UNITED STATES DISTRICT COURT

NORTHERN DISTRICT OF CALIFORNIA

SAN JOSE DIVISION

CHRISTINA GRACE and KEN POTTER, )

Individually and on Behalf of All Others, )

Similarly Situated, )

)

Plaintiffs, )

)

v. ) Case No. 5:17-cv-00551-LHK

)

APPLE, INC., )

)

Defendants. )

____________________________________)

Expert Report of Professor Justine S. Hastings, Ph.D.

REDACTED PURSUANT TO STIPULATED PROTECTIVE ORDER

Case 5:17-cv-00551-LHK Document 174-85 Filed 05/04/18 Page 1 of 52
TABLE OF CONTENTS

I. INTRODUCTION ......................................................................................................................... 1

I.A. Qualifications ............................................................................................................... 1

I.B. The Proposed Class...................................................................................................... 2

I.C. Assignment.................................................................................................................... 3

I.D. Summary of Conclusions.............................................................................................. 3

I.E. Outline of Report .......................................................................................................... 4

II. BACKGROUND ON THE BREAK.................................................................................................. 4

II.A. Summary of the Break – the Harmful Act..................................................................... 4

III. THE MARKET FOR USED SMARTPHONES................................................................................. 13

III.A. Used Phone Market .................................................................................................... 13

IV. ASSESSING COMMON IMPACT................................................................................................. 19

V. COMMON APPROACH TO ESTIMATING DAMAGES ................................................................... 20

VI. CONCLUSION .......................................................................................................................... 29

APPENDIX I: RESUME..................................................................................................................... 31

APPENDIX II: DOCUMENTS RELIED ON .......................................................................................... 41

APPENDIX III: SUPPLEMENTAL TABLES ......................................................................................... 46

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I. INTRODUCTION

I.A. Qualifications

1. My name is Justine Hastings. I am a Professor of Economics and International 

and Public Affairs at Brown University. Prior to my position at Brown, I was an Associate 

Professor at Yale University and an Assistant Professor at Dartmouth College. I earned a 

doctorate degree in Economics from the University of California at Berkeley in 2001, and a 

Master of Science in Agricultural and Resource Economics, as well as a Bachelor’s Degree in 

Economics during my four years as an undergraduate at the University of California at Davis. I 

am a Research Associate at the National Bureau of Economic Research (“NBER”), where I am

affiliated with several research programs including Industrial Organization, Public Economics, 

and the working group on Household Finance.

2. My research spans Industrial Organization (competition, marketing, and firm 

behavior), Public Economics (regulation, consumer behavior, and policy design), and Applied 

Econometrics (statistics applied to economics). In my research, I examine the interactions 

between consumer behavior and firm strategy to draw lessons for regulation and public policy. I 

have published papers in leading scholarly journals, including the Quarterly Journal of 

Economics, the American Economic Review, Econometrica, the American Economic Journal, 

Journal of Public Economics, and the International Journal of Industrial Organization. I have 

served as the Managing Editor for the International Journal of Industrial Organization and CoEditor for the Journal of Public Economics.

3. I have served on the Academic Research Council (“ARC”) for the United States 

Federal Consumer Financial Protection Bureau (“CFPB”), and on the Council of Economic 

Advisors for the Governor of Rhode Island. I am the Founding Director of the Rhode Island 

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Innovative Policy Lab (“RIIPL”), a social science research lab which, in partnership with public 

policy leaders, uses big data, economics, and data science to conduct objective, rigorous research 

which can be used to increase the effectiveness of public policy.

4. I have provided expert testimony before the U.S. Senate Committee on the 

Judiciary, Subcommittee on Antitrust, Competition, and Consumer Rights and before the 

California State Assembly, Select Committee on Gasoline Competition, Marketing, and Pricing. 

I have testified in New Hampshire State Court and the United States District Court for the 

Western District of Oklahoma. I have provided expert damages calculations in federal and state 

court cases, including damages calculations in class action cases. A copy of my curriculum vitae 

is attached to this report as Appendix I.

5. I am being compensated at the billing rate of $575 per hour, and my 

compensation is not dependent on the outcome of this litigation. My work on this matter is 

ongoing, and I reserve the right to supplement and modify my report as additional information 

and data become available. A detailed list of the materials and resources that I or the staff 

operating under my direction relied upon in preparing this report is contained in Appendix II.

I.B. The Proposed Class

6. I understand that the proposed class in this case (the “Proposed Class”) is defined 

as: All owners of Apple iPhone 4 or Apple iPhone 4S devices in the United States who on April 

16, 2014, had iOS 6 or earlier operating systems on their iPhone 4 or iPhone 4S devices.

1

I 

further understand that, as set forth in greater detail infra at [Section II – Background on the 

Break], on April 16, 2014, as programmed by Apple, a digital certificate necessary for the 

functioning of FaceTime expired for each member of the Proposed Class, leaving each such 

 

1 See Grace v. Apple Inc., Plaintiffs’ First Amended Complaint (April 5, 2017) (hereinafter “Amended Complaint”), 

¶ 112.

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individual with three options: (1) continue to use iOS 6 or an earlier operating system on their 

iPhone 4 or 4S device, but never regain the ability to use FaceTime on their device; (2) migrate 

to iOS 7, but suffer the lost functionality that iOS 7 caused to iPhone 4 and iPhone 4S devices; or 

(3) purchase a new iPhone device that possessed the processing capability necessary to operate 

iOS 7 without decreasing functionality, and thus regain the ability to use FaceTime on iOS 7. I

will refer to the April 16, 2014 expiration of the certificate that allowed the FaceTime feature to 

work as “the Break” hereafter.

I.C. Assignment

7. Plaintiffs’ counsel asked me to determine whether reliable economic 

methodologies that would be used to calculate damages in this matter are common to members 

of the Proposed Class. Specifically, I was asked to: (1) determine whether there exist economic 

methodologies which can be used to reliably demonstrate that members of the Proposed Class 

have incurred a common impact as a result of the alleged Break; and (2) determine whether there 

exist generally-accepted economic methodologies and evidence common to the Proposed Class 

which can be used to reliably quantify class-wide diminution in value damages as a result of the 

Break.

I.D. Summary of Conclusions

8. The facts or data upon which I am basing the opinions and inferences reflected in 

this report are of a type reasonably relied upon by experts in the field of Economics. My primary 

conclusions are:

• Fundamental economic principles and essential facts of the case can be used to reliably 

demonstrate common impact for members of the Proposed Class, and these principles 

and facts are common to the Proposed Class.

• Quantification of class-wide damages can be accomplished by estimating the diminution 

to the resale value of Proposed Class Members’ iPhones resulting from the Break.

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• Class-wide damages can be reliably quantified using well-accepted economic

methodologies and evidence common to the Proposed Class.

9. My opinions and conclusions are based on discovery to date. I reserve the right to 

amend and supplement my opinions and conclusions as discovery continues and additional 

information becomes available.

10. The results presented in this report are provisional, pending Apple’s production of 

data identifying all members of the Proposed Class and the possibility that third parties will 

produce more and complete data during the merits phase of the litigation. The results and the 

damages that they imply are presented to demonstrate at the class certification stage that there 

exist reliable methods for proving common impact of the Break and quantifying damages to 

members of the Proposed Class.

I.E. Outline of Report

11. My report is organized as follows. Section II provides a background on the

FaceTime Break and the events that transpired before and after the Break. Section III describes 

the market for used smartphones and the industry background. Section IV describes the common 

impact sustained by the Proposed Class due to the Break, and Section V describes reliable

methodologies to calculate aggregate damages and provides an estimate of aggregate damages. 

Finally, Section VI contains my conclusions.

II. BACKGROUND ON THE BREAK 

II.A. Summary of the Break – the Harmful Act

12. On June 24, 2010, Apple released the iPhone 4 with the addition of a new video 

and audio calling feature called FaceTime.2 FaceTime allows users to engage in real-time video 

 

2

“Apple Presents iPhone 4,” Apple Inc. (2010), available at https://www.apple.com/newsroom/2010/06/07ApplePresents-iPhone-4/.

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and audio calls. By introducing real-time video messaging and chat features to smartphones, 

FaceTime allowed users to connect with video and audio in real-time with “friends and loved 

ones separated by great distances, particularly at life’s most meaningful milestones.”

3

It 

accomplished this from the instantaneous and familiar setting of placing a phone call with a 

mobile phone,4and was described as “the simplest, most intuitive video chat there is,” with a 

“fluid and smooth” connection and a “clean and crisp” video quality which was “as simple as 

making a regular phone call”.

5 Additionally, “[m]aking a FaceTime call using an iPhone 4 [was

considered] just as simple as making a regular phone call.”

6

13. Since its introduction, FaceTime has been widely used. There were an estimated 

15 to 20 million FaceTime calls daily in 2013.

7

In the three months following the release of the 

iPhone 4 with FaceTime, Apple’s revenue set a record at over $20 billion, and iPhone year-overyear sales nearly doubled.8

 

 

 

9

 

3 Amended Complaint ¶ 4. See also Ritchie, R. (2016), “FaceTime: The ultimate guide,” iMore, available at 

https://www.imore.com/facetime. (“That’s what makes FaceTime perfect for seeing and hearing family during the 

holidays, when you’re on the road, keeping grandparents connected to grandkids, making international calls when 

you have no long-distance plan, getting a second opinion on that jacket while you’re out shopping, sharing a show, 

making a meeting, and much, much more.”) Id.

4

“Apple Presents iPhone 4,” Apple Inc. (2010), available at https://www.apple.com/newsroom/2010/06/07ApplePresents-iPhone-4/.

5 Colon, A. (2011), “FaceTime (for iPhone),” PC Magazine, available at 

https://www.pcmag.com/article2/0,2817,2385669,00.asp.

6 Colon, A. (2011), “FaceTime (for iPhone),” PC Magazine, available at 

https://www.pcmag.com/article2/0,2817,2385669,00.asp.

7 Clover, J. (2014), “Apple Handles ‘Several Billion’ iMessages and 15 to 20 Million FaceTime Calls Daily,” 

MacRumors, available at https://www.macrumors.com/2014/02/28/apple-40-billion-imessages/.

8

“Apple Reports Fourth Quarter Results,” Apple Inc. (2010), available at 

https://www.apple.com/newsroom/2010/10/18Apple-Reports-Fourth-Quarter-Results/.

9 APL-GRACE_00043021-159 at 44-45.

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14. 

 

 

 

10

 

 

11

 

 

 

12

15. 

 

13

 

 

 

14

 

 

15

 

16

16. In September 2013, Apple introduced the iOS 7 operating system.17 With iOS 7, 

Apple was able to establish P2P connections for FaceTime calls without infringing on VirnetX’s 

 

10 APL-GRACE_0010295 

11 APL-GRACE_00050788.

12 See, e.g., APL-GRACE_00000022 APL-GRACE_00099793 

 

13 APL-GRACE_00050788.

14 See VirnetX Inc. v. Apple, Inc., Case No. 6:13-CV-211 at ECF No. 53 (March 6, 2014) (Redacted February 25, 

2014 Order Granting in Part VirnetX’s Motion to Set an Ongoing Royalty Rate). 

15 APL-GRACE_00148220 

16 APL-GRACE_00000022 ); APL-GRACE_00000009 

 APL-GRACE 00010198 APLGRACE_00051571 APL-GRACE_ 

17 Amended Complaint, ¶ 67.

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patents.18 However, iPhone 4 and 4S users were slow to adopt iOS 7.

19 Plaintiffs allege and the 

evidence shows that iOS 7 imposed a significant functionality impairment on iPhone 4 and 

iPhone 4S devices,

20 and “users who transitioned to iOS 7 were unable to revert back to earlier 

versions of iOS.”

21

 

 

22

 

 

 

 

 

 

 

18 Id.

19 Id. at ¶¶ 88-89.

20 See, e.g., Rampell, C. (2013), “Cracking the Apple Trap,” New York Times, available at 

https://www.nytimes.com/2013/11/03/magazine/why-apple-wants-to-bust-your-iphone html (“When I called tech 

analysts, they said that the new operating system (iOS 7) being pushed out to existing users was making older 

models unbearably slow.”); Costello, S. (Updated 2018), “Should You Upgrade Your iPhone 4 to Ios 7?” Lifewire, 

available at https://www.lifewire.com/upgrade-iphone-4-ios-7-1999204 (“I’d be cautious . . . The combination will 

work, but it may be slower or more problematic than you’d like”); Apple Community (2013), “Does iOS 7 Slow 

Down an iPhone 4?” Apple Inc., available at https://discussions.apple.com/thread/5326618 (“Don’t upgrade to ios 7! 

It’s super slow on iPhone 4!”); APL-GRACE_00005636 APLGRACE_00002142 

APL-GRACE_00002160 and APL-GRACE_00005860 

21 Grace v. Apple Inc., Defendant Apple Inc.’s Answer to Plaintiffs’ First Amended Complaint (August 11, 2017), at 

¶ 79.

22 APL-GRACE_00001004; Amended Complaint, ¶¶ 88-89.

23 APL-GRACE_00056772; APL-GRACE_00056875; and APL-GRACE_00056973.

24 APL-GRACE_00056772; APL-GRACE_00056875; and APL-GRACE_00056973.

25 APL-GRACE_00005801; APL-GRACE_00005804 

 and APL-GRACE_00044231 

 

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8

 

 

 

 

 

19. 

 

 

 

 

 

 

20. Figure 2 shows Google search statistics for terms related to FaceTime and the

Break. This figure combines the “Interest over time”

31 indices for the Google trends terms:

“FaceTime Fail”, “FaceTime not Working”, “iPhone 4 FaceTime not Working,” and “iPhone 4S 

 

26 APL-GRACE_00025224.

27 See, e.g., APL-GRACE_00008039 

p 

28 APL-GRACE_00002942.

29

 

 APL-GRACE_00012205. See also, e.g., APL-GRACE_ 

 

 

30 APL-GRACE_00000988.

31 According to Google Trends’ website, the interest over time “represent[s] search interest relative to the highest 

point on the chart for the given region and time. A value of 100 is the peak popularity for the term. A value of 50 

means that the term is half as popular. A score of 0 means there was not enough data for this term.” See “Google 

Trends,” Google LLC, available at https://trends.google.com/trends/.

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FaceTime not working.” As shown in the figure, there is a clear spike in comparative searches 

regarding FaceTime failing right after April 16, 2014, and elevated searching continues through 

the fall of 2014. 

 

32

 

32 See, e.g., APL-GRACE_00003737 

 

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FIGURE 1

TIMELINE OF EVENTS SURROUNDING THE FACETIME BREAK

June 24, 2010:

[1]

August 11, 2010:

[2]

October 14, 2011:

[3]

November 7, 2012:

[4]

 

September 18, 2013:

[6]

September 19, 2013:

[7]

April 16, 2014: 

[8]

April 17, 2014:

[9]

April 20, 2014:

[10]

April 24, 2014:

[11]

January 29, 2016:

[12]

September 29, 2017:

[13]

Jan-2010 Jan-2011 Jan-2012 Jan-2013 Jan-2014 Jan-2015 Jan-2016 Jan-2017 Jan-2018

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LEGEND FOR FIGURE 1

Event Date and Number Event Description

June 24, 2010: [1] iPhone 4 and iOS 4 with FaceTime released

August 11, 2010: [2] VirnetX files lawsuit against Apple

October 14, 2011: [3] iPhone 4S released in stores

November 7, 2012: [4] Jury finds Apple guilty of patent infringement and awards 

VirnetX $368.2 million in damages

 

 

 

September 18, 2013: [6] iOS 7 released; earliest identified complaint on Apple’s 

message board about incompatibility of iPhone 4 and iOS 7

September 19, 2013: [7] Earliest identified complaint on Apple’s message board 

about incompatibility of iPhone 4S and iOS 7

April 16, 2014: [8] Apple breaks FaceTime for iOS 6 and earlier

April 17, 2014: [9] All iPhone users of iOS 6 or earlier have to shift to iOS 7 

in order to regain FaceTime on their device

April 20, 2014: [10]

During the week of April 20, the phrases “FaceTime Fail,”

“FaceTime Not Working,” “iPhone 4 FaceTime Not 

Working,” and “iPhone 4S FaceTime Not Working” peak 

in popularity on Google search, relative to other weeks. 

Elevated search continues for several months.

April 24, 2014: [11] Apple officially announces how to deal with the “bug” that 

caused FaceTime to fail for users of iOS 6 or earlier

January 29, 2016: [12] Sworn testimony where Apple’s Senior Software Engineer 

Dr. Thomas Jansen acknowledges FaceTime break

September 29, 2017: [13] Court awards VirnetX $439.7 million in damages for 

Apple’s infringement of its patents

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FIGURE 2

GOOGLE SEARCH TERM STATISTICS

“FACETIME FAIL,” “FACETIME NOT WORKING,” “IPHONE 4 FACETIME NOT WORKING,” AND “IPHONE 4S FACETIME NOT WORKING”

Notes: For comparative search results on Google Trends, Google takes the sum of the relative “Interest Over Time” for all four terms by date, or data period,

calculating a new point corresponding to each date, or data period. Then, Google scales the maximum of these new points proportional to 100, and uses the new 

points for the comparative search graph as shown above.

Sources: https://trends.google.com/trends/explore?date=2014-01-01%202015-12-31&geo=US&q=FaceTime%20fail, FaceTime%20not%20working,iPhone%20

4%20FaceTime%20not%20working,iPhone%204S%20FaceTime%20not%20working.

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21. Using economic principles, I deduce that the Break potentially harmed all Class 

Members in three ways. First, they immediately lost the value of using FaceTime on any iPhone 

4 or 4S running on iOS 6 or earlier. Class Members lost utility due to their inability to use the 

popular FaceTime feature, or they lost the option value of using the feature should they have 

desired. Second, if they upgraded the operating system of their iPhone 4 or 4S device to iOS 7, 

Class Members experienced loss due to reduced performance of their device. Third, every

member of the Proposed Class lost value due to a drop in the resale value of their iPhone 4 or 4S 

device. Owners of smartphones can resell or trade in their phones in an active and competitive 

secondary sale market. The Break caused features of the phone to stop working. This would have 

led to a drop in the market price of the phone due to a loss in desirable features. I have been 

asked whether there exist generally-accepted economic methodologies and evidence common to 

the Proposed Class which can be used to reliably quantify class-wide diminution in value 

damages as a result of the Break and, if so, to quantify estimated class-wide damages as a result 

of the Break.

III. THE MARKET FOR USED SMARTPHONES

III.A. Used Phone Market

22. The market for used smartphones is robust, developed, and competitive. It is 

estimated that over 81.3 million used smartphones were sold in 2015, and the used smartphones 

market is forecasted to grow to 222.6 million units in 2020.

33

23. Firms of all sizes as well as individuals can sell used phones on well-known 

platforms such as Amazon.com, eBay, Gazelle.com, and Craigslist. In addition, used phones are 

purchased and resold by many major corporations, small retailers, and individuals.

 

33 “Worldwide Market for Used Smartphones Forecast to Grow to 222.6 Million Units in 2020, According to IDC,” 

International Data Corporation (2016), available at https://www.idc.com/getdoc.jsp?containerId=prUS41929916.

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24. Examples of major corporations participating in the used phone market include 

Brightstar Corporation, “the world’s largest specialized wireless distributor and a leading global 

services company, serving mobile device manufacturers, wireless operators and retailers, with a 

local presence on six continents. Brightstar’s industry-leading services include value-added 

distribution, supply chain optimization, handset protection and insurance, buy-back and trade-in 

solutions and multi-channel retail solutions.”

34 Brightstar handles returns of used Apple devices 

through the Apple Reuse and Recycle Program, 35 Best Buy’s “entire inventory of returned 

mobile devices,”

36 and strategic sourcing and integrated supply chain services for some of 

Verizon Wireless’ largest dealers.37

25. Owners have many options for selling their used phones. Table 1 lists major 

platforms and the mechanism for purchasing used phones from individuals, and selling used 

phones (where applicable). Individuals can trade in their used phone to a carrier or cellular phone 

retailer. Major carriers and retailers who sell phones and phone plans offer buy-back programs 

tied to purchases of new goods and services, such as credit for a used phone towards the 

purchase of a new phone or new phone plan. Individuals can also sell their phone directly to 

resellers, or directly to end purchasers for cash (or for a broadly fungible credit such as an 

Amazon.com gift card) on platforms such as Amazon.com, Gazelle.com, and eBay.

 

34 “Best Buy Taps Brightstar To Streamline Reverse Supply Chain For Mobile Devices,” PR Newswire (2012), 

available at https://www.prnewswire.com/news-releases/best-buy-taps-brightstar-to-streamline-reverse-supplychain-for-mobile-devices-173138811.html.

35 Clover, J. (2017), “Apple Introduces New Apple Watch Recycling Program Offering Gift Cards Up To $175,” 

MacRumors, available at https://www.macrumors.com/2017/12/04/apple-watch-recycling-program-gift-cards/.

36 “Best Buy Taps Brightstar To Streamline Reverse Supply Chain For Mobile Devices,” PR Newswire (2012), 

available at https://www.prnewswire.com/news-releases/best-buy-taps-brightstar-to-streamline-reverse-supplychain-for-mobile-devices-173138811.html.

37 “Brightstar Named as Exclusive Handset Provider to Key Verizon Wireless Dealers,” PR Newswire (2012), 

available at https://www.prnewswire.com/news-releases/brightstar-named-as-exclusive-handset-provider-to-keyverizon-wireless-dealers-147900405.html.

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26. Consumer Intelligence Research Partners (CIRP) surveyed 1,000 subjects in the 

U.S. in 2017 and found that “[a]lmost one-third of Apple iPhones get sold or traded-in.”

38

Additionally, in the same survey pool, CIRP found that 39% of those surveyed sold or traded-in 

their old phones at their current mobile carrier, with the majority using non-carrier trade-in 

platforms for used products such as Best Buy, Amazon.com, Gazelle.com, Craigslist and eBay.39

27. Individuals can easily assess the value of their phone on the resale market. There 

are many information platforms which provide potential purchasers and sellers with information 

on used phone resale value based on the active market for used phones. Third-party websites, 

such as Movaluate.com, exist to help individuals and businesses determine the value of a phone. 

Movaluate.com provides estimates of the “fair price” of used smartphones. As the website

explains, Movaluate “combines data from millions of completed transactions with statistical 

analysis and expert review” to estimate a fair price for a used device.40 Swappa.com’s “Data 

Services” provides information about “the used retail price for mobile devices through its 

subscription-based [application programming interface] services.”

41

28. Similarly, eBay’s “Marketplace Research by Terapeak” platform allows a user to 

view average selling prices, gauge market demand and seasonality, and monitor competition.

42

Major carriers and cellular phone retailers, such as Best Buy, also provide used phone value 

 

38 Levin, M. (2017), “Used Phone Market Growing, Slowly,” The Huffington Post, available at 

https://www.huffingtonpost.com/michael-r-levin/used-phone-market-growing_b_4847583 html.

39 Levin, M. (2017), “Used Phone Market Growing, Slowly,” The Huffington Post, available at 

https://www.huffingtonpost.com/michael-r-levin/used-phone-market-growing_b_4847583 html.

40 “About Us,” Movaluate, available at http://www.movaluate.com/about.

41 “Data Services,” Swappa, available at https://swappa.com/data-services.

42 “Marketplace research by Terapeak,” eBay, available at https://pages.ebay.com/marketplace_research/. 

Additionally, eBay has been used to perform market research on used iPhones in the past as well (see, Whitney, L. 

(2015), “iPhone 6 resale value higher than previous models, analyst say,” CNET, available at 

https://www.cnet.com/uk/news/iphone-6-resale-value-higher-than-previous-models-analyst-says). This indicates that 

eBay holds a large share of the used iPhone resale market. See Appendix III, Table A4 for a sample of Terapeak’s 

available data.

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calculators on their websites to help phone owners gauge how much credit they will receive for 

their phone towards a new phone or plan should they opt to trade in their old phone. The value of 

a used smartphone is typically determined through a series of questions that assess the 

characteristics of the phone that impact its value on the resale market, such as the make and 

model, type of carrier, storage capacity, physical condition, and other basic functionality. Once 

individuals answer the prompted questions online, the platform presents an estimated value of 

their device. Appendix III, Table A1 lists the information collected by or displayed by various

third-party platforms in the process of assessing used smartphone prices or listing used phones 

for sale.

29. Prices in the used smartphone market are determined by the supply of and 

demand for used smartphones of various models and with various characteristics. Demand is 

determined by the value that individuals place on the used phone, i.e., the individual’s

willingness to pay for the used phone. Demand for phones varies based on characteristics such as 

condition, age, model, manufacturer, storage size, and other features which impact the value to 

the purchaser. Thus, these factors are typically requested by major resale sites and used phone 

resale information sites to assist with determining the value of a used phone. 

30. Supply is determined by factors, such as the release of new phone models, which 

prompt individuals to sell their phones into the secondary market. Demand and supply interact to 

determine an equilibrium price. If demand for a product falls, all else equal, prices will fall until 

more people are willing to purchase the product, and fewer suppliers are willing to sell it. 

Demand for the used iPhone 4 and 4S devices would have fallen as a result of diminished value 

from lost features caused by the Break.

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IV. ASSESSING COMMON IMPACT

31. Common impact can be assessed using economic principles which are common to 

the Proposed Class. A central premise in economic theory is that people act to maximize their 

expected utility. 43 Using this fundamental economic principle, I can deduce that the Break

harmed Class Members by potentially lowering utility in three ways.

32. First, Class Members immediately lost the value of using FaceTime on any 

iPhone 4 or 4S running on iOS 6 and earlier operating systems; the “valuable FaceTime feature 

immediately and abruptly stopped working for millions of users running”

44 on pre-iOS 7 systems

on April 16, 2014. Class Members lost utility due to their inability to use the popular FaceTime 

feature, or they lost the option value to use the feature should they have desired.

33. Second, if they upgraded the operating system of their iPhone 4 or 4S to iOS 7, 

Class Members experienced loss due to reduced performance. Older iPhone models, such as the 

iPhone 4 and 4S, were incompatible with the new iOS 7. When owners of older iPhone models 

operating on pre-iOS 7 systems attempted to transition to the new operating system, their devices 

were subjected to issues with the Wi-Fi and Bluetooth controller,45 reduced battery life,46 lagged 

application functionality, a poor user interface,47 and system crashes.48

 

43 See e.g., Bernheim, B. and Whinston, M. (2008), Microeconomics, New York, NY: McGraw-Hill Irwin, chapters 

4 and 5.

44 Amended Complaint, ¶ 11.

45 Cole, S. (2013), “iOS 7 update brings more Wi-Fi issues for some iPhone 4S owners,” Apple Insider, available at 

https://appleinsider.com/articles/13/10/10/ios-7-update-brings-more-wi-fi-issues-for-some-iphone-4s-owners.

46 Greenfield, R. (2013), “The Biggest Complaints About iOS 7 and How to Fix Them,” The Atlantic, available at 

https://www.theatlantic.com/technology/archive/2013/09/biggest-complaints-about-ios-7-and-how-fixthem/310738/.

47 Barr, A. and Martin, S. (2013), “Apple loses some of its magic touch with iOS 7,” USA Today, available at 

https://www.usatoday.com/story/tech/2013/10/17/apple-ios-7-problems/2986189/.

48 “Apple says working on fix for random iOS 7 crashing issue,” Apple Insider (2014), available at 

https://appleinsider.com/articles/14/01/22/apple-says-fix-in-the-works-for-random-ios-7-crashing-issue. See also, 

e.g., Rampell, C. (2013), “Cracking the Apple Trap,” New York Times, available at 

https://www.nytimes.com/2013/11/03/magazine/why-apple-wants-to-bust-your-iphone html (“When I called tech 

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34. Third, every Class Member lost value due to a drop in the resale value of the 

iPhone 4 or 4S that they owned. Smartphone owners have the option of reselling their phones in 

an active and competitive used smartphone market. As explained in Section III.A, a 

smartphone’s resale value depends on a number of characteristics, including its physical 

condition, make and model, and basic functionality, assessed by trade-in services or indirect or 

direct buyers themselves. Because the Break stopped FaceTime from working on the iPhone 4 

and 4S absent a migration to iOS 7 (and resulting decrease in functionality with migration), these 

models’ resale prices would have dropped due to a loss in value in the market for a valued

feature.

35. Standard economic theory of consumer choice states that individuals prefer 

products that work fully to those that do not, all else equal. Similarly, consumers prefer products 

with higher residual value or resale value, all else equal.

36. Therefore, all or almost all members of the Class were adversely affected by the 

Break. This is demonstrated using economic reasoning, economic principles, and facts related to 

the Break which are common to the class. The existence of each Class Member’s injury is an 

issue common to the Class and subject to generalized proof based on basic economic theory. The 

existence of each Class Member’s injury is not an issue unique to each Class Member.

V. COMMON APPROACH TO ESTIMATING DAMAGES

37. As stated by Professor Hall and Dr. Lazear in the Federal Judicial Center’s 

Reference Manual on Scientific Evidence, a damages “analysis considers the difference between 

the plaintiff’s economic position if the harmful event had not occurred and the plaintiff’s actual 

 

analysts, they said that the new operating system (iOS 7) being pushed out to existing users was making older 

models unbearably slow.”) (last visited 5/1/2018); Costello, S. (Updated 2018), “Should You Upgrade Your iPhone 

4 to Ios 7?” Lifewire, available at https://www.lifewire.com/upgrade-iphone-4-ios-7-1999204 (“I’d be cautious . . . 

The combination will work, but it may be slower or more problematic than you’d like”) (last visited 5/1/2018). 

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economic position. The damages study restates the plaintiff’s position ‘but for’ the harmful 

event; this part is often called the but-for analysis. Damages are the difference between the butfor value and the actual value.”

49 Here, the harmful event was the Break. The harm is the 

diminished value of the phone as measured by resale market prices. This is the resale value of the 

phone compared to what the resale value would have been but-for the Break.

38. There exist data and well-established economic methodologies which can be used 

to estimate damages due to diminished resale value of Class Members’ iPhone 4 and 4S devices

as a result of the Break. To estimate damages, I will use reliable multivariate regression models 

and analysis, and used smartphone prices to calculate the resale price of affected phone models 

but-for the Break. I will then compare the estimated but-for price to actual resale prices to 

calculate damages attributable to the Break. The data and methodology used in this calculation 

are common to the Proposed Class.

39. Common data exist through electronic records collected by resale market 

platforms as described in the prior section. Using transaction data from resale platforms and third 

parties, I can employ a common and reliable method to estimating damages – multivariate 

regression modeling. Determining the impact of the Break on prices involves comparing prices 

during the period affected by the Break to prices during a time when the market was unaffected 

by the Break. Here, the “benchmark” period is the period before the Break became publicly 

known and could be incorporated into customers’ willingness to pay in the resale market. The 

“damages period” can be compared to the “benchmark” period to estimate how prices changed as 

a result of the harmful act, holding other demand and supply factors constant. 

 

49 Allen, M., Hall, R., and Lazear, V. (2011), “Reference Guide on Estimation of Economic Damages,” in Reference 

Manual on Scientific Evidence, Federal Judicial Center, National Research Council of the National Academies 425-

502, at 284.

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40. Multivariate regression modeling is used to adjust for market factors other than 

the Break that would have impacted market price. This is done to isolate the impact of the Break 

on price and, thus, produce an estimate of damages attributable to the Break. 

41. Multivariate regression models are commonly relied upon to estimate overcharges 

and damages. The economist specifies a model which relates the price of the product in question 

to demand and supply factors which affect price based on economic principles and facts about 

the market. One of these variables captures the added effect of the harmful act on price by 

including a “dummy variable” – a variable that captures the average difference in price during 

the period the harmful act was in effect, controlling for the influence on price of other demand 

and supply factors. This approach is called the Dummy Variable Approach of calculating 

damages.50 The model demand and supply factors capture what price would have been but-for 

the harmful act; the dummy variable captures the impact of the harmful act relative to the but-for 

price.

42. Demand factors which affect the price of a used phone include the age of the 

model, the brand of the model, and other features of the model, such as color, storage size, and 

condition. These are the primary factors that customers choose when deciding how much they 

are willing to pay for a used phone as evidenced by collection of this data by platforms when 

determining how much a used phone is worth (see Appendix III, Tables A1 and A2).

43. Several supply factors may affect the probability that individuals sell their used 

phones. A primary factor is the release of new models, which would increase the value to current 

phone owners of selling their current phone to upgrade to the latest model.

 

50 See, e.g., Hastings, J.S. and Williams, M.A. (2016), “What is a But-For World?,” Antitrust, vol. 31, pp. 102-108; 

ABA Section of Antitrust Law (2017), Proving Antitrust Damages: Legal and Economic Issues, 3rd Ed., American 

Bar Association, Ch. 6, Section F; McCrary, J. and Rubinfeld, D. (2014), “Measuring Benchmark Damages in 

Antitrust Litigation,” Journal of Econometric Methods, vol. 3, pp. 63-74; and ABA Section of Antitrust Law (2014), 

Econometrics: Legal, Practical, and Technical Issues, 2nd ed., American Bar Association, Ch. 12.

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44. Macroeconomic factors such as measures of economic wellbeing, like GDP, may 

also affect price as they affect people’s decisions to make purchases, such as used or new 

phones, and may also affect people’s price sensitivity which in turn impacts market prices. Thus,

these factors may impact both supply and demand as they impact the rate at which individuals 

may purchase new phone models, and resell their existing phones, as well as the rate at which 

individuals purchase used phones and their price sensitivity when making a purchase. 

45. Once the model has been specified, it can be estimated on data common to the 

class as outlined above. The model and data produce an estimate of the impact of the Break on 

used iPhone 4 and 4S prices. A negative and significant coefficient on the dummy variable for 

the Break period for iPhone 4 and 4S models relative to other phone models would indicate a 

negative and significant impact of the Break on the prices of used affected iPhones, and thus,

significant damages to Class Members from the Break.

46. There exist data which are common to the class with which to estimate damages. 

Appendix III, Table A3 lists potential sources of data based on major purchasers and/or resellers 

of used smart phones. The final columns indicate whether data were requested, and whether any 

data have been provided to date. The table additionally includes a description of whether the data 

set provided to us is suitable for regression estimation, and the primary reason for my 

assessment. Among these data sets, Verizon and Sprint data are not suitable for estimating 

damages because the data sets represent aggregate information on prices insufficient to measure 

changes in price and control sufficiently for demand and supply variables, and/or the data 

providers have not given adequate explanation of the variables in the data and how they are 

designed. 

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47. For example, the Sprint data contain only 83 observations for limited phone 

models at two selected days during each year. The Verizon data give only 373 data points 

representing an aggregated price for a limited set of phone models. It is unclear how the prices 

were aggregated, and how much information is lost in the unknown aggregation process. In 

contrast, data provided by Best Buy contains millions of individual-level phone transactions with 

resale prices for the phones and detailed characteristics of each phone, along with the date of the 

sale.

48. Two data sets, AT&T and EcoATM arrived too close to the report filing date to 

be properly cleaned, understood, and analyzed, and/or we are awaiting responses to queries about 

data field and variable definitions needed to properly clean, understand, and analyze the data.

49. Thus, data and well-established methodologies for estimating damages exist, and 

these data and methodologies are common to the Proposed Class. To illustrate the common 

methodology using common evidence, I estimate a multivariate regression model on the Best 

Buy data. The Best Buy data arrived organized with clear and segmented information on phone 

characteristics. It includes transaction-level data from January 1, 2013 through December 31, 

2016 for over 2 million used phone trade-ins. The data include the trade-in resale prices for 

iPhone 4 models through iPhone 6 models, and Samsung Galaxy models S4 through S6. The

phone prices of these other models will provide a comparison group for estimating the impact of 

the Break on iPhone 4 and iPhone 4S resale prices, controlling for other factors impacting 

demand and supply for various phone models. 

50. For each phone, the data include phone characteristics such as the model, the 

condition, the storage size, and the color. The data include information on the buy-back program 

and value provided to the phone owner as part of the buy-back program, inclusive of additional 

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promotions towards the purchase of new goods and services. They also include the final price 

Best Buy received for the phone after reselling it to a third party for resale.

51. To estimate what the price of the iPhone 4 and 4S models would have been butfor the harmful act, I must first estimate a model of used phone prices as a function of factors 

which affect the demand for and supply of used phone models. Demand variables include the age 

of the model of the phone that is for sale, a time trend to capture overall demand trends in the 

market, dummy variables which capture the relative value of different manufacturers, colors, 

storage sizes, conditions, and carriers of phones. All of these factors may influence consumer 

demand for a particular phone. 

52. I additionally control for events related to releases of new models of phones by 

each manufacturer. I also control for economic factors impacting demand for and supply of used 

phones such as GDP. Dummy variables for each month of the year capture seasonal effects in 

demand and supply, and I include indicators for the weeks surrounding Christmas each year to 

account for holiday demand effects.

53. I use the price of the phone Best Buy received when it sold the phone to a thirdparty vendor for eventual resale on the used market to estimate damages. This variable is called 

“Revenue” as it represents the price Best Buy received for the phone. Best Buy’s data also 

includes trade-in values for phones, but because these are part of buy-back programs tied to the 

purchase of new goods and services from Best Buy, they do not reflect the market value of the 

phone, but may include a combination of market value of the phone, discounts, and incentives 

towards purchases of additional Best Buy products. This combination cannot be separated by the 

economist. By estimating the impact on Revenue, I can reliably estimate the impact of the Break 

and other demand and supply factors on the value of used phone, without error from misCase 5:17-cv-00551-LHK Document 174-85 Filed 05/04/18 Page 27 of 52
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measured buy-back values which may include incentives and discounts towards additional 

purchases.

54. The results of the model are presented in Table 2 below. The first column

estimates the model on the Best Buy data, and as discussed above, uses the log of Revenue as the 

dependent variable which measures price. The variable denoted “Impact” measures the effect of 

the Break on the prices of used iPhone 4 and 4S models relative to other phone models and 

controlling for other demand and supply factors. The coefficient on Impact is negative and 

highly significant. The coefficient of -0.136 translates into a 12.72% reduction in the value of the 

used iPhone 4 and 4S models due to the Break.

55. The measure effects of other explanatory variables in the model are economically 

sensible. As indicated by the variable denoted “Log Model Age,” the value of a phone model in 

the used market declines with the age of the phone model. The coefficient on “Log Time” is 

negative and significant, indicating that phone values in the market are generally declining over 

time. As indicated by the variable denoted “Log U.S. GDP,” used phone values vary negatively 

with the log of GDP. This is consistent with the fact that used phones are inferior goods to new 

phones, so people are less likely to sell their current phones to get a new model when GDP falls 

and people are more likely to purchase used instead of new phones when GDP falls. Supply 

should therefore drop and demand should increase for used phones, pushing used phone prices 

up when GDP falls. Thus, a negative relationship between used phone prices and GDP emerges. 

56. As a robustness check, column 2 presents the model estimated on data collected 

by a team under my direction from archived Amazon.com web pages at InternetArchive.org. The 

prices are for major smartphone models manufactured by Apple, HTC, LG, Motorola, Samsung, 

or ZTE, and listed for resale on Amazon’s website in the used smartphone category from May 8, 

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2010 through July 22, 2016.51 The Amazon data include iPhone 3 sales, as well as sales of postiPhone 4 models. The data include all smartphone features listed, including the device model, the 

model series, the manufacturer, the storage size, the carrier, whether the phone was “unlocked,”

the terms of the sale, the shipping cost, and the condition of the phone. In total, we collected 

4,583 used smartphone prices.

57. I find similar estimates of the impact of the Break on the resale price of iPhone 4

and 4S models as I do in the Best Buy data. The coefficient on Impact implies a 17.58% 

diminution in value to iPhone 4 and iPhone 4S models as a result of the Break.

 

51 Manufacturers Apple, HTC, LG, Motorola, Samsung, and ZTE had the largest smartphone market shares in the 

U.S. around the time of the Break. See “comScore Reports July 2014 U.S. Smartphone Subscriber Market Share,” 

comScore (2014), available at https://www.comscore.com/Insights/Rankings/comScore-Reports-July-2014-USSmartphone-Subscriber-Market-Share; Cheng, E. (2014), “The Chinese smartphone that’s ramping up in the US,” 

CNBC, available at https://www.cnbc.com/2014/11/13/chinese-smartphone-tracking-ztes-growth-in-us-mobilemarket html.

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TABLE 2

MULTIVARIATE REGRESSION ESTIMATES USING EXAMPLE DATA

Best Buy Trade-in Data Amazon.com Used Sales Price

Log Resale Price Log Used Resale Price

Impact -0.136*** -0.193***

(0.002) (0.032)

Log Time -0.038*** -0.404***

(0.001) (0.068)

Log Model Age -0.038*** -0.152***

(0.002) (0.019)

Log US GDP -0.210+ -5.089*

(0.118) (2.195)

Observations 1,941,517 3,169

R-squared 0.785 0.940

Implied Diminution in Value -12.72% -17.58%

Standard errors in parentheses. *** p<0.001, ** p<0.01, * p<0.05, + p<0.10

All regression specifications include: monthly controls, Christmas season controls, controls for new releases of 

Apple and Samsung phones, and controls for color of the phone. For Best Buy, the regression specification also 

includes fixed effects for the full interaction of phone model, phone condition, phone carrier, and phone storage 

size. For Amazon, the regression specification also includes fixed effects for the full interaction of phone model, 

phone carrier, and phone storage size.

58. The damages framework I present uses a reliable, common methodology and

common data and evidence to estimate aggregate damages for the class. I demonstrate the Break 

caused prices of used iPhone 4 and 4S devices to fall by an estimated 12.72% (using the damages 

estimate produced using the Best Buy data).

59. My understanding is that there exists a list of Potential Class Members along with 

a serial number for each iPhone 4 or 4S device owned by the Class Member at the time of the 

Break. My understanding is that the Proposed Class is currently estimated to include at least 

members. My understanding is that these serial numbers can be used to identify the 

model of the phone. Using data on prices received by sellers of used phones, along with the 

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estimated diminution in value, we can calculate aggregate damages using a common 

methodology and common evidence.

60. For example, the mean price of iPhone 4 and iPhone 4S models sold to the used 

market by Best Buy from April 1, 2014 to April 15, 2014 was . If we apply this average 

sale price to the number of Class Members listed above, and if the distribution of iPhone and 

iPhone 4S models sold in those weeks through Best Buy is similar to the distribution of these 

models in the Potential Class, then a reliable estimate of aggregate damages using methodology 

and data common to the class is 12.72% . This is equal to $455,684,338.

VI. CONCLUSION

61. I have demonstrated that fundamental economic principles and evidence from the 

case can be used to reliably demonstrate common impact for members of the Proposed Class. 

These economic principles and evidence are common to the Proposed Class. Moreover, I have 

demonstrated how class-wide damages can be estimated using the diminution in resale value of 

the Proposed Class Members’ iPhone 4 and 4S devices as a result of the Break. These damages 

can be quantified using common methodology and evidence of the type well-accepted and 

typically relied on by economist for estimating damages or overcharges. 

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I declare that the foregoing is true and correct to the best of my knowledge. Executed on this 4th

day of May at _____Providence, RI_______________________. 

________________________ 

Justine S. Hastings 

 

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APPENDIX I: RESUME

J U S T I N E S. H A S T I N G S 

Education

University of California at Berkeley, PhD in Economics, 1996-2001

Specialization: Industrial Organization, Public Economics, Econometrics.

University of California at Davis, 1992-1996, B.A. in Economics with Mathematics minor,

Summa Cum Laude, and M.S. in Agriculture and Resource Economics.

Current Academic Affiliations

Brown University, Professor of Economics and International and Public Affairs.

 

Research Associate, National Bureau of Economic Research, Program Affiliations in 

Industrial Organization, Public Economics, Aging, Education, and Energy and 

Environmental Economics.

Leadership and Advisory Positions

Director, Rhode Island Innovative Policy Lab (RIIPL). May 2015 - .

Governor’s Council of Economic Advisors, State of Rhode Island. May 2014 – May 2017.

Advisor, Academic Research Council, United States Federal Consumer Financial 

Protection Bureau. May 2012 – June 2017.

Editorial Positions

Brown University

Department of Economics

Watson Institute of International & Public Affairs

64 Waterman Street

Providence, RI 02912

E: justine_hastings@brown.edu

W: www.justinehastings.com

P: 415.326.6101

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Co-Editor, Journal of Public Economics, January 2014 to December 2015. 

Editorial Board, Journal of Economic Literature, January 2012 to 2015.

Managing Editor, International Journal of Industrial Organization, 2011 - 2013.

Co-Editor, International Journal of Industrial Organization, 2010 to May 2011.

Associate Editor, International Journal of Industrial Organization, 2009-2010.

 

Publications

“How Are SNAP Benefits Spent? Evidence From a Retail Panel,” with Jesse M. Shapiro. 

American Economic Review, Forthcoming. 

“Sales Force and Competition in Financial Product Markets: The Case of Mexico’s Social 

Security Privatization,” with Ali Hortaçsu and Chad Syverson. Econometrica. November, 

2017.

“(Un)Informed College Choice: Evidence from Chile,” with Christopher Neilson, Anely 

Ramirez, and Seth Zimmerman. Economics of Education Review. April 2016.

“Connecting Student Loans to Labor Market Outcomes: Policy Lessons from Chile," with 

Harald Beyer, Christopher Neilson and Seth Zimmerman. American Economic Review.

May 2015. 

“School Choice and College Attendance: Evidence from Randomized Lotteries,” with David 

Deming, Thomas Kane and Douglas Staiger. American Economic Review. March 2014. 

“Fungibility and Consumer Choice: Evidence from Commodity Price Shocks,” with Jesse 

Shapiro. Quarterly Journal of Economics. November 2013. Lead Article and Editor’s 

Choice.

“The First of the Month Effect: Consumer Behavior and Store Responses,” 

with Ebonya Washington. American Economic Journal: Economic Policy. 

May 2010.

“Investigating Income Effects in Scanner Data: Do Gasoline Prices Affect 

Grocery Purchases?” with Dora Gicheva and Sofia Villas Boas. American 

Economic Review. May 2010.

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“Information, School Choice and Academic Achievement: Evidence from Two 

Experiments,” with Jeffrey M. Weinstein. Quarterly Journal of Economics. November 

2008.

“Reformulating Competition? Gasoline Content Regulation and Wholesale Gasoline 

Prices,” with Jennifer Brown, Erin Mansur, and Sofia Villas-Boas, Journal of 

Environmental Economics and Management. January 2008.

“The Effect of Randomized School Admissions on Voter Participation” with Thomas Kane, 

Douglas Staiger, and Jeffrey Weinstein, Journal of Public Economics. June 2007.

“Gender, Performance and Preferences: Do Girls and Boys Respond Differently to School 

Environment? Evidence from School Assignment by Randomized Lottery,” with Thomas 

Kane and Douglas Staiger, American Economic Review. May 2006. 

“Vertical Integration in Gasoline Supply: An Empirical Test of Raising Rivals' Costs,” with 

Richard J. Gilbert, Journal of Industrial Economics. December 2005.

“Vertical Relationships and Competition in Retail Gasoline Markets: Empirical Evidence 

from Contract Changes in Southern California,” American Economic Review. March 2004.

“Abatement, Consumption, Capital, and Pollution Accumulation in an Optimal Program,”

by Justine S. Ghassemi and Michael R. Caputo, Pacific and Asian Journal of Energy, Vol. 7 

(1), 1997 (Senior Honors Thesis, UC Davis).

 

Working Papers 

“Are Some Degrees Worth More than Others: Evidence from College Admission Cutoffs in 

Chile,” with Christopher Neilson and Seth Zimmerman. NBER Working Paper w19241 

(Revised July 2017).

"Advertising, Reputation and Environmental Stewardship: Evidence from the BP Oil Spill,"

with Lint Barrage and Eric Chyn. NBER Working Paper w19838. Revision Requested, 

American Economic Journal: Economic Policy.

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“Fettered Consumers and Sophisticated Firms: Evidence from Mexico's Privatized Social 

Security Market,” with Fabian Duarte. NBER Working paper w18582 November (2012). 

Revised March 2014.

“The Effect of School Choice on Intrinsic Motivation and Academic Outcomes,” with 

Christopher Neilson and Seth Zimmerman. NBER Working Paper w18324, August (2012). 

Revised August 2014. 

“How Financial Literacy and Impatience Shape Retirement Wealth and Health Investment 

Behaviors,” with Olivia S. Mitchell, NBER Working Paper w16740, (January 2011).

“Fees, Framing, and Financial Literacy in the Choice of Pension Manager,” with Olivia 

Mitchell and Eric Chyn. Wharton Pension Research Council Working Paper, July (2010). 

“Wholesale Price Discrimination and Regulation: Implications for Retail 

Gasoline Prices,” Yale University Working Paper, February (2009).

“Financial Literacy, Information, and Demand Elasticity: Survey and 

Experimental Evidence from Mexico,” with Lydia Tejeda-Ashton. National 

Bureau of Economic Research Working Paper No. 14538, December (2008). 

Revise and Resubmit, American Economic Journal: Economic Policy.

“Heterogeneous Preferences and the Efficacy of Public School Choice,” with Thomas Kane 

and Douglas Staiger. Combines and replaces National Bureau of Economic Research Paper 

Working Papers No. 12145 and No. 11805. June (2008), Revised June (2009). 

Papers in Progress 

“The Impact of Home Visiting Programs: Evidence from Rhode Island MIECHV,” Angell, 

Georgia M., Sarah Bowman, Kristine Campagne, Justine Hastings, Catalina Ravizza, Sidra 

Scharff, and Preston White. 2017.

“Using Big Data to Curb the Opioid Crisis,” Hastings, Justine, Mark Howison, Sarah Inman, 

and Miraj Shah. 2017.

“What Predicts Student Achievement? New Evidence from Big Data.” Bald, Anthony, 

Samantha Gold, Justine Hastings, Mark Howison, and Miraj Shah. 2017.

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“Using Administrative Data to Predict and Lower Medicaid Emergency Department 

Overuse,” Berenbaum, David, Fernando Gelin, Justine Hastings, Mark Howison, Sarah 

Inman, and Emily Oster. 2017.

“The Impact of Paid Leave: Evidence from Temporary Disability Insurance in Rhode Island.” 

Campbell, Zakary, Eric Chyn, and Justine Hastings. 2017.

“The Impact of Temporary Disability Insurance on Labor and Long Term Disability.” 

Campbell, Zakary, Eric Chyn, and Justine Hastings. 2017.

“Optimal Unemployment Insurance Targeting: Causal Inference with Machine Learning.” 

Campbell, Zakary, Eric Chyn, and Justine Hastings. 2017.

“The Impact of Voter Identification Laws on Voter Participation: Evidence from Rhode 

Island.” Esposito, Francesco, Diego Focanti and Justine Hastings. 2017.

“The Effect of SNAP on Nutrition.” Hastings, Justine S., Ryan Kessler, and Jesse M. Shapiro. 

2017.

“The Impact of Child Protection on Children’s Outcomes.” Chyn, Eric, Justine S. Hastings, 

and Margartia Machelett. 2017.

“Impatience, Information and Investment Choice: Field Experimental Evidence in Mexico’s 

Privatized Social Security System.” Hastings, Justine S. and Lindsey M. Wilson. 2017.

Book Chapters, Book Reviews, and Other Publications

“What is a But-For World?” with Michael A. Williams. Antitrust (2016), vol. 31, pp. 102-

108.

“Financial Literacy, Financial Education and Economic Outcomes,” with Brigitte C. 

Madrian and William L. Skimmyhorn. Annual Review of Economics. January 2013.

Review of Nudge: Improving Decisions about Health, Wealth, and Happiness, by Richard 

H. Thaler and Cass R. Sunstein, Yale University Press (2008). Journal of Economic 

Literature. December (2009).

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External Grants

The Russell Sage Foundation, The Impact of Paid Maternity Leave: Evidence from 

Temporary Disability Insurance in Rhode Island, Co-Principal Investigator with Eric 

Chyn.

Center for Equitable Growth, The Impact of Paid Maternity Leave: Evidence from 

Temporary Disability Insurance in Rhode Island, Co-Principal Investigator with Eric 

Chyn. 2017-2018.

National Science Foundation Grant, The Effect of SNAP Receipt on household Behavior 

and Well-being: Evidence and Economic Interpretation, Co-Principal Investigator with 

Jesse M. Shapiro. 2017-2020.

The Smith Richardson Foundation, The Rhode Island Innovative Policy Lab. Principle 

Investigator. 2017-2019.

United States Social Security Administration Research Grant, Behavioral Economics and 

the Monthly Food Cycle Among Retirees: New Evidence from Linked Administrative 

Records in Rhode Island. Principal Investigator, 2016-2017.

United States Social Security Administration Research Grant, Does Health Insurance 

Access Affect DI/SSI Outcomes? Analyzing Which Factors Impact Outcomes Using the 

RIIPL Relational Database. Principal Investigator, 2016-2017.

Robert Wood Johnson Foundation, Improving measurement precision in evaluating the 

impact of the Supplemental Nutrition Assistance Program on nutrition and families' food 

expenditures. Co-Principal Investigator with Jesse Shapiro. 2016-2018. 

Russell Sage Foundation, The Effect of SNAP on Food Purchases and Family Nutrition.

Co- Principal Investigator with Jesse M. Shapiro. 2016-2017.

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United States Social Security Administration Research Grant, Disability Insurance Use 

and Impacts: New Evidence from Linked Administrative Records in Rhode Island. 

Principal Investigator, 2015-2016.

Laura and John Arnold Foundation, Home Visiting in Rhode Island. Co-Investigator with 

Emily Oster (PI). 2015-2019. 

Laura and John Arnold Foundation, Rhode Island Innovative Policy Lab. Principal 

Investigator, 2015-2018. 

Laura and John Arnold Foundation, Designing a Smarter SNAP. Principal Investigator, 

2015-2020. 

Russell Sage Foundation, Mental Accounting and Fungibility of Money: Evidence from a 

Retail Panel. Co- Principal Investigator with Jesse M. Shapiro. 2015-2016.

National Bureau of Economic Research Pilot Grant (National Institute of Health subaward), Measuring the Impact of Parental Education on Childhood and Family Outcomes. 

2013. 

United States Social Security Administration Research Grant, The Impact of Risk and the 

Financial Crisis on Investor Perceptions of Privatized Social Security and Retirement 

Planning. Principal Investigator, 2011-2013. 

United States Social Security Administration Research Grant, Investor Decisions and the 

Financial Crisis in a Privatized Social Security Market. Principal Investigator, 2009-2010.

MacArthur Foundation How Housing Matters to Families and Communities Grant.

Estimating the Impact of Housing Subsidies on Family Outcomes: Evidence from 

Mexico's Housing Subsidy Programs. Principal Investigator, 2011-2014. 

National Bureau of Economic Research Pilot Grant (National Institute of Health subaward), “Health Literacy and Preventative Health Care: Survey and Experimental 

Interventions in Mexico’s Public Health Care System.” Principal Investigator. 2011.

Case 5:17-cv-00551-LHK Document 174-85 Filed 05/04/18 Page 39 of 52
38

National Bureau of Economic Research Pilot Grant (National Institute of Health subaward), "Consumer Choice and Firm Response in a Privatized Social Security Market."

Principal Investigator. 2008-2009.

National Institute of Health Grant Number R01AG032411-01A2, Social Security 

Privatization: Investment Choice, Competition and Field Experiments in Mexico, Principal 

Investigator. 2009-2014.

United States Social Security Administration Research Grant, Financial Literacy, Shortrun Impatience, and the Determinants of Savings and Financial Management. CoInvestigator (with Olivia Mitchell), 2009-2010. 

United States Social Security Administration Research Grant, Investor Decisions and the 

Financial Crisis in a Privatized Social Security Market. Principal Investigator. 2009-2010.

United States Social Security Administration Research Grant, Fund Choices in a Private 

Accounts System: Implications for Disparities in Wealth at Retirement. Principal 

Investigator. 2008-2009. 

Smith Richardson Foundation Grant, Preferences, Information, and Parents’ Choice 

Behavior in Public School Choice. Principal Investigator. 2006-2008. 

United States Department of Education Grant for Research in Education Finance, 

Leadership, and Management, Co-Investigator with Thomas Kane and Douglas Staiger. 

2004-2009. 

National Science Foundation Grant, Estimating Demand with Consumer Heterogeneity: 

an Application to Wholesale Price Regulation in Retail Gasoline Markets. Principal 

Investigator. 2003-2005. 

Case 5:17-cv-00551-LHK Document 174-85 Filed 05/04/18 Page 40 of 52
39

EXPERT REPORTS AND PRIOR TESTIMONY

UNITED STATES DISTRICT COURT NORTHERN DISTRICT OF OHIO, EASTERN 

DIVISION

Greg Herrick et al., v. National Football League, National Football Museum, Inc. dba Pro 

Football Hall of Fame, Civil Action No. 5:17-cv- 472. Expert Report (2017) and Deposition 

(2017).

UNITED STATES DISTRICT COURT FOR THE DISTRICT OF NEW JERSEY

Gary Marchese, et al., v. Cablevision Systems Corp., Civil Action No. 10-2190. Expert Reports 

(2014) and Depositions (2014 and 2015).

UNITED STATES DISTRICT COURT FOR THE WESTERN DISTRICT OF OKLAHOMA

Richard Healy, et al., v. Cox Communications, Inc., Case No. CIV-12-481-C.

Expert Reports (2013), Depositions (2013 and 2015), and Trial testimony (2013

and 2015).

THE STATE OF NEW HAMPSHIRE MERRIMACK, SS. SUPERIOR COURT

State of New Hampshire v. Hess Corporation et al.

Expert Reports (2010, 2011, and 2012), Depositions (2011 and 2012), and Trial

testimony (2013).

STATE ATTORNEYS GENERAL OF MAINE, MASSACHUSETTS, NEW HAMPSHIRE, 

NEW YORK, AND VERMONT

“Report on Petroleum Products Markets in the Northeast,” prepared for the Attorneys General of 

the five states (2007).

U.S. SENATE, COMMITTEE ON THE JUDICIARY, SUBCOMMITTEE ON ANTITRUST

Hearings on “Competition Policy and Consumer Rights.” Expert Testimony (2004).

Case 5:17-cv-00551-LHK Document 174-85 Filed 05/04/18 Page 41 of 52
40

CALIFORNIA STATE ASSEMBLY, SELECT COMMITTEE ON GASOLINE 

COMPETITION, MARKETING, AND PRICING

California State Assembly Bill 1283, relating to the unbundled supply of retail gasoline.

Expert Testimony (2004).

CONNECTICUT SUPERIOR COURT, WATERBURY

Wyatt Energy, Inc. v. Motiva Enterprises LLC, et al.

Expert Report and Deposition Testimony (2003).

U.S. SENATE, COMMITTEE ON GOVERNMENT AFFAIRS, PERMANENT 

SUBCOMMITTEE ON INVESTIGATIONS

Hearings on “Gasoline Prices: How are They Really Set?” Expert Testimony (2002).

U.S. FEDERAL TRADE COMMISSION

Public Conference on Factors that Affect Prices of Refined Petroleum Products Speaker and 

Panelist (2001).

Case 5:17-cv-00551-LHK Document 174-85 Filed 05/04/18 Page 42 of 52
41

APPENDIX II: DOCUMENTS RELIED ON

Academic Articles & Books

ABA Section of Antitrust Law (2014), Econometrics: Legal, Practical, and Technical Issues, 

2nd ed., American Bar Association, Ch. 12

ABA Section of Antitrust Law (2017), Proving Antitrust Damages: Legal and Economic Issues, 

3rd Ed., American Bar Association, Ch. 6, Section F

Allen, M., Hall, R., and Lazear, V. (2011), “Reference Guide on Estimation of Economic 

Damages,” in Reference Manual on Scientific Evidence, Federal Judicial Center, National 

Research Council of the National Academies, 425-502

Bernheim, B. and Whinston, M. (2008), Microeconomics, New York, NY: McGraw-Hill Irwin, 

Ch. 4 and 5.

Hastings, J.S. and Williams, M.A. (2016), “What is a But-For World?,” Antitrust, vol. 31, pp. 

102-108

McCrary, J. and Rubinfeld, D. (2014), “Measuring Benchmark Damages in Antitrust Litigation,”

Journal of Econometric Methods, vol. 3, pp. 63-74

Pleadings, Submissions, Complaints, and Orders

Grace v. Apple Inc., Defendant Apple Inc.’s Answer to Plaintiffs’ First Amended Complaint 

(August 11, 2017)

Grace v. Apple Inc., Plaintiffs’ First Amended Complaint (April 5, 2017)

VirnetX Inc. v. Apple, Inc., Case No. 6:13-CV-211 at ECF No. 53 (March 6, 2014) (Redacted 

February 25, 2014 Order Granting in Part VirnetX’s Motion to Set an Ongoing Royalty Rate)

Bated Numbered Documents

APL-GRACE_00000009

APL-GRACE_00000022

APL-GRACE_00000988

APL-GRACE_00001004

APL-GRACE_00002142

APL-GRACE_00002160

APL-GRACE_00002942

APL-GRACE_00003737

Case 5:17-cv-00551-LHK Document 174-85 Filed 05/04/18 Page 43 of 52
42

APL-GRACE_00005636

APL-GRACE_00005636 

APL-GRACE_00005801

APL-GRACE_00005804

APL-GRACE_00005860

APL-GRACE_00008039

APL-GRACE_00010198

APL-GRACE_00012205

APL-GRACE_00025224

APL-GRACE_00034276

APL-GRACE_00042431

APL-GRACE_00043021-159

APL-GRACE_00044231

APL-GRACE_00050788

APL-GRACE_00051571

APL-GRACE_00056772

APL-GRACE_00056875

APL-GRACE_00056973

APL-GRACE_00099793

APL-GRACE_00102595

APL-GRACE_00148220

1_2013_Jan-Mar.xlsx

2_2013_Apr-May.xlsx

3_2013_June.xlsx

4_2013_July-Aug.xlsx

5_2013_Sep-Oct.xlsx

6_2013_Nov-Dec.xlsx

7_2014_Jan-Feb.xlsx

8_2014_Mar-May.xlsx

9_2014_Jun-Aug.xlsx

10_2014_Sep.xlsx

Case 5:17-cv-00551-LHK Document 174-85 Filed 05/04/18 Page 44 of 52
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11_2014_Oct.xlsx

12_2014_Nov.xlsx

13_2014_Dec.xlsx

14_2015_Jan-Jun.xlsx

15_2015_Jul-Dec.xlsx

16_2016_Jan-Dec.xlsx

Other

“Hot to sell your iPhone,” iMore, available at https://www.imore.com/how-to-sell-your-iphone

“How to Get the Most Money for Your Old iPhone,” Time, available at 

http://time.com/money/4937390/iphone-buy-sell-best-price/

“The best ways to sell or trade in your iPhone,” CNET, available at https://www.cnet.com/howto/sell-or-trade-in-your-iphone-7-or-7-plus/

“About Us,” Movaluate, available at http://www.movaluate.com/about

“Apple GiveBack - Turn the device you have into the one you want,” Apple Inc., available at 

https://www.apple.com/shop/trade-in

“Apple Launches iPhone 4S, iOS 5 & iCloud,” Apple Inc. (2011), available at 

https://www.apple.com/newsroom/2011/10/04Apple-Launches-iPhone-4S-iOS-5-iCloud/

“Apple Presents iPhone 4,” Apple Inc. (2010), available at 

https://www.apple.com/newsroom/2010/06/07Apple-Presents-iPhone-4/

“Apple Reports Fourth Quarter Results,” Apple Inc. (2010), available at 

https://www.apple.com/newsroom/2010/10/18Apple-Reports-Fourth-Quarter-Results/

“Apple says working on fix for random iOS 7 crashing issue,” Apple Insider (2014), available at 

https://appleinsider.com/articles/14/01/22/apple-says-fix-in-the-works-for-random-ios-7-

crashing-issue

“Best Buy Taps Brightstar To Streamline Reverse Supply Chain For Mobile Devices,” PR 

Newswire (2012), available at https://www.prnewswire.com/news-releases/best-buy-tapsbrightstar-to-streamline-reverse-supply-chain-for-mobile-devices-173138811.html

“Brightstar Named as Exclusive Handset Provider to Key Verizon Wireless Dealers,” PR 

Newswire (2012), available at https://www.prnewswire.com/news-releases/brightstar-named-asexclusive-handset-provider-to-key-verizon-wireless-dealers-147900405.html

“Business Buyback,” Sprint, available at https://secure.sprintbuyback.com/crp/

Case 5:17-cv-00551-LHK Document 174-85 Filed 05/04/18 Page 45 of 52
44

“comScore Reports July 2014 U.S. Smartphone Subscriber Market Share,” comScore (2014), 

available at https://www.comscore.com/Insights/Rankings/comScore-Reports-July-2014-USSmartphone-Subscriber-Market-Share

“Data Services,” Swappa, available at https://swappa.com/data-services

“Devices,” ecoATM, available at https://www.ecoatm.com/devices/

“Get an estimate,” T-Mobile, available at https://www.t-mobile.com/cell-phone-trade-in.html

“Google Trends,” Google LLC, available at https://trends.google.com/trends/

“iOS 7 With Completely Redesigned User Interface & Great New Features Available September 

18,” Apple Inc. (2013), available at https://www.apple.com/newsroom/2013/09/10iOS-7-WithCompletely-Redesigned-User-Interface-Great-New-Features-Available-September-18/

“Iphone 4s ios 7 battery issues,” Apple Communities (2013), available at 

https://discussions.apple.com/thread/5329381

“Marketplace research by Terapeak,” eBay, available at 

https://pages.ebay.com/marketplace_research/

“Mobile Device Protection & Support,” Assurant Inc., available at 

https://www.assurant.com/partner-with-us/mobile-device-protection-support

“Movaluate,” Movaluate, available at http://www.movaluate.com/

“Nextworth,” Nextworth, available at https://nextworth.com/

“Sell with Swappa,” Swappa, available at https://swappa.com/sell

“Sell,” Glyde, available at https://glyde.com/sell

“Terapeak,” eBay, available at https://www.terapeak.com/

“Trade-In,” Amazon Inc., available at 

https://www.amazon.com/b/ref=ti_surl_tradein?ie=UTF8&node=9187220011

“Trade-In,” Best Buy, available at https://tradein.bestbuy.com/client/#/catalog/

“Trading in your device is easier than ever,” Verizon Wireless, available at 

https://www.verizonwireless.com/od/trade-in/#/

“VirnetX Receives Court’s Final Judgment Affirming Jury’s Verdict of $1.20 Per Infringing 

Apple Device,” PR Newswire (2017), available at https://www.prnewswire.com/newsreleases/virnetx-receives-courts-final-judgment-affirming-jurys-verdict-of-120-per-infringingapple-device-300536936.html

“Worldwide Market for Used Smartphones Forecast to Grow to 222.6 Million Units in 2020, 

According to IDC,” International Data Corporation (2016), available at 

https://www.idc.com/getdoc.jsp?containerId=prUS41929916

Case 5:17-cv-00551-LHK Document 174-85 Filed 05/04/18 Page 46 of 52
45

Apple Community (2013), “Does iOS 7 Slow Down an iPhone 4?” Apple Inc., available at 

https://discussions.apple.com/thread/5326618

Barr, A. and Martin, S. (2013), “Apple loses some of its magic touch with iOS 7,” USA Today, 

available at https://www.usatoday.com/story/tech/2013/10/17/apple-ios-7-problems/2986189/

Cheng, E. (2014), “The Chinese smartphone that’s ramping up in the US,” CNBC, available at 

https://www.cnbc.com/2014/11/13/chinese-smartphone-tracking-ztes-growth-in-us-mobilemarket.html

Clover, J. (2014), “Apple Handles ‘Several Billion’ iMessages and 15 to 20 Million FaceTime 

Calls Daily,” MacRumors, available at https://www.macrumors.com/2014/02/28/apple-40-

billion-imessages/

Clover, J. (2014), “iOS 6 Users on Devices Able to Run iOS 7 Must Upgrade to Fix FaceTime,”

MacRumors, available at https://www.macrumors.com/2014/04/24/ios-6-facetime-fix/

Clover, J. (2017), “Apple Introduces New Apple Watch Recycling Program Offering Gift Cards 

Up To $175,” MacRumors, available at https://www.macrumors.com/2017/12/04/apple-watchrecycling-program-gift-cards/

Cole, S. (2013), “iOS 7 update brings more Wi-Fi issues for some iPhone 4S owners,” Apple 

Insider, available at https://appleinsider.com/articles/13/10/10/ios-7-update-brings-more-wi-fiissues-for-some-iphone-4s-owners

Colon, A. (2011), “FaceTime (for iPhone),” PC Magazine, available at 

https://www.pcmag.com/article2/0,2817,2385669,00.asp

Costello, S. (Updated 2018), “Should You Upgrade Your iPhone 4 to Ios 7?” Lifewire, available 

at https://www.lifewire.com/upgrade-iphone-4-ios-7-1999204

Greenfield, R. (2013), “The Biggest Complaints About iOS 7 and How to Fix Them,” The 

Atlantic, available at https://www.theatlantic.com/technology/archive/2013/09/biggestcomplaints-about-ios-7-and-how-fix-them/310738/

Levin, M. (2017), “Used Phone Market Growing, Slowly,” The Huffington Post, available at 

https://www.huffingtonpost.com/michael-r-levin/used-phone-market-growing_b_4847583.html

Rampell, C. (2013), “Cracking the Apple Trap,” New York Times, available at 

https://www.nytimes.com/2013/11/03/magazine/why-apple-wants-to-bust-your-iphone.html

Ritchie, R. (2016), “FaceTime: The ultimate guide,” iMore, available at 

https://www.imore.com/facetime

Whitney, L. (2015), “iPhone 6 resale value higher than previous models, analyst say,” CNET, 

available at https://www.cnet.com/uk/news/iphone-6-resale-value-higher-than-previous-modelsanalyst-says

Case 5:17-cv-00551-LHK Document 174-85 Filed 05/04/18 Page 47 of 52
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APPENDIX III: SUPPLEMENTAL TABLES

TABLE A1

INFORMATION COLLECTED BY OR DISPLAYED BY THIRD-PARTIES FOR SMARTPHONE TRADE-INS

Platform

Information Collected

Device Information Displayed

Model Carrier Storage Size Color Condition

Glyde.com Y Y Y Y Y

Provides price trend for the past 5 months, “Sells 

Slower” price, “Market Price,” “Sells Faster” price, 

and “In your pocket” amount after Glyde’s service 

cost.

Swappa.com Y Y N N N

Provides “Recent Prices” by carrier, and 

information on the required criteria for sale (i.e., 

conditions). After clicking the “Prices” button, the 

“Recent Sold Avg Price,” “Last Sold Price,”

“Lowest Current Price,” and a price trend is

displayed by storage size.

Verizon Wireless Device TradeIn and Recycling Program Y Y Y Y Y Provides the “estimated trade-in value.”

Amazon Trade-In Store Y Y Y Y Y

Provides the estimated “Trade-In Value” and 

product descriptions (e.g., UPC number, model 

name, and storage size.)

Apple Trade-Up Program Y N Y N Y Provides the estimated trade-in value (gift card.)

BestBuy Trade-In Program Y Y Y Y Y

Provides the “Estimated Trade-In Value” (gift 

card.)

Gazelle.com

(includes EcoATM) Y Y Y N N Provides the estimated price range.

Case 5:17-cv-00551-LHK Document 174-85 Filed 05/04/18 Page 48 of 52
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TABLE A1 (CONT.)

INFORMATION COLLECTED BY OR DISPLAYED BY THIRD-PARTIES FOR SMARTPHONE TRADE-INS

Platform

Information Collected

Device Information Displayed

Model Carrier Storage Size Color Condition

Movaluate.com Y Y Y Y Y

Provides the phone model number, “Fair Market 

Price,” “Fair Market Range,” “Price Certainty,”

and sales prices for the past 10 days, sales price 

and volume trends, and environmental impact of 

recycling by user-inputted phone conditions.

Nextworth.com Y Y Y Y Y Provides “Today’s Trade-in Value.”

Sprint BuyBack Y Y Y N N Provides the “Estimated Value” by storage size.

T-Mobile Y Y Y Y N Provides the estimated total value.

Source: “Sell,” Glyde, available at https://glyde.com/sell; “Sell with Swappa,” Swappa, available at https://swappa.com/sell; “Trading in your device is 

easier than ever,” Verizon Wireless, available at https://www.verizonwireless.com/od/trade-in/#/; “Trade-In,” Amazon Inc., available at 

https://www.amazon.com/b/ref=ti_surl_tradein?ie=UTF8&node=9187220011; “Apple GiveBack - Turn the device you have into the one you want,” Apple 

Inc. available at https://www.apple.com/shop/trade-in; “Trade-In,” Best Buy, available at https://tradein.bestbuy.com/client/#/catalog/; “Devices,” ecoATM, 

available at https://www.ecoatm.com/devices/; “Movaluate,” Movaluate, available at http://www movaluate.com/; “Nextworth,” Nextworth, available at 

https://nextworth.com/; “Business Buyback,” Sprint, available at https://secure.sprintbuyback.com/crp/; and “Get an estimate,” T-Mobile, available at

https://www.t-mobile.com/cell-phone-trade-in.html.

Case 5:17-cv-00551-LHK Document 174-85 Filed 05/04/18 Page 49 of 52
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TABLE A2

LIST OF SUBPOENAED BUY-BACK / TRADE-IN PROGRAM DATA

Trade-in and/or Resale Program 

or Platform\1

Data Fields Requested

Amazon.com, Inc. For all Cell Phones and Smart Phones received from 1/1/2010 to present in the United States:

AT&T Unique transaction identifier

Verizon Transaction date and time

Best Buy Manufacturer/Brand of phone (e.g., Apple, Samsung, LG)

Brightstar Corp. Network/Carrier (e.g., Verizon, Sprint, Unlocked)

Gazelle.com

(includes EcoATM)

 Device model name (e.g., iPhone 5, Galaxy S5)

Sprint Device model numeric identifier (SKU, UPC)

T-Mobile Color

 Storage size (e.g., 64GB, 128GB)

 All variables related to phone condition, reported and assessed

 All variables related to phone characteristics (e.g. camera resolution)

 Trade in value offered

 Trade in value credited to customer (price paid)

 Customer location: city, state, country, zip

 Information relating to shipping/packaging (e.g., Apple provides free shipping)

 Resale price of the phone received once resold

 Date phone was resold

 Unique identifier for purchaser of re-sold phone

Note:

\1 Data from Assurant, Inc. has also been subpoenaed. Assurant, Inc. is an insurance company that provides mobile device protection plans and support for 

customers worldwide (see “Mobile Device Protection & Support,” Assurant, Inc., available at https://www.assurant.com/partner-with-us/mobile-deviceprotection-support.)

Case 5:17-cv-00551-LHK Document 174-85 Filed 05/04/18 Page 50 of 52
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TABLE A3

LIST OF SUBPOENAED BUY-BACK / TRADE-IN PROGRAM DATA RECEIVED TO DATE

Trade-in and/or 

Resale Program or 

Platform

Data Requested 

Through 

Subpoena

Data

Received

Date of Data 

Received Data Suitable for Regression Estimation?

Amazon.com, Inc. Yes No N/A N/A

AT&T Yes Yes March 2, 2018

To be determined. AT&T data were received recently 

and require substantial cleaning to extract needed 

information to assess usability for damages 

estimation.

Verizon Yes Yes February 15, 

2018

No. Verizon data give only 373 data points 

representing an aggregated price for a limited set of 

phone models.

Best Buy Yes Yes March 5, 2018 Yes. Best Buy data is used in this report.

Brightstar Corp. Yes No N/A N/A

Gazelle.com

(includes EcoATM) Yes Yes April 23, 2018

To be determined. ecoATM data were very close to 

report filing. We are awaiting responses to questions 

regarding data and field definitions.

Sprint Yes Yes February 22, 

2018

No. Sprint data contain only 83 observations for 

limited phone models at two selected days during 

each year.

T-Mobile Yes No N/A N/A

Case 5:17-cv-00551-LHK Document 174-85 Filed 05/04/18 Page 51 of 52
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TABLE A4

TERAPEAK – SAMPLE DATA

This file was downloaded on January 5 2018 2:12:22 PM UTC-08:00

Keywords iphone 5

Date Range 2015-01-03 - 2018-01-02

Site: ebay.com

Product Condition: Refurbished Used

Buyer Country: US

Seller Country: US

Transaction Site: ebay.com

Category: Cell Phones & Smartphones

Date Items Sold Average Selling Price Total Sales

1/3/2015 8 195.73 USD 1565.80 USD

1/4/2015 474 191.36 USD 90702.71 USD

1/5/2015 235 191.43 USD 44985.15 USD

1/6/2015 242 196.99 USD 47672.75 USD

1/7/2015 231 188.20 USD 43474.93 USD

1/8/2015 236 191.88 USD 45284.85 USD

1/9/2015 235 183.91 USD 43219.06 USD

1/10/2015 234 186.25 USD 43583.21 USD

1/11/2015 4 275.49 USD 1101.95 USD

1/12/2015 461 194.75 USD 89779.33 USD

1/13/2015 239 188.21 USD 44981.35 USD

1/14/2015 230 184.96 USD 42541.08 USD

1/15/2015 228 184.21 USD 42000.96 USD

1/16/2015 236 201.87 USD 47642.00 USD

1/17/2015 229 192.83 USD 44158.78 USD

1/18/2015 249 183.48 USD 45686.13 USD

1/19/2015 234 193.75 USD 45337.89 USD

1/20/2015 94 216.03 USD 20307.08 USD

1/21/2015 163 200.75 USD 32722.52 USD

1/22/2015 347 191.79 USD 66549.49 USD

1/23/2015 383 183.92 USD 70443.24 USD

1/24/2015 231 183.26 USD 42332.40 USD

1/25/2015 231 179.33 USD 41425.10 USD

1/26/2015 239 185.05 USD 44225.77 USD

Source: “Terapeak,” eBay, available at https://www.terapeak.com/.

Case 5:17-cv-00551-LHK Document 174-85 Filed 05/04/18 Page 52 of 52