1 1 IN THE UNITED STATES DISTRICT COURT FOR THE DISTRICT OF COLUMBIA 2 FEDERAL TRADE COMMISSION, . DOCKET NO. CA-07-1021 (PLF) 3 . PLAINTIFF, . 4 . WASHINGTON, D.C. V. . JULY 31, 2007 5 . 9:00 A.M. WHOLE FOODS MARKET, INC., ET AL, . 6 . DEFENDANT. . 7 . . . . . . . . . . . . . . . . . . 8 TRANSCRIPT OF MOTIONS HEARING - MORNING SESSION BEFORE THE HONORABLE PAUL L. FRIEDMAN 9 UNITED STATES DISTRICT JUDGE 10 APPEARANCES: 11 FOR THE PLAINTIFF: FEDERAL TRADE COMMISSION BY: MICHAEL J. BLOOM, Esquire 12 THOMAS H. BROCK, ESQUIRE CATHARINE M. MOSCATELLI, ESQUIRE 13 MATTHEW J. REILLY, ESQUIRE THOMAS J. LANG, ESQUIRE 14 MICHAEL FRANCHAK, ESQUIRE 600 PENNSYLVANIA AVENUE, NORTHWEST 15 WASHINGTON, D.C. 20580 202.326.2475 16 FOR THE DEFENDANT: VINSON & ELKINS 17 BY: ALDEN L. ATKINS, ESQUIRE JOHN D. TAURMAN, ESQUIRE 18 1455 PENNSYLVANIA AVENUE, NORTHWEST WASHINGTON, D.C. 20004 19 202.639.6613 20 SKADDEN, ARPS, SLATE, MEAGHER & FLOM BY: CLIFFORD H. ARONSON, ESQUIRE 21 MATTHEW P. HENDRICKSON, ESQUIRE FOUR TIMES SQUARE 22 NEW YORK, NEW YORK 10036 212.735.3000 23 24 25 Linda L. Russo, RPR Official Court Reporter 2 1 FOR THE DEFENDANT: DECHERT, LLP BY: PAUL H. FRIEDMAN, ESQUIRE 2 PAUL T. DENIS, ESQUIRE JAMES A. FISHKIN, ESQUIRE 3 JEFFREY W. BRENNA, ESQUIRE 1775 I STREET, NORTHWEST 4 WASHINGTON, D.C. 20006 202.261.3300 5 6 COURT REPORTER: LINDA L. RUSSO, RPR 7 OFFICIAL COURT REPORTER ROOM 6403, U.S. COURTHOUSE 8 WASHINGTON, D.C. 20001 202.354.3244 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 PROCEEDINGS REPORTED BY MACHINE SHORTHAND, TRANSCRIPT PRODUCED BY COMPUTER-AIDED TRANSCRIPTION 25 Linda L. Russo, RPR Official Court Reporter 3 1 INDEX 2 Direct Cross Redirect Recross 3 4 WITNESSES FOR THE 5 PLAINTIFF: 6 Kevin Murphy 17 17 97 -- 7 8 9 10 11 12 EXHIBITS: 13 (No Exhibits were received in evidence.) 14 15 16 17 18 19 20 21 22 23 24 25 Linda L. Russo, RPR Official Court Reporter 4 1 P R O C E E D I N G S 2 THE CLERK: Civil Action 07--10231 Federal Trade 3 Commission versus Whole Foods Market, Inc, et al. Counsel, 4 please identify yourself for the record. 5 MR. BLOOM: Mike Bloom for Federal Trade Commission, 6 Your Honor. 7 MR. DENIS: Paul Denis of Dechert, LLP on behalf of 8 Whole Foods Market. 9 MR. ATKINS: Alden Atkins from Vinson and Elkins for 10 Whole Foods Market. 11 MR. FRIEDMAN: Good Morning, Your Honor. Paul 12 Friedman from Dechert for Whole Foods. 13 THE COURT: We're going to have that confusion again. 14 MR. FRIEDMAN: I trust we will. 15 MR. BRENNAN: Jeff Brennan from Dechert for Whole 16 Foods. 17 MR. FISHKIN: Good morning. James Fishkin from 18 Dechert, LLP for Whole Foods. 19 MR. TAURMAN: John Taurman from Vinson and Elkins for 20 Whole Foods. 21 MR. HENDRICKSON: Good Morning. Matt Hendrickson 22 from Skadden, Arps for Wild Oats. 23 MR. ARONSON: Good morning. Cliff Aronson from 24 Skadden, Arps for Wild Oats. 25 MR. REILLY: Matt Reilly from the Federal Trade Linda L. Russo, RPR Official Court Reporter 5 1 Commission. 2 MR. LANG: Good morning. Tom Lang for the Federal 3 Trade Commission. 4 MS. MOSCATELLI: Good morning, Your Honor. Catharine 5 Moscatelli for the Federal Trade Commission. 6 MR. FRANCHAK: Good morning, Your Honor. Mike 7 Franchak for the Federal Trade Commission. 8 MR. BLOOM: Your Honor, if I may, also seated at 9 counsel table for the Federal Trade Commission is Mr. Sanghvi, 10 an economist with the agency. 11 THE COURT: Good morning. Okay, let me say a couple 12 of things, and then I know counsel may have some preliminary 13 matters. Just so everybody here and in the courtroom next door 14 is clear, there was an order, actually an amended order, that 15 was issued on July 26th, and I hope everybody is aware of it. 16 Cameras of any kind, including camera phones, laptop 17 computer cameras, video cameras, video phones and cameras 18 connected to laptop computers, audio recording devices are not 19 permitted in the courthouse. In the courthouse. And they're 20 certainly not permitted in the courtroom. 21 Other than items that I have authorized counsel and 22 their people to possess, no other individuals are permitted to 23 have cameras, cell phones, camera or video telephones, tape 24 recording devices, laptops, or other electronic devices in the 25 courtroom. Paging devices that do not have a transmission Linda L. Russo, RPR Official Court Reporter 6 1 capability are permitted, but the alert signal must be on 2 inaudible or vibration settings. Photographic and video and 3 audio recordings or transmission of court proceedings are 4 strictly prohibited. 5 Any violation may result in contempt sanctions. And 6 these same rules apply to courtroom 28-A next door. 7 There are issues of confidentiality. There are a 8 number of issues that may come up that are sensitive to the 9 defendants in this case, as well as to some other people who 10 are here and the representatives of other supermarkets and 11 other food purveyors, I think both the FTC and the defendants 12 have tried to be very sensitive to that in their public filings 13 and in prior proceedings, and we need to do that during the 14 course of this hearing. 15 The plan is to do as much of this hearing as we can 16 in open court, but there may be times with each witness, each 17 of the two witnesses, there are only going to be two witnesses 18 today that we're going to have to close the courtroom and turn 19 off the sound in the other courtroom. 20 When we do that, people are going to have to leave, 21 and then I know we're going to have some logistical problems 22 getting people back in. I'm afraid that we're going to have to 23 revert to seating on a first-come first-serve basis, except for 24 the reserve rows. 25 I want to talk to counsel in a minute about how we're Linda L. Russo, RPR Official Court Reporter 7 1 going to deal with exhibits. At the moment I have I don't know 2 how many notebooks filled with exhibits and deposition 3 transcripts. At some point I assume they're all going to be in 4 evidence, or you've agreed they're all in evidence. The 5 question is for purposes of today which of them must remain 6 confidential, and which of them can be shown on this screen or 7 on the television screen over in the corner there. And I 8 assume counsel have figured that out. And we're going to have 9 to deal with the logistics of that with Ms. Moon. 10 There will be at least one break during the morning 11 session and one in the afternoon, there will be a lunch break. 12 We have agreed, the lawyers and I have agreed that each side is 13 entitled to up to three hours today to use as they see fit. 14 And while a lawyer is, I think what we have agreed is that each 15 expert will take the stand and will affirm his or her expert, 16 in this case his expert report, and may have no additional 17 direct testimony. And then there will be cross-examination and 18 then redirect. 19 The time will be charged against the party whose 20 lawyer is asking questions at the time. Any questions that I 21 ask will, I think, be charged against the lawyer who is on his 22 feet asking questions at the time, because my questions will 23 largely be suggested by the topic that we're talking about at 24 that time. 25 For those in the room and next door who are not Linda L. Russo, RPR Official Court Reporter 8 1 lawyers, let me say this. Don't draw any inferences or 2 suggestions of what I'm thinking from any questions that I 3 might ask. Judges sometimes ask questions because they're 4 stupid. Sometimes they ask questions because they just want to 5 know. Sometimes they ask questions because they don't think 6 the answer is very clear. There are all sorts of reasons why 7 judges ask questions, and it usually is not suggestive of what 8 they're thinking about how the case should come out. 9 At least that was my experience when I was arguing 10 appellate cases, and I was sometimes very surprised when the 11 decision came out. So I know that you're all going to write in 12 the newspapers and communicate to whomever you're communicating 13 to whatever you want to, but I want to make that comment for 14 what it's worth in fairness to the parties. And the 15 significance of these proceedings and the outcome of these 16 proceedings to the parties and to the markets. 17 So those are the preliminary sort of ground rules and 18 preliminary things I wanted to say. I just have one other 19 housekeeping thing just so I'm clear, then I'll ask counsel 20 what preliminary matters we need to discuss. 21 I received yesterday a motion to unseal the 22 memorandum of points and authorities in support of plaintiffs 23 motion for preliminary injunction, and there was a chart 24 connected to it. And it sort of stopped, and it has to do, for 25 those that care, about filing this document on the public Linda L. Russo, RPR Official Court Reporter 9 1 record with certain redactions, and the parties have agreed on 2 some but disagreed on others. The charts stopped at about page 3 67, even though the next 20 or so pages also had some green 4 highlights and some yellow highlights. Am I correct from a 5 conversation that somebody from the FTC had with my law clerk 6 that after page 67 the parties are in agreement? 7 MR. LANG: That's correct, Your Honor. The green 8 highlighting on page's 67, 68 and 70 should not have been 9 there, so the table is what governs, not the extra green 10 highlighting on those last three instances. And we informed 11 defendants counsel of that. 12 THE COURT: I thought I was missing something. 13 MR. ATKINS: Your Honor, Alden Atkins. We were 14 surprised by the motion. We certainly didn't want the Court to 15 have to deal with confidentiality of the brief. In fact, we 16 had an agreement with the FTC last week that all of these 17 redactions would be made, but they changed their mind over the 18 weekend. We have seen your order, Your Honor, we understand 19 that you're going to rule tomorrow morning. 20 THE COURT: No, I'm going to rule tonight, so that 21 you can be prepared for tomorrow morning. 22 MR. ATKINS: Your Honor, we have been struggling all 23 night. We're going to have a brief in your hands today. I 24 would ask the Court, I'm not sure that we will make the 4:00 25 deadline to file something under seal today, and if the Court Linda L. Russo, RPR Official Court Reporter 10 1 would give us the indulgence, can we deliver it to your 2 chambers and then file it with the clerk tomorrow morning? 3 THE COURT: Sure. But I'd like to rule on this 4 before we start tomorrow morning. And just to give you some 5 guidance, my tentative view is that we should redact all 6 references to cities. 7 MR. ATKINS: Thank you, Your Honor. That guidance 8 is very helpful. 9 THE COURT: But beyond that I have an open mind. 10 MR. ATKINS: Thank you, Your Honor. 11 THE COURT: Okay. Preliminary matters. What else 12 do we need to talk about before you all put Dr. Murphy on the 13 stand? 14 MR. BLOOM: Your Honor, we received notice of several 15 objections to our proposed demonstrative exhibits, and I think 16 it would be appropriate for the Court to consider those matters 17 at this time. As I understand the objections, the first is a 18 question as to whether certain entry events in one of Dr. 19 Murphy's exhibits were in evidence. In fact, that information 20 was in third party subpoena responses that are in evidence in 21 this proceeding. 22 The second objection relates to a question of 23 statistical significance where the defendants' view, as I 24 understand it, is that there should be a notation on an exhibit 25 that a particular column is statistically significant at the 85 Linda L. Russo, RPR Official Court Reporter 11 1 percent confidence level. It seems to me that that is an 2 appropriate topic for cross-examination or argument, but not an 3 appropriate requirement for the demonstrative exhibit. 4 THE COURT: And for argument both tomorrow and in the 5 brief. 6 MR. BLOOM: That's correct, Your Honor. 7 THE COURT: In the Conclusions of Law, or whatever. 8 MR. BLOOM: Yes, Your Honor. The other matters 9 relate to two things. We attempted to on the demonstratives 10 indicate the sources of the data, and in some instances we said 11 Whole Foods and Wild Oats margin data or identified one of the 12 parties. Several of those are, in fact, incorrect. I 13 appreciate defense counsel's calling that to our attention. We 14 are in the process of getting those corrected even as we speak. 15 Should they be used prior to our having corrected versions in 16 the hands of the Court, I'll correct them at that time. 17 In addition, there are two substantive errors that 18 were made in timelines. For a city where we had 19 months of 19 data, the time line was inadvertently extended to two years. 20 Again, I appreciate counsel's calling that to our attention. 21 We regret the error, and we'll correct that as quickly as 22 possible. 23 THE COURT: So the last two categories will be 24 corrected, and the first two are still at issue. 25 MR. BLOOM: Yes, Your Honor. Linda L. Russo, RPR Official Court Reporter 12 1 MR. FRIEDMAN: Your Honor, Paul Friedman. If I could 2 address the categories that are at issue. The new entry events 3 that appear on the first PDF, if they would show us the 4 information that they're relying on, then we can perhaps 5 resolve that. And if it's in evidence, we'll withdraw the 6 objection. But they didn't communicate that to us. 7 The second is a demonstrative of a chart that's 8 already in Dr. Murphy's report, and Dr. Murphy says in his 9 report that the results in all but two categories are not 10 statistically significant. We think it's misleading to present 11 a demonstrative that omits that indicator because they're 12 purporting to hold it out as something that is what it isn't. 13 And I think those are the only objections that 14 they're not correcting. 15 THE COURT: What I would suggest on the second one is 16 they use the demonstrative, you ask Dr. Murphy about it, and 17 you're going on say in Exhibit Six of your, whatever exhibit it 18 is, of your report, it's the same thing, but you failed to 19 include this, or the Federal Trade Commission has failed to 20 include this, what's the story? And he presumably will confirm 21 what he said in his report, and we can annotate the 22 demonstrative, or I can rely on what's in the report as opposed 23 to the demonstrative, unless the Federal Trade Commissioner 24 wants to correct it after they hear what Dr. Murphy has to say. 25 If he's saying something different today from what he Linda L. Russo, RPR Official Court Reporter 13 1 said in his report, that goes to credibility, that goes to 2 weight, it seems to me. 3 MR. FRIEDMAN: That's fine. If you hear me say 4 "what's the story" to Dr. Murphy, I hope lightning strikes me, 5 Your Honor. 6 MR. BLOOM: Your Honor, I'd just like to make clear 7 that our view is that information that is statistically 8 significant at the 85 percent confidence level is perfectly 9 probative, and that the failure to notate that is in no way a 10 failure to disclose important information to this Court. 11 THE COURT: Okay. Anything else preliminarily before 12 I raise one other question? 13 At some point I think we discussed the fact that 14 everything that I have in binders in my chambers under lock and 15 key will be moved into evidence, and if anybody has any 16 objections, they will lodge them in writing sooner rather than 17 later. 18 The question, however, is for purposes of today and 19 tomorrow, and perhaps going -- well, going forward as I write 20 the opinion, which of these exhibits are public and which are 21 not? In a normal trial if you moved exhibits in evidence, they 22 would all be public. And under the Court's rules, at the end 23 of the trial, in fact, each side takes their own exhibits home. 24 We don't keep them in the courthouse because we don't have room 25 to keep them in the courthouse, and you're charged with keeping Linda L. Russo, RPR Official Court Reporter 14 1 them for purposes of appeal. 2 And sometimes in a trial of high public interest, 3 however, and I'm sure Judge Walton had this in the Libby trial, 4 I know I had it in a trial I had with a man named David 5 Safavian, who played golf with Jack Abramoff in Scotland, and 6 the press wanted certain exhibits, and they were public. And 7 so we made those exhibits available. The main one they wanted 8 was a photograph standing before a private jet of Congressman 9 Ney and his staffer and Mr. Safavian and Mr. Abramoff and 10 others. It turned out there was a request for documents, but 11 that was the only one they really cared about. The vouchers 12 were too complicated, I guess. 13 So what are we doing for purposes of this hearing in 14 terms of our goal of doing as much of it as possible in open 15 court and putting it up on either this screen and that screen, 16 or this big screen up here? Have you all reached some sort of 17 an agreement as to what's public and what's not public? 18 MR. FRIEDMAN: Your Honor, Paul Friedman. For 19 purposes of the cross-examination of Dr. Murphy, I'm planning 20 to just provide Dr. Murphy a notebook with paper copies of the 21 exhibits, and I'll provide that to the FTC. Your Honor has 22 that and I'll give a copy to your clerk. So they won't need to 23 be published on the screen. 24 There may be instances where his deposition testimony 25 needs to be shown to him. I have a paper copy of it. I'm Linda L. Russo, RPR Official Court Reporter 15 1 prepared to put that on the screen, if nobody has any objection 2 to that. I think that the areas where I'm going to be asking 3 him questions ought not to elicit responses that reveal 4 confidential information 5 THE COURT: That's the goal that we talked about at 6 the last status conference of trying to prepare the witnesses 7 so that they can answer as many of these questions as possible 8 in a public form. 9 MR. BLOOM: Your Honor, Michael Bloom. Our intention 10 would be to indicate to the Court if we have a demonstrative 11 exhibit and they are confidential, in advance of suggesting 12 that they come up on the monitors that it is confidential so 13 that the Court can take appropriate action to ensure that those 14 monitors are cut off and the screen is cut off. In addition, 15 we'll make every effort to refer Your Honor to the left-hand 16 column or speak in terms that will enable Your Honor to follow 17 but to remain in open session. 18 THE COURT: Just so I understand the logistics, I 19 think that if you put things, if things come up on these 20 television screens, we have the ability to either limit them to 21 the witness and to myself and to my law clerk and to counsel, 22 as opposed to putting them up on that screen over there. If we 23 are using this screen, however, I don't think we have that 24 ability, do we? Or do we? 25 Well, I guess the answer is that if everything is Linda L. Russo, RPR Official Court Reporter 16 1 electronically appearing, if there's nothing that's appearing 2 there that isn't also appearing here, then we have no problem. 3 We can turn that off. I thought you were using old fashioned 4 technology with respect to the screen, but I'm wrong. 5 Okay, are we ready? 6 MR. BLOOM: Ready, Your Honor. 7 MR. FRIEDMAN: Yes, Your Honor. 8 THE COURT: Well, then, why don't you call your 9 witness. 10 MR. BLOOM: We call Professor Kevin Murphy. 11 KEVIN MURPHY, PLAINTIFF'S WITNESS, SWORN 12 THE COURT: Good morning. 13 MR. FRIEDMAN: May I approach the witness, Your 14 Honor? 15 THE COURT: Yes. I think what we should do for 16 completeness, even though we are not having direct, is that I 17 ought to ask Dr. Murphy, or you can ask him if you want to, put 18 the report in front of him, somebody should ask him, put the 19 report in front of him and ask him if it's his report, ask him 20 if that's his signature swearing to its truth, and ask him if 21 he still agrees with everything in it day or has any additions 22 or corrections before we begin with the cross. So Mr. Bloom 23 can do that or Mr. Friedman can do that. That seems to me to 24 be at least the substitute for direct examination. 25 MR. BLOOM: Yes, Your Honor. Linda L. Russo, RPR Official Court Reporter 17 1 DIRECT EXAMINATION 2 BY MR. BLOOM: 3 Q. Good morning, Professor Murphy. 4 A. Good morning. 5 Q. I'd ask you to turn, please, to tab 3 in the index of 6 documents that you've just received. I believe that should be 7 PX-2878. 8 A. Okay. 9 Q. Can you identify for the Court PX-2878? 10 A. Yes. That's my expert report. 11 Q. Would you turn to the signature page, please. 12 A. Okay. 13 Q. And is that your signature? 14 A. Yes, it is. 15 Q. Do your opinions today remain the opinions expressed in 16 your report? 17 A. Yes, they do. 18 MR. BLOOM: Thank you. 19 CROSS-EXAMINATION 20 BY MR. FRIEDMAN: 21 Q. Good morning, Dr. Murphy. 22 A. Good morning. 23 Q. We met before? 24 A. Yes, we did, at my deposition. 25 Q. Right. This is the first time you've testified in court Linda L. Russo, RPR Official Court Reporter 18 1 as an expert on economic issues in a merger case, correct? 2 A. That is correct. 3 Q. And you've testified in court only three times before this 4 on any trust matters, correct? 5 A. I'm trying to remember. I think it's actually four. 6 Q. None of those was a merger case, correct? 7 A. None of those was a merger case, no. 8 Q. And none of your publications has specifically addressed 9 Section Seven of the Clayton Act, correct? 10 A. That's correct. 11 Q. You have indicated that you have more than 20 years 12 experience consulting as an economist; is that right? 13 A. That is correct. 14 Q. And you indicate that you have consulted in about 50 15 antitrust cases; is that right? 16 A. That would be roughly correct, yes. 17 Q. And roughly five of those engagements has involved 18 mergers; is that right? 19 A. I believe that's about right. 20 Q. And when we met at your deposition the only merger case 21 that you were able specifically to remember working on was the 22 Whirlpool Kitchen Aid merger, correct? 23 A. That is correct. 24 Q. That merge occurred in about 1985; is that right? 25 A. That sounds about right. Linda L. Russo, RPR Official Court Reporter 19 1 Q. You were not a testifying expert in that case? 2 A. No, I was not. 3 Q. Before this matter, you have not been a testifying expert 4 in any merger matter, correct? 5 A. That is correct. 6 Q. Okay. And you've never filed an expert report in a case 7 that involved a merger challenge before this one, right? 8 A. That's correct. 9 Q. You never made a presentation to the Federal Trade 10 Commission in a merger investigation, have you? 11 A. That's correct. 12 Q. And you never made a presentation to the Department of 13 Justice in a merger investigation, correct? 14 A. That's correct as well. 15 Q. You have never provided written or oral testimony at 16 deposition hearing or trial in a merger case before this one, 17 right? 18 A. That is correct. 19 Q. And you've never testified in court with respect to 20 product market definition before this case, correct? 21 A. I believe that's correct, although there may have been a 22 few questions, but that has not been a focus of my testimony 23 before. 24 Q. Now, your opinions are reflected in your July 9 report 25 that you were just presented by Mr. Bloom, correct? Linda L. Russo, RPR Official Court Reporter 20 1 A. In addition, I filed two other reports that also reflect 2 my opinions. 3 Q. Correct. And before you completed your initial report, 4 the July 9 report, Plaintiffs Exhibit 2878, you had spent 5 approximately 100 hours in toto working on this matter, 6 correct? 7 A. That's correct. 8 Q. Now, I just want to make sure about one thing. Mr. Bloom 9 asked you whether the signature on your report, PX-2878, was 10 your signature, and you affirmed that it was, correct? 11 A. Yes. 12 Q. I notice that none of your reports was submitted under 13 oath, so I want to make sure that you understand that the Court 14 is receiving all three of your reports under the penalties of 15 perjury; do you understand that? 16 A. Absolutely. 17 Q. All right. And I want to talk about, when I talk about 18 your report, since it's been received as your direct testimony, 19 I may refer to it as your testimony, or things that you've 20 testified, fair enough? 21 A. That seems fair. 22 Q. And you've testified that the central concern of the 23 merger guidelines is with the impact of competition on price, 24 correct? 25 A. I would say the impact on competition and price, I think. Linda L. Russo, RPR Official Court Reporter 21 1 Q. Well, let me ask you to look at paragraph 54 in PX-2878. 2 That's your testimony, right? 3 A. Yes, it is. 4 Q. You say there, the central concern of the merger 5 guidelines is with the impact of competition on prices, 6 correct? 7 A. That's what I say there, correct. 8 Q. You stand by that, right? 9 A. Yes, although I think a better way to state it, is what 10 we're interested in is what's the impact on competition and 11 price. 12 Q. But what you have told the Court in your direct testimony 13 is the central concern of the merger guidelines is with the 14 impact of competition on prices, correct? 15 A. That is correct. 16 Q. All right. Now, you've also testified that because this 17 is a merger case, a major question in your analysis is the 18 effect of reducing the number of sellers in the relevant 19 market, right? 20 A. I have testified to that, yes. 21 Q. All right. And you've testified that the question about 22 the effect of reducing the number of sellers in the market 23 applies directly to overlap markets in which Wild Oats stores 24 will be closed after the acquisition, right? 25 A. It's not limited to those markets, but it would apply to Linda L. Russo, RPR Official Court Reporter 22 1 those markets. 2 Q. But you've testified in this case that that is a major 3 question in your analysis of the markets in which Wild Oats 4 will be closed, correct? 5 A. What was that again? 6 Q. I'll put the question to you again. You have testified 7 that the question of the effect of reducing the number of 8 sellers in the relevant market applies directly to overlap 9 markets in which Wild Oats will be closed after the 10 acquisition? 11 A. That is correct. 12 Q. Now, in connection with your initial direct testimony, 13 PX-2878, you presented three sets of econometric analyses, 14 right? 15 A. I believe there were more than three. 16 Q. Well, you did an entry impact on margins, correct? That's 17 one. 18 A. I did an entry impact on margins, I did an entry impact on 19 sales for those both being for Wild Oats. I did the same 20 analysis for Whole Foods. I then did an analysis on prices for 21 Wild Oats. I then did an analysis of the impact over time on 22 sales and margins for Wild Oats. I then did an analysis of 23 comparing Whole Foods, Whole Foods Markets with Whole Foods 24 Wild Oats markets in the cross section. I then did a 25 comparative entry analysis between the two. So that sounds Linda L. Russo, RPR Official Court Reporter 23 1 like more than three. 2 Q. All right, Dr. Murphy. Your entry impact on margins and 3 sales of Wild Oats is presented in Exhibit Three of your 4 report, correct? 5 A. That is correct. 6 Q. And your entry analysis -- 7 A. I'm sorry, I spoke incorrectly. That is an analysis of 8 that subject. That same subject is also addressed in other 9 tables as well. 10 Q. All right. Dr. Murphy, one of the econometric analyses 11 you performed studied the impact of banner entry by various 12 food and grocery retailers on Wild Oats, sales, and gross 13 margins, right? 14 A. Yes, for example Exhibit Three. 15 Q. All right. And by banner entry, you mean the store 16 opening representing the first entry by a particular player 17 into a market, right? 18 A. That would be the appearance of a banner in a marketplace. 19 And, actually, in that regression, what we're looking at is 20 actually whether that banner is present or not in the market. 21 Q. You've got something you called a presence variable, 22 correct? 23 A. That's exactly what it would be. 24 THE COURT: A what? 25 THE WITNESS: It's a variable that measures whether Linda L. Russo, RPR Official Court Reporter 24 1 that particular banner is there or not at a point in time. 2 BY MR. FRIEDMAN: 3 Q. In order for the regression to -- let me strike that. 4 You performed the same kind of econometric exercise 5 to study the impact of banner entry on Whole Foods sales and 6 margins at the store level, correct? 7 A. Yes. That would be in Exhibit Four. 8 Q. And both the econometric analysis that is presented in 9 Exhibit Four, and the econometric analysis that is presented in 10 Exhibit Three is an analysis of sales and margins, correct? 11 A. That is correct. 12 Q. The data that you used for that study was the store level 13 sales data and the store level margin data in one case for Wild 14 Oats, in the other case for Whole Foods, right? 15 A. Yes, that would roughly accurately characterize the data. 16 Q. You did ask the Federal Trade Commission to obtain from 17 Whole Foods and Wild Oats pricing data, correct? 18 A. Yes, we did. 19 Q. And you received pricing data by UPC code, Universal 20 Product Code, and by store from both of the parties, correct? 21 A. Yes, we did. That was quite a bit further into the time 22 frame. But, yeah, we did ultimately receive that. 23 Q. And the analysis that you presented in Exhibit Three and 24 Exhibit Four did not use that pricing data that we just 25 described, correct? Linda L. Russo, RPR Official Court Reporter 25 1 A. That is correct. 2 Q. Okay. Now, you've testified in your direct testimony that 3 if unit costs are constant and do not vary with the amount 4 sold, changes in gross margin can be used to infer the 5 magnitude of price change, or price effect, right? 6 A. That would be correct. 7 Q. But you've also testified that if unit costs are not 8 constant, then changes in margin can be a misleading indicator 9 of price effects, correct? 10 A. They can be, based on how -- when you say not constant, it 11 depends on the way in which they would vary and how they would 12 vary. I believe I discussed that explicitly in my report. 13 Q. Let me direct you to paragraph 55 of your direct 14 testimony. You said if unit costs in a representative store 15 are not constant, then changes in margins can be a misleading 16 indicator of price effects, correct? 17 A. Exactly. What I'm saying here is what I covered in the 18 ensuing couple of sentences. I just want to be clear with what 19 I'm trying to a say and what the point is. 20 Q. I understand, but what I want you to do, and we've talked 21 about this before is, I'm going to ask you questions, and you 22 can answer my questions, if there's something that you want to 23 elaborate on, Mr. Bloom will have an opportunity to do that. 24 MR. BLOOM: Your Honor, by the same token the witness 25 should understand that if a simple yes or no answer doesn't Linda L. Russo, RPR Official Court Reporter 26 1 adequately convey the truth of the situation, that he's not 2 required to give a yes or no answer. 3 THE COURT: I agree. 4 BY MR. FRIEDMAN: 5 Q. Now, a second, perhaps you want to call it a third or 6 fourth, but a second type of econometric analysis that you 7 presented estimated the impact of Whole Foods banner entry on 8 Wild Oats prices, correct? 9 A. That is correct. 10 Q. And the results of that analysis are presented in your 11 Exhibit Five to your July 9 report, PX-2878, correct? 12 A. That would be correct. 13 Q. Now, there is no analysis of Whole Foods price data in 14 Exhibit Five, right? 15 A. No, that's Wild Oats data. 16 Q. So the only price data that is analyzed and presented in 17 Exhibit Five is Wild Oats price data, correct? 18 A. That is correct. 19 Q. Now, you've testified that you have not studied the effect 20 of Wild Oats entry in a market on Whole Foods prices or margins 21 or sales, right? 22 A. That was true at the time I had written my report, yes. 23 Q. Well, and that's because there is no event in which Wild 24 Oats entered a Whole Foods market, right? 25 A. Actually, there's some data from the more recent period. Linda L. Russo, RPR Official Court Reporter 27 1 Recently Wild Oats announced that they were going to open a 2 store in Boulder, Colorado, and if you look at the Whole Foods 3 pricing data for that period, in anticipation of the entry of 4 the Wild Oats store, you find, using the same methodology we 5 used in North Carolina, that prices at Whole Foods declined 6 roughly two percent even before the store came in. Simply the 7 announcement of the potential entry. That's the best event 8 that I was able to uncover. And so that would add to the 9 pieces of the puzzle. 10 Q. Is that in your July 9th report? 11 A. No, it's not. 12 Q. Is that in your July 13th report? 13 A. No, it's not. 14 Q. Is that in your July 16th report? 15 A. No. It's work I did in response to questions you asked me 16 at my deposition, so I went back and looked. 17 Q. So it's work that's never been disclosed to defendants; is 18 that correct? 19 A. They have the data. 20 Q. It's work that you did that's never been disclosed to the 21 defendants; is that correct? 22 A. I don't believe so, no. 23 Q. You don't believe it's correct, or you don't believe it's 24 been disclosed? 25 A. It has not been disclosed. It's work I have been doing Linda L. Russo, RPR Official Court Reporter 28 1 ongoing since my deposition. 2 MR. FRIEDMAN: I'm going to move to strike that, Your 3 Honor. We have no opportunity or ability to cross-examine work 4 that we've not been shown. 5 MR. BLOOM: Counsel opened the door for this line of 6 questioning. 7 THE COURT: Well, I'll consider it for what it's 8 worth. You can keep exploring it if you want to, and Dr. 9 Murphy can make available all underlying data and documentation 10 that supports his discussion of this. And he will. Not only 11 can he make it available, he will make it available. 12 MR. BLOOM: Yes, he will, Your Honor. 13 MR. FRIEDMAN: And when will that happen, Your Honor? 14 THE WITNESS: We could do it today if you want. 15 THE COURT: Okay, today. 16 MR. FRIEDMAN: And then will we have an opportunity 17 to bring him back and ask him questions about it? 18 THE COURT: You can tell me after you received it 19 whether you want to do that. 20 MR. FRIEDMAN: Thank you. 21 BY MR. FRIEDMAN: 22 Q. Now, in your direct testimony at paragraph 63 you said 23 there was only one fairly recent event in which Wild Oats 24 exited a Whole Foods market, correct? 25 A. That's correct, within the parameters of the sample that I Linda L. Russo, RPR Official Court Reporter 29 1 was looking at. 2 Q. Pardon me? 3 A. Within the parameters of my sample, so something that 4 would have potentially been useful for my statistical analysis. 5 Q. Within the parameters of the sample means you were 6 limiting Wild Oats stores to those stores that were 25,000 7 square feet in size or larger; that was one parameter, correct? 8 A. That's correct. 9 Q. And the other parameter was, you were limiting yourself to 10 Wild Oats stores that were within five miles of a Whole Foods 11 store, correct? 12 A. Both of those would be correct. 13 THE COURT: Why 25,000 square feet or larger? 14 THE WITNESS: What we found from looking at the 15 record, that people had commented that the smaller, older Wild 16 Oats stores were, some people said were not competitively 17 significant. And there are some very small stores. For 18 example in New York, I think there was a store under 3,000 19 square feet. So we had to decide, like, we didn't want to 20 include those because if you include stores that are really not 21 significant in a sample with stores that are significant, 22 you're going to get kind of biased results. So we wanted to 23 try to eliminate those less or nonsignificant stores and we had 24 to decide where to draw the line. 25 Now in statistics, it's a pretty simple principle to Linda L. Russo, RPR Official Court Reporter 30 1 think of it this way. If you include things that should not be 2 included, that will bias your results. On the other hand, if 3 you play it on the safe side and exclude things -- if you go 4 the other way and exclude some things that could have been 5 included, you don't bias your results because the sample you 6 have included is still a relevant sample for analyzing the 7 issue. 8 So we drew the line at 25, not because 24,000 wasn't 9 significant and 26 was, we thought that 25 was a good place to 10 draw the line. It also turns out that, for example, if you're 11 looking at Exhibit Number Four, that had you drawn the line 12 lower, say at 20,000, there would have only been one potential 13 event, which would have been Fort Lauderdale. And it turns out 14 in the Fort Lauderdale case, that that store was originally 15 slated as a relocate. 16 And a relocate store is not going to have the same 17 competitive effect that would a true exit of a store, 18 particularly if you're thinking about how a competitor would 19 respond to his pricing. That is, a competitor is very unlikely 20 to, say, raise price, if they know the store is going to come 21 back in, in a better location later. That would be sort of 22 from a pricing point of view, not a very wise strategy. In 23 fact, you might even think they would cut price in that case in 24 order to try to win the customers and keep them when the other 25 comes back. And so that was, as it turned out, 25 turned to be Linda L. Russo, RPR Official Court Reporter 31 1 a pretty good place from our point of view to draw the line. 2 THE COURT: In the 18 markets that you and the 3 Federal Trade Commission focus on in this litigation, did you 4 exclude stores in any of those particular markets? Or to put 5 it another way, if there were stores of 25,000 square feet or 6 less, does that suggest that the closing of Wild Oats stores in 7 any of those 18 markets would not have an anticompetitive 8 effect after the merger? 9 THE WITNESS: No. It would just mean that the 10 effects that we quantified in our empirical analysis would be 11 directly applicable to the stores about 25,000 square feet. 12 You'd have to do some inference to say, well, if I'm going 13 below that level, would I get a smaller effect? And, for 14 example, how far down do I actually get an effect? We didn't 15 really address that, so I chose to focus on the nine markets 16 where the closings would occur with stores above the 25,000 17 square feet, and focus the discussion even in the markets where 18 they would stay open on the markets where the stores were, 19 again, above 25,000 square feet, because those are the markets 20 to which my empirical analysis was the most directly relevant. 21 THE COURT: Okay. 22 BY MR. FRIEDMAN: 23 Q. Let me follow up on that, Dr. Murphy. In fact, at 24 paragraph 26 of your direct testimony, contrary to what you 25 just said, you testified that the documentary and econometric Linda L. Russo, RPR Official Court Reporter 32 1 evidence suggests that the smaller, older Wild Oats stores, are 2 not competitively significant; that was your testimony, wasn't 3 it? 4 A. And that's exactly what I just said. 5 Q. So you, as a consequence of that conclusion, limited your 6 analysis to Wild Oats stores with square footage in excess of 7 25,000 square feet? 8 A. But that don't say -- 9 Q. Correct? Yes or no? 10 A. Correct. But that doesn't say -- 11 Q. Thank you. 12 A. You've got to be careful. That doesn't say that the ones 13 below 25,000 are not significant. Because we knew there were 14 some below 25,000 that were not significant, we had to draw the 15 line somewhere. 25,000 seemed like a pretty safe way to draw 16 the line in order to not run into that problem. 17 Q. And you testified at paragraph 26 that the stores that 18 were smaller and older are not competitively significant, 19 correct? 20 A. Right, but that's not synonymous with the stores under 21 25,000 square feet, for exactly the reason I just explained 22 when you're talking about sample inclusion. 23 Q. We can all read what you said there. Now, Dr. Murphy, you 24 would agree with me that if you're drawing a line, it's 25 important to draw the line consistently, right? Linda L. Russo, RPR Official Court Reporter 33 1 A. Not necessarily, it depends on how you're going to use the 2 analysis. 3 Q. So you could draw the line at 25,000 feet but look at a 4 store that's 24,000 feet? 5 A. You could. Typically what you do when you do a particular 6 analysis is, you draw the line, and then you do the analysis 7 using that line. Sometime you'll vary the line that you draw 8 to see what the impact of that was. And one of the things I 9 just described was sort of a little bit of a sensitivity 10 question about what happens if you draw the line slightly 11 differently. 12 Q. So let me go back to talking about what you said at 13 paragraph 63, where you said that as of the time you wrote this 14 report, you were only aware of one fairly recent example in 15 which a Wild Oats store exited a Whole Foods market, correct? 16 A. Yeah. That would refer to the above 25,000 feet, and 17 within five miles. 18 Q. And so you reached the conclusions that you presented in 19 your July 9th report without any economic analysis of the 20 effect of that recent Wild Oats banner exit on Whole Foods 21 prices, right? 22 A. That's correct. We did not have data that extended beyond 23 the point of exit at the time. 24 Q. All right. Now, there have not been any Whole Foods 25 banner exits in Wild Oats markets, correct? Linda L. Russo, RPR Official Court Reporter 34 1 A. I believe that's correct. 2 Q. Okay. Now, you've testified, again, I'm focusing on 3 paragraph 63, that since there are no events in which Wild Oats 4 entered a Whole Foods market, and only that one recent example 5 of Wild Oats exiting from a Whole Foods market, the data that 6 you had and that you analyzed in Exhibits Three, Four and Five, 7 "do not offer a direct test of the extent to which the Wild 8 Oats presents unique constraints to Whole Foods that will 9 disappear as a result of the proposed transaction." Right? 10 A. It's very important to realize that there's the Ds data. 11 So we're referring to a very specific set of data, which is the 12 data that are analyzed in Exhibit Four. There's actually 13 evidence on this point that comes from other tables. 14 Q. So what I'm focusing on is what you said in your prior 15 testimony, that the data that you analyzed in Exhibit Four 16 which was banner exits and banner entries by Wild Oats into 17 Whole Foods markets. That's what you're talking about in 18 Exhibit Four, correct? 19 A. There are none of those observations in Exhibit Four, so 20 the data in Exhibit Four do not contain any of those 21 observations. That's what we're saying in paragraph 63. 22 Q. Exactly. What you're saying is that because you didn't 23 have any observations of Wild Oats entry or Wild Oats exits 24 that met your criteria of size and proximity, that you did not 25 offer a direct test of the extent to which Wild Oats presented Linda L. Russo, RPR Official Court Reporter 35 1 unique constraints to Whole Foods that will disappear as a 2 result of the proposed transaction, correct? 3 A. No, what you said is not correct. You said I did not 4 offer a test. I did not offer a test in Exhibit Four. That's 5 a different statement than what you just made. 6 Q. Let me make sure that the record is clear. What you said 7 in your prior testimony is that as a consequence of the absence 8 of evidence of Wild Oats banner entry, or Wild Oats banner 9 exit, that you did not have data that was studied in Exhibit 10 Four that offered a direct test of the extent to which Wild 11 Oats presented a unique constraint to Whole Foods that would 12 disappear as a result of the proposed transaction, correct? 13 A. That sounds correct. 14 Q. All right. Now, you also testified in your direct 15 testimony that your Whole Foods entry analysis in Exhibits 16 Three and Five does not directly address the test or the issue 17 contemplated by the Guidelines market definition test in those 18 cases where Whole Foods would operate both the Whole Foods and 19 the Wild Oats store under the Whole Foods banner, correct? 20 A. Let me go back. Which paragraph are you referring to? I 21 want to make sure we're on the same page. 22 Q. Let me direct you to it, and I will restate the question. 23 You testified in paragraph 64 of your direct 24 testimony that your Whole Foods entry analysis does not 25 directly address the issue contemplated by the merger Linda L. Russo, RPR Official Court Reporter 36 1 Guidelines market definition test in those cases where Whole 2 Foods would operate both stores under a single banner, correct? 3 A. That's correct. 4 Q. All right. 5 A. Entry analysis doesn't directly look at the change of 6 ownership question. It looks at the fact of changing who is in 7 the marketplace, which is a slightly different question. 8 Q. So the issue that you were looking at for change of 9 ownership was if Whole Foods and Wild Oats were under a single 10 ownership, would prices be materially and sustainably higher, 11 correct? 12 A. That's part of the issue. I mean, there's -- 13 Q. Let's look at what you said in your direct testimony. You 14 said, "In addition, my Whole Foods entry analysis does not 15 directly address the issue contemplated by the Guidelines 16 market definition test in those cases where Whole Foods would 17 choose to operate both stores under a single banner." 18 Question: If a particular set of suppliers, here 19 Whole Foods and Wild Oats, were under a single ownership, would 20 prices be materially and sustainably higher. That's the 21 question, isn't it? 22 A. I agree, but you made a statement that was much broader 23 than just the Guidelines market definition test. If you're 24 talking about the context of the Guidelines market definition 25 test, which if you're going to go for the most strict kind of Linda L. Russo, RPR Official Court Reporter 37 1 definition, it's changing who controls the assets without 2 changing the assets that are there. 3 That's the hypothetical monopolist question is, you 4 take the producers, and you say one guy is going to control 5 those assets and set the pricing. That is the extent to which 6 I meant when I said the entry analysis isn't precisely that 7 issue. Because when you have the entry analysis, you have 8 somebody coming in, rather than simply changing ownership. 9 Now, the entry analysis can help you understand that 10 question. The only point I'm making here is, it's not an exact 11 correspondence. That's all I'm trying to say. 12 Q. So you did another econometric analysis, right? 13 A. That's correct. 14 Q. And that's your two firm cross-sectional analysis that's 15 reported in Exhibit Seven, right? 16 A. Yes, I did add that analysis because I thought it would be 17 helpful. 18 Q. And the analysis that you did for Exhibit Seven does not 19 analyze the UPC price data that you had asked the FTC to get 20 and that Whole Foods produced, right? 21 A. No, it did not, because we were interested in looking at 22 Whole Foods, and the data we received for Whole Foods turned 23 out to be quite difficult to use. And at the time of my 24 report, we had not been able to figure out a way to suitably 25 use the Whole Foods pricing data. Linda L. Russo, RPR Official Court Reporter 38 1 Q. So your analysis for that two firm study was based on 2 margin data, correct? 3 A. Yes, it was. 4 Q. All right. Now, the only econometric analysis that you 5 presented in any of your three reports that analyzed the Whole 6 Foods UPC price data that you received, was presented in your 7 third report, the supplemental rebuttal report, correct? 8 A. That is correct. 9 Q. And that analysis looked at Whole Foods prices in North 10 Carolina, correct? 11 A. That's correct. 12 Q. And there are no Wild Oats stores in those North Carolina 13 markets that you looked at, correct? 14 A. That's correct. 15 Q. And Wild Oats has not ever had a store in North Carolina, 16 correct? 17 A. I would believe that's correct, but I'd have to check. 18 Q. Now, I want to talk about the store size issue. You said 19 that you limited your econometric analysis to stores operating 20 under the Wild Oats banner that exceeded 25,000 square feet, 21 right? 22 A. That's correct. 23 Q. And I take it that you think there are 38 of the 71 Wild 24 Oats stores that meet that criterion; is that right? 25 A. I'd have to go back. I don't know the number, to be Linda L. Russo, RPR Official Court Reporter 39 1 honest. 2 Q. You did not exclude stores owned or operated by any other 3 supermarket that were under 25,000 square feet, did you? 4 A. No, I did not. 5 Q. Okay. So you only excluded Wild Oats stores that were 6 under 25,000 square feet from your studies? 7 A. No. We also excluded Whole Foods, I'm sorry. 8 Q. In one of the analyses? 9 A. In the analysis -- I'd have to go back and see which one, 10 but, yes, we did exclude Whole Foods 25,000 square feet. 11 Q. In one study out of the all the studies? 12 A. I don't know. I'd have to go back and double check that. 13 Q. You did say that you had performed some sensitivity test 14 to see whether choosing a different store size cut-off made a 15 difference in the analysis, right? 16 A. Yes, some of which I talked to you about today. 17 Q. And none of the data output from those analyses was 18 produced to defense counsel; isn't that right? 19 A. That is correct. That's my standard operating procedure I 20 use in these types of matters, as well as my academic work. 21 Q. And, in fact, the output from those sensitivity tests 22 analyzing whether store size made a difference was destroyed. 23 It was not preserved; isn't that right? 24 A. I think that would be a correct way to say it. 25 Q. All right. Now, you also imposed a five mile radius or Linda L. Russo, RPR Official Court Reporter 40 1 proximity limit in selecting the stores that you had studied, 2 correct? 3 A. That is correct. 4 Q. And you performed some sensitivity analysis to see whether 5 it mattered if you used three miles or five miles, or some 6 other distance; isn't that right? 7 A. Yes, we did. 8 Q. Those results were not turned over to the defendants 9 either, were they? 10 A. No, actually, for some of those results I believe they 11 were. I believe the results for Exhibit Five contained both 12 the three mile and five mile result, if I recall. 13 Q. Did the results for Exhibit Three or Exhibit Four? 14 A. I don't believe so, no. 15 Q. Those results were not preserved, were they? 16 A. I don't believe so. 17 Q. In your supplemental rebuttal report, you drew circles of 18 six miles radius around each store, and concluded that the 19 union of those circles represented the relevant geographic 20 market, right? 21 A. That was in my report. I can discuss a little bit about 22 what we did. We actually sat down with the maps for each of 23 these areas. 24 THE COURT: He hasn't asked you about it. He just 25 asked you whether you used the six mile radius in the third Linda L. Russo, RPR Official Court Reporter 41 1 report. 2 THE WITNESS: That's fine. Yes, we did. 3 BY MR. FRIEDMAN: 4 Q. And so what I want to know is whether as a result of doing 5 the six mile radius in the third report, did you redo any of 6 the econometric analyses from your July 9th report to fit the 7 geographic market you specified in the supplemental report? 8 A. No. I did it just the other way. This is what I was 9 going to explain. 10 As we went through and drew the market, what I did 11 is, the Federal Trade Commission had proposed a six mile number 12 and so we drew those circles in keeping with what the Federal 13 Trade Commission had proposed. But as we went through market 14 by market, we asked the question, would this still be an 15 overlap market, and would it meet the criteria, and we found 16 that would make anticompetitive effects using a five mile 17 radius at the same time. 18 And my conclusion from going through that is, you 19 come to the same markets whether you use the five or the six. 20 The major difference might be, and I point this out in my 21 report, that sometimes the radius you would use would effect 22 whether stores on the periphery of the region would be included 23 or not. And that would be important mostly in regions that had 24 quite a few stores. For example, Denver, Chicago, where there 25 are multiple stores, and so whether -- there's always overlap, Linda L. Russo, RPR Official Court Reporter 42 1 but whether some additional stores would get included or not 2 might vary. 3 But that's also true for other things. So when we 4 went through the maps, rather than go back and redo all the 5 empirical analysis, I just wanted to make sure the markets we 6 used ended up being consistent with the five mile analysis, and 7 they were. So that's the corroboration I did, rather than go 8 back and redo all the analysis. 9 Q. So let me ask you this, Dr. Murphy. If you turn to tab 1 10 in your binder it has something called Defendant's Exhibit 589. 11 It says at the top, "Wild Oats Store Exit Events." Do you see 12 that? 13 A. Yes. 14 Q. If you go down about midway on the first page, there's an 15 entry for Irvine, California; do you see that? 16 A. Yes. 17 Q. That was a banner entry of a Wild Oats store; is that 18 correct? 19 A. No. This is, I believe this is an exit. 20 Q. I'm sorry, banner exit. You're correct. 21 A. This is an exhibit of a Wild Oats store that's located 22 near the University of Irvine, I believe, and it's about 5.7 23 miles. So it's outside the five mile range. 24 Q. Right. And you testified at deposition that you didn't 25 study the effect of that exit on Whole Foods prices because it Linda L. Russo, RPR Official Court Reporter 43 1 was outside the five mile range, right? 2 A. That's correct. 3 Q. After you changed to a six mile radius, you didn't go back 4 and test the effect of that particular exit on Whole Foods 5 prices, did you? 6 A. I didn't change to a six -- I just explained where the 7 five and six mile numbers came from, and the way in which I 8 worked to make those consistent in terms of my analysis. I 9 didn't change the lens of my econometric analysis to six miles. 10 I have never done that, and I didn't do that. So that's why 11 these guys wouldn't be included. 12 Q. So, Dr. Murphy, in your supplemental rebuttal report, you 13 accepted as appropriate a geographic market that was 14 circumscribed by six mile radii around Wild Oats and Whole 15 Foods stores, correct? 16 A. I said that that led to reasonable -- those led to 17 relevant geographic markets. And they lead to relevant 18 geographic markets precisely because the markets you get are 19 not sensitive exactly to the distance that you use. So whether 20 you use five or six, you're going to get the same markets. And 21 that's the sense to which six miles was an appropriate distance 22 to use. Had there been a different configuration of markets, 23 in some hypothetical world you might have had to address the 24 question of whether five or six made more sense. But in the 25 markets that we had, they led to the same results, so both lead Linda L. Russo, RPR Official Court Reporter 44 1 to acceptable geographic market definitions. 2 Q. Dr. Murphy, you did not study the effect of the Irvine, 3 California, Wild Oats exit on Whole Foods prices, correct? 4 A. I did not. 5 Q. Thank you. You know what a SSNIP test is, right? 6 A. Yes, I do. 7 THE COURT: The court reporter doesn't. Can you 8 spell it. 9 MR. FRIEDMAN: S-S-N-I-P, all caps. 10 BY MR. FRIEDMAN: 11 Q. Dr. Murphy, you've testified that under the Guidelines, 12 product market is defined using the hypothetical monopolist 13 test, right? 14 A. Yes, that's correct. 15 Q. And if you look at paragraph 96 of your report, what you 16 said is that the hypothetical monopolist test asks whether a 17 hypothetical firm that was the sole seller of a given set of 18 products would find it profitable to impose a small but 19 significant, usually five percent, nontransitory price increase 20 in the given set of products, correct? 21 A. You left out some words. You left out the "but not 22 always." Why did you leave that out? 23 Q. You're free to add "but not always," Dr. Murphy. 24 A. It seems like a pretty conspicuous absence to me. 25 Q. Would you like to add "but not always"? Please go ahead. Linda L. Russo, RPR Official Court Reporter 45 1 A. Definitely I would. 2 Q. So I'll read it out loud again. What you testified is 3 that in the hypothetical monopolist test, one asks "whether a 4 hypothetical firm that was the sole seller of a given set of 5 products would find it profitable to impose a small but 6 significant, usually, but not always, taken to be five percent, 7 nontransitory increase in the price of any of those products." 8 Is that what you said? 9 A. Yes, it is. 10 Q. All right. Are you happy now that I said "but not 11 always"? 12 A. Sure. I just wanted you to quote it accurately. 13 Q. I'm happy to do that, sir. Now, you have also testified 14 that nontransitory typically means that the price increase must 15 persist for two years, correct? 16 A. Yeah. Again, it's like anything else. There's no bright 17 line, but that's roughly the time period people are thinking 18 about for nontransitory. 19 Q. And you have also testified that product market definition 20 focuses on the demand side response to a SSNIP, correct? 21 A. That is correct. 22 Q. All right. Now, you have testified that from an economic 23 standpoint other firms compete with Whole Foods and Wild Oats 24 and constrain the prices that either firm can charge for its 25 services, correct? Linda L. Russo, RPR Official Court Reporter 46 1 A. Yeah. I think the best way to put it would be to provide 2 some constraint. We went over this and over this at the 3 deposition, so I think you understand my point on this. 4 Q. I certainly do. Now, you do not have data on the pricing 5 or promotional strategies of all other supermarkets that you 6 listed in your Exhibit Three, correct? 7 A. No, I do not. 8 Q. And, likewise, you don't have data on pricing or 9 promotional strategies of all other supermarkets listed on 10 Exhibit Four, correct? 11 A. That's correct. 12 Q. So it is correct that Exhibit Three does not explicitly 13 hold constant or control for the pricing or promotional 14 strategies of all other supermarkets, correct? 15 A. Nor would you want to, under the Guidelines definition of 16 how you would do the analysis. The Guidelines want to know how 17 those other firms are going to respond in the marketplace. And 18 so you want to look at demand side substitution and the ability 19 of people to substitute. 20 Q. The Guidelines test assumes that a hypothetical monopolist 21 is the sole seller, and therefore controls all promotions and 22 prices of firms in the imperative market, right? 23 A. That's correct. 24 Q. And you in Exhibit Three, and in your econometric analysis 25 make no attempt to control explicitly for whether other Linda L. Russo, RPR Official Court Reporter 47 1 supermarkets change their prices or promotions in response to 2 Whole Foods entry, correct? 3 A. That's correct. 4 Q. Okay. And that's also true for Exhibit Four, right? 5 A. That's also true for Exhibit Four. 6 Q. And it's also true for Exhibit Five, right? 7 A. That would be true for Exhibit Five. 8 Q. Okay. Now, you've also testified that if you have two 9 unique events that happen at the same time, if those events 10 can't be separated, you may not be able to use them, right? 11 A. No. It's not that you can't use them, it's that you can't 12 separate them. Because if you can't separate them, you can't 13 separate them. 14 Q. If you can't separate them, you can't distinguish between 15 which entry event caused the effect, right? 16 A. Not without additional information, no. 17 Q. Okay. Now, in your direct testimony at paragraph 50, you 18 talked about new entry by New Seasons; do you remember that? 19 A. Yes, I do. 20 Q. And what you said in your direct testimony was that "entry 21 by New Seasons actually caused Wild Oats margins to rise." 22 Isn't that what you said? 23 A. That's not what I said. If you read the sentence, the 24 sentence says, "The estimate for New Seasons is positive, 25 suggesting that entry by New Seasons actually causes Wild Oats Linda L. Russo, RPR Official Court Reporter 48 1 margins to rise." 2 Q. And that statement is not a correct statement? 3 A. It is not correct that New Seasons entry caused Wild Oats 4 margin to rise. Notice I didn't use the word "caused." I used 5 the word "suggesting." Let me just explain what it is. 6 What happened at the time that New Seasons entered, 7 they entered the same time that Whole Foods did. So in my data 8 what you find is the combined effect of the two. That's what 9 the data can tell you. Because they came in, in the same 10 quarter, what you're going to measure in the change in sales 11 and in the change in prices is it combined effect of the two. 12 So you can look in Exhibit Number Four, add together 13 the effects of Whole Foods and New Seasons, and that will 14 precisely give you the combined effect. So the combined volume 15 effect, you add together the two sales effects for the Whole 16 Foods and New Seasons. For the margin effect, you add together 17 the same two effects. That's what you can do. 18 Q. It's actually your Exhibit Three. Why don't we take a 19 look at that. 20 A. I'm sorry, Exhibit Three, correct 21 Q. Why don't you take a look at Exhibit Three, which is a tab 22 that's marked Exhibit Three as part of your report. Do you 23 have that in front of you? 24 A. Yes, I do. 25 Q. All right. What you see there is that your chart says Linda L. Russo, RPR Official Court Reporter 49 1 that New Seasons effect on Wild Oats margins when it enters is 2 positive .009, right? 3 A. That's correct. 4 Q. And what you see above it is, you say that Whole Foods 5 effect on Wild Oats margins is .029, right? 6 A. Minus .029. 7 Q. Correct. And what you're telling us is that in the case 8 of the Tualatin, Oregon, entry, both New Seasons and Whole 9 Foods entered in the same quarter, right? 10 A. I believe that's correct. 11 Q. And so the regression that you used doesn't independently 12 estimate the effect of New Seasons entry, correct? 13 A. That's not quite the right way to put it. What the 14 regression does, because there's a single event of New Seasons 15 entry, the regression is going to fit that entry event 16 precisely. And so the sum of those two co-efficients, which 17 would be the minus .029 and the plus .009, which if you add 18 them together you get a minus .020 roughly, that would be the 19 impact on Wild Oats margins of the simultaneous entry of those 20 two firms. 21 Q. Let me try to make it clear for the Court. With respect 22 to entry in Tualatin, Oregon, the effect of entry by Whole 23 Foods and New Seasons at the same time on Wild Oats margins, 24 according to your study, was to depress those margins by two 25 percent, right? Linda L. Russo, RPR Official Court Reporter 50 1 A. That's correct. 2 Q. But what your chart shows, Exhibit Three to your report, 3 shows that New Seasons had a positive effect on Wild Oats 4 margins when it entered, right? 5 A. That's why I used the word "suggested" in my report. 6 That's why, when I went through to explain it, it's very clear 7 what's going on. What happened is, the two firms came in, and 8 prices fell two percent. 9 THE COURT: Whose prices? 10 THE WITNESS: I'm sorry, margins. Margins of Wild 11 Oats fell two percent when the two firms came in. Now, where 12 does the minus .029 effect come from? It comes from all the 13 other cases where Whole Foods entered so. So in other markets, 14 in all the other markets where Whole Foods entered, on average 15 you had a minus 2.9 percent. 16 So what the regressions does is say, look, when Whole 17 Foods comes in, in the other markets, on average I've got minus 18 2.9, here I've got minus 2.0, how do I make up the difference? 19 Well, I assign .009 to New Seasons because that's what's 20 different about the Tualatin, Oregon, event from the other 21 events. 22 So regression is a mechanical exercise. That's 23 exactly what it did. And so what this means is, is that the 24 combined effect was smaller than the typical effect we see for 25 Whole Foods in other markets. Linda L. Russo, RPR Official Court Reporter 51 1 But, actually, what's interesting here, and this was 2 something that came to me as I was working on this, it was 3 quite interesting because the Portland, Oregon, market and that 4 marketplace has a lot of these types of firms already. 5 THE COURT: A lot of which types of firms? 6 THE WITNESS: A lot of PNOS type firms. It has 7 several New Seasons stores, Whole Foods stores, Wild Oats. 8 It's one of the more heavily concentrated markets, not 9 concentrated in the antitrust sense, but in terms of number of 10 firms there, it had lots of competitors. And the fact that you 11 would get a smaller impact in a market that already had lots of 12 people in it makes perfect economic sense. That is, if you 13 have eight firms going to nine, that's not going to be as big a 14 deal in a place as going from two to three, typically. So the 15 fact that you have a smaller effect there actually to me sort 16 of made sense. So that actually makes you think that the -- 17 that adds to the story I think rather than subtracts. 18 THE COURT: Is that because you consider New Seasons 19 to be in the same product market that the Federal Trade 20 Commission says that Whole Foods and Wild Oats says they're in? 21 THE WITNESS: Exactly. This would tend to 22 corroborate that. 23 THE COURT: So you would be surprised if you found 24 the same results if Trader Joes or Safeway entered instead of 25 New Seasons in that same market in the same quarter as Wild Linda L. Russo, RPR Official Court Reporter 52 1 Oats? 2 THE WITNESS: Yeah. You would not necessarily see 3 the same diminution in that case because they might not be as 4 close -- they wouldn't have the same relevance of the 5 additional people already there. I would agree with that. 6 THE COURT: Would not have the same relevance? 7 THE WITNESS: Yeah. 8 THE COURT: And when you say they would not be as 9 close, do you mean geographically closer in terms of the 10 products they offer? 11 THE WITNESS: I would say in terms of the products 12 they're offering. That would be the major difference. 13 THE COURT: So what's important about these 14 paragraphs, paragraphs 50 and 51, in the chart that 15 Mr. Friedman has just been talking about, is that this 16 phenomena discussed here is important because New Seasons is 17 just like Wild Oats and Whole Foods, and is in the same 18 submarket that the Federal Trade Commission argues ought to be 19 the right market for product definition in this case? 20 THE WITNESS: I think that's roughly correct, sir. 21 BY MR. FRIEDMAN: 22 Q. What you have also told us is that when you have 23 simultaneous entry of two firms in the same market, you can't 24 tell what is attributable to Whole Foods entry, and what is 25 attributable to New Seasons entry, right? Linda L. Russo, RPR Official Court Reporter 53 1 A. You would get a minus 2.0 percent for the sum of the two. 2 Q. And likewise in Fort Collins, when you have simultaneous 3 entry of multiple firms, you can't tell what part of the margin 4 effect or price effect is attributable to Whole Foods, and what 5 part is attributable to other entries, correct? 6 A. It depends upon whether the effect of those other entries 7 would be the same in that market that it would be in other 8 places. 9 Q. But if there is simultaneous entry of two firms in the 10 same market that you're looking at, your regression doesn't 11 tell you, doesn't permit you to tell which of the firms is 12 causing how much of the effect, right? 13 A. If you focused on that observation alone, you could not. 14 Q. All right. We talked a little bit about the presence 15 variable. I want to spend a few more minutes on that. The 16 model that you used for Exhibits Three and Four uses a presence 17 variable, correct? 18 A. It uses a presence variable largely because of the 19 econometric specification that we have. 20 Q. So the data that was included in the regressions included 21 both exit and entry events for all firms that were being 22 studied, right? 23 A. To the extent there were exits, they would have been 24 included. 25 Q. And Exhibit Four looked at the effect of banner entry on Linda L. Russo, RPR Official Court Reporter 54 1 Whole Foods margins, correct? 2 A. Exhibit Four, yes. 3 Q. And Exhibit Four does not include a presence variable for 4 Wild Oats, correct? 5 A. No, it does not. Well, whether it included one or not it 6 wouldn't matter because it doesn't vary. Anything that doesn't 7 vary over time wouldn't show up in the regression. That's the 8 important thing to realize, that is, even if Wild Oats is 9 there, if it doesn't change, it doesn't enter, it doesn't exit, 10 then it won't be estimated by the regression. So whether you 11 had a presence variable there or not would have no effect 12 whatsoever. 13 Q. So just to be clear, the data that you studied for Exhibit 14 Four did not include any Wild Oats entry events or any Wild 15 Oats exit events, correct? 16 A. Yeah, because they didn't incur within my sample. 17 Q. Okay. Now, there have been a number of Wild Oats exits 18 under 25,000 square feet within five miles of a Whole Foods, 19 and you didn't include those in your sample, right? 20 A. That's correct. 21 Q. And there were a number of Wild Oats exits that were 22 greater than 25,000 square feet, but more than five miles away 23 from Whole Foods, and you didn't include those in your sample 24 either, right? 25 A. Well, there are obviously a number of events. If you Linda L. Russo, RPR Official Court Reporter 55 1 don't put any limit on distance, I guess all of them were exit 2 events at some distance from a Wild Oats store. The question 3 is, is how many were there going out further. For example, you 4 use the six mile criteria, I believe there was one, which was 5 the Irvine store. 6 Q. And you didn't include Irvine in your data set, right, for 7 Exhibit Four? 8 A. Well, let me tell you what's going on here. 9 Q. Can you answer my question? 10 A. I did not. 11 Q. Thank you. Now, Fort Collins was an exit within five 12 miles of Whole Foods, and it was greater than 25,000 square 13 feet, right? 14 A. Yes, but given the data we had, we didn't have any data 15 for the post period, so we couldn't estimate an exit effect 16 when we didn't have the margin data for the full quarter 17 subsequent to the exit. 18 Q. You didn't include Fort Collins in the data set for 19 Exhibit Four, correct? 20 A. The exit event wouldn't be included. The exit event would 21 not be included, although the Fort Collins Whole Foods store 22 would be included. 23 Q. All right. Now, I'm going to switch to one of our 24 favorite subjects. 25 THE COURT: There is some mention of Fort Collins. Linda L. Russo, RPR Official Court Reporter 56 1 Well, I guess that's in a different context in paragraphs 58 2 through 59, I guess, and maybe through -- 3 THE WITNESS: I believe that's the entry event where 4 the Whole Foods store entered in competition with the Wild Oats 5 store. And what we're referring to now is the subsequent exit 6 of the Wild Oats store that occurred I believe in late 2006. 7 MR. FRIEDMAN: Let me see if I can clarify it with a 8 question or two. 9 THE COURT: But you also say in paragraph 59, it is 10 noteworthy that the Fort Collins Wild Oats store was closed in 11 December of 2006. 12 THE WITNESS: That's correct. But because we didn't 13 have a full quarter's worth of margin data for the Whole Foods 14 store after the date of exit, we couldn't analyze that exit 15 event. We knew it occurred, but we need the post data in order 16 to analyze the exit event. 17 THE COURT: So it's worth noting, but there's no data 18 that helps figure out what it means. 19 THE WITNESS: It was worth noting. If you go through 20 the context here, we're talking about the size of the reduction 21 in price, and the size of the reduction in sales, and so the 22 note there is they said a very substantial reduction in price, 23 they had a very substantial reduction in sales. And guess 24 what? They ended up leaving. So that's what we meant by the 25 noteworthy that, you know, they had sustained quite a bit of, Linda L. Russo, RPR Official Court Reporter 57 1 you know, loss in both the price -- in both the margin and 2 sales dimensions. And it wasn't -- therefore, that's 3 surprising as an economic matter that maybe they might exit. 4 BY MR. FRIEDMAN: 5 Q. Just so we're clear, you did study the effect of Whole 6 Foods entry in Fort Collins within five miles of Wild Oats on 7 Wild Oats, right? 8 A. That's correct. 9 Q. And you noted Wild Oats exit from that location, but in 10 your reports, the three reports, you did not study the effect 11 of Wild Oats exit on Whole Foods prices, correct? 12 A. That's correct, and there are a number of reasons why, of 13 which I just mentioned one. 14 Q. So we are now going to switch to, hopefully briefly, one 15 of your and my favorite subjects, the subject is shrink. 16 A. Regular shrink or partial shrink? 17 Q. We're going to talk about both kinds of shrink. 18 S-h-r-i-n-k. 19 Now, Dr. Murphy, shrink is product that is lost that 20 does not go out for sale, right? 21 A. I guess now we're talking not about partial shrink, we're 22 talking about regular shrink? 23 Q. That's right. 24 A. Yeah, regular shrink is generally regarded as product that 25 does not fetch the price, it doesn't go out for sale. Linda L. Russo, RPR Official Court Reporter 58 1 Sometimes it's theft, sometimes it's spoilage, sometimes it's 2 breakage. It could be any of those things. 3 Q. And shrink may be expected to rise after significant 4 competitive entry, right? 5 A. It can. It doesn't have to, but it can. 6 Q. You have testified that shrink may be expected to rise 7 after significant competitive entry, right? 8 A. Yes. It's just the "may" part you have to keep in mind 9 because there are forces working in the other direction. 10 Q. And you deducted in your analysis of margins, you deducted 11 the impact of shrink on margins before you ran your 12 regressions, right? 13 A. Yes. 14 Q. And you know that in this case Mr. Martin from Wild Oats 15 has submitted a supplemental declaration. Are you aware of 16 that? 17 A. I don't recall that off the top of my head, no. 18 Q. Well, let's turn to tab 2. It's right there. Do you have 19 that in front of you? 20 A. Yes. 21 Q. Mr. Martin says in paragraph 6, Mr. Martin is the Senior 22 Vice President of Operations for Wild Oats and has 23 responsibility for loss prevention, including management of 24 shrink; do you see that? 25 A. Yeah, he got the same three reasons I did. That's good. Linda L. Russo, RPR Official Court Reporter 59 1 Q. Is that a yes? 2 A. Yes. 3 Q. So maybe you read it and you just didn't remember. 4 A. No. I think I remember from my supermarket days. 5 Q. Were you a bagger? 6 A. No. Actually, I started that. I started sorting Coke 7 bottles, made my way up to bagger, checker, eventually quite a 8 bit higher. 9 Q. We'll talk about that after you leave the stand. So 10 Mr. Martin says in paragraph six that Wild Oats accounts for 11 known shrink, "which includes items that are wholly spoiled or 12 completely damaged;" do you see that? 13 A. Yes. 14 Q. Mr. Martin also says in paragraph three that "partial 15 shrink occurs when a product is not lost, but is substantially 16 discounted for sale;" do you see that? 17 A. Yes, that's what he says. 18 Q. And Mr. Martin says in paragraph four that Wild Oats does 19 not assign a new universal product code, or product look up 20 identifier to partial shrink items, except involving bags of 21 distressed bananas; do you see that? 22 A. Yes. 23 Q. In paragraph five, Mr. Martin says that Wild Oats has no 24 uniform policy or practice regarding treatment of partial 25 shrink items; do you see that? Linda L. Russo, RPR Official Court Reporter 60 1 A. I'm trying to read what he says. Okay. 2 Q. So let's suppose I want to remove the effect of partial 3 shrink from the margin calculation. If the cost of goods sold 4 is not adjusted for partial shrink, you're not able to remove 5 the effect of partial shrink from your margin calculation, 6 right? 7 A. I would believe that's true by definition, yes. 8 Q. Where there is partial shrink because perishables get old 9 and the UPC code is not changed, part of the mark-down in price 10 reflects a reduction in quality that is unobserved by you for 11 that UPC code, correct? 12 A. It may. 13 Q. Your margin analysis only removed what you referred to as 14 the mechanical effect of known and recorded shrink, correct? 15 A. It removed the shrink as had been reported to us by the 16 parties. 17 Q. And so it didn't remove shrink that was unknown to you, 18 right? 19 A. No, I only could remove what they gave us. 20 Q. And you testified previously that it is probable that you 21 would get a different measure of margins if you do not take out 22 the effect of partial shrink than if you do? 23 A. At any individual point in time you would get a different 24 measure of a margin. Assuming you take something out from the 25 margin you did measure, the measure you get would be different. Linda L. Russo, RPR Official Court Reporter 61 1 Q. Now, you testified previously that you would expect the 2 rise in partial shrink that accompanies competitive entry to 3 last only a few months, right? 4 A. I think that's possible. 5 Q. Now, Mr. Martin says in his declaration at paragraph seven 6 that the partial shrink problem persisted in Hartford, 7 Connecticut, for over 18 months after Whole Foods entered; do 8 you see that? 9 A. That's his one example. I don't know why he picked that 10 particular example. 11 Q. Well, he did. And you see that there, don't you? 12 A. Okay. Paragraph seven, "While in principle the increase 13 in known and unknown shrink should have been short-lived, six 14 to eight weeks," I think that's in line with what I had said, 15 "Wild Oats has found that it is very hard to get its store 16 managers to adjust their order rates downward after a rival 17 enters because the managers typically have an over-optimistic 18 expectation that sales will bounce back. For example, at our 19 store in West Hartford, Connecticut, it took over 18 months to 20 get order rates into alignment with actual sales and I had to 21 threaten to fire that store manager to get him to fix his order 22 practices to adjust for shrink." 23 Q. Now, you have both seen it and read it for the record. 24 Thank you. In paragraph eight you see that Mr. Martin 25 estimates that Wild Oats' partial shrink -- I'm sorry, its Linda L. Russo, RPR Official Court Reporter 62 1 unknown shrink, including partial shrink, is much larger than 2 known shrink; do you see that? 3 A. Yeah, okay. 4 Q. And the known shrink in Hartford for the first quarter of 5 2007 was six and a half percent; is that right? 6 A. I don't remember that number off the top of my head. 7 Q. But you did look at what the known shrink was in the 8 markets that you studied, right? 9 A. We took it out of the analysis, yes. 10 Q. And so if I represent to you that the known shrink in 11 Hartford in the first quarter of 2007 was six and a half 12 percent, and the known shrink in Portland, Maine, in the first 13 quarter of 2007 was four and a half percent, and in Tualatin, 14 Oregon, it was seven and a half percent, you took that amount 15 of known shrink out of the margin analysis, correct? 16 A. That's correct. 17 Q. And if Mr. Martin is correct that the amount of unknown 18 shrink is at least as large as that, and if we wanted to take 19 the partial shrink out, then we would be taking out of the 20 margin analysis a like amount, correct? 21 A. First of all, it's not clear why -- partial shrink is 22 different than regular shrink. In the case of regular shrink, 23 consumers receive no product in exchange, so taking that out 24 would be something you would want to do because there's no 25 product being sold. Linda L. Russo, RPR Official Court Reporter 63 1 In a case of something like partial shrink where you 2 have a mark-down, even when you take a mark-down, typically the 3 quality adjusted price will actually still go down. That's how 4 you expect to move it faster because if you didn't lower the 5 quality adjusted price, it wouldn't move fast. So there is a 6 price reduction even in the cases if you had partial shrink, so 7 you wouldn't want to take all of it out even if you had the 8 data to do so. 9 Q. But you've taken some of it -- 10 A. No. Remember, the distinction between partial shrink and 11 regular shrink is the consumer gets the product in the partial 12 shrink case. Let me give you an example. Let's say I'm 13 running the produce department and I see I got too many apples, 14 and so I mark them down. I say instead of 69 a pound, I'm 15 going to make them 59 a pound because I want to get rid of 16 them. When you're running a produce department, if you want to 17 get rid of stuff, it's better to mark it down before it gets 18 old than when it is old because people like new stuff and not 19 old stuff. So part of what would be taken in mark-downs 20 doesn't have necessarily a quality, corresponding quality 21 adjustment. Even if there is some quality adjustment, 22 typically a quality adjusted price will fall because you're 23 trying to get rid of on it. If you didn't lower the quality 24 adjusted price, you couldn't get rid of it. 25 Q. Dr. Murphy, in your deposition I asked you the following Linda L. Russo, RPR Official Court Reporter 64 1 question, and you gave me the following answer: 2 Question: But this is a price response that is because 3 the goods are getting old, because the traffic in the store is 4 not as great, it's not a competitive price response to 5 discounting. 6 Answer: That would be part of what's going on in 7 there, but there would also be part of that response that would 8 be a response to competition. 9 That was your testimony at your deposition, correct? 10 THE COURT: Wait a second. There's an objection. 11 Your lawyer is objecting. 12 MR. BLOOM: Improper impeachment. There's no 13 inconsistency in the testimony. 14 THE WITNESS: It's fine because -- 15 THE COURT: He wants to answer the question. 16 THE WITNESS: If you go back to my deposition, you 17 asked me these questions like 97 times, and I answered. And 18 you're going to read back one of these answers. If somebody 19 wants to know what my thinking is, I'll tell them now, you can 20 read all 97 answers, but I'm telling you the same thing all the 21 time. We go round and round, and I'll use different words 22 different times, but the message is the same. 23 BY MR. FRIEDMAN: 24 Q. Dr. Murphy, the question in front of you was, was that 25 your testimony at your deposition? Yes or no? Linda L. Russo, RPR Official Court Reporter 65 1 A. It was one of my 97 answers. 2 Q. Was that your testimony at your deposition? 3 A. Yes, it was. 4 Q. Thank you. 5 THE COURT: Are you moving on to another topic? 6 MR. FRIEDMAN: I am moving off of shrink. 7 THE COURT: Because I want to ask a question which 8 may be going back to something we discussed earlier. And maybe 9 when I ask it, Dr. Murphy will tell me that for lack of a 10 better term I'm by this question asking to compare apples and 11 oranges. 12 But you said a moment ago, you don't understand why 13 Mr. Martin focused on West Hartford in discussing this topic. 14 I guess my question goes back to paragraphs 58, 59, 60, and 15 Exhibit Five which do focus on two markets, West Hartford, the 16 same West Hartford, Connecticut, and Fort Collins, Colorado, 17 which, as we know, came and went. And maybe it suggests my 18 lack of understanding about the kind of analysis that we're 19 talking about, but are you in this analysis extrapolating the 20 conclusions across the board to these 18 markets that are at 21 issue in this case from these two markets, even though there 22 may be other variables in other markets that might effect 23 pricing or advertising, or a whole bunch of things that might 24 have some sort of an impact on the conclusions that you seem to 25 draw? Why are we focusing on those two markets, other than the Linda L. Russo, RPR Official Court Reporter 66 1 fact that we happen to have information about those two 2 markets, although apparently not complete information about 3 Fort Collins, and are we drawing very broad conclusions about 4 18 markets from these two? 5 THE WITNESS: No. First of all, when we do, for 6 example, Exhibit Three or the other exhibits where we're doing 7 the margin analysis, we had the margin data for a longer period 8 of time, so we were able to look at a broader range of events 9 in the margin data than we could in the price data where the 10 tile period was more truncated. 11 First of all, we have the margin data, we're able to 12 look at a broader mix of markets. In the case of Wild Oats 13 price data, there were five markets that we could look at 14 simply because of the duration of the data. Those five markets 15 are also included in the margin analysis. But for the price 16 analysis, because of the time period available, we only had 17 five to start with. 18 Again, because we had this truncated period of data 19 availability, what happened is, most of the events run up 20 against the end. So, for example, if you look at Exhibit Five, 21 you'll see the five events, some of which we can follow for the 22 first six months, some of them we can follow into months seven 23 to 12, some of which, only two of which we can follow into 24 months 13 and beyond. That's for the price data because of the 25 truncated availability. And that's why those two were Linda L. Russo, RPR Official Court Reporter 67 1 highlight in that particular study. 2 But the analysis we do covers a broader range of 3 markets, albeit with the margin data, as opposed to the pure 4 price data. Then with the data we use, now that we have the 5 Whole Foods data, what format we can use, we did the North 6 Carolina study, which again looks at, in this case Whole Foods 7 prices, and using the time frame available for Whole Foods. 8 And we have been able to do that same thing for the Colorado 9 area as well. 10 THE COURT: Okay. I'm done for the moment. 11 BY MR. FRIEDMAN: 12 Q. I'm going to move to Exhibit Five just to follow up on 13 what you said, Dr. Murphy. Exhibit Three, just so we're clear, 14 studies the impact of banner entry of various firms on Wild 15 Oats' margins and sales, correct? 16 A. Yes. It's also informative about Whole Foods. 17 Q. In Exhibit Four -- 18 A. No, Three is as well. 19 Q. I'm talking about Exhibit Four now. I'm asking you a 20 fresh question. Exhibit Four studies the impact of banner 21 entry of various firms on Whole Foods, correct? 22 A. That would be correct. 23 Q. And it looks at the effect on Whole Foods margins and 24 sales, correct? 25 A. That would be correct. Linda L. Russo, RPR Official Court Reporter 68 1 Q. And you have sought to infer from the margin results that 2 you got from Exhibits Three and Four price estimates, correct? 3 A. They would imply price estimates, yes. 4 Q. Okay. But you don't have in the study of Exhibit Four an 5 assessment of the effect of Wild Oats banner entry, or Wild 6 Oats banner exit, on Whole Foods margins or sales, correct? 7 A. That's correct. 8 Q. So then we go to Exhibit Five. And Exhibit Five studies 9 the effect of Whole Foods banner entry on Wild Oats prices, 10 right? 11 A. That's correct. 12 Q. So one of the differences between Exhibit Three and 13 Exhibit Five is, Exhibit Five is actually studying prices from 14 price data that you received from Wild Oats, correct? 15 A. That would be one of the differences, yes. 16 Q. And another difference is that Exhibit Five is looking 17 only at the effect of Whole Foods banner entry on Wild Oats 18 prices, right? 19 A. Well, we're controlling for other things, but what's being 20 presented in there is the results for Whole Foods. 21 Q. And you say you're controlling for other things, but the 22 regression that you used in Exhibit Five does not explicitly 23 control for third party pricing behavior, right? 24 A. It controls for the presence of third parties. 25 Q. But it doesn't explicitly control for third party pricing Linda L. Russo, RPR Official Court Reporter 69 1 behavior, right? 2 A. That's correct. 3 Q. Okay. And that means that any third party responses that 4 effected Wild Oats prices or sales are captured as an effect of 5 Whole Foods entry, correct? 6 A. Any responses to the Whole Foods event would be captured, 7 yes. 8 Q. Now, we're just working so well together because that was 9 my next question. You have testified that new entry by another 10 firm that is independent of Whole Foods entry should not be 11 included in that total effect that you want to capture, right? 12 A. It wouldn't be, unless you considered the entry response. 13 If the entry was considered a response, you'd probably want to 14 include it, certainly for competitive effects analysis. 15 Q. But if -- 16 A. If that was an exogenous event, to use the term economists 17 use, that is something that occurred independent of the Whole 18 Foods entry, you would not want to -- you'd want to separate 19 that out. 20 Q. And if we use the word "independent" which lawyers use, 21 instead of "exogenous" which economists use, you're okay with 22 that? 23 A. I'll try to be. 24 Q. We appreciate that. 25 THE COURT: But you just said you did control for the Linda L. Russo, RPR Official Court Reporter 70 1 presence of third parties, but Dr. Scheffman criticizes your 2 analysis for not having control group stores in doing the entry 3 analysis in Exhibit Five, or, I think that's what he said, or 4 if he didn't say that, he said or in selecting control group 5 stores that are not similar or in any way like the stores, or 6 like the locations of the Wild Oats or Whole Foods, I can't 7 remember which stores that were examined. 8 THE WITNESS: No, actually, in terms of the control 9 groups, what we presented there was one particular set of 10 control groups. What we actually did was three different sets 11 of control groups, going from the broadest down to the 12 narrowest set of controls. We used the control groups that we 13 used there, which is the region variable from the Wild Oats 14 data. We also used a price zone variable to do controls. And 15 we also used controls that were suggested by CRA, who was the 16 economic consulting group used by the defendants, who had 17 suggested a set of controls. We used their controls. All 18 three sets of results were turned over to the defendants in 19 this case. 20 And my reading of those results is no appreciable 21 difference between the different set of controls in terms of 22 the relevant outcomes shown in the table. So it was robust 23 with respect to those different controls. 24 BY MR. FRIEDMAN: 25 Q. Let me stay with that for a minute because there's a Linda L. Russo, RPR Official Court Reporter 71 1 difference between control stores and controlling for 2 independent entry. The fact of the matter is that in the 3 regression that was run in Exhibit Five, the regression does 4 not control for independent entry by another firm, correct? 5 A. No, it does. We presented results both ways. 6 Q. Let me read to you from your testimony, page 250 beginning 7 at line 11, to page 251 at line 1. 8 MR. BLOOM: Can I have a copy of that testimony? 9 THE COURT: Sure. Just a second while Mr. Bloom 10 looks at the transcript. 11 MR. BLOOM: What page are you on? 12 MR. FRIEDMAN: 250. 13 BY MR. FRIEDMAN: 14 Q. I'm just going to read it to you. 15 "Question: Okay. And so in your analysis of Fort 16 Collins I take it that entry by King Sooper within five miles 17 of Wild Oats at about the same time as the Whole Foods entry is 18 part of the totality of the effect that you would capture in 19 this exhibit; is that right? 20 "Answer: If King Sooper enters during that period of 21 time, that would be -- unless we think that that is linked to 22 the entry of Wild Oats, if that's an independent event that was 23 not a response to the entry of Whole Foods, then no, that would 24 not be something that would be captured in what I would call 25 the -- would be captured in what I would call the total effect Linda L. Russo, RPR Official Court Reporter 72 1 we're trying to measure. 2 "Question: And how did you control for that in your 3 regression in Exhibit Five? 4 "Answer: In Exhibit Five, that would not be 5 controlled for." 6 That was your testimony, wasn't it? 7 MR. BLOOM: If I may, that was quite a mouthful. I 8 think it would be helpful if Dr. Murphy had it in front of -- 9 had the document in front of him to look at. 10 THE COURT: That's fine. 11 MR. BLOOM: May I approach? 12 THE COURT: Yes, Please. 13 MR. BLOOM: Thank you. 14 BY MR. FRIEDMAN: 15 Q. It begins on line 11 on page 250, Dr. Murphy. 16 A. Yes, I believe I actually probably misspoke there. I 17 think I forgot which of the results we had actually put in the 18 table. In the material we turned over to the defense, we had 19 the simple differencing approach, as well as the controlled 20 approach, and I believe the results in the table actually are 21 the ones. So we did it many different ways. I think the one 22 that's in the table is the one that controls. It doesn't make 23 a significant difference one way or the other, so whether you 24 did that or not would not effect materially your results. 25 I believe actually that I misspoke in my deposition. Linda L. Russo, RPR Official Court Reporter 73 1 I think that actually that the ones in the paper, or in the 2 report, are actually the ones with controls. But as I said, it 3 doesn't matter significantly for the results. 4 Q. Well, let me ask you this, whether it matters 5 significantly or not. If two firms enter, independent of each 6 other at the same time, and you do not have a control in the 7 regression for the new entry by the second firm, that's going 8 to effect the impact you show as a result of your regression 9 analysis, isn't it? 10 A. Whether it does or not is an empirical question. What I'm 11 saying is, we don't have to speculate. We have the answer to 12 that empirical question, which is, whether you control or not 13 doesn't make a difference. So I don't know how else to say it, 14 other than that. 15 Q. So tell me this. You studied the impact of Whole Foods 16 entry on Wild Oats prices in, for example, Hartford, 17 Connecticut, correct? 18 A. That's correct. 19 Q. And you used Wild Oats pricing data, correct? 20 A. That's correct. 21 Q. You did not conduct a study of the effect on Wild Oats 22 prices using Wild Oats pricing data of the entry of Trader Joes 23 in Hartford, Connecticut, in the same period, did you? 24 A. You could back it out from the regression. We didn't 25 present it in that table. Linda L. Russo, RPR Official Court Reporter 74 1 Q. You did not conduct a separate study of the effect of 2 Trader Joes entry in Hartford, Connecticut, on Wild Oats 3 prices, correct? 4 A. No, I did not. 5 Q. And, in fact, what you present as an effect on Wild Oats 6 prices is the aggregate effect on Wild Oats prices, just like 7 in Tualatin when you had New Seasons and Whole Foods entering 8 at the same time; isn't that right? 9 A. No, that's not correct. 10 Q. Now, let's talk about Hartford for a minute. Hartford, 11 you don't have two years of post entry data, correct? 12 A. Yeah, I believe there's 17 months -- 19 months. Which one 13 was it? 14 Q. It was 19 months. And your study shows the price effect 15 in Hartford declines with time, right? 16 A. It declines over some periods, yes. 17 Q. Well, it declines, if you look at your table five, you 18 show that after six months the price effect was negative 2.9 19 percent in Hartford, in the 7 to 12 months period it was 2.2 20 percent. That's a decline, right? 21 A. Yeah. Ignoring sign, yeah. 22 Q. Pardon me? 23 A. Ignoring sign. 24 Q. In the third period the price effect was negative 1.1 25 percent, right? Linda L. Russo, RPR Official Court Reporter 75 1 A. That's correct. 2 Q. So in each period the price effect was lessening, correct? 3 A. That's the point estimates, yes. 4 Q. And those are your estimates, right? 5 A. Yes, they are. 6 Q. And you recall that Mr. Martin's supplemental declaration 7 noted that it took 18 months to get the shrink problem under 8 control in Hartford; do you remember that? 9 A. That's correct. 10 Q. Now, you've talked about outliers in connection with the 11 UPC data that Whole Foods produced to the Federal Trade 12 Commission, correct? 13 A. That's correct. 14 Q. And an outlier is, for example, some sort of idiosyncrasy 15 in price data? 16 A. Generally, an outlier is thought to be an observation in a 17 data set that's not really representative of the overall 18 picture. 19 Q. And so when you worked with Whole Foods price data, what 20 you ended up doing with outliers was, you masked the effect of 21 the outliers, right? 22 A. We tried -- I would think it more like filter out the 23 effect of the outliers. 24 Q. Fair enough. And you had about, outliers that accounted 25 for about 10 percent of the sales in the Whole Foods data, Linda L. Russo, RPR Official Court Reporter 76 1 right? 2 A. That would be roughly correct. 3 Q. Did you check for outliers in the Wild Oats data? 4 A. I remember going through and looking at the data, although 5 I don't recall there being a specific outlier problem there. 6 Q. Did you notice any outliers or idiosyncrasies in the 7 Hartford Wild Oats data? 8 A. I don't know if it was in Hartford. There were a couple 9 of strange observations that we found. I think we found a beer 10 coupon, I remember. I think that was in the Wild Oats data, 11 that you pay $45 extra for a case of beer, or something like 12 that. It was a very strange observation. That's the one that 13 I remember. I remember going through the data and looking at a 14 few odd observations. That's the one that never made any sense 15 to me. 16 Q. So did you know that -- 17 A. It seemed like a good coupon to get in the mail at the 18 time. 19 Q. We're going to move from the sublime to something else. I 20 think we're going to move from beer to salad bar. 21 A. Okay. 22 Q. Did you observe in the Hartford Wild Oats price data any 23 idiosyncrasies in the pricing for salad bar? 24 A. I don't recall. 25 Q. Did you know that if you simply filter out the salad bar Linda L. Russo, RPR Official Court Reporter 77 1 UPC from the Hartford data that you studied from the 2 regression, the price effect in the last period becomes 3 seven-tenths of one percent instead of 1.1 percent, just by 4 that one filtering out the UPC code? 5 A. You have to be very careful. I mean, we were very careful 6 in the analysis we did for Whole Foods to make sure we trimmed 7 out both sides that are both positive and negative. It's easy 8 to move estimates around by selectively choosing one side or 9 the other. What was nice about what we found in the Whole 10 Foods data when we filtered was the uniformity of the filtering 11 and the symmetry of the filtering, which really gave me 12 confidence that what we were taking out was noise. 13 When you selectively take out noise, you don't 14 necessarily make the world better. You could make the world 15 worse. So when you tell me about removing a single 16 observation, you really want to focus on, if I have a 17 systematic rule for moving observations one side or the other, 18 how does it move things. Because I can tell you for sure on 19 most datas that you have, if you go through and say I'm going 20 to cut out the lowest negative observations, it's going to make 21 a difference. But that's not a valid statistical procedure. 22 If you're going to filter noise, you want to filter both ends. 23 And what we found in the Whole Foods data was that the 24 filtering was very uniform. 25 Q. So let me ask you to answer the question that I asked you. Linda L. Russo, RPR Official Court Reporter 78 1 Did you know that if you simply filter out the UPC code for 2 salad bar from the Hartford data, then the price effect that 3 you get in the last period that you're studying drops from 1.1 4 percent to seven-tenths of one percent; did you know that? 5 A. I did not know that. 6 Q. All right. Now, you've testified that the effect of Wild 7 Oats exit, that you expect the effect of Wild Oats exit to be 8 somewhat smaller than the effect of Whole Foods entry, owning 9 to the greater size of Whole Foods in overlap markets, right? 10 A. That would be true. 11 Q. I'm going to switch briefly to talk about your Exhibit 12 Seven, that cross-sectional analysis. 13 THE COURT: Just a second, Mr. Friedman. 14 MR. BLOOM: Your Honor, we've been going quite a 15 while. I wonder if this is an appropriate time for a break. 16 THE COURT: Let me ask Mr. Friedman two questions. 17 One is how much longer you're going to be, and secondly, is any 18 portion of what you're going to do, going to require us to go 19 into closed session? 20 MR. FRIEDMAN: I'll answer the second question first. 21 I hope we will not need to go into close session. And with a 22 little luck, I'll be done in ten minutes. 23 THE COURT: Okay, we will rely on luck. 24 BY MR. FRIEDMAN: 25 Q. Dr. Murphy, we will rely on your good efforts as well. Linda L. Russo, RPR Official Court Reporter 79 1 A. Nothing but. 2 Q. I expect nothing less, sir. So your third econometric 3 study purports to study how margins might change for Whole 4 Foods stores with exactly one Wild Oats, but no other Whole 5 Foods store within five miles, right? 6 A. You used the word "change" but you only had a predicate, 7 as opposed to a beginning and an end. 8 Q. I must have written the question badly. Let me try it 9 again. Your hypothesis is that Whole Foods stores with exactly 10 one other Whole Foods store, but no Wild Oats store within five 11 miles, reflects what would occur after a change of ownership in 12 Whole Foods, Wild Oats locales would both stores continue to 13 operate; is that right? 14 A. Yeah. The difference between those two would reflect the 15 change, I think is probably the best way to put it. 16 Q. This is probably my second most favorite topic to discuss 17 with you. At the store level, you came up with a result, 18 looking at the margin analysis that is not statistically, 19 significantly different from zero, correct? 20 MR. REILLY: Objection. Vague and ambiguous. 21 THE COURT: Why don't you rephrase it. 22 BY MR. FRIEDMAN: 23 Q. I'll rephrase it. At the store level, you came up with a 24 result that is not statistically significantly different from 25 zero at the five percent level, correct? Linda L. Russo, RPR Official Court Reporter 80 1 A. That I believe would be correct. 2 MR. FRIEDMAN: Thank you for your objection. 3 BY MR. FRIEDMAN: 4 Q. Are you familiar with the Federal Judicial Center's 5 reference manual on scientific evidence? 6 A. Yes, I am. 7 Q. And had you reviewed it before your work in this case? 8 A. Not specifically for this case, but I have read it before. 9 Q. All right. And at page 194 the Federal Judicial Center's 10 Reference Guide on Multiple Regression, states that in most 11 scientific work, the level of statistical significance required 12 to obtain a statistically significant result is set at five 13 percent. Do you agree with that statement? 14 A. I would agree. That's probably standard. 15 Q. And the Federal Judicial Center notes that a more 16 stringent test of one percent is sometimes applied and can 17 provide useful information. Do you agree with that statement? 18 A. Yeah, depending what you're interested in showing, yes. 19 Q. And the Federal Judicial Center also speaks of a less 20 stringent 10 percent test that can provide useful information. 21 Do you agree with that? 22 A. I believe that would be the case. 23 Q. The Federal Judicial Center Reference Guide on Multiple 24 Regression does not discuss the usefulness of a 15 percent 25 test, does it? Linda L. Russo, RPR Official Court Reporter 81 1 A. I never proposed a 15 percent test. 2 Q. And it doesn't discuss a 16 percent test either, does it? 3 A. No, it does not. 4 Q. And it doesn't discuss a 17 percent test, does it? 5 A. No, it does not. 6 Q. Now, you report in addition to a result, a margin 7 difference that is not statistically significantly different 8 from zero at the five percent level. You report something 9 called a P-value, right? 10 A. That's correct. 11 Q. For example, the letter "P" as in "Paul." 12 A. Yes. 13 THE COURT: For example. 14 BY MR. FRIEDMAN: 15 Q. Just for example. 16 A. Yes, I do present a P-value. 17 Q. And you report a P-value of .1625, right? 18 A. That's correct. 19 Q. Now, the Federal Judicial Center says that the P-value is 20 the probability that a co-efficient of the magnitude that 21 you've come up with, or larger, could have occurred by chance 22 if the null hypothesis were true; do you agree with that 23 statement? 24 A. Yeah, as long as you recognize that that's a two-tail 25 test, so it's the chance that you would get something either Linda L. Russo, RPR Official Court Reporter 82 1 positive or negative of that absolute value. 2 Q. And you conducted a two-tail test here, didn't you? 3 A. No. I reported a two-tail P-value. 4 Q. Very well. And so what that means is, if the true 5 difference in margins was zero, the P-value is the probability 6 that you would get a result as great or greater than what you 7 got in this case by chance, right? 8 A. You got to be careful because that's a two-tail test, 9 where the alternative hypothesis is implicitly in either 10 direction. This particular case I believe would be one where 11 the alternative hypothesis would be the null being no effect 12 against there being a negative co-efficient, which means -- no, 13 it's important to realize, so when they provide this .16 14 probability, or roughly one in six chance of getting something 15 at least this big, it means there's only a one in 12 chance 16 that you would get something this negative by chance. And 17 that's probative in this case where the alternative hypothesis 18 is zero versus negative. 19 Q. Let me -- 20 A. That's all I'm trying to say. What that amounts to, and 21 this is what I said in my report, and it's what I said in my 22 deposition, the way you want to interpret that, it's a one in 23 12 chance of getting something this negative simply by chance. 24 Q. Let me go back to what the reference guide on multiple 25 regression says, published by the Federal Judicial Center. It Linda L. Russo, RPR Official Court Reporter 83 1 says, small P-values like .05 argue for the plaintiff because 2 there is a relatively low probability that the result is due to 3 chance; do you agree with that statement? 4 A. Yeah. 5 Q. And, conversely, the Federal Judicial Center, actually 6 this is on the -- I misspoke, it's on the Federal Judicial 7 Center's Reference Guideline Statistics, on page 122. It says, 8 conversely, large P-values argue for the defense because 9 there's a relatively greater probability that the result is due 10 to chance; do you agree with that statement? 11 A. I agree, but you don't have to use the imprecise words of 12 small and large. The P-value is what it is. It's interesting, 13 when you run a regression, and the regression outputs the 14 value, you notice they put the P-value there. They don't, 15 like, put a star if it's significant at the five percent level. 16 They print out the P-value, because that's, if you're trying to 17 say what did I get, that tells you what you got. And to say 18 that there's a bright line and you're going to go one way or 19 the other, you just want to interpret the evidence as what it 20 is. 21 Q. Let me ask you a question. 22 THE COURT: Mr. Bloom is standing for some reason. 23 MR. BLOOM: I do not have the courtroom copy of the 24 reference manuals that are being discussed. I would appreciate 25 an opportunity to subsequently look at these, and if there is Linda L. Russo, RPR Official Court Reporter 84 1 material that ought to come in under the Rule of Completeness, 2 to have the opportunity to put that material into the record. 3 MR. ATKINS: I'll be happy to share them with 4 Mr. Bloom. I would note that they're cited in the government's 5 response brief, but I will let him look at my copy on the 6 break. 7 THE COURT: Just so we are clear, you have been 8 referring to two different Federal Judicial Center books. 9 MR. FRIEDMAN: It's one publication. There's 10 separate chapters. If Your Honor were to go on-line, I can 11 provide the -- 12 THE COURT: One is called the F.J.C. Manual on 13 Scientific Evidence, which I have a copy of in my chambers, but 14 then you said the F.J.C. Reference Guide on Statistics. Is 15 that a part on the Manual on Scientific Evidence, or is it a 16 different book? 17 MR. FRIEDMAN: Those are both parts of the Manual on 18 Scientific Evidence. It's the Reference Guide on Multiple 19 Regression, begins at page 179, and the Reference Guide on 20 Statistics begins at page 83. 21 MR. BLOOM: Your Honor, if I may, it may be somewhat 22 difficult for me to penetrate this material during the break. 23 If I have something to you in the morning, would that be 24 appropriate? 25 THE COURT: Okay, so you have now suggested a reason Linda L. Russo, RPR Official Court Reporter 85 1 why we may want to hear briefly from Dr. Murphy in the morning, 2 and Mr. Friedman also has also suggested earlier a reason why 3 we may want to hear from Dr. Murphy again in the morning, the 4 data that he's going to provide you today. 5 MR. FRIEDMAN: Yes, Your Honor. His regressions are 6 rather dense. It may take us a while to penetrate. 7 THE COURT: Ten minutes, you said. 8 MR. FRIEDMAN: For him, not for me. Oh, my ten 9 minutes. That's if he answers my questions right. 10 THE COURT: If he answers them right or if he answers 11 them briefly? 12 MR. FRIEDMAN: Right is briefly in this case, Your 13 Honor. 14 BY MR. FRIEDMAN: 15 Q. So, one or two more questions on P-values. You report a 16 P-value of .1625, right? 17 A. That's correct. 18 Q. And the Federal Judicial Center speaks of a P-value of 19 .05, right? 20 A. Well, the thing you just read me talked about large and 21 small P-value, so it was really talking about a range. 22 Q. And the P-value that you reported, just doing the math, is 23 three times larger, a little more than three times larger than 24 .05, right? 25 A. Yeah. Linda L. Russo, RPR Official Court Reporter 86 1 Q. Okay. Now, you also in Exhibit Seven reported results at 2 the department level, not just the store level, correct? 3 A. That's correct. 4 Q. And you looked at nine departments, right? 5 A. Sounds about right. 6 Q. Well, you have bakery, grocery, meat, other prepared 7 foods, produce, seafood, specialty, wine and liquor, nine 8 departments, right? 9 A. You're counting them. I'm sorry, I wasn't counting along. 10 I'll take your word for it. 11 THE COURT: You have Exhibit Seven in front of you? 12 THE WITNESS: I'm trying to find it right now. 13 BY MR. FRIEDMAN: 14 Q. Of those nine departments that you looked at, you found a 15 statistically significant result in only two of those 16 departments, right? 17 MR. BLOOM: Objection. 18 BY MR. FRIEDMAN: 19 Q. At the five percent level, you found a statistically 20 significant result at the five percent level in only two of the 21 nine departments you looked at, correct? 22 A. Yeah, that would be correct. 23 Q. And those two departments are produce and seafood, 24 correct? 25 A. Those would be two departments, yes. Linda L. Russo, RPR Official Court Reporter 87 1 Q. Those are the two departments in which you found a 2 statistically significant difference at the five percent level, 3 correct? 4 A. That sounds correct. 5 Q. You're not suggesting that produce sold at premium natural 6 and organic supermarkets is a separate relevant product market, 7 are you? 8 A. No. 9 Q. You're not suggesting that seafood sold at a premium 10 natural and organic store is a separate relevant product 11 market, are you? 12 A. No. 13 Q. You said it would be misleading to do a product-by-product 14 analysis because consumers do not choose retailers on a 15 product-by-product basis, right? 16 A. That's in reference to market definition. I didn't think 17 we'd want to define separate markets product-by-product. That 18 doesn't mean you wouldn't want to look at individual products 19 for purposes of analysis. Those are two separate questions. 20 One is, what's my analytical frame, the other is what do I end 21 up doing in terms of an ultimate market definition. Those are 22 separate questions. 23 Q. Let's look at paragraph 97 of your report. This is your 24 direct testimony. You said, "Given the thousands of products 25 sold by supermarkets, a product-by-product analysis is not Linda L. Russo, RPR Official Court Reporter 88 1 feasible. Such an analysis would also be misleading because 2 consumers do not typically choose retailers of the goods in 3 question on a product-by-product basis; rather, they typically 4 purchase an array of products from a single source." Is that 5 your testimony, sir? 6 A. You know, you got to take it in context, because we're 7 talking in here in the context of how we're going to define the 8 markets. And we're discussing that we're going to define the 9 markets not at the product-by-product level. When you say it 10 wouldn't be appropriate to do an analysis product-by-product, 11 that's a completely different issue. That is the 12 product-by-product analysis can be informative about the 13 overall market definition even if ultimately you're going to 14 settle on a market definition that's not product-by-product. 15 And that's certainly the case with regard to what we're doing 16 in Exhibit Seven. 17 Q. Dr. Murphy, your words, paragraph 97: "Such an analysis 18 would also be misleading." Were those your words? 19 A. Such an analysis of product market definition, not such a 20 regression analysis, for example. When you say "such an 21 analysis," you got to say what the "such" refers to. And the 22 "such" in this is talking explicitly about how we're going to 23 define the product market. You don't want to say that I'm 24 saying you shouldn't do an analysis product-by-product in a 25 regression context. Those are two completely different things. Linda L. Russo, RPR Official Court Reporter 89 1 THE COURT: In fairness, paragraph 97 is under a 2 heading in his report that says, it is captioned The Relevant 3 Product Market: Applying the Hypothetical Monopolist Test. 4 THE WITNESS: That was a better way of putting it. 5 BY MR. FRIEDMAN: 6 Q. We've talked about the fact -- I'm switching subjects -- 7 that you said that since the data that the parties had 8 produced, that you looked at in Exhibit Four, didn't contain 9 events in which Wild Oats entered Whole Foods market, in just 10 that one fourth column exit example, that the data did not 11 offer a direct test of the extent to which Wild Oats presented 12 unique constraints to Whole Foods that would disappear as a 13 result of the proposed transaction. Do you remember that? 14 A. That would be referring to the data in Exhibit Four. 15 Q. Understood. In fact, there are two banner exits that fit 16 precisely within your requirement of the Wild Oats 25,000 17 square foot store within five miles of Whole Foods, aren't 18 there? 19 A. No, not in terms of the overall requirements. I believe 20 there is an Arizona event, and then the Fort Collins one we 21 have been talking about. I discussed the Fort Collins one 22 extensively. 23 Q. Why don't you look at Exhibit 589, which is tab one. If 24 you look at the first page of that exhibit, the next to the 25 last entry on the first page, Scottsdale, Arizona; do you see Linda L. Russo, RPR Official Court Reporter 90 1 that? 2 A. Yeah, that's the one I was just talking about. 3 Q. That is a banner exit by Wild Oats in January of 2005 of a 4 28,000 square foot store within three miles of Whole Foods; do 5 you see that? 6 A. Yeah, but I discussed this explicitly in my report. The 7 Scottsdale, Arizona, one, I believe. And it was fairly 8 complicated. I believe the store was relocated, reflagged, and 9 eventually exited. To try to call that an exit event for which 10 we're going to identify the impact on competition, to me was 11 not a very reliable indicator. As such, it was not included in 12 my analysis. 13 Q. All right. So you didn't do an exit analysis of that 14 store, correct? 15 A. Because it was not appropriate to do so. 16 Q. And then if you look at Fort Collins, that was a banner 17 exit in December of 2006, correct? 18 A. That's correct. We didn't have the data to do that. 19 Q. Okay. And you know that among the materials that you 20 reviewed was the investigational hearing testimony of Whole 21 Foods Regional President, Will Paradise; do you remember that. 22 THE COURT: Say that again. 23 BY MR. FRIEDMAN: 24 Q. Will Paradise. You know that Mr. Paradise testified that 25 in Fort Collins, Whole Foods did not raise prices after Wild Linda L. Russo, RPR Official Court Reporter 91 1 Oats exit, because it was constrained by a King Sooper in the 2 same parking lot; you know that? 3 A. I believe that might be the case. 4 Q. That's actually in your book at DX-625, there's an excerpt 5 from his transcript. But we won't spend our time looking at 6 that now. We talked about Irvine, California, which is also on 7 Exhibit 589, right? 8 A. That's correct. 9 Q. That was a banner exit, correct? 10 A. Yeah, beyond five miles. 11 Q. It was 5.67 miles, right? 12 A. That's correct. 13 Q. So you didn't look at that because of the .67 miles, 14 right? 15 A. First of all, I wasn't particularly focusing on exit 16 events. That is Exhibit Three and Four are labeled "Entry" 17 because that was my primary interest. Exit events have a 18 number of problems, I believe some of which we have talked 19 about. As clean events go, they tend to be less suitable for 20 several reasons. And in particular, while people tend to 21 respond sharply on price with entry, there's very little 22 incentive to respond sharply on price on exit. That is one of 23 the things you do when you respond sharply with price is, it 24 becomes aware to consumers that you're doing it. When you're 25 cutting prices, raising consumer awareness is actually a good Linda L. Russo, RPR Official Court Reporter 92 1 idea. If you're in business and you're raising prices, usually 2 you try to not make it so bold. So you would expect a more 3 gradual affect to the exits. 4 Secondly, and I think this is the most important 5 reason, people exit for a reason. And usually when a firm 6 decides to exit, its competitive significance has been 7 declining for a while. That's usually why they exit. So exit 8 events have a selection issue, not so present with entry 9 events, that make them less suitable for this kind of analysis. 10 Q. So the short answer to my question is, you did not study 11 that exit event, correct? 12 A. I was trying to explain just general ideas about why one 13 might be cautious about doing so. 14 Q. But the short answer to my question is, you did not study 15 that exit event, correct? 16 A. Yes, that's correct. 17 Q. And Fort Lauderdale was a banner exit in February of 2006, 18 with 23,500 square foot store, a mile away from Whole Foods; do 19 you see that? 20 A. Yeah, it was less than 25,000, and as I discussed earlier 21 today, it was originally discussed as a relocation, which, 22 again, causes additional problems beyond the ones I already 23 mentioned. 24 Q. So you chose not to study the effect of the Wild Oats exit 25 in Fort Lauderdale, Florida, on Whole Foods prices, correct? Linda L. Russo, RPR Official Court Reporter 93 1 A. No. That latter reason would be an additional reason. 2 They didn't meet the 25,000 cut-off, which would have kept them 3 out anyway. 4 Q. But the fact of the matter is that you chose not to study 5 the effect of that Fort Lauderdale exit on Whole Foods prices, 6 correct? 7 A. For good reason. 8 Q. Correct? 9 A. Correct. 10 Q. All right. If you look at all of the other exits that are 11 on DX-589, some are small stores, some are big stores, some are 12 too far away, you didn't study the effect of any of those exits 13 on Whole Foods prices; isn't that correct? 14 A. That is correct. Many of those are in-fill stores, and 15 we've already discussed the problem with in-fill at my 16 deposition. 17 Q. And some of them are banner exits as well, right? 18 A. We've been through all of them. 19 THE COURT: He wants an answer to his question. 20 THE WITNESS: Yes. 21 MR. FRIEDMAN: Thank you. I have no further 22 questions at this time. 23 THE COURT: All right, so you started, by my watch, 24 at 9:30, by that clock by 9:30, and it's now 11:13. 25 MR. FRIEDMAN: You're tough. Linda L. Russo, RPR Official Court Reporter 94 1 THE COURT: I'm doing the best I can. My law clerk 2 has a chess clock, so we'll see if she and I agree. So I think 3 if we take 15 minutes, try to get everybody out and back in, in 4 15 minutes, Mr. Bloom can begin then. 5 (Recess taken) 6 THE COURT: If you're going to put something up on 7 the screen, you'll let Ms. Moon know whether it should be 8 publicly displayed or not. 9 MR. BLOOM: Thank you, Your Honor. In fact, I would 10 ask that none of the exhibits that I'm going to use be put on 11 the screen. I'll have to talk about them elliptically. I do 12 have revised copies of these exhibits for the Court, if I may 13 approach. 14 THE COURT: You can give them to Ms. Moon. If you 15 have an extra copy for my law clerk, that will be great. 16 We have multiple copies, and that way the court 17 reporter can have one. Do you all have enough copies? 18 MR. FRIEDMAN: We have one. These are demonstrative. 19 THE COURT: If you need more than one, and you 20 probably do, I think Ms. Moon and Ms. Russo can share one for 21 the time being. Why don't you give one to Mr. Friedman. Are 22 you ready? 23 MR. BLOOM: Your Honor, with respect to our exhibit 24 relating to the North Carolina Whole Foods, this was the 25 subject of the objection about the additional entry events Linda L. Russo, RPR Official Court Reporter 95 1 noted, I've had folks go back to the office and they have 2 determined that this information was turned over as part of our 3 turning over of CID responses of third parties. It has not yet 4 been PX'd, so I will ask my people to PX it, and we will submit 5 it to the Court immediately. The underlying data has been 6 provided in the due course of discovery, and we'll identify 7 specifically where that is. 8 MR. FRIEDMAN: I have two objections. I told 9 Mr. Bloom I would have this objection, which may moot this 10 issue altogether. My cross-examination did not inquire of Dr. 11 Murphy at all about North Carolina or Earth Fare. There were a 12 few answers where he volunteered some information either in 13 response to Your Honor's question or something I asked on an 14 altogether different subject. I don't think that opens the 15 door for redirect on North Carolina. 16 THE COURT: I do think we agreed the other day, or 17 when we were last here, that we're going to limit redirect to 18 the scope of cross, but that the scope of cross also includes 19 questions that I asked, and answers that I elicited. So it may 20 or may not be necessary to get into some of these areas. I 21 think if you think he's going beyond the scope of cross, you 22 can object. 23 MR. FRIEDMAN: I generally think that anything about 24 North Carolina is beyond the scope of cross. 25 MR. BLOOM: Your Honor, if I may. Your questions did Linda L. Russo, RPR Official Court Reporter 96 1 inquire about Earth Fare, and there were also questions about 2 the longevity of effects about whether the entry of other firms 3 confounds the results. This is probative on all of those 4 matters. 5 THE COURT: I'm inclined to agree with Mr. Bloom, 6 Mr. Friedman, that just because we didn't talk about a 7 particular market, if the use of a particular geographic 8 market, or discussion of a particular geographic market is 9 relevant to the topics that were covered in cross, and in fact 10 may enable Dr. Murphy to -- the whole point of redirect is to 11 let him clarify and bolster his direct to the extent it's been 12 undermined by the cross, and I don't think we can limit him to 13 particular geographic markets if, by discussing other 14 geographic markets, it enables him through Mr. Bloom's 15 questioning to do that. 16 MR. FRIEDMAN: I don't think it's relevant, but I 17 won't belabor the point. What he testified is, there's no Wild 18 Oats in North Carolina, never is, never has been. So how can 19 that be probative of anything that we care about here? 20 MR. BLOOM: I'm sure we will clarify that in the 21 course of the questioning. 22 THE COURT: We'll see. Obviously, you can object if 23 you feel the need to. Okay. 24 25 REDIRECT EXAMINATION Linda L. Russo, RPR Official Court Reporter 97 1 BY MR. BLOOM: 2 Q. Hello again, Professor Murphy. 3 A. Hello. 4 Q. Did any of your -- let's start at the very beginning. You 5 testified that you've been involved in testifying in only a few 6 matters in court; is that correct? 7 A. Yes, I believe there are four. 8 Q. And you've consulted you said in only about five merger 9 matters? 10 A. In that range, yes. 11 Q. What have you been doing with your time? 12 A. Most of the time I spend teaching. I actually have 13 probably the heaviest teaching load of anybody in the 14 department or the business school in Chicago. 15 Q. Can you tell us a little bit about your publications? 16 A. Yeah. I published probably about 60 papers in a range of 17 fields, really across a wide range of economics, including 18 issues in the industrial organization/antitrust area. 19 Q. How about in econometrics, specifically? 20 A. I don't consider myself too published in "econometrics" 21 papers. I publish a lot of empirical papers that utilize 22 econometric techniques. That's what we do in this case, and 23 that's what I do for a living. So that's the relevant part. 24 You might not want somebody who called himself, quote, somebody 25 who published any kind of metrics. A lot of that is more Linda L. Russo, RPR Official Court Reporter 98 1 technical stuff, and what you really need to do in these kind 2 of problems is really focus on the applied issues about how you 3 use those techniques to analyze data. And that's what I do in 4 my research. 5 Q. Have your contributions to the field of economics been 6 recognized by the receipt of any awards? 7 A. Yeah, I have received a couple of awards. I received the 8 1997 John Bates Clark metal from the American Economics 9 Association. That's awarded every other year to outstanding 10 American economist under the age of 40. 11 Q. Is that a prestigious award? 12 A. I think so. 13 Q. So I'm told. What sorts of other work have you done in 14 the context of professional consultancy that relates to the 15 kinds of issues that we face in a merger investigation? 16 A. Well, I deal a lot with competition issues generally 17 about, you know, what firms compete with what other firms and 18 how contracts and other relationships in the market effect 19 competition. The roles of entry and competition across a range 20 of different products, often with differentiated products and 21 product that compete with one another that may be somewhat 22 different from one another, but nonetheless compete. The same 23 kind of issues we have in this case that have come up with most 24 of the cases I deal with. 25 Q. Have you conducted studies of the so-called but-for world Linda L. Russo, RPR Official Court Reporter 99 1 in your other work? 2 A. Almost always. Almost always these cases come down to 3 asking a question about how would the world be different if 4 somebody changed. That's fundamentally the question. 5 Sometimes it's based on historical events, what would have 6 happened if something had changed differently in the past. 7 Sometimes it's more forward looking like we have in a merger 8 case where it's what would be the likely consequence of a 9 change going forward. Sometimes it's a combination of the two, 10 both past and future. 11 Q. Now, you testified that in many of your studies you used 12 margin data rather than price data; is that correct? 13 A. That margin data, I think the right way to think about it 14 is that margin data and price data both have their strengths 15 and weaknesses, and often it's good to use both sorts of data. 16 And that's what I tried to do in this analysis, and that's the 17 kind of general practice that I think people have used in the 18 past. 19 Q. Can you make inferences about price from margin 20 information? 21 A. Yes, you can. Price, remember price is a major ingredient 22 in a margin calculation. So margins can be informative about 23 what happens with prices. 24 Q. Is it always going to be the case that a price effect will 25 be less than a margin effect? Linda L. Russo, RPR Official Court Reporter 100 1 A. No, that's not theoretically the case, that's not even 2 empirically the case. And, in fact, in this case, we find 3 several instances where it's not, where the price effects 4 actually are larger than the margin effects. Even scaled, 5 where we scaled the margin effects up to translate into price 6 effects at fixed cost. 7 Q. What do you mean when you say scale them up? 8 A. When we discuss in the paper a change in the margin of .7, 9 at fixed cost that would mean prices would be rising by 1.1 10 percent. What I'm saying here is oftentimes you'll find that 11 the price effects are actually bigger than even the implied 12 price effects from the margin data. So you might get 1.4 or 13 something, for example, in that hypothetical. 14 Q. I think you just spoke of margin points. There may have 15 been some confusion previously in the difference between margin 16 points and margin percentages. Could you explain that? 17 A. Well, the margin is defined as the -- it's price minus 18 cost over price. So it's what fraction of the revenue is not 19 accounted for by cost. So that's what we mean by margin. 20 Since price is both the enumerator and the 21 denominator of that fraction, a change in margin requires a 22 more than one for one change in price. If you're holding a 23 cost constant, and you want to raise the margin by .7, in this 24 example you'd have to raise the price by 1.1. The net effect 25 of raising it in the enumerator and denominator would be a .7 Linda L. Russo, RPR Official Court Reporter 101 1 increase. 2 Q. You mentioned some difficulties with respect to the 3 pricing data provided Whole Foods. When did you first request 4 that pricing data? 5 A. I don't recall the precise date. I know it was a long 6 wait until we got it. I don't remember exactly how long that 7 was. I'm sorry. 8 Q. When did you get it? 9 A. I don't recall precisely. 10 Q. Was it within the last three weeks? 11 A. Not three weeks from today, no. It would have had to have 12 been before that, because today is July 31st, so three weeks 13 ago would have been July 10th. That would have been after my 14 report was filed, and so it would had to have been before that. 15 Q. Do you recall about how long before your report that you 16 got it? 17 A. No. I'm really bad with dates. I'm sorry. 18 Q. That's fine. 19 A. But somebody's got to know. I'm sorry, I can't remember 20 certain things, and dates are one of them. It's all mushes 21 together. 22 Q. What were the problems that you had with respect to using 23 that data? 24 A. Well, you know, when you match SKUs, or when you match the 25 codes across stores for what are supposed to be the same Linda L. Russo, RPR Official Court Reporter 102 1 products, you would expect the prices to be not necessarily 2 equal, but similar. So you wouldn't expect the same product, 3 for example, to sell for $1 in one store, and $20 in another 4 store. That's probably indicative that that's an improper 5 match, that somehow they have coded things differently in the 6 two stores. So what we found in the Whole Foods data was a lot 7 of very large discrepancies, both over time and 8 cross-sectionally. And those large discrepancies obviously had 9 an ability to cause a lot of noise in your data. 10 What was actually interesting was that while it 11 created a lot of noise in the data, it didn't really prevent 12 you from seeing the underlying patterns. But what was actually 13 quite nice in terms of, as an empirical economist who likes 14 working with data was that as you filter the noise out, the 15 picture became extraordinarily clear, and that was actually a 16 very useful thing. 17 MR. FRIEDMAN: Your Honor, I'm sorry, but it's 18 difficult for me to object if we are not going question and 19 answer. The question was what were the problems with the data, 20 and we went on to talk about what was nice in the data. 21 THE COURT: Try to answer the question that's put to 22 you. 23 THE WITNESS: I'm sorry. 24 BY MR. BLOOM: 25 Q. What did you do to clean up the noise in the data? Linda L. Russo, RPR Official Court Reporter 103 1 A. I think I just described, we looked for those large 2 discrepancies and eliminated any products that had a large 3 discrepancy from the analysis. So not just in the time they 4 had the large discrepancy, but eliminated those products from 5 the analysis. And the magnitude of the discrepancy we used, 6 and this is unfortunate because economists think in logs, so it 7 was a log difference of at least one, which, given that the 8 natural -- there's the letter "e" in mathematics, and it's like 9 two and a half, so it would be a factor of two and a half 10 difference, which is a very large difference for supposedly the 11 same product in two different places. So we filtered out those 12 large differences, and that really tended to clean things up a 13 lot. 14 Q. I believe you testified that you had not studied -- you 15 had been asked whether you studied a Whole Foods entry event; 16 is that correct? Do you recall that? 17 THE COURT: Earlier today. 18 THE WITNESS: A Whole Foods entry event? 19 BY MR. BLOOM: 20 Q. Yes. 21 A. Yeah, we did study Whole Foods entry events. 22 Q. Where did you study Whole Foods entry events? 23 A. Whole Foods entry events would be directly addressed in 24 Exhibit Three, they would also be addressed in -- I'll have to 25 look, I believe it's Exhibit One, because Exhibit One is Linda L. Russo, RPR Official Court Reporter 104 1 Markets Where Whole Foods Entered, so it would definitely be 2 there. It would be also in Exhibit Five, also in Exhibit Six. 3 Implicitly it would be included in Exhibit Seven, as well as 4 Exhibit Eight. 5 Q. So in a number of your studies you looked at Whole Foods 6 entry events. Did you determine whether there were any 7 patterns across these different analyses? 8 A. Yeah, there was a pattern of Whole Foods entry generated a 9 substantial decline in Wild Oats margins, as well as a 10 substantial and persistent decline in their sales. 11 Q. With respect to Oats entry events, what have you learned 12 to date about entry events of Wild Oats? 13 A. The only entry event for which we had -- were able to 14 really do the analysis, hadn't even become a complete entry 15 event. This is the one I referred to earlier today where Wild 16 Oats announced entry into the new store in the Boulder, 17 Colorado, area. The opening of that store generated a price 18 response from Whole Foods. 19 Q. And what was the magnitude of that price response? 20 A. About two percent. 21 Q. You were asked about your exclusion of stores under 25,000 22 square feet; do you recall? 23 A. Yes, I do. 24 Q. And that was related to concern about their competitive 25 significance; is that right? Linda L. Russo, RPR Official Court Reporter 105 1 A. My understanding was that people in the record had 2 suggested that those stores either were not competitively 3 significant, or less competitively significant. And so we felt 4 we needed to draw a line at some point in order to make sure 5 the sample of stores we looked at were the stores that would be 6 deemed competitively significant. We chose that line at 7 25,000. 8 Q. Mr. Friedman pointed out that you had written that those 9 smaller older stores are not competitively significant. Did 10 you mean literally that they have no competitive significance? 11 A. No, I did not. 12 Q. Would you explain, please? 13 A. As a matter of economics, we would typically expect that 14 smaller stores would be less significant partly because, one, 15 they're simply smaller so they have less of a presence in the 16 marketplace. Second, they often would carry a different mix of 17 products, typically a narrower mix of products. If you have a 18 small store, you don't just have less sales. You also 19 typically have a narrower mix of products. Therefore, they 20 might be less, and one would expect them to be less significant 21 than larger stores. 22 There may even be a threshold to which they had no 23 significance. But whether they're no or much less 24 significance, really isn't key. The key issue is, what you'd 25 like to do is look about a sample of stores that you think Linda L. Russo, RPR Official Court Reporter 106 1 would be significant, and draw a line at such a point so that 2 the included sample is stores for which you'd expect there to 3 be an effect. It would be better to leave out a few things 4 that could have been included, than to include things that 5 shouldn't have been. 6 Q. Changing topics for a moment, there was also some 7 quibbling about the use of a five versus a six mile radius in 8 defining markets; do you recall that? 9 A. Yes. 10 MR. FRIEDMAN: Object to the characterization of 11 "quibbling." 12 THE COURT: I'll disregard the characterization. 13 BY MR. BLOOM: 14 Q. Is there a relationship between the strength of 15 competitive interaction, and the distance between a store and 16 competitors? 17 A. Typically, there would be a relationship between distance 18 and the strength of the relationship, yes. 19 Q. What would be the nature of that relationship? 20 A. Well, I think the nature would be generally that places 21 that are further away would have less significant competitive 22 interactions. Places that are right across the street 23 typically will have greater interaction than places that are 24 two miles apart, which would be probably greater than things 25 that are further. The further you go, presumably the smaller Linda L. Russo, RPR Official Court Reporter 107 1 the effect. 2 Q. If, instead of a five mile or a six mile radius was used, 3 let's say a ten mile radius was used, would that have changed 4 the concentration in the premium natural and organic 5 supermarket in any of the markets you've studied? 6 A. It wouldn't have changed the significant characteristics 7 of those markets from an economic point of view. Whether it 8 would have changed the precise numbers that one would have 9 calculated, we'd have to go through and check. For example, in 10 Portland where you had three firms operating, you have New 11 Seasons, you have Whole Foods, you have Wild Oats, as you vary 12 what you include, the numbers may change a little bit for 13 example if you're doing a Herfindahl, or some number like that. 14 THE COURT: Herfindahl? 15 THE WITNESS: I'm sorry, my pronunciation. 16 THE COURT: That's fine, but somebody spell it. 17 THE WITNESS: Don't ask me. I can't spell either. 18 MR. BLOOM: I believe it's H-e-r-f-i-n-d-a-h-l. 19 THE COURT: Somebody tell Ms. Russo later. 20 MR. BLOOM: I can say it. Spelling it is a different 21 matter. 22 THE COURT: There's a difference in the real world. 23 Is there a difference in terms of the analysis that you do 24 between markets. For example, a five mile radius in Portland, 25 Oregon, or in the outskirts of Portland, Oregon, is going to be Linda L. Russo, RPR Official Court Reporter 108 1 different from a five mile radius in Washington, D.C. or from 2 the Union Square store in Manhattan to the next nearest store, 3 isn't it? 4 THE WITNESS: Yeah, and that's why you might expect 5 that you don't get a constant effect, for example, across 6 markets, because what five miles means is going to be different 7 in different places. In principle, that means that you've kind 8 of mixed people with bigger effects with people with smaller 9 effects, so you're getting some kind of, in some sense, an 10 average of the ones that were included. The further out you 11 go, you include more distant relationships, and therefore 12 typically you expect a smaller number for the overall average. 13 In principle, you could try to do a refined measure where you 14 could say, okay, I'm going to measure the distance using a 15 metric other than five miles. You could do it using some 16 mapping software, or something like that. This has been a very 17 abbreviated proceeding, for which we used the five mile, in 18 some sense shortcut, that you could have done that if you had 19 more time, but we didn't. 20 THE COURT: But in the real world, I take it that the 21 five mile or six mile radius is really a proxy for how long it 22 takes to get there, and how convenient it is for customers. 23 THE WITNESS: Although when you look at travel 24 patterns, they don't always just follow convenience. That is, 25 people like to go some ways and they don't like to go others. Linda L. Russo, RPR Official Court Reporter 109 1 So, for example, if people typically shop for one thing in one 2 direction, they may be more likely to also shop for other 3 things. I know my own shopping patterns, for example. And 4 people are creatures of habit. That's a very important part of 5 economics. So you might even, ultimately could include things 6 like that. But, again, like I said, it's an abbreviated 7 proceeding. We thought five miles was a reasonable proxy. 8 If we included things that were "because it was 9 inconvenient" presumably that would make our numbers come out 10 smaller than they should have. Because if you put things in 11 that don't really compete, that's going to tend to push your 12 numbers downward from what they would otherwise be. If you 13 refine the analysis, you would expect the numbers to get 14 somewhat bigger. 15 BY MR. BLOOM: 16 Q. Looking at the question of geographic market analysis 17 again, in setting aside Oregon for a moment, how far would you 18 have to go from any nearby Wild Oats and Whole Foods before you 19 picked up another premium natural and organic supermarket? 20 A. You mean one that wouldn't be owned by those two? 21 Q. Correct. 22 A. That would be a long ways. 23 Q. More than ten miles? 24 A. I would definitely think more than ten miles. 25 Q. More than a state in many instances? Linda L. Russo, RPR Official Court Reporter 110 1 A. Certainly. 2 Q. You were asked about your not having retained certain 3 sensitivity analyses; do you recall that? 4 A. Yes, I do. 5 Q. Is that consistent with your regular practice? 6 A. Yes, it is. 7 Q. Is it consistent with your practice when you're doing 8 academic work? 9 A. Absolutely. 10 Q. Why do you work that way? 11 A. Well, you know, what you try to do in any report or any 12 economics paper that you publish is present something that you 13 think is representative of what you're studying. And to get 14 something that's representative of what you're studying, 15 typically you want to know more about it than what you're 16 actually going to end up presenting to the reader. Because you 17 wouldn't want to present something to the reader if you know 18 that if you looked at it slightly different you'd see something 19 different, then you'd probably want to find another way to look 20 at it that was more robust in some sense. So you do that as 21 part of the process of analysis generally. That's what we did 22 in this case, and that's what I do in research. That's what I 23 teach my students when I teach about how you do research. 24 Q. Did the defendants have all of the data necessary to 25 replicate any sensitivity analysis that you conducted? Linda L. Russo, RPR Official Court Reporter 111 1 A. Absolutely. 2 Q. To your knowledge have they done so? 3 A. No, not that they've ever presented to me. 4 Q. To your knowledge have they made any effort to do so? 5 A. I have no idea what they've done. 6 THE COURT: I guess the real question, the only thing 7 that we've got in rebuttal to you and on the other side of the 8 question is Dr. Scheffman's initial report and his rebuttal 9 report. So I suppose that's what Mr. Bloom is talking about 10 primarily, or maybe even exclusively. 11 BY MR. BLOOM: 12 Q. Let me ask that directly. Did Dr. Scheffman's initial or 13 rebuttal report in any way suggest that he had sought to 14 replicate your sensitivity analyses? 15 A. It didn't say that he had replicated them or tried to do 16 any sensitivity analysis. There is a mention of sorting 17 through 105 SAS programs, so that tells me he at least looked 18 at them. 19 Q. There was some discussion of Irvine and the Wild Oats 20 store in Irvine; do you recall that? 21 A. Yes, I do. 22 Q. How long was that Irvine store open before it closed? 23 A. I don't remember precisely, maybe something like 18 24 months, but I could be mixing my events. 25 Q. If it was 18 months, would that make it more or less Linda L. Russo, RPR Official Court Reporter 112 1 likely to be a competitively relevant store for your analysis? 2 A. Probably a little bit less, although not tremendously 3 less. Just probably a little less. There's a difficulty with 4 exit events generally that I talked about earlier, which is, 5 people exit for a reason. And usually they exit because 6 they're not having great competitive success. And therefore 7 you're going to expect less of an impact from that than you 8 would from sort of eliminating somebody exogenously, taking 9 somebody out who didn't choose to leave. That is, the people 10 who choose to leave won't be representative of the people who 11 are there, because the people who choose to leave left for a 12 reason, namely, they were having less competitive success. I 13 think it's almost self-evident. And if you choose to leave 14 after 18 months, you probably weren't very successful. I think 15 that's what you're getting to. 16 Q. The question is where you're getting to? 17 A. You know, the point is, it's a very general point that at 18 the end of their life, these people are going to be less 19 competitively significant almost by definition. That's going 20 to be true for people who were there for a while, and people 21 who were there for 18 months. 22 THE COURT: People who were only there for 18 months 23 probably have been less competitively successful for a period 24 of time during that 18 months. You don't have one bad week and 25 close down. Linda L. Russo, RPR Official Court Reporter 113 1 THE WITNESS: No, but if you've been there for 20 2 years, you don't have one bad year and close down, either. So 3 that's what I'm saying. People who close down presumably have 4 been doing badly for a while. That's true whether you opened 5 18 months ago or whether you opened 36 months ago, or 127 6 months ago. If you leave after 18 months, you must have got a 7 pretty bad shock, because you thought you were going to do 8 better, you came in -- otherwise you wouldn't have come in. 9 The guy who's been there for 20 years, he may have had great 10 days at one time, so probably the 18 months guy has got a 11 little worse news than the other people did. 12 BY MR. BLOOM: 13 Q. I want to shift to your decision to use a 25,000 square 14 foot cut-off in your regressions. If you had -- you testified 15 that you didn't apply that standard to third parties. Do I 16 have that correct? 17 A. Yeah. For example, you wouldn't -- no, that is correct. 18 Q. If you had applied that standard to third parties, would 19 you have been able to learn anything at all about the impact of 20 Trader Joes? 21 A. I don't believe Trader Joes has any stores over 25. I 22 know their typical store is around 11,000, so applying a 25,000 23 square foot standard to Trader Joes would be like not looking 24 at Trader Joes. 25 Q. Was it important to look at Trader Joes? Linda L. Russo, RPR Official Court Reporter 114 1 A. I thought it was informative. 2 Q. You talked about a SSNIP, a small but significant 3 nontransitory increase in price, and you said that 4 nontransitory typically means that it lasts two years; isn't 5 that correct? 6 A. I think I said on the order of two years. It's not a 7 bright line. It's not like something that lasts 23 and a half 8 months is so different than something that lasts 24 and a half. 9 It's like the 25,000 square feet thing. It's a guideline, you 10 say around two years is what we would say, we're now getting 11 into nontransitory. Some people might draw the line earlier, 12 some people might draw it later. 13 Q. What's the purpose of drawing that line as you understand 14 it? 15 A. I think what you're really trying to do, remember, if 16 you're thinking about it in terms of the product market 17 definition part of the guidelines which focus on consumer 18 response, that's the demand side response that you're focusing 19 on, on that part of the guidelines, you're giving consumers a 20 chance to adjust to the new equilibrium, and the new conditions 21 in the marketplace. You'd want to say, look, maybe people 22 can't figure out where else to go in the first day, and it may 23 take them time. 24 Now, depending on the marketplace that you're dealing 25 with, you may equilibrate faster or slower, but that's why you Linda L. Russo, RPR Official Court Reporter 115 1 want nontransitory, because the ability of people to substitute 2 typically grows with time. 3 Q. In a market where consumers make purchases on a weekly or 4 more frequent basis, would you expect them to adjust more or 5 less rapidly? 6 A. If it's -- certainly it's a nondurable item, like most 7 food items are, they're consumed, and they purchase them 8 frequently, that would tend to lead to a more rapid adjustment. 9 Q. What are the implications of that for an adequate SSNIP in 10 the context of the supermarket industry, and the premium 11 natural and organic supermarket industry in particular? 12 A. I mean, if you're doing a study of consumer demand, you 13 might think that you could study long-run consumer demand 14 responses in a shorter period of time. And you do see that, 15 for example, in the quantity data in our studies. That is, the 16 quantity data, remember, are really capturing consumer 17 behavior. That's what consumers do. 18 Firms choose prices, and consumers chose the 19 quantities. The owners of the store choose the prices they're 20 going to charge, and as a consumer, I decide where I'm going to 21 buy. You do notice the quantity responses happen pretty 22 quickly, like in the first six months. They change a little 23 bit after that, but most of the consumer side response is done 24 in the first six months. You can see that in figure 5 and 25 figure 6 in my report, and that would be to be expected in a Linda L. Russo, RPR Official Court Reporter 116 1 market like this. 2 Q. Do your margin regressions provide some insight into the 3 impact of these simultaneous entry situations from the point of 4 view of understanding each firm's contribution? 5 A. Yeah. There are two ways to think about it. First, in 6 the case like we had in Portland of a single entry event, I 7 went through exactly how to interpret those two co-efficients. 8 More generally by looking at cross-markets, you can attempt to 9 disentangle the effects of simultaneous entry, because while 10 you had the two people enter simultaneously here, they may be 11 entered at separate times in other markets. And by combining 12 the information across markets, that can help you disentangle 13 it. 14 Think about it in terms of arithmetic, you have like 15 in this market, A plus B, in another market you see A, in 16 another market you see B. Well if I know A plus B, and I know 17 A and I know B, I can get an estimate of them independently. 18 Or even if I had an A plus B and just A, I can get an estimate 19 of B. 20 One difficulty that arises in these multiple entry 21 events is that the effects may not be the same in every market, 22 and that's what I was talking about in Portland. And that's 23 what I think contributes to the finding we have in Portland. 24 Q. You mentioned that you didn't study the effect of Whole 25 Foods entry in Fort Collins, and I think also didn't study the Linda L. Russo, RPR Official Court Reporter 117 1 effect of a Wild Oats exit; is that correct? 2 A. We studied the effect of Whole Foods entry in Fort 3 Collins. We were not able to study the effect of Wild Oats 4 exit in Fort Collins. 5 Q. Why not? 6 A. The data we had when we were preparing Exhibit Three 7 didn't go far enough to allow us to do that. 8 Q. There was a methodological problem with the data? 9 A. It was a time coverage problem. In order to study the 10 exit event, you would have to have data pre- and post-exit, 11 because that's frankly how you identify the effect of exit, is 12 how do things look afterwards compared to how they looked 13 before. And if you don't have after data, you can't very well 14 study what the impact of the exit event really would be. It's 15 the simplest form of kind of identification in economics. 16 Q. I'd like to turn to partial shrink for a moment. 17 A. My favorite topic. 18 Q. When was the first time in the context of this 19 investigation that the defendants ever mentioned the word 20 partial shrink? 21 A. To my knowledge it was during my deposition the first time 22 I heard it. 23 Q. Had you made inquiries about factors that could affect 24 your margin calculations from the defendants? 25 A. We asked for data from the defendants that they thought Linda L. Russo, RPR Official Court Reporter 118 1 were reflective of their price and cost data. And that was one 2 of the reasons they provided us the shrink information to begin 3 with. So, yes, we had requested information on what they 4 thought was relevant. 5 Q. And at that time partial shrink was not mentioned? 6 A. To the best of my knowledge, no. 7 Q. Could partial shrink have affected the price decrease at 8 Whole Foods that you observed in Bolder in February of 2007? 9 A. No. 10 MR. FRIEDMAN: Objection. This is the same issue 11 that he's testifying about stuff that we haven't seen data, and 12 don't have any ability to assess the answers. 13 THE COURT: This is the data that -- does this go, 14 Mr. Bloom, to the same area that we were discussing earlier 15 that Dr. Murphy said that he really didn't look at this 16 question until after he submitted his supplemental report? 17 MR. BLOOM: That is correct, Your Honor. 18 THE COURT: So if he's going to go into this, you and 19 he have promised to provide the underlying data to the 20 defendants today, with the understanding that they may want to 21 examine him further tomorrow morning. So if we go into that, 22 that is a possibility. 23 MR. BLOOM: We recognize that, Your Honor. I have 24 not consulted with Professor Murphy as to whether that's going 25 to cause a particular problem for him tomorrow, and I can do Linda L. Russo, RPR Official Court Reporter 119 1 that if you'd like us to take a moment. But it's my intention 2 to make him available. 3 THE COURT: Are you available tomorrow morning if we 4 need you? 5 THE WITNESS: If you can explain to my wife why I'm 6 not leaving on vacation with her tomorrow, yeah. 7 No, if required to do so, I will be here. 8 MR. FRIEDMAN: Your Honor, frankly, I feel like this 9 is trial by ambush. At Dr. Murphy's deposition, we asked what 10 other studies he was doing with respect to pricing data. He 11 didn't mention a word about Bolder. We asked him if he was 12 planning to give us any additional studies. In fairness, if 13 the FTC had this study, they should have turned it over to us 14 ahead of time. It's not appropriate for them to spring this on 15 us in the middle of trial, and expect us to study something 16 that -- I mean, he did a regression analysis that has 105 17 separate SAS programs, which I don't even understand what that 18 means, thousands of equations. It took our experts days to 19 peel it apart. 20 And so we're supposed to take this, go back tonight, 21 peel it apart, and have a meaningful, effective opportunity to 22 redirect him? It's just the height of unfairness. 23 MR. BLOOM: Your Honor, this data is the defendant's 24 own data. They have had it for all time. Professor Murphy 25 advised me of this finding yesterday afternoon. The finding is Linda L. Russo, RPR Official Court Reporter 120 1 of, I think, tremendous significance. And it seems to me that 2 there is a way to give them an opportunity to examine the data. 3 If it means bringing Professor Murphy back three days from 4 now -- well, Professor Murphy's looking -- 5 THE COURT: That's the real issue. You say it's 6 terribly significant, and yet it hasn't been significant until 7 yesterday, or at least nobody appreciated its significance 8 until yesterday. They haven't had a chance to depose him on 9 it, they haven't had a chance to have Dr. Scheffman look at it. 10 He's leaving on vacation, you want to bring him back from 11 vacation in three days. 12 We set a schedule, and I'm willing to do it tomorrow 13 morning, but that may not give the defendants enough to time to 14 really evaluate what he's saying or the material he's going to 15 give them sometime today. 16 THE WITNESS: I have one thing, which is, it is 17 exactly the same methodology we used in North Carolina. So, if 18 they understand the North Carolina process, they will 19 understand this perfectly. There's no difference in the way in 20 which it was done. It was done using the same exact 21 programming strategy that we used in North Carolina. So from 22 the point of view of detangling and understanding it, that 23 should actually be fairly straightforward. 24 MR. FRIEDMAN: Judge, from the point of view of trial 25 practice, if he knew about it yesterday and he wanted to use Linda L. Russo, RPR Official Court Reporter 121 1 it, he should have given it to us yesterday. They had time to 2 file motions yesterday, they had time to send us demonstratives 3 yesterday, but they wait until we come in here this morning and 4 spring it on me in the middle of my cross-examination. I'm 5 outraged, I'm just outraged. 6 And, frankly, to say to me that I have time, I'm a 7 lawyer. I'm not a Ph.D economist. This stuff is hard for me. 8 To say to me that I can take it at 5:00 tonight and go back and 9 huddle with my economist, and figure out what he's done and 10 come in and conduct a meaningful cross-examination of this man, 11 I'm at a loss for words, Your Honor. 12 MR. BLOOM: Your Honor, Professor Murphy was asked at 13 his deposition whether he intended to continue his work. He 14 said he did intend to continue his work. The question about 15 this was raised by opposing counsel. He continued the work, he 16 made a discovery, the discovery is relevant. If Your Honor is 17 inclined to exclude it, I think what's important to recognize 18 is that the nature of this proceeding is highly preliminary, 19 the evidence that would be presented to the Federal Trade 20 Commission and ultimately to a Court of Appeal is going to be 21 different than the record in this case to the extent that we 22 will have time to develop additional evidence. 23 THE COURT: But you're basically saying if you 24 exclude it and deny the motion for preliminary injunction, 25 that's no argument. Linda L. Russo, RPR Official Court Reporter 122 1 MR. BLOOM: All I'm suggesting, Your Honor, is that 2 this is a preliminary proceeding, and that -- 3 THE COURT: Well, the defendants will have a chance 4 to deal with it if I grant the preliminary injunction, but they 5 won't have a chance to deal with it effectively at this 6 hearing, is what you're saying. 7 MR. BLOOM: I think they can deal with this 8 effectively at this hearing. It may not be a matter of being 9 able to do it overnight, but I will bring Professor Murphy 10 back. It is the information used in North Carolina. 11 MR. FRIEDMAN: Your Honor, this would be his second 12 supplemental rebuttal report out of time. We fought about the 13 first supplemental rebuttal report, and now he's doing it 14 again, but this time it's worse. At least that time he gave it 15 to us the day before his deposition. This is just not right. 16 THE COURT: This topic aside, how much more do you 17 have with Dr. Murphy? Is he going to be back after lunch, or 18 not? 19 MR. BLOOM: I'm sorry, I couldn't hear you, Your 20 Honor. 21 THE COURT: With this topic aside, how much more do 22 you have with Dr. Murphy? 23 MR. BLOOM: I have about another half an hour, I 24 believe. 25 THE COURT: What I'm inclined to do is say the Linda L. Russo, RPR Official Court Reporter 123 1 following. 2 I think that Mr. Friedman's objection is well taken, 3 that I should strike this testimony and the testimony from 4 earlier this morning, that I should not consider it. 5 But I was going to suggest that I give Mr. Friedman 6 and his colleagues to think about this question over lunch. 7 Are they comfortable with my doing that in the 8 following hypothetical scenario. I exclude the evidence, and I 9 deny the motion for preliminary injunction in which the F.T.C. 10 has the burden of proof, and they go to the Court of Appeals 11 and they say that one of the errors that was made in the 12 District Court was the exclusion of this highly significant 13 testimony. 14 So you need to think about that and balance it 15 against the unfairness that you point to in the trial practice 16 evidentiary procedural point that you're raising, and tell me 17 after lunch. And I'm prepared to strike it and not consider 18 it, if that's what the defendants want. But you also have to 19 understand the potential consequences of the Federal Trade 20 Commission saying that I have excluded important significant 21 evidence. 22 MR. FRIEDMAN: All right. 23 THE COURT: And Mr. Bloom had said, over Dr. Murphy's 24 wife's objection, that he's prepared to bring him back. So why 25 don't we proceed with that in the air. Linda L. Russo, RPR Official Court Reporter 124 1 MR. BLOOM: This exhibit is confidential, so I'd ask 2 that it not be put up on the monitors for the public. 3 BY MR. BLOOM: 4 Q. Professor Murphy, I'd like to direct your attention to the 5 exhibit based on your supplemental rebuttal report, Exhibit 6 One, relating to Earth Fare. 7 THE COURT: So the exhibit is in the supplemental 8 report, or -- 9 MR. BLOOM: This is the exhibit from the supplemental 10 report, but it is in here in color, and with the additional 11 entry events that we spoke of. 12 MR. FRIEDMAN: Just so we're clear, this is a 13 demonstrative exhibit, it's not evidence. That's what my 14 understanding was, that these were demonstrative. 15 MR. BLOOM: These are demonstrative exhibits. This 16 evidence will be in the record. 17 THE COURT: Well, demonstrative exhibits, under the 18 Rules of Evidence is not in the record. 19 MR. BLOOM: The underlying facts will be in the 20 Findings of Fact. 21 THE COURT: The underlying facts, but the pile of 22 materials that was handed to me, none of them have numbers on 23 them. So what am I looking at? 24 MR. FRIEDMAN: I understand these are demonstratives. 25 THE COURT: Right. Linda L. Russo, RPR Official Court Reporter 125 1 MR. BLOOM: The document is headed North Carolina 2 Whole Foods Stores that Faced Increased Competition. 3 THE COURT: Okay, I'm looking at the right one. 4 BY MR. BLOOM: 5 Q. Professor Murphy, what do you attempt to capture in this 6 analysis? 7 A. There's several things in this analysis. First and 8 foremost is the impact that the two Earth Fare entry events had 9 on Whole Foods pricing. And you can see the sort of pinkish 10 lines there denote the Earth Fare entry times. And you can see 11 the impacts that they had on Whole Foods prices, the first 12 entry event being in Chapel Hill with the associated effect on 13 the Chapel Hill store. 14 Q. Let me ask you to pause so we can back up and get a little 15 better understanding. What are you actually graphing here? 16 A. These are measures of the impact on Whole Foods prices at 17 various stores. So there are three stores shown on this graph, 18 there's a Chapel Hill store, a Raleigh store, and a Durham 19 store. In order to control for other general price movements, 20 we have used the other stores in North Carolina as control 21 groups. I believe those are Cary and Winston Salem. 22 So what you can see in the figure is that prices at 23 all three of these stores, namely the Raleigh store, the Durham 24 store and the Chapel Hill store, track the control store very 25 closely for roughly the first two-fifths of the time period. Linda L. Russo, RPR Official Court Reporter 126 1 Q. If you'd pause there, I'd like the Court to understand why 2 it was important to do an analysis involving Earth Fare. 3 A. Earth Fare is a PNOS competitor that we identified and 4 people in the record identified as a firm that competed 5 directly with Whole Foods in these markets. And one of the 6 things we wanted to see was what happened when that firm came 7 into the marketplace, and how the impact of that firm would 8 compare to the impacts of other firms coming into the 9 marketplace. 10 Q. What's the relationship then between Earth Fare entry and 11 the Wild Oats entry? 12 A. Well, they're somewhat similar in the sense that they both 13 have a similar general store mission, they also both have 14 competed head-to-head with Whole Foods. So we felt that this 15 was a good analogy to use to try to understand what the effect 16 of PNOS competition was. 17 Q. Now, if you could explain your findings for us, please. 18 A. I think the thing is, you want to think about tracking 19 these lines over time as tracking prices at the three stores 20 relative to other stores in North Carolina. So anything that 21 generally moved prices of groceries around wouldn't impact this 22 because we're doing a price comparison. 23 So what you will notice is the three stores track the 24 zero line pretty closely for a fairly long period of time, 25 running from the beginning of the sample, which is the Linda L. Russo, RPR Official Court Reporter 127 1 beginning of '04, up through sometime in the first five months 2 of '05. And then precisely right around the time of the Earth 3 Fare entry, you see a dramatic fall in Whole Foods prices. 4 Q. What's the magnitude of that fall? 5 A. In this case it's a little over five percent. This is at 6 the Chapel Hill store, which is where the Earth Fare store 7 entered. 8 Q. Does it occur at the other stores? 9 A. No. The Raleigh and Durham stores continue to track very 10 close to the zero line for a couple of months more, until 11 there's a second entry event of Earth Fare in Raleigh, Durham, 12 which causes the Raleigh and Durham stores to fall, and the 13 Chapel Hill store to fall again, back from where it was. And 14 then you can see they track out over time. 15 Q. What do you conclude from these falls that you have 16 described? 17 A. I would say that Whole Foods responds to competition from 18 other players in the PNOS marketplace. 19 Q. How do you know that there wouldn't have been a similar 20 fall-off from the entry of someone who is not in the premium, 21 natural and organic supermarket market? 22 A. We have on this figure identified four other entry events. 23 So the first one would be a target who enters back, the first 24 one, and you can see there's really very little or no change. 25 There's a Sam Club that enters subsequent to that, with little Linda L. Russo, RPR Official Court Reporter 128 1 effect. There's the banner entry of Kroger that occurs 2 slightly after that, again with no perceptible effect on 3 prices. Then we have the two Earth Fare events, which stand 4 out very clearly on the graph. 5 And then there's finally a CostCo entry which occurs 6 toward the right-hand side of the graph, which does have an 7 effect on the Raleigh store. What's interesting about that is, 8 CostCo came in Raleigh, but if you compare the magnitude of 9 that CostCo dip, which is way to the right, with the magnitude 10 of either of the two Earth Fare dips, you really get a feeling 11 for how different they are. So CostCo had some effect, much 12 smaller. Notably, Kroger had virtually no perceptible effect. 13 And this really illustrates that there was a 14 difference in how Whole Foods responded to these different 15 competitors, really quite in differential ways. 16 Q. What does that tell you about market definition? 17 A. It tells me that from the point of view of competition 18 with Whole Foods, it looks like Earth Fare was a lot more 19 important than any of these other events. 20 Q. And would you extrapolate that finding from Earth Fare to 21 premium, natural and organic supermarkets generally? 22 A. As an economist, I would think that would be the logical 23 conclusion, that it was the type of store that entered that 24 made the difference, not the name or something else. 25 Q. Let me direct your attention to the period of the first Linda L. Russo, RPR Official Court Reporter 129 1 number of months in your data where it tracks closely the zero 2 line. Do you see where I'm referring to? 3 A. Yes. 4 Q. What does that mean when it's tracking close to the zero 5 line again? 6 A. It means we have a set of controls that seem to be 7 eliminating the impact of other variables. There are very 8 little unexplained movements in the prices in these stores, 9 other than corresponding to the entry events that we see. 10 Q. If you had done a study on any single day to see if the 11 pricing across the North Carolina Whole Foods stores that you 12 looked at was the same or varied in response to competitive 13 events, let's say you did that on March 1, what would you have 14 concluded from that single day analysis? 15 A. If you had done March 1, '04, you would conclude that 16 prices were very uniform across the stores. 17 Q. And would that be true anywhere along -- any one day 18 analysis that you did, anywhere along the line, up until the 19 Earth Fare entry event? 20 A. Pretty much you would come to similar conclusions 21 throughout that interval. 22 Q. Have you examined documents and testimony relating to the 23 Earth Fare entry events in North Carolina? 24 A. Yes. I cite a couple of documents in my report where they 25 discuss in particular the Chapel Hill event and the pricing Linda L. Russo, RPR Official Court Reporter 130 1 response that they would have where they discuss making 2 significant price cuts on a number of items in response to the 3 potential and actual entry of Earth Fare. And that shows up in 4 the pricing data that we see here, that this price fall is 5 accounted for, there's a number of substantial price reductions 6 on a range of items that generate this overall price response. 7 Q. Is their testimony as well that you regard as consistent 8 with this? 9 A. Yes, I believe so. That is, the testimony in this case, 10 as well as the documents from the case, document that Whole 11 Foods responded and desired to respond to the competitive 12 threat posed by Earth Fare. And the evidence here would 13 suggest they had a substantial response, much bigger than the 14 responses they had to any of these other potential competitors. 15 Q. Is this finding on the Earth Fare exhibit consistent or 16 inconsistent with the conclusions you've drawn in your other 17 analyses? 18 A. I believe it's consistent. 19 Q. Could you explain how they come together. 20 A. Well, I think it illustrates something we have been 21 finding throughout the analysis, that the largest effects tend 22 to be associated with competition between the people we 23 identify as PNOS competitors. That was true when we looked at 24 the effect of Whole Foods on Wild Oats. That's true here when 25 we look at Earth Fare's effect. And that would be true of the Linda L. Russo, RPR Official Court Reporter 131 1 thing we see in Bolder as well. 2 MR. FRIEDMAN: Move to strike the last reference to 3 Bolder. 4 THE COURT: Right, subject to this afternoon's 5 discussion. 6 BY MR. BLOOM: 7 Q. You were questioned about Exhibit Five to your report. 8 I'd like you to turn to that in the binder that defense counsel 9 gave to you. 10 THE COURT: In the original report? 11 MR. BLOOM: Yes. 12 BY MR. BLOOM: 13 Q. I'd like you as well in our exhibit binder, again, this is 14 confidential material, to take a look, please, at the document 15 entitled Entry by Whole Foods Reduced Wild Oats Prices. And in 16 the right-hand corner it says Source, and it includes Murphy 17 Exhibit Five. 18 A. I think this one might be mislabeled, because it's very 19 blurry, but it looks like these are actually quantity effects 20 as opposed to prices. I think these are sales. 21 Q. Let's set it aside in that case and look directly at 22 Exhibit Five. 23 A. There it is. This is -- oh. 24 THE COURT: You've got a couple of different charts 25 in this packet, Mr. Bloom. One is Entry by Whole Foods Reduced Linda L. Russo, RPR Official Court Reporter 132 1 Wild Oats Volume. One is Entry by Whole Foods Reduced Wild 2 Oats Prices. They both cite to Exhibit Five as their source. 3 THE WITNESS: They're both from Exhibit Five, but in 4 the ones I have on my screen, the titles are interchanged. 5 BY MR. BLOOM: 6 Q. Rather than take the Court's time, let's look directly at 7 Exhibit Five. Are you extrapolating any conclusions -- let me 8 change that. 9 What are your gross conclusions from the information 10 that you've gathered and presented in Exhibit Five? 11 A. I think the things you would learn from Exhibit Five is 12 Whole Foods Entry reduces Wild Oats prices and reduces their 13 sales volume. If you look at the sales volume figures, the 14 vast majority of the decline happens in the first six months. 15 There tends to be some downward drift from there, but the vast 16 majority occurs in the first six months. The price effects, 17 the prices fall substantially initially. There's some rebound 18 to those prices, although on the ones you can follow the 19 furthest out, you get a rebound in Hartford, and really no 20 substantial rebound in Fort Collins. So those two pieces of 21 evidence would give you somewhere between a rebound and maybe 22 no rebound, depending on the two. 23 If you're looking at Exhibit Five alone, that's what 24 you can learn from Exhibit Five taken by itself. 25 Q. In combination with other exhibits, what does Exhibit Five Linda L. Russo, RPR Official Court Reporter 133 1 help to inform? 2 A. It helps to inform you on a number of things. First, the 3 size of the sales and price responses, the time patterns of 4 those, if you put it together with Exhibit Six, which is done 5 on the margin data, and the reason -- one reason to look at the 6 margin data is because it covers a longer time span. We're 7 able to follow more events further out in time, past their time 8 of beginning. So we have confirmation of what we're seeing in 9 margins as indicated in prices, by Exhibit Five, so we can go 10 back now to Exhibit Six where we're using margins. We have a 11 broader set of data on which to base it. 12 And there we can see again the sort of relatively 13 large and initial quantity response that does not recover. And 14 in Exhibit Six-B we see a price response that then drifts 15 gradually up through time, but stabilizes well below where it 16 starts, even out A-plus quarters. So what's nice about the 17 margin data, because they cover a longer time span, they 18 allowed us to use additional events in covering a longer period 19 of time, and follow more events for a longer period. So we can 20 use that to sort of look further out from the entry event than 21 was possible, using the price data alone. 22 Q. If you would now turn to Exhibit Seven of your report, 23 which is in tab seven, Exhibit Seven tab of the binder counsel 24 gave you. You mentioned that you found -- 25 THE COURT: We're looking at the exhibit in the Linda L. Russo, RPR Official Court Reporter 134 1 report itself, Exhibit Seven, not what's on the screen, for the 2 moment. 3 MR. BLOOM: That's correct. 4 MR. BLOOM: 5 Q. I believe you testified that both produce and seafood, 6 that your findings were statistically significant at the 95 7 percent confidence level; is that correct? 8 A. I think usually people would refer to it as statistically 9 significantly different from zero at the five percent level. 10 Q. What was your finding with respect to meat? 11 A. For meat you get a P-value, I believe, of about 5.1, so it 12 would be just short of that five percent level. 13 Q. Short of it by? 14 A. I think a tenth of a percent, or so. 15 Q. And do you rely on the statistical significance, the 16 estimate for all departments? 17 A. I believe the estimate for all departments is informative. 18 Q. Let's go to what it is, it's .0070, and that's a point, a 19 percentage point estimate? 20 A. That's a percentage point of margins. 21 Q. Could you translate that to price, please? 22 A. That would, in terms of a price change at fixed cost, that 23 would give you about 1.1 or so. 24 Q. Do you think that's a sound finding? 25 A. I think it is -- on all these things, it is what it is. Linda L. Russo, RPR Official Court Reporter 135 1 It's a finding of minus .007 on margins, which translates to 2 roughly 1.1 or so, maybe a little bigger than that on prices. 3 The probability that you would get that large of an estimate 4 just by chance in that direction is about one in 12, which is 5 not that often. So under the no hypothesis of no effect, this 6 doesn't happen that often. It happens about one in 12. You 7 should take it as telling you exactly that. That's the 8 information that it has. 9 You combine that with other information, to reach a 10 conclusion about what you want to say. I don't know how to put 11 it any clearer than that. That is the thing about statistics, 12 and the reason the regression programs tell you the P-value is, 13 that is a nice way to summarize what information is contained 14 in that evidence. And you don't want to say it's more than it 15 is or it's less than it is. It is what it is. 16 Q. What are the price declines that you find with respect to 17 meat, produce, and seafood respectively? 18 A. They're larger. Doing arithmetic in my head is not 19 something I like. You have to divide those numbers by .6. If 20 you divide those numbers by .6, you're going to get a little 21 less than three for meat, you're going to get three and a half 22 I think for produce. You're going to get about 3.1 or 2 for 23 seafood. I mean, you want the exact number, divide by .6 24 roughly. 25 Q. Do your findings with respect to meat, produce and Linda L. Russo, RPR Official Court Reporter 136 1 seafood, surprise you in any way? 2 A. No. 3 Q. Are they consistent with your understanding of the way 4 competition works here? 5 A. Yeah. Those are departments where I might expect to see 6 these results. 7 Q. Why? 8 A. Those would be departments where the relative uniqueness 9 of Whole Foods and Wild Oats might be likely to show up. 10 Q. Can you in general summarize the nature of your findings 11 from your econometric work. 12 MR. FRIEDMAN: Object to the form. 13 MR. BLOOM: I'll withdraw the question. 14 BY MR. BLOOM: 15 Q. Does any of the discussion in your examination by 16 Mr. Friedman cause you to lose confidence in any of the 17 conclusions represented in your report? 18 A. No. 19 MR. BLOOM: No further questions. Thank you. 20 THE COURT: So are we done with Dr. Murphy, subject 21 to the discussion we're going to have immediately after lunch? 22 MR. FRIEDMAN: Would you like any recross, or have 23 you had enough? 24 THE COURT: Did we discuss at our pretrial discussion 25 whether we were going to have recross? Linda L. Russo, RPR Official Court Reporter 137 1 MR. FRIEDMAN: I don't think it came up. 2 MR. BLOOM: I don't believe it came up either, Your 3 Honor. 4 THE COURT: Let me tell you my thinking about that. 5 Obviously, in a normal -- Dr. Murphy won't like what I'm about 6 to say. In a normal trial, with any witness you would have 7 direct, you'd have cross, you'd have redirect. Recross is a 8 little more discretionary, I suppose. On the other hand, this 9 is our, other than the deposition testimony in which apparently 10 you asked a certain question 97 times. 11 MR. FRIEDMAN: It was only 62 times. 12 THE COURT: This is everybody's only opportunity, and 13 subject to his wife -- 14 THE WITNESS: I can make it back if you need me. 15 THE COURT: -- to discuss anything with Dr. Murphy. 16 So what I guess I would suggest to Mr. Friedman with respect to 17 Dr. Murphy and with you, Mr. Bloom, with respect to Dr. 18 Scheffman, if there's anything really, really crucial that we 19 can do briefly, I'll permit limited recross. 20 MR. FRIEDMAN: I don't think there's anything that's 21 really, really crucial, so I will pass. 22 THE COURT: That's my evidentiary standard. 23 MR. FRIEDMAN: I think I understand. 24 THE COURT: Okay, it is 20 minutes to one. I don't 25 know what arrangements everybody has made to eat lunch and Linda L. Russo, RPR Official Court Reporter 138 1 think about things, but we could agree to come back in an hour, 2 at a quarter to two, or we could agree to open the courtroom at 3 a quarter to two and have everybody who has reserved seats and 4 anybody who wants to come in after those with reserved seats, 5 to come in at a quarter to two, and then ask counsel to be in 6 their places by five to two. 7 The question is, do you want an hour, or do you want 8 an hour and ten minutes? I haven't added up how much time 9 everybody has taken so far, but recognizing that we have a 10 limited amount of total time for the day. 11 MR. FRIEDMAN: Your Honor, I think our preference 12 would be just an hour. 13 MR. BLOOM: We are at the Court's convenience. 14 THE COURT: So, in that case, we will open the 15 courtroom in 50 minutes, and anybody who wants to leave can 16 leave except for the lawyers, while we're talking about 17 logistics for one minute. 18 So we're going to lock the courtroom. We're going to 19 lock the courtroom because there's a lot of material here. And 20 we will open it in 50 minutes, and there will be somebody here, 21 and then we will start in 60 minutes. 22 (Proceedings concluded.) 23 24 25 Linda L. Russo, RPR Official Court Reporter 139 1 CERTIFICATE 2 I, LINDA L. RUSSO, Official Court Reporter, certify 3 that the foregoing pages are a correct transcript from the 4 record of proceedings of the morning in the above-entitled 5 matter. 6 7 8 _______________________________ Linda L. Russo, RPR 9 Virginia CCR No: 0313102 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 Linda L. Russo, RPR Official Court Reporter 141 < Dates > .6. 135:20 "may" 58:9 .67 91:14 July 16th 27:14 .7 100:9, 100:24, 101:1 July 26th 5:15 JULY 31, 2007 1:8 July 31st 101:13 < 0 > July 9 19:24, 20:4, 26:11 0313102 139:9 July 9th 27:10, 33:20, 41:7 07--10231 4:2 March 1 129:14 March 1, '04 129:16 $1 102:4 < 1 > $20 102:4 1 42:10 $45 76:12 1. 71:8 '04 127:2 1.1 74:25, 77:4, 78:4, 100:10, 134:24, 135:3 '05. 127:3 1.1. 100:25 .007 135:2 1.4 100:13 .0070 134:19 10 76:1, 80:21 .009 49:3, 49:18, 50:20 100 20:5 .020 49:19 10036 1:42 .029 49:6, 49:18, 50:13 105 111:18, 119:17 .029. 49:7 10th 101:14 .05 83:2, 85:20, 85:25 11 71:8, 72:16 .16 82:14 11,000 113:23 .1625 81:18, 85:17 11:13. 93:25 .6 135:21, 135:24 12 66:24, 74:20, 82:16, 82:24, 135:5 143 2.9 50:16, 50:19, 74:19 12. 135:7 20 9:3, 18:11, 113:2, 113:10, 137:25 122. 83:8 20,000 30:12 127 113:6 20001 2:15 13 66:25 20004 1:35 13th 27:12 20006 2:7 1455 1:34 2005 90:4 15 80:25, 81:2, 94:4, 94:5 2006 90:18, 92:18 16 81:3 2006. 56:7, 56:12 17 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25:13 58 56:2, 65:15 589 89:24, 91:8 < 8 > 589. 42:11 83. 84:21 59 56:3, 56:10, 63:16, 65:15 85 10:25, 13:8 5:00 121:9 < 9 > < 6 > 95 134:7 6 58:22, 116:1 96 44:16 60 65:15, 97:17, 138:22 97 3:6, 64:18, 64:21, 65:2, 87:24, 88:18, 89:2, 600 1:27 137:11 62 137:12 9:00 1:9 63 28:22, 33:14, 34:4 9:30 93:25 63. 34:22 64 35:24 6403 2:14 < A > 67 9:3, 9:6, 9:8 A-plus 133:17 A.M. 1:9 abbreviated 108:18, 109:7 ability 15:20, 15:24, 28:3, 46:19, 102:10, 115:2, 118:13 able 18:21, 27:8, 37:25, 47:11, 60:5, 66:9, 66:12, 67:9, 104:14, 113:20, 117:4, 122:10, 133:8 above 31:16, 31:19, 33:17, 49:5 above-entitled 139:4 Abramoff 14:5, 14:9 absence 35:8, 44:25 absolute 82:2 Absolutely 20:16, 110:10, 111:2 academic 39:21, 110:9 acceptable 44:2 accepted 43:14 accompanies 61:3 according 49:25 accounted 75:25, 100:20, 130:6 accounts 59:11 accurately 24:15, 45:13 acquisition 21:24, 22:10 across 65:21, 97:18, 98:20, 102:1, 104:8, 106:23, 108:6, 116:13, 129:12, 129:17 Act 18:9 151 advance 15:11 Action 4:2, 15:13 advertising 65:24 actual 61:21, 130:4 advised 120:1 Actually 5:14, 18:5, 23:19, 23:20, 26:25, affect 92:4, 117:24 31:14, 34:13, 40:11, 40:23, 47:22, 48:1, affected 118:8 48:19, 51:2, 51:16, 51:17, 59:7, 63:4, affirm 7:15 68:14, 70:9, 70:11, 72:17, 72:18, 72:21, affirmed 20:10 73:1, 73:2, 73:3, 83:6, 91:5, 92:1, 97:13, afraid 6:22 100:5, 100:12, 102:11, 102:13, 102:16, afternoon 7:11, 120:1, 131:5 110:17, 120:24, 125:16, 131:20 afterwards 117:13 add 27:8, 37:17, 44:24, 45:1, 48:13, 48:16, age 98:11 48:17, 49:18 agency 5:10 added 138:9 aggregate 74:7 addition 11:17, 15:14, 20:1, 36:15, 81:7 ago 65:13, 101:14, 113:6, 113:7 additional 7:16, 42:2, 47:17, 52:6, 92:23, agree 26:3, 32:25, 36:23, 52:6, 80:14, 80:15, 93:2, 95:1, 119:13, 121:23, 124:11, 133:19 80:18, 80:22, 81:23, 83:4, 83:11, 83:12, additions 16:21 94:3, 96:6, 138:2, 138:3 address 12:2, 31:15, 35:17, 36:1, 36:16, agreed 7:4, 7:12, 7:14, 9:1, 95:17 43:24 agreement 9:6, 9:16, 14:17 addressed 18:8, 23:8, 103:24, 103:25 agrees 16:21 adds 51:18 ahead 45:1, 119:15 adequate 115:10 Aid 18:22 adequately 26:1 air 124:1 adjust 61:17, 61:23, 114:21, 115:5 AL 1:10, 4:3 adjusted 60:5, 63:4, 63:6, 63:23, 63:25 albeit 67:4 adjustment 63:22, 115:9 Alden 1:32, 4:9, 9:13 alert 6:1 alignment 61:21 allow 117:8 allowed 133:19 Almost 99:3, 112:14, 112:20 alone 53:14, 132:24, 133:22 already 12:8, 51:5, 51:12, 52:6, 92:23, 93:16 alternative 82:10, 82:12, 82:18 Although 19:21, 21:9, 55:22, 66:3, 76:5, 108:24, 112:3, 132:19 altogether 95:11, 95:15 always. 44:23 ambiguous 79:21 ambush 119:10 amended 5:14 American 98:9, 98:11 among 90:20 amount 25:3, 62:15, 62:18, 62:21, 138:11 amounts 82:21 analogy 126:16 analyses 22:13, 23:10, 39:9, 39:18, 41:7, 104:8, 110:4, 111:15, 130:18 analytical 87:21 analyze 37:20, 56:15, 56:17, 98:4 analyzed 26:16, 34:7, 34:13, 34:16, 38:6 155 apples 63:14, 65:11 analyzing 30:6, 39:23 applicable 31:11 annotate 12:21 applied 80:17, 98:3, 113:19 announced 27:1, 104:17 applies 21:23, 22:8 announcement 27:7 apply 6:6, 21:25, 113:16 Answer 8:6, 15:7, 15:25, 25:22, 25:25, 26:2, Applying 89:4, 113:23 55:10, 64:2, 64:7, 64:16, 71:21, 72:5, appreciable 70:21 73:12, 78:1, 78:21, 92:11, 92:15, 93:20, appreciate 11:13, 11:20, 69:25, 83:25 102:20, 102:22 appreciated 120:8 answered 64:18 approach 16:13, 72:12, 72:20, 72:21, 94:14answers 64:19, 64:21, 65:2, 85:10, 85:11, appropriate 10:16, 11:2, 11:3, 15:13, 43:14, 95:13, 95:20, 118:13 43:22, 78:16, 84:25, 88:11, 90:16, 119:15anticipation 27:3 approximately 20:5 anticompetitive 31:7, 41:17 area 67:10, 97:19, 104:18, 118:15 antitrust 18:15, 51:10 areas 15:2, 40:24, 95:21 anybody 13:15, 97:14, 138:5, 138:16 argue 83:2, 83:9 anyway 93:4 argues 52:19 apart 106:25, 119:20, 119:22 arguing 8:9 apparently 66:3, 137:10 argument 11:2, 11:4, 122:1 Appeal 14:1, 121:21 arises 116:21 Appeals 123:11 arithmetic 116:15, 135:19 appear 12:3 Arizona 89:21, 90:1, 90:8 appearance 23:18 Aronson 1:39, 4:23 APPEARANCES 1:19 around 40:19, 43:15, 77:9, 113:23, 114:11, appearing 16:1, 16:2 126:22, 127:3 appellate 8:10 Arps 1:38, 4:22, 4:24 arrangements 138:1 array 88:5 aside 109:18, 122:17, 122:22, 131:22 asks 44:17, 45:4 assess 118:13 assessment 68:6 assets 37:2, 37:3, 37:6 assign 50:20, 59:20 associated 125:13, 130:23 Association 98:10 assume 7:3, 7:8 assumes 46:21 Assuming 60:25 ATKINS 1:32, 4:9, 9:13, 9:22, 10:7, 10:10, 84:4 attempt 47:1, 116:9, 125:6 attempted 11:9 attention 11:13, 11:20, 124:5, 129:1 attributable 52:25, 53:1, 53:5, 53:6 audio 5:18, 6:3 authorities 8:22 authorized 5:21 availability 66:20, 67:1 available 14:7, 28:9, 28:11, 66:17, 67:8, 119:3, 119:4 159 banner 23:11, 23:15, 23:18, 23:20, 24:1, AVENUE 1:27, 1:34 24:5, 26:7, 33:21, 34:1, 34:17, 35:9, 35:20, average 50:15, 50:18, 108:11, 108:13 36:3, 38:21, 42:18, 42:21, 54:1, 67:15, award 98:12 67:21, 68:6, 68:7, 68:10, 68:18, 89:16, awarded 98:10 90:4, 90:17, 91:10, 92:18, 93:18, 128:2awards 98:7, 98:8 banner. 36:18 aware 5:15, 33:15, 58:16, 91:25 bar 76:21, 76:24, 77:1, 78:3 awareness 92:1 base 133:12 away 54:23, 92:19, 93:13, 106:22 based 25:10, 38:2, 99:6, 124:6 basically 121:24 basis 6:23, 87:16, 88:4, 115:5 < B > Bates 98:9 B. 116:17, 116:20 became 102:16 back 6:22, 27:16, 28:17, 30:21, 30:25, 33:13, become 104:15 35:21, 39:1, 39:10, 39:13, 42:5, 42:9, 43:4, becomes 77:3, 91:25 61:19, 64:17, 64:19, 65:9, 65:15, 73:25, beer 76:10, 76:12, 76:21 82:25, 94:4, 95:2, 119:21, 120:4, 120:11, begin 16:22, 94:5, 118:3 121:9, 122:11, 122:18, 123:25, 125:15, beginning 71:7, 79:8, 97:5, 127:1, 127:2, 127:14, 127:24, 133:11, 137:15, 138:2 133:9 bad 101:18, 112:25, 113:3, 113:8 begins 72:16, 84:20, 84:21 badly 79:9, 113:5 behalf 4:7 bagger 59:6, 59:8 behavior 68:24, 69:2, 115:18 bags 59:21 belabor 96:18 bakery 86:7 below 31:13, 32:14, 32:15, 133:16 balance 123:15 best 27:7, 46:2, 79:16, 94:2, 118:7 bananas 59:22 better 21:9, 30:21, 63:18, 65:11, 77:15, 89:5, 106:4, 113:9, 125:16 beyond 10:9, 33:23, 66:25, 91:11, 92:23, 95:22, 95:25 bias 30:2, 30:5 biased 29:22 big 14:16, 51:14, 82:16, 93:12 bigger 100:12, 108:9, 109:15, 130:14, 135:3 binder 42:11, 131:9, 131:14, 133:24 binders 13:14 bit 24:21, 33:10, 40:22, 53:15, 57:1, 59:9, 97:16, 107:13, 112:3, 115:24 blurry 131:20 board 65:21 bold 92:3 Bolder 118:9, 119:12, 131:2, 131:4 bolster 96:12 book 84:17, 91:5 books 84:9 bottles 59:8 Boulder 27:2, 104:17 bounce 61:19 break 7:10, 7:11, 78:16, 84:7, 84:23 breakage 58:3 BRENNA 2:5 163 called 23:21, 42:11, 81:10, 84:13, 97:25Brennan 4:15 calling 11:13, 11:20 brief 9:15, 9:23, 11:5, 84:6 camera 5:16, 5:23 briefly 57:15, 78:12, 85:2, 85:12, 85:13, Cameras 5:16, 5:17, 5:23 137:20 capability 6:1 bright 45:17, 83:19, 114:8 caps 44:10 bring 28:17, 120:11, 122:10, 123:25 captioned 89:3 bringing 120:4 capture 69:12, 71:19, 125:6 broad 66:4 captured 69:5, 69:7, 71:25, 72:1 broader 36:23, 66:9, 66:13, 67:3, 133:12 capturing 115:17 broadest 70:12 care 8:25, 96:20 BROCK 1:22 cared 14:11 bunch 65:24 careful 32:13, 77:6, 82:9 burden 123:11 Carolina 27:5, 38:11, 38:13, 38:16, 67:7, business 92:2, 97:15 94:25, 95:12, 95:16, 95:25, 96:19, 120:18, but-for 99:1 120:19, 120:22, 122:11, 125:2, 125:21, buy 115:22 126:21, 129:12, 129:24 carry 105:17 Cary 125:22 < C > cases 8:10, 18:15, 35:19, 36:2, 36:17, 50:14, CA-07-1021 1:4 63:7, 98:25, 99:3 calculated 107:10 categories 11:23, 12:2, 12:9 calculation 60:4, 60:6, 99:23 Catharine 1:23, 5:4 calculations 117:25 cause 102:10, 119:1, 136:17 California 42:16, 44:4, 91:7 caused 47:16, 47:22, 48:4 call 16:8, 16:10, 26:5, 71:25, 72:1, 90:10 caused. 48:5 causes 48:1, 92:23, 127:13 causing 53:13 cautious 92:14 CCR 139:9 cell 5:23 Center 80:5, 80:10, 80:16, 80:20, 80:24, 81:20, 83:1, 83:6, 83:8, 84:9, 85:19 central 20:22, 21:4, 21:13 certain 9:1, 10:18, 14:6, 101:21, 110:3, 137:11 Certainly 5:20, 9:14, 46:5, 69:15, 88:16, 110:2, 115:7 CERTIFICATE 139:1 certify 139:2 challenge 19:7 chambers 10:2, 13:14, 84:14 chance 81:22, 82:1, 82:8, 82:15, 82:16, 82:17, 82:24, 83:4, 83:11, 114:21, 120:9, 120:10, 122:4, 122:6, 135:5 change 25:5, 36:6, 36:9, 43:7, 43:10, 47:2, 48:11, 48:12, 54:10, 79:4, 79:7, 79:12, 79:16, 99:10, 100:9, 100:22, 100:23, 107:13, 115:23, 127:25, 132:9, 134:23 changed 9:17, 43:4, 60:10, 99:5, 99:7, 107:4, 107:7, 107:9 167 cities 10:6 changes 25:4, 25:8, 25:15 city 11:18 Changing 36:7, 37:2, 37:3, 37:9, 106:7 Civil 4:2 Chapel 125:13, 125:14, 125:19, 125:25, clarify 56:8, 96:12, 96:21 127:7, 127:14, 130:1 Clark 98:9 chapters 84:11 Clayton 18:9 characteristics 107:7 clean 91:20, 103:1, 103:13 characterization 106:11, 106:13 clear 5:14, 8:6, 8:19, 13:6, 25:18, 35:7, characterize 24:15 49:22, 50:7, 54:14, 57:6, 62:22, 67:14, charge 45:25, 115:21 84:8, 102:16, 124:13 charged 7:19, 7:21, 13:25 clearer 135:12 chart 8:23, 12:7, 49:1, 50:3, 52:15 clearly 128:5 charts 9:2, 131:25 CLERK 4:2, 9:5, 10:2, 14:22, 15:21, 94:2, check 38:18, 39:13, 76:4, 107:10 94:16 checker 59:8 Cliff 4:23 chess 94:3 CLIFFORD 1:39 Chicago 41:25, 97:15 clock 93:25, 94:3 choose 36:18, 87:15, 88:3, 112:10, 112:11, close 6:18, 52:5, 52:10, 78:22, 113:1, 113:3, 112:12, 112:14, 115:19, 115:20 113:4, 127:11, 129:5 choosing 39:15, 77:9 closed 21:24, 22:4, 22:9, 56:11, 78:20, chose 31:15, 92:25, 93:5, 105:7, 115:19 111:23 CID 95:4 closely 126:1, 126:25, 129:2 circles 40:18, 40:20, 41:13 closer 52:10 circumscribed 43:15 closing 31:6 cite 129:25, 132:3 closings 31:16 cited 84:5 Club 128:1 co-efficient 81:21, 82:13 co-efficients 49:17, 116:8 Code 24:19, 24:20, 59:20, 60:10, 60:12, 77:5, 78:2 coded 102:6 codes 102:1 Coke 59:7 colleagues 123:7 Collins 53:3, 55:12, 55:19, 55:22, 56:1, 56:11, 57:7, 65:17, 66:4, 71:17, 89:21, 89:22, 90:17, 91:1, 117:1, 117:4, 117:5, 132:21 color 124:11 Colorado 27:2, 65:17, 67:9, 104:18 COLUMBIA 1:2 column 10:25, 15:16, 89:11 combination 99:10, 133:1 combine 135:10 combined 48:9, 48:12, 48:15, 50:25 combining 116:12 comes 30:25, 34:14, 50:13, 50:18 comfortable 123:8 coming 37:9, 126:9 comment 8:13 commented 29:15 171 130:24 Commission 1:4, 1:20, 4:3, 4:5, 5:1, 5:3, 5:5, complete 66:3, 104:15 5:7, 5:9, 12:19, 19:10, 24:16, 31:3, 41:12, completed 20:3 41:14, 51:21, 52:19, 75:13, 121:21, 123:21 completely 59:13, 88:12, 89:1 Commissioner 12:23 Completeness 16:16, 84:2 communicate 8:12, 12:6 complicated 14:12, 90:9 communicating 8:12 computer 5:17 comparative 22:25 COMPUTER-AIDED 2:48 compare 65:11, 126:9, 128:9 computers 5:18 compared 117:13 concentrated 51:9, 51:10 comparing 22:23 concentration 107:5 comparison 126:23 concern 20:22, 21:4, 21:13, 104:25 compete 45:24, 98:18, 98:22, 98:23, 109:12 conclude 127:16, 129:16 competed 126:5, 126:15 concluded 40:19, 129:15 Competition 20:23, 20:25, 21:5, 21:10, concluded. 138:23 21:14, 56:5, 64:9, 90:11, 98:17, 98:20, conclusion 32:6, 41:19, 128:24, 135:11125:3, 126:17, 127:18, 128:18, 130:23, Conclusions 11:7, 33:19, 65:21, 65:25, 66:4, 136:5 129:21, 130:17, 132:8, 132:10, 136:18 competitive 30:17, 58:5, 58:8, 61:3, 64:5, conditions 114:21 69:15, 92:7, 104:25, 105:11, 106:16, conduct 73:22, 74:2, 121:11 106:22, 112:7, 112:13, 129:13, 130:12 conducted 82:3, 99:1, 111:1 competitively 29:16, 32:3, 32:19, 105:3, conference 15:6 105:4, 105:7, 105:10, 112:2, 112:20, confidence 11:1, 13:8, 77:13, 134:8, 136:17112:24 confidential 7:6, 15:4, 15:11, 15:12, 124:2, competitor 30:18, 30:19, 126:4 131:15 competitors 51:11, 106:17, 128:16, 130:15, confidentiality 6:7, 9:15 configuration 43:23 confirm 12:20 confirmation 133:9 confounds 96:4 confusion 4:13, 100:16 Congressman 14:8 connected 5:18, 8:24 Connecticut 61:8, 61:20, 65:17, 73:18, 73:24, 74:3 connection 22:12, 75:11 consequence 32:6, 35:8, 99:9 consequences 123:20 consider 10:16, 28:7, 51:19, 97:21, 123:5, 123:18 considered 69:13, 69:14 consistent 42:7, 43:9, 110:6, 110:8, 130:8, 130:16, 130:19, 136:4 consistently 33:1 conspicuous 44:25 constant 25:3, 25:8, 25:10, 25:15, 46:14, 100:24, 108:6 constrain 45:25 constrained 91:2 constraint 35:12, 46:3 constraints 34:9, 35:2, 89:13 175 controlled 72:6, 72:20 consultancy 98:15 controlling 68:20, 68:22, 71:2 consulted 18:14, 97:9, 118:25 controls 37:2, 46:22, 68:25, 70:13, 70:15, consulting 18:12, 70:17 70:16, 70:18, 70:22, 70:24, 72:23, 73:3, consumed 115:8 129:7 consumer 63:12, 92:1, 114:18, 115:13, convenience 108:25, 138:14 115:14, 115:17, 115:21, 115:24 convenient 108:23 consumers 62:24, 87:15, 88:3, 91:25, conversation 9:5 114:20, 115:4, 115:18, 115:19 conversely 83:6, 83:9 contain 34:21, 89:9 convey 26:1 contained 40:12, 135:14 copies 14:20, 94:13, 94:17, 94:18 contemplated 35:18, 36:1, 36:16 copy 14:22, 14:25, 71:9, 83:24, 84:6, 84:14, contempt 6:5 94:16 context 36:25, 56:2, 56:21, 88:7, 88:8, 89:1, corner 7:7, 131:17 98:15, 115:11, 117:19 corrected 11:14, 11:15, 11:24 continue 79:13, 121:14, 121:15, 127:10 correcting 12:14 continued 121:16 corrections 16:22 contracts 98:19 correspondence 37:12 contrary 31:25 corresponding 63:21, 129:10 contributes 116:24 corroborate 51:23 contribution 116:5 corroboration 42:8 contributions 98:6 cost 60:4, 100:7, 100:10, 100:19, 100:20, control 37:5, 46:14, 47:1, 68:24, 69:1, 70:1, 100:24, 118:2, 134:23 70:3, 70:5, 70:9, 70:11, 70:12, 70:13, 71:2, Costco 128:6, 128:9, 128:10, 128:12 71:5, 72:3, 73:7, 73:13, 75:9, 125:20, costs 25:3, 25:7, 25:14 125:21, 125:25 Counsel 4:3, 5:9, 5:12, 5:21, 6:25, 7:8, 8:19, 9:11, 11:13, 11:20, 15:21, 28:5, 39:19, 121:16, 131:9, 133:24, 138:6 counting 86:10 couple 5:11, 25:18, 76:9, 98:8, 127:11, 129:25, 131:25 coupon 76:11, 76:18 course 6:14, 95:7, 96:22 COURTHOUSE 2:14, 5:19, 13:24, 13:25 courtroom 5:13, 5:20, 5:25, 6:6, 6:18, 6:19, 83:24, 138:3, 138:16, 138:19, 138:20 cover 133:18 coverage 117:10 covered 25:17, 96:10 covering 133:19 covers 67:3, 133:7 CRA 70:16 created 102:12 creatures 109:5 credibility 13:1 criteria 34:25, 41:16, 55:5 criterion 38:25 criticizes 70:2 Cross 3:2, 16:22, 22:24, 95:19, 95:22, 95:25, 96:10, 96:13, 137:8 179 deal 7:1, 7:9, 9:15, 51:15, 98:17, 98:25, CROSS-EXAMINATION 7:17, 11:2, 14:19, 122:5, 122:6, 122:8 17:19, 95:11, 121:5, 121:11 dealing 114:25 cross-examine 28:3 December 56:12, 90:18 cross-markets 116:9 Dechert 2:1, 4:7, 4:12, 4:15, 4:18 cross-sectional 37:15, 78:13 decide 29:19, 29:24, 115:21 cross-sectionally 102:9 decides 92:7 crucial 137:19, 137:22 decision 8:11, 113:14 customers 30:24, 108:23 declaration 58:16, 61:6, 75:7 cut 15:14, 30:23, 77:21 decline 74:21, 104:10, 104:11, 132:15 cut-off 39:15, 93:3, 113:15 declined 27:5 cuts 130:3 declines 74:16, 74:17, 74:18, 135:17 cutting 92:1 declining 92:8 decrease 118:8 deducted 58:11 < D > deemed 105:7 D. 1:33 Defendant 1:12, 1:31, 2:1, 42:11, 119:24damaged 59:13 defendants 6:9, 6:11, 9:11, 10:23, 27:17, datas 77:20 27:21, 40:9, 70:17, 70:19, 110:25, 117:20, date 56:15, 101:6, 104:13 117:25, 118:1, 118:21, 120:14, 122:4, dates 101:18, 101:21 123:19 David 14:4 defense 11:13, 39:19, 72:19, 83:9, 131:9day 16:21, 95:17, 114:23, 122:16, 129:11, define 87:18, 88:8, 88:9, 88:24 129:15, 129:18, 138:11 defined 44:13, 100:18 days 59:5, 113:11, 119:19, 120:4, 120:12 defining 106:9 deadline 9:25 Definitely 45:2, 104:2, 109:25 definition 19:20, 35:18, 36:2, 36:17, 36:24, 36:25, 37:2, 45:20, 46:16, 52:20, 60:8, 87:17, 87:22, 88:14, 88:15, 88:20, 112:20, 114:18, 128:17 definitions 44:2 deliver 10:1 demand 45:21, 46:19, 114:19, 115:13, 115:14 demonstrative 10:15, 11:3, 12:7, 12:11, 12:16, 12:22, 12:23, 15:10, 94:19, 124:14, 124:15, 124:16, 124:18 demonstratives 11:9, 121:3, 124:25 Denis 2:3, 4:7 denominator 100:22, 101:1 denote 125:11 dense 85:7 Denver 41:25 deny 121:25, 123:10 Department 19:12, 63:14, 63:17, 86:3, 97:15 departments 86:5, 86:9, 86:15, 86:17, 86:22, 86:24, 87:1, 87:2, 134:17, 134:18, 136:6, 136:9 depending 80:19, 114:25, 132:23 depends 25:11, 33:2, 53:7 depose 120:9 183 difficulty 112:4, 116:21 deposition 7:2, 14:24, 17:24, 18:20, 19:16, dimensions 57:3 27:16, 28:1, 42:25, 46:4, 64:1, 64:10, diminution 52:4 64:17, 65:1, 65:3, 73:1, 82:23, 93:17, dip 128:10 117:22, 119:10, 121:14, 122:16, 137:10 dips 128:11 depress 49:25 DIRECT 3:2, 7:17, 16:16, 16:24, 17:1, 20:18, described 24:25, 33:10, 103:2, 127:17 21:12, 22:12, 25:2, 25:13, 28:22, 31:25, desired 130:12 34:8, 35:1, 35:11, 35:15, 35:23, 35:24, destroyed 39:23 36:14, 47:18, 47:21, 87:25, 89:12, 96:12, detangling 120:23 124:5, 129:1, 137:8 determine 104:7 direction 58:10, 82:11, 109:3, 135:5 determined 95:3 directly 21:23, 22:8, 31:11, 31:20, 35:17, develop 121:23 36:1, 36:6, 36:16, 103:24, 111:13, 126:6, devices 5:18, 5:24, 5:25 131:22, 132:7 difference 39:16, 39:23, 41:21, 50:19, 52:13, disagreed 9:2 68:17, 70:22, 71:2, 72:24, 73:14, 77:22, disappear 34:10, 35:2, 35:13, 89:13 79:15, 81:8, 82:6, 87:3, 100:16, 103:8, disclose 13:10 103:11, 107:23, 107:24, 120:20, 128:15, disclosed 27:17, 27:20, 27:24, 27:25 128:25 discounted 59:17 differences 68:13, 68:16, 103:13 discounting 64:6 differencing 72:20 discovery 95:7, 121:17 differential 128:16 discrepancies 102:8, 102:9, 103:3 differentiated 98:21 discrepancy 103:4, 103:5, 103:6 differently 33:12, 99:7, 102:6 discretionary 137:9 difficult 37:24, 84:23, 102:19 discuss 8:20, 40:22, 79:17, 80:25, 81:3, difficulties 101:3 81:5, 100:9, 130:1, 130:2, 136:25, 137:16 discussed 13:13, 25:12, 52:17, 65:9, 83:25, 89:22, 90:7, 92:21, 92:22, 93:16 discussing 65:14, 88:9, 96:14, 118:15 discussion 28:10, 31:17, 96:9, 111:20, 131:6, 136:16, 136:22, 136:25 disentangle 116:10, 116:13 displayed 94:9 disregard 106:13 distance 40:7, 43:20, 43:22, 55:2, 55:3, 106:16, 106:18, 108:15 distant 108:12 distinction 63:11 distinguish 47:15 distressed 59:22 District 1:1, 1:2, 1:17, 123:13 divide 135:20, 135:21, 135:24 DOCKET 1:4 document 8:25, 72:10, 125:2, 130:11, 131:15 documentary 32:1 documentation 28:9 documents 14:10, 17:6, 129:23, 129:25, 130:11 Doing 14:13, 14:14, 27:25, 41:5, 66:7, 70:3, 75:21, 85:23, 87:22, 88:16, 91:25, 92:14, 94:2, 97:12, 107:14, 110:8, 113:5, 115:13, 187 117:22 119:11, 122:14, 123:8, 126:23, 135:19 DX-589 93:12 done 43:11, 67:11, 78:23, 98:14, 108:19, DX-625 91:5 111:3, 111:6, 115:24, 120:21, 121:10, 129:11, 129:16, 133:5, 136:21 door 5:13, 6:6, 7:25, 28:5, 95:16 < E > double 39:13 Earlier 65:9, 85:3, 92:21, 103:18, 104:16, down 31:14, 40:23, 42:15, 63:4, 63:15, 112:5, 114:12, 118:15, 123:5 63:18, 70:12, 99:3, 113:1, 113:3, 113:4 Earth 95:12, 96:2, 124:7, 125:9, 125:11, downward 61:17, 109:13, 132:16 126:3, 126:4, 126:11, 127:3, 127:7, dramatic 127:4 127:12, 128:4, 128:11, 128:19, 128:21, draw 8:1, 29:24, 30:10, 31:1, 32:15, 32:16, 129:20, 129:24, 130:4, 130:13, 130:16, 33:1, 33:4, 33:7, 33:8, 33:11, 66:1, 105:5, 131:1 106:2, 114:12, 114:13 easy 77:8 drawing 32:25, 66:4, 114:14 eat 138:1 drawn 30:11, 130:17 econometric 22:13, 23:10, 24:4, 24:8, 24:9, drew 30:8, 40:18, 41:11, 41:13 26:6, 32:1, 37:13, 38:5, 38:20, 41:7, 43:10, drift 132:16 46:25, 53:20, 79:3, 97:23, 136:12 drifts 133:15 econometrics 97:20, 97:21 drops 78:4 economic 18:1, 33:20, 45:23, 51:13, 57:4, Ds 34:11 70:17, 107:8 due 83:3, 83:10, 95:7 Economics 97:18, 98:6, 98:9, 105:14, 109:6, duration 66:15 110:13, 117:16 Durham 125:19, 125:24, 127:10, 127:12, economist 5:10, 18:12, 98:11, 102:14, 121:8, 127:13 121:10, 128:23 during 6:13, 7:10, 71:21, 84:23, 112:25, economists 69:17, 69:22, 103:7 effected 69:5 effective 119:22 effectively 122:6, 122:9 effects 25:9, 25:16, 31:10, 41:17, 48:14, 48:16, 48:18, 69:15, 96:3, 100:4, 100:5, 100:6, 100:7, 100:12, 100:13, 108:9, 108:10, 116:10, 116:22, 130:22, 131:20, 132:17 effort 15:15, 111:5 efforts 79:1 eight 51:14, 61:15, 61:25 Eight. 104:5 either 14:15, 15:20, 40:10, 45:25, 54:25, 81:3, 82:1, 82:10, 95:13, 105:3, 107:18, 113:3, 128:11, 137:3 elaborate 25:23 electronic 5:24 electronically 16:1 elicit 15:3 elicited 95:20 eliminate 29:23 eliminated 103:3, 103:5 eliminating 112:9, 129:8 Elkins 1:31, 4:9, 4:19 elliptically 94:12 191 equilibrate 115:1 empirical 31:10, 31:20, 42:6, 73:11, 73:13, equilibrium 114:21 97:22, 102:14 error 11:21 empirically 100:3 errors 11:17, 123:12 enable 15:16, 96:11 ESQUIRE 1:21, 1:22, 1:23, 1:24, 1:25, 1:26, enables 96:15 1:32, 1:33, 1:39, 1:40, 2:2, 2:3, 2:4, 2:5end 13:22, 66:21, 79:8, 87:21, 110:17, estimate 47:25, 49:13, 55:16, 116:18, 112:19 116:19, 134:17, 134:18, 134:20, 135:4 ended 42:7, 56:25, 75:21 estimated 26:7, 54:11 ends 77:23 estimates 62:1, 68:3, 68:4, 75:4, 75:5, 77:9engagements 18:17 ET 1:10, 4:3 enough 20:20, 75:25, 94:18, 117:8, 120:14, evaluate 120:15 136:24 event 26:23, 27:7, 28:23, 30:13, 47:16, ensuing 25:18 49:15, 49:16, 50:21, 55:21, 56:4, 56:16, ensure 15:13 56:17, 69:7, 69:17, 71:23, 89:21, 90:10, enter 54:10, 73:6, 116:11 92:12, 92:16, 103:16, 103:19, 104:14, Entered 26:24, 34:5, 48:7, 48:8, 49:10, 50:5, 104:16, 116:7, 117:11, 117:15, 125:13, 50:14, 50:15, 51:25, 56:5, 61:8, 89:10, 127:12, 129:20, 130:1, 133:21 104:2, 116:12, 127:8, 128:24 Events. 42:12 entering 74:8 eventually 59:8, 90:10 enters 49:2, 61:18, 71:21, 127:24, 128:1 everybody 5:13, 5:15, 94:4, 137:13, 138:1, entitled 7:13, 131:16 138:4, 138:10 entries 34:17, 53:6, 53:7 everything 13:14, 15:25, 16:21 enumerator 100:21, 101:1 Evidence 7:4, 10:19, 10:20, 12:5, 13:15, equal 102:3 13:21, 32:2, 34:14, 35:9, 80:6, 83:20, equations 119:19 84:14, 84:16, 84:19, 121:20, 121:23, 123:9, 123:22, 124:14, 124:17, 124:19, 130:13, 132:22, 135:15 evidence. 3:13 evidentiary 123:17, 137:23 exact 37:11, 120:21, 135:24 Exactly 23:23, 25:17, 32:5, 32:22, 34:23, 43:20, 50:24, 51:22, 79:5, 79:10, 101:7, 116:8, 120:18, 135:8 EXAMINATION 16:24, 17:1, 97:1, 136:16 examine 118:22, 120:3 examined 70:8, 129:23 example 23:14, 29:18, 30:10, 31:14, 33:15, 34:5, 41:25, 55:4, 61:10, 61:11, 61:19, 63:13, 66:7, 66:21, 73:17, 75:15, 81:12, 81:14, 81:16, 88:21, 89:11, 100:14, 100:25, 102:4, 107:10, 107:14, 107:25, 108:6, 109:2, 109:4, 113:18, 115:16 exceeded 38:21 except 6:23, 59:21, 138:17 excerpt 91:5 excess 32:7 exchange 62:24 exclude 30:3, 30:4, 31:4, 39:3, 39:11, 121:18, 121:25, 123:9 195 105:13, 119:6, 126:18, 130:20 excluded 39:6, 39:8, 123:21 explained 32:22, 43:7 exclusion 104:22, 123:13 explicitly 25:12, 46:13, 47:1, 68:23, 69:1, exclusively 111:11 88:23, 90:7 exercise 24:4, 50:23 exploring 28:8 Exhibits 3:12, 3:13, 7:1, 7:2, 10:15, 10:19, expressed 17:15 13:20, 13:21, 13:23, 14:6, 14:7, 14:21, extended 11:19, 33:23 34:7, 35:16, 53:17, 66:7, 68:3, 94:11, extensively 89:23 94:13, 124:16, 124:18, 133:1 extent 34:8, 35:1, 35:11, 37:6, 53:24, 89:12, exited 28:24, 33:16, 90:10 96:12, 121:22 exiting 34:6 extra 9:9, 76:12, 94:16 exits 34:1, 34:17, 34:24, 53:24, 54:18, 54:22, extraordinarily 102:16 89:16, 92:4, 93:11, 93:13, 93:18 extrapolate 128:21 exogenous 69:17, 69:22 extrapolating 65:20, 132:8 exogenously 112:9 expect 61:2, 63:5, 78:8, 79:3, 92:3, 102:2, 102:3, 105:14, 105:21, 106:3, 108:5, < F > 108:13, 109:14, 112:8, 115:5, 119:16, face 98:16 136:6 Faced 125:3 expectation 61:19 Fact 9:15, 10:19, 11:12, 13:13, 13:23, 30:23, expected 58:4, 58:7, 116:1 31:24, 36:7, 39:22, 51:11, 51:16, 66:2, experience 8:9, 18:12 71:3, 74:6, 89:7, 89:16, 93:5, 94:10, 96:10, expert 7:15, 7:16, 17:10, 18:1, 19:1, 19:3, 100:3, 124:21 19:6 factor 103:10 experts 119:19 factors 117:24 explain 41:10, 48:6, 50:7, 92:13, 100:17, facts 124:20, 124:22 failed 12:18, 12:19 failure 13:9, 13:10 Fair 20:20, 20:21, 75:25 fairly 28:23, 33:15, 90:8, 120:24, 126:25 fairness 8:14, 89:2, 119:13 fall 63:23, 127:4, 127:5, 127:13, 127:14, 130:5, 132:18 fall-off 127:21 falls 127:16 familiar 80:5 far 31:14, 93:13, 109:18, 117:8, 138:10 Fare 95:12, 96:2, 124:7, 125:9, 125:11, 126:3, 126:4, 126:11, 127:4, 127:7, 127:12, 128:4, 128:11, 128:19, 128:21, 129:20, 129:24, 130:4, 130:13, 130:16, 131:1 fashioned 16:3 fast 63:6 faster 63:5, 115:1 favorite 55:25, 57:16, 79:17, 117:18 feasible 88:2 February 92:18, 118:9 Federal 1:4, 1:20, 4:2, 4:5, 4:25, 5:2, 5:5, 5:7, 5:9, 12:19, 12:23, 19:9, 24:16, 31:3, 41:12, 41:13, 51:20, 52:19, 75:12, 80:5, 80:10, 199 filtered 77:11, 103:12 80:16, 80:20, 80:24, 81:20, 83:1, 83:6, filtering 77:5, 77:11, 77:12, 77:25 83:7, 84:9, 85:19, 121:20, 123:20 finally 128:6 feel 96:24, 119:9 find 27:4, 44:19, 45:6, 48:9, 86:13, 100:3, feeling 128:11 100:11, 110:20, 135:17 feet 7:22, 29:7, 29:13, 29:19, 31:5, 31:11, finding 116:24, 120:1, 128:21, 130:16, 31:17, 31:19, 32:8, 32:22, 33:4, 33:5, 130:22, 134:11, 134:25, 135:2 33:17, 38:21, 39:4, 39:7, 39:11, 54:19, Findings 124:21, 126:18, 134:7, 136:1, 54:23, 55:14, 104:23, 114:10 136:11 fell 50:9, 50:12 fine 13:3, 41:3, 64:15, 72:11, 101:19, 107:17felt 105:4, 126:15 fire 61:22 fetch 58:1 firm 37:15, 38:2, 44:18, 45:5, 45:25, 69:11, few 19:22, 41:25, 53:16, 61:4, 76:15, 95:13, 71:5, 73:8, 92:6, 116:5, 126:5, 126:7, 97:6, 106:4 126:8 field 98:6 Firms 45:24, 46:18, 46:23, 49:21, 50:8, fields 97:18 50:12, 51:5, 51:6, 51:7, 51:11, 51:14, figure 37:25, 56:19, 114:23, 115:25, 116:1, 52:24, 53:4, 53:10, 53:12, 53:22, 67:15, 121:10, 125:23, 127:23 67:22, 73:6, 96:3, 98:18, 107:11, 115:19, figured 7:8 126:9 figures 132:14 First 10:17, 11:24, 12:3, 17:25, 23:16, 42:15, file 9:25, 10:2, 121:3 62:5, 62:12, 62:13, 62:22, 66:6, 66:12, filed 19:6, 20:1, 101:15 66:23, 78:21, 89:25, 90:1, 91:16, 101:4, filing 8:25 114:23, 115:23, 115:25, 116:6, 117:19, filings 6:12 117:22, 122:14, 125:8, 125:12, 126:1, filled 7:2 127:2, 127:24, 129:1, 132:15, 132:17, filter 75:23, 77:1, 77:23, 78:2, 102:15 133:3 first-come 6:23 first-serve 6:23 Fishkin 2:4, 4:17 fit 7:13, 41:7, 49:16, 89:16 Five. 47:8, 68:9, 131:18, 131:23, 132:8 fix 61:22 fixed 100:7, 100:10, 134:23 FLOM 1:38 Florida 93:1 focus 19:22, 31:3, 31:15, 31:17, 65:16, 77:17, 98:3, 114:18 focused 53:14, 65:14 focuses 45:21 focusing 34:3, 34:15, 66:1, 91:16, 114:19 folks 95:2 follow 15:16, 31:24, 66:22, 66:23, 66:24, 67:13, 108:25, 132:19, 133:8, 133:20 following 64:1, 64:2, 123:2, 123:9 food 6:11, 23:12, 115:8 foot 89:18, 90:5, 92:19, 113:15, 113:24 footage 32:7 for. 72:6 forces 58:10 foregoing 139:3 foremost 125:9 203 frequent 115:5 forgot 72:18 frequently 115:9 form 15:8, 117:16, 136:13 fresh 67:21 format 67:6 front 16:18, 16:19, 48:24, 58:20, 64:25, 72:9, Fort 30:13, 30:14, 53:3, 55:12, 55:19, 55:22, 72:10, 86:12 56:1, 56:11, 57:7, 65:17, 66:4, 71:16, FTC 6:11, 9:5, 9:16, 14:21, 37:20, 119:1489:21, 89:22, 90:17, 91:1, 92:18, 93:1, full 55:17, 56:14 93:6, 117:1, 117:3, 117:5, 132:21 fundamentally 99:5 forward 13:19, 99:8, 99:10 furthest 132:20 fought 122:13 future 99:11 found 29:14, 41:16, 51:24, 61:16, 76:10, 77:10, 77:24, 86:15, 86:20, 87:2, 102:7, 133:25 < G > Four 1:41, 24:9, 24:24, 30:11, 34:7, 34:16, gathered 132:11 34:19, 34:20, 34:21, 35:11, 40:14, 46:11, gave 60:20, 64:2, 77:12, 122:15, 131:10, 47:5, 48:13, 53:17, 54:1, 54:3, 54:4, 54:15, 133:25 55:8, 55:20, 59:19, 62:14, 67:18, 67:20, general 92:13, 99:18, 112:18, 125:20, 67:21, 68:3, 68:5, 89:9, 91:17, 127:23 126:14, 136:11 Four. 18:5, 24:7, 34:13, 35:5, 47:6, 89:15, Generally 57:25, 75:17, 95:24, 98:17, 97:8 106:21, 110:22, 112:5, 116:9, 126:22, fourth 26:6, 89:11 128:22 fraction 100:19, 100:22 generate 130:7 frame 24:22, 67:8, 87:21 generated 104:9, 104:18 Franchak 1:26, 5:6, 5:7 geographic 40:20, 41:8, 43:14, 43:18, 43:19, frankly 117:12, 119:9, 121:7 44:2, 96:8, 96:9, 96:14, 96:15, 109:17free 44:24 geographically 52:10 gets 63:12, 63:18 getting 6:22, 11:14, 64:4, 82:15, 82:24, 108:10, 112:16, 112:17, 114:11 give 10:1, 10:4, 14:22, 26:2, 48:15, 63:13, 94:15, 94:22, 119:13, 120:3, 120:14, 120:16, 123:6, 132:22, 134:24 Given 44:18, 44:21, 45:5, 55:15, 87:25, 103:8, 121:2 giving 114:20 goal 14:14, 15:5 golf 14:5 goods 60:4, 64:4, 88:3 government 84:5 governs 9:9 gradual 92:4 gradually 133:16 grant 122:5 graph 125:18, 128:5, 128:7 graphing 125:16 great 64:5, 82:7, 94:16, 112:7, 113:10 greater 54:23, 55:13, 78:10, 82:7, 83:10, 106:24, 106:25 green 9:3, 9:7, 9:9 groceries 126:22 grocery 23:12, 86:7 207 handed 124:23 gross 23:12, 25:4, 132:10 hands 9:23, 11:16 ground 8:17 happen 28:13, 47:10, 66:2, 115:22, 135:7group 70:3, 70:5, 70:17 happened 48:7, 50:8, 66:20, 99:7, 126:7groups 70:10, 70:11, 70:12, 70:13, 125:22 happens 33:11, 99:24, 132:15, 135:7 grows 115:3 happy 45:11, 45:14, 84:4 guess 14:12, 15:25, 55:2, 56:2, 56:3, 56:24, hard 61:16, 121:8 57:22, 65:15, 111:7, 137:17 Hartford 61:7, 61:20, 62:5, 62:12, 65:14, guidance 10:5, 10:7 65:16, 65:17, 73:17, 73:24, 74:3, 74:11, Guide 80:11, 80:24, 82:25, 84:15, 84:19, 74:16, 74:20, 75:9, 76:8, 76:9, 76:23, 77:2, 84:20 78:3, 132:20 Guideline 83:8, 114:10 head 58:18, 62:7, 135:19 Guidelines 20:23, 21:5, 21:13, 35:18, 36:2, head-to-head 126:15 36:16, 36:24, 36:25, 44:12, 46:16, 46:17, headed 125:2 46:21, 114:18, 114:20 heading 89:3 guy 37:5, 113:10, 113:11 hear 12:24, 13:3, 85:2, 85:4, 122:20 guys 43:12 heard 117:23 HEARING 1:15, 6:14, 6:15, 14:13, 19:16, 90:21, 122:7, 122:9 < H > heaviest 97:14 H-e-r-f-i-n-d-a-h-l 107:19 heavily 51:9 H. 1:22, 1:39, 2:2 height 119:23 habit 109:5 Hello 97:3, 97:4 half 62:6, 62:12, 62:14, 62:15, 103:10, 114:8, help 37:10, 116:13, 133:2 114:9, 122:24, 135:22 helpful 10:8, 37:18, 72:9 hand 30:2, 137:9 helps 56:19, 133:3 Hendrickson 1:40, 4:21 Herfindahl 107:14, 107:15 high 14:2 higher 36:11, 36:21, 59:9 highlight 67:2 highlighting 9:8, 9:10 highlights 9:4 highly 121:19, 123:13 Hill 125:13, 125:14, 125:19, 125:25, 127:7, 127:14, 130:1 historical 99:6 hold 12:12, 46:14 holding 100:23 home 13:23 honest 39:2 HONORABLE 1:16 hope 5:15, 13:4, 78:22 hopefully 57:15 hour 122:24, 138:2, 138:8, 138:9, 138:13 hours 7:13, 20:5 housekeeping 8:19 huddle 121:10 hypothesis 79:10, 81:23, 82:10, 82:12, 82:18, 135:6 Hypothetical 37:4, 43:24, 44:13, 44:17, 211 imperative 46:23 44:18, 45:4, 45:5, 46:21, 89:4, 100:14, implications 115:10 123:9 Implicitly 82:10, 104:4 implied 100:12 imply 68:4 < I > important 13:10, 33:1, 34:11, 41:24, 52:14, idea 92:2, 111:6 52:17, 54:9, 82:14, 92:5, 109:5, 114:1, ideas 92:13 121:18, 123:21, 126:3, 128:20 identification 117:16 impose 44:19, 45:6 identified 11:11, 126:4, 126:5, 127:23 imposed 40:1 identifier 59:21 imprecise 83:12 identify 4:4, 17:9, 90:11, 95:7, 117:12, Improper 64:13, 102:5 130:24 in-fill 93:15, 93:16 idiosyncrasies 76:7, 76:24 in. 6:22, 27:6, 50:12, 113:9 idiosyncrasy 75:15 inadvertently 11:19 Ignoring 74:22, 74:24 inaudible 6:2 illustrates 128:14, 130:21 Inc 4:3 immediately 95:6, 136:22 INC. 1:10 impact 20:23, 20:25, 21:5, 21:10, 21:14, incentive 91:23 22:16, 22:18, 22:21, 23:2, 23:11, 24:5, inclined 96:6, 121:18, 123:1 26:7, 33:9, 49:20, 51:12, 58:12, 65:25, include 12:19, 12:20, 29:20, 30:1, 54:4, 67:15, 67:21, 73:9, 73:16, 90:11, 112:8, 54:15, 54:20, 54:24, 55:7, 55:19, 69:15, 113:20, 116:4, 117:15, 125:9, 125:17, 106:5, 107:13, 108:12, 109:6 126:8, 126:22, 129:8 included 30:2, 30:5, 30:6, 41:23, 42:2, 43:12, impacts 125:12, 126:9 53:21, 53:25, 54:6, 55:21, 55:22, 55:23, impeachment 64:13 66:16, 69:12, 90:12, 104:4, 106:3, 106:5, 108:11, 109:9 includes 59:12, 95:19, 131:17 including 5:16, 58:24, 62:2, 97:18 inclusion 32:23 inconsistency 64:14 inconsistent 130:17 inconvenient 109:10 incorrect 11:12 incorrectly 23:7 increase 44:20, 45:8, 45:15, 61:13, 101:2, 114:4 Increased 125:3 incur 54:17 independent 69:11, 69:18, 69:21, 71:3, 71:5, 71:23, 73:6 independently 49:12, 116:18 INDEX 3:1, 17:5 indicate 11:10, 15:10, 18:14 indicated 18:11, 133:10 indicative 102:5 indicator 12:11, 25:8, 25:16, 90:12 individual 60:24, 87:19 individuals 5:22 indulgence 10:1 215 interaction 106:16, 106:24 industrial 97:19 interactions 106:23 industry 115:11, 115:12 interchanged 132:5 infer 25:4, 68:2 interest 14:2, 91:18 inference 31:12 interested 21:10, 37:22, 80:19 inferences 8:1, 99:20 interesting 51:2, 51:4, 83:13, 102:11, 128:8inform 133:2, 133:3 interpret 82:23, 83:20, 116:8 information 10:19, 12:4, 13:7, 13:10, 15:4, interval 129:22 47:17, 66:2, 66:3, 80:18, 80:21, 95:3, investigation 19:10, 19:13, 98:16, 117:2095:13, 99:21, 116:13, 118:3, 118:4, investigational 90:21 122:11, 132:10, 135:9, 135:10, 135:14 involved 18:17, 19:7, 97:6 informative 67:17, 88:13, 99:23, 114:2, involving 59:21, 126:3 134:18 Irvine 42:16, 42:23, 44:3, 55:6, 55:7, 91:7, informed 9:10 111:20, 111:21, 111:23 ingredient 99:22 issue 11:24, 12:2, 30:7, 35:17, 36:1, 36:9, initial 20:3, 22:12, 111:9, 111:13, 133:14 36:13, 36:16, 37:8, 38:19, 65:22, 88:12, initially 132:18 92:9, 95:11, 105:25, 118:11, 120:6 injunction 8:23, 121:25, 122:5, 123:10 issued 5:15 inquire 95:11, 96:2 issues 6:7, 6:8, 18:1, 97:19, 98:3, 98:16, inquiries 117:24 98:17, 98:24 insight 116:3 item 115:7 instances 9:10, 11:10, 14:24, 100:4, 110:1 items 5:21, 59:12, 59:21, 60:1, 115:8, 130:3, instead 51:25, 63:15, 69:22, 77:4, 107:3 130:7 intend 121:15 itself 132:25, 134:2 intended 121:14 intention 15:9, 119:2 < J > J. 1:21, 1:24, 1:25 Jack 14:5 James 2:4, 4:17 January 90:4 Jeff 4:15 JEFFREY 2:5 jet 14:8 Joes 51:25, 73:23, 74:3, 113:21, 113:22, 113:24, 113:25, 114:1 John 1:33, 4:19, 98:9 Judge 1:17, 14:3, 120:25 Judges 8:3, 8:7 Judicial 80:5, 80:10, 80:16, 80:20, 80:24, 81:20, 83:1, 83:6, 83:7, 84:9, 85:19 July 27:12, 101:14 Justice 19:13 < K > keep 13:24, 13:25, 28:8, 30:24, 58:9 keeping 13:25, 41:13 kept 93:3 KEVIN 3:6, 16:10, 16:11 219 105:22, 135:19 key 13:15, 105:25 largest 130:22 kind 5:16, 24:4, 29:22, 37:1, 65:19, 92:10, last 9:10, 9:16, 11:23, 15:6, 61:4, 77:3, 78:4, 98:1, 98:2, 98:24, 99:18, 108:8, 108:10, 90:1, 95:18, 101:11, 131:3 117:16 lasts 114:5, 114:8, 114:9 kinds 57:18, 98:16 late 56:7 King 71:17, 71:21, 91:2 later 13:17, 30:21, 107:20, 114:13 Kitchen 18:22 latter 93:2 knowledge 111:3, 111:5, 117:22, 118:7 Lauderdale 30:13, 30:14, 92:18, 93:1, 93:6known 59:12, 60:15, 61:14, 62:3, 62:5, 62:8, Law 9:5, 11:7, 15:21, 94:2, 94:16 62:11, 62:13, 62:16 lawyer 7:14, 7:20, 7:21, 64:12, 121:8 Kroger 128:2, 128:13 lawyers 7:12, 8:1, 69:21, 138:17 lead 43:18, 44:1, 115:9 learn 113:20, 132:12, 132:25 < L > learned 104:12 L. 1:16, 1:32, 2:12, 139:2, 139:8 least 7:10, 8:9, 16:24, 62:19, 82:16, 103:8, labeled 91:17 111:18, 120:8, 122:15 lack 65:10, 65:19 leave 6:20, 44:23, 59:10, 106:4, 112:10, LANG 1:25, 5:2, 9:7 112:11, 112:12, 112:14, 113:7, 138:16, laptop 5:16, 5:18 138:17 laptops 5:24 leaving 56:25, 119:7, 120:11 large 62:19, 83:9, 83:13, 85:21, 102:8, 102:9, led 43:17, 44:1 103:2, 103:3, 103:5, 103:11, 103:13, left 44:22, 112:12 133:14, 135:4 left-hand 15:15 largely 7:23, 53:19 lens 43:10 larger 29:7, 29:13, 62:2, 81:22, 85:24, 100:5, less 29:23, 31:6, 79:3, 80:20, 91:20, 92:10, 92:21, 100:1, 105:4, 105:15, 105:16, 105:19, 105:21, 105:24, 106:22, 112:1, 112:3, 112:4, 112:8, 112:13, 112:19, 112:24, 115:6, 135:16, 135:22 lessening 75:3 letter 81:12, 103:9 level 11:1, 13:8, 24:6, 24:12, 24:13, 31:13, 79:18, 79:24, 80:1, 80:12, 81:9, 83:16, 86:3, 86:20, 86:21, 87:3, 88:10, 134:8, 134:10, 134:13 Libby 14:3 life 112:19 lightning 13:4 likely 99:9, 109:3, 112:2, 136:10 likes 102:14 likewise 46:9, 53:3 limit 15:20, 40:2, 55:2, 95:18, 96:13 limited 21:25, 32:6, 38:20, 137:20, 138:11 limiting 29:6, 29:9 Linda 2:12, 139:2, 139:8 line 11:19, 28:5, 29:24, 30:8, 30:10, 30:11, 31:1, 32:16, 32:17, 32:25, 33:1, 33:4, 33:7, 33:8, 33:11, 45:18, 61:15, 71:8, 72:16, 83:19, 105:5, 105:7, 106:2, 114:8, 114:12, 223 logs 103:7 114:14, 126:25, 127:11, 129:3, 129:6, long 81:25, 101:6, 101:7, 101:16, 108:22, 129:19 109:23, 111:23, 126:25 lines 125:11, 126:20 long-run 115:14 linked 71:22 longer 66:8, 78:18, 133:7, 133:18, 133:19, liquor 86:8 133:20 listed 46:7, 46:10 longevity 96:3 literally 105:11 looked 27:16, 38:10, 38:14, 54:1, 86:5, litigation 31:3 86:15, 86:22, 89:9, 103:2, 104:6, 105:6, little 33:10, 40:22, 53:15, 78:23, 85:24, 110:19, 111:18, 117:13, 129:13, 130:2491:22, 97:16, 107:13, 112:3, 112:4, Looking 23:19, 29:1, 29:14, 30:11, 36:9, 113:12, 115:23, 125:15, 127:6, 127:25, 37:22, 53:11, 68:17, 76:5, 76:14, 79:19, 128:1, 129:9, 135:3, 135:21, 137:9 91:6, 99:8, 109:17, 113:24, 116:9, 120:5, living 97:24 124:24, 125:4, 132:24, 134:1 LLP 2:1, 4:7, 4:18 looks 36:7, 67:7, 67:24, 71:11, 128:19, load 97:14 131:20 locales 79:13 lose 136:17 located 42:22 loss 57:2, 58:24, 121:12 location 30:21, 57:10 lost 57:20, 59:16 locations 70:7 lot 51:5, 51:6, 51:7, 91:3, 97:22, 98:1, 98:17, lock 13:14, 138:19, 138:20 102:7, 102:10, 102:12, 103:14, 128:19, lodge 13:16 138:20 log 103:8 lots 51:11, 51:12 logical 128:23 loud 45:3 logistical 6:21 low 83:3 logistics 7:9, 15:18, 138:18 lower 30:12, 63:5, 63:24 lowest 77:21 luck 78:23, 78:24 lunch 7:11, 122:18, 123:7, 123:18, 136:22, 138:1 < M > M. 1:23 MACHINE 2:47 magnitude 25:5, 81:21, 103:6, 104:20, 127:5, 128:9, 128:10 mail 76:18 main 14:7 Maine 62:13 major 21:17, 22:2, 41:21, 52:13, 99:22 majority 132:15, 132:17 man 14:4, 121:11 management 58:24 manager 61:22 managers 61:17, 61:18 Manhattan 108:3 Manual 80:6, 84:13, 84:16, 84:18 manuals 83:25 mapping 108:17 maps 40:23, 42:5 227 73:4, 93:5, 105:14, 107:22, 122:9, 139:4Margins 22:16, 22:18, 22:22, 23:2, 23:13, mattered 40:6 24:6, 24:10, 25:15, 26:20, 47:22, 48:2, matters 5:13, 8:20, 10:11, 10:16, 11:8, 18:4, 49:2, 49:6, 49:20, 49:24, 49:25, 50:5, 39:21, 73:5, 96:5, 97:7, 97:10 50:11, 54:2, 58:11, 58:12, 60:22, 67:16, MATTHEW 1:24, 1:40 67:24, 68:7, 79:4, 82:6, 99:23, 104:10, MEAGHER 1:38 133:10, 133:11, 134:21, 135:2 mean 23:15, 31:9, 36:13, 52:10, 77:6, 87:19, mark 63:15, 63:18 100:8, 100:10, 100:20, 105:11, 109:21, mark-down 60:10, 63:3 115:13, 119:17, 129:5, 135:24 mark-downs 63:20 meaningful 119:22, 121:11 marked 48:23 means 29:5, 45:15, 50:24, 56:19, 69:4, 82:5, marketplace 23:18, 36:8, 46:18, 51:5, 82:13, 82:16, 108:7, 108:8, 114:5, 119:19, 105:17, 114:22, 114:25, 126:8, 126:10, 120:4, 129:7 127:19 meant 37:7, 56:25 Martin 58:15, 58:22, 59:11, 59:15, 59:19, measure 48:11, 60:22, 60:25, 61:1, 72:2, 59:24, 61:6, 61:25, 62:18, 65:14, 75:7 108:14, 108:15 masked 75:21 measures 23:25, 125:17 match 101:25, 102:6 meat 86:7, 134:11, 134:12, 135:18, 135:22, material 72:19, 84:2, 84:3, 84:23, 120:15, 136:1 131:15, 138:20 mechanical 50:23, 60:15 materially 36:11, 36:21, 72:25 meet 38:25, 41:16, 93:3 materials 90:20, 124:23 memorandum 8:22 math 85:23 mention 56:1, 111:17, 119:12 mathematics 103:9 mentioned 57:14, 92:24, 101:3, 116:25, Matt 4:21, 4:25 117:20, 118:6, 133:25 matter 19:3, 19:4, 20:5, 54:7, 57:4, 71:3, merge 18:24 merger 18:1, 18:6, 18:7, 18:20, 18:22, 19:4, 19:7, 19:10, 19:13, 19:16, 20:23, 21:4, 21:13, 21:17, 31:8, 36:1, 97:9, 98:16, 99:8 mergers 18:18 message 64:23 met 17:23, 18:20, 34:25 metal 98:9 methodological 117:9 methodology 27:4, 120:18 metric 108:16 metrics 98:1 Michael 1:21, 1:26, 15:9 middle 119:16, 121:5 midway 42:15 Mike 4:5, 5:6 mile 40:1, 40:13, 41:1, 41:6, 41:12, 41:17, 42:7, 42:24, 43:2, 43:4, 43:8, 43:15, 55:5, 92:19, 106:8, 107:3, 107:4, 107:25, 108:2, 108:18, 108:22 miles 29:10, 33:18, 40:6, 40:19, 42:24, 43:10, 43:22, 54:19, 54:23, 55:13, 57:7, 71:17, 79:6, 79:12, 89:18, 90:5, 91:11, 91:12, 91:14, 106:25, 108:7, 108:16, 109:8, 109:24, 109:25 mind 9:17, 10:9, 58:9 231 115:23, 115:25, 127:2, 127:11, 129:2, Minus 49:7, 49:18, 49:19, 50:13, 50:16, 132:15, 132:17 50:18, 50:19, 53:2, 100:18, 135:2 Moon 7:9, 94:8, 94:15, 94:21 minute 6:25, 71:1, 74:11, 138:18 moot 95:10 minutes 53:16, 78:23, 85:8, 85:10, 94:4, Morning 4:11, 4:17, 4:21, 4:23, 5:2, 5:4, 5:6, 94:5, 137:25, 138:9, 138:16, 138:21, 5:11, 7:10, 9:19, 9:21, 10:2, 10:4, 16:12, 138:22 17:3, 17:4, 17:21, 17:22, 84:24, 85:2, 85:4, mislabeled 131:19 118:22, 119:4, 120:14, 121:4, 123:5 misleading 12:10, 25:8, 25:15, 87:14, 88:2 Moscatelli 1:23, 5:4, 5:5 misleading. 88:19 mostly 41:24 missing 9:12 motion 8:21, 8:23, 9:14, 121:25, 123:10mission 126:14 MOTIONS 1:15, 121:3 misspoke 72:17, 73:1, 83:7 mouthful 72:8 mix 66:13, 105:17, 105:18, 105:20 Move 28:2, 63:5, 63:6, 67:13, 76:20, 76:21, mixed 108:9 77:9, 77:19, 131:3 mixing 111:25 moved 13:15, 13:21, 126:22 model 53:17 movements 125:20, 129:9 moment 7:1, 65:13, 67:11, 106:7, 109:18, moving 65:6, 65:7, 77:18 117:17, 119:2, 134:3 Ms. 5:4, 7:9, 94:8, 94:15, 94:21, 107:20monitors 15:12, 15:14, 124:3 Multiple 42:1, 53:4, 80:11, 80:24, 82:25, Monopolist 37:4, 44:13, 44:17, 45:4, 46:21, 84:19, 94:17, 116:21 89:4 mushes 101:21 months 11:18, 61:4, 61:8, 61:20, 66:23, myself 15:21, 97:21 66:25, 74:13, 74:15, 74:19, 74:20, 75:8, 111:25, 112:1, 112:15, 112:22, 112:23, 112:25, 113:6, 113:7, 113:11, 114:9, < N > name 128:25 named 14:4 namely 112:13, 125:24 narrower 105:18, 105:20 narrowest 70:13 natural 87:6, 87:11, 103:9, 107:5, 109:20, 115:12, 127:22, 128:22 nature 106:20, 106:21, 121:19, 136:11 near 42:23 nearby 109:19 nearest 108:3 necessarily 33:2, 52:3, 63:21, 77:15, 102:2 necessary 95:21, 110:25 need 6:13, 8:20, 10:12, 14:22, 56:16, 78:22, 94:20, 96:24, 98:2, 119:5, 123:15, 137:15 needed 105:5 needs 14:25 negative 74:19, 74:25, 77:8, 77:21, 82:2, 82:13, 82:17, 82:19, 82:24 net 100:25 New 1:42, 12:2, 29:18, 47:19, 47:22, 47:25, 48:1, 48:4, 48:7, 48:14, 48:17, 49:2, 49:9, 49:13, 49:15, 49:24, 50:4, 50:20, 51:8, 51:19, 52:1, 52:17, 53:1, 59:20, 63:19, 69:10, 73:8, 74:8, 104:17, 107:11, 114:21 235 notate 13:9 news 113:12 notation 10:24 newspapers 8:12 note 56:23, 84:5 next 5:13, 6:6, 7:25, 9:3, 69:10, 89:25, 108:3 notebook 14:20 Ney 14:9 notebooks 7:2 nice 77:10, 102:14, 102:21, 133:17, 135:14 noted 57:10, 75:8, 95:2 night 9:23 notes 80:16 nine 31:15, 51:14, 86:5, 86:8, 86:15, 86:22 noteworthy 56:11, 57:1 nobody 15:1, 120:8 Nothing 16:1, 79:2, 79:3 noise 77:13, 77:14, 77:23, 102:10, 102:12, Notice 10:14, 20:12, 48:5, 76:7, 83:15, 102:15, 103:1 115:22, 126:24 nondurable 115:7 noting 56:18, 56:20 None 18:6, 18:7, 18:8, 20:12, 34:20, 39:18, null 81:23, 82:12 94:11, 124:23 Number 6:8, 21:18, 21:22, 22:7, 30:11, 39:1, nonetheless 98:23 41:12, 48:13, 51:10, 54:18, 54:22, 55:1, nonsignificant 29:23 57:13, 62:7, 91:19, 104:6, 107:14, 108:13, nontransitory 44:20, 45:8, 45:15, 45:19, 129:2, 130:3, 130:6, 133:3, 135:24 114:4, 114:5, 114:12, 115:2 numbers 43:8, 107:9, 107:13, 109:10, Nor 46:16 109:13, 109:14, 124:23, 135:20, 135:21normal 13:21, 137:6, 137:7 North 27:5, 38:10, 38:13, 38:16, 67:6, 94:25, 95:12, 95:16, 95:25, 96:19, 120:18, < O > 120:19, 120:22, 122:11, 125:2, 125:21, oath 20:13 126:21, 129:12, 129:24 Object 95:23, 96:23, 102:19, 106:11, 136:13NORTHWEST 1:27, 1:34, 2:6 objecting 64:12 Notably 128:13 Objection 10:22, 12:6, 15:1, 64:11, 79:21, 80:3, 86:18, 95:1, 95:10, 118:11, 123:3, 123:25 objections 10:15, 10:17, 12:13, 13:16, 95:9 observation 53:14, 75:17, 76:13, 77:17 observations 34:20, 34:22, 34:24, 76:10, 76:15, 77:18, 77:21 observe 76:23 observed 118:9 obtain 24:16, 80:13 Obviously 55:1, 96:23, 102:9, 137:6 occur 31:16, 79:12, 127:9 occurred 18:24, 56:7, 56:16, 69:18, 81:22 occurs 59:16, 128:2, 128:6, 132:17 odd 76:15 offer 34:8, 35:1, 35:5, 52:11, 89:12 offered 35:11 offering 52:13 office 95:2 Official 2:13, 139:2 often 98:21, 99:16, 105:17, 135:6, 135:7 oftentimes 100:11 Okay 5:11, 10:11, 13:11, 16:5, 17:8, 17:12, 19:6, 25:2, 28:15, 31:22, 34:3, 39:6, 47:5, 47:9, 47:18, 54:18, 60:2, 61:13, 62:4, 239 opposed 12:22, 15:22, 67:4, 79:8, 131:2167:11, 68:5, 69:4, 69:22, 71:16, 76:22, opposing 121:16 78:24, 85:1, 86:2, 90:20, 96:24, 108:15, oral 19:15 125:4, 137:25 oranges 65:12 old 16:3, 60:9, 63:19, 63:20, 64:4 order 5:14, 9:18, 24:3, 30:24, 32:17, 56:16, older 29:15, 32:2, 32:19, 105:10 61:17, 61:21, 61:22, 105:5, 114:7, 117:10, omits 12:11 125:20 on-line 84:11 Oregon 49:9, 49:23, 50:21, 51:4, 62:15, one. 22:17, 57:14, 89:24, 94:18, 94:19, 108:1, 109:18 125:4, 137:25 organic 87:7, 87:11, 107:5, 109:20, 115:12, ones 32:13, 72:22, 73:2, 73:3, 92:23, 108:11, 127:22, 128:22 132:5, 132:19 organization/antitrust 97:19 ongoing 28:1 original 131:11 open 6:16, 10:9, 14:14, 15:17, 27:1, 31:18, originally 30:14, 92:22 111:23, 138:3, 138:15, 138:21 others 9:2, 14:10, 109:1 opened 28:5, 113:5, 113:6 otherwise 109:13, 113:9 opening 23:16, 104:18 ought 15:3, 16:17, 52:19, 84:2 opens 95:15 outcome 8:15 operate 35:19, 36:3, 36:18, 79:14 outcomes 70:23 operated 39:3 outlier 75:15, 75:17, 76:6 operating 38:20, 39:20, 107:11 outliers 75:11, 75:21, 75:22, 75:24, 75:25, Operations 58:23 76:4, 76:7 opinion 13:20 output 39:18, 39:22 opinions 17:15, 19:24, 20:2 outputs 83:14 opportunity 25:23, 28:3, 28:16, 84:1, 84:3, outraged 121:6 119:22, 120:3, 137:13 outside 42:24, 43:2 outskirts 108:1 outstanding 98:10 over-optimistic 61:18 overall 75:18, 88:14, 89:20, 108:13, 130:7 overlap 21:23, 22:8, 41:16, 42:1, 78:10 overnight 122:10 own 13:23, 109:4, 119:25 owned 39:3, 109:21 owners 115:20 ownership 36:7, 36:10, 36:11, 36:20, 37:9, 79:12 owning 78:9 < P > P-value 81:10, 81:17, 81:18, 81:20, 82:4, 82:6, 83:13, 83:15, 83:17, 85:17, 85:19, 85:22, 85:23, 134:12, 135:13 P-values 83:2, 83:9, 85:16 P. 1:40 packet 132:1 page 9:2, 9:6, 9:8, 17:11, 35:22, 42:15, 71:7, 71:8, 71:12, 72:16, 80:10, 83:8, 84:20, 84:21, 89:25, 90:1 pages 9:3, 139:3 243 particularly 30:18, 91:16 Paging 5:25 parties 8:14, 8:16, 9:1, 9:6, 11:12, 24:20, paper 14:20, 14:25, 73:2, 100:9, 110:13 60:17, 68:25, 70:2, 89:8, 95:4, 113:16, papers 97:17, 97:22 113:19 Paradise 90:22, 90:25 partly 105:15 Paragraph 21:1, 25:13, 28:22, 31:25, 32:18, parts 84:18 33:14, 34:4, 34:22, 35:21, 35:24, 44:16, party 7:19, 10:20, 68:24, 69:1, 69:4 47:18, 56:10, 58:22, 59:11, 59:15, 59:19, pass 137:22 59:24, 61:6, 61:13, 61:25, 87:24, 88:18, past 99:7, 99:11, 99:19, 133:8 89:2 pattern 104:9 paragraphs 52:15, 56:2, 65:15 patterns 102:13, 104:8, 108:25, 109:4, 133:4parameter 29:7, 29:9 Paul 1:16, 2:2, 2:3, 4:7, 4:11, 12:1, 14:18parameters 28:25, 29:3, 29:5 Paul. 81:12 Pardon 29:2, 74:23 pause 125:15, 126:2 parking 91:3 pay 76:12 part 36:13, 48:23, 53:4, 53:6, 58:9, 60:10, PDF 12:3 63:20, 64:7, 64:8, 71:19, 84:16, 95:3, peel 119:20, 119:22 97:24, 109:5, 110:22, 114:18, 114:20 penalties 20:14 partial 57:17, 57:22, 59:15, 59:21, 59:25, penetrate 84:23, 85:7 60:3, 60:5, 60:6, 60:9, 60:23, 61:3, 61:7, PENNSYLVANIA 1:27, 1:34 62:1, 62:2, 62:20, 62:22, 63:2, 63:7, 63:11, People 5:22, 6:9, 6:20, 6:22, 29:15, 29:16, 63:12, 117:17, 117:21, 118:6, 118:8 45:18, 46:20, 51:13, 52:6, 63:19, 91:21, particular 10:25, 23:16, 24:1, 31:4, 33:6, 92:6, 95:5, 99:18, 105:2, 108:9, 109:1, 36:19, 43:5, 61:11, 67:2, 70:10, 82:11, 109:2, 109:5, 112:6, 112:10, 112:11, 91:21, 96:8, 96:9, 96:14, 115:12, 119:1, 112:12, 112:19, 112:21, 112:23, 113:4, 130:1 113:12, 114:12, 114:13, 114:22, 115:2, 116:11, 126:5, 130:23, 134:9 percent 11:1, 13:8, 27:6, 44:20, 45:7, 50:1, 50:9, 50:12, 50:16, 53:2, 62:6, 62:13, 62:14, 62:15, 74:20, 74:21, 75:1, 76:1, 77:4, 78:5, 80:1, 80:14, 80:17, 80:21, 80:25, 81:2, 81:3, 81:5, 81:9, 83:16, 86:20, 86:21, 87:3, 100:11, 104:21, 127:6, 134:8, 134:10, 134:13, 134:15 percentage 134:20, 134:21 percentages 100:17 perceptible 128:3, 128:13 perfect 51:13 perfectly 13:8, 120:20 performed 23:11, 24:4, 39:14, 40:5 perhaps 12:4, 13:19, 26:5 period 26:25, 27:3, 45:18, 55:16, 66:8, 66:11, 66:17, 66:19, 71:21, 73:24, 74:20, 74:25, 75:3, 77:3, 78:4, 112:24, 115:15, 126:1, 126:25, 129:1, 133:19, 133:20 periods 74:17 periphery 41:23 perishables 60:9 perjury 20:15 permit 53:12, 137:20 247 players 127:19 permitted 5:19, 5:20, 5:22, 6:1 Please 4:4, 17:5, 17:11, 45:1, 72:13, 105:13, persist 45:16 126:18, 131:15, 134:22 persisted 61:7 PLF 1:4 persistent 104:11 plus 49:18, 116:16, 116:17, 116:19 Ph.d 121:8 PNOS 51:7, 126:4, 126:17, 127:19, 130:24phenomena 52:17 point 7:3, 13:13, 24:1, 25:19, 30:22, 31:1, phones 5:16, 5:17, 5:23 33:24, 34:14, 37:11, 41:21, 46:4, 60:24, photograph 14:8 75:4, 96:11, 105:5, 106:2, 107:8, 112:18, Photographic 6:2 116:4, 120:23, 120:25, 123:16, 123:17, picked 61:10, 109:20 128:18, 134:19, 134:20, 134:21 picture 75:19, 102:16 point. 96:18 pieces 27:9, 132:21 pointed 105:9 pile 124:22 points 8:22, 100:15, 100:17 pinkish 125:10 policy 59:25 place 30:9, 31:1, 51:15 portion 78:19 Places 53:9, 103:12, 106:21, 106:23, 106:24, Portland 51:4, 62:13, 107:11, 107:25, 108:1, 108:8, 138:7 116:7, 116:23, 116:24 PLAINTIFF 1:6, 1:20, 3:5, 83:2 posed 130:13 PLAINTIFF'S 16:11 positive 47:25, 49:3, 50:4, 77:8, 82:2Plaintiffs 8:22, 20:4 possess 5:22 plan 6:15 possibility 118:23 planning 14:19, 119:13 possible 11:22, 14:14, 15:7, 61:5, 133:22play 30:3 post 55:16, 56:16, 74:12 played 14:5 post-exit 117:11 player 23:16 potential 27:7, 30:12, 123:20, 130:4, 130:15 potentially 29:4 pound 63:15, 63:16 practice 59:25, 99:18, 110:6, 110:8, 121:1, 123:16 practices 61:23 pre- 117:11 precise 101:6, 107:9 precisely 37:7, 43:19, 48:15, 49:17, 89:17, 101:10, 111:24, 127:3 predicate 79:7 preference 138:12 preliminarily 13:11 Preliminary 5:12, 8:17, 8:18, 8:20, 8:23, 10:11, 121:19, 121:25, 122:3, 122:5, 123:10 premium 87:6, 87:10, 107:5, 109:20, 115:11, 127:21, 128:22 prepare 15:6 prepared 9:21, 15:1, 86:7, 123:18, 123:25 preparing 117:7 presence 23:21, 53:15, 53:17, 53:19, 54:4, 54:12, 68:25, 70:2, 105:16 present 12:10, 23:20, 74:1, 74:6, 81:17, 92:9, 110:13, 110:18 presentation 19:9, 19:12 251 print 83:17 presented 19:25, 22:13, 23:3, 24:8, 24:9, prior 6:13, 11:15, 34:15, 35:8 24:23, 26:7, 26:10, 26:16, 33:19, 35:1, private 14:8 35:12, 38:6, 38:7, 68:21, 70:10, 71:6, probability 81:21, 82:6, 82:15, 83:3, 83:10, 89:12, 111:4, 121:20, 132:11 135:4 presenting 110:17 probable 60:21 presents 34:9 Probably 69:14, 72:17, 79:16, 79:17, 80:15, preserved 39:24, 40:16 94:21, 97:14, 97:17, 102:5, 106:25, President 58:23, 90:22 110:20, 112:3, 112:4, 112:15, 112:24, press 14:6 113:11 prestigious 98:12 probative 13:9, 82:18, 96:4, 96:20 presumably 12:20, 107:1, 109:10, 113:4 problem 16:2, 32:17, 61:7, 75:8, 76:6, 93:16, pretrial 136:25 117:9, 117:10, 119:1 Pretty 29:25, 31:1, 32:16, 44:25, 113:8, problems 6:21, 91:19, 92:23, 98:3, 101:23, 115:22, 126:25, 129:21 102:20 prevent 102:12 procedural 123:17 prevention 58:24 procedure 39:20, 77:22 previously 60:21, 61:2, 100:16 proceed 124:1 pricing 24:17, 24:19, 24:24, 27:3, 30:19, proceeding 10:21, 108:18, 109:8, 121:19, 30:22, 37:6, 38:1, 46:5, 46:9, 46:14, 65:24, 122:3 68:24, 69:1, 73:20, 73:23, 76:24, 101:4, Proceedings 2:47, 6:3, 6:13, 8:15, 8:16, 101:5, 119:11, 125:10, 129:12, 130:1, 138:23, 139:4 130:5 process 11:14, 110:22, 120:19 primarily 111:11 produce 63:14, 63:17, 86:8, 86:24, 87:6, primary 91:18 134:6, 135:18, 135:23, 136:1 principle 29:25, 61:13, 108:8, 108:14 PRODUCED 2:47, 37:21, 39:19, 75:12, 89:9 producers 37:5 Product 19:20, 24:20, 44:13, 45:20, 51:20, 52:20, 57:20, 57:25, 59:16, 59:20, 62:24, 63:1, 63:12, 87:7, 87:11, 88:20, 88:24, 89:4, 98:22, 102:3, 103:12, 114:17 product-by-product 87:14, 87:16, 87:18, 88:1, 88:4, 88:10, 88:11, 88:13, 88:15, 88:25 products 44:19, 44:21, 45:6, 52:11, 52:12, 87:19, 87:25, 88:5, 98:21, 102:2, 103:3, 103:5, 105:18, 105:20 products. 45:8 professional 98:15 Professor 16:10, 17:3, 97:3, 118:25, 119:25, 120:4, 120:5, 121:13, 122:10, 124:5, 125:6 profitable 44:19, 45:6 programming 120:22 programs 111:18, 119:18, 135:13 prohibited 6:4 promised 118:20 promotional 46:6, 46:10, 46:14 promotions 46:22, 47:2 pronunciation 107:16 proof 123:11 proposed 10:15, 34:10, 35:3, 35:13, 41:12, 255 83:15, 83:16, 84:3, 94:7, 94:11, 102:22, 41:14, 81:2, 89:14 109:11, 124:3, 133:5, 135:11 provide 14:20, 14:21, 46:2, 80:18, 80:21, putting 14:15, 15:22, 89:5 82:14, 84:12, 85:5, 116:3, 118:20 puzzle 27:9 provided 19:15, 95:7, 101:4, 118:3 PX 95:5 proximity 34:25, 40:2 Px'd 95:5 proxy 108:22, 109:8 PX-2878 17:7, 17:9, 20:9, 21:1, 22:13, 26:11public 6:12, 8:25, 13:20, 13:22, 14:2, 14:6, 14:17, 15:8, 124:3 publication 84:10 < Q > publications 18:8, 97:16 quality 60:11, 63:4, 63:6, 63:21, 63:22, publicly 94:9 63:23, 63:24 publish 97:22, 110:13 quantified 31:10 published 14:23, 83:1, 97:17, 97:21, 98:1 quantities 115:20 purchase 88:5, 115:8 quantity 115:16, 115:17, 115:22, 131:20, purchases 115:4 133:14 pure 67:4 quarter 48:11, 49:10, 52:1, 55:17, 56:14, purporting 12:12 62:5, 62:12, 62:14, 138:3, 138:4, 138:6purports 79:4 quarters 133:17 purpose 114:14 questioned 131:8 purposes 7:5, 13:18, 14:1, 14:13, 14:19, questioning 28:6, 96:16, 96:22 87:20 questions 7:20, 7:22, 8:2, 8:3, 8:4, 8:5, 8:7, purveyors 6:11 15:3, 15:7, 19:22, 25:21, 25:22, 27:15, push 109:12 28:17, 64:18, 78:17, 85:10, 85:16, 87:20, put 10:12, 15:1, 15:19, 16:17, 16:18, 22:6, 87:23, 93:23, 95:20, 96:1, 96:2, 136:2031:4, 46:2, 49:14, 55:2, 72:18, 79:16, quibbling 106:8 quibbling. 106:12 quickly 11:21, 115:23 quite 24:21, 37:24, 41:25, 49:14, 51:4, 57:1, 59:8, 72:8, 78:15, 102:14, 128:16 quote 45:13, 97:25 < R > radii 43:15 radius 40:1, 40:19, 41:1, 41:6, 41:18, 41:22, 43:4, 106:8, 107:3, 107:4, 107:25, 108:2, 108:22 raise 13:12, 30:20, 91:1, 100:24, 100:25 raised 121:16 raising 92:1, 92:2, 101:1, 123:17 Raleigh 125:19, 125:24, 127:10, 127:12, 127:13, 128:8, 128:9 ran 58:12 range 42:24, 43:2, 66:9, 67:3, 85:22, 97:11, 97:17, 97:18, 98:20, 130:7 rapid 115:9 rapidly 115:6 rates 61:17, 61:21 Rather 13:16, 37:9, 42:5, 42:8, 51:18, 85:7, 88:4, 99:13, 132:7 259 110:4, 111:21 reach 135:10 receipt 98:7 reached 14:16, 33:19 receive 24:22, 62:24 read 32:24, 45:3, 47:24, 59:4, 60:2, 61:24, received 3:13, 8:21, 10:14, 17:6, 20:18, 64:19, 64:21, 71:7, 71:15, 80:9, 85:21 24:19, 28:18, 37:23, 38:7, 68:15, 98:8reader 110:17, 110:18 receiving 20:14 reading 70:21 recent 26:25, 28:23, 33:15, 33:21, 34:5Ready 16:5, 16:6, 94:23 Recently 27:1 real 107:23, 108:21, 111:7, 120:6 Recess 94:6 realize 34:11, 54:9, 82:14 recognize 81:25, 118:24, 121:18 really 14:11, 29:20, 31:15, 75:18, 77:12, recognized 98:7 77:17, 85:22, 97:18, 98:2, 98:3, 101:18, recognizing 138:10 102:12, 103:13, 104:15, 105:25, 108:22, record 4:4, 9:1, 29:15, 35:7, 61:24, 84:3, 109:12, 114:16, 115:17, 117:15, 118:16, 105:2, 121:22, 124:17, 124:19, 126:5, 120:15, 127:25, 128:11, 128:14, 128:16, 139:4 132:20, 137:19, 137:22 recorded 60:15 reason 32:22, 83:23, 85:1, 85:3, 92:6, 93:2, recording 5:18, 5:24 93:8, 112:6, 112:13, 133:6, 135:13 recordings 6:3 reasonable 43:17, 109:8 recover 133:14 reasons 8:6, 57:13, 59:1, 91:21, 118:3 Recross 3:2, 136:23, 137:1, 137:8, 137:20rebound 132:18, 132:20, 132:21, 132:22, redact 10:5 132:23 redactions 9:1, 9:17 rebuttal 38:8, 40:18, 43:13, 111:8, 111:9, REDIRECT 3:2, 7:18, 95:16, 95:18, 96:11, 111:14, 122:13, 122:14, 124:6 97:1, 119:23, 137:8 recall 40:13, 58:18, 75:7, 76:6, 76:25, 101:6, redo 41:6, 42:5, 42:9 101:10, 101:16, 103:17, 104:23, 106:9, Reduced 131:16, 132:1, 132:2 reduces 132:13 reducing 21:18, 21:22, 22:7 reduction 56:21, 56:22, 56:23, 56:24, 60:11, 63:7 reductions 130:6 refer 15:15, 20:19, 33:17, 134:9 Reference 80:6, 80:11, 80:24, 82:25, 83:8, 83:25, 84:15, 84:19, 84:20, 87:17, 131:3 references 10:6 referred 60:14, 104:16 referring 34:12, 35:21, 56:6, 84:9, 89:15, 129:3 refers 88:22 refine 109:14 refined 108:14 reflagged 90:9 reflect 20:1, 79:15 reflected 19:24 reflective 118:2 reflects 60:11, 79:12 regard 88:16, 130:8 regarded 57:25 regarding 59:25 region 41:23, 70:14 Regional 90:22 263 reliable 90:12 regions 41:24 relocate 30:15, 30:16 Regression 23:19, 24:3, 49:12, 49:15, 49:16, relocated 90:9 50:23, 53:11, 54:8, 54:11, 68:23, 71:4, relocation 92:22 72:4, 73:8, 73:9, 73:25, 77:3, 80:11, 80:25, rely 12:22, 78:24, 79:1, 134:16 83:1, 83:14, 84:20, 88:21, 89:1, 119:17, relying 12:4 135:13 remain 7:5, 15:17, 17:15 regressions 50:17, 53:21, 58:13, 85:6, Remember 18:5, 18:21, 47:19, 59:4, 59:5, 113:15, 116:3 62:7, 63:11, 70:8, 75:9, 76:5, 76:11, 76:14, regret 11:21 89:14, 90:22, 99:22, 101:7, 101:20, Regular 57:17, 57:23, 57:25, 62:23, 63:12, 111:24, 114:16, 115:17 110:6 remove 60:3, 60:5, 60:18, 60:20 REILLY 1:24, 4:25, 79:21 removed 60:14, 60:16 relate 11:9 removing 77:16 related 104:25 rephrase 79:22, 79:24 relates 10:22, 98:15 replicate 111:1, 111:15 relating 94:25, 124:7, 129:23 replicated 111:16 relationship 106:15, 106:18, 106:19, 106:20, REPORTED 2:47, 37:16, 60:16, 82:4, 85:23, 126:11 86:2 relationships 98:19, 108:12 Reporter 2:12, 2:13, 44:8, 94:18, 139:2relative 126:21, 136:9 reports 20:1, 20:12, 20:14, 38:6, 57:11relatively 83:3, 83:10, 133:13 represent 62:11 relevance 52:5, 52:7 representative 25:14, 75:18, 110:14, 110:15, Relevant 21:18, 22:8, 30:6, 31:21, 40:20, 112:11 43:18, 70:23, 87:7, 87:11, 89:3, 96:10, representatives 6:10 96:17, 97:24, 112:2, 118:5, 121:17 represented 40:20, 136:18 representing 23:16 request 14:10, 101:4 requested 118:4 require 78:19 required 26:2, 80:12, 119:8 requirement 11:3, 89:17 requirements 89:20 requires 100:22 research 98:5, 110:23, 110:24 reserve 6:24 reserved 138:4, 138:5 resolve 12:5 respect 16:4, 19:19, 49:22, 70:24, 94:24, 101:3, 101:23, 104:12, 119:11, 134:11, 135:17, 136:1, 137:17, 137:18 respectively 135:18 respond 30:19, 46:18, 91:22, 91:23, 91:24, 130:12 responded 128:15, 130:12 responds 127:18 response 27:15, 45:21, 47:2, 64:3, 64:5, 64:8, 64:9, 69:13, 69:14, 71:24, 84:6, 95:14, 104:19, 104:20, 114:19, 115:24, 129:13, 130:2, 130:3, 130:7, 130:14, 133:14, 133:15 267 roles 98:20 responses 10:20, 15:3, 69:4, 69:7, 95:4, ROOM 2:14, 7:25, 13:24 115:15, 115:22, 130:15, 133:4 roughly 18:16, 18:17, 24:15, 27:6, 45:18, responsibility 58:24 49:19, 52:21, 76:3, 82:15, 126:1, 135:3, restate 35:23 135:25 result 6:5, 34:10, 35:3, 35:13, 40:13, 41:5, round 64:22 73:9, 79:18, 79:25, 80:13, 81:7, 82:7, 83:3, rows 6:24 83:10, 86:16, 86:21, 89:14 RPR 2:12, 139:8 results 12:9, 26:10, 29:22, 30:2, 30:5, 40:9, Rule 9:19, 9:20, 10:3, 77:18, 84:2 40:11, 40:12, 40:14, 40:16, 44:1, 51:25, Rules 6:6, 8:17, 13:22, 124:19 68:2, 68:21, 70:19, 70:21, 71:6, 72:18, run 32:17, 66:20, 71:4, 83:14 72:21, 72:25, 73:4, 86:2, 96:4, 136:7 running 63:14, 63:17, 127:1 retailers 23:12, 87:15, 88:3 Russo 2:12, 94:21, 107:20, 139:2, 139:8retained 110:3 reveal 15:3 revenue 100:19 < S > revert 6:23 S-h-r-i-n-k 57:19 reviewed 80:8, 90:21 S-S-N-I-P 44:10 revised 94:13 Safavian 14:5, 14:9 rid 63:16, 63:18, 63:24, 63:25 safe 30:3, 32:16 right-hand 128:7, 131:17 Safeway 51:25 rise 48:5, 58:4, 58:7, 61:3 salad 76:21, 76:24, 77:1, 78:3 rise. 47:22, 48:2 sale 57:21, 58:1, 59:17 rising 100:10 Salem 125:22 rival 61:17 sales 22:19, 22:22, 23:3, 23:12, 24:5, 24:10, robust 70:23, 110:21 24:13, 26:21, 48:11, 48:16, 56:22, 56:24, 57:3, 61:19, 61:21, 67:16, 67:25, 68:7, 69:5, 76:1, 104:11, 105:19, 131:21, 132:14, 133:4 Sam 128:1 sample 28:25, 29:3, 29:5, 29:21, 30:5, 30:6, 32:23, 54:17, 54:20, 54:24, 105:6, 106:1, 106:3, 127:1 sanctions 6:5 Sanghvi 5:9 SAS 111:18, 119:18 sat 40:23 saying 12:25, 25:17, 34:22, 34:23, 73:12, 88:25, 100:11, 113:4, 120:15, 121:24, 122:7, 123:21 says 12:8, 42:12, 47:25, 49:1, 51:21, 58:22, 59:11, 59:15, 59:18, 59:19, 59:24, 60:2, 61:6, 81:20, 83:1, 83:2, 83:8, 89:3, 131:17 scale 100:8 scaled 100:5, 100:6 scenario 123:9 schedule 120:13 Scheffman 70:2, 111:9, 111:13, 120:10, 137:19 school 97:15 271 seemed 32:16, 76:18 Scientific 80:6, 80:12, 84:14, 84:16, 84:19 seems 11:1, 13:2, 16:23, 20:21, 44:25, 120:2scope 95:19, 95:22, 95:25 seen 9:18, 61:24, 118:12 Scotland 14:5 selecting 40:2, 70:5 Scottsdale 90:1, 90:8 selection 92:9 screen 7:6, 7:7, 14:15, 14:16, 14:23, 15:1, selectively 77:9, 77:14 15:14, 15:22, 15:23, 16:4, 94:8, 94:12, self-evident 112:14 132:5, 134:2 sell 102:4 screens 15:20 seller 44:18, 45:5, 46:22 seafood 86:8, 86:24, 87:10, 134:6, 135:18, sellers 21:18, 21:22, 22:8 135:24, 136:2 send 121:3 seal 9:25 Senior 58:22 Seasons 47:19, 47:22, 47:25, 48:1, 48:4, sense 43:22, 43:25, 51:10, 51:13, 51:17, 48:7, 48:14, 48:17, 49:2, 49:9, 49:13, 76:15, 108:10, 108:19, 110:21, 126:13 49:15, 49:24, 50:4, 50:20, 51:8, 51:19, sensitive 6:8, 6:12, 43:20 52:1, 52:17, 53:1, 74:8, 107:12 sensitivity 33:10, 39:14, 39:22, 40:5, 110:4, seated 5:8 111:1, 111:15, 111:17 seating 6:23 sentence 47:24, 47:25 seats 138:4, 138:5 sentences 25:18 Second 10:22, 12:7, 12:15, 26:5, 26:6, 64:11, separate 47:13, 47:14, 47:15, 69:19, 74:2, 71:10, 73:8, 78:14, 78:21, 79:17, 105:17, 84:11, 87:7, 87:11, 87:18, 87:20, 87:23, 122:12, 127:12 116:12, 119:18 Secondly 78:18, 92:5 separated 47:11 Section 18:9, 22:24 services 46:1 seeing 102:13, 133:9 session 7:11, 15:17, 78:20, 78:22 seem 65:25, 129:7 set 34:12, 36:19, 37:6, 44:18, 44:21, 45:5, 55:7, 55:19, 70:10, 70:13, 70:18, 70:22, 75:18, 80:13, 120:13, 129:7, 131:22, 133:12 sets 22:13, 70:11, 70:19 setting 109:18 settings 6:2 settle 88:15 Seven 18:9, 37:16, 37:19, 61:6, 61:13, 62:15, 66:23, 78:13, 86:2, 86:12, 104:4, 133:23, 133:24, 134:2 seven-tenths 77:4, 78:5 Seven. 88:17 Several 10:14, 11:12, 51:8, 91:21, 100:4, 125:8 share 84:4, 94:21 sharply 91:22, 91:23, 91:24 shift 113:14 shock 113:8 shop 109:2, 109:3 shopping 109:4 Short 92:11, 92:15, 134:13, 134:14 short-lived 61:14 shortcut 108:19 shorter 115:15 275 similar 70:6, 102:3, 126:13, 126:14, 127:20, SHORTHAND 2:47 129:21 shouldn't 88:25, 106:6 simple 25:25, 29:25, 72:20 show 12:3, 54:8, 73:9, 74:19, 136:10 simplest 117:16 showing 80:19 Simply 27:6, 37:9, 66:15, 77:1, 78:2, 82:24, shown 7:6, 14:25, 28:4, 70:23, 125:18 105:16 shows 50:3, 50:4, 74:15, 130:4 simultaneous 49:20, 52:24, 53:3, 53:10, shrink. 61:23 116:4, 116:10 side 7:12, 13:23, 30:3, 45:21, 46:19, 77:9, simultaneously 116:11 77:18, 111:8, 114:19, 115:24, 128:7 single 36:3, 36:10, 36:18, 36:20, 49:15, sides 77:8 77:16, 88:5, 116:7, 129:11, 129:15 sign 74:22, 74:24 sir 45:14, 52:21, 79:3, 88:6 signal 6:1 situation 26:1 signature 16:20, 17:11, 17:13, 20:9, 20:10 situations 116:4 significance 8:15, 10:23, 80:12, 92:7, 105:1, Six 12:17, 40:19, 41:1, 41:6, 41:12, 43:4, 105:11, 105:24, 105:25, 120:2, 120:8, 43:7, 43:8, 43:10, 43:15, 43:21, 43:22, 134:16 43:25, 55:5, 59:11, 61:14, 62:6, 62:12, significant 10:25, 12:10, 13:8, 29:17, 29:21, 66:23, 74:19, 82:15, 106:8, 107:3, 108:22, 30:9, 32:3, 32:14, 32:15, 32:19, 44:20, 115:23, 115:25, 132:15, 132:17, 133:5, 45:7, 58:4, 58:8, 72:24, 80:13, 83:16, 133:11 86:16, 86:21, 87:3, 105:4, 105:7, 105:10, Six-b 133:15 105:15, 105:21, 106:2, 106:22, 107:7, Six. 41:20, 104:3 112:20, 114:3, 120:7, 123:13, 123:21, size 29:7, 34:25, 38:19, 39:15, 39:23, 56:21, 130:3, 134:7 56:22, 78:10, 133:4 significantly 73:4, 73:6, 79:20, 79:25, 81:8, Skadden 1:38, 4:22, 4:24 134:10 Skus 101:25 SLATE 1:38 slated 30:15 slightly 33:11, 36:8, 110:19, 128:3 slower 115:1 small 29:17, 44:19, 45:6, 83:2, 83:13, 85:22, 93:12, 105:19, 114:3 smaller 29:15, 31:13, 32:2, 32:19, 50:25, 51:12, 51:16, 78:9, 105:10, 105:15, 105:16, 107:1, 108:9, 108:13, 109:11, 128:13 so-called 99:1 software 108:17 sold 25:4, 60:4, 63:1, 87:6, 87:10, 88:1 sole 44:18, 45:5, 46:22 Somebody 9:5, 16:18, 37:9, 64:19, 97:25, 99:5, 101:20, 107:17, 107:20, 112:9, 112:10, 138:21 somehow 102:6 someone 127:21 Sometime 33:8, 120:16, 127:2 Sometimes 8:3, 8:4, 8:5, 8:10, 14:2, 41:22, 58:2, 80:17, 99:6, 99:8, 99:10 somewhat 78:9, 84:22, 98:22, 109:15, 126:13 somewhere 32:16, 132:22 279 Spelling 107:21 sooner 13:16 spend 53:16, 91:6, 97:13 Sooper 71:17, 71:21, 91:2 spent 20:4 sorry 23:7, 39:8, 42:21, 48:21, 50:11, 62:1, spoilage 58:2 86:10, 101:8, 101:18, 101:20, 102:18, spoiled 59:12 102:24, 107:16, 122:20 spoke 23:7, 100:15, 124:12 sort 8:17, 8:24, 14:16, 30:21, 33:10, 51:16, spring 119:15, 121:5 65:25, 75:15, 112:9, 125:10, 133:13, Square 1:41, 29:7, 29:13, 29:19, 31:5, 31:11, 133:21 31:17, 31:19, 32:7, 32:8, 32:22, 38:21, sorting 59:7, 111:17 39:4, 39:7, 39:11, 54:19, 54:23, 55:13, sorts 8:6, 98:14, 99:16 89:18, 90:5, 92:19, 104:23, 108:3, 113:14, sought 68:2, 111:14 113:24, 114:10 sound 6:19, 134:25 SSNIP 44:6, 45:21, 114:3, 115:10 Sounds 18:25, 22:25, 35:14, 86:6, 87:5 stabilizes 133:16 Source 131:17, 132:3 staffer 14:9 source. 88:5 stand 7:15, 10:13, 21:8, 59:10, 128:4 sources 11:10 standard 39:20, 80:15, 113:16, 113:19, span 133:7, 133:18 113:24, 137:23 speaks 80:20, 85:19 standing 14:8, 83:23 specialty 86:8 standpoint 45:24 specific 34:12, 76:6 star 83:16 specifically 18:8, 18:21, 80:9, 95:8, 97:20 start 10:4, 66:18, 97:5, 138:22 specification 53:20 started 59:7, 93:24 specified 41:8 starts 133:17 speculate 73:12 state 21:9, 110:1 spell 44:9, 107:17, 107:18 statement 35:6, 36:23, 48:3, 80:14, 80:18, 81:24, 83:4, 83:11 STATES 1:1, 1:17, 80:11 statistical 10:23, 29:4, 77:22, 80:12, 134:16 statistically 10:25, 12:10, 13:7, 79:19, 79:25, 80:13, 81:8, 86:16, 86:20, 87:3, 134:7, 134:9 Statistics 29:25, 83:8, 84:15, 84:21, 135:12 status 15:6 stay 31:18, 71:1 stopped 8:24, 9:2 story 12:20, 13:4, 51:18 straightforward 120:24 strange 76:10, 76:13 strategies 46:6, 46:10, 46:15 strategy 30:22, 120:22 STREET 2:6, 106:23 strength 106:15, 106:19 strengths 99:15 strict 37:1 strictly 6:4 strike 24:3, 28:2, 123:4, 123:18, 131:3 strikes 13:4 stringent 80:17, 80:21 struggling 9:22 283 substantial 56:23, 56:24, 104:10, 104:11, students 110:24 130:6, 130:14, 132:21 studied 23:11, 26:19, 35:10, 40:2, 53:23, substantially 59:16, 132:18 54:14, 62:9, 73:16, 77:2, 103:15, 103:16, substantive 11:17 107:6, 117:3 substitute 16:24, 46:20, 115:2 studies 39:7, 39:12, 67:15, 67:21, 68:9, 99:1, substitution 46:19 99:12, 104:6, 115:16, 119:11, 119:13 subtracts 51:18 study 24:5, 24:12, 38:2, 39:12, 43:1, 44:3, success 112:7, 112:13 49:25, 57:6, 57:11, 67:2, 67:7, 68:5, 73:22, successful 112:15, 112:24 74:2, 74:15, 79:4, 92:11, 92:15, 92:25, suggest 12:15, 31:6, 111:14, 123:6, 130:14, 93:5, 93:13, 103:22, 103:23, 115:13, 137:17 115:14, 116:25, 117:1, 117:4, 117:10, suggested 7:23, 50:6, 70:16, 70:18, 85:1, 117:15, 119:14, 119:16, 129:11 85:3, 105:3 studying 68:14, 78:4, 110:14, 110:15 suggesting 15:11, 48:1, 87:6, 87:10, 122:2stuff 63:18, 63:19, 63:20, 98:2, 118:12, 121:8 suggesting. 48:6 stupid 8:4 suggestions 8:2 subject 23:8, 57:16, 95:1, 95:15, 131:5, suggestive 8:7 136:21, 137:14 suggests 32:2, 65:18 subjects 55:25, 57:16, 89:7 suitable 91:20, 92:10 sublime 76:20 suitably 37:25 submarket 52:19 sum 49:17, 53:2 submit 95:5 summarize 135:14, 136:11 submitted 20:12, 58:16, 118:17 supermarket 39:4, 59:5, 107:6, 109:20, subpoena 10:20 115:11, 115:12, 127:22 subsequent 55:18, 56:6, 128:1 supermarkets 6:10, 46:6, 46:10, 46:15, 47:2, subsequently 84:1 87:7, 88:1, 128:22 supplemental 38:8, 40:18, 41:8, 43:13, 58:16, 75:7, 118:17, 122:13, 122:14, 124:6, 124:8, 124:10 suppliers 36:19 support 8:22 supports 28:10 suppose 60:3, 111:10, 137:9 supposed 102:1, 119:21 supposedly 103:11 surprise 136:2 surprised 8:10, 9:14, 51:24 surprising 57:4 sustainably 36:11, 36:21 sustained 57:1 swearing 16:20 switch 55:24, 57:15, 78:12 switching 89:7 SWORN 16:11 symmetry 77:12 synonymous 32:21 systematic 77:18 < T > T. 2:3 287 tenth 134:15 tab 17:5, 42:10, 48:22, 58:19, 89:24, 133:24 term 65:11, 69:17 table 5:9, 9:9, 70:23, 72:19, 72:21, 72:23, terms 14:14, 15:16, 43:9, 51:10, 52:10, 74:1, 74:18 52:12, 70:9, 70:22, 87:22, 89:20, 102:14, tables 23:9, 34:14 107:24, 114:17, 116:15, 134:23 talked 15:5, 25:20, 39:17, 47:19, 53:15, terribly 120:7 75:11, 85:21, 89:7, 91:7, 91:19, 112:5, Test 34:8, 35:1, 35:5, 35:11, 35:17, 35:18, 114:3 36:2, 36:17, 36:24, 37:1, 39:14, 43:5, 44:6, tape 5:23 44:14, 44:17, 45:4, 46:21, 80:17, 80:21, target 127:24 81:1, 81:2, 81:3, 81:5, 82:1, 82:3, 82:9, Taurman 1:33, 4:19 89:4, 89:12 teach 110:24 testified 17:25, 18:3, 19:19, 20:20, 20:22, teaching 97:13, 97:14 21:16, 21:20, 21:21, 22:2, 22:6, 25:2, 25:7, technical 98:2 26:19, 32:1, 32:18, 34:3, 35:15, 35:24, techniques 97:23, 98:4 42:25, 44:12, 45:3, 45:14, 45:20, 45:23, technology 16:4 47:9, 58:7, 60:21, 61:2, 69:10, 78:7, 90:25, telephones 5:23 96:18, 97:6, 99:12, 103:15, 113:15, 134:6television 7:7, 15:20 testifying 19:1, 19:3, 97:6, 118:12 tells 83:18, 111:18, 128:18 testimony 7:17, 14:24, 19:15, 19:22, 20:18, Ten 78:23, 85:8, 85:9, 107:4, 109:24, 109:25, 20:19, 21:2, 21:12, 22:12, 25:2, 25:14, 138:9 28:22, 31:25, 32:3, 34:16, 35:8, 35:16, tend 51:22, 91:20, 91:21, 109:12, 115:9, 35:25, 36:14, 47:18, 47:21, 64:10, 64:14, 130:22 65:1, 65:3, 71:7, 71:9, 72:7, 87:25, 88:6, tended 103:13 90:21, 123:4, 123:14, 129:23, 130:8, tends 132:16 130:10, 137:10 tentative 10:5 tests 39:22 theft 58:2 theoretically 100:2 they've 111:4, 111:6 thinking 8:2, 8:8, 30:18, 45:18, 64:20, 114:17, 137:5 third 10:20, 26:5, 38:8, 41:1, 41:6, 68:24, 68:25, 69:1, 69:4, 70:2, 74:25, 79:3, 95:4, 113:16, 113:19 THOMAS 1:22, 1:25 though 9:3, 16:16, 65:22 thousands 87:25, 119:19 threat 130:13 threaten 61:22 Three. 22:15, 23:1, 23:14, 48:19 threshold 105:23 throughout 129:22, 130:22 tile 66:11 timelines 11:18 titles 132:5 today 6:18, 7:5, 7:13, 9:23, 9:25, 12:25, 13:18, 17:15, 28:14, 28:15, 39:17, 85:5, 92:22, 101:12, 101:13, 103:18, 104:16, 118:21, 120:16 together 48:13, 48:16, 48:17, 49:19, 69:9, 101:22, 130:20, 133:5 291 transaction. 34:10 token 25:24 TRANSCRIPT 1:15, 2:47, 71:11, 91:6, 139:3Tom 5:2 TRANSCRIPTION 2:48 tomorrow 9:19, 9:21, 10:2, 10:4, 11:4, 13:19, transcripts 7:3 118:22, 119:1, 119:4, 119:7, 120:13 translate 100:6, 134:22 tonight 9:20, 119:21, 121:9 translates 135:2 took 61:20, 62:10, 62:15, 75:8, 119:19 transmission 5:25, 6:3 top 42:12, 58:18, 62:7 travel 108:24 topic 7:23, 11:2, 65:6, 65:14, 79:17, 117:18, treatment 59:25 122:17, 122:22 tremendous 120:2 topics 96:10, 106:7 tremendously 112:3 total 69:12, 72:1, 138:11 trial 13:21, 13:23, 14:2, 14:3, 14:4, 19:16, totality 71:19 119:10, 119:16, 120:25, 123:16, 137:7 toto 20:5 tried 6:12, 75:23, 99:17, 111:16 tough 94:1 trimmed 77:7 toward 128:7 true 26:22, 30:17, 42:4, 47:5, 47:6, 47:7, track 125:25, 126:24, 127:10, 127:15 47:8, 60:8, 78:11, 81:23, 82:5, 112:21, tracking 126:19, 126:20, 129:5 113:5, 129:18, 130:24, 130:25, 131:1 tracks 129:2 truncated 66:11, 66:19, 67:1 Trade 1:4, 1:20, 4:2, 4:5, 4:25, 5:3, 5:5, 5:7, trust 4:14, 18:4 5:9, 12:19, 12:23, 19:9, 24:16, 31:3, 41:12, truth 16:20, 26:1 41:14, 51:20, 52:19, 75:12, 121:20, 123:20 Try 29:23, 30:24, 49:22, 69:24, 79:9, 90:10, Trader 51:25, 73:23, 74:3, 113:21, 113:22, 92:3, 94:4, 102:22, 108:14, 110:12, 126:16113:24, 113:25, 114:1 trying 15:6, 18:5, 25:19, 37:12, 60:2, 63:24, traffic 64:4 72:2, 82:21, 83:17, 86:13, 92:13, 114:16transaction 35:3, 35:13, 89:14 Tualatin 49:9, 49:23, 50:21, 62:14, 74:8 turn 6:18, 16:3, 17:5, 17:11, 42:10, 58:19, 117:17, 131:9, 133:23 turned 14:10, 30:25, 37:23, 40:9, 70:19, 72:19, 95:3, 119:14 turning 95:4 turns 30:10, 30:13 two-fifths 126:1 two-tail 81:25, 82:3, 82:4, 82:9 two. 22:25, 48:9, 48:12, 53:2, 56:9, 132:23, 138:7 type 26:6, 51:7, 128:24 types 39:21, 51:5, 51:6 typical 50:25, 113:23 Typically 33:6, 45:15, 51:15, 61:18, 63:3, 63:23, 88:3, 88:4, 105:14, 105:18, 105:20, 106:18, 106:24, 108:13, 109:2, 110:16, 114:5, 115:3 < U > ultimate 87:22 ultimately 24:22, 88:14, 109:6, 121:21 uncover 27:8 underlying 28:9, 95:6, 102:13, 118:20, 124:20, 124:22 295 until 101:7, 118:17, 120:7, 120:9, 121:4, undermined 96:13 127:11, 129:19 understand 9:18, 10:17, 10:24, 15:18, 20:13, UPC 24:19, 37:20, 38:7, 60:10, 60:12, 75:12, 20:15, 25:20, 25:25, 37:10, 46:4, 65:13, 77:2, 77:5, 78:2 114:14, 119:18, 120:19, 120:20, 123:20, useful 29:4, 80:18, 80:21, 102:17 124:25, 126:2, 126:16, 137:24 usefulness 80:25 understanding 65:19, 105:2, 116:5, 118:21, uses 53:17, 53:19 120:23, 124:15, 125:16, 136:4 using 15:23, 16:3, 27:4, 33:8, 41:17, 44:13, Understood 89:16 67:8, 73:23, 101:23, 108:15, 108:16, unexplained 129:9 120:21, 133:11, 133:22 unfairness 119:23, 123:16 utilize 97:22 unfortunate 103:7 uniform 59:25, 77:25, 129:17 uniformity 77:11 < V > Union 40:20, 108:3 V. 1:8 unique 34:9, 35:2, 35:12, 47:10, 89:13 vacation 119:7, 120:11, 120:12 uniqueness 136:9 Vague 79:21 unit 25:3, 25:7, 25:14 valid 77:22 UNITED 1:1, 1:17 value 82:2, 83:15 Universal 24:19, 59:20 variable 23:21, 23:25, 53:16, 53:18, 53:19, University 42:23 54:4, 54:12, 70:14, 70:15 unknown 60:18, 61:14, 62:2, 62:18 variables 65:23, 129:8 unless 12:23, 69:13, 71:22 varied 129:13 unlikely 30:19 various 23:11, 67:15, 67:22, 125:18 unobserved 60:11 vary 25:3, 25:11, 25:12, 33:8, 42:3, 54:7, unseal 8:21 54:8, 107:12 vast 132:15, 132:16 versions 11:15 versus 4:3, 82:19, 106:8 vibration 6:2 Vice 58:23 video 5:17, 5:23, 6:2 view 10:5, 10:23, 13:7, 30:22, 31:1, 107:8, 116:5, 120:23, 120:25, 128:18 Vinson 1:31, 4:9, 4:19 violation 6:5 Virginia 139:9 virtually 128:13 Volume 48:15, 132:2, 132:14 volunteered 95:13 vouchers 14:11 < W > W. 2:5 Wait 64:11, 101:7, 121:4 Walton 14:3 wanted 8:18, 14:6, 14:7, 29:22, 42:6, 45:13, 62:19, 121:1, 126:7 wants 12:24, 64:16, 64:20, 93:20, 138:5, 138:16 299 willing 120:13 Washington 1:7, 1:28, 1:35, 2:7, 2:15, 108:2 win 30:24 watch 93:24 wine 86:8 ways 71:6, 72:22, 109:1, 109:23, 116:6, Winston 125:22 128:16 wise 30:22 weaknesses 99:16 withdraw 12:5, 136:14 week 9:16, 112:25 Within 28:25, 29:3, 29:5, 29:10, 33:18, 54:17, weekend 9:18 54:19, 55:12, 57:7, 71:17, 79:6, 79:11, weekly 115:4 89:17, 89:18, 90:5, 101:11 weeks 61:15, 101:11, 101:12, 101:13 without 33:20, 37:2, 47:17 weight 13:2 WITNESS 6:16, 15:21, 16:9, 16:11, 16:13, West 61:20, 65:14, 65:16, 65:17 23:25, 25:24, 28:14, 29:14, 31:9, 41:3, whatever 8:13, 11:7, 12:17 50:11, 51:7, 51:22, 52:3, 52:8, 52:12, whatsoever 54:13 52:21, 56:4, 56:13, 56:20, 64:15, 64:17, Whether 10:18, 20:9, 23:20, 23:25, 28:19, 66:6, 70:9, 86:13, 89:5, 93:21, 102:24, 39:15, 39:23, 40:5, 41:1, 41:5, 41:20, 103:19, 107:16, 107:18, 108:5, 108:24, 41:23, 42:1, 42:2, 43:20, 43:25, 44:17, 113:2, 119:6, 120:17, 132:4, 137:7, 137:1545:4, 47:1, 53:7, 54:6, 54:11, 72:24, 73:5, WITNESSES 3:4, 6:17, 15:6 73:11, 73:13, 94:8, 96:3, 103:16, 104:7, wonder 78:16 105:24, 107:8, 113:5, 113:6, 118:25, word 48:5, 48:6, 50:6, 69:21, 79:7, 86:11, 121:14, 137:1 117:20, 119:12 Whirlpool 18:22 words 44:22, 64:22, 83:12, 88:18, 88:19, wholly 59:12 121:12 whomever 8:12 work 27:15, 27:17, 27:20, 27:25, 28:3, 39:21, wide 97:18 80:8, 80:12, 98:14, 99:2, 110:9, 110:11, wife 119:6, 123:25, 137:14 121:14, 121:15, 121:16, 136:12 worked 43:9, 75:20 working 18:21, 20:5, 51:3, 58:10, 69:9, 102:15 works 136:5 world 43:24, 77:15, 99:1, 99:4, 107:23, 108:21 worse 77:16, 113:12, 122:15 worth 8:14, 28:8, 56:14, 56:18, 56:20 write 8:11, 13:19 writing 13:16 written 19:15, 26:22, 79:9, 105:9 wrote 33:14 < Y > year 98:10, 113:3 years 11:19, 18:11, 45:16, 74:12, 113:3, 113:10, 114:5, 114:7, 114:11 yellow 9:4 yesterday 8:21, 120:1, 120:8, 120:9, 121:1, 121:2, 121:3, 121:4 York 1:42, 29:18 yourself 4:4, 29:9 303 < Z > zero 79:20, 80:1, 81:9, 82:6, 82:19, 126:25, 127:11, 129:2, 129:5, 134:10 zone 70:15