Hitotsubashi University
Institute of Innovation Research

An Economic Analysis
of Deferred Examination System:
Evidence from Policy Reforms in Japan

Isamu Yamauchi
Sadao Nagaoka
IIR Working Paper WP#14-05

Jun. 2014

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

An Economic Analysis of Deferred Examination System: Evidence
from Policy Reforms in Japan†

Isamu Yamauchi
Research Institute of Economy, Trade and Industry

Sadao Nagaoka**Institute of Innovation Research, Hitotsubashi University

June 2014

Abstract
We investigate how a deferred patent examination system promotes ex-ante screening ofpatent applications, which reduces both the number of granted patents and the use of
economic resources for examinations, without reducing the return from R&D. Based on areal option theory, we develop a model of examination request behaviors. Exploiting the
responses of Japanese firms to recent policy reform, we find that the shortening of theallowable period for an examination request significantly increases both eventual andearly requests, controlling for the blocking use of a pending patent application. This effectis stronger in technology areas with higher uncertainty. These results support theimportance of uncertainty for an applicant and of ex-ante screening.

JEL classification numbers: C41, L21, O34
Keywords: patent, examination, option value, fee structure, R&D† We would like to thank conference and seminar participants at the Far Eastern Econometric Society

Meeting, Ludwig-Maximilians-Universitat, the European Patent Office, the U.S. Patent Office, and theGeorgia Institute of Technology. This paper is partly based on research conducted for a study commissionedby the Japan Patent Office (JPO) that was undertaken by the Institute of Intellectual Property (IIP). We
would like to thank the participants in that study for insightful comments. We would like to express our
gratitude to Paul Jensen for his great help in improving our paper. We are also grateful to four anonymousreferees for their helpful comments.

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
Unlike the United States Patent and Trademark Office (USPTO), the Japan Patent Office(JPO) and the European Patent Office (EPO) only examine patent applications after
receiving formal examination requests from applicants. In Japan, if such a request is notreceived within three years of the date of the application, the application is deemed to bewithdrawn. Under the first-to-file system, an inventor has an incentive to file his patentapplication as soon as possible. Therefore, inventors apply for a patent on even such an
invention that has significant uncertainty in patentability and in the probability of its
commercialization. Examining all applications has two important economic costs. First, it
increases significantly the number of patent grants. Such grants constrain third parties
without increasing the ex-ante profit of an applicant from its R&D. Second, economic
resources are used for more examinations. Under the recent environment of “patent
explosions,” increasing patent applications place strains on the patent office, which can
result in longer pendency periods and a higher probability of mistakes in grant decisions.
A deferred examination or an examination request system provides an importantmechanism reducing these social costs. It does so by providing patent applicants withmore time to screen their inventions before requesting examinations. Such anarrangement is likely to be especially important when uncertainty in commercialization2

is high. In this regard, what ultimately matters for a firm in seeking patent protection is
not the technical quality of an invention per se but the value of patenting such invention,
which depends on a number of factors, including the availability of complementary assets.
For many inventions, the resolution of uncertainty in the value of patenting can take along time.1 However, the examination request system may also induce applicants to use
pending applications, even if they do not meet patentability standards, to block
third-party innovative investment. An examination request by a third party may notadequately prevent this blocking use of pending applications.2
Thus, a trade off may well exist in introducing or designing a deferred examination
system: a longer examination request period enhances the ex-ante “screening effect” ofexaminations, thereby decreasing the number of patent examinations (as well as patent
grants) and reducing the burden on a patent office, while increasing the “blocking effect”
of pending applications. Perhaps reflecting this tradeoff, not all countries have adopted
an examination request system, and the allowable period for examination requests varies

A telling example is a drug patent. In the pharmaceutical industry, firms often need more than ten years
after filing a patent to introduce a new drug into the market. Uncertainty is gradually reduced throughlaboratory testing, preclinical testing, and clinical trials.
2 A third party can request an examination and will do so if it benefits from an early clarification of thepatentability of pending applications are greater than the cost of requesting an examination. However, theindividual benefit for a third party may not be large, when the possibility of being blocked is relatively small,the cost of developing a circumventing invention is small, or the invention may not immediately be used. Still,
the collective benefit for third parties from early clarification can be significant. However, even if that is thecase, a free rider problem among third parties for examination requests makes it difficult to realize suchaggregate benefits.
13

among patent offices. In particular, all patent applications are automatically examined at
the USPTO, although there have been debates on whether the U.S. should also introduce
a deferred examination system.3 Moreover, concern over pending applications led in 2001
to the reduction of the allowable period for examination requests from seven to three
years in Japan.
A comprehensive economic analysis of the deferred examination system does not exist.
This paper provides both a theoretical model for such a system, based on a real option
theory and an empirical validation of the importance of the ex-ante screening effectpredicted by the model, by examining the responses of Japanese firms to this policychange. Our theoretical model explains why applicants might delay examination requests
in an environment in which new information arrives in the future, with particular focus
on the importance of the screening effect. We take into account the blocking value of apending application, although we do not model the interactions between firms. We
analytically solve the model and provide comparative statics results on how the
maximum length of the pending period affects the volume of examination requests andtheir timing. In particular, we show theoretically that examination requests increase

On January 28, 2009 the USPTO solicited public comments on whether a deferred examination procedure
should be introduced in the US.

34

with the reduction of the maximum pending period more in sectors where ex-antescreening is important and that ultimate examination requests are not affected by theblocking value of pending applications.
Our empirical analysis seeks to validate these theoretical results. The reduction of
the allowable period for Japanese examination requests from seven to three years in 2001
provides us with a unique exogenous shock, which affects the amount of information thatan applicant can use in making an examination request decision. Utilizing the panel dataat the monthly and individual patent application levels, we can control for demand,technology, and patent system changes over time, when we identify the effects of thepolicy change. We can also control for the importance of blocking motivations of pending
and granted patents in our estimations.
The rest of the paper is organized as follows. Section 2 presents a survey of related
studies. In Section 3, we provide an option-based theoretical model and develop
hypotheses grounded on comparative statics results. Section 4 describes the dataset andprovides the empirical results. Section 5 concludes the paper, discussing the policy
implications of our analysis.

5

2. Related Studies
A patent renewal decision is similar to that of postponing a patent examination request,
in the sense that both involve the evaluation of option values. Our research addresses
related but distinct questions, compared with the existing studies on patent renewals.
Pakes (1986) is a pioneering paper, which develops the option theory of patents andassesses the value of patent protection from patent renewal data. In his model, theunderlying stochastic process of patent renewal incorporates the possibility of discovering
the zero value of maintaining a patent for an invention, the decay of the current return,and some probability of innovation (a multiplicative increase of the return). He estimates
the parameters characterizing the above stochastic process by using historical patent
renewal data in three patent offices (France, Germany, and United Kingdom).4 Although
his model is very general, the research focuses on the calibration of the model to thepatent renewal schedules in order to derive the statistical distribution of patent values.
Furthermore, in his paper, analytical solutions are not provided; thus, comparative
statics are not available. Our research addresses ex-ante screening of patent examination,
which can avoid the tradeoff between the number of granted patents and the profit from
Using Pakes’ approach, Deng (2007) analyzes the changes in the value of patents after the establishment of
the EPO. She suggests that the harmonization of the patenting process in the EPO reduced the differences in
the patent value among these countries, while the changes in patent length and renewal fees had only modest
effects on patent value.

4

6

R&D and it can reduce the use of resources for examinations. We provide analyticalresults on the effect of shorter deferral period on examination requests from comparative
statics and their empirical assessments.
Cornelli and Schankerman (1999) and Scotchmer (1999) focus on renewal fees as
instruments for socially optimal patent protection.5 They show that policy makers canmaximize social welfare by setting renewal fees to make firms choose optimal patent
lengths. Scotchmer suggests that firms honestly reveal their willingness to pay under theeffective renewal fee (or subsidy) structure, when the value and the cost of innovation
have positive correlations. In both analyses, a firm knows the private value and the costof an invention, while the government does not, and the renewal fee schedule works as arevelation mechanism. In comparison, this paper focuses on the uncertainty for the firm.
In our model, the firm itself does not know the value of patent protection for its invention
so that the pendency period before the examination request allows the firm to accumulate
information for its decision on patenting. The policy issue addressed is also different: theoptimal length of patent protection vs. ex-ante screening for patent examination.
Regibeau and Rockett (2010) analyze the relationship between the examination

There are seminal papers that examine the influence of patent breadth and patent length on the innovative
activities of firms or social welfare, such as Gilbert and Shapiro (1990), Matutes et al. (1996), andO’Donoghue et al. (1998).

5

7

duration of the patent office and the importance of patents. They assume that the
duration of a patent examination is endogenous to the effort of the applicant and that its
accuracy improves as technology matures. They show that the more important inventions
are examined earlier and that over time the examination duration decreases for good
applications and increases for bad applications, all things being equal. Their framework
includes an information asymmetry between applicant and examiner regarding thepatentability of the application. The applicant changes the amount of the effort that heexerts in the examination process according to the importance of applications so that apatent is granted earlier to its more important invention. Our model focuses on theapplicant’s learning process of the application value and analyses the screening effect of
the examination request system, while we do not consider the examiner’s learning.
Harhoff and Wagner (2009) also find that potentially valuable patents will be granted
earlier and that a withdrawal of such patents will be delayed. Further, they indicate thatapplications with complex examination tasks (a large number of references, claims, andso on) are withdrawn earlier by applicants during the examination process. Moreover, theapplicant becomes more cooperative in this process when the value of an invention is
high.

8

A few studies investigate the applicant’s behavior for delaying an examination
request.6 Using a matched sample of patent applications filed simultaneously in four
patent offices, Palangkaraya et al. (2008) show that the timing of examination requests
for the same patent application varies among countries because of differences in theallowable periods. They argue that applicants may use their private knowledge about thepatentability of their inventions to constrain the R&D activities of rival firms by delaying
the decision on the examination request. Henkel and Jell (2010) analyze the applicant’s
incentive to defer the examination process, focusing on the request behavior of German
patent applicants. Based on interviews and surveys of inventors, they find that both the
motivations of “gaining time for evaluation” and “creating insecurity” are significantly
negatively correlated with early examination requests.7 Although these studies provide
important insights, they do not offer an underlying theoretical model or an empiricalverification of the importance of uncertainty, based on an exogenous shock. Our model
provides such an analysis, while taking into account the blocking use of a pending
application.

Sampat (2011) suggests that the applicants have an inventive to contribute more to the prior art searchwhen the inventions are more important for them.
7 Koenen and Peitz (2011) also emphasize the importance of a blocking motivation for the applicants(creating insecurity).
6

93. A Theoretical Model
3.1 Framework
We use a simple two-stage model (1, 2), where a firm has two chances to decide

whether it requests an examination for its patent application.8 The first chance is thedate of the patent application (1), and the second chance is the end of the allowable

period of the examination request (2). In this paper, we ignore examination requests

by third parties, even though they are possible under the Japanese or European patent
laws, since we focus on the ex-ante screening of an applicant.
We assume that an applicant does not know the true (private) economic value ofpatenting his application ,. The true value

consists of two parts: the part known

ex-ante (we interpret this as the quality of technology and denote by) and the part

unknown ex-ante (we interpret this as the market size and denote by). That is, anapplicant knows its technological quality but not its future market size. We assume thatvariableis uniformly distributed over the range

1, 1 with

0, without a lossof generality. We can write the true economic value of patenting an application as.

(1)

The option right, such as a patent renewal right and the right for an examination request, is an American
option that can be exercised at the any time before the expiration date. Unlike European option, it is quitedifficult to solve the equilibrium values of American option in general form, and thus, past studies haveresorted to a simulation analysis. Instead of a simulation analysis, we will develop a simple two-stage modelso that we can conduct a comparative statistics.

810

In each stage, the firm decides whether to request an examination, based on thesubjective value of patenting its application (denoted byapplication’s true value, ),without knowing the. At the date of the patent application, when the firm has no

information about the market size, the expected value of patenting the application of thefirm is given by.

,

By delaying the decision of the examination request, the firm may obtain a signal
from nature. The signal in the second stage can narrow the gap between the firm’s initialexpectation regarding the subjective patenting value

and the true value

so thatthe firm revises its expectation. We write this signal in the second stage as follows:

,

where

,

(2)

represents a noise with E

0.

A firm can only estimate the amount of the necessary revision of its expectation, since
it cannot directly observe the exact correction
estimator of the optimal revision,

to be made. The efficientis given by

∙ ,
where

(3)

measures the preciseness of the signal’s information. It is given as the ratio ofthe variance of a true signal,

to the variance of noise

11, that is,

1/ 1

. Variable/(

depends on the allowable period of the examination request), since the available information increases with the increase in the period.

Furthermore, the amount of information available during the pendency period differs
depending on the sector-specific uncertainty (denoted by ). Therefore, we can write,. We assume that

respect to0 and0, whereis the derivative of, . We also assume that the marginal effects of

and

as
with

are independent:

0.
The subjective value of the firm’s applicationin each stage,

is represented asfollows:
(4)

,

,

1

,

Let us denote the maximum length of the patent protection as(5). Our model analyzes

the firm’s behavior after its filing of an application. Therefore, we take the firm’s patentapplication behavior as exogenous. If the firm requests an examination in the first stage,
it can enjoy patent protection for

periods. However, by delaying the decision to the nextstage, the firm can acquire additional information about market size. Considering thistradeoff, the firm decides whether it will exercise the examination request option. In the12case where the firm requests an examination in the second stage, the length of the patent
protection becomes
Let

and

,

.9
denote the examination request fee to be paid at the beginning of thestage and the expected present value of the patent protection when the patent is granted
at period , respectively. In this model, we assume that the discount factor is equal to one.
The firm can obtain the blocking value from a pending application denoted by(net present value) in the first period by delaying its decision, although in the second
stage the blocking value of a pending application disappears because of the clarification ofright. Naturally, the exclusive power is larger when the invention is protected by thepatent (,). Note that the value of patent protection includes the blocking value of a

granted patent, whilemeasures only the blocking value of a pending application.

The blocking value of a pending application increases with the length of the pending
period, but it is assumed to be independent ofbenefit of pending application, . For simplicity, we assume that theincreases proportionally with the length of thepending period.

In a model with continuous time, the length of patent protection depends on the waiting period of an
applicant. Specifically, an applicant decides on the optimal delay by considering what amount of information
should be accumulated. In this continuous time setting, the essence of the applicant’s decision under theexamination request system remains the tradeoff between the length of effective patent protection and theamount of information to save the cost of patenting. Our two-period model is simple but is meant to capture
this essential tradeoff for the applicant.

9

13

,
where

(6)

is a constant value.

For simplification, we assume that all applications that request examination are
granted.10 Our model also assumes that the value of lapsed applications is zero. Then,the value of application,in stage ,

,

,

,

, 0

, , is given by the following equation:

1

,

.

2

(7)

Equation (7) implies that the present value of the right of an examination request
becomes whichever is greater: the expected profit of requesting an examination in stage 1or the expected present value of the right in stage 2, with delaying the decision. The
expected present value of a granted patent at the second stage
the period,

becomes longer, since the patent protection period is,

becomes smaller as.We can defineby the following equation, using the subjective value of application

renewal fee,,

and the

:
, ,

1 ,

≡

1

,

,

1, 2.

(8)

3.2 Solution
The result does not change if we assume that the probability of a grant is an exogenous variable. We canalso consider the case in which the probability of a grant is a function of the technological quality, i.e.,.
In this case, the main results would not change, since the value of requesting an examination is an increasing
function of the grant rate, although the calculation becomes quite complicated.

10

14

To solve the model, we can write firm ’s decision-making problem in stage
following equations, where,

1 means that firm,

as therequests an examination and0 means that the firm does not request it.

Given

,

1
0

,

1
0

0

,

.

,

,

, let us denote the critical value ofequation (9) by

(9)
.

(10)
satisfying

0 in

,

. Then, the applications whose signal is sufficiently large () are,

on average, the subjects of an examination in the second stage. Similarly, given thecritical value of the initial expectation

satisfying

applications with technological quality higher than

,

(

,

, the

, are, on average, thesubjects of an examination in the first stage (we formally show later that the applicant
requests early examination, or,

1 in equation (10) is more likely to be satisfied, if

the invention quality is above this line, as Lemma 1 in the next section). We can define
these critical values (and) by the following equations.
,

(11)
.

In equation (12),(12)

indicates the probability that the applicant will request an

15

examination in the second stage (Pr). The square bracket at the right hand side ofequation (12) is the conditional expected value of patenting the application:. Note that the conditional market size of the applied patent is,given by.

We assume that the applicant always requests an examination, if he cannot use any
information (0).

Assumption 1:

0 or, equivalently,

0 , for any

underconsideration.
The two conditions of this assumption are equivalent from equation (11). The
condition

0 indicates that the firm will request an examination, even if it receives

some negative news on the size of the market in the second period.
The parameter restrictions imposed by Assumption 1 is represented in Figure 1. In
this figure a negatively sloped line (hereafter called “market size threshold”) represents
equation (11) and the horizontal line with(hereafter called “invention quality

threshold”) represents the solution of equation (12). Note that the applicant who made an
early examination request cannot withdraw its request, even if he receives the negative
signal on the market size in the second stage. The area above this invention quality

16threshold represents the set of the combinations of the two parameters, for which earlyexamination requests are made. The area between the invention quality threshold andthe market size threshold represents the set of the combinations of the two parameters
for which late examination requests are made. The aggregation of these two areas
represents the parameter combinations where the eventual examination requests are
made.
[Place Figure 1 approximately here]

3.3 Comparative Statics
In this section, we analyze the impacts of the changes in the exogenous variables on thecritical levels

andand thereby on the examination request profile. First, we show

the effects of shortening the allowable period of the examination request on the rate ofeventual examination requests. Thus, we examine the effects of the decrease offor a given

on

.
/

0,

(13)

The reduction of the allowable period has two positive effects on the rate of eventual
examination requests. The first effect is derived from increasing the period of patent17

protection:
the available information:/. The second effect is generated from the reduction of; it is also positive if the expected patenting value

is sufficiently large (Assumption 1 holds), so that

0. Longer patent protection

increases the value of patenting, and the reduction of the available information makes it
more difficult to screen out low-quality applications (that is, the applications, which have
only low patenting values) for examination. As shown in Figure 1, the negatively sloped
market threshold line has a lower intersect with the vertical axis and also rotates in the
direction of left-hand side with the reduction of. Therefore, shorter allowable period

results in the increase of the area where the eventual examination requests are made.
Note that the blocking motivation of a pending application (denoted by) does notaffect the firm’s behavior with regard to eventual examination requests, and thus, itsvariation does not alter the effects of the above policy changes on the rate of eventual
examination requests.

Proposition 1 (eventual examination request)(a) The reduction of an allowable period for examination requests decreases the average
quality of applications requested for examination (18⁄

0 for any given), whichimplies the increases of eventual examination requests.
(b) The blocking motivation of a pending application does not affect the firm’s behavior
with regard to eventual examination requests

Second, we examine whether the impact of the shortening of the period of examination
request is affected by the degree of sector specific uncertainty ( ), under Assumption 1.
/

0.

(14)

Equation (14) suggests that the impact of the policy change increases with the degree of
uncertainty under Assumption 1. In the technology field, where the degree of uncertainty
is high, the decrease in the amount of information makes it more difficult for the firm toassess the value of its application during the allowable period. This increases the firm’s
incentive to request an examination. Again, the blocking value of a pending application
does not affect the magnitude of the impact of policy reform on eventual examination
requests.

Proposition 2 (uncertainty)
A higher degree of uncertainty increases the effect of the shortening of the allowable19

period on eventual examination requests.

If Assumption 1 does not hold, and

0 for any

under consideration, a firm will

not request an examination, unless it receives good news on the market size. In such case,the reduction of information tends to increase the threshold of requesting an
examination—that is,is negative. If this effect is sufficiently strong, theshortening of the allowable period decreases eventual examination requests and such aneffect can be larger in the sector with high uncertainty, contrary to the prediction of
Proposition 2.
Last, we analyze the impacts of policy changes on the rate of early examination
requests. Note that the value of an early examination request is not directly affected by
the length of the allowable period, since the firm’s decision is simultaneously made withthe patent application. However, the changes of the option value of an examination
request affect the firm’s decision in the early stage. Denoting the right hand side ofequation (12) by RHS, which is a function of
LHS, which is a function of only

,

,

and

, and the left hand side by, we have the following relation.

.

(15)

20

First, we show that the denominator of the equation (15) is positive. This is because
, ∀

1

∈

(16)

1,1 . 11This result implies that the value of an early examination request increases more rapidly
with the technical quality of an invention than with that of postponing the request. Thus,
we have the following lemma:

Lemma 1
A firm requests for an early examination for high quality inventions.

) depends only on that of

Furthermore, the sign of equation (15) (, since0.

,since the effect of the marginal change ofeffects of marginal decrease of(17)

has no effect from equation (11).12 Thus, theon the expected option value of postponing the. Substituting

11

from equation (11), we have1.

can be rewritten as

12which is 0 from equation (11).

21,examination request to the second stage () can be decomposed into three effects. The

first effect (negative) stems from the decrease in the amount of information available for0. Thethe applicant, expressed by the second term in the bracket:

applicant discounts more significantly the news on the market size, which is on the
average positive. The second effect (negative) is from the decrease in the blocking value ofa pending patent application, represented as the last term:

0. The last effect(positive) is derived from the increase in the value of protection of the invention becauseof the longer protection period for the patent whose examination should be requested in
the second stage, expressed as the first term in the bracket:

0. 13

Therefore, we find that the reduction of the allowable period increases the rate of theearly examination request by reducing the invention quality threshold (the amount of information of the signal is large, i.e.,of a pending application is large; that is,0), if (a)is large or (b) the blocking value

is large. In Figure 1, such effect isrepresented as the downward shift of the horizontal invention quality threshold line.

Proposition 3 (early examination request)

13 It is important to note that this is clearly an artifact of the model, since in the continuous model, a firm canchoose to request an examination at any time during the deferral period.

22

The shortening of the period of an examination request decreases the average quality of
inventions subject to early examination (⁄0), or, equivalently, it increases therate of early examination requests, especially in the sectors where the importance ofscreening () is high, or the blocking value of a pending application ( ) is large

The expected effects of policy changes are summarized in Table 1.
[Place Table 1 approximately here]

4. The Data
4.1 The examination request system and policy reform in JapanThe examination request system was introduced to Japan in 1971. An examination
request is made for each patent application. 14 It can be made by anyone and isirrevocable. We estimate that the third parties account for around 0.5 % of theexamination requests made during the sample period. As indicated above, the maximum
pending period was reduced from seven to three years in 2001.15
14 Before the introduction of the multiple claim system in 1988, most patent applications included only one
claim. The number of claims per application has been increasing since 1988. We control for the number ofclaims in our estimation, since it could affect the examination of request behaviors.
15 Following this policy change, the JPO fee structure was revised in 2004, so as to increase the examination

23

4.2 Data collection
We use two types of data: patent data and financial accounting data. Our patent data is
obtained from IIP Patent Database (IIP-DB)16 and Industrial Property Digital Library(IPDL). The accounting data is from the NEEDS Database, provided by Nihon Keizai
Shimbun, Inc. We have employed the IPDL to extend the examination request data in
IIP-DB until December 2008. 17 Therefore, in our dataset, all applications filed by
December 2005 have exhausted their allowable examination request periods; thus, there
are no truncation problems. We restrict our analysis to the firms that were publicly
traded from 1986-2005 and that disclosed their R&D expenses during this whole period(704 firms). We matched patent data to these firms, using their harmonized names andaddresses. As a result, the final number of sample firms is 697. Our sample covers, on
average, about 50.6% of all patent applications in Japan from 1986 to 2005.
Our estimations are based on individual patent application data. We define our focal
explanatory variables on uncertainty at the International Patent Classification (IPC)

request fee to the level of the marginal cost, while reducing annual fees (and application fees) in order tomaintain revenue-neutrality. This increased the total expected cost of patenting for “low-quality” inventions
and decreased such cost for “high-quality” inventions, where we measure the quality of patent applications by
the probability of them being granted and the average length of their maintenance periods, once granted.
16 IIP-DB is provided by Institute of Intellectual Property and A Life-Laboratory. It covers the patents filedwith the Japan Patent Office, and consists of patent application files, registration files, applicant files, rightholder files, citation information files, and inventor files. The detailed explanation of IIP-DB is given by Gotoand Motohashi (2007).
17 The last publication date of the application included in IIP-DB is the end of May 2008. IPDL offers the
public access to IP Gazettes of the JPO through the internet.

24

class (roughly 120 IPC classes) level. We will compare the magnitude of the effect of policy
reform on the examination request decision for the patent applications in the IPC classes
with higher uncertainty and for the other IPC classes. We use monthly (not yearly) datain order to identify the impact of the reforms of the examination request system, which
took place in October 2001; we introduce IPC by year dummies as control variables in ourestimations. The last application month of our patent data is December 2005.
For the dependent variables, we use two dummy variables: “eventual examination
request” dummy and the “early examination request” dummy. The variable “eventual
examination request” represents whether the firm eventually requests an examination
for the application within the allowable period. The variable “early examination request”
indicates whether the firm makes an examination request at the same time as the date ofpatent application.

4.3 Brief overview of overall trend
We start with some descriptive information about our dataset. Figure 2 shows thenumber of examination requests of our sample in 2005 by elapsed months from the dateof application. The profile of examination requests had two peaks over the deferral period25

in Japan. The first peak was close to the date of application. The second, bigger peakoccurred around the end of the allowable period of examination requests. This isconsistent with the framework of the theoretical model discussed above.
[Place Figure 2 approximately here]
Figure 3 illustrates the rate of eventual examination requests, the total number ofapplications, and the average number of claims of those applications by application
year. 18 We draw this figure from patent application-level yearly data, although ourestimations are based on monthly data. The rate of eventual examination requests showsa gradual but substantial increase of around 15 % points from 1988 to 2001, with anincrease in the number of claims per patent, while the rate shows a jump in 2002. Ourlater econometric analysis finds that these changes significantly reflect the gradualincrease of the number of claims and the shortening of the period of examination request
in 2001.
[Place Figure 3 approximately here]
Table 2 reveals the changes in the rate of eventual examination request by industries
from September 2001 to October 2001 for the top five and the bottom five industries.19

Note that the number of applications and examination requests are fractionally counted by the number ofapplicants in this paper, so as to avoid the double counting of the co-applied patents.
19 In Table 2, we ignored the industry where the average number of applications is lower than 20.
18

26

The rate of eventual examination requests in the pharmaceutical industry was, on
average, 50.3 % for the applications filed in September 2001, and it increased to 76.5 %for those filed in October 2001. Table 2 indicates that the impact of the reduction of theallowable period for examination request is larger in the industries where the degree of
uncertainty about the value of patenting is high.
[Place Table 2 approximately here]
Table 3 indicates the grant rate (the ratio of the number of granted patents to thenumber of applications) in 1998 and in 2002. Given the introduction of the new policy in
2001, the final date of the allowable period of examination requests in both application
years was 2005. We find that the grant rate significantly increased (up by 4.5 % points
from 32.7 %) after the reduction of the available period of examination requests. This
indicates that the reduction of the deferral period increased examination requests, which
in turn led to more granted patents.
[Place Table 3 approximately here]

4.4 Estimation framework
We estimate the following equation to analyze the effects of the policy reform on the27eventual and early examination request decision.

,

,

∑ ∑

and

,

∑ ∑

,

In this specification,patent application,

,

and

, and

(18)

denotes the firm that filed thethe main IPC class of the patent applications,
,

,

, .

,

denotes a patent application,

the yearly time. The vectors

variables,

the monthly time,

are the coefficient parameters. The

are IPC dummies and year dummies. We introduce the cross term offirm dummies and IPC dummies, ∑ ∑dummies and year dummies, ∑ ∑,and the cross term of IPC. We include these dummy variables,

so as to control for the potential biases due to firm-specific differences in the patenting
propensity and sector-specific differences in the importance of patenting. With thesecontrol variables, we can partially control for the variations of quality of applications
across firms and technological fields, in the dimensions not measured by the number ofclaims and forward citations. We can also control for the technology field- or macro-level
annual changes in demand, appropriability, and patent systems. The variableerror term.

28

,

is an

The dependent variable,

is the binary variables that reflect the decisions

on making “eventual examination request” and “early examination request” for thepatent application

filed at time . The independent variable

is the monthly

step function variable, which takes value 0 before September 2001 and value 1 after
October 2001. According to Proposition 1, the reduction of the allowable period increases
the probability that the application is eventually requested examination.
Our central focus is on the screening feature of the examination request system.
Proposition 2 suggests that the impact of the shortening of the period is larger in thetechnology area with higher uncertainty. To test this proposition, we compare thecoefficients of the variable

between the estimation results for the technology

sectors with high uncertainty and those for the other sectors. As the indices of uncertainty,
we use two variables constructed from the RIETI Inventor Survey on Innovation 2007.20
The first index is related to the non-use rate and the other is regarding the share of thebasic research. As for the first index, the survey asks the inventors of patent applications
whether the patent is used and, if not, whether the blocking motivation is the main
reason for non-use. We use a deviation of the average non-use rate in each technology

20 The survey was conducted in 2007 by Research Institute of Economy, Trade and Industry. See Nagaoka
and Walsh (2009) for a detailed explanation of this survey.

29

field (59 IPC sub-classes) from the overall mean, while non-use rate is defined as the ratioof the number of unused patents excluding those that are unused solely for the blocking
motivation to the total number of patents for each technology field. Thus, our non-use
rate does not reflect the blocking motivation and only measures the degree of uncertainty.
Moreover, the survey collect an information on the stage of R&D which generated theinvention under the survey; basic research, applied research and development. We use
the share of the basic research in each IPC as another index of uncertainty. We will
analyze whether the magnitude of coefficients of the variable

differs between

the subsamples with top 10% uncertainty and with bottom 90% uncertainty.
According to the Proposition 3, we expect that in a sector with a strong pending
application blocking effect, the reduction of the maximum length is more likely toincrease early examination requests. Since this effect can confound that of uncertainty,
we need to control for it. We introduce a direct measure of the importance of a blocking
motivation, which is also obtained from the RIETI Inventor Survey. It is the share of the“blocking” patents (those used by the applicant only for a blocking purpose) in all
surveyed patents in each technology field. We denote a deviation of this share from theoverall mean by. Although there are two distinct types of blocking: ex-ante30

blocking of a pending application (expressed byin the theoretical model) and the

ex-post blocking of granted patents (which can increaseandin our model), wecannot separately identify these two types of blocking values. Thus, it is important torepresents the effect of these two types

note that the coefficient of the variableof blocking motivations. The average non-use rate across technology fields, exclusive ofblocking motivation, is 29.2 %, and the average rate of pure “blocking” patents is 13.6%.
Others are control variables. A variable

is the logarithm of the number of,claims for each patent application.21 A variable

is the logarithm of the number,of forward citations that the application is received. 22 These variables measure andcontrol for the quality of invention. A variable,

is the R&D intensity of a firm,

which is the relative scale of R&D expenditure to firm size, measured by the tangible
asset. We use the logarithm of tangible asset (,) as the proxy variable of thefirm’s complementary assets. Since we use firm fixed effects, these variables control forthe effects of inter-temporal changes of a firm’s specific R&D capability and the size of its
complementary assets. We include the logarithm of total number of applications in therelevant IPC class (, ) to control for the variation of technological opportunity and

We add the value 1 before taking the logarithm of the independent variables: ln(1+x).
There is a truncation problem in that newer patent applications receive smaller number of citations. We
control for this problem by introducing the technology fields by year dummies in the estimation.
21
22

31

patenting propensity over time.
The explanations and the descriptive statistics of all variables used in the estimations
are summarized in Table A-1 and Table A-2 in Appendix.

4.4 Basic Estimation results
Table 4 reports the results of the OLS estimation of equation (18) for eventual and earlyexamination requests. Our estimation limits the sample period to 5 years before and after
policy change: 1997-2005.23 In Table 4 the estimation models (1) and (2) use the fullsample, while the models (3) and (4) use the subsamples that include only technology
fields with “Top 10%” uncertainty measured by the share of basic research or the non-use
rate, respectively. For the estimation on the eventual examination request, we added theestimation results with the samples of “Bottom 90%”, by excluding the top 10%
subsamples from the full sample, as in model (5) and (6).
[Place Table 4 approximately here]
One of our central interests is the effect of the shortening of the period of examination
requests. The coefficients ofare highly significant and positive for both eventual

23 We evaluate the effect of policy reform by using the symmetric pre- and post- length, while we overviewed
the overall trend with longitudinal data that covers 20 years since 1986. Due to the limitation of processing
capacity of the computer, we employ OLS estimation since the maximum likelihood estimation takes
considerable time.

32

examination request and early examination request; model (1), (2), (7) and (8) in Table 4.
We find that the reduction of the allowable period for patent examination requests
increased the probability of making eventual examination request by about 8.7% points
from 62.3 %. Furthermore, the rate of early examination request also significantly
increased by 1.6 % points from 4.2 % because of the policy reform. These results are
consistent with Proposition 1 (a) and Proposition 3.
The magnitude of the coefficients of the variable

for the eventual

examination request is higher for the subsample of higher uncertainty. In the estimation
model (3) and (4) for the eventual examination request, the coefficients are 0.113 and0.113, compared with 0.0884 and 0.0893 in model (5) and (6). These differences are highly
statistically significant.24 This result supports Proposition 2. Specifically, the impact of
the shortening of the allowable period becomes larger as the uncertainty becomes higher.
Controlling for the blocking motivations of pending applications and granted patents does
not materially affect the effect of uncertainty, since the coefficients of

have

almost the same values for the model (1) and (2). The above evidence strongly suggestthat the screening feature of the examination request system was quite important for theapplicant and that the reduction of the allowable period significantly decreased the option
24

The estimated standard deviations of the differences are 0.000016 and 0.000033.

33

value of postponing examination requests for this purpose. A blocking motivation has asignificant and positive coefficient only for early examination request in model (7). These
results are consistent with Proposition 1 (b) and Proposition (3).
Both the number of forward citations and the number of claims have highly significant
coefficients in accounting for the level of the eventual examination requests. Higher
invention quality is associated with lower threshold for examination requests (seeequation (11) and Figure 1) , consistent with our theoretical model.

4.5 Robustness checks
As shown in Appendix (Table A-3), our main results explained above are robust even if
we limit the sample period to just before and after policy reform, from October 2000 toNovember 2002, by which the results are less likely to be affected by the long-term trends.
The coefficients ofhave highly significant coefficients for both eventual andearly examination requests, the sizes of which are similar to those reported in Table 4.
The differences in the magnitude of coefficients between the fields with high uncertainty
and those with the other are similar to the results with Table 4.
Furthermore, the results for early examination requests are also robust, even if we

34

use the dummy variable reflecting the decision of examination request within 12 months
from the date of applications as the dependent variable for early examination request (seeTable A-4).

5. Conclusions
In this paper, we tested the major implications of real option theory on patentexamination request behaviors, exploiting the responses of Japanese firms to the changeof the deferred examination system.
Our theoretical analysis suggests that: (I) The reduction of the period allowable for
examination requests leads to an increase in eventual examination requests, especially inthe technology areas with high uncertainty, since it weakens the ex-ante screening ofpatent applications. (II) It also increases the firm’s early examination requests, when the
reduction of the allowable period for examination requests significantly reduces thelearning opportunity on the value of patenting its application. The blocking value of apending application also increases the impact of such policy on early examination
requests, while it does not affect the level of eventual examination requests.

35

Our empirical analysis supports these implications. In particular, the reduction of theallowable period increased the probability of making eventual examination request by
about 8.7 % points from 62.3 % even after controlling for the blocking effects of pending
patent applications. Such an effect is stronger in technology areas with higher
uncertainty. The reduction of the allowable period also increased the probability ofmaking early examination request by about 1.6 % points from 4.2 %. These findings point
to the importance of the ex-ante screening effect of the examination request system.
Our research has an important policy implication. A deferred patent examination
system can potentially improve the welfare of all parties involved: a smaller number ofgranted patents (for third parties), fewer resources used for patent examination (forpatent offices and applicants), and more ex-ante profit from R&D (for applicants). One
potential negative consequence is a blocking effect of pending applications that do notmeet patentability. This outcome could be controlled by allowing a third party to request
patent examination, perhaps with a subsidized fee.
A number of additional issues remain to be analyzed. One potentially important effectof the shortening of the allowable period in Japan is that it constrains the opportunity ofthe patent office to collect information. This outcome may reduce the accuracy of the36

patent examinations. In a future research, we plan to examine how the accuracy of patentexaminations has been affected by the acceleration of the examination process in Japan25.
The second issue is the joint design of the deferred examination and renewal systems forrealizing an efficient patent system. Such design needs to consider both uncertainty(inventor learning) and information asymmetry (examiner learning). A deferredexamination may be less important if a patent renewal system can effectively solve boththe uncertainty and information asymmetry problems. However, having multiple
instruments may be advantageous. The third issue is an empirical assessment of theblocking effect of a pending application that is unlikely to meet patentability criteria. We
intend to address this question by examining the results of examinations that wererequested by third parties.

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37

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39

Scotchmer, S. On the optimality of the patent renewal system. RAND Journal of
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Appendix A[Place Tables A-1, A-2, A-3 and A-4 approximately here]40

Fig. 1 Relation between thresholds of market size and invention quality

41

Fig. 2 Number of examination requests by elapsed months (in 2005)

number of examination requests

18000
16000
14000
12000
10000
8000
6000
4000
2000
0
0

2

4

6

8

10 12 14 16 18 20 22 24 26 28 30 32 34 36
months since application date42

Table 1 Signs of the policy effects under Assumption 1

Reduction of the allowable period (decreasein L)

Eventual

Early

examination

examination

requestrequest++(1)

Reduction of the allowable period interactedwith uncertainty (decrease in

when

is

+

large)
Note (1): When the importance of screening (pending application ( ) is large

43) is high and the blocking value of a

Fig. 3 Rate of eventual examination requests by application year
7

0.75

number of applications (100 thouthands)
6

average number of claims

0.7

rate of eventual examination (right axis)
5

0.65

4

0.6

3

0.55

2

0.5

1

0.45

0

0.4
1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005

44

Table 2 Changes in the rate of examination requests after the reduction of the allowable
periodLarge increase (Top 5)
Industry

beforeafter(Sep. 2001) (Oct. 2001)

Decrease or small increase (Bottom 5)
increase

Industry

beforeafter(Sep. 2001) (Oct. 2001)

increase

Pharmaceutical

50.3%

76.5%

26.2%

Communications

78.3%

66.3%

-12.0%

Ceramic

38.9%

64.2%

25.4%

Ship-building

62.9%

61.3%

-1.6%

Automobile

54.7%

79.5%

24.8%

Service

95.2%

96.6%

1.5%

Food

65.1%

81.6%

16.4%

Steel

65.5%

67.3%

1.8%

Chemical

47.9%

63.7%

15.8%

Gas

71.2%

73.0%

1.8%

45

Table 3 Changes in the grant rate after the reduction of the allowable period
year

Patentapplications

Examination
request rate

Grant rate
(to applications)1998

382,979

59.7%

32.7%

2002

392,486

71.9%

37.2%

46

Table 4 Impacts of reform on the examination request decisions: 1997-2005 (OLS)
eventual examination
request dummy
(1)

(2)

full sample

shorten t

0.0869***(30.49)blocking j ×shorten t-0.0338(-0.584)
lncited it
0.127***(96.63)lnclaim it
0.0822***(113.9)rdint kY
0.00712*(1.862)lnasset kY-0.0306***(-18.14)lnipcap jt
0.109(0.000332)
Constant-0.113(-4.10e-05)
IPC
yes
year
yes
IPC*yearyes
firm*IPC
yes
Observations
1,276,373
R-squared
0.036
t-statistics in parentheses*** p<0.01, ** p<0.05, * p<0.1

0.0859***(33.24)0.126***(100.5)0.0812***(117.9)0.00470(1.262)-0.0318***(-19.48)-0.0172(-4.12e-05)
0.942(0.000285)
yes
yes
yes
yes
1,435,351
0.036

(3)

early examination request
dummy

(4)

(5)

(6)

Top 10%basic
research

Top 10%
non-use rate

Bottom 90%
basic
research

Bottom 90%
non-use rate

0.113***(12.42)-0.0472(-0.181)0.141***(66.30)0.0504***(31.18)-0.0451***(-3.980)-0.0697***(-17.30)-0.0276(-0.646)
1.516***(4.632)
yes
yes
yes
yes
315,8450.034

0.113***(7.276)-0.308(-0.688)
0.147***(53.38)0.0648***(31.45)-0.102***(-7.089)-0.0722***(-20.18)-0.0120(-0.481)1.379***(6.569)
yes
yes
yes
yes
180,847
0.045

0.0884***(27.47)-0.107(-1.550)
0.128***(88.76)0.0860***(108.9)0.0115***(2.808)-0.0287***(-16.11)0.0312(0.000174)
0.483(0.000307)
yes
yes
yes
yes
1,045,163
0.038

0.0893***(28.75)-0.104(-1.543)
0.128***(90.60)0.0841***(109.0)0.00866**(2.169)-0.0300***(-16.61)
0.00676(2.18e-05)
0.694(0.000269)
yes
yes
yes
yes
1,103,771
0.037

47

(7)

(8)
full sample

0.0160***(13.52)
0.0617**(2.574)0.00223***(4.092)-0.0211***(-70.42)0.0634***(40.00)0.0104***(14.92)-0.0149(-0.000110)
0.0563(4.94e-05)
yes
yes
yes
yes
1,276,373
0.018

0.0159***(14.95)0.00240***(4.678)-0.0202***(-71.36)
0.0611***(39.99)0.00994***(14.84)
0.0934(0.000545)-0.805(-0.000596)
yes
yes
yes
yes
1,435,351
0.017

Table A-1 Explanations of variables
Variable

Explanation

Level

shorten t

Dummy variable that takes 1 after shortening of the period monthlyof examination request (in October 2001)

uncertainty j

Deviation of the average nonuse rate (excluding theblocking motivation) in each technologicaly field (59 IPC
sub-classes) from the overall mean / Share of the basic
research in each technologicaly field

blocking j

Deviation of the fraction of the unused patents by reason of IPC
blocking among the all unused patents in each technology
field to the overall mean

blocking j ×shorten t Cross term of blocing and shorten

IPC

IPC, monthly

lncited it

Logarithm of the number of forward citations

patent, monthly

lnclaim it

Logarithm of the number of claims

patent, monthly

rdint kY

R&D intensity (=R&D/tangible asset)

firm, yearlylnasset kY

Logarithm of tangible asset

firm, yearlylnipcap jt

Logarithm of total number of applications in relevant IPC

IPC, monthly

48

Table A-2 Descriptive statistics

eventual examination request
early examination request
shortenuncertainty (nonuse rate)
uncertainty (basic research)
blocking
blocking×shorten
lncitedlnclaimrdint
lnassetlnipcap

Obs

Mean

Std. Dev.

Min

Max

1437738

0.623

0.485

0.000

1.000

1437738

0.042

0.200

0.000

1.000

1437738

0.432

0.495

0.000

1.000

1278602

0.054

0.078

-0.2920.258

1278602

0.178

0.095

0.000

0.561

1278602

0.014

0.048

-0.1360.214

1278602

0.007

0.032

-0.1360.214

1437738

0.124

0.320

0.000

4.263

1435351

1.894

0.631

0.693

5.951

1437738

0.254

0.245

0.000

21.4571437738

11.917

1.314

3.497

16.2961437738

8.080

1.317

0.087

9.769

49

Table A-3 Estimation results restricting the sample period: Oct. 2000 – Nov. 2002 (OLS)
eventual examination
request dummy(1)(2)
full sample

shorten t
blocking j ×shorten tlncited it
lnclaim it
rdint kY
lnasset kY
lnipcap jt
Constant

0.0856***(29.66)-0.0222(-0.377)0.119***(39.04)0.0907***(62.47)0.259***(5.774)0.0379***(3.002)--0.102(-0.658)
IPC
yes
year
yes
IPC*yearyes
firm*IPC
yes
Observations
317,175
R-squared
0.028
t-statistics in parentheses*** p<0.01, ** p<0.05, * p<0.1

0.0844***(32.30)0.117***(40.19)0.0897***(64.58)0.249***(5.667)0.0319***(2.658)-0.0710(-0.000106)
0.557(0.000103)
yes
yes
yes
yes
355,925
0.028

early examination request
dummy

(3)

(4)

(5)

(6)

Top 10%basic
research

Top 10%
non-use rate

Bottom 90%
basic
research

Bottom 90%
non-use rate

0.106***(11.81)0.0570(0.220)0.126***(13.07)0.0673***(14.61)-0.199*(-1.745)-0.0528(-1.259)-

0.116***(7.372)-0.283(-0.624)0.140***(11.04)0.0918***(15.88)0.0946(0.659)0.0837(1.456)-0.0869***(26.72)-0.0920(-1.315)0.120***(35.72)
0.0955***(60.29)0.379***(7.490)0.0594***(4.207)-0.0877***(27.92)-0.0876(-1.283)
0.119***(36.48)0.0927***(59.76)0.310***(6.345)0.0437***(3.180)-0.0152***(12.86)
0.0630***(2.612)0.00842***(6.723)-0.0138***(-23.17)0.107***(5.820)-0.0193***(-3.729)-

1.127**(2.316)
yes
yes
yes
yes
35,5070.023-0.649(-0.934)
yes
yes
yes
yes
20,8030.030-0.404(-0.000271)
yes
yes
yes
yes
258,479
0.031-0.194(-1.142)
yes
yes
yes
yes
273,183
0.029

0.257***(4.034)
yes
yes
yes
yes
317,175
0.005

50

(7)

(8)

full sample
0.0149***(14.00)0.00922***(7.758)-0.0130***(-23.01)0.100***(5.594)-0.0174***(-3.570)0.00305(1.11e-05)
0.212(9.65e-05)
yes
yes
yes
yes
355,9250.005

Table A-4 Impacts of reforms on early examination requests(using examination requests within 12 months from application dates)
examination request within 12 months
limited sample period(Oct. 2000 - Nov. 2001)

full sample(1)

shorten t

0.0231***(15.38)blocking j ×shorten t 0.0859***(2.818)lncited it
0.00797***(11.49)lnclaim it-0.0182***(-47.90)
rdint kY
0.0887***(44.03)lnasset kY
0.0385***(43.33)lnipcap jt
0.00978(5.66e-05)
Constant-0.469(-0.000324)
IPC
yes
year
yes
IPC*yearyes
firm*IPC
yes
Observations
1,276,373
R-squared
0.009
t-statistics in parentheses*** p<0.01, ** p<0.05, * p<0.1(2)0.0231***(17.00)0.00826***(12.56)-0.0175***(-48.40)0.0861***(43.97)
0.0364***(42.43)
0.0983(0.000448)-1.133(-0.000654)
yes
yes
yes
yes
1,435,351
0.009

51

(3)

(4)

0.0215***0.0216***(13.73)(15.25)0.0928***(2.902)0.0166***0.0178***(9.986)(11.24)-0.00946*** -0.00840***(-12.00)(-11.16)0.303***
0.288***(12.44)(12.12)0.180***
0.170***(26.20)(26.14)-0.157(-0.000430)-2.140***-0.753(-25.33)(-0.000258)
yes
yes
yes
yes
yes
yes
yes
yes
317,175
355,9250.006
0.006