made by the JPO as an ISA was caused by the unexpected drastic policychange by the JPO from quantity-oriented to quality-oriented in 1999. To reveal that10

there was actually a policy change in 1999, it first reviews documents relating to the
JPO’s examination policy.
In 1998, the patent examination policy was oriented to quantity, known as the“FA12 policy,” which meant taking the first office action within 12 months of therequest for examination by the end of 2000. This policy was officially announced on
December 25, 1997 (JPO, 1998). 11 Sasaki (1999) published on January 14, 1999
describes Deputy Commissioner Sasaki’s view of the prospect of accomplishing “FA12”by the end of year 2000.
During 1999, however, the policy was switched to one that focused on thequality of search and examination. Ishii (2000), which was written by Deputy
Commissioner Ishii and published in January 2000, did not refer to the “FA12 policy”
but rather to the “quality of search and examination.” Ogiya (2000), which was writtenby the Director of the Patent Examination Policy Planning Office, emphasizes theimportance of raising the quality of search and examination and does not refer to the
speed of patent examination. Keidanren (2000) was an article based on an interview
with Mr. Kozo Oikawa, Commissioner of the JPO, in a magazine published by theJapan Business Federation, a comprehensive economic organization with a membershipof more than 1,000 Japanese companies. This article refers to Commissioner Oikawa’s
intention to realize a “search and examination in quality comparable to that of foreigncounterparts” and does not refer to “FA12.”
Sasaki (1999), Ishii (2000) and Ogiya (2000) were articles in Tokugikon, whichis the magazine published by Tokkyo-gijutsu-konwakai, the association of the JPO’s
examiners, shows that the examination policy is different between January 1999 andJanuary 2000.
Next, this article presents evidence based on statistical data. Fig. 1A presents
the average number of foreign patent documents cited in ISRs that have no patentfamilies written in Japanese, calculated by the calendar month of the filing date 12. The
value jumped to a relatively high value of around 0.13 after August 1999, whereas thenumber was small before August 1999 (around 0.6). Fig. 1B presents the average
number of non-patent literature (NPL) documents cited in ISRs. There seems to be a11

Before the FA12 policy started, the examination policy was also quantity-oriented, known as“Plan 24,” which meant reducing the backlog of pending applications below the amount of work of
24 months by the end of 1995. The “FA12” policy emphasized further the speed of patentexamination.
12 Applications are restricted to applications that designated the United States as the designatedcountry. Applications of co-ownership and applications claiming no priority are removed. Applicants
are restricted to those that have 10 or more applications between fiscal year (FY) 1998 and FY2000.
The fiscal year of Japan runs from April to March in the following year. (See section 3.1)
11

leap around August 1999. Figs. 1C and 1D present the average number of X and XY
documents, respectively, highlighting the small jump right after August 1999. Theinternational filing date is used as horizontal axes in the figures, as the precise date on
which an ISR was prepared for each application is unavailable. As an ISR is usually
prepared within three months of the international filing date and the dates on which the
ISRs were created range between one and two months considering the clerical work
operation time, some ISRs may have been created under the former policy and others
under the new policy even though the international filing dates are the same, which will
make the slopes gentler 13. These results indicate that the JPO’s unexpected policychange really occurred in 1999 and the date is probably between August and September
in 1999. Later, this article carries out a regression analysis, controlling for the variables
that relate to the quality and volume of the inventions in PCT applications.
(Fig. 1 around here)
Fig. 2 presents the change in the number of examiners in the JPO including
assistant examiners as well as the number of first actions made and number of grant
decisions. The number of patent examiners including assistant examiners changed little
around this period. Because only a tenth of the first actions are decisions to grant 14,
most grant decisions are made as second or subsequent actions. Both the number of firstactions and the number of grant decisions decreased after the policy change, suggestingthat the examination policy change brought about a drop in output and that the quality
improvement is driven by allocating more time for the examination of each application.
(Fig. 2 around here)
2.4. Hypotheses development
This study aims to reveal the significance of the quality of prior art information
provided by ISR’s for applicants and investigates whether the improvement in thequality of an ISR affects the applicant’s decision to enter the national/regional phase;hence, the main hypothesis is set as follows:
Hypothesis H1: Improving the quality of the prior art information provided by ISRs
reduces the rate of applicants’ decision to enter the national/regional phase significantly,
controlling for endogeneity with respect to the characteristics of applications that may
correlates with the value of patenting overseas such as the quality and volume of the13

It often takes time for an examiner to obtain a copy of the NPLs from libraries, which might
explain why the onset of the leap in the NPL is earlier than that of another citation.
14 According to Tokugikon Study Group on examination quality (2012), 11% of the first actions aredecisions to grant.
12

inventions in PCT applications.
(Fig. 3 around here)
This study hypothesizes that the drastic patent examination policy change by
the JPO in 1999 caused a leap in the number of citations in ISRs. Fig. 3 presents thetrend of PCT applications received by the JPO by calendar month, showing the number
almost doubled from the beginning to the end of the study period, April, 1998 to March,
2001; hence, the characteristics of applications such as the number of claims in PCTapplications might have changed over time. Sub hypothesis H1a relates to whether thatobserved in Fig. 1 is supported if we control for the characteristics of applications suchas the quality and volume of the inventions contained in PCT patent applications.
Sub hypothesis H1a: The JPO’s 1999 patent examination policy change increased
dramatically the numbers of such citations in ISRs as 1) foreign patent documents thathave no patent families written in Japanese, 2) NPL documents, 3) X documents, and 4)
XY documents, controlling for the quality and volume of the inventions in PCTapplications.
(Fig. 4A and Fig. 4B around here)
If an ISR provides the applicant with significant information about the prior art
that denies the novelty or inventive step of claimed inventions and the quality of suchinformation rises, the rate of entering the national/regional phase will drop. Figs. 4A and4B present the rate of entering the US national phase and the European (also termed EP
hereafter) regional phase by calendar month, respectively. Both values dropped after theexamination policy change. Sub hypothesis H1b relates to this in the reduced form of
the quality variable for each ISR. In other words, it relates to whether what we observein Fig.4A and Fig. 4B is supported if we control for the quality and volume of theinventions contained in PCT applications.
Sub hypothesis H1b: The rate of entering the US national phase or EP regional phaseof PCT applications for ISRs prepared by the JPO reduced dramatically after the JPO’s
1999 unexpected patent examination policy change, controlling for the quality andvolume of the inventions in PCT applications.

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3. Data construction and estimated model
3.1. Data construction
We developed a novel database of PCT applications that contains information about
designated countries and national/regional phase entrance for each application as well as
the citations cited in each ISR.
First, we took PCT application data including bibliographic data and citation
data from the PATSTAT database provided by the EPO (2015 autumn version). We
chose one fiscal year 15 before and after the fiscal year in which the JPO changed its
examination policy, that is, the filing date of the sample ran from April 1998 to March
2001.
Next, we prepared the data on entering the EP regional phase by using theexistence of EP patent family documents in PATSTAT. The Data on entering the US
national phase, however, are not sufficiently made from the existence of the US patentfamily documents in PATSTAT, as the United States adopted an 18-month early
publication system in 1999, which is effective on or after November 29, 2000, and therejected patent applications filed before then were not published, even if the PCT
applications entered the US national phase, Instead, we gathered data on entering the
US national phase from the online PATENTSCOPE database provided by the WIPO.
Because the data on the number of claims in PCT applications are lacking fromthe PATSTAT database, we substituted the number of claims in EP publications entering
the EP regional phase for it if applicable: otherwise, we supplemented the deficient data
by obtaining the corresponding data using the PATENTSCOPE database.
Finally, we prepared the data on designating EP or US by using the
PCT-Bibliographic database provided by the WIPO.
We removed applications claiming no priority as the date on which the ISR is
made is ambiguous (within nine months of the filing date). We also removed
applications of co-ownership to carry out regressions with the fixed effect of applicants.
3.2. Variables and estimation models
This study uses linear regression models to test the hypotheses, where suffix i stands forthe application, suffix j stands for the technology field, suffix k stands for the applicant(assignee), and suffix t stands for the filing date in the calendar month of theapplication.
In order to test the hypotheses, this article introduce a dummy variable,
policy_change_dummy, which is set to zero if the filing date is in or before August 1999,
15

The fiscal year of Japan runs from April to March in the following year.
14and set to one if the filing date is after August 1999.
To test sub hypothesis H1a, this study uses the following four variables as thedependent variables: i) 𝑙𝑙𝑙𝑙_𝑁𝑁𝑁𝑁𝑁𝑁_𝑋𝑋_𝑑𝑑𝑑𝑑𝑑𝑑𝑖𝑖,𝑗𝑗,𝑘𝑘,𝑡𝑡 , the logarithm of the number of X
documents in an ISR; ii) 𝑙𝑙𝑙𝑙_𝑁𝑁𝑁𝑁𝑁𝑁_𝑋𝑋𝑋𝑋_𝑑𝑑𝑑𝑑𝑑𝑑𝑖𝑖,𝑗𝑗,𝑘𝑘,𝑡𝑡 , the logarithm of the number of XY
documents in an ISR; iii) 𝑙𝑙𝑙𝑙_𝑁𝑁𝑁𝑁𝑁𝑁_𝑁𝑁𝑁𝑁𝑁𝑁𝑖𝑖,𝑗𝑗,𝑘𝑘,𝑡𝑡 , the logarithm of the number of
non-patent literature (NPL) documents in an ISR; and iv) 𝑙𝑙𝑙𝑙_𝑁𝑁𝑁𝑁𝑁𝑁_𝐹𝐹_𝑃𝑃𝑃𝑃𝑃𝑃𝑖𝑖,𝑗𝑗,𝑘𝑘,𝑡𝑡 , thelogarithm of the number of foreign patent documents having no patent families written
in Japanese.
As the control variables, this study use the variables that relate to the volume
and quality of the inventions in each application and are conventionally used in priorliterature (Harhoff et al., 2003; Nagaoka et al., 2010): ln_Num_claims (the logarithm of
the number of claims in the application) and ln_Num_inventors (the logarithm of thenumber of inventors). In addition, this study use ln_Num_priority (the logarithm of thenumber of applications for which the focal application claims the priority), based on theintuition that the volume of inventions tends to larger for applications claiming morenumber of prior applications. I expect the dependent variables to be positively
correlated with these three control variables.
Further, to control for technology areas, this study uses technology dummies
corresponding to the 35 technology areas assigned to each application based on the first
IPC subclass classification assigned to each application (Schmoch, 2008). To control forthe trend, this study uses dummies for fiscal years, i.e. FY 1998 dummy and FY 2000
dummy, with FY 1999 serving as the baseline as well as interaction terms between thefiscal year dummies and technology dummies. To use the applicant fixed effect model,
dummies for applicants are used based on the “DOCDB standard name id” in the
PATSTAT database.
The models for testing sub hypothesis H1a, sub-models A1–A4, are as follows(I expect the coefficient for policy_change_dummy, 𝛽𝛽0, to be positive and statisticallysignificant):
Sub-models A1–A4
𝑙𝑙𝑙𝑙_𝑁𝑁𝑁𝑁𝑁𝑁_𝐹𝐹_𝑃𝑃𝑃𝑃𝑃𝑃𝑖𝑖,𝑗𝑗,𝑘𝑘,𝑡𝑡 (or 𝑙𝑙𝑙𝑙_𝑁𝑁𝑁𝑁𝑁𝑁_𝑙𝑙𝑙𝑙_𝑁𝑁𝑁𝑁𝑁𝑁𝑖𝑖,𝑗𝑗,𝑘𝑘,𝑡𝑡 , 𝑙𝑙𝑙𝑙_𝑁𝑁𝑁𝑁𝑁𝑁_𝑋𝑋_𝑑𝑑𝑑𝑑𝑑𝑑𝑖𝑖,𝑗𝑗,𝑘𝑘,𝑡𝑡 ,
𝑙𝑙𝑙𝑙_𝑁𝑁𝑁𝑁𝑁𝑁_𝑋𝑋𝑋𝑋_𝑑𝑑𝑑𝑑𝑑𝑑𝑖𝑖,𝑗𝑗,𝑘𝑘,𝑡𝑡 )= 𝛽𝛽0 𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝_𝑐𝑐ℎ𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎_𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑y+ 𝛽𝛽1 𝑙𝑙𝑙𝑙_𝑁𝑁𝑁𝑁𝑁𝑁_𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑖𝑖 + 𝛽𝛽2 𝑙𝑙𝑙𝑙_𝑁𝑁𝑁𝑁𝑁𝑁_𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑖𝑖+ 𝛽𝛽3 𝑙𝑙𝑙𝑙_𝑁𝑁𝑁𝑁𝑁𝑁_𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖+𝛽𝛽𝑗𝑗 𝑡𝑡𝑡𝑡ℎ𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛_𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑 + 𝛽𝛽𝑡𝑡 𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓_𝑦𝑦𝑦𝑦𝑦𝑦𝑦𝑦_𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑

15

+ 𝛽𝛽𝑗𝑗,𝑡𝑡 𝑡𝑡𝑡𝑡ℎ𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛_𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑 × 𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓_𝑦𝑦𝑦𝑦𝑦𝑦𝑦𝑦_𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑+ 𝛽𝛽𝑘𝑘 𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎_𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑 + 𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 + 𝜀𝜀(1)

To test sub hypothesis H1b, this study introduces two binary variables as thedependent variables. The first is 𝑈𝑈𝑈𝑈_𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒_𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑖𝑖𝑖𝑖 , which takes the value of 1 if
PCT application i filed at t entered the US national phase and 0 otherwise. The second

one is 𝐸𝐸𝐸𝐸_𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒_𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑖𝑖𝑖𝑖 , which takes the value of 1 if PCT application i filed at tentered the EP regional phase and 0 otherwise. This article uses two linear probability
models in which only the dependent variable is different from the other, with theindependent variables the same as those used in sub-models A1–A4; hence, theestimation models for testing sub hypothesis H1b, sub-models B1 and B2, are as

follows (I expect the coefficient for policy_change_dummy, 𝛽𝛽0, to be negative andstatistically significant and the dependent variables to be positively correlated with thethree control variables.):
Sub-models B1 and B2
𝑈𝑈𝑈𝑈_𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒_𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑖𝑖,𝑗𝑗,𝑘𝑘,𝑡𝑡 (or 𝐸𝐸𝐸𝐸_𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒_𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑖𝑖,𝑗𝑗,𝑘𝑘,𝑡𝑡 )= 𝛽𝛽0 𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝_𝑐𝑐ℎ𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎_𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑y+ 𝛽𝛽1 𝑙𝑙𝑙𝑙_𝑁𝑁𝑁𝑁𝑁𝑁_𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑖𝑖 + 𝛽𝛽2 𝑙𝑙𝑙𝑙_𝑁𝑁𝑁𝑁𝑁𝑁_𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑖𝑖+ 𝛽𝛽3 𝑙𝑙𝑙𝑙_𝑁𝑁𝑁𝑁𝑁𝑁_𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖+ 𝛽𝛽𝑗𝑗 𝑡𝑡𝑡𝑡ℎ𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛_𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑 + 𝛽𝛽𝑡𝑡 𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓_𝑦𝑦𝑦𝑦𝑦𝑦𝑦𝑦_𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑+ 𝛽𝛽𝑗𝑗,𝑡𝑡 𝑡𝑡𝑡𝑡ℎ𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛_𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑 × 𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓_𝑦𝑦𝑦𝑦𝑦𝑦𝑦𝑦_𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑+ 𝛽𝛽𝑘𝑘 𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎_𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑 + 𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 + 𝜀𝜀(2)

To test hypothesis H1, this study introduces a variable for the quality of theprior art information provided by an ISR prepared for each PCT application i, 𝑞𝑞i . The
independent variables are the same as those used in the sub-models except for

𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝_𝑐𝑐ℎ𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎_𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑y; hence, by adopting linear probability modes, the estimation
models for testing H1 are expressed as follows, although these contain unobservablevariable 𝑞𝑞it :Model 1
= 𝛽𝛽0

𝑈𝑈𝑈𝑈_𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒_𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑖𝑖𝑖𝑖 (or 𝐸𝐸𝐸𝐸_𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒_𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑖𝑖𝑖𝑖 )𝑞𝑞i

16

+ 𝛽𝛽1 𝑙𝑙𝑙𝑙_𝑁𝑁𝑁𝑁𝑁𝑁_𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑖𝑖 + 𝛽𝛽2 𝑙𝑙𝑙𝑙_𝑁𝑁𝑁𝑁𝑁𝑁_𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑖𝑖+ 𝛽𝛽3 𝑙𝑙𝑙𝑙_𝑁𝑁𝑁𝑁𝑁𝑁_𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖+ 𝛽𝛽𝑗𝑗 𝑡𝑡𝑡𝑡ℎ𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛_𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑 + 𝛽𝛽𝑡𝑡 𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓_𝑦𝑦𝑦𝑦𝑦𝑦𝑦𝑦_𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑+ 𝛽𝛽𝑗𝑗,𝑡𝑡 𝑡𝑡𝑡𝑡ℎ𝑛𝑛𝑛𝑛𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙_𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑 × 𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓_𝑦𝑦𝑦𝑦𝑦𝑦𝑦𝑦_𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑+ 𝛽𝛽𝑘𝑘 𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎_𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑 + 𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 + 𝜀𝜀
(3)This study aims to reveal whether 𝛽𝛽0, the coefficient of unobservable variable

𝑞𝑞it , is negative as well as its absolute value. Since both X documents and Y documents
deny novelty or inventive step of filed inventions, this study uses 𝑙𝑙𝑙𝑙_𝑁𝑁𝑁𝑁𝑁𝑁_𝑋𝑋𝑋𝑋_𝑑𝑑𝑑𝑑𝑑𝑑𝑖𝑖 asa proxy for unobservable variable 𝑞𝑞i . If Sub hypothesis H1a holds and an increase in
𝑙𝑙𝑙𝑙_𝑁𝑁𝑁𝑁𝑁𝑁_𝑋𝑋𝑋𝑋_𝑑𝑑𝑑𝑑𝑑𝑑𝑖𝑖 is detected after the policy change, this would justify using thisvariable as a proxy for 𝑞𝑞it .
In many cases, combination of two Y documents deny inventive step whereas
one X document deny novelty or inventive step of a claimed invention. Hence, one canconsider two Y documents are equivalent to one X document. Based on this intuition,
this study introduce the following variable as another proxy variable for 𝑞𝑞i ,
𝑙𝑙𝑙𝑙_𝑁𝑁𝑁𝑁𝑁𝑁_𝑋𝑋ℎ𝑌𝑌_𝑑𝑑𝑑𝑑𝑑𝑑𝑖𝑖 , the logarithm of the number of X documents added by the half ofthe number of Y documents in an ISR.
Since these proxies relates to the number of the examiner’s backward citations
and they are supposed to be highly endogenous with the value of the patenting overseasof the filed inventions, which is not fully controlled for by the set of control variables,
namely 𝑙𝑙𝑙𝑙_𝑁𝑁𝑁𝑁𝑁𝑁_𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑖𝑖 , 𝑙𝑙𝑙𝑙_𝑁𝑁𝑁𝑁𝑁𝑁_𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑖𝑖 , and 𝑙𝑙𝑙𝑙_𝑁𝑁𝑁𝑁𝑁𝑁_𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖 , with
dummies for fiscal years, dummies for technology areas, and dummies for applicants.

To address this endogeneity, this study uses 𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝_𝑐𝑐ℎ𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎_𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑 as an
instrumental variable for the proxies for variable 𝑞𝑞i . Because the examination policychange was an exogenous shock to applicants, this policy change does not correlate withthe value of the patenting overseas of the inventions in the PCT applications
immediately after the policy change, nor applicants’ ex-post search or ex-post
knowledge and possible obsolescence of the invention. In other words, the policychange affected the applicant’s decision to enter the national/regional phase only
through the changes in the prior art information provided by the ISR produced for theapplication. That is, the IV used is very likely to satisfy the exclusion restrictions.
4. Results and discussion
4.1. Results of the regression analysis
174.1.1 A marked rise in the number of each kind of documents after August 1999
Table 1 presents a summary results of the regression analyses based on sub-models A1–
A4 using the sample that consist of applications that designed US. The regression iscarried out for both the sample that designed US and the sample that designated EP,
however, the results of the regression analyses on the latter sample is omitted because
the results are almost the same. In each regression estimation, applicants are restricted
to those that have 5 or more applications in the period. Table 2 presents the descriptive
statistics of the data.
The coefficient values for Policy_change_dummy are positive and statisticallysignificant at the 1% level for all estimates, controlling for the variables that relate to thevolume and quality of the inventions in each application such as the number ofapplications of which the priority is claimed by the focal application, the number ofclaims, and the number of inventors with the applicant fixed effect. The results indicatethat there was a marked rise after August 1999 in the number of each type of documents,
i.e. the number of X documents rose 9.7%, the number of XY documents rose 9.6%, thenumber of foreign patent documents that have no patent family documents written in
Japanese rose 3.4%, and the number of non-patent literature documents rose 5.2% after
August 1999. Thus, the unexpected examination policy change by the JPO increased theaverage number of documents cited in an ISR significantly and dramatically. These
results thus support sub hypothesis H1a.
(Table 1 and Table 2 around here)
4.1.2 A significant drop in the rates of entering national/regional phases
Table 3 presents a summary results of the regression analyses based on
sub-models B1 and B2. The data used are the same as those used in the previous
regression analyses based on sub-models A1–A4. The coefficient values for
Policy_change_dummy are negative (-0.035 and -0.057) and statistically significant at
the 1% level in both estimates, controlling for the trend and variables that relate to thevolume and quality of the inventions in the PCT application. These results mean that the
number of PCT applications that should have entered the national/regional phasedecreased by 3.5% for the US national phase and by 5.7% for the EP regional phase
after the examination policy change. These facts support sub hypothesis H1b.
In addition, the coefficient values for such control variables as,
𝑙𝑙𝑙𝑙_𝑁𝑁𝑁𝑁𝑁𝑁_𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑖𝑖𝑖𝑖 , 𝑙𝑙𝑙𝑙_𝑁𝑁𝑁𝑁𝑁𝑁_𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑖𝑖𝑖𝑖 ,and 𝑙𝑙𝑙𝑙_𝑁𝑁𝑁𝑁𝑁𝑁_𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖 are all positive andstatistically significant, indicating that PCT applications with more volume ofinventions and higher quality inventions are more likely to enter the national/regional
18phase reflecting higher values of patenting overseas. As the JPO’s unexpected switch inits patent examination policy caused a drop in the rate of entering the national/regional
phase and this policy turnaround, an exogenous shock to applicants, was able to affectthem only by improving the quality of the information provided by the ISRs, the policychange made the information provided by an ISR become significantly more useful tothe applicant and thus enhanced the screening function of ISRs.
(Table 3 around here)
4.1.3 Results of regression analyses by model 1 using instrumental variable method
Table 4 presents a summary results of the regression analyses by the mainmodel 1, Table 4A on US_enter_dummy as the explained variable and Table 4B on
EP_enter_dummy as the explained variable, respectively. The values of Cragg-Donald
Wald F statistic being 13.5 18.5, 12.2, 16.5 in estimation (2), (5), (8), and (11), to showthat the variable PolicyChange_dummy correlates strongly with the variables
ln_Num_XY and ln_Num_XhY, and PolicyChange_dummy seems to be a good
instrument. Because the values of Cragg-Donald Wald F statistic is greater for
ln_Num_XhY than for ln_Num_XY, ln_Num_XhY is more proper as a proxy for 𝑞𝑞i thanln_Num_XY.

The coefficient values for 𝑙𝑙𝑙𝑙_𝑁𝑁𝑁𝑁𝑁𝑁_𝑋𝑋𝑋𝑋_𝑑𝑑𝑑𝑑𝑑𝑑𝑖𝑖 and 𝑙𝑙𝑙𝑙_𝑁𝑁𝑁𝑁𝑁𝑁_𝑋𝑋ℎ𝑌𝑌_𝑑𝑑𝑑𝑑𝑑𝑑𝑖𝑖 are
negative and statistically significant at the 5% level in estimate (1) and the 1% level inestimates (4), (7), and (10), respectively. The values are almost same value, -0.37 inestimate (1) and estimate (4), respectively, where the explained variable is
US_enter_dummy. and -0.60 and -0.61 in estimate (7) and estimate (10), respectively,
where the explained variable is EP_enter_dummy. The result that the estimated valuesof the coefficients are almost same seems to also justify the method of this study
because IV method will remove the effect of possible random measurement error in q
on its estimated coefficient.
The estimated effect of the quality improvement of ISRs on the applicant’s
decision is large: a 10% increase in quality causes a 4% decrease in entering the US
national procedure and a 6% decrease in entering the European regional procedure.
These facts support H1.
In addition, the coefficient values for such control variables as,
𝑙𝑙𝑙𝑙_𝑁𝑁𝑁𝑁𝑁𝑁_𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑖𝑖 , 𝑙𝑙𝑙𝑙_𝑁𝑁𝑁𝑁𝑁𝑁_𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑖𝑖 , and 𝑙𝑙𝑙𝑙_𝑁𝑁𝑁𝑁𝑁𝑁_𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖 are all positive andstatistically significant, indicating that PCT applications with more volume ofinventions and higher quality inventions are more likely to enter the national/regional
phase, reflecting more values of patenting overseas.
Furthermore, the coefficient values for ln_Num_XY and ln_Num_XhY estimated19

by using instrumental variable method are an order of magnitude greater than thoseestimated by using the OLS method (-0.032 and-0.038 for US; -0.037 and – 0.044 forEP), suggesting that the endogeneity with respect to the value obtainable by patenting
inventions overseas is very large and not well controlled for by the other control
variables; hence, the bias is positive. It is hence very difficult for patent examiners tofeel the screening function of their prepared ISRs on the applicants’ decision on whether
to enter national or regional phases.
Moreover, the regression analyses imply the larger effect of sifting of ISR’s for
the European regional phase than that for the US national phase, though the difference
may not pass a statistical test considering relatively large standard errors of ourestimates. The difference might reflect that the standard of the inventive step in the
United States was assumed to be lower than that in Europe by applicants in the period(Quillen & Webster, 2006) or that the economic value of patenting an invention in the
United States was larger than that in Europe for Japanese applicants.
(Table 4 around here)
4.2. Robustness check
One might consider that the pooled regression analyses explained above may be result
from a boom of inventions of the information technology, in which the average rate of
the applications entering national/regional phase might be lower than those of theapplications in other technologies, e.g. pharmaceuticals. To address this problem, thisstudy implements regression analyses by dividing the sample by technology fields.
Because the size of the sample is not very large, the instrumental variable
method will not work well .if the sample is divided into several parts. This study, hence,
divides the sample into mainly two parts. Technology fields are often largely divided
into two fields, complex and discrete (Cohen, Nelson, and Walsh, 2000). WIPO 35
technology fields are grouped to five larger technology sectors, i.e. “Electricalengineering”, “Instruments”, “Chemistry”, “Mechanical engineering”, “Other fields”(Schmoch, 2008). This study regroups these to three groups, i.e. “Complex”, “Discrete”,
and “Others”. “Complex” consists of “Electrical engineering”, “Instruments”, and“Mechanical engineering”; “Discrete” consists of “Chemistry”; and “Others” consists of“Other fields” (see Appendix table A).
The regression analyses are implemented by the same models used in thepooled regression analyses for technology areas of both “Complex” and “Discrete”. To
increase the sample size, applicants are restricted to those that filed five or more
applications in the period in each technology areas.
20

Table 5 presents a summary results of the regression analyses based on
sub-models B1 and B2. The coefficient values for Policy_change_dummy are negative(-0.032 and -0.047) and statistically significant at least at the 5% level in both Complex
and Discrete technology areas for the US national phase, and are negative (-0.067 and-0.51) and statistically significant at least at the 5% level in both Complex and Discrete
technology areas for the EP national phase, controlling for the trend and variables that
relate to the volume and quality of the inventions in the PCT application. These facts
support H1b.
Table 6 presents a summary results of the regression analyses by the mainmodel 1 by technology areas using instrumental variable method on US_enter_dummy.
Only ln_Num_XhY is used as a proxy for 𝑞𝑞i . The values of Cragg-Donald Wald F
statistic being 7.6 and 11.0 for “Complex” and “Discrete” in estimation (2) and (4), toshow that the variable PolicyChange_dummy correlates strongly with the variable
ln_Num_XhY , and PolicyChange_dummy seems to be a good instrument in both
samples. The coefficient values for 𝑙𝑙𝑙𝑙_𝑁𝑁𝑁𝑁𝑁𝑁_𝑋𝑋ℎ𝑌𝑌_𝑑𝑑𝑑𝑑𝑑𝑑𝑖𝑖 are negative (-0.41 for“Complex” and -0.36 for “Discrete”), but statistically significant only at the 10% levelin estimates (1) and (3). The decrease of the statistical significance compared to those ofpooled regression analyses may come from the decrease of the sample size. Except forthis statistical significance decrease, the results are similar to the results of pooled
regression analyses.
Estimates (5) to (8) are obtained by implementing the same regression analyses
for samples that exclude the applications filed in August, 1999 because ISR’s made forthese applications may include those that are made both before and after theexamination policy change. The coefficient values for 𝑙𝑙𝑙𝑙_𝑁𝑁𝑁𝑁𝑁𝑁_𝑋𝑋ℎ𝑌𝑌_𝑑𝑑𝑑𝑑𝑑𝑑𝑖𝑖 are negative(-0.43 for “Complex” and -0.39 for “Discrete”) and statistically significant at the 5%
level in estimates (5) and (7) and the values of Cragg-Donald Wald F statistic are 7.6
and 12.1 for “Complex” and “Discrete” in estimates (6) and (8). The results support sub
hypothesis H1.

4.3. Discussion
This study revealed that the drastic examination policy change by the Patent Office of
the Japanese government markedly increased the number of references cited in an ISR
prepared under the PCT system, controlling for such application characteristics asvolume and quality, causing a drop in applicants’ decision to enter the national/regional
phase. The results suggest that the effect of the 1999 examination policy change was21substantive and contributed to the enhancement of the screening function of ISRs.
From the view point of foreign patent authorities, the policy change reduced
the duplication of examinations by the USPTO and EPO, contributing to increasing theefficiency of the global patent examination system. Moreover, some of the dropped
applications would have been granted by the EPO or USPTO, though these would havebeen potentially invalid, had there been no improvement in ISRs prepared by the JPO.
In addition, improved information on prior art would have helped examiners in the
USPTO and EPO narrow the scope of patents that were granted eventually. The 1999
policy change thus would have reduced the social cost that potentially invalid patents
might have placed on the domestic and foreign public (Farrell & Shapiro, 2008; Lemley& Shapiro, 2005), thereby benefitting the global public at large.
The average total cost of entering the US and EP procedures for applicants isabove one million yen 16 and improving the quality of ISRs enables applicants to savesuch costly expenditure. More importantly, it would help the applicants to avoid making
sunk investment under the premise of non-existing patent protection, which would
increase the efficiency of applicants’ innovation activities.
As examination speed was still important for the JPO at that time (Ogiya,
2000) and the examination policy change brought about a drop in output as explained in
Section 2.3, it seems natural to conclude that no quality improvement would haveoccurred without a reduction in output and an increase in the average time spentexamining one application (e.g., more dedication to prior art search). The present study
was unable to assess whether the cost of increasing ISR quality is justified in light ofthis tradeoff. Further study with more enhanced data would be necessary to tackle thematter and hopefully to refute the conclusions by Cockburn et al. (2002) that providing
more time for patent examiners to examine each patent application creates a backlog but
subtle change in the quality of patents.
This study used 𝑙𝑙𝑙𝑙_𝑁𝑁𝑁𝑁𝑁𝑁_𝑋𝑋ℎ𝑌𝑌_𝑑𝑑𝑑𝑑𝑑𝑑𝑖𝑖 and 𝑙𝑙𝑙𝑙_𝑁𝑁𝑁𝑁𝑁𝑁_𝑋𝑋𝑋𝑋_𝑑𝑑𝑑𝑑𝑑𝑑𝑖𝑖 as proxyvariables for 𝑞𝑞i , the quality of the prior art information of an ISR, and both of which
seems to have worked well. Yet, the former seems better since the values of
Cragg-Donald Wald F statistic are greater than those of the other, which seems very
natural considering the intuition that one X documents worth a combination of two Y
documents.
From the perspective of managing examination process at Patent Offices of the16

According to AIPPI JAPAN (2008), the average cost for each PCT applicant is as follows:translation cost, ¥260,000; patent attorney fee, ¥560,000; US national phase entering fee, $1,300; EP
entering fee, 1,300 Euro. Personnel expenses for applicants’ employees are unknown.
22

governments in the world, the importance of measuring search quality is wellrecognized in order to enhance policy making, and promoting international cooperation
among patent authorities (Kappos & Graham, 2012; US Government Accountability
Office, 2016a, 2016b), however, no established methods have thus far been proposed.
This study implies that the number of ISR cited XY documents and the rate of entering
the national/regional phase may be potentially valuable indicators for such purposes ifthey are used with control variables such as the volume and the quality of inventions. It
is, hence, desirable for patent authorities globally as well as the WIPO to enhance therelevant data and enable authorities, applicants, and scholars to assess and use such data
in a timely and costless manner.
5. Conclusion
This study confirmed that the unexpected drastic examination policy change fromquantity-oriented into quality-oriented by the Patent Office of the Japanese government
in 1999 increased the quality of ISRs substantially. This exogenous shock brought about
a 4% decrease in the US national phase entrance and a 6% decline in the European
regional entrance of PCT applications, controlling for the volume and quality of theinventions and the applicant fixed effect as well as technology fields, fiscal year, andinteraction terms threreof. By using this exogenous shock, this study revealed that theprior art information provided by an ISR is crucial to the applicant and that improving
quality of ISRs affects significantly applicants’ decisions to enter the national/regional
phase: indeed, a 10% increase in quality causes a 4% decrease in entering the US
national procedure and a 6% decrease in entering the European regional procedure.
These facts suggest that ISRs provide a valuable screening function and that its
enhancement by a national patent office would significantly contribute to applicants’better decisions as well as to raising the efficiency of the global patent examination
system.
Importantly, the examination policy change increased search quality at theexpense of a drop in examination output. However, the present study was unable toassess whether the cost of increasing ISR quality is justified in light of this tradeoff.
Further study with more enhanced data would be necessary to tackle the matter.
Although the importance of measuring search quality is well recognized forsuch purposes as managing the operations of patent offices, enhancing policy making,and promoting international cooperation among patent authorities, no establishedmethods have thus far been proposed. The number of XY documents cited in an ISR andthe rate of entering the national/regional phase may be potentially valuable indicators
23

for such purposes if they are used with control variables such as the volume and thequality of inventions. It is, hence, desirable for patent authorities globally as well as theWIPO to enhance the relevant data and enable authorities, applicants, and scholars toassess and use such data in a timely and costless manner.
Acknowledgements
This work was financially supported by the Japan Science and Technology Agency(JST) under the RISTEX project entitled ‘‘Development of Benchmarks of the Qualityof Prior Art Search in International Patent Prosecution Processes.” I would like to thankthe JST for granting this aid. I also thank Professor Sadao Nagaoka, Professor Atsushi
Ohyama, Professor Kenta Nakamura, Professor Tetsuo Wada, Professor Stuart Graham,and Professor Mark Schankerman for their helpful comments on this work as well as Mr.
Yusuke Naito and Ms. Junko Morikawa for their assistance in preparing the data.

24

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27

Fig. 1 Average number of ISR-citing documents by filing dateFig. 1A
Fig. 1B
0.2

Num_F_Pat

0.8

Num_NPL

0.15

0.6

0.1

0.4

0.05

0.2

0

0

1998 1998 1999 1999 2000 2000
APR OCT APR OCT APR OCT

1998 1998 1999 1999 2000 2000
APR OCT APR OCT APR OCTFiling date

Filing dateFig. 1C
1.5

Fig. 1D

Num_X

3.5

Num_XY

1

3

0.5

2.5

0

2

1998 1998 1999 1999 2000 2000
APR OCT APR OCT APR OCT

1998 1998 1999 1999 2000 2000
APR OCT APR OCT APR OCTFiling date

Filing date

Data source: Constructed by the author from PATSTAT database (2015 autumn version),
PATENTSCOPE database, and PCT-Bibliographic database.
Note: 1A: Foreign patent documents having no Japanese language families, 1B: Non-patent
literature, 1C: X documents, 1D: XY documents. Applications are restricted to those that designatedthe United States as the designated country. Applications of co-ownership (two or more assignees) or
claiming no priority are removed. Assignees are restricted to those that have six or more applicationsin the period from FY1998 to FY2000.
28

Fig. 2. Change in the number of examiners, first actions, and grant decisions

250,000

1,200
1,000

200,000

800

150,000

600
100,000

400

50,000

200

0

0
1997

1998

1999

2000

2001

calendar year
first action (left axis)
decision to grant (left axis)
examiners and assistant examiners(right axis)
Data Source: Annual report of each year by the Japan Patent Office29

Fig. 3 Trend of PCT applications
1000

Number of applications

900
800
700
600
500
400
300
200
100
0

1997 1997 1998 1998 1999 1999 2000 2000 2001 2001
Apr Oct Apr Oct Apr Oct Apr Oct Apr Oct
Filing date

Data source: Constructed by the author from PATSTAT database (2015 autumn version)and PCT-Bibliographic database.
Note: Applications are restricted to applications that designated the United States as oneof the designated countries. Applications of co-ownership (two or more assignees) andclaiming no priority are removed. Assignees are restricted to those that have six or more
applications in the period from FY1998 to FY2000.

30

Fig. 4 Rate of entering the national/regional phase procedure
Fig. 4A US national phase

US entering rate
100.0%
95.0%
90.0%
85.0%
80.0%
75.0%
70.0%
65.0%
60.0%
1998
Apr

1998
Oct

1999
Apr

1999
Oct

2000
Apr

2000
Oct

2000
Apr

2000
Oct

Fig. 4A EP regional phase

EP entering rate
100.0%
95.0%
90.0%
85.0%
80.0%
75.0%
70.0%
65.0%
60.0%
1998
Apr

1998
Oct

1999
Apr

1999
Oct

Data source: Constructed by the author from PATSTAT database (2015 autumn version),
PATENTSCOPE database, and PCT-Bibliographic database.
31

Table 1 Policy change effect on the number of documents cited in ISRs

Explained variables
PolicyChange_dummy
ln_Num_priority
ln_Num_claims
ln_Num_inventors
fiscal year
tech35fiscal year tech35
applicantObservations
R-squared
Number of applicants
adjusted R-Squared
Log Likelihood

(1)
(2)
(3)
(4)
ln_Num_X ln_Num_XY ln_Num_F_Pat ln_Num_NPL.0967***(.0215).0873***(.0143).100***(.00935).0305***(.00918)
yes
yes
yes
FE
13,523.0510
395
0.0434-12289.0957***(.0236).111***(.0172).147***(.0149).0413***(.0142)
yes
yes
yes
FE
13,523.0562
395
0.0486-15402.0335***(.00742).00840(.00547).00553*(.00282).00423(.00328)
yes
yes
yes
FE
13,523.0288
395
0.02101684.0519***(.0134).0129(.00942).0338***(.00802)-.00525(.00767)
yes
yes
yes
FE
13,523
.131
395
0.124
-5995

Note: 1. Robust standard errors in parentheses.
2. *** p<0.01, ** p<0.05, * p<0.10.
3. Samples are those that designated the United States as a designated country and thatclaims priority based on earlier patent application and that filed six or more applications infiscal 1998 - 2000.

32

Table 2 Descriptive statistics for the data used in the regression analysis
2A PCT patent applications that designated the United States
N=13,523
mean

sd

p50

min

max

US_enter_dummy

0.85

0.36

1

0

1

Policy_change_dummy

0.63

0.48

1

0

1

ln_Num_X_doc

0.50

0.64

0

0

4.16

ln_Num_XY_doc

0.99

0.81

1.10

0

4.16

ln_Num_XhY_doc

0.82

0.69

0.92

0

4.16

ln_Num_NPL

0.20

0.48

0

0

3.50

ln_Num_F_Pat

0.06

0.23

0

0

2.40

ln_Num_priority

0.29

0.49

0

0

3.14

ln_Num_claims

2.48

0.78

2.48

0

5.98

ln_Num_inventors

1.00

0.62

1.10

0

3.09

2B PCT patent applications that designated European patents
N = 12,480

mean

sd

p50

min

max

EP_enter_dummy

0.80

0.40

1

0

1

Policy_change_dummy

0.63

0.48

1

0

1

ln_Num_X_doc

0.50

0.64

0

0

4.16

ln_Num_XY_doc

0.99

0.81

1.10

0

4.16

ln_Num_XhY_doc

0.82

0.69

0.92

0

4.16

ln_Num_NPL

0.21

0.49

0

0

3.50

ln_Num_F_Pat

0.07

0.23

0

0

2.40

ln_Num_priority

0.30

0.50

0

0

3.14

ln_Num_claims

2.48

0.78

2.48

0

5.98

ln_Num_inventors

1.02

0.62

1.10

0

3.09

33

Table 3 Policy change effect of entering the US national phase or EP regional phase
Explained Variables
(1)

(2)

US_enter_dummy

EP_enter_dummy-.0352***-.0567***(.0107)(.0131).0236***.0248***(.00702)(.00919).0263***.0301***(.00596)(.00692).0158**.0266***(.00623)(.00767)

fiscal year dummies

yes

yes

tech35_dummies
fiscal_dummies *tech35_dummies
applicant

yes
yes

yes
yes

FE

FE

Observations
R-squared
Number of applicants

13,523

12,480

.0281

.0293

395

384

Explanatory Variables
PolicyChange_dummy
ln_Num_priority
ln_Num_claims
ln_Num_inventors

Note: 1. Robust standard errors in parentheses.
2. *** p<0.01, ** p<0.05, * p<0.10.

34

Table 4 The summary results of the regression analyses by the main model 1 using
Instrumental variable method
Table 4A Analyses on US_enter_dummy

Explanatory variables(1)IV
secondstage

ln_Num_XhY
ln_Num_XY-.368**(-2.52)

PolicyChange_dummy
ln_Num_priority
ln_Num_claims
ln_Num_inventors
tech35_dummies
fiscal year
fiscal*tech35
applicant.0645***(3.51).0804***(3.60).0310***(3.41)
yes
yes
yes
FE

Explained variable: US_enter_dummy
(2)
(3)
(4)
(5)
OLS
IV
secondfirst stage
first stage
stage-.370***(-2.68)-.0316***(-8.55).0957***.0952***(3.68)(4.31).111*** .0275*** .0621***.104***(6.75)(3.95)(3.76)(7.44).147*** .0308*** .0758***.134***(13.7)(6.73)(3.92)(14.6).0413*** .0174*** .0300*** .0383***(3.22)(3.21)(3.61)(3.52)
yes
yes
yes
yes
yes
yes
yes
yes
yes
yes
yes
yes
FE
FE
FE
FE

Observations
13,523
13,523R-squared
-.583
.0562
Number of applicants
395
395
C-D W F statistic
13.54
Note: 1. Z-statistics or t-statistics in parentheses.
2. *** p<0.01, ** p<0.05, * p<0.10.

13,523.0328
395

13,523-.401
395

13,523
.0600
395
18.54

(6)
OLS

-.0377***(-8.66).0279***(4.00).0312***(6.81).0175***(3.23)
yes
yes
yes
FE
13,523
.0329
395

35

Table 4B Analyses on EP_enter_dummy

Explained variable: EP_enter_dummy
(7)

(8)

IV
Explanatory variables

second
stage

(9)

(10)

OLS

IV
stage

-.599***-.0368***(-2.87)(-8.56)

PolicyChange_dummy
ln_Num_priority

(12)
OLS

secondfirst stageln_Num_XhY
ln_Num_XY(11)

first stage-.606***-.0438***(-3.13)(-8.67).0947***.0936***(3.49)(4.06).0934***.115***.0294***.0901***.108***.0299***(3.48)(6.76)(3.68)(3.81)(7.48)(3.74).120***.150***.0352***.113***.136***.0357***(3.68)(13.3)(6.58)(4.09)(14.2)(6.66).0423***.0262*.0278***.0433***.0277**.0281***(3.76)(1.94)(4.36)(4.14)(2.40)(4.40)

tech35_dummies

yes

yes

yes

yes

yes

yes

fiscal year

yes

yes

yes

yes

yes

yes

fiscal*tech35

yes

yes

yes

yes

yes

yes

applicant

FE

FE

FE

FE

FE

FE

Observations

12,48012,48012,48012,48012,48012,480R-squared

-1.34

.0572

.0336

-.963

.0611

.0338

Number of applicants

384

384

384

384

384

384

ln_Num_claims
ln_Num_inventors

C-D W F statistic

12.21

16.48

Note: 1. Z-statistics or t-statistics in parentheses.
2. *** p<0.01, ** p<0.05, * p<0.10.

36

Table 5 A summary results of the regression analyses based on sub-models B1 andB2 by technology areas
Explained variables

US_enter_dummy

EP_enter_dummy

(1)

(2)

(3)

(4)

ComplexDiscrete

ComplexDiscrete-.0320**-.0468***-.0672***-.0505**(.0131)(.0178)(.0177)(.0214).0288***.0188.0330***.0190(.00832)(.0136)(.0122)(.0154).0131***.0518***.0124*.0597***(.00494)(.0105)(.00672)(.0117).0120*.0175.0282***.0185(.00684)(.0126)(.00918)(.0142)

fiscal year
tech35fiscal year tech35
applicant

yes
yes
yes
FE

yes
yes
yes
FE

yes
yes
yes
FE

yes
yes
yes
FE

Observations

8,063

5,201

7,194

5,004

R-squared

.0343

.0271

.0394

.0242

Number of applicants

264

243

250

231

adjusted R-Squared

0.02520.02050.02930.0173

Log Likelihood

-1272

-2080

-2333

-2216

PolicyChange_dummy
ln_Num_priority
ln_Num_claims
ln_Num_inventors

Note: 1. Robust standard errors in parentheses.
2. *** p<0.01, ** p<0.05, * p<0.10.

37

Table 6 A summary results of the regression analyses based on model 1 by technology areas using instrumental variable method
(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

Explained variable: US_enter_dummy
VARIABLES
ln_Num_XhY

Complex

ComplexDiscrete

Discrete

Complex

ComplexDiscrete

Discrete

2nd stage

1st stage

2nd stage

1st stage

2nd stage

1st stage

2nd stage

1st stage

#1

#1

#1

#1

-.412*-.356*-.427**-.388**(-1.95)(-1.89)(-1.99)(-2.08)

PolicyChange_dummy
ln_Num_priority
ln_Num_claims
ln_Num_inventors.0762***.130***.0776***.138***(2.76)(3.32)(2.76)(3.47).0699***.104***.0564**.104***.0715***.107***.0604**.107***(2.91)(5.89)(2.26)(4.24)(2.87)(6.00)(2.35)(4.33).0669**.131***.104***.147***.0689**.129***.109***.147***(2.36)(11.7)(3.45)(8.77)(2.42)(11.4)(3.63)(8.67).0353**.0548***.0207.00789.0365**.0566***.0185.00236(2.56)(4.23)(1.54)(.37)(2.54)(4.34)(1.32)(.109)

Observations

7,853

7,853

5,016

5,016

7,699

7,699

4,882

4,882

R-squared

-.545

.0711

-.358

.0502

-.588

.0714

-.439

.051

Number of applicants

222

222

206

206

222

222

206

206

C-D W F statistic

7.63

11.03

7.63

12.05

Note: 1. Z-statistics or t-statistics in parentheses.
2. *** p<0.01, ** p<0.05, * p<0.10.
3. Analyses (5) to (6) marked with “#1” are implemented with samples that exclude applications filed in August, 1999.
38

Appendix Table A. Technical fields
C or D

Technology sector

Technology field
1 Electrical machinery, apparatus, energy, 2
Audio-visual technology, 3 Telecommunications, 4Complex

Electrical engineering

Digital communication, 5 Basic communication
processes, 6 Computer technology, 7 IT methods
for management, 8 Semiconductors

Complex

Instruments

9. Optics, 10 Measurement, 11 Analysis of biologicalmaterials, 12. Control, 13. Medical technology
14 Organic fine chemistry, 15 Biotechnology, 16
Pharmaceuticals, 17 Macromolecular chemistry,
polymers, 18 Food chemistry, 19 Basic materials

Discrete

Chemistry

chemistry, 20 Materials, metallurgy, 21 Surface
technology, coating,, 22 Micro-structural andnano-technology, 23 Chemical engineering, 24
Environmental technology
25 Handling, 26 Machine tools, 27 Engines, pumps,

Complex

Mechanical engineering

turbines, 28 Textile and paper machines, 29 Other
special machines, 30 Thermal processes andapparatus, 31 Mechanical elements, 32 Transport

OthersOther fields

33 Furniture, games, 34 Other consumer goods, 35
Civil engineering

39