ONLINE APPENDIX Deadlines, Work Flows, Task Sorting and...

ONLINE APPENDIX

to Deadlines, Work Flows, Task Sorting and Work Quality

This online appendix is meant to be a companion to “Deadlines, Work Flows, Task Sorting and

Work Quality.” It provides the following information:

Section I: Illustrative example and model proofs

Section II: Additional details on the calibration exercise

Section III: Patent application process and glossary of select terms

Section IV: Robustness checks

Section V: Survey description, analysis of responses and summary tables (S1-S4).

Notes:

Throughout, D1, D3, and D5 refer to a dummy variable indicating last one, three and five

working days of a month, respectively. For aggregated day-level regressions corresponding to

Table 1 in the main text, these dummies refer to calendar days of a month.

Some analyses are performed using patent data only because the application data did not

contain the required information. In such cases, measures that rely completely on applications

(e.g., application success) are not presented.

All coefficients and standard errors have been multiplied by 1000 for presentation purposes.

Unless stated otherwise, standard errors are clustered by firm. **: p<0.01, *: p<0.05, +: p<0.1.

1

I. ILLUSTRATIVE EXAMPLE AND MODEL PROOFS

2

Illustrative Example

This stylized example depicts a hypothetical patent application at a typical medium/large sized

inventing firm using an external law firm for filing. It is intended to provide a better idea of the

underlying model intuition and the filing process that our model reflects. The intuition is

similar for filings using internal attorneys.

Suppose an inventor, Curie, invents something patentable on, say, January 15. She then writes

up a 1-2 page disclosure note and forwards it to an internal review committee. The committee

may meet once a month, say January 25. Then, if the committee decides to file a patent

application, in most cases an external law firm attorney, say, John, is hired based on subject

matter expertise. As the “agent” executing the work, John has two principals: the partner

(Paula) he reports to in his law firm, and the inventing firm’s head of R&D (Peter) that John’s

firm works for (see the structure in the Figure below).

Upon receiving the work, the attorney, John, estimates the likely date of completion. He knows

that he has to interact with Curie, the inventor several times over a period of a few days to a few

weeks, to draft the patent application. John estimates his “optimal” time based on his own cost-

benefit tradeoff. Among others, John’s costs include the opportunity cost of his time and the

cost to him of making any errors in the application. Suppose John estimates that working at his

“normal” or “optimal” pace, the work will be completed and the application filed on March 20.

Then, a month-end deadline on March 31 would be immaterial to him, and a deadline on

February 28 would likely be too soon for him to complete the task (without making extremely

costly errors). In this case, he completes the work on March 20, and all of the work is billed to

the inventing firm (about $8,000 to $12,000 per application) at the end of the billing cycle,

typically March 31.

Instead of being completed on March 20, suppose John figures that some work on the

application will still be pending in the last week of March, so that at his “normal” or “optimal”

pace, John would file the application on April 3. To deal with cases like these, both his

principals have motives to impose a deadline-related penalty or incentive around March 31,

even though they know that it may cause additional errors because John has to work faster than his

optimal rate to complete by that date. For Paula, getting the work completed before March 31

would help reduce working capital costs by getting the billing of about $10,000 done a month

earlier than otherwise (if the work is completed on April 3, it would typically be billed at the

end of April). As long as the cost of the additional errors is smaller than the savings from earlier

billing, it is optimal for Paula to impose a deadline. Similarly, Peter, as head of the R&D

department, typically sets monthly/quarterly targets for patent filings, and also has an

obligation to accurately report patent-related expenditure for the month/quarter to the

accounting department. He may also have to report his progress on the invention at the next

review committee meeting. For these reasons, Peter has an incentive to try and get the

application work completed by March 31, if possible. In each of these cases, the optimal

3

completion date for the principals is different from the agent’s, and the role of the deadline is to

align the completion dates. The misalignment arises because the principals and the agents do

not share the same costs and benefits with respect to completion time.

John knows that he will likely face some pressure from Paula and Peter around the deadline.

The “pressure” on John could be from any number of mechanisms including a negative

performance review, reduction in the number of unbilled hours, potential loss of future jobs

from the inventing firm, and peer disapproval. John is also aware that he is likely to make more

mistakes or may have to file a less complete application if he accelerates his work. These can

sometimes be corrected later (e.g., by filing an additional document at a later date for a fee) but

sometimes they may not be (e.g., if some relevant matter was not included). Nonetheless, they

are costly to correct, and the inventing firm may take note of it, especially if there is a repeating

pattern of mistakes. Given these trade-offs, John may find it feasible, given the pressure from

Paula and Peter, to accelerate work to finish the application by March 31, fully knowing that the

application is likely to contain more errors, than if he had completed by April 3.

In this example, if the work had actually started earlier and had taken longer because it was a

technically complex invention or an invention with many claims, then the associated unbilled

hours (and expenses) would be larger, likely increasing the pressure from Paula (and Peter) on

John.

Note that the reason for the work being incomplete in the last week of March is immaterial (for

the predictions relating to work clustering, task sorting and work quality). For instance, it could

be that John is a procrastinator. In this case, he sub-optimally (to the principals) delays work on

the application, so that by March 20, he has two weeks of work left. John could also be an

overcautious worker who wants to reduce the probability of errors more than the principals

think is optimal, and hence ends up on March 20 with about two weeks of work left. From the

perspective of the two principals (his partner Paula, and the inventing firm R&D manager

Peter) working at an optimal rate, John should be done with the work and file the application

by March 31. Then faced with pressure from his partner (on unbilled balances) and from the

inventing firm manager (to meet the quarterly target), John may rush to file by March 31. In the

first case, the patent was procrastinated on but still ends up being rushed to be filed by March

31—hence procrastination and “rushing” are not mutually exclusive outcomes. Thus, an

application accelerated to be filed on March 31 in our framework is the result of an agent

working sub-optimally long relative to what the principals want; whether this is because the

agent was being diligent but too cautious or procrastinating is immaterial to our model.

4

Principal Agent Relationships in the Filing Process (Using External Law Firms)

Principal Agent Relationships in the Filing Process (Using Internal Attorneys)

External Law Firm Partners

[Agent for Inventing firm, Principal for Attorney – Working

Capital Considerations]

External Law Firm Attorney

[Agent – Own

quality/opportunity cost

considerations]

Inventing Firm Managers[Principal -- Corporate planning,

priority date considerations]

PETER

PAULA

JOHN

Inventing Firm Attorney

[Agent – Own

quality/opportunity cost

considerations]

Inventing Firm Managers[Principal -- Corporate planning,

priority date considerations]

5

I Model Proofs

I.A Lemma 3: Properties of z∗

(i) Expression for z∗: Setting (f(t∗)[

z2

2t∗2(t∗−z)2

]= γ) and solving for z∗ yields

z∗ = t∗[

t∗µ

1 + t∗µ

]where µ =

√2γ

f(t∗)(1)

Since the left-hand side of inequality

[a(x)t∗−z −

b(x)2

(1

t∗−z

)2> a(x)

t∗ − b(x)2t∗2 − γc(x)

]is increasing in z,

z∗ represents the upper bound beyond which it is not optimal to accelerate tasks of a given complexity.

(ii) z∗ is increasing in γ for any given t∗: Taking the partial derivative of z∗ w.r.t. γ, we get∂z∗

∂γ = µ(t∗)2

2γ(1+t∗µ)2 > 0.

(iii) z∗

t∗ is increasing in γ for any given t∗: It follows from equation (1) that z∗

t∗ =[

t∗µ1+t∗µ

]. Taking the

partial derivative of this w.r.t. γ, we get ∂(z∗/t∗)∂γ = t∗µ

2γ(1+t∗µ)2 > 0.

(iv) If f(t∗) is non-increasing in t∗, z∗ is increasing in t∗ for any given γ: Taking the partial derivative of

z∗ w.r.t. t∗, we get ∂z∗

∂t∗ = (t∗)2

(1+t∗µ)2

(µ(2 + µt∗) − t∗

2µ

f(t∗)∂f(t∗)∂t∗

)> 0 if ∂f(t∗)

∂t∗ ≤ 0.

(v) Sign of[∂2(z∗/t∗)∂t∗∂γ

]: Using the result from above for the first partial derivative w.r.t. γ, and then

taking its partial derivative w.r.t. t∗, we get[∂2(z∗/t∗)∂t∗∂γ

]= 1

2γ∂φ∂t∗

1−φ1+φ where φ = t∗µ. Therefore, at

very low values of γ, (1 − φ) > 0 so that the sign of the second derivative is the same as the sign of[∂φ∂t∗

]. Similarly, for high enough γ, (1−φ) < 0 so that the sign of the second derivative is the opposite

of[∂φ∂t∗

]. The result follows from the fact the partial derivative of

[z∗

t∗

]w.r.t. t∗ has the same sign as[

∂φ∂t∗

].

I.B Proposition 3: Clustering and Complexity

Consider the derivative of[z∗

t∗

]w.r.t. t∗. The sign of the derivative depends on the sign on

t∗[∂µ∂t∗

]+ µ. Substituting µ =

√2γf(t∗) , and simplifying, we get

√2γf(t∗)

[1 − t∗f ′(t∗)

2f(t∗)

]. Thus, when

f ′(t∗) < 2f(t∗)t∗ for all t∗,

[z∗

t∗

]is increasing in t∗. Then among accelerated tasks, the mean complexity

=

∫ TTt∗ z∗

t∗ τ(t∗)dt∗∫ TT

z∗

t∗ τ(t∗)dt∗>∫ TTt∗τ(t∗)dt∗ = the mean complexity for all other days.

6

II. ADDITIONAL DETAILS ON THE CALIBRATION EXERCISE

7

II Additional Details on the Calibration Exercise

Overall Model Structure: To calibrate, we impose additional structure on the baseline model

provided in the Appendix of the paper. We assume a(x) = c(x) = x2, and b(x) = x3, so that t∗ = x

and f(t∗) = t∗, b(x)a(x) and a(x)2

b(x) are strictly increasing in x and f ′(t∗) = 1 < 2 = 2f(t∗)t∗ for all t∗. We then

simulate data for 54 months of 22 working days each for 50 firms, with patent filing jobs arriving at a rate

of one per day. To abstract from initial transitional dynamics, we drop the first six months. We set T = 25

and T = 126 so that the range of durations extends from about one month to about five months; this is

consistent with the range of days indicated by the lawyers surveyed (see Online Appendix Table S2B). We

add a stochastic component to the filing date, to capture unmodeled factors (e.g., disruptions due to health

issues or personal vacations); we allow for each application to finish up to five days before or after a scheduled

date, with a 5% probability for each of the ten alternative days.

Calibration of Standardized Deadline Penalty: Using these simulated data, we first calibrate

γ to a value that yields a last-day share equal to that in our sample of applications. We standardize this

value of γ to be γs = 1. We then compare this case to a “No Deadline” regime, where there is no month-

end penalty. As can be seen from the figure and table below, these simulated data replicate key empirical

results fairly well. In particular, we find that in the deadline regime: (i) there is significant clustering at the

month-end, (ii) complexity is higher at the month-end, and (iii) the error rate is higher at the month-end,

both conditional and unconditional on complexity.

Calibration of Error Rates: To calibrate error rates, we need to form a mapping from the excess error

for the last day of the deadline period in the simulation (defined as the mean error rate for last day less the

mean error rate for other days), to the observed excess error in the data. We begin with the “Application

Incomplete” measure. We use our real data on the top 200 patenting firms to obtain a mapping of the

additional period-end error rate in the simulations to the actual error rates on this measure. Specifically, we

form a smoothed expected excess error rate variable using a locally weighted smoothing (lowess) regression

(default bandwidth of 0.8) of the mean actual excess error rate on the simulated excess error rate.

To calibrate excess period-end error rates for each of the other seven process measures, we use the ratios

of the month-end excess frequencies for the month-end (D1) as reflected in Table 3. For instance, for the

“Separate Inventor Oaths”, the ratio of its D1 coefficient to D1 coefficient for “Application Incomplete”

(col 2 of Table 3) as 1.062. Then, we form the estimate for excess period-end errors for “Separate Inventor

Oaths” as the product of this ratio and the calibrated excess error rate for “Application Incomplete”.

Calibration of Additional Error Costs: We obtained USPTO fees associated with each of the

eight work process quality measures in Table 3. To obtain estimates of additional time required to address

the office actions associated with the process quality measures, we undertook a survey (detailed in Online

Appendix Section V.S4).1 We then used an opportunity cost per hour of $250 (based on an estimate

provided by a patent attorney interviewee), to translate the time requirements into dollar costs. These

estimates of additional costs are presented in Online Appendix Table B29. The sum over all the work

quality/error measures of the excess error rates multiplied by the total cost for each type of error yields the

total additional error costs for the period-end.

1The survey-based averages were similar to those obtained through an interview with a practicing attorney.

8

Simulation – Month-end Clustering, Complexity and Work Quality

The first row corresponds to a deadline punishment parameter s = 1, and the second row of figures corresponds tosimulation without a penalty for crossing the month-end threshold. In the second and third figures of each row, theline denotes predicted fractional polynomial fit; the area denotes 95% confidence interval; the horizontal axis indicatesworking day of the month. The dependent variable in the first figure in each row is the day-share of total patents, inthe second figure it is complexity (x in the model), and in the third figure it is error rate (as defined in the model).A month is defined as 22 working days.

.002

.003

.004

.005

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are

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22 66 110 154 198 242Year−day

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Deadline (std. penalty=1), Period = 22 days

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04.0

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7474

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9

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,Complexityand

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10

III. PATENT APPLICATION PROCESS

& GLOSSARY OF SELECT TERMS

11

III. Patent Application Process and Glossary

GLOSSARY OF SELECT TERMS

Term Brief Non-Technical Description$

Priority Date Date which decides what prior art affects the patentability of an application. For

many applications, this is the date on which the patent application is filed with

the USPTO.

Specification A written description of an invention that forms the basis for the claims covered

by the patent.

Claims Specific descriptions of what is protected by the patent.

Provisional

Application

An application that allows the applicant to establish an early priority date by

including only a specification and drawing (if needed) at a lower cost than a

regular non-provisional application. No claims are needed. The applicant must

file a corresponding non-provisional patent application within one year to

benefit from the earlier filing of the provisional application. The patent term

usually starts from the filing date of the non-provisional application.

Continuing Patent

Application

(Continuation)

An application that requests additional claims to an invention explained in an

earlier application that has not yet been issued or abandoned. It has the priority

date of the original application (and hence, the patent term starts from the original

priority date). No new matter may be added in this application. Hence, the new

claims must be supported by the specification in the original application.

Continuation-in-

Part

An application that partly claims the priority date of another application but

adds new matter not disclosed in that application. The original specification

must be substantially repeated in this application. Claims based on the new

matter do not benefit from the original priority date. The patent term is

determined by the filing date of the original application.

Divisional Patent An application that claims a distinct invention carved out of a pending

application, and claims the same priority date as that application (and hence, the

patent term is determined by that date). No new matter may be added. Often

results from a "restriction requirement" issued by the USPTO, because the

original application had multiple inventions (a patent can only claim a single

invention).

Non-Final Rejection Typically the first statement from the examiner rejecting the patentability of

some or all the claims. In response, applicants may argue the examiner is

incorrect, and/or amend the claims to overcome the examiner’s rejections

without additional fees. A vast majority of patents receive this notice.

Information

Disclosure

Statement (IDS)

A statement, required of all applicants, disclosing prior art relevant to the

patentability of an invention. Applicants may not knowingly omit relevant prior

art in their application.

Restriction

Requirement

Statement by the examiner that an application contains multiple inventions and

requiring the applicant to choose one of them. The other inventions are

withdrawn from the application (and may be filed again as a divisional

application).

$: This table provides a non-technical glossary for readers unfamiliar with some terms used in the paper. For

precise legal definitions, refer to the USPTO MPEP.

12


PATENT APPLICATION PROCESS

In this appendix, we describe the general process of patent application. In particular, we focus

on the factors that may affect the timing of patent application and discuss how routines and

deadlines, both internal and external, may play a role in this process. We first discuss various

rules that regulate the timing of patent application. We then provide detailed steps of the

patenting process, particularly from the inception of ideas to patent filing. The specifics of the

patenting procedure vary across jurisdictions; except wherein applicable, we limit our

discussion to the case of the U.S., which is the context of our empirical investigation.

DATE OF PATENT APPLICATION

A patent is a government-granted monopoly right to an invention. Given that two inventors

may generate similar ideas independently, it is critical to determine who gets the grant of a

patent. Two systems exist for this criterion: first-to-file (FTF) system and first-to-invent (FTI)

system. As of June 30, 2015, all countries with a patent system adopt the FTF system that assigns

the right to whoever first applies for a protection of the given invention by filing a patent

application. Prior to March 6, 2013, the U.S. maintained the FTI system that assigns the right to

the person who conceived the invention first, though the person may not have filed it first. Even

in this case, however, the first person to file an application retains the prima facie right to the

grant of a patent. If a later applicant wants to claim the priority for the same invention, the

person can institute inference proceedings to determine the first inventor. But this procedure “is

costly and often very protracted; frequently it moves from a USPTO administrative proceeding

to full court litigation” (Merrill, Levin and Myers, 20041, pp 124-125). Also, in practice, FTF has

been the basis for an overwhelming majority of applications in the U.S., with less than 0.1% of

the cases ending up in inference proceedings because a second filer claims to be the first

inventor (Merrill, Levin and Myers, 2004, pp 125). Hence, even under the FTI system, the

inventor had the incentive to file an application as soon as possible to establish effective

priority. The U.S. has switched to a FTF system on March 6, 2013 with the enactment of the

America Invents Act.

The filing date of a patent application is the date on which the application is submitted for an

examination. For mailed filings, the postmarked date is the date of application. For electronic

filings, it is the date of electronic submission. In principle, the filing of a patent application

establishes the right of priority and the filing date of the first patent application becomes the

priority date for the application. This priority date determines what prior art affects the

patentability of an application. All inventions (whether already in a patent or in a pending

application) disclosed prior to that date will be considered prior art and cannot be claimed on

the application. This priority date is also important for other reasons. Based on this priority, the

claimant can file a subsequent application in another jurisdiction for the same invention. To use

1 Merrill, S. A., Levin, R. A., and Myers, M. B., (Eds.). 2004. A patent system for the 21st century. Committee on Intellectual Property Rights in the Knowledge-Based Economy, National Research Council. Washington, DC: National Academies Press.

13


the right of priority, the applicant must claim the priority of the first application in subsequent

applications.2

The priority right is effective for twelve months (six months for industrial designs and

trademarks). That is, once the inventor has established the priority right, he or she has a full

year to seek protection of the invention in other countries without her priority interfered with

due to differences in legal systems.

No New Matter Rule

37 CFR 1.121 (f) says: "No new matter. No amendment may introduce new matter into the disclosure of

an application." Simply put, this rule means that an applicant cannot add any new material to a

specification (that is, the description of an invention) that was not included in the original

application.3 Any such new matter will either be rejected or can be inserted only with the loss of

the original priority date.

Note that this does not mean that no new claims can be modified or added. In fact, there is no

restriction on adding new claims or modifying them as long as the specification enables those

claims. For example, if the claims relate to “fruit” in the filing but the specifications describe

only bananas, then oranges cannot be added without losing the original filing date. Then, the

only choices will be to go with a narrower claim (only for bananas) or lose the filing date by

subsequently filing a new application which adequately describes and enables the claims to

“fruit” (which new application will have a later filing date).

Hence, as one our respondents said, “complete, broad disclosure in the first stage that can

enable the claims is the first priority for lawyers.”

NON-STANDARD APPLICATIONS

For many applications, the priority date is the date on which the patent application is filed with

the USPTO. However, there are several rules that complicate the pendency of priority right and

inventors sometimes exploit these rules strategically to preempt others, reduce filing costs or

effectively extend the period of priority right. These rules allow for non-standard applications

which can influence the inventing firm’s decision on the actual timing of filing a patent

application. Below we discuss some of the most important ones in detail.

Provisional Applications

A provisional application is a U.S. national application for patent which allows filing without a

formal patent claim or any information disclosure statement while still establishing an early

effective filing date for a later-filed standard ("non-provisional") patent application. To file a

provisional application, the applicant has only to include a brief description of the invention

2 For instance, an inventor may have filed first in Japan and then files an application in the U.S. Then, the

applicant should include in the application document the information of the earlier Japanese application

including the priority date under the ”Foreign Application Data”. 3 Definition of specification: “The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention” 35 USC 112 (pre-AIA).

14


and any drawings that help understand the invention, along with the standard information

items such as inventor names and addresses. Hence, it provides the inventor with a lower-cost

means to establish the priority right. After filing a provisional application, the inventor has a

pendency period of twelve months, which is non-extendable, to decide on one of the following:

(i) file a corresponding non-provisional application; (ii) file a grantable petition to convert the

provisional application into a non-provisional application; or (iii) simply let the pendency

expire. If the inventor files a corresponding non-provisional application, the term of the granted

patent is measured from the date of this non-provisional application, not the date of the

associated provisional application. However, if a grantable petition for a conversion is filed, the

term is measured from the date of the provisional application. Therefore, if filed appropriately,

the provisional application provides the inventor with two distinct benefits. First, it reduces the

cost of establishing the priority right, especially when the inventor faces a severe time constraint

in preparation or when the inventor wants to minimize initial investments until she is sure of

whether to ultimately seek a patent. Second, by filing a non-provisional application based on

the provisional application, the inventor can effectively extend the period of patent protection

by up to one year.

Nonetheless, a provisional application is not a panacea to meet deadlines. In general, our interviewees

were hesitant to recommend provisionals as a substitute to a fully prepared non-provisional

application except in certain strategic cases where the provisional is actually a fully prepared

application (e.g., in pharma where a provisional gives the assignee an additional year of

protection; not surprisingly, in our data drugs and medical patents account for less than 4% of

non-provisional patents but nearly 15% of provisional patents). The biggest risk to provisionals,

they stated, is the inability to add new matter to the subsequent non-provisional application

without losing the priority date. As one respondent put it, ““Provisionals can be dangerous”.

Though easier and cheaper than the complete non-provisional app, it may not be thought out carefully,

and may miss important material (e.g., material desired for protection, material necessary to enable the

invention, etc.). If the provisional is filed with these defects, it is not possible to correct the defects with a

subsequent filed application without losing the priority claim. This may become a major issue if the

inventor has already presented that omitted material publicly. It may prove to be a fatal error, for

example, if the provisional application was not enabling. Indeed, the subsequent filed application would

not be able to claim priority to the provisional application and the loss of the priority claim may result in

prior activities creating a barring event.” Indeed, Crouch (2011)4 mentions that over 40% of the

provisional applications are abandoned without being used to claim priority based on those

application dates. The same risk is associated with the use of continuations, which require that

the continuation not include anything which would constitute new matter if inserted in the

original application.

Patent Cooperation Treaty (PCT) Applications

A PCT application is a patent application filed under the PCT, an international law treaty that

provides a unified procedure for filing patent applications. The inventor may file a PCT

application as the first filing or as a subsequent filing referencing an earlier application in a

jurisdiction. If filed, a PCT application establishes a filing date in all member countries (148 as of

4 Crouch, D. 2011. Patent Stats: Abandoning Provisional Patent Applications. PatentlyO.

http://patentlyo.com/patent/2011/12/patent‐stats‐abandoning‐provisional‐patent‐applications.html.

15


June 2015) and hence the inventor has no need to file separately in these countries to establish

the priority right. However, to seek a patent on the invention in a specific jurisdiction, the

applicant must enter the national phase within the specified period (typically 30 months from

the date of PCT filing or the earliest priority date) by paying the national fee and, if required,

provide a translation of the application. Filing through the PCT, instead of directly in the

countries of interest, the inventor can enjoy several benefits. First, since the inventor only needs

to file in a single language with a single jurisdiction, the PCT application significantly reduces

the cost of establishing the priority rights in multiple countries. Second, it buys time for the

inventor to gather further information before deciding where else to file patent applications.

Third, owing to the 30 month of international phase, the PCT application practically extends the

period of priority in a given jurisdiction by up to 18 months.

Continuing Applications

A continuing patent application is a patent application that follows and claims priority to an

earlier patent application (the “parent'” application) filed by the same applicant. There are three

types of continuing patent applications: (i) continuation; (ii) divisional; and (iii) continuation-in-

part.

A continuation application is filed when the applicant wants to include additional claims (but

no new subject matter) to an invention disclosed in the parent application that is still under

examination. Though potentially useful in cases where some claims in the parent application

are rejected while others are allowed, the continuation application is often used to simply buy

more examination time. In this case, the priority date of the original application applies to this

continuation. However, this application gets a shortened patent term since the patent term starts with

the filing date of the earliest parent application.

Applicants usually file a divisional application when the examiner determines that the parent

application contains more than one invention and issues a “restriction requirement”. In this

case, the applicant can decide which invention to include in the pending application and choose

to prosecute the rest as divisional applications. As with continuations, the patent term is shortened.

In a continuation-in-part application, the applicant can add subject matter that is not disclosed

in the parent application but repeat a considerable portion of the parent's specification. This

type of application is used when the inventor comes up with enhancements to the invention

after filing the parent application. In this case, the new matter does not receive the priority

benefits of the parent application but the patent term starts from the filing date of the earliest

parent application. This also takes the longest time to prepare among the three types of

continuing patents (see table below).

Although different in the usage and the associated requirements, all of three types of continuing

application claim, in full or in part, as the priority date, the filing date of the parent application.

The continuing application provides opportunities and considerable flexibility for the inventor

to claim the full scope of a disclosed invention by filing as many continuation applications as

deemed necessary and thereby seek a broadest possible protection of the invention. However,

16


this procedure is subject to criticism that such flexibility creates uncertainty about the ultimate

scope of a given patent application.5

As with provisionals, continuing patents are not a panacea to meet deadlines. For instance, one may

be tempted to file a not-so-well prepared application assuming that any problems can be fixed

later using continuing applications. First of all, they are each treated as a new application with

regard to USPTO fees, thus considerably increasing the costs. Moreover, except continuations-

in-part, the other options do not allow any addition of new matter, thus allowing only minor

changes to the original application, if any. Perhaps, most important, they all result in loss of

patent term for the new application.

The loss of patent term is particularly important for continuations-in-part. It requires the

inventors to seriously examine why they want to file a continuation-in-part on an improvement

that the applicant believes is novel and nonobvious over the previously filed subject matter

since they will be giving up patent term, even if all claims include the new matter. With a

continuation-in-part, there may be little benefit with a guaranteed loss of patent term.

Priority Date Patent Term Effort to Prepare$

Continuation Same as Earliest

Parent Application

Starts from Filing

Date of Earliest Parent

Application

Small; 10-20% of

initial filing; 1-3

hours

Continuation-

in-part (CIP)

Same as Earliest

Parent Application

for “old” matter

Filing date of CIP

for new matter

Starts from Filing


Application

Medium-Large; 20-

50% of initial filing;

10-30 hours

Divisional Same as Earliest

Parent Application

Starts from Filing


Application

Small; 5-10% of

initial filing; 1-3

hours

$: Based on estimates provided by two patent attorneys we interviewed.

PATENT APPLICATION PROCESSES

We now turn to the detailed steps of patenting process. Depending on the inventor's status of

affiliation, the application process can be quite different across inventors. A patent can be

legally assigned to an individual or to an organization. In the former case, it is the inventor who

owns the claim to the invention and, if any, the economic rent from it. In the latter, it is the

organization who owns the claim. In general, organizations include universities, research

centers, government bodies and corporate firms. Our discussion will focus on corporate firms.

For convenience, we call the inventor who also claims the ownership to herself as the “inventor-

5 In August 2007, the USPTO announced a new rule that limits the number of continuation applications

for each invention disclosed in the original patent application. However, in March 2009, after facing

strong opposition from many parties including lawsuits, the USPTO finally withdrew the proposed

changes to the continuation procedure.

17


owner”, and the inventor whose patent is legally assigned to an organization as the “R&D

personnel”.

Patent Application Process for Individuals

For the inventor-owner, there is no typical process of application; in principle, the inventor

decides whether and when to apply for the protection of an invention.6 Also, the inventor faces

little procedural constraints in filing an application. The inventor may work with a patent

lawyer for the actual filing but key decisions lie with the inventor.

Patent Application Process for Corporate Firms

For R&D personnel at corporate firms, the patent application process is more complicated. The

process begins with the inventor's disclosure of an invention and ends with either the

abandonment of the idea or the filing of a patent application. Various steps and feedback loops

exist in between.

The figure below illustrates the process flow for a typical firm that has established procedures

for patent prosecution.7 When the R&D personnel come up with a patentable idea, she first

submits it to an internal review committee for an assessment. This “disclosure” document is not

yet a full description of the idea; it could be a one-page memo or a short technical note that

outlines the subject matter of the invention. The review committee typically comprises senior

managers in the R&D department and the legal team that is responsible for patent prosecutions.

The committee regularly meets to discuss and determine if ideas submitted from various

research teams are worth pursuing for a patent.8 If an idea is approved by the committee, it is

then drafted into a formal patent application document. The inventor may write the first draft

and pass it on to the legal staff of the inventing firm (i.e., internal lawyer), or the legal staff may

write up the draft based on the information the inventor provides. In either case, multiple

rounds of meetings, online and offline, take place between the inventor and the lawyer before

the application document is finalized. Many firms entirely outsource this portion of the patent

prosecution to external law firms (i.e., external lawyer), while some use a mix between internal

and external lawyers. In our data, about 79% of the applications were represented by external

lawyers.

6 In the U.S., 14.4% of all patents granted during 1976-2009 were assigned to individual inventors. 7 Note that while this flow is broadly representative of the process followed by the firms we spoke with,

specific practices vary across firms. For instance, the ranking system and the disclosure review committee

composition likely varies across firms. 8 This step of assessment often involves more than a simple selection/rejection. For those ideas that are

selected for the next step, the committee could further sort them into several “grade” levels depending on

the expected value of the idea. The idea that receives a higher grade gets a higher priority in prosecution

(e.g., expedited processing). Lower-graded ideas may be pursued for patenting in a limited number of

jurisdictions or even only in a single market. The rejected ideas are not always bad ones. For firms that

are cutting-edge in certain technological fields, even the rejected ideas can be valuable from other

perspectives. One of our interviewees recalled incidences in which some academics spent their sabbatical

year at his firm to dig through past rejected disclosures and turned some of them into academic papers.

Also, we were told that some ideas are not approved for patenting, not because they are less than worth

patenting, but because they are assessed to be more valuable if kept secret.

18


Once the patent application is finalized, the lawyer (either internal or external) files it with the

patent office in the corresponding jurisdiction (e.g., USPTO, WPO). In the U.S., most filings

today are done through the electronic filing system (EFS), which was introduced in March 2006.

Before the introduction of the EFS, USPS express mail was the primary method of filing an

application. The date stamped by the post office on the mail is considered as the filing date by

the patent office. The patent office gives a unique identifier to each application and assigns it to

a patent examiner for a review.9 During the examination process, the patent examiner may issue

office actions that demand follow-up actions from the applicant such as further clarification on

the invention's specifications. These requests are mostly handled by the lawyers who drafted

the application, but sometimes with input from the inventor. For many firms, external lawyers

are also responsible for the maintenance of granted patents such as alerting the client to renewal

notices and, upon the client's renewal decision, paying renewal fees on behalf of the client.

Deadlines and Related Incentives for Agents

As in many other tasks, deadlines play an important role in the process of patent application.

The types of deadlines and the associated costs of missing (or equivalently, incentives to meet)

9 The actions taking place within the patent office critically impact a number of specifics of a patent,

including the breadth of coverage, references, and of course, granting and the timing thereof. However,

given our primary interest in the timing of application, we abstract away from the internal process of the

patent office.

19


these deadlines differ depending on the stage of application process and the agents involved in

the process. For instance, for internal management purposes the inventing firm may place

certain periodic target dates by which R&D personnel are required to disclose patentable

inventions. Also, internal review committees described earlier may be convened only

infrequently (e.g., monthly, quarterly) to minimize task interruptions or better coordinate across

different functions involved in R&D. Hence, these meetings may also entail certain deadlines

for collecting ideas to be evaluated. Our interviews and surveys of inventors as well as legal

staff at inventing firms, presented in this Online Appendix V.S1, confirm the practices of these

internal deadlines.

More importantly for our study, agents that work on documenting and filing the applications

(i.e., internal lawyers for the internally filed applications, and attorneys at external law firms for

outsourced applications) face different types of deadlines and associated costs and incentives.

Some of the deadlines are statutory, such as the 12-month period to claim the right of priority

based on a foreign application. These statutory deadlines apply equally to internal lawyers and

external lawyers. Our interviews with practicing lawyers suggest that missing statutory

deadlines, though not common, can have severe consequences for the lawyers as it often leads

to a loss of priority right. For external lawyers, it may very well mean losing the client or (in

severe cases) even a malpractice lawsuit.

More traditional nonstatutory deadlines are widely prevalent in the filing process. Our

interviews and surveys, part of which are presented in this Online Appendix V.S2 and V.S3,

indicate that internal lawyers tend to work with deadlines arising from work schedules in R&D

departments of the inventing firms. The most common cost of missing deadlines for internal

lawyers, according to our surveys and interviews, was lower performance evaluation,

especially if that was a pattern of behavior. One interviewee noted a practice of monthly status

reports in one prominent patenting firm that listed completed and remaining work on

applications for each of the internal attorneys, which could serve as informal deadlines (as it is

reviewed by superiors and peers), even when there are no formal penalties or incentives

associated with it. In outsourced applications, clients frequently impose deadlines to external

lawyers to complete the task (e.g., file an application by a certain date). When the client-law

firm transactions are based on a renewable fixed-term contract (typically one year), both parties

establish a routine for settling the account, which includes regular billing cycles (typically

monthly). Under this type of arrangement, external law firms are paid only after filing of the

application. Hence, at least for partners at law firms, these billing cycles function as deadlines in

managing the flow of application work. When missed, these nonstatutory deadlines can also

have important consequences for the partners and lawyers. Indeed, our interviewees and

survey respondents suggested as possible consequences the loss of monetary incentives, lower

performance evaluations, and pressure from colleagues. For partners at external law firms,

unfiled applications at the end of the billing cycle would mean unbilled hours for the work that

has already occurred. Missing deadlines, especially if repeated, could also lead to loss of the

client.

Our interviewees indicated that rework costs are often passed on to the inventing firm by the

external law firm. However, our interviewees suggest that this specific agency problem is

mitigated by the law firm’s consideration of potential consequences (such as bad performance

reviews and client dissatisfaction) of too frequent or too obvious errors. In fact, some of our

20


interviewees suggested that large clients, working with multiple law firms for patent

prosecution, regularly review the quality of the filing work (in terms of timeliness,

documentation errors, etc.) and determine the assignment of volume in the subsequent period,

and sometimes even demand removal of lawyers whose performance falls below certain

threshold. Thus, even in cases where costs are passed on, there are indeed long-term

consequences for external law firms.

In this setting, though the principal may be unable to perfectly monitor the agent’s efforts, (s)he

can still observe ex-post work outcomes that will help the principal make inferences about the

agent’s efforts. For instance, one of our interviewees said “[c]lients also have the opportunity to review the quality of the patent application after the application is filed and when the Patent Office sends a response to the filed application. For instance, the client may recognize that a patent was poorly drafted if the examiner points out errors that occurred when drafting the application.”

Drivers of Duration of Patent Application Preparation

In our formal model, the defining characteristic of a patent application is a scalar that we term

“complexity”. This complexity in our model is related closely to the duration required to

prepare the application.

To confirm that this usage of complexity is consistent with practice, we requested the input of

one of our interviewees, an experienced corporate attorney (who was exceptionally generous

with his time and expertise), on the drivers of the time it takes for the agent to prepare a patent

application document.

The interviewee confirmed that complexity was indeed related to duration. To quote directly

from his email “Complexity of the invention: Some inventions are more technically complex than

others—requiring significant review to determine the best way to claim the invention.”

The interviewee also notes the role of searching through prior art in increasing complexity and

hence duration of work. In particular, he notes: “Crowded prior art: The number of prior art

references can increase complexity - particularly if they are all very close to the point of novelty that is

being claimed. Indeed, if there are a lot of close prior art references, it is necessary to determine how much

you can claim without running into references that already disclose the claimed subject matter. If there

are many desired points of novelty in the invention, each point of novelty needs to be explored to

determine the breadth of the claim that will provide desired claim scope while still defining over the prior

art.”

Another key factor is the quality of the invention disclosure by the inventor. The attorney noted:

“Sometimes experimental data needs to be provided to support claim features—sometimes the

experiments have not yet been performed—so we may need to wait for experimental results to support

some claim features.”

Lastly, duration also depends on the number of points of novelty claimed in the application.

The interviewee notes: “Some inventions only have one aspect that we are trying to claim. Others have

many new features that need to be claimed. When there are many new features, extra time needs to be

spent to fully explain and claim each feature individually as well as in combination with other

features. This can increase the number of claims and time necessary not only to describe each point of

novelty, but how each point of novelty can be used alone or in combination with the other points of

novelty.”

21

IV. ROBUSTNESS CHECKS

22

IV. Robustness Checks

In this section, we present rich evidence from our primary data and additional empirical

analyses to check the robustness of our results while eliminating several alternative accounts.

ARE THE CLUSTERING PATTERNS ATTRIBUTABLE TO DEADLINES?

Evidence From Interviews and Surveys of Practitioners

The most direct support for the observed clustering being due to deadlines comes directly from

our surveys and interviews of practitioners. When asked about the possible reasons for the

observed clustering, not a single one of the 64 respondents in our attorney surveys chose a non-

deadline related reason. Also, every one of the 16 interviewees attributed the observed

clustering to organizational deadlines.

The evidence suggests a strong role for each of the dual principal-agent relationships embedded

in the patent application process. In particular, we found important roles for billing deadlines

pressure-related to working capital considerations imposed by law firm partners (serving as a

principal for the external patent attorneys), as well as reporting and planning routines-related

deadlines imposed by the inventing firm (serving as a principal for both internal and external

attorneys).

Stressing the role of monthly billing deadlines, one interviewee said, “The most likely thing that

could be driving these results is law firm internal revenue issues…” Another attorney remarked,

“There may be a lot of pressure on attorneys at law firms to bill out any billable work for that month. So,

they may have a motivation to complete work by the month-end so they can invoice the clients for it.” The

same respondent also stressed a role for inventing firm routines, “[Also], … many inventing firms

(especially the larger, sophisticated ones), are likely to have metrics and cyclical reports (monthly,

quarterly, and yearly) to encourage employees/attorneys to file patents in a timely manner.”

Consistent with this, in our inventor survey, we find a positive correlation between the pattern

of monthly clustering and the reporting deadlines for external attorneys. Specifically, Figure

S1A and Table S1E show that organizational clustering patterns correspond exactly with the

reported deadlines (annual deadline firms show year-end, quarterly deadline firms show

quarterly, and monthly deadline firms show monthly clustering). Additional evidence comes

from our law firm attorney surveys. We compared filing patterns for firms whose respondents

cited monthly billing cycles as a possible reason for the clustering to filing patterns for firms

who did not mention these cycles as a reason. Figure S2B shows that those who mentioned

monthly billing cycles (indicated by a solid blue line) are more likely to exhibit month-end

clustering.

Our surveys and interviews suggest a prominent role also for deadlines imposed by the

inventing firm, both on external and internal lawyers. About 53% of external attorneys (35 of 65

respondents), and about 69% (9 of 13 respondents) of internal attorneys suggested a role for

inventing firm (client) imposed deadlines in the monthly clustering pattern. A number of

corporate attorney interviewees stressed the importance of quarterly, half-yearly and yearly

accounting and planning routines. An interviewee from a very large patenting firm noted that

patent filing and related expenses amount to several million dollars for top filers, and because

these expenses need to be reported in quarterly accounting statements, it becomes imperative to

plan and file patents within quarterly time windows, leading naturally to quarter-end

deadlines. Consistent with this comment, six of eight attorneys that filed patents internally

23


reported that applications are sometimes or often expedited to meet non-statutory deadlines

(e.g., fiscal year closing, performance evaluation deadlines). Further, our interviews suggested

usage of monthly reporting schedules is common in R&D departments of large firms, which

could spur internal attorneys to finish up work before the month-end reporting deadline.

Our surveys also indicate that patent attorneys face significant costs if they do not meet a

deadline. Nearly three-quarters of all external attorney respondents said that missing a deadline

is likely to lead to lower performance evaluations sometimes or more often (Table S2D). More

than a third rated such a possibility as often or higher. Related qualitative comments on possible

consequences of missing a deadline also pointed to such costs (e.g., reduction in available work,

unhappy client, and payment for loss or damages). We performed a more formal analysis of whether

these perceptions of costs are associated with month-end clustering. We defined a dummy

variable costlymiss as one if the respondent rated any of the three aforementioned consequences

as sometimes or higher. We then plotted the month-end share of filings for these two groups of

patents. The results presented in Figure S2D clearly indicate a much higher prevalence of

month-end clustering among the group that rated the consequences as more likely (solid line

represents costlymiss = 1). This supports a direct association between the disincentives related to

missing deadlines and month-end clustering.10

Our respondents also provided their opinion on the negative perceptions associated with

several transactions during the patent prosecution process. We created a dummy variable,

negpercep, defined as one if the respondent rated the occurrence of any of four transactions

(application incomplete, request for extension of time, new drawings to be filed, additional

filing fees) as somewhat negative or worse. We then plotted the month-end share of filings for

these two groups of patents. The results clearly indicate a much lower prevalence of month-end

clustering among the group that had a more negative perception of receiving these office

actions (solid line represents negpercep = 1; Figure S2A). This is consistent with the respondents

being aware of the costs of rushing a filing at month-end, and avoiding it if they believe the

costs are high.

Finally, we put this all together in regressions of a month-end dummy on costlymiss, negpercep,

billcluster (defined as one if they mentioned billing cycles as a possible reason), and clientcluster

(defined as one if they mentioned client-imposed deadlines as a possible reason) with month

and application year fixed effects. Table S2G presents the results. In line with the corresponding

figure, the coefficients on costlymiss are strongly positive and statistically significant throughout.

This supports an association between the disincentives related to missing deadlines and month-

end clustering. The coefficients on negpercep are negative and generally statistically significant,

indicating that attorneys avoid rushing at month-ends if they believe the costs of rushing are

high. Billcluster is generally positive, consistent with our argument (though the significance

weakens on longer windows), while clientcluster stays insignificant throughout, suggesting that

incentives of attorneys may be a relatively more important driver of month-end clustering of

filings.

10 The results in relating baseline results to firm size (Hypothesis 4, Table 4, Section 4.4) suggest that inventing firm indeed plays an important role in the clustering patterns. In addition, results in this Online Appendix Tables B7A and B7B, discussed below, point to a big role for fiscal-year end deadlines in explaining month-end clustering patterns.

24


Additional Empirical Tests on Firm Routines

In the baseline analysis in Section 4.1, we found that filings by individuals show little or no

clustering at month-ends (except before October 1, when the USPTO usually makes fee

changes). In line with this, we do not see any month-end effects on quality or complexity for

patent filings by individuals (Tables B3 and B4). We also compared large (more than 100 patents

over the data period) and small firms (only one patent over the data period), and find that large

firms exhibit significantly greater clustering compared with small firms (Table B5). The large

firm size effect was robust to the inclusion of lawyer fixed effects and lawyer volume (Table B6).

Together, these results strongly establish that larger firms are more likely to have month-end

clustering patterns than individuals or small firms.

In addition, following Oyer (1998), we exploit changes in fiscal year-ends to see if clustering

patterns within firms shift in the expected direction. Though this focuses not on month-end

clustering but on year-end clustering, it provides a useful link between a known routine-related

deadline and clustering of filings. We find that, across firms, clustering is indeed correlated

with fiscal year-ends; specifically, the share of filings that occur in the last month of the fiscal

year is significantly larger than that for any other month (Table B7A). Further, we regressed a

dummy variable that is one if the patent was applied in the month in which the old fiscal year

ended, on a dummy variable for the time period prior to the fiscal year switch and other

controls (application year, month, and firm fixed effects). The coefficient on the old fiscal-year

dummy is strongly positive, implying that the propensity to file at the old fiscal year-end

diminishes after the switch (by 3.6%, Table B7B).11 Together, these tests strongly support a role

for large firm routines in driving the observed clustering patterns in patent filings.

ARE INVENTORS THE PRIMARY SOURCE OF CLUSTERING?

Thus far, our arguments have focused on the final stages of the filing process, just before the

application is filed. However, it is possible that routines associated with upstream stages, such

as inventors’ performance evaluation cycles, are causing the clustering patterns. Based on our

surveys, for several reasons, we believe that the observed clustering is unlikely to be due to

inventor behavior.

Our inventor survey suggests that it typically takes anywhere from a week to 12 months (with a

mode of 1–3 months) between management approval and patent filing, implying that inventors

do not have control over the exact timing of the filing (Table S1A). Our surveys of attorneys

yielded a similar timeline between invention disclosure to the attorney and filing (Table S2B).

Further, our survey of attorneys confirmed that the exact timing of patent filing is primarily

determined by either the law firm attorneys (42% of the responses) or corporate legal staff

(43%); only 4% replied that inventors play any role in deciding the timing of the filing (Table

S2A).

The modest (if any) role of inventors is consistent with our inventor survey evidence that the

number of patents applied for is only one of the criteria for performance evaluation of the R&D

11 Corresponding changes in complexity and quality were noisy, though generally in the expected direction, suggesting that the magnitude of these effects don’t vary sharply across month- and fiscal-end deadlines (Table B8).

25


organization, and in fact is not even the most frequent one (Table S1B, Panel A). Even for

individual R&D staff, though patent filing and grants were somewhat important, it was not the

most important criteria for internal performance reviews (Table S1C). As a direct test, we

checked for clustering patterns in the reported month of inventor performance evaluation; we

did not find evidence for any significant clustering. In fact, fewer patents are filed in the month

inventors reported they are evaluated for performance compared with other months (Table

S1D). Moreover, no inventor reported having monthly performance evaluations (Table S1F).

Deadlines related to inventor performance evaluation were not mentioned as a possible reason

for the observed clustering in any of the over 20 interviews we conducted with attorneys. In

fact, in these interviews, none of the R&D staff were aware of the clustering pattern in patent

filings. Together, these pieces of evidence strongly suggest incentives and penalties related to

inventors are unlikely to play a significant role in the observed clustering of patent filings.

IS THE MONTH-END CLUSTERING ATTRIBUTABLE TO ECONOMIZING ON

COMMON COSTS?

Firms may choose to file patents together to economize common costs of filing or other

coordination reasons unrelated to deadlines (e.g., R&D managers may choose to interact with

external attorneys about filings on a certain set of days to avoid distractions to their primary

jobs). Alternatively, firms may choose to file all patents related to the same invention on the

same day in order to avoid having different priority dates for those patents. At the outset, note

that these possibilities imply clustering, but not necessarily at month- ends. Nonetheless, we tried

estimating the magnitude, if any, of the bunching of applications due to such reasons. For all

applications filed by a firm in a given application-year-month cell, we computed the share of

applications filed on any given day. We then computed the deviation of these shares (excess rate)

from a hypothetical uniform share based on the number of applications in a given month (e.g.,

if the firm filed 10 patents in a given month uniformly (i.e., one-a-day), then the uniform daily

share will be 1/10; on the other hand, if it filed all the patents on a single date, the average daily

share will be 1). The mean excess rate in the sample was 0.0336, implying that the probability

that applications are processed in a batch is about 3.36 percentage points higher than the

expected uniform rate. The excess rate decreased sharply with the number of monthly

applications (since the applications are more likely to spread out over the month) but never

reached zero, indicating the existence of some bunching during the month, possibly due to

economization of costs related to filing. However, this excess rate was significantly higher at

month-ends (Table B9). If the clustering is purely due to economization of costs and unrelated

to deadlines, there is no reason to expect this excess bunching to be higher at month-ends.

In a different test, we used shared backward citations as an indicator of different patents

belonging to the same invention.12 We constructed all patent-to-patent pairs filed in the same

month by the same firm, and computed for each of these approximately 88 million patent pairs,

a dummy for sharing a backward citation, and the number of backward citations shared

between them. A pair of patents filed by the same firm on the same day is about 12 times more

likely to share a backward citation than a pair of patents filed by the same assignee on different

days of the same month (0.092 vs. 0.0075). But, we find that conditioning on the pair of patents

being filed on the same day, the probability that any two patents share at least one backward

12 We thank an anonymous reviewer for suggesting this test.

26


citation is significantly lower at month-ends than at non-month-ends (Table B10). Likewise, the

number of shared backward citations at month-ends is also significantly lower than that at non-

month-ends. This is inconsistent with month-end clustering primarily being driven by the

incentive to economize on costs related to the same invention; if that were the case, we should

see that for the patent pairs filed on the same day, the pairs filed at month-ends share a greater

number of backward citations than that of those filed at non-month-ends.

Our theoretical framework posits clustering as arising from rushing to avoid deadline penalties.

A plausible alternative is that observed clustering is instead caused by waiting to save on

common costs by filing at periodic (incidentally at month-end) check- points. A number of

results suggest this is not the case. If waiting were causing clustering, one would expect the

decline in the rate of filing to be toward the middle or latter part of the month, when the waiting

would be for a few days, rather than at the beginning of the month, when the wait would be

close to a month. However, the results show a decline in the filing rate at the beginning of the

month (e.g., the negative coefficient on days 1–7 in columns 7–9 of Table 1). Further, we observe

clustering at the month-end even for subsamples of firms with just one filing per month, which

additionally rules out a role for fixed costs savings. Also, there appears to be no plausible

reason for higher error rates (or more-complex applications) at month-ends, if clustering were

due to waiting; in fact, delayed filing may allow for some errors to be corrected, so that we

could expect fewer errors at month-end. Another piece of evidence against this “waiting”

hypothesis comes from our analysis of accelerated filing using foreign priority dates (discussed

below). That analysis shows that applications for which the expiration date to file based on

foreign priority falls within the first few days of a month are significantly more likely to be filed

in the last five days of the previous month. Because these applications have guaranteed priority

dates based on their foreign applications, they have no compelling reason to be accelerated.

Nonetheless, the filers of these applications chose to file earlier rather than waiting until the

deadline. Hence, this analysis renders additional support for acceleration, rather than waiting,

as the driver of clustering patterns we document in this study.

IS CLUSTERING DRIVEN SOLELY BY PRIORITY DATE CONSIDERATIONS?

One of the sources for deadlines discussed in our theoretical framework (Section 2, and Figure

1) is in- congruence between the principal and the agent in perceived benefits from an earlier

priority date. The heterogeneity of results with technology cycle time (Hypothesis 4, and

Section 4.4) confirms a role for priority date considerations. A question that arises is whether all

of the observed clustering may be driven by this concern, with no role for any of the other

sources for deadlines discussed in our theory (planning, coordination, or working capital

considerations). Note that as with economizing on fixed costs, simply rushing for getting an

earlier priority date neither directly causes clustering (if all applications get accelerated) nor

explains why clustering happens exactly at month-ends.

To check if earlier priority date is the sole consideration, we examined U.S. patent applications

that claim priority to a foreign patent. Because these applications already have a priority date,

they do not have any rushing benefits related to priority date considerations. However, they do

have a statutory deadline to meet; they must be filed within twelve months from the day the

foreign application is filed. In fact, we find that these filings also show month-end clustering,

though not quite as sharp as other filings (Figure B1 and Table B11). Because such clustering

27


may be driven by the timing of the original filings, we examine if such filings with a statutory

deadline on the first few days of a month are more likely to be filed 1–5 days earlier (so that

they are filed at the previous month-end). We find evidence of such acceleration, which strongly

suggests that there is rushing of tasks to meet a month-end deadline, over and above the

benefits of an earlier priority date (Table B12). Finally, we checked and found that the month-

end results for higher complexity and lower work quality generally hold for patents with

foreign priority dates (Table B11). These results confirm that early priority dates are not the sole

driver of month-end clustering patterns in the data.

THE ROLE OF SPECIAL APPLICATIONS (PROVISIONALS AND CONTINUING

PATENTS)

In our analysis so far, we used data on all applications. However, some of these applications are

different from the standard non-provisional application, and there may be a concern that these

applications are somehow biasing or driving the results. Our results in this section strongly rule

that possibility out. There are four main categories of special applications: (i) provisional, (ii)

continuation, (iii) divisional, and (iv) continuation-in-part (explained in detail in Section III of

this Online Appendix).

First, we checked and verified that the significant month-end clustering, higher month-end

complexity and lower month-end work quality (except for the examiner-added cites measure)

results hold in the sample excluding these patents, with little change in the magnitude of effects

(Table B13).

Second, we examined if clustering patterns for these types conform to what we would expect

given the key sources of deadline pressure. Note that in our framework, deadline effects are

more likely if applications are: (i) time/effort-intensive (hence, higher fee, which then is likely to

generate implications for planning/coordination or working capital), and/or (ii) priority-

relevant (so that firms may need task completion using a deadline earlier than the attorney

would otherwise want to). Continuation applications are modifications of previously filed

patents, and the application cannot contain “new matter” (USPTO MPEP, Section 201.06).

Divisional applications are “for a distinct or independent invention, carved out of a pending

application and disclosing and claiming only subject matter disclosed in the earlier or parent

application” and “often filed as a result of a restriction requirement made by the examiner”

(USPTO MPEP, Section 201.06). Thus, the time and effort intensity is limited for both (as

confirmed by two practitioners; see “Patent Application Process and Glossary” in this Online

Appendix III). Further, both these types of applications take the priority date from the original

or parent patent application, so the timing of filing of neither type of applications is priority-

relevant. Thus, these two types of patents are likely to face little, if any, deadline pressure.

Provisional applications are much shorter than standard non-provisional applications

(minimally one cover page plus one or more pages; Quinn 2013), so deadline pressure from

time/effort-intensity is likely to be low.13 But these are relevant for setting priority date – in fact,

these are primarily used to secure a priority.14 In contrast, continuation-in-part applications take

13 Quinn, G. 2013. The benefits of a provisional patent application (blog). www.ipwatchdog.com. Updated September 14, 2013. 14 Claims or oaths are not needed for provisional patents, and these are not examined for patentability (per USPTO MPEP, Section201.04, http://www.uspto.gov/web/offices/pac/mpep/s201.html).

28

http://www.ipwatchdog.com/

http://www.uspto.gov/web/offices/pac/mpep/s201.html


priority date from the parent application (USPTO MPEP, Section 201.08), so they have low

priority-relevance but can include new matter. Hence they are likely to be more time-intensive

than simple continuation applications (also confirmed by two practitioners). Thus, both

provisional and continuation-in-part applications are likely to face moderate amounts of dead-

line pressure. In line with our expectations, we do find a moderate amount of clustering for

both provisional and continuation-in-part applications, but little clustering for continuation and

divisional applications (Table B14A and B14B).15

OTHER ROBUSTNESS CHECKS

We performed a series of other checks to verify the robustness of our results. We describe them

briefly here, referring the reader to the tables in this section of the Online Appendix for the

detailed results.16

(i) We excluded the ten largest firms in terms of patent volume, and confirmed that our results

were not being driven by a handful of outliers (Table B15).

(ii) Using an earlier cohort (patents applied before 1995) shows similar results to the baseline,

though many of the work quality measures were not available for that period (Table B16).

Figure B2 graphically confirms the complexity-related results for that cohort of patents.

(iii) We replicated baseline results separately for each of six NBER technology categories

(Chemicals, Computers & Communications, Drugs & Medical, Electrical & Electronics,

Mechanical, and Miscellaneous). We confirmed that the month-end clustering pattern is stark

for all the categories (Table B17A).17 Sorting and work quality results are largely robust as well

(Panels A to F of Table B17B). These results confirm that the baseline results are quite broad-

based and not influenced by one particular technology.

(v) Excluding provisionals, continuations, continuations-in-part, divisionals, and patents with

foreign priority more than doubled the magnitude of the observed clustering and work quality

effects, particularly on work process (Table B19).

(vi) The results were largely robust to using alternative time windows to measure citations and

renewal probabilities (Table B20A), and to excluding self-citations (Table B20B).

15 A related question is why might there be no additional clustering of provisional applications since they provide a cheap way to obtain earlier priority. When faced with a deadline, one would expect firms to file a provisional application. We find no support for this view. The coefficient on the provisional dummy in Table B14A is strongly negative for two of the three month-end dummies, and only weakly positive for D1; so, they are not used disproportionately at month-ends. As explained in Section III of this Online Appendix, a provisional application is not a panacea to meet deadlines. In general, our interviewees were hesitant to recommend provisionals as a substitute to a fully prepared non-provisional application except in certain strategic cases where the provisional is actually a fully prepared application (e.g., in pharma where a provisional gives the assignee an additional year of protection). The biggest risk to provisionals, they stated, is the inability to add “new matter” to the subsequent non-provisional application without losing the priority date (consistent with the discussion in Quinn 2013). 16 We thank anonymous reviewers and the Associate Editor for suggesting some of these robustness checks. 17 Clustering is stronger for Computers & Communications, and Electrical and Electronics (presumably because of stronger competition in these categories), and somewhat lower in Drugs & Medical, relative to the baseline “Miscellaneous category.”

29


(vii) Using all available data (instead of 2001–04) to analyze examiner citations yielded stronger

results (Table B21).

(viii) Using a dummy for “application resulting in continuation-in-part” as an alternative

measure of complexity (as a sign of the firm continuing to work on that invention), and a

dummy for “resulting in divisional” as an alternative measure of work quality (since this action

is usually the result of a restriction requirement) revealed that these were more likely to occur

for applications filed at month-ends (Table B22).

(ix) Including the daily volume of filings (for each firm) as an additional control did not change

the substance of the results (Table B23).

(x) Using alternative measures of size (assets, sales, and employment) did not affect the results

relating to the firm size–clustering association. When jointly included with patent volume (our

measure of firm size), only patent volume remained significant (Table B24).

(xi) The firm size–deadline clustering association is robust to using application data (Table

B25A), and the inclusion of technology class or inventor fixed effects (Table B25B).

(xii) We verified robustness of the quality results to splitting the sample by more and less than

20 claims (Tables B26A–B). Interacting the month-end dummy with a dummy for more than 20

claims showed positive interaction terms, though they were generally insignificant (Tables

B26C).

(xiii) The quality results were robust to including joint firm–claims fixed effects (Table B27A).

(xiv) The complexity and quality results were robust to including joint firm–monthly volume

for the firm fixed effects (Table B27B), and to using firm–year–month fixed effects instead of

firm fixed effects (Table B28).

30


TABLE B1: Key Results

Table in Text D1 D3 D5 N

Work clustering

1 (7-9) Mean daily share

0.389**

(0.108)

0.353**

(0.058)

0.336**

(0.049)

366

4 (1-3) Log firm-year

size

2.842*

(0.582)

5.533*

(0.702)

6.542*

(0.676)

2,878,229

Work sorting at month-ends

2 Log claims 17.354*

(3.156)

9.434*

(2.259)

7.953*

(2.155)

1,801,602

2 Log cites (5 yrs.) 15.018*

(3.018)

6.116*

(1.968)

3.897+

(1.682)

2,633,488

2 Renewal (3.5 yrs.) 2.823+

(1.253)

2.051+

(0.859)

2.161*

(0.765)

1,938,296

Work quality at month-ends

Work process-based measures

3 (2-5) App. incomplete 45.820**

(10.737)

36.129**

(7.063)

29.983**

(5.550)

92, 533

3 (2-5) Sep. inv. oaths 48.661**

(8.605)

37.288**

(6.208)

32.278**

(4.871)

92,533

3 (2-5) Add. filing fees 46.607**

(9.403)

36.410**

(6.745)

30.267**

(5.405)

92,533

Work outcome-based measures

3 (2-5) Exam. add. cites 0.254

(3.388)

4.140+

(1.980)

4.095*

(1.788)

627,209

3 (2-5) App. approved -1.441

(2.239)

-4.578*

(1.497)

-4.456*

(1.153)

785,051

3 (2-5) Log review time 23.139**

(4.015)

14.246**

(2.526)

9.011**

(2.403)

557,383

This table presents some of the main results (“Key” results henceforth) in one place for convenient comparison with other

results presented in appendix tables. Refer to the main text for details on these specifications.

31


TABLE B2: Construction of the samples (Tables 1-4 in the main text)

Table Models Type of Data Beg.

Year

End.

year

N. Obs. Notes

Patent 1976 2009 2,878,229 Baseline patent data. Utility patents

assigned to corporates.

Application 2001 2010 1,856,934 Baseline application data. App. data

not available before 2001.

1 All Patent 1976 2009 366 Aggregated to day-of-year level from

underlying Baseline patent data

2 Claims Application 2001 2009 1,801,602 Baseline application data limited to

those applied in 2001-09.

2 Drawings/

Draw. Shts.

Patent 1976 2010 2,829,361 Baseline application data with

available drawings.

2 Cites Patent 1976 2004 2,633,488 Baseline patent data limited to those

applied before 2005 (dep. var. is 5-year

citation).

2 Renewal Patent 1980 2005 1,938,296 Baseline patent data limited to those

applied before 2006 (dep. var. is 3.5-

year renewal). Renewal data not

available before 1980.

3, 4(size) Work

process

Transaction 2001 2004 92,533 Baseline transaction data. 25% random

download, limited to 8GB per

download.

3, 4(size) Exam. Cite Patent 2001 2004 627,209

Baseline patent data limited to those

applied in 2001-04 and matched to

exam. cite data

3, 4(size) App.

Approved

Application 2001 2004 785,051

Baseline application data limited to

those applied in 2001-04

3, 4(size) Review

Duration

Patent 2001 2004 557,383 Baseline patent data limited to those

applied in 2001-04.

4 (tech) Patent All based on patent data. Same as

those corresponding to 4(size) limited

to those with available class data.

32


TABLE B3: Summary of Results Based on Individually Assigned Patents Only

Dep. Var. D1 D3 D5 N


Log claims -3.494

(12.536)

-2.278

(7.835)

-2.768

(6.541)

488,802

Log cites (5 yrs.) 7.256

(12.970)

-5.529

(8.318)

-3.745

(6.815)

464,228

Renewal (3.5 yrs.) 4.727

(7.895)

3.755

(5.007)

3.129

(4.166)

356,976



Exam. add. cites -10.407

(12.212)

3.726

(7.546)

2.409

(6.224)

135,087

Log review time 0.619

(6.785)

-5.167

(4.281)

-4.476

(3.521)

488,782

Note: These regressions replicate the Key results on complexity and quality for patents assigned to individuals. All

analyses are based on granted patents from 1976 to 2009.

TABLE B4: Summary of Results with Individual Assignee Interaction

Dep. Var. D1 D3 D5 N


Log claims -37.523**

(7.522)

-18.939**

(5.024)

-12.182**

(4.045)

3,367,031

Log cites (5 yrs.) -33.811**

(7.368)

-15.106**

(4.564)

-8.417*

(3.610)

3,097,716

Renewal (3.5 yrs.) -3.041

(3.833)

-0.405

(2.446)

-5.142*

(2.035)

2,295,271




(6.826)

-9.880*

(4.355)

-10.878**

(3.462)

1,349,963

Log review time -24.894**

(5.004)

-15.611**

(3.036)

-9.744**

(2.348)

3,366,915

Note: These regressions replicate the Key results with the end-of-month dummies interacted with a dummy

indicating if the patent has individual assignees. The coefficient in each cell represents that of the interaction term.

All analyses are based on granted patents from 1976 to 2009.

33


Table B5: Large vs. Small Firms

(1) (2) (3) (4) (5) (6)

(Granted Patents Data) (Application Data)

Days 1-7 -0.117** -0.369** -0.282** -0.167** -0.469** -0.377**

(0.031) (0.053) (0.054) (0.033) (0.059) (0.054)

Days 8-15 -0.148** -0.401** -0.314** -0.182** -0.484** -0.392**

(0.024) (0.049) (0.050) (0.033) (0.058) (0.053)

Days 16-23 -0.044 -0.296** -0.209** -0.037 -0.339** -0.248**

(0.039) (0.059) (0.059) (0.039) (0.062) (0.057)

Days 24 and

Beyond 0.314**

0.390**

(0.044) (0.056)

Last Day of Month 0.461** 0.659**

(0.137) (0.214)

Last 3 Days of

Month

0.371** 0.449**

(0.087) (0.117)

Constant 0.253** 0.165** 0.302** 0.210**

(0.043) (0.044) (0.048) (0.042)

N 366 366 366 366 366 366

Note: The table presents coefficients from OLS regressions. The dependent variable is the difference between the

day-share of annual patenting (or applications) for “Large” corporate assignees and the corresponding share for

“Small” corporate assignees. “Large” assignees are defined as those with more than 100 patents filed over the data

period. “Small” assignees are defined as those with just a single patent over the data period. The independent

variables are dummy variables corresponding to the period indicated in the rows. The first three columns use data

on granted patents from 1976-2009 while the next three use data on published applications that were applied

between 2001 and 2010.

Table B6: Size Effect Controlling for Lawyer Volume

(1) (2) (3) (4) (5) (6)

Dep. Var. D1 D3 D5 D1 D3 D5

Log Firm-Year Size 2.620** 5.559** 6.473** 0.945* 2.297** 2.987**

(0.438) (0.580) (0.601) (0.373) (0.551) (0.555)

Log Lawyer-Firm-

Year-Month Volume

5.930**

(1.246)

11.552**

(2.049)

12.342**

(2.138)

N 1,792,838 1,792,838 1,792,838 1,792,838 1,792,838 1,792,838

Notes: The table presents coefficients from OLS regressions. These regressions use data on granted patents from

1995—2009. The dependent variable in each column is a month-end dummy variable Lawyer-firm-year-month

volume is defined as the number of patents applied by a lawyer for a given firm in a given month. All models include

lawyer-year fixed effects.

34


TABLE B7A: Effects of Fiscal Year Shift on Work Flows

Notes: The numbers represent the monthly-share of filings for a given fiscal year-end month. For instance, the top

left cell (16.2) indicates that of all the filings related to firms that have January as the fiscal year-end, 16.2% of them

were in January. Cells highlighted in grey represent maximum within the respective columns. Numbers highlighted

in bold font indicate they are different from 8.3% (i.e. 1/12) at or below the 5% level.

Month Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Jan 16.2 5.9 6.5 6.9 6.4 6.7 7.2 6.6 6.7 7.9 5.9 6.7

Feb 6.1 22.1 7.7 7.4 8.5 7.2 7.2 9 7.4 7 7.0 6.8

Mar 6.4 8.0 14.1 9.7 8.3 9.4 8.3 8.1 9.1 8.7 8.3 8.5

Apr 7.3 7.1 8.4 18.7 8.7 8.2 7.2 7.6 7.5 9.6 9.2 7.8

May 7.6 8.2 7.5 5.8 13.7 8.2 8.7 7.4 8.8 7.9 8.2 8.2

Jun 7.0 9.2 9.2 6.9 8.5 14.6 10.2 8.4 9.3 8.4 8.4 9.6

Jul 8.7 5.7 7.4 5.6 6.8 7.5 11.6 8.6 7.6 8.4 6.6 7.3

Aug 7.6 5.5 8.5 6.7 8.2 6.9 7.3 18.3 8.5 8.2 8.4 7.9

Sep 6.7 7.0 8.4 7.8 8.0 7.4 7.2 6.9 12.6 7.9 8.0 8.4

Oct 8.4 7.2 7.9 9.7 8.3 7.9 8.5 6.4 7.9 12.3 7.8 8.4

Nov 7.6 7.1 6.8 6.5 7.2 7.7 7.3 6.1 6.8 6.8 13.2 7.9

Dec 10.5 7.2 7.6 8.3 7.7 8.3 9.4 6.7 7.7 6.9 9.0 12.5

100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0

Fiscal Year Month-End

35


TABLE B7B: Effects of Fiscal Year Shift on Work Flows

Do Dn Dn-Do Do Dn Dn-Do

Old Regime

Dummy

36.417**

(6.896)

-19.724**

(5.780)

-56.141**

(11.140)

19.986**

(6.036)

-2.502

(6.364)

-22.488*

(10.648)

This table presents coefficients from OLS regressions with firm-fixed effects. The first three columns (N=59,457) use

data on granted patents from 1976 to 2009 while the next three (N=105,530) use the sample of published

applications that were applied in 2001-2010. Data in all columns are based on the sample of “switchers” - firms that

change fiscal years. Among the dependent variables, Do is a dummy that is 1 if a patent is applied in the month

corresponding to firm's old fiscal year-end, and 0 otherwise; and Dn is a dummy that equals 1 if a patent is applied

in the month corresponding to firm's new fiscal year-end, and 0 otherwise. The main independent variable of

interest, “Old Regime Dummy”, is 1 before the firm switches to its new fiscal year, and 0 thereafter.

TABLE B8: Effects of Fiscal Year Shift on Work Complexity and Quality

D1 D3 D5

App claims (N=50,909)

Old FY-end Month Dummy

X New FY Regime Dummy

-57.628

(53.898)

-63.632

(47.869)

-65.020

(41.701)



X Month-end Dummy

-335.881*

(143.009)

-106.110

(108.784)

-22.206

(120.599)

Log cites: 5 years (N= 54,505)



-42.996

(37.822)

-47.463

(40.750)

-55.434

(40.862)



X Month-end Dummy

-10.904

(111.740)

27.854

(72.731)

44.687

(65.098)

Renewal: 3.5 years (N= 43,350)



-25.010*

(11.497)

-35.093*

(12.340)

-32.787*

(13.942)



X Month-end Dummy

-17.270

(45.584)

42.141

(28.881)

23.036

(26.292)

App incomplete (N=6,013)



10.458**

(3.751)

10.256**

(3.814)

7.449+

(4.151)



X Month-end Dummy

a -248.113**

(8.472)

171.227

(132.736)

Sep. inventor oaths (N=6,013)

47.069 49.153 30.747

36


D1 D3 D5 Old FY-end Month Dummy


(43.531) (43.413) (43.530)



X Month-end Dummy

a -179.804*

(88.012)

250.965

(171.341)

Add. filing fees (N=6,013)



38.806

(51.233)

39.359

(50.104)

27.215

(50.662)



X Month-end Dummy

a -205.034*

(92.214)

111.875

(122.600)

Exam cites (N=28,228)



18.868

(29.198)

18.868

(32.673)

3.889

(37.248)



X Month-end Dummy

-4.240

(76.680)

-3.616

(62.087)

55.155

(65.512)

App. approved (N=50,913)



54.188**

(13.213)

52.725**

(15.900)

50.8973**

(15.968)



X Month-end Dummy

8.693

(15.096)

17.655

(7.990)

9.750

(59.167)

Log. review time (N=37,389)



-64.497**

(16.359)

-62.739**

(16.992)

-52.025**

(17.325)



X Month-end Dummy

-80.208

(142.257)

-50.702

(32.319)

-98.104**

(32.806)

This table examines the change in complexity and quality measures with a fiscal year change. These dependent

variables are regressed on a triple interaction of a dummy for the last month of the old fiscal-year end, a new fiscal-

year regime dummy and a month-end period dummy (D1, D3, and D5). A full set of double interactions and the

direct terms are also included. Application year, month, and firm fixed effects are included in all models. a:

unspecified due to insufficient observations.

37


TABLE B9: Analysis of Economizing on Fixed Costs

D1 D3 D5

Excess bunching 11.248**

(0.626)

6.613**

(0.353)

4.679**

(0.270)

N 1,948,752 1,948,752 1,948,752

This table presents analyses of excess bunching of patents observed at month-ends. “Excess bunching” is

defined as the excess share of patents filed on a single day over an expected uniform rate. Hence, suppose a firm

filed all 10 patents that it filed in a month on a single day. Then, the actual average daily share is 1 while the

expected uniform rate (assuming each patent would have been filed on a separate day in the absence of fixed

costs) is 0.10. Thus, the excess bunching is 0.90. This variable is regressed on a month-end dummy, and

application year, month, and firm fixed effects as controls. A positive coefficient on a month-end dummy

indicates greater excess bunching relative to other days.

TABLE B10: Analysis of Same Invention Filed for Multiple Patents

D1 D3 D5

Prob. of sharing at least one

backward citation

-16.375**

(3.138)

-12.156**

(2.706)

-8.683**

(2.394)

N 5,532,674 5,532,674 5,532,674

Note: Restricting to pairs of patents filed on the same day, this table examines whether pairs by a firm filed on

month-ends are more likely to share a backward citation than pairs filed by the same firm on other days of the

month. The dependent variable is 1 if the patents in a patent pair share at least one backward citation and 0

otherwise. Hence, regressions are at a patent-pair level. Log firm size-year, and application, month and firm

fixed effects are included throughout.

38


FIGURE B1: Distribution of Filing Volume by Foreign Priority Status

The graph illustrates the difference (in day-share of filings) between corporates and individuals

over a month. The solid line indicates the patent with a foreign priority date and the dotted line

indicates otherwise.

-0.2

%0

.0%

0.2

%0

.4%

0.6

%0

.8%

1.0

%

0 10 20 30

39


TABLE B11: Summary of Results Based on Foreign Priority Patents Only

D1 D3 D5 N

Work clustering

Mean daily share$

(month-end

relative to month-

beginning)

0.200**

(0.067)

0.344**

(0.059)

0.320**

(0.056)

366

Log firm-year

size

0.832**

(0.218)

2.979**

(0.492)

4.219**

(0.636)

1,016,350


Log claims 10.675*

(4.466)

7.648*

(3.214)

8.267**

(2.544)

1,634,162


(4.295)

2.020

(3.010)

2.144

(2.528)

1,505,537


(2.075)

1.079

(1.229)

1.641

(1.072)

1,146,889



App. incomplete -3.315

(13.069)

16.729*

(8.417)

20.692**

(6.814)

37,794

Sep. inv. oaths 6.143

(10.908)

11.372

(8.428)

22.236**

(6.467)

37,794

Add. filing fees -3.186

(12.038)

6.626

(9.586)

17.233*

(7.497)

37,794


Exam. add. cites -5.437*

(2.544)

0.553

(2.307)

1.583

(2.011)

425,522


(2.385)

4.762**

(1.568)

2.784+

(1.485)

1,016,350

Note: This table replicates the Key results limited to patents that claim priority to a foreign patent. All analyses are

based on patent data. $: These coefficients are relative to the first seven days of the month.

40


TABLE B12: Analysis of Accelerated Filing Using Foreign Priority Dates

Deadline for Filing

Day 1 of

Month

Days 1-3 of

Month

Days 1-5 of

Month

N

Accelerated 1 day 24.380*

(10.721)

157,780

Accelerated up to 3 days 45.793**

(7.334)

40.787**

(5.868)

243,985

Accelerated up to 5 days 46.461**

(6.089)

59.695**

(6.216)

12.742**

(1.937)

311,089

This table presents coefficient estimates from regressing a dummy that indicates if the filing was accelerated by m

days (row, calculated based on the actual filing date) to file at the end of the previous month, on a dummy that

indicates if the expected deadline (i.e., 365 days after the foreign priority date) falls within the first n days of the next

month (column). Hence, for instance, suppose a patent claims priority to a foreign filing and that foreign filing was

made on Apr 2. Then, the expected deadline based on the 365-day deadline is Apr 2 of the next year, which falls

within the first three days of a month (column “days 1-3 of month”). Now suppose the filing U.S. filing was

actually made on Mar. 31 of the next year. Then, it was accelerated by 2 days (row “accelerated up to 3 days”).

Firm-year size, application year, month, the number of claims, and firm fixed effects are controlled for in all models.

41


TABLE B13: Summary of Results Excluding Provisionals and Continuing Patents

D1 D3 D5 N

Work clustering

Mean daily share

0.476**

(0.138)

0.420**

(0.073)

0.417**

(0.059)

366

Log firm-year

size

3.308**

(0.732)

6.411**

(8.797)

7.710**

(0.853)

2,124,261


Log claims 21.383**

(3.152)

11.058**

(2.037)

8.097**

(1.780)

2,124,261

Log cites (5 yrs.) 11.662*

(3.368)

3.448+

(2.092)

2.601

(1.840)

1,981,709

Renewal (3.5 yrs.) 2.756+

(1.555)

1.866+

(1.039)

2.398*

(0.926)

1,981,709



App. incomplete 46.007**

(13.620)

39.353**

(8.675)

32.747**

(6.909)

47,082

Sep. inv. oaths 44.528**

(9.824)

37.701**

(7.488)

34.515**

(5.935)

47,082

Add. filing fees 42.392**

(11.489)

35.890**

(8.270)

29.664**

(6.541)

47,082


Exam. add. cites -7.989**

(2.464)

-4.390**

(1.540)

-2.533*

(1.251)

861,432

Log review time 11.119**

(1.548)

4.236**

(1.072)

1.807*

(0.906)

2,124,189

Note: This table replicates the Key results excluding provisionals, continuations, continuations-in-part and

divisionals.

42


TABLE B14A: Analysis of End-of-Month Clustering for Provisionals and Continuing Patents

Dependent variable End-of-month dummy

D1 D3 D5

Provisional only 4.152+

(2.234)

-12.539**

(3.336)

-19.452**

(3.537)

Continuation only -17.164**

(1.631)

-30.842**

(2.254)

-31.862**

(2.376)

Continuation-in-part only -2.332**

(1.029)

-9.980**

(1.483)

-13.075**

(1.744)

Divisional only -13.929**

(2.099)

-27.203**

(2.819)

-28.467**

(3.003)

Multiple -13.180**

(1.508)

-26.459**

(2.094)

-30.584**

(2.445)

N 2,839,693 2,839,693 2,839,693

Note: This table presents coefficients on five dummies: a “provisional”, “continuation”, “continuation-in-part”,

and “divisional” dummy indicating that the patent in question was applied as one of those types. The “multiple”

indicates that the patent in question was linked to a parent application in more than one of the aforementioned

ways except a provisional (e.g., divisional of a continuation). Provisionals that were also one of the other types were

dropped due to the non-availability of an exact filing date. The dependent variable is an end-of-month dummy. The

date of filing for provisionals is set to the date of filing of the original provisional application, not the subsequent

non-provisional application. All others use the filing date of the “child” application. Log firm-year size, and fixed

effects for application year, month, and firm are included in all models.

TABLE B14B: End-of-Month Clustering for Provisionals and Continuing Patents (Aggregate)

Dependent variable End-of-month dummy

D1 D3 D5

Provisional only (N=365) 0.591**

(0.165)

0.497**

(0.115)

0.346**

(0.080)

Continuation only (N=364) -0.119

(0.102)

0.000

(0.078)

-0.044

(0.090)

Continuation-in-part only

(N=364)

0.339**

(0.108)

0.297**

(0.080)

0.331**

(0.081)

Divisional only (N=363) 0.072

(0.145)

0.214+

(0.119)

-0.026

(0.119)

Note: This table replicates the results from Table 1 (Col. 7-9) for each of these types of patents/applications.

43


TABLE B15: Summary of Results Excluding Top 10 Largest Firms

D1 D3 D5 N

Work clustering

Mean daily share

0.366**

(0.105)

0.331**

(0.057)

0.311**

(0.047)

366

Log firm-year

size

3.229**

(0.659)

5.832**

(0.886)

6.804**

(0.880)

2,571,478


Log claims 18.394**

(3.379)

8.818**

(2.365)

7.798**

(2.329)

1,527,186


(3.257)

6.236**

(2.087)

3.814*

(1.696)

2,359,999


(1.273)

1.634+

(0.881)

1.777*

(0.751)

1,738,012




(8.806)

28.413**

(5.545)

24.286**

(4.799)

80,740


(7.728)

31.580**

(5.247)

27.808**

(4.474)

80,740


(8.666)

31.435**

(5.937)

26.015**

(5.051)

80,740


Exam. add. cites 2.724

(3.372)

4.695*

(2.045)

4.183*

(1.699)

550,160

App. approved -0.029

(2.342)

-4.307**

(1.610)

-4.396**

(1.267)

690,633


(3.443)

12.738**

(2.416)

7.155**

(2.150)

482,223

Note: This table replicates the Key results excluding the ten largest firms (in terms of patent volume).

44


TABLE B16: Summary of Results Using Pre-1995 Patents

D1 D3 D5 N

Work clustering

Mean daily share

0.157+

(0.852)

0.194**

(0.054)

0.233**

(0.049)

366

Log firm-year

size

2.157**

(0.535)

4.067**

(0.703)

5.203**

(0.782)

1,178,352


Log claims 20.996**

(3.951)

12.322**

(2.668)

9.141**

(1.957)

1,178,352


(4.602)

5.497*

(2.647)

2.197

(2.030)

1,178,352

Renewal (3.5 yrs.) 4.434*

(2.018)

3.903**

(1.302)

4.420**

(1.103)

935,151




(2.345)

8.500**

(1.369)

4.308**

(1.143)

1,178,287

Note: This table replicates the Key results using data on patents applied before 1995. Other measures of work quality are not

available for that time period.

45


FIGURE B2: Month-ends and Application Complexity (Pre-1995)

Note: These graphs replicate the corresponding graphs (Fig. 3 in the paper) for the pre-1995

cohort.

46


TABLE B17A: Inter-Category Differences in Clustering (Aggregated)

D1 D3 D5

Dn 0.095

(0.076)

0.143**

(0.042)

0.167**

(0.035)

Dn X Chemicals 0.031

(0.126)

0.010

(0.072)

0.007

(0.055)

Dn X Computers & Comm. 0.671**

(0.206)

0.621**

(0.106)

0.468**

(0.085)

Dn X Drugs & Medical -0.122

(0.123)

-0.136+

(0.074)

-0.086

(0.057)

Dn X Electrical & Electronics 0.450**

(0.171)

0.332**

(0.085)

0.276**

(0.068)

Dn X Mechanical 0.070

(0.131)

0.020

(0.059)

0.003

(0.048)

N 366 366 366

Note: The regressions are analogous to the columns 7-9 of Table 1 except that these day-level regressions include

interactions of month-end dummies with the technological category. “Miscellaneous” is the omitted category. The

difference between daily share of corporate and individual patents is the dependent variable, and a month-end

dummy is the independent variable of interest. Beginning of month dummy (Days 1-7), and two middle-of-month

dummies (Days 8-15 and Days 16-23) are included in all models. Robust standard errors are in parentheses.

47


TABLE B17B: Summary of Results by Technology Category

D1 D3 D5 N

PANEL A: CHEMICALS

Work clustering

Mean daily share

0.169

(0.106)

0.173*

(0.068)

0.173**

(0.063)

365

Log firm-year

size (Pat.)

1.309

(0.823)

2.884*

(1.399)

2.488

(1.535)

136,239


Log claims 20.895**

(5.709)

17.019**

(4.110)

10.751**

(3.317)

482,504


(6.901)

7.227+

(4.079)

2.539

(3.490)

461,803


(3.119)

2.014

(2.151)

1.923

(1.789)

349,600



App. incomplete -2.320

(34.776)

11.163

(22.468)

13.201

(17.391)

7,705


(30.821)

38.332+

(20.795)

32.008+

(16.672)

7,705

Add. filing fees -3.098

(30.245)

19.471

(20.857)

24.725

(16.687)

7,705



(5.777)

-0.103

(3.376)

3.358

(2.858)

136,239


(6.140)

4.782

(3.887)

4.102

(3.353)

136,239

Note: These regressions replicate the Key results for the “Chemicals” category. All analyses are based on granted

patents.

48



D1 D3 D5 N

PANEL B: COMPUTERS & COMMUNICATIONS

Work clustering

Mean daily share

0.632**

(0.205)

0.729**

(0.112)

0.676**

(0.096)

366

Log firm-year

size (Pat.)

3.758**

(1.375)

7.052**

(1.728)

7.401**

(1.759)

368,755


Log claims 22.783**

(4.758)

11.973**

(3.450)

10.584**

(3.516)

628,109

Log cites (5 yrs.) 16.786**

(6.052)

5.192

(3.820)

2.326

(3.451)

557,785


(2.101)

0.395

(1.421)

1.036

(1.337)

368,895




(20.425)

53.684**

(14.172)

45.154**

(11.418)

20,055


(16.258)

52.863**

(11.938)

48.198**

(9.877)

20,055


(18.354)

44.716**

(13.519)

42.581**

(10.858)

20,055



(3.727)

4.921+

(2.803)

5.098*

(2.230)

368,755


(3.436)

15.941**

(2.889)

10.318**

(2.396)

368,755

Note: These regressions replicate the Key results for the “Computers & Communications” category. All analyses are

based on granted patents.

49



D1 D3 D5 N

PANEL C: DRUGS & MEDICAL

Work clustering

Mean daily share

0.056

(0.102)

0.038

(0.071)

0.901

(0.068)

364

Log firm-year

size (Pat.)

5.692+

(2.935)

8.184**

(3.122)

8.830**

(2.913)

99,873


Log claims 29.210**

(10.588)

16.564**

(6.101)

8.915+

(4.978)

246,973

Log cites (5 yrs.) 22.784+

(12.219)

11.095+

(6.672)

0.204

(5.322)

232,986


(3.749)

3.143

(3.039)

2.988

(2.589)

176,989



App. incomplete 89.002

(60.146)

39.933

(37.095)

20.699

(28.611)

5,115


(52.422)

31.061

(34.750)

-2.439

(27.009)

5,115

Add. filing fees 102.857+

(55.652)

50.186

(35.693)

15.405

(27.535)

5,115



(6.801)

-6.258

(4.057)

-4.358

(3.118)

99,873


(12.593)

1.114

(6.109)

0.227

(4.433)

99,873

Note: These regressions replicate the Key results for the “Drugs & Medical” category. All analyses are based on

granted patents.

50



D1 D3 D5 N

PANEL D: ELECTRICAL & ELECTRONICS

Work clustering

Mean daily share

0.457**

(0.159)

0.399**

(0.089)

0.384**

(0.078)

366

Log firm-year

size (Pat.)

2.300*

(1.037)

5.604**

(1.409)

6.595**

(1.454)

303,486


Log claims 30.880**

(5.406)

19.198**

(3.994)

16.183**

(2.963)

630,045


(6.001)

3.886

(4.288)

4.143

(3.250)

549,336


(2.315)

3.758*

(1.466)

2.687*

(1.311)

411,296



App. incomplete 35.415+

(20.750)

19.470

(12.165)

18.384

(11.280)

16,886


(14.631)

12.091

(9.319)

16.403+

(8.719)

16,886

Add. filing fees 24.055

(16.687)

10.512

(10.183)

8.205

(9.581)

16,886



(3.817)

4.899

(3.010)

5.645*

(2.461)

303,486


(4.127)

4.384*

(2.453)

3.585+

(2.129)

303,486

Note: These regressions replicate the Key results for the “Electrical & Electronics” category. All analyses are based

on granted patents.

51



D1 D3 D5 N

PANEL E: MECHANICAL

Work clustering

Mean daily share

0.204+

(0.110)

0.176**

(0.053)

0.143**

(0.052)

366

Log firm-year

size (Pat.)

2.331**

(0.623)

5.878**

(0.883)

7.333**

(0.897)

176,269


Log claims 30.869**

(5.425)

19.477**

(3.496)

15.897**

(2.824)

491,269


(6.185)

6.147

(3.954)

3.789

(3.208)

454,093


(2.922)

2.031

(1.948)

2.111

(1.644)

343,173




(26.538)

42.418*

(17.487)

35.210*

(16.058)

10,483


(23.868)

26.581+

(15.335)

28.093*

(14.209)

10,483

Add. filing fees 27.698

(26.001)

35.263*

(17.427)

37.283*

(14.627)

10,483



(4.587)

1.248

(2.636)

1.665

(2.279)

176,269


(5.542)

9.681**

(3.325)

6.250*

(3.063)

176,269

Note: These regressions replicate the Key results for the “Mechanical” category. All analyses are based on granted

patents.

52



D1 D3 D5 N

PANEL F: MISCELLANEOUS

Work clustering

Mean daily share

0.153+

(0.078)

0.186**

(0.045)

0.204**

(0.043)

366

Log firm-year

size (Pat.)

3.003**

(0.770)

5.623**

(1.222)

7.151**

(1.373)

129,998


Log claims 24.667**

(6.185)

11.142**

(4.092)

6.382+

(3.643)

398,723


(7.853)

-0.463

(5.345)

6.053

(4.728)

376,890


(3.597)

0.391

(2.438)

2.658

(2.079)

287,828




(40.464)

38.873

(27.443)

46.564*

(23.445)

7,555

Sep. inv. oaths 63.647+

(35.742)

49.453+

(26.647)

54.997*

(21.909)

7,555

Add. filing fees 78.504*

(39.109)

60.925*

(28.219)

56.129*

(24.489)

7,555



(4.943)

3.485

(3.239)

0.609

(2.973)

129,998


(7.099)

4.762

(4.143)

4.385

(3.713)

129,998

Note: These regressions replicate the Key results for the “Miscellaneous” category. All analyses are based on granted

patents.

53


TABLE B18: Summary of Results Excluding Foreign Priority Patents

D1 D3 D5 N

Work clustering

Mean daily share

0.870**

(0.161)

0.625**

(0.091)

0.521**

(0.071)

366

Log firm-year

size (Pat.)

5.523**

(0.780)

8.607**

(1.057)

9.299**

(1.052)

1,629,597


Log claims 33.530**

(3.786)

20.643**

(2.578)

15.065**

(2.202)

1,629,597


(4.297)

5.921*

(2.947)

3.456

(2.387)

1,489,150


(1.690)

1.634

(1.248)

1.735

(1.122)

1,079,167




(16.616)

62.287**

(11.478)

48.349**

(9.945)

37,322


(13.046)

63.460**

(9.076)

48.674**

(8.461)

37,322


(14.308)

61.743**

(10.178)

45.000**

(9.513)

37,322


Exam. add. cites 6.912*

(3.145)

6.047*

(2.515)

5.464**

(1.251)

700,141


(2.573)

14.322**

(1.872)

8.147**

(1.521)

1,629,546

Note: This table replicates the Key results excluding patents that claim priority to a foreign patent. All analyses are

based on patent data.

54


TABLE B19: Results Excluding Provisional, Continuations etc. and Foreign Priority Patents

D1 D3 D5 N

Work clustering

Mean daily share

1.177*

(0.220)

0.834**

(0.123)

0.701**

(0.946)

366

Log firm-year

size (Pat.)

6.789**

(1.016)

10.340**

(1.389)

11.309**

(1.384)

1,101,914


Log claims 19.032**

(4.279)

10.481**

(2.702)

7.579**

(2.436)

1,101,958

Log cites (5 yrs.) 8.429+

(4.944)

1.454

(3.172)

1.059

(2.698)

1,036,961


(2.192)

1.297

(1.552)

1.717

(1.405)

777,231




(17.158)

80.545**

(12.584)

64.199**

(11.488)

21,861


(12.627)

82.907**

(9.363)

66.732**

(9.261)

21,861


(14.556)

82.260**

(10.406)

60.275**

(10.636)

21,861



(3.025)

-2.611

(2.270)

-0.580

(1.863)

433,946


(2.111)

5.887**

(1.514)

3.066**

(1.284)

1,101,878

Note: This table replicates the Key results excluding patents started as a provisional application, patents that are

continuations, continuations-in-part or divisionals, and those that claim priority to a foreign patent. All analyses

are based on patent data.

55


TABLE B20A: Robustness to Alternative Citations and Renewal Time Windows

D1 D3 D5 N



(4.293)

4.452+

(2.463)

1.697

(1.871)

1,178,352


(4.873)

6.508*

(2.807)

3.904+

(2.176)

1,178,352


(5.0152)

7.155*

(2.839)

3.545

(2.230)

1,178,352

Log cites (all yrs.) 2.640

(2.182)

2.654

(1.320)

0.000

(1.163)

1,111,225


(2.312)

2.699+

(1.557)

2.932*

(1.416)

932,751


(2.417)

0.871

(1.610)

1.197

(1.361)

903,480

Note: This table replicates the corresponding Key results for alternative citation windows (3, 8, 12 years and all

available years) and alternative renewal periods (7.5 and 11.5 years). All analyses are based on patent data.

TABLE B20B: Nature of Task Sorting to Month-Ends: Excluding Self-Citations

D1 D3 D5

Log number of citations in 5 years

(excl. self-citations)

15.018**

(3.018)

6.116**

(1.969)

3.897*

(1.682)

N 2,633,488 2,633,488 2,633,488

Note: This table presents regressions of log number of citations during the 5 years after application, excluding

self-citations, on a month-end dummy. Application year, month, and firm fixed effects are included in all

models.

56


TABLE B21 Analysis of Examiner Citations (All years)

D1 D3 D5

Share of citations that are

added by examiner

1.650

(2.288)

3.718*

(1.664)

3.923**

(1.369)

N 1,214,876 1,214,876 1,214,876

Note: This table presents analysis of the share of examiner-added citations using data from all available years

instead of 2001-04 used in the Key estimates. Application year, month, and firm fixed effects are included in all

models.

Table B22: Alternative Measure of Complexity and Quality based on Continuing Patents

D1 D3 D5 N

Resulted in continuation in part

(Complexity)

2.762**

(0.548)

0.654*

(0.324)

0.070

(0.270) 3,901,937

Resulted in divisional

(Quality)

1.966**

(0.673)

0.884*

(0.439)

0.957**

(0.353) 3,901,937

Note: This table replicates the propensity for a month-end application to result in a continuation-in-part (top row), and in a

divisional (bottom row) relative to a non month-end application. Analysis based on related application data from 1976-09.

Application year, month, and firm fixed effects are included in all models.

57


Table B23: Work Flow Clustering and Work Quality (Addition Control of Daily Volume)

Measure D1 D3 D5 N

Work process-based

measures

Application

Incomplete Notice

48.093**

(10.798)

36.148**

(7.657)

29.389**

(5.940)

71,983

Separate Inventor

Oaths

45.449**

(8.629)

35.547**

(6.617)

30.886**

(5.092)

71,983

Additional App.

Filing Fees

14.399*

(6.900)

13.211**

(4.503)

8.418*

(3.913)

71,983

New/Additional

Drawings

41.180**

(9.548)

32.982**

(7.288)

27.325**

(5.775)

71,983

Info. Discl. Stmt.

After Initial Filing

21.268**

(6.392)

10.998*

(4.679)

8.588*

(4.258)

71,983

Non-Final Rejection 19.437*

(8.815)

7.531

(6.080)

8.575+

(4.978)

71,983

Request for

Extension of Time

20.751**

(6.125)

11.951*

(4.645)

16.648**

(3.818)

71,983

Restriction/Election

Requirement

19.854*

(9.120)

10.911

(6.661)

11.839*

(5.606)

71,983

Quality Factor 1 102.667**

(19.487)

79.288**

(14.807)

67.600**

(11.497)

71,983

Work outcome-based

measures

Examiner Add. Cite

Share

3.507

(3.513)

6.479**

(2.025)

5.740**

(1.760)

627,209

Application

Approved

-23.909**

(2.726)

-17.211**

(1.930)

-14.004**

(1.542)

634,972

Log Review

Duration

16.532**

(3.661)

9.650**

(2.469)

5.410*

(2.103)

557,493

Note: Each cell presents the coefficient estimate and the standard error of the corresponding end-of-month

dummy (D1, D3, and D5). Log firm-year size, log firm-day application volume, application year, month, and

firm fixed effects are included in all models.

58


TABLE B24: Alternative Measures of Firm size

Dep. Var.: End-of-

month Dummy

Specification Size measure Coeff. on

Firm Size

Coeff. on

Pat. Vol.

Last Working Day Size only Log Assets 4.223** -

Last Working Day Size & volume Log Assets 1.812 2.994*

Last 3 Working Days Size only Log Assets 6.822** -

Last 3 Working Days Size & volume Log Assets 2.289 5.629**

Last 5 Working Days Size only Log Assets 7.968** -

Last 5 Working Days Size & volume Log Assets 3.341+ 5.745**

Last Working Day Size only Log Sales 4.206** -

Last Working Day Size & volume Log Sales 2.230+ 2.604*

Last 3 Working Days Size only Log Sales 6.577** -

Last 3 Working Days Size & volume Log Sales 2.282 5.660**

Last 5 Working Days Size only Log Sales 7.517** -

Last 5 Working Days Size & volume Log Sales 2.762+ 6.267**

Last Working Day Size only Log Employment 4.145** -

Last Working Day Size & volume Log Employment 0.858 3.941**

Last 3 Working Days Size only Log Employment 6.668** -

Last 3 Working Days Size & volume Log Employment 0.642 7.224**

Last 5 Working Days Size only Log Employment 7.615** -

Last 5 Working Days Size & volume Log Employment 0.833 8.131**

Note: This table presents estimates from regressions of a month-end dummy on alternative measures of firm size and

our preferred measure of firm size (annual patent volume). Standard errors not presented to conserve space.

59


TABLE B25A: Firm Size-Deadlines Association with Application Data

D1 D3 D5

Log Firm-year Size 2.662**

(0.700)

5.350**

(1.075)

6.001**

(1.195)

N 1,856,934 1,856,934 1,856,934

Note: This table presents re-estimates of log firm-year size result (Table 4, row 1) using application data from

2001-10.

TABLE B25B: Firm Size-Deadlines Association with Inventor and Class Fixed Effects

D1 D3 D5

Patent class fixed effects 2.284**

(0.454)

4.560**

(0.571)

5.481**

(0.578)

Inventor fixed effects 1.464** 2.573** 2.670**

(0.238) (0.392) (0.481)

Note: This table presents estimates on log firm-year size with patent class and inventor fixed effects. The

dependent variable is 1 if the application was filed on a month-end and zero otherwise. The regressions are

estimated using patent-level data in the first row (N=2,878,229) and inventor-patent level data in the second row

(N=6,386,845).

60


Table B26A: Key Results for Patents/Apps with Less than or Equal to 20 Claims

D1 D3 D5 N

Work clustering

Mean daily share

0.296**

(0.099)

0.289**

(0.053)

0.282**

(0..046)

366

Log firm-year

size

2.326**

(0.464)

4.822**

(0.564)

5.831**

(0.561)

2,235,680




(10.677)

28.927**

(7.074)

28.080**

(5.637)

53,007


(9.327)

27.751**

(6.495)

29.541**

(5.179)

53,007


(10.771)

30.199**

(7.413)

29.444**

(5.943)

53,007



(3.292)

5.379*

(2.113)

5.982**

(1.961)

426,513


(2.631)

-5.662**

(1.822)

-3.867**

(1.504)

437,397


(4.476)

14.890**

(3.281)

8.370**

(2.821)

317,558

Note: This table replicates the key estimations for patents and applications with less than or equal to 20 claims.

61


Table B26B: Key Results for Patents/Apps with More than 20 Claims

D1 D3 D5 N

Work clustering

Mean daily share

0.623**

(0.050)

0.557**

(0.082)

0.516**

(0..068)

365

Log firm-year

size (Pat.)

5.629**

(1.273)

9.813**

(1.578)

11.099**

(1.499)

642,549




(16.958)

47.655**

(11.471)

33.346**

(8.970)

39,526


(13.950)

52.819**

(10.371)

38.842**

(7.923)

39,526


(14.966)

46.092**

(11.201)

31.682**

(8.606)

39,526



(5.295)

2.768

(3.117)

1.074

(2.739)

200,696


(3.321)

-3.340

(2.213)

-5.082**

(1.710)

347,762


(4.945)

10.108**

(3.347)

7.292**

(3.079)

239,892

Note: This table replicates the key estimations for patents and applications with more than 20 claims.

62


Table B26C: Work Flow Clustering and Application Work Quality (Interaction with Claims)

Measure D1 D3 D5 N

Work process-based

measures

Application

Incomplete Notice

40.029*

(15.771)

12.917

(10.184)

0.056

(0.781)

92,533

Separate Inventor

Oaths

23.052

(14.570)

12.916

(9.651)

1.908

(7.373)

92,533

Additional App.

Filing Fees

12.255

(14.824)

1.344

(9.711)

-6.211

(7.522)

92,533

Work outcome-based

measures

Examiner Add. Cite

Share

15.928*

(6.254)

5.655

(4.161)

0.987

(3.534)

627,209

Application

Approved

5.790

(5.552)

2.755

(3.614)

-1.951

(2.922)

785,159

Log Review

Duration

0.694*

(0.334)

0.900

(2.368)

1.011

(1.861)

2,878,133

Note: This table replicates the key estimations on work quality with a dummy that is 1 if the number of claims is more than

or equal to 20. Each of the above cells presents the coefficient estimate and the standard error of the interaction term.

Application year, month, and firm fixed effects are included in all models.

63


TABLE B27A: Work Quality Controlling for Firm-Claims Fixed Effects

Measure D1 D3 D5 N

Work process-based

measures

Application

Incomplete Notice

50.341*

(19.074)

38.685**

(12.886)

34.371**

(10.081)

92,533

Separate Inventor

Oaths

50.853**

(15.040)

35.354**

(11.155)

35.168**

(8.617)

92,533

Additional App.

Filing Fees

44.915**

(16.640)

31.693**

(12.220)

30.793**

(9.681)

92,533

Work outcome-based

measures

Examiner Add. Cite

Share

1.929

(4.904)

5.184+

(2.788)

5.365*

(2.541)

627,209

Application

Approved

-3.423

(2.961)

-5.524**

(2.005)

5.576**

(1.576)

785,159

Log Review

Duration

21.233**

(5.109)

13.772**

(3.512)

9.025**

(3.189)

557,493

Note: This table replicates the key estimations on work quality with joint firm-claims fixed effects included. Application

year, and month fixed effects are also included in all models.

64


TABLE B27B: Work Complexity and Quality Controlling for Firm-Volume Fixed Effects

D1 D3 D5 N


Log claims 19.702**

(2.964)

12.010**

(1.916)

8.302**

(1.527)

1,856,804


(2.855)

5.992**

(1.918)

3.414*

(1.544)

2,633,488


(1.186)

2.141**

(0.823)

2.177**

(0.725)

1,938,295




(10.222)

36.284**

(6.845)

27.934**

(5.436)

92,533


(8.013)

37.570**

(6.102)

30.721**

(4.911)

92,533


(8.875)

35.440**

(6.709)

27.776**

(5.491)

92,533



(3.308)

3.352+

(1.862)

3.594*

(1.705)

627,209

Application approved -1.551

(2.137)

-4.223**

(1.474)

-4.402**

(1.158)

785,159


(3.852)

13.149**

(2.576)

8.482**

(2.373)

557,493

Note: This table replicates the key estimations on work quality with joint firm-volume fixed effects included. Volume is

defined as the number of patents or applications in a firm-application year-month cell. Application year, and month fixed

effects are also included in all models.

65


TABLE B28: Work Complexity and Quality Controlling for Firm-Year-Month Fixed Effects

D1 D3 D5 N


Log claims 20.519**

(3.948)

12.666**

(2.592)

9.050**

(2.050)

1,856,804


(4.122)

7.508*

(3.040)

5.121*

(2.404)

2,633,488


(1.667)

2.226+

(1.191)

1.996+

(1.075)

1,938,295




(16.711)

38.502**

(12.014)

29.714**

(9.505)

92,533


(12.229)

36.624**

(10.504)

30.284**

(8.386)

92,533


(13.895)

35.413**

(11.597)

28.408**

(9.297)

92,533



(4.534)

3.052

(2.567)

3.781

(2.397)

627,209

Application approved -1.528

(2.791)

-4.510*

(1.965)

-4.815**

(1.534)

785,159


(5.189)

14.751**

(3.537)

9.956**

(3.304)

557,493

Note: This table replicates the key estimations on work quality with joint firm-year-month fixed effects included.

66


TABLE B29: Costs associated with Work Process Quality Measures

Process Quality Measure USPTO

Fees

Attorney

time

costs

Total

Costs

Application Incomplete Notice 140 262 402

Separate Inventor Oaths 140 207 347

Additional App. Filing Fees 140 86 226

New/Additional Drawings 140 380 520

Info. Discl. Stmt. After Initial Filing 0 167 167

Non-Final Rejection 0 1770 1770

Request for Extension of Time 200 68 268

Restriction/Election Requirement 0 437 437

Note: Information for atoner time costs are obtained as a product of the average attorney opportunity cost of time (estimated

at $250/hour) and the average additional time costs indicated by respondents to a survey for each of the indicated process

quality measures (See Online Appendix V.S4 for details on the survey). The USPTO fees (and our estimate of the

opportunity cost of attorney time) are based on information provided by a patent attorney interviewee; USPTO fees were

verified using information from the USPTO website.

67

V. SURVEY DESCRIPTION, ANALYSIS OF RESPONSES AND

SUMMARY TABLES

68

V.S1: Survey of R&D Inventors

S1: SURVEY OF R&D INVENTORS

OVERVIEW

This is one of four online surveys we conducted including (a) Research and Development

(R&D) Inventors (S1) (b) Patent Attorneys at Law Firms (S2) (c) Patent Attorneys at Corporate

Firms (S3). We also undertook a brief follow-on survey with the patent attorneys at law firms, to

assess attorney’s reasons for the observed pattern of greater complexity at month-ends, as well

as costs of rework associated with process work quality measures (S4).

The broad objective of these surveys was to understand the use of deadlines in their

organizations, specifically around patenting and related outcomes. All surveys were conducted

online using the Qualtrics website provided by our employers. Where information on

individuals was being collected (among R&D inventors), the survey instrument was reviewed

and approved by the Institutional Review Board at [a] University.

This survey was administered to alumni of a globally known technology institute based in

India, whose email addresses were available at the alumni office of that institution. The alumni

office administered the survey instrument via an email link. Alumni of this institute are widely

dispersed around the world and many of them work in leading technology firms as engineers

and inventors. While the choice of this institution was driven by our own histories, we believe

that the use of the alumni office not only led to a higher response rate but also greater accuracy

of responses.

The initial part of the survey focused on the career paths and specializations of the alumni

including whether they work (or have worked) in R&D. This part of the survey was not used

for this study. The second part of the survey focused on performance evaluation for inventors at

their organizations, while the third part examined patenting practices.

We provide the overall number of responses and where relevant, the mean response by

question later in this note. Note that we do not provide the response rate since not everyone in

the target population worked in R&D, and we do not know the number who work(ed) in R&D.

Since the respondents were employed in firms and other organizations, where relevant, we also

provide the corresponding numbers for those who were employed at firms. Firms were

identified using a visual examination combined with an Internet search.

69


ANALYSIS AND SELECT RESPONSE SUMMARIES

TABLE S1A: Time from management approval to filing

Time period Number of

responses

% of responses

< 15 days 6 8%

15 days--1 month 13 18%

1--3 months 33 46%

3--6 months 3 4%

6--12 months 15 21%

Other/unknown 2 3%

Total 72 100%

70


TABLE S1B: Key performance criteria for R&D organization

PANEL A: OVERALL DISTRIBUTION

Criteria Number of

responses

% of responses

Number of patents applied for 50 35%

Number of new products introduced 85 60%

Cycle time for new product development 69 49%

Number of articles published 53 38%

Process improvements & cost savings

achieved

87 62%

Other$ 29 21%

Total 141

$: Some examples in this category include grants, quality of research, research progress, and

regulatory approvals.

PANEL B: DISTRIBUTION AMONG THOSE NUMBER OF PATENT

APPLICATIONS AS CRITERION

Criteria Number of

responses

% of responses

Number of new products introduced 37 74%

Cycle time for new product development 32 64%

Number of articles published 27 54%


achieved

36 72%

Other 10 20%

Total 50

71


TABLE S1C: Importance of performance criteria for individual inventor

Criteria Mean

Importance

(1-10)

Number of

responses

Journal Publications 4.17 127

Conference Papers 4.21 128

Patent Applications 6.38 130

Patent Grants 6.65 127

Other$ 9.21

62

$: The main criteria in this category appears to be related to commercialization of the invention,

and includes criteria such as new product development, revenues, market introduction, product

launch etc.

TABLE S1D: Reported inventor performance review months and distribution of patent

filings

Month of patenting Min. Mode Max. Mode

Same month as review month 8.08% 8.89%

Month prior to review month 9.22% 9.55%

Other months (average) 8.27% 8.16%

Note: Based on granted patent data from 1996-2009 from 21 organizations (42 assignees)

mentioned as employers by respondents and that could be matched to patent and lawyer

data. For organizations with multiple respondents with differing deadline periods, the

most frequent deadline period was chosen.

TABLE S1E: Reported attorney deadlines and distribution of patent filings

Deadline

Period

J F M A M J J A S O N D Number

of

Patents

Monthly 8.45 7.16 8.63 8.43 8.25 9.53 8.01 8.02 8.52 8.57 7.60 8.83 75,177

Quarterly 6.69 6.30 9.89 7.51 7.51 11.84 6.82 7.15 9.20 7.67 6.90 12.53 51,195

Annual 6.30 6.09 7.43 6.92 7.44 8.22 7.11 8.31 8.40 9.29 9.65 14.85$ 17,682

Note: Numbers shaded in gray denote difference from corresponding share for the monthly deadlines significantly

higher at the 1% level. $: Significantly higher than corresponding share for the quarterly deadlines. Based on

granted patent data from 1996-2009 from 21 organizations (42 assignees) mentioned as employers by respondents

and that could be matched to patent and lawyer data. For organizations with multiple respondents with differing

deadline periods, the most frequent deadline period was chosen.

72


FIGURE S1A: Reported external attorney deadlines and distribution of patent filings

Note: Blue (solid): Monthly; Green (dash): Quarterly; Red (dot): Annual. Difference between quarter-end shares for

quarterly deadlines from corresponding share for the monthly deadlines significantly higher at the 1% level. Year-

end share for annual deadline significantly higher than corresponding share for the quarterly deadlines. Based on




0.05

0.10

0.15

Mo

nth

ly S

har

e

3 6 9 12Month

73


FIGURE S1B: Reported internal reporting deadlines and distribution of patent filings

Note: Blue (solid): Monthly; Green (dash): Quarterly; Red (dot): Annual. Difference between quarter-end shares for

quarterly deadlines from corresponding share for the monthly deadlines significantly higher at the 1% level. Year-

end share for annual deadline significantly lower than corresponding share for the quarterly deadlines. Based on




TABLE S1F: Reported number of performance evaluations per year

Annual 62

Monthly 0

Semi-Annual 91

Quarterly 16

Total 169

0.05

0.10

0.15

Mo

nth

ly S

har

e

3 6 9 12Month

74


SUMMARY OF ALL RESPONSES

Questions 1-9 focused on the career paths and specializations of the respondents, and are

unrelated to this study.

Question 10. Which performance measures are important in internal performance reviews in your firm

(or the group) you work for? Rate on a score of 1 (low importance) to 10 (high importance).

ALL RESPONSES

Criteria Number of

responses

Mean

Importance

Number of patents applied for 226 5.96

Number of new products introduced 226 5.19

Cycle time for new product development 223 6.29

Number of articles published 219 6.54


achieved

106 8.93

Other$ 118 -



FIRMS ONLY

Criteria Number of

responses

Mean

Importance

Number of patents applied for 127 4.17

Number of new products introduced 128 4.21

Cycle time for new product development 130 6.38

Number of articles published 127 6.65


achieved

62 9.21

Other$ 70 -



75


Q11. What is the annual planning and reporting cycle at your organization? (i.e., do you follow the

calendar year, or do you have a different internal reporting year?)

ALL RESPONSES

Cycle start date Number of

responses

Jan 1 87

Apr 1 48

Other 73

Total 208

FIRMS

Cycle start date Number of

responses

Jan 1 54

Apr 1 13

Other 9

Total 86

76


Q12. What is the frequency of internal reports? Please consider only those reports that are part of the

formal management reporting system.

ALL RESPONSES

Number of

responses

Monthly 58

Quarterly 45

Semi-annual 30

Annual 62

Other 26

Don’t know 17

Total 240

FIRMS

Number of

responses

Monthly 33

Quarterly 29

Semi-annual 9

Annual 12

Other 6

Don’t know 9

Total 98

77


Q13. Which performance measures are important parts of the annual plan for the R&D department or

organization as a whole? Please select all that apply.

ALL RESPONSES

Criteria Number of

responses

Number of patents applied for 126

Number of new products introduced 102

Cycle time for new product development 88

Number of articles published 106


achieved

129

Other$ 52

FIRMS

Criteria Number of

responses

Number of patents applied for 50

Number of new products introduced 85

Cycle time for new product development 69

Number of articles published 53


achieved

87

Other$ 29

$: Some examples in this category include grants, quality of research,

research progress, and regulatory approvals.

78


Q14. In any year, when are R&D personnel reviewed for their performance? Please include the

main/annual review date and any other dates, if applicable.

ALL RESPONSES (MAIN/ANNUAL REVIEW)

Month Number of

responses

January 15

February 6

March 25

April 19

May 9

June 10

July 9

August 5

September 4

October 7

November 10

December 28

Other 9

Total 156

79


FIRMS

Month Number of

responses

January 11

February 4

March 12

April 6

May 3

June 6

July 4

August 2

September 1

October 3

November 8

December 11

Other 3

Total 74

Q15. Are you reasonably familiar with the patenting process?

ALL FIRMS

Yes 159 85

No 97 19

Q16. As an inventor, what is your average contribution in the drafting of the patent application? Rate

on a 10 point scale with 1 (very little of the drafting) to 10 (Almost all of the drafting).

All Respondents: N: 153; Average: 5.90

Firms: N: 82; Average: 6.33

80


Q17. Does the patent application require approval from top management? If yes, how long does it take

(on average) from approval by management to filing of the application?

ALL FIRMS

Yes 128 68

No 24 16

Total 152 84

Time period ALL FIRMS

< 15 days 13 6

15 days--1 month 16 13

1--3 months 44 33

3--6 months 16 3

6--12 months 9 15

Other/unknown 4 2

Total 104 72

Q18. If you use internal attorneys to file patents, what are their deadlines for reporting and review?

Please check all that apply. If reporting and review have different deadlines, please choose “other” and

elaborate in the space provided.

ALL FIRMS

End of month 11 7

End of quarter 24 17

End of calendar year 11 4

Other 30 10

Don’t know 68 32

Total 144 70

81


Q19. Do you provide specific calendar deadlines to external attorneys to file patents?

ALL FIRMS

Yes 128 25

No 24 54

Total 152 79

Q20. If you answered yes to the above question, what are the deadlines for them to report to you? Please

select all that apply.

ALL FIRMS

End of month 6 2

End of quarter 16 9

End of calendar year 6 3

Other 13 8

Don’t know 7 3

Total 48 25

82

V.S2: Survey of Law Firm Patent Attorneys

S2: SURVEY OF LAW FIRM PATENT ATTORNEYS

OVERVIEW

This is one of four online surveys we conducted: (a) Research and Development (R&D)

Inventors (b) Patent Attorneys at Law Firms (c) Patent Attorneys at Corporate Firms (d) Patent

Attorneys at Law Firms (Follow-up). The broad objective of these surveys was to understand

the use of deadlines in their organizations, specifically around patenting and related outcomes.

All surveys were conducted online using the Qualtrics website provided by our employers.

Where information on individuals was being collected (among R&D inventors), the survey

instrument was reviewed and approved by the Institutional Review Board at [a] University.

This survey was administered to patent attorneys at law firms based on a list of email addresses

(and names of the attorneys and their law firms) purchased from Exactdata.com. The survey

was sent to a total of 768 valid email addresses. The number of responses varied from 47 to 65

corresponding to a response rate of (6.1 to 8.5%). The exact number of responses by question is

included in the tables later in the note. The responses were then matched to the patent data

using the names of the law firms. Together, the firms that we were able to match to the patent

data accounted for about 114,000 patents applied (and granted) between 1995 and 2009 though

the number dropped considerably when matching to individual questions (to between 38,000

and 65,000).

83


ANALYSIS AND SELECT RESPONSE SUMMARIES

Since many of the questions in this survey were the same as the survey of corporate patent

attorneys, we present a combined analysis where appropriate.

TABLE S2A: Who determines the exact date of application filing?

Agent Number of

responses

% of responses

Inventor 3 4%

Law firm attorney 29 42%

Client IP/legal 30 43%

Other 7 10%

Total 69 100%

Note: Based on surveys of law firm attorneys (N=56) and corporate patent

attorneys (N=13). “Other” includes business requirements, planned public

disclosure, both law firm and in-house counsel etc.

TABLE S2B: Time between invention disclosure to attorney and filing


responses

% of responses

2 weeks--1 month 16 24%

1--2 months 27 41%

2--3 months 12 18%

3 months or longer 9 14%

Other/unknown 2 3%

Total 66 100%

Note: Based on surveys of law firm attorneys (N=53) and corporate patent

attorneys (N=13).

84


TABLE S2C: Risks related to rushing

Frequency of Occurrence

Risk “Sometimes” or

more often

“Often” or

more often

(1) Lack of clarity in specifications$ 84% 32%

(2) Inadequate prior art disclosure 48% 19%

(3) Loss of priority date# 18% 8%

(4) Additional work, filing fees etc. 60% 17%

(5) Rejection of certain claims 64% 18%

(6) Client dissatisfaction 52% 10%

Note: Based on surveys of law firm attorneys (N~50) and corporate patent attorneys

(N~13) except client dissatisfaction, which is based only on law firm attorneys. $:

Mann-Whitney two-sample statistic significantly different from zero at the 5% level

or less when risk (1) is compared with every other risk. #: Mann-Whitney two-

sample statistic significantly different from zero at the 5% level or less when risk (3)

is compared with every other risk. All other comparisons yield statistically

insignificant Mann-Whitney two-sample statistics.

TABLE S2D: Cost (to attorney) of not meeting deadline

Frequency of Occurrence

Risk “Sometimes” or

more often

“Often” or

more often

(1) Loss of monetary incentives 31% 8%

(2) Lower performance evaluations 74% 36%

(3) Pressure from colleagues 60% 19%

Note: Based on surveys of law firm attorneys (N~48).

85


TABLE S2E: Perceived negative effect of office actions

Office action Perceived as “Somewhat

negatively” or worse

(1) Application incomplete 59%

(2) Request for extension of time$ 70%

(3) Non-final rejection# 0%

(4) Restriction/election requirement# 2%

(5) New drawings to be filed 52%

(6) Additional filing fees 45%

Note: Based on surveys of law firm attorneys (N~50) and corporate patent

attorneys (N=12). $: Mann-Whitney two-sample statistic significantly

different from zero at the 5% level or less when action (2) is compared with

(3), (4), (5) and (6). #: Mann-Whitney two-sample statistic significantly

different from zero when actions (3) and (4) are compared with every other

action except with each other. All other comparisons yield statistically

insignificant Mann-Whitney two-sample statistics.

TABLE S2F: Billing cycles for external attorneys

Periodicity Number of

responses

Share of

responses

At the end of every month 38 69%

At the end of every quarter 1 2%

At the end of every year 0 0%

Irregular/other 16 29%

Total 55 100%

Note: Based on surveys of law firm attorneys (N=50) and corporate patent attorneys (N=5).

86


TABLE S2G: Determinants of Month-end Filing

Dependent Var. D1 D3 D5

Costly to miss

deadlines

22.137**

(7.170)

26.428*

(11.504)

40.442**

(13.181)

Negative perception -27.050**

(4.921)

-25.428*

(10.311)

-19.472+

(10.201)

Billing as a reason for

clustering

23.022**

(5.985)

6.683

(9.026)

-3.407

(10.086)

Client-imposed

deadlines

-1.591

(5.476)

7.743

(8.451)

8.103

(10.493)

Note: N=38,457. Application year, and month fixed effects are included in all models. Errors are clustered

by firm.

87


TABLE S2H: Effects of Clustering on Task Sorting and Work Quality

D1 D3 D5


Log claims

(N=38,457)

Costly to miss deadlines -61.447

(73.899)

51.564

(47.886)

30.189

(46.847)

Negative perception 53.650

(68.187)

88.062+

(51.222)

48.100

(48.368)

Billing as reason for clustering 64.800

(64.318)

-56.433

(46.228)

-45.956

(38.239)

Client-imposed deadlines -87.902+

(44.647)

-45.790

(40.730)

-29.969

(35.533)

Log cites (5 yrs.) Costly to miss deadlines -78.523

(121.252)

64.750

(61.226)

57.123

(51.898)

Negative perception 92.865

(103.461)

239.655**

(65.805)

154.926**

(53.719)

Billing as reason for clustering -104.636

(116.518)

-184.154**

(67.858)

-72.942

(55.604)

Client-imposed deadlines -97.850

(75.861)

-53.748

(59.924)

14.448

(48.927)

Renewal (3.5 yrs.) Costly to miss deadlines -15.256

(23.843)

12.533

(13.739)

24.061+

(14.562)

Negative perception -19.093

(22.881)

-3.338

(10.947)

3.069

(11.643)


(24.206)

-6.479

(12.461)

-8.022

(12.575)


(21.370)

-22.792

(13.843)

-19.986

(12.946)


Share of examiner-added

cites

Costly to miss deadlines 34.861

(32.673)

21.571

(21.379)

19.932

(18.531)

(N=33,476) Negative perception 23.882 -41.882+ -48.173**

88


(29.180) (22.314) (17.240)


(28.863)

12.332

(19.963)

37.845*

(17.746)


(26.937)

-18.266

(18.554)

-8.343

(15.009)

Review duration

(N=38,457)

Costly to miss deadlines 23.242

(37.364)

-.3.0494

(27.046)

-15.984

(22.826)

Negative perception -55.859+

(33.001)

-55.640*

(22.307)

-37.911*

(16.726)


(33.600)

20.225

(25.034)

31.803+

(18.959)


(23.043)

-12.403

(19.887)

-1.516

(16.931)

Note: Each cell presents the coefficient estimate and the standard error of the interaction term between the

reason for the clustering and end-of-month dummy (D1, D3, and D5). Application year and month fixed

effects are included in all models. Errors are clustered by firm.

89


FIGURE S2A: Effect of Negative Perception of Office Actions on Clustering of Patent Filing

Note: This figure depicts the average share of patents filed on the last day of the month

over the year. Solid line indicates applications filed by law firms with negative perception

= 1 and the dotted line with negative perception = 0. Negative perception was defined as 1

if the respondents rated receiving any of the four office actions in Table S2E (1, 2, 5, and

6) as being viewed “Somewhat negatively” or worse.

90


FIGURE S2B: Billing Clustering As a Likely Reason and Clustering of Patent Filings


over the year. Solid line indicates patents filed by the responder law firms who said billing

was a likely reason for the clustering and the dotted line corresponds to patents filed by

those who did not choose billing as a likely reason for the observed clustering.

91


FIGURE S2C: Client-imposed Deadlines as a Likely Reason and Clustering of Patent Filings


over the year. Solid line indicates patents filed by responder law firms who indicated

client-imposed deadlines as a likely reason for the observed clustering and the dotted line

corresponds to law firms who did not choose client-imposed deadlines as a likely reason for

the observed clustering.

92


FIGURE S2D: Effects of Costly-to-Miss Deadlines on Clustering of Patent Filing

Note: This figure depicts the average share of patents filed on the last day of the month over the year.

Solid line indicates patents filed by responder law firms who indicated “costlymiss,” defined as 1 if the

respondent rated any of the consequences (loss of monetary incentives, lower performance evaluations,

and pressure from colleagues) at “sometimes” or higher, and the dotted line indicates otherwise.

93



Question 1. Which technology does your group (or firm) predominantly work in?

ALL RESPONSES

Criteria Number of

responses

a. Chemicals 4

b. Computers & communications 8

c. Drugs & medical 12

d. Electrical & electronics 25

e. Mechanical 15

f. Others 1

Total 65

Question 2. What is the typical time (in working days) between an invention disclosure by the client to

the application filing?


responses

2 weeks--1 month 15

1--2 months 22

2--3 months 12

3 months or longer 2

Other/unknown 2

Total 53

94


Question 3. Who typically determines the exact date of filing of the patent application?

ALL RESPONSES

Criteria Number of

responses

a. Inventor 2

b. Law firm attorney 27

c. Client IP/legal department 22

d. Other 5

Total 56

Question 4. Our statistical analyses of USPTO data show that patent application filing volumes are not

uniform over all days of the year, but show certain regular clustering patterns. Based on your firm’s

experience and industry practices, what would be the timing of these patterns? Check all that apply.

ALL RESPONSES

Criteria Number of

responses

a. The first day of the month 25

b. The 15th day of the month 0

c. The last day of the month 1

d. The last day of the quarter 16

e. The last day of the calendar year 13

f. Other 11

Total --

95


Question 5. We find that filings are clustered in the last few days of every month. Based on industry

practices, what may be likely reason(s) for this clustering? Check all that apply.

ALL RESPONSES

Criteria Number of

responses

a. Deadlines associated with billing

cycles at law firms

21

b. Deadlines associated with individual

attorney work schedules

13

c. Client-imposed deadlines 35

d. Deadlines facing inventors 6

e. Deadlines arising from work

schedules in corporate R&D

departments

13

f. Other deadlines (please specify) 6

g. Other factors not related to deadlines

(please specify)

0

Total --

96


Question 6.1. What are the risks of expediting an application to meet a deadline? Please ignore

statutory deadlines such as the 12-month period for foreign filings here. Choose all that apply and

rate them on how likely they are to occur (Never, Rarely, Sometimes, Often, Almost every time).

a. Inadequate detail/lack of clarity in the specifications

ALL RESPONSES

Criteria Number of

responses

Never 0

Rarely 8

Sometimes 25

Often 12

Almost every time 5

Total 50

b. Inadequate prior art disclosure

ALL RESPONSES

Criteria Number of

responses

Never 11

Rarely 16

Sometimes 14

Often 6

Almost every time 3

Total 50

97


c. Loss of priority date

ALL RESPONSES

Criteria Number of

responses

Never 22

Rarely 17

Sometimes 6

Often 3

Almost every time 1

Total 49

d. Additional work, filing fees etc.

ALL RESPONSES

Criteria Number of

responses

Never 5

Rarely 15

Sometimes 20

Often 7

Almost every time 3

Total 50

98


e. Rejection of certain claims

ALL RESPONSES

Criteria Number of

responses

Never 6

Rarely 12

Sometimes 23

Often 5

Almost every time 2

Total 48

f. Client dissatisfaction with work quality

ALL RESPONSES

Criteria Number of

responses

Never 5

Rarely 19

Sometimes 21

Often 5

Almost every time 0

Total 50

99


Question 7. How often are applications expedited to meet a non-statutory deadline (e.g., billing cycle or

revenue-related)? (Never, Rarely, Sometimes, Often, Almost every time)

ALL RESPONSES

Criteria Number of

responses

Never 6

Rarely 10

Sometimes 28

Often 5

Almost every time 1

Total 50

Question 8.1. Suppose an application was not filed on time to meet a non-statutory deadline due to a

reason under the attorney’s control. What are the possible consequences (to the attorney) of missing the

deadline? Choose all that apply and rate them on how likely they are to occur (Never, Rarely, Sometimes,

Often, Almost every time).

a. Loss of monetary incentives, if any, associated with that filing

ALL RESPONSES

Criteria Number of

responses

Never 19

Rarely 14

Sometimes 11

Often 2

Almost every time 2

Total 48

100


b. Lower ratings in performance evaluations

ALL RESPONSES

Criteria Number of

responses

Never 5

Rarely 7

Sometimes 18

Often 12

Almost every time 5

Total 47

c. Pressure from colleagues/superiors relating to unbilled hours

ALL RESPONSES

Criteria Number of

responses

Never 10

Rarely 9

Sometimes 20

Often 8

Almost every time 1

Total 48

101


Question 9.1. Suppose an application filed by your firm received or required the following office actions.

Rate them on how they might reflect on the quality of the work performed by the attorney (Positively, No

Effect, Somewhat Negatively, Negatively, Very Negatively). Consider the actions one at a time,

independent of others.

a. Application Incomplete – Filing Date Assigned

ALL RESPONSES

Criteria Number of

responses

Positively 0

No Effect 20

Somewhat Negatively 24

Negatively 2

Very Negatively 3

Total 49

b. Request for Extension of Time

ALL RESPONSES

Criteria Number of

responses

Positively 0

No Effect 14


Negatively 9

Very Negatively 1

Total 48

102


c. Non-final Rejection

ALL RESPONSES

Criteria Number of

responses

Positively 0

No Effect 47


Negatively 0

Very Negatively 0

Total 47

d. Restriction/Election Requirement

ALL RESPONSES

Criteria Number of

responses

Positively 1

No Effect 47


Negatively 0

Very Negatively 0

Total 49

103


e. Payment of additional filing fee/Preexam

ALL RESPONSES

Criteria Number of

responses

Positively 0

No Effect 0


Negatively 0

Very Negatively 0

Total 0

f. New or Additional Drawing Filed

ALL RESPONSES

Criteria Number of

responses

Positively 0

No Effect 24


Negatively 8

Very Negatively 1

Total 50

g. Additional Application Filing Fees

ALL RESPONSES

Criteria Number of

responses

Positively 1

No Effect 27


Negatively 7

Very Negatively 1

Total 50

104


Question 10. Does your firm have a regular billing cycle for your clients? If yes, what is the cycle?

ALL RESPONSES

Criteria Number of

responses

No, we do not have a regular billing cycle 7

Yes, at the end of every month 34

Yes, at the end of every quarter 1

Yes, at the end of every year 0

Yes, other 8

Total 50

Question 11. Do the fees for attorney services normally depend on the complexity of the application (e.g.,

are the fees dependent on the number of claims, specifications and drawings)?

ALL RESPONSES

Criteria Number of

responses

No 15

Yes 35

Total 50

Question 12. When are fees for attorney services related to application filing typically paid?

ALL RESPONSES

Criteria Number of

responses

Periodically, based on hours incurred 14

Upon filing of the application 29

Other (please specify) 7

Total 50

105

V.S3: Survey of Corporate Patent Attorneys

S3: SURVEY OF CORPORATE PATENT ATTORNEYS

OVERVIEW








This survey was administered to patent attorneys at inventing firms based on a list of email

addresses (and names of the attorneys and their law firms) purchased from Exactdata.com. The

survey was sent to a total of 338 valid email addresses. We received 13 responses (response rate

of 3.4%). Since the number of response was not adequate for any detailed statistical analyses, we

did not match them to the patent data. Instead, we used them primarily to identify any

anecdotal patterns and checking consistency with the results of other surveys and our own

conjectures. In some instances when presenting the results of the survey, where appropriate, we

combined the responses with the results from the survey of attorneys at law firms.

106



Question 1. Which technology does your group or firm predominantly work in?

ALL RESPONSES

Criteria Number of

responses

a. Chemicals 3

b. Computers & communications 2

c. Drugs & medical 1

d. Electrical & electronics 3

e. Mechanical 4

f. Others 0

Total 13

Question 2. Our statistical analyses of USPTO data show that patent application filing volumes are not

uniform over all days of the year, but show certain regular clustering patterns. Based on your firm’s

experience and industry practices, what would be the timing of these patterns? Check all that apply.

ALL RESPONSES

Criteria Number of

responses

a. The first day of the month 0

b. The 15th day of the month 0

c. The last day of the month 4

d. The last day of the quarter 2

e. The last day of the calendar year 4

f. The last day of the fiscal year 2

g. Other 5

Total --

107


Question 3. We find that filings are clustered in the last few days of every month. Based on industry

practices, what may be likely reason(s) for this clustering? Check all that apply.

ALL RESPONSES

Criteria Number of

responses

a. Deadlines associated with billing

cycles at law firms

6

b. Deadlines associated with individual

attorney work schedules

0

c. Client-imposed deadlines 9

d. Deadlines facing inventors 4

e. Deadlines arising from work

schedules in corporate R&D

departments

6

f. Other deadlines (please specify) 0

g. Other factors not related to deadlines

(please specify)

1

Total --

Question 4. Who normally files patent applications for your group or firm? (In case you use both, choose

the one that is used more frequently.)

ALL RESPONSES

Criteria Number of

responses

Internal IP group 8

External law firm 5

Total 13

108


Question 5. What is the typical (in working days) between an invention disclosure by the inventor and

the associated patent filing date?

ALL RESPONSES

Criteria Number of

responses

2 weeks--1 month 1

1--3 months 5

3 months or longer 2

Total 8

IF ANSWER TO QUESTION 4 WAS INTERNAL IP GROUP


ALL RESPONSES

Criteria Number of

responses

e. Inventor 1

f. Internal corporate patent attorney 6

g. Other (please specify) 1

Total 8

Question 7. How often are applications expedited to meet a non-statutory deadline (e.g., fiscal year

closing, performance evaluation, etc.)? Ignore statutory deadlines such as the 12-month period for

foreign filings here. (Never, Rarely, Sometimes, Often, Almost every time).

ALL RESPONSES

Criteria Number of responses

Never 0

Rarely 2

Sometimes 3

Often 3

Almost every time 0

Total 8

109






ALL RESPONSES

Criteria Number of

responses

Never 0

Rarely 2

Sometimes 5

Often 1

Almost every time 0

Total 8


ALL RESPONSES

Criteria Number of

responses

Never 0

Rarely 3

Sometimes 3

Often 2

Almost every time 0

Total 8

110



ALL RESPONSES

Criteria Number of

responses

Never 2

Rarely 6

Sometimes 0

Often 0

Almost every time 0

Total 8


ALL RESPONSES

Criteria Number of

responses

Never 1

Rarely 4

Sometimes 3

Often 0

Almost every time 0

Total 8


ALL RESPONSES

Criteria Number of

responses

Never 0

Rarely 2

Sometimes 3

Often 3

Almost every time 0

Total 8

111







ALL RESPONSES

Criteria Number of

responses

Never 6

Rarely 2

Sometimes 0

Often 0

Almost every time 0

Total 8


ALL RESPONSES

Criteria Number of

responses

Never 1

Rarely 4

Sometimes 3

Often 0

Almost every time 0

Total 8

Question 10.1. Suppose an application filed by your firm received or required the following office actions.

Rate them on how they might reflect on the quality of the work performed by the attorney (Positively, No

Effect, Somewhat Negatively, Negatively, Very Negatively). Consider the actions one at a time,

independent of others.

112


a. Application Incomplete – Filing Date Assigned

ALL RESPONSES

Criteria Number of

responses

Positively 0

No Effect 4


Negatively 0

Very Negatively 0

Total 8

b. Request for Extension of Time

ALL RESPONSES

Criteria Number of

responses

Positively 0

No Effect 3


Negatively 1

Very Negatively 1

Total 8

c. Non-final Rejection

ALL RESPONSES

Criteria Number of

responses

Positively 1

No Effect 7


Negatively 0

Very Negatively 0

Total 8

113


d. Restriction/Election Requirement

ALL RESPONSES

Criteria Number of

responses

Positively 0

No Effect 8


Negatively 0

Very Negatively 0

Total 8

e. New or Additional Drawing Filed

ALL RESPONSES

Criteria Number of

responses

Positively 0

No Effect 4


Negatively 0

Very Negatively 0

Total 8

f. Additional Application Filing Fees

ALL RESPONSES

Criteria Number of

responses

Positively 0

No Effect 4


Negatively 0

Very Negatively 0

Total 8

-------------------------------------------------------------------------------------------------------------------------------

114


IF ANSWER TO QUESTION 4 WAS EXTERNAL LAW FIRM


ALL RESPONSES


a. Inventor 0

b. Law firm attorney 2

c. Your IP/legal department 2

d. Other (please specify) 1

Total 5





ALL RESPONSES


Never 0

Rarely 0

Sometimes 3

Often 1

Almost every time 1

Total 5


ALL RESPONSES


Never 1

Rarely 2

Sometimes 1

Often 1

Almost every time 0

Total 5

115



ALL RESPONSES

Criteria Number of

responses

Never 2

Rarely 2

Sometimes 0

Often 1

Almost every time 0

Total 5


ALL RESPONSES

Criteria Number of

responses

Never 0

Rarely 0

Sometimes 4

Often 1

Almost every time 0

Total 5


ALL RESPONSES

Criteria Number of

responses

Never 0

Rarely 2

Sometimes 2

Often 1

Almost every time 0

Total 5

116







ALL RESPONSES

Criteria Number of

responses

Never 1

Rarely 0

Sometimes 0

Often 4

Almost every time 0

Total 5


ALL RESPONSES

Criteria Number of

responses

Never 0

Rarely 0

Sometimes 2

Often 2

Almost every time 1

Total 5

117


c. Application Incomplete – Filing Date Assigned

ALL RESPONSES


Positively 0

No Effect 1


Negatively 0

Very Negatively 1

Total 4

d. Request for Extension of Time

ALL RESPONSES


Positively 0

No Effect 1


Negatively 2

Very Negatively 0

Total 4

e. Non-final Rejection

ALL RESPONSES


Positively 2

No Effect 2


Negatively 0

Very Negatively 0

Total 4

118


f. Restriction/Election Requirement

ALL RESPONSES


Positively 1

No Effect 3


Negatively 0

Very Negatively 0

Total 4

g. New or Additional Drawing Filed

ALL RESPONSES


Positively 0

No Effect 2


Negatively 0

Very Negatively 0

Total 4

h. Additional Application Filing Fees

ALL RESPONSES


Positively 0

No Effect 2


Negatively 0

Very Negatively 0

Total 4

119


Question 11. Do(es) your external law firm(s)have regular billing cycle(s)? If yes, what is the cycle?

ALL RESPONSES

Criteria Number of

responses

No, we do not have a regular billing cycle 0

Yes, at the end of every month 4

Yes, at the end of every quarter 0

Yes, at the end of every year 0

Yes, other 1

Total 5

Question 12. Do the fees for attorney services normally depend on the complexity of the application (e.g.,

are the fees dependent on the number of claims, specifications and drawings)?

ALL RESPONSES

Criteria Number of

responses

No 3

Yes 2

Total 5

Question 13. When are fees for attorney services related to application filing typically paid?

ALL RESPONSES

Criteria Number of

responses

Periodically, based on hours incurred 2

Upon filing of the application 3

Other (please specify) 0

Total 5

120

V.S4: Follow-up Survey of Corporate Patent Attorneys

S4: FOLLOW-UP SURVEY OF LAW FIRM PATENT ATTORNEYS

OVERVIEW








This survey was administered to patent attorneys at law firms based on a list of email addresses

(and names of the attorneys and their law firms) purchased from Exactdata.com. The survey

was sent to a total of 722 valid email addresses, from which we received 29 responses (response

rate of 4.2%). We primarily used these responses to obtain robust data on the monetary cost of

correcting errors in patent applications while identifying anecdotal evidence for our own

conjectures on a few details of application process.

121



Question 1. Our statistical analyses of USPTO data show that applications filed at month-ends tend to

have more claims, drawings and drawing sheets. They also tend to be cited by more future patents and

more likely to be renewed after 3.5 years. What could be the reason(s) for this pattern?

ALL RESPONSES

Criteria Number of

responses

a. These applications require more time to work and

hence generate more revenue, thus get filed before

month-ends to reduce outstanding unbilled hours.

5

b. These applications are more complex and hence

require more involvement/input from the client,

which tend to push the filing to month-ends to

accommodate the client’s work schedule.

4

c. Don’t know. 17

d. Others 4

Total 30

Note: Multiple responses allowed.

Question 2. How frequently do clients file an application and abandon it within 18 months of filing?

ALL RESPONSES

Criteria Number of

responses

a. Very rare (less than 5% of applications are

abandoned)

23

b. Unusual (5 to 10% of applications are

abandoned)

3

c. Sometimes (10 to 25% of applications are

abandoned)

2

d. Often (more than 25% of applications are

abandoned)

1

Total 29

122


Question 3: Please consider the following activities during the patent prosecution process. How many

additional hours of lawyer time would each of these activities typically involve? If an activity involves

merely delaying something that would have been done anyway (e.g., an IDS filing), consider only the

additional time resulting from the delay. Hence, for instance, if an IDS filing takes 1 hour whether it is

filed before or after the initial filing, there are no additional hours of lawyer time involved if the IDS is

filed after the initial filing (5 below).

ALL RESPONSES

Responding during prosecution Approx. Additional Hours of

Work

Mean Min Max

(1) Responding to Application Incomplete Notice

(Filing Date Assigned)

1.05 0 2.5

(2) Separate inventor oaths submission (that is,

after the application filing)

0.83 0 3

(3) New/additional drawings to be filed after the

initial submission

1.52 0 4

(4) Additional filing fees 0.34 0 1

(5) IDS filing after the initial filing 0.67 0 2

(6) Requesting an extension of time 0.27 0 1

(7) Responding to a non-final rejection 7.08 0 15

(8) Restriction/election requirement 1.75 0 4.5

Total 13.85 - -

Note: Figures based on 29 responses.

123

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