Hitotsubashi University
Institute of Innovation Research

Does the outsourcing of prior art search increase theefficiency of patent examination?

Isamu Yamauchi
Sadao Nagaoka

IIR Working Paper WP#13-12

May 2013

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

Does the outsourcing of prior art search increase the efficiency of patentexamination?†
Isamu Yamauchi
Research Institute of Economy, Trade and Industry

Sadao Nagaoka**Institute of Innovation Research, Hitotsubashi University

May 2013
Abstract
This paper investigates the effects of outsourcing of prior art search on the efficiency of patentexamination, using a large scale Japanese patent examination data. Outsourcing may increase
examination quality by expanding the scope of prior art search, while it may have a negative
effect if the synergy between search and examination is important. If examination quality is the
predominant concern for outsourcing decision and the outsourcing is constrained by budgetary
resources, we expect that outsourcing enhances examination quality at its margin. On the other
hand, if an examiner can save private cost by outsourcing, an increase in outsourcing candecrease the quality. Controlling for the endogeneity of outsourcing decision as well as
examiners’ fixed effects, we found that the outsourcing of prior art search significantly
decreased the frequency of appeals against both examiners’ rejection and grant decisions andreduced the length of examination duration. At the same time we found that the prior art searchof complex inventions is not outsourced. These suggest that the opportunity for exploiting
external knowledge and capability can increase the quality as well as the speed of examination.
JEL classification numbers: O38, O34, O30
Keyword: patent, examination, outsourcing, search, prior art† This research is based on our research “Determinants of the Backlog and the Efficiency of Patent

Examination” in the Study Report on the Industrial Property Activity for Further Economic Growth,
published by Institute of Intellectual Property (commissioned by Japan Patent Office). We would liketo thank for the comments from the participants in the committee. We also thank to the JPO for
providing us the valuable data on outsourcing of prior art search. This research received financial
support from the Japan Society for the Promotion of Science (JSPS), Grant-in-Aid for Scientific
Research (S) (No. 20223002).
Corresponding author. 1-3-1 Kasumigaseki, Chiyoda-ku, Tokyo 100-8901, Tel.:+81 3 3501 1393, Emailaddress: yamauchi-isamu@rieti.go.jp** Institute of Innovation Research, Hitotsubashi University, Email address: nagaoka@iir.hit-u.ac.jp

11. Introduction
Patent system should be designed to effectively promote innovation. Especially, the outcomeof patent examination defines the scope of public domain and affects the appropriability of firms’
R&D. The timely completion of an examination is also important for that objective. Therefore,
the design of efficient patent examination process is crucial to keep the patent system functional.
The global surge of patent applications causes a great concern about the increasing backlog ofpending patent applications in many countries. The increased backlog delays the examination
process due to the overload problem of examiners, which can decrease the quality of
examination and lead to an increase in the patents with dubious patentability. The increasing
complexity of inventions also aggravates the problem.
In response to this concern, the Japan Patent Office (JPO) has increased outsourcing of priorart search, in order to reduce the pendency period and to maintain adequate quality of patentexamination. The JPO spent about 236 million dollars (calculated at 1 USD = 90 yen) foroutsourcing in 2010, while the total labour cost of the JPO is 371 million dollars. The number ofapplications of which the prior art search is outsourced reached 246 thousands in 2010 (about
65% of all examined applications). The cost of outsourcing per examined applications is about
947 USD, which can account for 40 % of the direct cost of patent examination1.
Due to the large investment in outsourcing, the number of decisions per examiner per monthhas been significantly increasing: the average number of monthly examinations per
examiner increased from 13.6 to 16.0 between 1999 and 2007, as the rate of outsourcing
increased from 30% to 70%2.

The decision on which applications should be outsourced is left to individual examiners,
though there is a limitation on the maximum number of outsourcing per month due to thebudget constraint. Note that the individual examiners take ultimate responsibility for the search
results even when they outsourced the prior art search. Therefore, they supplement the search
results if needed in the examination.
The work of patent examiners is divided into two tasks: (1) searching prior art in patents andpublished literature for identifying relevant prior art for the evaluation of novelty and inventive
step, and (2) substantive examination of whether the invention meets the patentability
requirements (novelty, non-obviousness and industrial application). The central question of thispaper is whether the outsourcing of prior art search increases the efficiency of patentexamination process measured in terms of quality and speed, given that the volume of
1 According to the JPO’s estimates, the direct cost of examination is 22,000 yen (244 USD) per claim in2010. Therefore, the direct cost of examination per examined application is assumed to be about
209,000 yen (2,322 USD) as the average number of claims per application is 9.5 in 2010.
2 In the previous version of this paper, using the examiner-level panel data, we found that the numberof decisions of each examiner per month increased by about 39 % on average as the rate of outsourcingof prior art search increased from 0% to 100%.

2

examination per examiner significantly increased due to outsourcing.

One possible view (“synergy view”) is that the quality and the speed of examination become
higher if the same examiner conducts both prior art search and substantive examination. This isbecause the integration of two closely interconnected tasks deepens the examiner’s
understanding of the contents of the invention and enhances the efficiency of both search andexamination. The integration can also save the time necessary for communication andcoordination between two individuals, examiners and searchers, if the two tasks are divided. An
alternative view (“search scope view”) is that the outsourcing of prior art search enhances theefficiency of the examination process, since the examiner can take advantage of the searchability of the searchers specialized in prior art identification and thus he can expand thepotential search scope. Identifying the adequate prior art is a vital step in the patentexamination.
The European Patent Office (EPO) pursues the synergy view, where a single lead examiner
undertakes both search and examination under the “BEST” (“Bringing Examination and Search
Together”) program. On the other hand the JPO takes the search scope view, substantiallybecause the JPO has not been able to significantly increase the number of examiners, given thebudgetary ceiling on the number of civil servants in Japan.
This paper tries to identify which view is true under the specific circumstances, using theJapanese patent examination data. In reality we expect that both forces are at work. Especially,
if examination quality is the predominant concern in an outsourcing decision and theoutsourcing is constrained by budgetary resources, we expect that outsourcing enhances
examination quality at its margin. We found that the outsourcing of prior art search significantly
decreased the frequency of appeals against the rejection decisions as well as against the grant
decisions of examiners, controlling for the endogeneity of outsourcing, the complexity of
examination task, the value of patenting the inventions and the differences in the examiners(that is, examiners’ fixed effects). We also found that the outsourcing increased the speed of
examination by reducing the period of communications between examiners and applicants inboth grant and rejection process. These effects are still observed despite of the fact that thevolume of final decisions by an examiner per unit of time increases significantly with anincrease in outsourcing of prior art search.
These results suggest that the outsourcing of prior art search has increased the quality as
well as the speed of examination. It is noteworthy that, according to our estimation results,
outsourcing is chosen for less complex patent applications, which indicates the advantage of
integrating two tasks for complex patent applications. Therefore, giving an examiner an option
to use the outsourcing of prior art search can play an important role for improving the efficiencyof patent examination, given the large variety of the complexity of inventions.
3

The rest of the paper is organized as follows. Section 2 surveys related studies, and Section
3 describes the data. We provide the analytical and estimation framework in Section 4, andestimation results in Section 5. Finally, Section 6 concludes the paper.
2. Related Studies
Not many but some studies address the issue of patent examination process. However,
empirical analysis focusing on the quality of examination process is scarce and, to the best of
our knowledge, no studies have analyzed the effects of outsourcing.
The most related paper is Harhoff and Wagner (2009). They analyze the determinants of theexamination duration, and identify the different effects on the granted, withdrawn and refused
applications. They divide the main determinants into three groups: the characteristics ofapplicants, the value related characteristics of inventions, and the complexity of examination
task. According to their study, the potentially valuable applications are granted earlier andwithdrawn slower. Moreover, they show that more complex inventions, measured by the numberof claims and backward citations, need more time to complete the examination process.
However, they do not analyze the effects on the quality of examination in terms of the frequencyof the appeals against the decisions of the Patent Offices.
Caillaud and Duchene (2011) theoretically analyze how the workload of examiners affects
the firms’ R&D incentives, assuming the tradeoff between the workload and the quality of
examination. They suggest that the introduction of a penalty system on the applicants forrejected patent applications and the commitment of the non-obviousness standard could attainthe high-R&D equilibrium, since those policies increase the firms’ incentive to screen out the
low-quality inventions, and thus reduce the workload of examiners and increase the quality of
examination.
Based on the queuing theory, Sharon and Liu (2008) simulate the impacts of institutional
factors on the pending applications in the U.S. According to their simulation results, therestriction on the number of the times of non-final rejection significantly decreases the backlogs,
while the restrictions on the number of times of requests for continued examination orcontinuations have little effect.
Batabyal and Nijkamp (2008) is another theoretical study which applies the queuing theory.
Assuming the tradeoff between the quality and the speed of examination, they compare thedesirability of two policy regimes: the speed-oriented examination with a small number of
examiners, and the accuracy-oriented examination with a large number of examiners. Theysuggest that the former regime is rational when the pendency period is a great concern and thelatter is desirable when the quality of examination is regarded as a big problem.
Cockburn et al. (2002), focusing on the characteristics of examiners, empirically shows that4the examination process significantly varies across examiners. They find that the number andthe pattern of citations and the grant rate differ depending on the examiner’s experience,
specialty, workloads and examination period per application. On the other hand, they also findthat the experience and workloads of examiners have little effect on the frequency ofinvalidation, which implies the quality of examination does not depend on the variation of
examiners.
Regibeau and Rockett (2010) show that the more important inventions are examined earlier
when they control for the life cycle of technology, and the more advanced technologies are
examined slower when they control for the quality of inventions. Their analysis is based on theassumptions that an applicant has an incentive to accelerate the examination process for its
important inventions over the life cycle of technology, while an examiner can evaluate theapplication more accurately by delaying the decision and accumulating more technologicalknowledge. Thus, their analysis recognizes knowledge constraint in the patent examination,
which could be alleviated using external knowledge.
There are some empirical studies which focus on the applicants’ strategic motivation.
Lemley and Sampat (2010) suggest that an applicant uses the continuation to delay theexamination process so that she can keep the opportunity to amend the contents of applications
according to the market situation.
Sampat (2010) analyses the applicant’s effort for the prior art search, and find that the shareof applicant’s citations against the examiner’s citations becomes higher when the invention ismore important for the applicant. This result indicates that the applicant’s incentive to contributeto the prior art search significantly differs due to the applicant’s strategic motivation.
These studies show that the duration of patent examination varies depending on theapplicant’s motivation. Relating to this point, Palangkaraya et. al. (2008) and Henkel and Jell(2010), focusing on the firm’s examination request behavior, suggest that the applicants have an
incentive to prolong the examination process due to the strategic motivation such as increasing
the third party’s uncertainty. However, according to Yamauchi and Nagaoka (2009), another andmore important motivation of applicants to delay their decision on examination request could be
to learn the value of their applications.
Pop et al. (2003) focuses on the characteristics of invention and suggests that the main
determinant factor of the increasing examination duration is the complexity of technology rather
than the applicant characteristics.
In this paper, different form the above existing studies, we investigate the effects of policy
tool such as an outsourcing of prior art search on the efficiency of examination process from theviewpoint of the speed and quality, using the patent level data. In assessing the quality of theexamination, we use the frequency of appeals against the grant and the rejection decisions by
5

the Patent office. Based on the Harhoff and Wagner’s research, we introduce the complexity ofthe examination task and the value of patenting an invention for an applicant, as thedeterminants of examination outcome and the efficiency of the examination. We also control forthe differences among examiners, which would otherwise affect the efficiency of examinationsuggested by Cockburn et al. (2002). After controlling for these factors, we identify thecircumstances where the scope of search view adopted in Japanese examination process is more
efficient to improve the examination performance.
3. Data and descriptive statistics
3.1 Data source
The patent data we use here is obtained from PatR Database provided by ALIFE-Laboratory,
which is constructed from the processing data of JPO (Seiri Hyojunka Data)3 for the purpose ofstatistical analysis. It covers all patent applications filed with the JPO and includes theexamination outcomes. We matched the information on the outsourcing of prior art search andexaminer code provided by the JPO to the patent application data of PatR. We restrict oursample to the applications that were applied and requested for examinations between 1996 and2007, so that we can get almost complete information on the outsourcing and examination
results4.
Japan has an examination request system, under which an examiner undertakes theexamination only after receiving a request for examination from the applicant. The allowable
period of examination request was seven years for the applications filed before September 2001,
and it was reduced to three years for the applications filed after October 2001. Restricting oursample to the applications requested examination by December 2007, we can use information
on most of the final decisions with the latest PatR, though the decisions have not been made fora small percentage of patent applications.
3.2 Examination process
Figure 1 illustrates a brief overview of Japanese examination process. In this paper, we
define the examination duration as the period between the date of applicant’s examination
request and the date of examiner’s final decision, since the information on the starting date of
examination is not available.
[Figure 1]
The database consists of patent application file, registration file, applicant file, right holder file,citation information file and inventor file (see Goto and Motohashi (2007) for detailed explanation).
4 There are many missing values in outsourcing data for the applications requested examination
before 1996. This made us decide to use the data after 1996.
3

6

Within 60 days from the posting date of the notice of reasons for refusal, an applicant can
submit a written argument to explain the difference of the invention from the prior art and canamend the claims to remove the reasons for refusal. Then, the examiner reconsiders thepatentability of the invention. There are no limitations about the number of submissions of thearguments and the amendments.
An applicant can withdraw its application anytime it wants. A withdrawal occurs mainly
when the applicant thinks of its application as non-patentable after reading the examiner’s
negative opinion.
We define the period between the date of the first action (the first notification from theexaminer) and the date of the final decision as the communication period. Note that the prior art
search is basically conducted before the first action. Therefore, communication period is a
useful index to measure not only the speed of examination but also the adequacy of the search,since high quality search should reduce the applicants’ need to communicate with examiners.
When the applicant is dissatisfied with the final decision, she can appeal for reversing thedecision of refusal. Similarly, the third party can appeal for invalidating the granted patent when
they doubt the patentability of the inventions. Note that an applicant has to submit an appeal to
the refusal decision within 90 days from the examiner’s decision, while the invalidation trial canbe appealed at any time by anyone. We assume that the frequency of the appeals measures thequality of examinations.
3.3 Brief overview of overall trend
Responding to the sharp increase in examination requests, the JPO has increased the numberof outsourcing of prior art search. We draw, in Figure 2, the outsourcing rate as a line graph byexamination request year. It is defined as the ratio of the examined applications for which
examiners outsourced the prior art search to the overall examined applications. The bar graphs
are the number of examination requests and the number of outsourcing. Note that the number of
examination requests has almost the same meaning as the total number of examined applications,since most of the applications requested examinations by 2007 had their final decisions.
The outsourcing rate shows a sharp increase from late 1990s to early 2000s. However it has
been stable at about 70% after 2002, which would be partly because of the supply constraint of
the contractors for outsourcing. The allowable period for examination requests was reduced
from seven years to three years for the applications filed after 2001. Therefore, there are
overlaps of examination requests for the applications made before and after the policy change,
which leads to the significant increase in the examination requests during the years following
the policy change, especially between 2004 and 2007, in examination request year in Figure 2.

7

[Figure 2]
Figure 3 and Figure 4 depicts the rate of appeals against the refusal decisions and the rate ofappeals for the patent invalidations by examination request year, respectively. These rates are
the quality indices of examination process, which are the ratio of the appeals to the number ofrefusal decisions and to the number of grant decisions. We also draw the rates separately for theoutsourced applications and for the non-outsourced applications. These figures show that thefrequency of appeals is significantly higher for the non-outsourced applications than for theoutsourced applications5.
[Figure 3][Figure 4]
Figure 5 shows the length of the communication period defined as the monthly length
between the date of the first action and the date of the final decision as line graphs byexamination request year. We divide the sample into outsourced applications andnon-outsourced applications. We also depict the total examination duration as bar graph. We
find that the communication period has been gradually decreasing, while the total examination
duration shows an increasing trend after 1998. This indicates the first action period has been
increasing, due to the increased backlog of pending applications. According to this figure, theaverage communication period is about 7 months for the applications requested examinations in
2007. This figure also shows that the communication period of outsourced applications isshorter than that of non-outsourced applications. This result suggests that the outsourcing
contributes to reducing the number of communications between examiners and applicants.
[Figure 5]
Figure 6 shows the changes in the characteristics of examined applications by examination
request year; the number of claims, the number of IPCs6, the number of inventors and thenumber of related prior arts the applicant referred to in published patent documents. The lastvariable is the number of cited patents by inventors in the description part of the patentdocument, which was specified by text mining in the published documents7. We call thisWe can see, in Figure 3 and 4, the data on appeals is truncated, and we will control for thistruncation problem by introducing year dummies in the estimation model.
6 IPC stands for International Patent Classification. The technical content of patent documents isclassified using the IPC system. We use IPC-class level (3 digits) data, which have roughly 120
categories.
7 The detailed explanation of the data and method is given in Suzuki et al. (2008).
58

variable as the number of inventor citations.
These variables can capture the complexity of inventions and difficulty of the examination
task. According to this figure, the numbers of claims, inventors and inventor citations per
application have been increasing, whereas the number of IPCs included in one applicationshows a decreasing trend. This result suggests that the technological knowledge necessary for
examination has been getting deeper and the scope of a patent has been getting narrower, which
would increase the complexity of examination task.
[Figure 6]
Figure 7 shows the share of the applications simultaneously requested for an examination
with the filing of applications (“rate of simultaneous examination request”) and the share of theapplications for which applicants use the accelerated examination system, by application year.
In Japan, an applicant can significantly reduce the patent pendency period by submitting an
accelerated examination request with no additional fees if the application meets the requirement
to use the system. These indices can reflect the applicant’s need for early patent protection, andwe find it has been consistently increasing over the sample period. This would have been an
additional source of increasing burden on examiners.
[Figure 7]
4 Analytical framework and estimation model
4.1 Analytical framework
We consider the following simple model of the choice of outsourcing of the prior art search.
If the examiner does the search, he incurs the direct labor cost for a search and examination(denoted by ), and the expected psychological costfrom making a wrong decision, wheremeans the probability of making a wrong decision andis the psychological cost. If an

examiner decides to outsource the prior art search, he can avoid doing the initial search, though
he incurs the costs of verifying the search result and of a supplementary search when needed.
We can write the sum of these verification costs and examination cost as, which includes thecommunication cost between the external searcher and the examiner. We assume that theprobability of making a wrong decision
examination task

depends on the complexity of the search andof a patent application, whileandare independent offor8

simplicity .
The following analysis holds even if
independent of .

8

andincreases with , as long as the difference between the two is9Given these assumptions, the expected private cost of an internal search of the prior art isgiven by the following equation (the upper script

stands for internalization of the search):.

internal search:(1)

The expected cost of outsourcing the prior art search for a patent application withcomplexity

is given by the following equation (the upper script

stands for outsourcing of

the search):outsource:,(2)
under the outsourcing.

where the probability of making a decision error is given by

We assume that an examiner has pending applications with mass of 1 indexed byover

0, 1 . According to the search scope view, outsourcing could expand the search scope for priorliterature since the examiner undertakes a supplementary search if necessary. This could
increase the quality of patent examination and would result in the decrease of a wrong decisionby an examiner. On the other hand, according to the synergy view, outsourcing results in lessunderstanding of the invention by the examiner, which will reduce the quality of both tasks.
These two views are not mutually exclusive and both forces work simultaneously. We assume
that the tasks are ordered according to the relative importance of the search scope view. That is,
the size of the reduction of the probability of making an error in examination due to outsourcing) is a monotonic decreasing function of∈ 0,1 , that is, for some tasks integration is

outsourcing is not always better in the range ofbetter:̅ whereis positive for any

negative when

. Moreover, we assume that̅ satisfies

̅

0 for ̅ ∈ 0,1 , andis̅.

We assume that an examiner will decide whether it will outsource prior art search or not, inorder to minimize the total expected private cost, subject to the budgetary constraint on the total
number of outsourcing.
First, we consider the benchmark case where the examiner acts to minimize the aggregate
probability of making errors in examination. This would be the case if there is no difference
betweenandor if the perceived penalty from a wrong decision is very large. If the

maximum budget available for the outsourcing (denoted bysearch for the tasks between 0,) is less than̅, then the prior art

are outsourced and the search for the rest of tasks areinternally done, as illustrated in Figure 8. Therefore, the expected aggregate probability ofmaking an examination error∗

is written as the following equation.

10

∗

(3)

If the budget becomes more generous for outsourcing under the situation that the budget
constraint is binding, the expected probability of making an examination error decreases:
∗⁄

0

̅ .

if

(4)

[Figure 8]̅), only the tasks up to ̅ are outsourced. In thisIf, however, the budget is not binding (case, an increase in the budget does not affect the amount of outsourcing. Thus, if the examiner
behaves so as to maximize examination quality, we will observe only a non-negative effect ofoutsourcing, since the outsourcing is chosen only when it will improve the examination quality.
Therefore, we have the following hypothesis.
Hypothesis 1: Search scope is important at the margin
When an examiner behaves so as to maximize examination quality, an increase in theoutsourcing due to a larger budget results in the quality improvement of examination (that is,smaller probability of making decision errors), if budgetary constraint is binding.
Then we consider the general case where the difference between

andmatters. In thiscase, the examiner will choose outsourcing if the expected cost of outsourcing is smaller thanthat of internal search:. This condition can be rewritten

as the following equation.
/(5)

Thus, the threshold of the complexity where the prior art is outsourced can be expressed as̅ satisfying̅̅/ . This suggests that outsourcing can be choseneven if it increases the probability of making an examination error, when the examiner can0) and the budget available for outsourcing

reduce his private cost by outsourcing ((denoted by⁄) is binding but exceeds

̅ ( ̅

0

if

̅

as shown in Figure 8. That is,
0 and ̅

11

̅ .

(6)

In this case, we have the following Hypothesis 2.
Hypothesis 2: Synergy is important at the margin
If an examiner can save private cost by outsourcing and the budget for outsourcing exceeds
the amount minimizing the probability of making decision errors, an increase in outsourcing
due to an increase in budget constraint decreases the quality of examination (that is, larger
probability of making wrong decisions).
There is a question of how the complexity of an examination task is related to the effect ofoutsourcing of prior art search. An increase in the complexity makes it more difficult for an
examiner to understand the invention but it will also make his search scope narrower relative tothe scope of the invention. Outsourcing can hinder the proper understanding of the complex
invention, even though it helps expanding the search scope for identification of prior art. Thus,
we have the following Hypothesis on the choice of outsourcing.
Hypothesis 3: Choice of outsourcing
If the complexity of the application enhances the benefit of deepening the understanding of
the invention more than the benefit of widening the search scope, outsourcing will be lessused for a complex application.
Outsourcing will also affect the communication period between the examiner and theapplicant. Under the search scope view, relevant prior art is more likely to be identified throughoutsourcing. Therefore, it would generally result in more rapid final decisions, since an
inclusive identification of relevant prior art helps to reach an early agreement on the evaluationof inventive step and the scope of the patent right. When the patent is being granted, theapplicant will not maintain its request for a broader claim unjustified by the combination of thedisclosure and prior art. Therefore, we will observe a shorter communication period for thepatent application resulting in the grant decision. Similarly, if the examiner can present prior art
convincingly denying the novelty of the invention, the applicant will not ask for a second lookbased on a revision of the patent application. Thus, under the search scope view, we can expectthat outsourcing reduces the communication period.
Under the synergy view, outsourcing will reduce not only the efficiency of prior art search
but also the examiner’s understanding of the invention. The former effect on the communication
period is likely to be positive. The latter effect on the communication period is howevertheoretically ambiguous. When an examiner underestimates the novelty of the invention due to12poor understanding of prior art, the applicant will spend more time for making the examinerrecognize that. Thus, the communication period can become longer. On the other hand, whenthe examiner overestimates the novelty of the invention, her decision is biased toward a grant
decision which results in the shorter communication period.
Hypothesis 4: Effects on communication period
Under the search scope view, the effect of outsourcing on the length of the communication
period is likely to be negative, while it is ambiguous under the synergy view.
4.2 Expected effects of the complexity of patent applications and the value of patenting
We expect that the more complex the examination task is, the more communication periods
the applicants and examiners need. Furthermore, we expect that higher complexity of
examination will decrease the quality of examination which would increase the frequency of
appeals against the refusal decision. The effect of complexity of the examination task on thefrequency of appeals for invalidation is not obvious, since the third parties may also face larger
difficulty in bringing its appeal against the validity of the granted patents when the patentapplication is complex.
The value of patenting an invention can depend on the technical quality of the invention andthe complementarity with the firm’s complementary assets. When the value of patenting is high,the applicant has a stronger incentive to obtain a patent protection and to put more resources andtime for that objective, as suggested by Harhoff and Wagner (2009). This will increase thecommunication period for a rejection and the frequency of appeals against refusal decisions.
However, the effects of the value of patenting on the duration to the grant and on the frequencyof the appeals for invalidation are ambiguous. Since the applicant invests more resources forgetting a patent, the duration to the grant tends to be shorter when there is no basic disagreement
between the applicant and the patent office. On the other hand, when a substantive disagreement
exists and the value of patenting is high, the duration to the grant can become long, since theapplicant does not easily give up patenting. If the latter effect is dominant, the duration to the
grant becomes longer. A high value patent is less likely to have ground for invalidation since it
is supported by high inventive step. However, the influence of such patent on the third party’s
business activity should be large, and thus the third party has more incentive to take an action
for invalidating the patent for a given probability of success. If the latter effect dominates, highquality patent is more likely to be litigated.
Table 1 provides a summary of the expected effects of the outsourcing and thecharacteristics of the patent applications on the efficiency of examination when the outsourcing
improves the quality of patent examination (under the search scope view).
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[Table 1]

4.3 Estimation model
Our focus is on the effects of outsourcing on the efficiency of examination which wemeasure by the frequency of the appeals and the length of the communication period.
Furthermore, we build an estimation model which accounts for the effects of the complexity ofthe examination task and the value of patenting of the invention on the quality and the durationof examination.
In order to assess the effects of outsourcing of prior art search on the variations of theperformance indices, we take into account the endogeneity of outsourcing decision. As
Hypothesis 3 suggests, an examiner is more likely to choose outsourcing when the search task isless complex, if the benefit of deepening the understanding of invention is large. At the sametime, the examiner is less likely to make a mistake when the invention is not complex. Thus, theoutsourcing decision is likely to be positively correlated with the examination performance,
which however does not indicate the causal effect of outsourcing. In order to control for thisendgogeneity bias, we employ two-stage least squares (2SLS) regression with instrumental
variables, in addition to introducing the control variables measuring the complexity of an
invention and the examiner fixed effect controlling for his capability and experience.
The estimation model of the second stage is represented by the following
specification (7), and the model of the first stage is expressed by the selection equation(8). In order to assess the impact of endogeneity, we will show the results using a simple
OLS method according to specification (7) in Appendix.
We can test the Hypotheses 1, 2 and 4 with the second stage estimation model (7) as
well as the theoretical expectations shown in Table 1. We can also test the Hypothesis 3
with the first stage estimation model (8).
As for control variables, we introduce the measures representing the difficulty of an
examination task, the value of patenting the invention for an applicant, thetechnological fields and the examiner specific factors (fixed effects). Our estimations are
based on examination data of individual patent applications sorted by examination
request month.

,

,

,

,

∑ ∑ ∑

∗

14

,

∗

, .

(7)

,

, ,

∌,
,

,

∑ ∑ ∑
In these specifications,

,

∗

∗

, .

(8)

denotes the examined patent application andexamination request date (monthly time). The vectors

,

,

and

denotes theare the coefficientparameters.
Considering the potential correlation between variable,

and error term,inequation (7), we implement an instrumental variables estimation as specified by equation (8).
Let

and

denote an examiner and an IPC class for application

requested for an

examination in . As instrumental variables, we use the lagged ratio of outsourcing by examiner
in IPC class(, ,examiners except examiner
Examiner
period, and the lagged IPC-level overall ratio of outsourcing of all
in IPC class

(

∌,

.

’s decision on outsourcing for the applications requested for examinations in

1 do not directly affect the examination performance for the applications requested

for examinations in period , since they are independent applications. Since an examiner isultimately responsible for prior art search, even if it is outsourced, the examiner’s learning fromexamination is not significantly affected by outsourcing per se, especially when we focus on arelatively short time interval. Similarly, the change in the rate of outsourcing of other examiners
is also unrelated to the performance of that examiner. On the other hand, the decision on
outsourcing in period

1 would be highly correlated with the outsourcing rate of thatexaminer in period , due to the rigidity or inertia of budgetary or the other resource allocations
for outsourcing. Similarly, an increase in the outsourcing of other examiners due to the increasein the budgetary or the other resource allocation to a certain IPC class will enable more
outsourcing of any examiner in the same field.
As dependent variables (, ), we use the length of the communication period which is themonthly duration between an examiner’s first action and its final decision, and the dummy
variables reflecting the occurrence of the appeals. The reason why we use the communication
period, not the examination duration, is that our focus is on the length between the starting date
and the ending date of examination. That is, the length of the first action period (between theexamination request and the first action) depends mainly on the backlog and does not reflect theactual examination task. We also differentiate the effects on the eventually refused applications
and eventually granted applications.
Our main focus is on the coefficient of the independent variable,in the second

stage estimation (7). This variable is the dummy variable which set to one if the examiner
outsourced the prior art search for its examination.
15

Moreover, we focus on the characteristics of applications in terms of following two aspects;, ), and (B) the value of patenting the(A) the complexity of the examination task (invention (, ). Harhoff and Wagner (2009) found that the accelerated examination and thenumber of backward citations have significant effect on examination duration. We confirm thisfinding, using the Japanese patent examination data.
In this paper, as an index of the complexity of the examination task and the scope of
invention, we use the number of claims (number of inventors (, ), the number of IPCs (, ), the, ) in an application, and the dummy variable reflecting

whether the patent application is an international application through Patent Cooperate Treaty(, ) and the number of inventor citations (, ).

We measure the value of patenting of an invention by the dummy variable set to one if theapplication is submitted for accelerated examination (forward citations by either applicant or examiner (, ),and the number of, ). Only the patent applications

which have been disclosed can be outsourced. Thus, the prior art search for the applications
requesting early examinations are less likely to be outsourced.
In order to control for the impact of the changes in the magnitude of backlog in eachtechnological field on the length of communication period and on the examination quality, we
introduce the IPC class level (3 digits) backlog variable,

where application, .

The variable

is the logarithm of the total number of examination requests in the IPC classis filed. This variable controls for the changes in the workloads of

examiners and the needs for outsourcing across the technological fields. An increase in backlog
would result in more efforts of the Patent Office to reduce the length of the communication
period, and thereby prevent significant increase in the total length of the examination period. At
the same time, more demand for outsourcing may reduce the marginal opportunity for an
application to be outsourced, if the available supply of external experts on prior art search islimited. These effects would induce a spurious positive correlation between outsourcing and theperformance variables. Moreover, we include the cross term of examiner fixed effect denoted by, IPC dummies denoted byand year dummies denoted by. The 3

digits IPC-class include 121 technological fields.
These control variables aim at removing the spurious correlations between outsourcing andexamination performance and the truncation bias. One potential source of such endogeneity is
the possibility that a capable and experienced examiner, whose examination performance is high,can exploit outsourcing more effectively. Another potential source is that both examination
performance and ease of outsourcing might be high in the technology areas where prior art can
be clearly identified. We use the final decision year dummies as time dummies for theestimation on the occurrence of appeals while we use the first action year dummies for the16

estimation on the communication period so that we can control for the truncation bias as well as
the time trend.
The descriptive statistics used in the estimations are summarized in Table 2.
[Table 2]

5 Estimation results
Table 3 shows the results of 2SLS estimations when we use the occurrence of appeals as
dependent variables. We provide, in Table 4, the results with the communication periods as
dependent variables. These tables provide the results of subsamples of the eventually refused
applications and the eventually granted applications, respectively.
5.1 Choice of outsourcing of prior art searchFirst, looking at the results of the first stage estimation in Table 3 and 4, the coefficients of
instrumental variables are positive and significant. Therefore, we can confirm that theexaminer’s use of outsourcing has inertia and depends on the budgetary constraint allocated to acertain technology field. These instrumental variables work well.
As for the other determinants, we find that the coefficients of the complexity indices except
for the number of inventor citations are negative and statistically significant in all estimation
models. More specifically, the number of claims, the number of IPCs, the number of inventors
and the PCT application dummy have significantly negative effects on the examiner’s decisionon using outsourcing. These results suggest that an examiner uses outsourcing more actively
when the search task is less complex. This supports the Hypothesis 3, indicating the relative
importance of the verification cost for the high complex inventions. The number of inventor
citations can reflect the easiness of identifying the prior art. Thus, this variable could haveinverse relation with the novelty and inventiveness of inventions and the verification cost.
The fact that the complexity has statistically significant effects also suggests that the simple
OLS estimation can overestimate the effect of outsourcing on the examination performance.
We can also confirm that outsourcing is significantly less used when there is a request for
accelerated examination, consistently with the JPO practice.
5.2 Effects on the quality of examination
The results in Table 3 provide clear evidence that the increase in the outsourcing increases
the quality of examination. Outsourcing has significant negative effects on the occurrences ofappeals against both types of decisions, though the significance is relative small for the patent17

invalidation because of the low frequency. According to the results, the probability ofoccurrence of appeal against the refusal decision decreases by about 49% point (the mean is7.9%), and that of appeal for the patent invalidation decreases by about 70% (the mean is
0.12%) if the prior art search is outsourced. These changes are substantial.
Considering the results that the outsourcing is more frequently used for the inventions withlow complexity, our results can support the Hypothesis 1 for the inventions with low complexity
and can support the Hypothesis 2 for the inventions with high complexity. This indicates thatgiving an examiner an option for outsourcing is crucial to improve the quality of examination.
We expect that the increase in the complexity of examination task increases the frequency of
appeals against the refusal decision, since it becomes a source of the discrepancy of the viewson the patentability between examiners and applicants due to the difficulty of identifying
relevant prior art, as shown in Table 1. The results in Table 3 support this expectation.
The complexity of examination task is expected to have an ambiguous effect on thefrequency of appeals for invalidation in Table 1, since it also increases the difficulty for third
parties to question the grant decision. Table 3 shows that the statistical significances for thevariables of complexity are low, which reflect this mutually opposite effects.
Table 3 also shows that high value of patenting, measured by the use of accelerated
examination system and the frequency of forward citations, increases the appeals against
refusals, as expected in Table 1. Both variables are also found to have positive effects on theappeals against grants. These results suggest that third parties challenge high value patents morethan low value patents for invalidations even if the probability of the success of such challenge
is small, perhaps because the relative benefit of challenge is larger for the high value patents.
The effects of accelerated examinations as estimated in Table 3 allow an interpretation, otherthan the fact that the applications requested for early examinations tend to have high values.
From the examiner’s viewpoint, apart from the regular first-in first-out procedure, changing theorder of examinations in responding to the applicant’s request could cause the inefficiency of
examination process. Changing the order of the tasks forces the examiner to adjust thepatentability standard by adopting new priority dates for examinations. This reduces the qualityof examination, which could result in high frequency of appeals for both decisions.
[Table 3]
5.3. Effects on the length of the communication period
In Table 4, the coefficients of the variable,

are significantly negative in all

estimation models. This suggests that outsourcing reduces the necessity of communication
between the examiner and the applicant, which leads to the reduction of the length of18

examination duration. This result shows the large benefit of outsourcing in identifying theconvincing prior art.
We find that higher complexity of examination prolongs the communication period, as
expected in Table 1. More specifically, the numbers of claims, the number of IPCs, the numberof inventors and the number of references have positive effects on the length of thecommunication period in the estimations based on the total sample9. PCT applications also have
longer communication period, which is consistent with the fact that they tend to include
advanced technology and an examiner often has to understand them with translated
documents. These results suggest that the examiners and applicants need more communications

to establish a common knowledge ground for assessing complex applications.
Table 4 also shows that a more complex examination task results in longer
communication period for both refusals and grants, except for the effect of the numberof inventor citations.

We expect that higher value of patenting has a positive effect on the communication period
for the eventually refused applications, while the effect is ambiguous on the eventually granted
applications, from Table 1. This expectation is supported by the results. Both of
and

,

,

have positive effects on the length of the communication period for the

eventually refused applications. On the other hand, not surprisingly, the coefficients of,are negative for the eventually granted applications since they are on the fast

truck though the statistical significance is low. The above results suggest that an applicant has
an incentive to persistently fight against the reasons for refusal when the invention includes
important technological contributions and the value of patenting is high.
The backlog variable at IPC levels has a significant effect but its inclusion does not
significantly affect the coefficients of the other explanatory variables. In particular, an
increasing backlog over time is associated with a shorter communication period, which may
indicate the effort of the patent office to reduce the backlog.
[Table 4]
5.4 Effects of endogeneity of selections
In Appendix, we show the results of OLS estimations, to assess the effects of endogenous
selection of outsourcing. The signs of all independent variables are the same with the results of

The number of references has negative effects when we use the subsamples of the eventually refused
applications and the eventually granted applications, though the coefficient is positive in theestimation based on the pooled data. This is due to the composition effect that the number ofreferences has larger effect on the granted applications that have longer communication period than
the refused applications.

919

2SLS estimations. However, the magnitude of the effect of outsourcing is much larger with OLS
results. This suggests that two-stage estimations correct the overestimation of the effect ofoutsourcing, due to an endogenous selection of outsourcing.
The likely source of such endogeneity is that less complex patent applications are more
frequently outsourced. At the same time, the coefficients of outsourcing are significant, evenafter controlling for this endogeneity.
6. Conclusions
The global surge of patent application causes a great concern not only about the increasing
backlog of pending patent applications in many countries, but also the quality of examination.
The increasing complexity of inventions also aggravates the problem. Under thesecircumstances, the improvement of the efficiency of examination process has been recognized
as an urgent task. Outsourcing of prior art search is one promising solution. Outsourcing may
increase examination quality by expanding the scope of prior art search, while it may also
reduce the quality by weakening the synergy between search and examination. This paper
empirically assesse the determinants of the efficiency of patent examination, with a central
focus on the effect of outsourcing of prior art search. We use a large scale patent examination
data in Japan, involving more than 1.6 million applications requested for examinations from1996 to 2007 for our econometric exercises.
There are two offsetting effects of outsourcing. Outsourcing enables an examiner to takeadvantage of the search ability of the searchers specialized in prior art identification so that thepotential search scope can be expanded. On the other hand outsourcing can hamper the synergy
between search and examination. If examination quality is the predominant concern of an
examiner for the choice of an outsourcing decision and the outsourcing is constrained bybudgetary resources, we expect that an increase in outsourcing enhances examination quality at
its margin. On the other hand, if an examiner can save private cost by outsourcing and thebudget for outsourcing exceeds the amount minimizing the probability of making decision
errors, an increase in outsourcing decreases the quality of examination
Our estimation results show that the increase in the outsourcing of prior art searchsignificantly increases not only the speed but also the quality of examination. We find that theincrease in the outsourcing decreases the probability of appeals against refusal decision by
49.7%, and it also reduces the probability of appeals for patent invalidation by 70.0%. These
results indicate a large benefit of outsourcing on the efficiency of patent examination.
Exploiting the knowledge of the outside searcher specialized in prior art identification

improves the quality of examination, since identifying the adequate prior art is a vital step in thepatent examination process.
20

Our study does not suggest that all of prior art search should be outsourced. We provide theevidence that integration is chosen for complex patent applications, which indicates theexistence of an inherent advantage of integrating search and examination. Our results, therefore,
simply suggest that creating the opportunities for “make” and “buy” choice with respect to priorart search can significantly improve the quality and speed of patent examination.
In these assessments of the effects of outsourcing, we controlled for the endogeneity ofusing the outsourcing, the complexity of examination task for each patent application and thevalue of patenting an invention. We confirmed that more complex patent applications and higher
value of patenting resulted in longer communication period for both grants and for rejections,consistent with earlier related studies. We also found new evidence that more complex
inventions were involved in more appeals against rejections and in fewer appeals against grants,
while higher value of patenting resulted in more appeals against both decisions.
There are important remaining research issues. One is the negative effects of accelerated
examination system on the efficiency of patent examination. Our results allow twointerpretations. One is simply that the patent application requested for accelerated examination
has high value, and thus the applicant put more efforts for patenting. This lengthens the period
to rejection and increases the frequency of appeals. Another interpretation is the effect throughstronger informational constraint on examining the applications submitted to accelerated
examination. If the latter effect is more important, our results imply the necessity ofconsideration on the tradeoff between the applicant’s need for early protection and the efficiencyof examination process, when we design optimal examination system. Clarifying thesemechanisms requires another research.

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22

Figure 1. Definition of examination duration

A. Examination Duration

B. First Action
Period(1)
PatentApplication(2)
Examination
RequestApplicantRequest /Withdraw

ExaminerC. Communication
Period(4)
Final
Decision(3)
First Action

Argument /Amendment /Withdraw
Notification of
Reasons for Refusal /
Grant

23

(5)
Trial
Decision

Appeal against
Decision of Refusal

Refusal /Grant

Figure 2. Outsourcing rate

Outsourcing rate
90.0%
80.0%

number of examination request (right axis)
number of outsourcing (right axis)
rate of outsourcing (left axis)

450,000
400,000

70.0%

350,000

60.0%

300,000

50.0%

250,000

40.0%

200,000

30.0%

150,000

20.0%

100,000

10.0%

50,000-0.0%
1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
examination request year

24

Figure 3. Appeal rate to the refusal decision
14.0%
12.0%

Rate of appeals against the refusal decision
Rate of appeals to the refusal decision
Outsourced
Non-outsourced

10.0%
8.0%
6.0%
4.0%
2.0%
0.0%
1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
examination request year25

Figure 4. Appeal rate to the grant decision

0.25%
0.20%

Rate of appeals for the patent invalidation
Rate of appeals for the patent invalidation
Outsourced
Non-outsourced

0.15%
0.10%
0.05%
0.00%
1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
examination request year26

Figure 5. Examination duration

13.0

Communication Period
Communication period (left axis)
Outsourced
Non-outsourced

12.0
11.0

40.0

35.0

30.0

10.0
25.0

9.0
8.0

20.0

7.0
15.0

6.0
1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
examination request year

27

Total examination duration (months)

Communication period (months)

14.0

Figure 6. Characteristics of examined applications

Characteristics of applications

12.00

Num. of claims
Num. of IPCs
Num. of inventors
Num. of inventor citations

10.00
8.00
6.00
4.00
2.00
0.00
1996

1997

1998

1999

2000 2001 2002 2003
examination request year

28

2004

2005

2006

2007

Figure 7. Applicants’ needs for early patent protection

1.40%

2.50%
rate of simultaneous examination request(left axis)

1.20%

rate of using the acceralated examination
system (right axis)

1.00%

2.00%

1.50%

0.80%
0.60%

1.00%

0.40%
0.50%
0.20%
0.00%

0.00%

application year

29

Figure 8. Choice of outsourcing by an examiner

outsourcing
outsourcing

internal
internal(complexity of invention)
relative advantage of outsourcing
}
={

30

}

Table 1. Expected signs of determinants of the examination outcomes
Frequency of appeals

Communication Period

againstrefusalforinvalidatoin

Total

refusalgrant

under the search scope view

-

-

-

-

-

under the synergy view

+

+

?

?

?

Complexity of the examination task

+

?

+

+

+

Value of patenting

+

?

+

+

?

Outsourcing of prior art search

31

Table 2. Descriptive statistics
Variables

Dependent
variables

Observations

Mean

SD

Min

Max

Communication period (for whole applications)

1667671

8.700

7.566

0

123

Communication period (for refused applications)

753624

6.858

5.417

0

112

Communication period (for granted applications)

797999

8.597

5.961

1

70

Occurance of appeal against the decision of refusal

771958

0.079

0.270

0

1

Occurance of appeal for patent invalidation

10073820.0012

0.035

0

1

outsource

1900807

0.601

0.490

0

1

numclaim

1900807

7.292

9.328

1

999

numIPC

1900807

5.877

8.372

1

1071

numinventor

1900807

2.423

1.676

1

42

PCT

1900807

0.082

0.275

0

1

1900807

1.329

4.191

0

2422

accelerated

1900807

0.013

0.112

0

1

forward1900807

1.439

2.028

0

262

Ln IPCbacklog

1682253

0.593

0.336

0.00

1.00

outrate k, j, t-1

1680988

0.567

0.208

0

1

IPCoutrate j, t-1

1900807

6.230

1.178

Independent
numinvcitevariables

32

0.69315 8.40827

Table 3. Effects on the frequency of appeals
Occurance of Appeals
against the refusal decision
Second stage

outsource

(1)

(2)

-0.039***(-9.71)for patent invalidation

First stage: outsource(2)-0.040***-0.00085*-0.00086*(-10.09)(-1.90)(-1.92)

IPCoutrate j, t-1(2)

Second stage(1)

outrate k, j, t-1(1)

First stage: outsource
(1)

(2)

0.32837***0.325***

0.325***

0.32815***(149.51)(149.72)(166.47)(166.59)

0.295***

0.295***

0.24136***0.24177***(58.27)(58.27)-0.002***-0.002***(56.35)(56.44)-0.00350***-0.00350***

numclaim

0.001***(19.93)(19.76)(-40.12)(-40.07)(0.34)(0.34)(-64.49)(-64.56)

numIPC

0.000***

0.000***-0.001***-0.001***-0.00001-0.00001-0.00041***-0.00041***(4.93)(5.17)(-10.20)(-10.34)(-1.51)(-1.51)(-7.73)(-7.75)numinventor

0.005***

0.005***-0.002***-0.002***-0.00008***-0.00008***-0.00254***-0.00254***(22.23)(22.19)(-8.28)(-8.27)(-3.41)(-3.41)(-9.91)(-9.90)PCT

0.057***

0.057***-0.373***-0.373***0.00006

0.00007-0.42002***-0.42066***(27.45)(27.63)(-191.51)(-191.97)(0.25)(0.27)(-232.35)(-232.88)

numinvcite

0.000**

0.000**

0.001***

0.001***-0.00000-0.00000

0.00099***0.00100***(2.22)(2.04)(7.76)(7.86)(-0.54)(-0.55)(10.07)(10.21)accelerated

0.306***

0.303***-0.500***-0.498***0.01234***

0.01232***-0.51224***-0.51088***(64.18)(63.54)(-83.16)(-82.87)(32.02)(32.03)(-144.51)(-144.25)

forward0.009***

0.009***

0.003***

0.003***

0.00037***0.00037***0.00138***0.00137***(44.87)(44.96)(11.57)(11.53)(20.86)(20.87)(6.91)(6.87)Ln IPCbacklog-0.030***0.022***-0.00021

0.01655***(-20.45)(10.83)(-1.28)(8.98)

Eexaminer*IPC*Year
Observations

0.001***

0.00000

yes

yes

yes

yes

yes

yes

yes

yes

683,429

683,429

683,429

683,429

890,540

890,540

890,540

890,540

0.121

0.120

0.134

0.134

32,51332,51332,51332,51333,32933,32933,32933,329R-squared
Number of exipcfirstyear

0.00000

z-statistics and t-statistics in parentheses*** p<0.01, ** p<0.05, * p<0.1

33

Table 4. Effects on the communication period
Communication Period
Total
Second stage

outsource

(1)

(2)

-0.676***-0.681***(-8.00)(-8.08)outrate k, j, t-1
IPCoutrate j, t-1

Grant decisions

Refusal decisions
First stage: outsource
(1)

(2)

Second stage
(1)

(2)

-0.728***-0.733***(-8.44)(-8.52)First stage: outsource
(1)

(2)

Second stage
(1)

(2)

-0.502***-0.512***(-5.81)(-5.93)First stage: outsource
(1)

(2)

0.279***

0.282***

0.282***

0.288***

0.289***

0.279***(187.37)(187.68)(131.11)(131.43)(124.79)(124.91)

0.193***

0.193***

0.215***

0.216***

0.173***

0.173***(55.23)(55.32)-0.003***-0.003***(41.64)(41.73)-0.002***-0.002***(33.93)(33.97)-0.003***-0.003***

numclaim

0.043***(62.40)(62.40)(-72.72)(-72.77)(46.36)(46.35)(-39.94)(-39.94)(60.29)(60.27)(-59.09)(-59.12)

numIPC0.004***

0.004***-0.000***-0.000***0.011***

0.011***-0.001***-0.001***0.008***

0.008***-0.000***-0.000***(5.73)(5.73)(-7.11)(-7.15)(12.63)(12.64)(-10.66)(-10.75)(11.51)(11.52)(-5.52)(-5.53)numinventor

0.113***

0.113***-0.003***-0.003***0.079***

0.079***-0.002***-0.002***0.040***

0.040***-0.003***-0.003***(32.58)(32.58)(-14.36)(-14.32)(21.24)(21.23)(-7.98)(-7.94)(11.83)(11.82)(-9.83)(-9.83)PCT

3.762***

3.762***-0.377***-0.377***2.996***

2.996***-0.365***-0.366***3.508***

3.508***-0.397***-0.398***(94.60)(94.60)(-293.63)(-294.15)(73.33)(73.35)(-187.92)(-188.31)(84.08)(84.07)(-210.48)(-210.73)

numinvcite

0.032***

0.032***

0.001***

0.001***-0.007***-0.007***0.001***

0.001***-0.013***-0.013***0.001***

0.001***(22.86)(22.83)(9.17)(9.41)(-3.51)(-3.53)(8.57)(8.72)(-10.49)(-10.58)(7.04)(7.15)

accelerated-0.521***-0.530***-0.505***-0.503***

0.129

0.120

-0.508***-0.505***-2.733***-2.750***-0.511***-0.510***(-7.71)(-7.87)(-174.26)(-173.68)(1.46)(1.36)(-86.64)(-86.15)(-42.52)(-42.90)(-133.95)(-133.75)

forward0.156***

0.156***

0.002***

0.002***

0.084***

0.084***

0.003***

0.003***

0.037***

0.037***

0.002***

0.002***(55.64)(55.65)(12.37)(12.38)(24.54)(24.54)(9.99)(10.01)(14.29)(14.29)(7.30)(7.30)Ln IPCbacklog-0.079***0.043***

0.024***(-3.08)Eexaminer*IPC*Year
Observations

0.033***-0.065**(17.07)0.045***-0.160***0.031***(-2.42)0.045***

0.016***(-6.28)(15.43)(7.48)

yes

yes

yes

yes

yes

yes

yes

yes

yes

yes

yes

yes

1,474,552

1,474,552

1,474,552

1,474,552

667,175

667,175

667,175

667,175

705,298

705,298

705,298

705,298

0.117

0.117

0.109

0.109

0.126

0.126

35,13935,13935,13935,13930,59330,59330,59330,59331,49731,49731,49731,497R-squared
Number of exipcfirstyear

0.033***

z-statistics and t-statistics in parentheses*** p<0.01, ** p<0.05, * p<0.1

34

Appendix. Results of OLS estimations

Occurance of Appeals
against the refusal decision

Communication period

for patent invalidation

Total

Refusal decisions

Grant decisions

(1)

(2)

(1)

(2)

(1)

(2)

(1)

(2)

(1)

(2)

-0.0162***-0.0166***-0.00067***-0.00068***-0.961***-0.962***-0.817***-0.818***-0.601***-0.602***(-19.68)(-20.09)(-7.53)(-7.54)(-68.33)(-68.41)(-53.36)(-53.46)(-43.22)(-43.30)0.0008***0.0008***0.00001

0.00001

0.043***

0.043***

0.033***

0.033***

0.045***

0.045***(23.39)(23.25)(1.62)(1.63)(69.32)(69.32)(51.37)(51.36)(69.75)(69.78)

numIPC

0.0003***0.0003***-0.00001-0.00001

0.005***

0.005***

0.012***

0.013***

0.009***

0.009***(5.80)(6.11)(-1.47)(-1.47)(7.09)(7.10)(14.73)(14.75)(13.11)(13.12)numinventor

0.0046***0.0046***-0.00009***-0.00009***0.110***

0.110***

0.077***

0.077***

0.038***

0.038***(23.29)(23.28)(-4.02)(-4.02)(33.61)(33.60)(21.84)(21.83)(11.76)(11.76)PCT

0.0663***0.0672***0.000120.00013

3.671***

3.673***

2.989***

2.991***

3.463***

3.466***(48.83)(49.54)(0.76)(0.80)(162.89)(163.01)(120.95)(121.03)(154.19)(154.38)

numinvcite

0.0002*0.0002*-0.00001-0.00001

0.033***

0.033***-0.006***-0.006***-0.014***-0.014***(1.93)(1.72)(-0.76)(-0.78)(24.30)(24.26)(-3.33)(-3.36)(-11.74)(-11.85)

accelerated

0.3154***0.3124***0.01353***

0.01352***-0.622***-0.630***

0.101

0.092

-2.747***-2.761***(78.61)(77.86)(46.05)(46.05)(-12.75)(-12.94)(1.42)(1.29)(-63.24)(-63.62)

forward0.0085***0.0085***0.00035***0.00035***

0.158***

0.158***

0.083***

0.083***

0.038***

0.038***(46.69)(46.79)(20.34)(20.35)(59.54)(59.54)(25.62)(25.62)(15.28)(15.28)outsource
numclaim

Ln IPCbacklog-0.0311***-0.00015-0.089***-0.083***(-22.90)(-1.00)(-3.73)(-3.33)Eexaminer*IPC*Year-0.158***(-6.61)

yes

yes

yes

yes

yes

yes

yes

yes

yes

yes

Observations

771,948

771,948

1,007,376

1,007,376

1,667,671

1,667,671

753,624753,624

797,999

797,999

R-squared

0.020

0.019

0.003

0.003

0.034

0.034

0.043

0.043

0.056

0.056

Number of fixed effects

42,164

42,16446,06046,06053,692

53,692

40,46940,46942,90642,906t-statistics in parentheses*** p<0.01, ** p<0.05, * p<0.135