FEDERAL TRADE COMMISSION

Agency decision

Ask Donna

What actually matters in this document.

Text

In the Matter of:

)

WORKSHOP ON SECOND REQUEST AND

)

MERGER INVESTIGATION BEST PRACTICES )

------------------------------------)

JULY 10, 2002

Room 332

Federal Trade Commission

600 Pennsylvania Avenue, N.W.

Washington, D.C. 20580

The above-entitled workshop came on for comments,

pursuant to notice, at 2:03 p.m.

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APPEARANCES:

ON BEHALF OF THE FEDERAL TRADE COMMISSION:

MARY T. COLEMAN, Deputy Director, Bureau of

Economics

MICHAEL G. COWIE, Assistant Director, Bureau of

Competition

GABRIEL H. DAGEN, Acting Assistant Director for

Accounting and Financial Analysis

ELIZABETH SCHNEIROV, Special Assistant to Director,

Bureau of Economics

PANELISTS:

MIKE DENGER, ESQUIRE, Gibson, Dunn & Crutcher

MEG GEURIN-CALVERT, Economists, Inc.

RICHARD HIGGINS, LECG

TIM DANIEL, NERA

JOHN WOODBURY, Charles River

DAVID PAINTER, LECG

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FEDERAL TRADE COMMISSION

I N D E X

PAGE:

WORKSHOP:

Mike Denger

Meg Geurin-Calvert

Richard Higgins

John Woodbury

Tim Daniel

David Painter

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P R O C E E D I N G S

MS. COLEMAN:

Good afternoon.

We're here for the

final of the Second Request and Merger Investigation Best

Practices Workshops and this one is involving data issues:

accounting and financial economic data.

I'm Mary Coleman, and I'm the Deputy Director of

Bureau of Economics.

With me is Elizabeth Schneirov who is Special

Assistant to the Director, Bureau of Economics, Gabe Dagen,

who is Acting Assistant Director for Accounting and Financial

Analysis, Bureau of Economics, and Mike Cowie, who is

Assistant Director, Bureau of Competition.

The purpose of these workshops is to try to get

feedback from the outside bar and consulting firms and

practitioners on issues of the merger investigation process

and how we can improve that process.

And our role here is to listen and answer

questions there are, to give any feedback to points raised by

individuals.

We have spoken to some people who were interested

in speaking at this workshop, and I'll introduce them and let

them give their discussion.

This is being transcribed.

And we don't have a

microphone up front just to try to make this a little more

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informal, so we just ask that as people speak, that you

identify yourself and who you work with and speak up so that

the court reporter can hear what you're saying.

Okay, I'm just going to start by introducing

folks.

I'll start out with Mike Denger.

He is at

Gibson,

Dunn and Crutcher and he's worked in the antitrust field for

many years, has done work on merger investigations over that

time frame and he has prepared a proposed short PowerPoint

presentation which, I think, is out in the -- as you walk in

in the hallway.

MR. DENGER:

Do you want me to come up there or --

MS. COLEMAN:

No; you can just speak from your

MR. DENGER:

I always find it hard to speak with

seat.

my back to the audience.

MS. COLEMAN:

You are welcome to -- whatever makes

you comfortable.

MR. DENGER:

I haven't tried that.

I always feel nervous when they ask a lawyer to

come and talk about financial data and syndicated data and

cost data.

if they have me here on the data issues.

I guess I probably don't do too well as a lawyer,

And what I want to talk about a little bit is what

I think is the advantages in cooperation and data-sharing

with the antitrust enforcement agencies during the merger

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review process.

And I think from the standpoint of a party to a

prospective merger, there are some advantages to working

closely with the agency in this area.

First of all, I think you can get a common frame

of reference if you understand the data that they want and

need and the format that they're looking at.

I think it helps both the respondent understand

the focus and concerns of financial analysts and economists

and the staff at the agency and it helps for a more

constructive dialogue where you do not have two trains

passing in the night, so to speak, on data issues.

It also allows the FTC, if they have the same data

that you're working from, to replicate the type of work that

your economists or financial analysts may do, and I think

that is always helpful in establishing the credibility of

counsel.

I think if you work with the agency, you will also

reduce the cost of compliance oftentimes limiting the

production of duplicative or unnecessary information.

For example, in a retail merger, if one party has

IRI data and one has Nielsen data, if you can work together

and sort of agree, get everybody that's concerned with we'll

either use Nielsen or IRI, you're establishing a common

framework from which you can have the dialogue.

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I also think it reduces the merger review time.

It takes away a lot of time when it is focused on compliance

issues and things that are not really the substantive issues

and focuses of the staff.

And I think ultimately what a party's counsel and

probably his economist and financial analyst have to offer

imparts their credibility and if you cut out the Mickey Mouse

work and try to get to a common set of data that you can both

work from, I think that helps.

For example, let me focus first on producing

syndicated data.

data in the form used internally by the company, explaining

what you can provide and what you can't provide, provide them

some samples explaining the limitations.

It oftentimes results in the narrowing by the FTC

I would advocate providing early samples of

staff of the information that they seek.

You know, I can probably say I've never met an

economist or a financial analyst who didn't have data that he

wouldn't like or she wouldn't like if they had their choice,

but I think that the staff will be realistic if you can

explain what they're going to waste their time on, as well as

you wasting your time on in trying to find a meaningful data

set.

We had a case in a recent merger where we were

allowed to directly communicate with the FTC analyst and

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economist to try to resolve the data problems sometimes

without FTC lawyers on the phone, and that came as a result

of, I think, the trust and credibility that both sides

developed in each other.

I think if you work together, you can prioritize

data requests.

basis.

I would advise providing it on a rolling

Sometimes if you give it on a rolling basis, give

the early years first, or the most current year's first,

oftentimes I think the FTC staff will say that's all they

need.

lot of information that you otherwise would have to do.

They don't really need you to go back and to upload a

Similarly, in terms of financial data, we would --

I think have found it very useful to provide exemplars right

early on, oftentimes in the first meeting that you have with

the staff of your sales data, how your cost data is

formatted, how your data is organized, if you have customer P

& L's that sort of thing, what their limitations are.

And again, when you look at what data is

reasonably available and obtainable, I think oftentimes you

can narrow it to what is meaningful to everybody concerned.

And also, it's not a one-way street.

I think by

respondents learning what data the FTC is really focusing on

and wants, you understand how they are approaching their

analysis.

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So again, provide an early sample, sequence your

production, arrange meetings between people who are

knowledgeable in the company with the FTC staff that's

actually seeking the data, the economists and the financial

analysts, and by having people who actually know what they're

talking about explain it, rather than always putting a lawyer

in as an intermediary, I think we found that makes it a lot

easier for everybody else concerned and oftentimes it leads

to a narrowing of the search requests by the FTC staff.

When you've agreed on what you're going to produce

in some form, we often provide sample reports to make sure

that everybody is agreed and understood on what each other

wants before you go to all of the expense of running it for

all of the years or all of the markets or all of the products

in question.

And again, oftentimes that early cooperation can

eliminate costs and eliminate burdens on the company, as

well.

I guess our philosophy is sort of this: The facts

are the facts.

are all speaking about the same kinds of data and the same

facts.

And it's easy to have a dialogue when people

It's important to have trust and credibility and I

think that that can best be obtained by -- frankly on the

substance, but not on all of these procedural issues.

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And don't always view the FTC staff as the enemy

who is out to get you, which lawyers sometimes have a

tendency to do.

The FTC employees just have a job and we expect

them to do it thoroughly.

You also, I think if you cooperate

with them, can avoid a lot of waste, unnecessary duplication,

looking at data that is really not going to advance the

analysis on either side.

So I guess that's what I would say.

And I guess

our philosophy in all of this has sort of been like the

philosophy we have in litigation.

And I will say I've tried a fair number of

preliminary injunction merger cases over the years, but when

you try to be hard-nosed and fight over every point, all you

do is waste your client's money and annoy the agency.

As every firefighter knows, blaring the siren can

be fun, but the point of the job is to douse the flames.

this case, the point of the job is to try to get the merger

through in an economically viable form.

fight over the substance all we want, but I think it really

pays to try to work with the agency to get the data and the

basic facts set out so then you can have a substantive

dialogue.

Thank you.

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And we can

MS. COLEMAN:

Geurin-Calvert.

Thank you, Mike.

Next up is Meg

She's currently at Economists, Incorporated.

She also worked at the antitrust division for a

number of years and she is going to talk about issues related

to transactional-level data.

please.

MS. GEURIN-CALVERT:

Meg, if you could come up,

Thanks, Mary.

I appreciate

the opportunity to be here.

and just cover some brief topics so there's lots of

opportunity for discussion.

And let me follow Mike's lead

The perspective I bring is, as Mary mentioned, I

was at the antitrust division as an assistant chief and had

been a total of ten years at the antitrust division and at

the Federal Reserve Board with some time in between in the

private sector as a consultant.

And I think what I have learned best about the

particular topic we're addressing today, which is data and

both financial and accounting and transactional in assessing

mergers, was when I went back to the division as an assistant

chief working on my first second request where I understood

better, having worked on a very large number of second

requests on the receiving side, just what all the costs were

that were associated with compliance and what all the effort

was that it took to get the data together, but at the same

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time understanding the kinds of data that were available in

firms somewhat better than I had when I had been in the

division the first time.

So I had more of a sense of what was out there,

but at the same time came to a little bit more of a

perspective of that don't ask for what you can't use.

And so I guess I have six words to present to think on

the topic of transactional data: testable hypotheses,

critical loss and don't assume.

And what I would like to put the perspective in is

I think that there's a common goal between the private

parties and the government agencies that are reviewing a

given merger.

The common goal is essentially to have a review

process that hopefully ends in a significant review of the

appropriate issues and from the party's perspective, a

resolution of those issues and the mergers proceeding or from

the government's perspective, to the extent there is a

significant anti-competitive concern, having a strong

litigation base built up such that you can go to court and

demonstrate persuasively to a court that the merger actually

does present a problem.

To get there, I think it's the same process.

need full integration from the beginning and up to the

decision-making point of the data with the analysis, you need

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You

consistency of the data analysis and the data work with the

documentary review, the depositions, and so on, and you

obviously need time limits.

And I think in any industry, essentially what that

means is you need clear theories to be spelled out on both

sides as early on very specifically as to what are the

concerns, the product, geographic entry and competitive

effects.

I think everyone knows the merger guidelines and

what needs to be laid out in-house very clearly in the

government and the agency, particularly by the economists and

lawyers working together as what is our theory of the case,

what are the two or three things on which this particular

case turns.

That leads them to the next thing, again in-house,

which is what are the testable hypotheses.

And that is why I agree with Mike completely that

that's where the dialogue starts between the FTC staff and

the outside parties as to, "Here are our hypotheses.

are how we would like to test them.

we're looking for," and then I think you can focus lastly on

what are the results of the analyses.

Here

Here's the information

You may differ on theories and have a dialogue;

you may differ on the tests and have a dialogue; you may

differ on the reliability or the meaning of the results and

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you can have a dialogue.

And let me briefly talk about three types of areas

in which it plays out in different ways.

There are three

kinds of transactional data that I think occur -- a context

in which they occur.

The first is what I would call industry-wide,

where both parties, private parties and the FTC or the

government agency have access to industry-wide databases.

This occurs largely in healthcare, in airlines, in banking,

in electricity.

regulated has some pretty good data.

Essentially anything that was or is

Everybody has transactional-level data down to the

zip code and the DRG, or whatever, with which to work.

And as a result, you can focus.

The outside

economists can start much earlier, can do a full-scale

analysis.

can proceed much more quickly to very specific kinds of

analyses and discussions.

They'll know what the issues are, and the dialogue

And so I think that is a case where everyone, more

or less, has a level playing field, but where it's very, very

critical that when the agency staff have particular concerns

about a narrow product market or are particularly concerned

about the standard by which one defines the geographic

market, inclusion or exclusion of certain kinds of zip codes,

that they articulate it so it can be discussed and tested.

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The second area Mike dealt with in terms of

standard data, so I won't go into more other than to say that

there I think the issue is much more so, not the availability

of the data, but the methodologies that are applied or what

the testable hypotheses are and the debate over the nature of

the results.

productive dialogues helps that.

But I agree with Mike completely that having

I think the hard world is the third one which is,

unfortunately, most of the transactions.

kind deals; it's almost every manufacturing industry merger.

It is the one of a

When you think about it, the private parties have

extraordinary access to their own data.

detailed set of every transaction, most likely, that they

ever did, although it's surprising to some extent in the

computerized world how little data certain companies have

electronically and how much they have in hard copy, but where

the agencies have the advantage of having third party

discovery and third party data sets.

They have a good and

And I think I'd give just some basic pointers to

talk about.

I think that this is an area particularly where

the advanced work that the consulting economists or the

consulting legal team can do is to sit down and work with

their clients and identify what are the likely dispositive

issues, what are the testable hypotheses,

issues, is it private or is it geographic market, to set up

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what are the key

evaluation of critical loss as to how many consumers would

have to leave to discipline pricing and then to work very

well with the people inside of the company to identify what

kind of data is available, who is knowledgeable about it and

to get as far up the learning curve as possible about the

data.

I think that will help them ultimately when the

staff at an agency wants data, that there is better

communication in terms of what is available.

I do think what is useful, though, having been an

assistant chief and worked on a very large number of mergers,

the approach I found I took after a couple circumstances of

unfortunately having asked for data and received it and then

found that we did not even have time to process it before the

decision had to be reached, before a recommendation had to go

out is I found what worked -- and this works on the outside,

too -- is to sit everyone down before the second request goes

out and ask two questions.

One is what are our testable hypotheses; what is

the key issue in this case.

unlimited computer resources, unlimited time, what would you

want to get to test those hypotheses;

And if we had unlimited data,

And then to pose the second question, which is

then, we have a budget and a time constraint.

minimum sufficient data that you need to address that.

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What is the

What I found consistently is that when everyone

focused together, oftentimes it was the case that people

could look at just the top 50 customers, what they had done,

who they had bought from, whether they had switched it or

not.

In a very large number of cases, one did not need

huge transactional databases of every single transaction that

anybody had ever done in the industry.

The other thing I found is that it served also to

meld the staff economists and the staff managers better with

the legal team.

Oftentimes there is a tendency in very complicated

industries where there is huge transactional data for the

economists to be doing a lot of empirical analysis that is

running on a separate track from the data and the documentary

-- the documentary and the evidentiary kinds of evidence.

And I think if you focused earlier on testable

hypotheses and minimum sufficient data, answers would be

available.

The last thing I say is one advantage that private

consulting firms have that the government typically does not

have is a lot of research assistants who are very skilled at

manipulating huge amounts of data.

And so to the extent, early on the FTC had to

identify testable hypotheses data and asked that it be done,

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to the extent it is doable, because more likely a lot of

processing could get done with results being given.

In conclusion, I would just agree completely with

Mike.

I think the process works best if there is a clear

dialogue, and that's my last set of words of don't assume.

I think there is a sense, because there is a very

good respect on both sides of the table for people, that

outside economists will understand or divine what the theory

of concern is.

I think the more that the staff early on can say

here specifically is -- you know, we are worried about -- if

I could fill in the blank -- price discrimination of this

sort, geographic market of this scope, customer concerns of

this type, the more it is that the outside economists can do

their best effort to put information forward.

If they are not able to address the concerns, I

think that gives you a better sense of having a strong case

for litigation.

Then you'll know what it is that you would be up

against in that litigation were it to occur or, more

fortunately, could hopefully resolve the concerns.

MS. COLEMAN:

Thank you, Mary.

Next up, I would

like to introduce Richard Higgins who is with LECG.

He's going to talk about standard data -- and it's been

discussed to some extent already, but he's going to discuss

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in more detail the issues that arise not only in the

collection of standard data, but how it is used throughout

the merger review process.

MR. HIGGINS:

Well, actually, I was watching you

very closely, because that's the first I heard of what I was

to do.

John.

I thought I was just going to wait and comment on

MR. WOODBURY:

Oh, really.

MR. HIGGINS:

So far I don't have anything to say

about what was said before, except that I disagree with Mr.

Denger about agreeing on IRI versus Nielsen.

of disagreement.

I like the idea

And I mean, there are a lot of parties to mergers

and I just can't imagine getting them all in the same room

and telling them what data set they should be using.

And there are only two companies thanks to you all

-- that is to say, there would have been one had it not been

for you all.

And I wanted to also ask a question.

Panel data

is something that the Nielsen people and the IRI people have

and I've never gotten to use it.

all ever asked for those data.

And I just wondered if you

I've not seen the second request, which was asked

for, and I have found that the IRI and the Nielsen people are

becoming a lot more jealous of what they ownand, in fact,

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the last couple of times I had to work with data, I had to

sign something.

time, but the agreement worked out.

It really wasn't onerous, but it took a long

MR. COWIE:

MR. HIGGINS:

Richard, what is panel data?

Well, Neilsen, for example, has

surveyed or has a sample 40,000 households and it gives them

a little machine that they can scan their own products.

have their own scanner at home.

They are asked -- and I guess they're paid

something -- they are asked to scan all of their purchases.

And the value of it is it's a different type of data; it's

not just the time series stuff that we all have worked with.

We usually have, you know, lots of time and

especially if it's weekly data, and not -- well, I guess 54

cities or whatever is enough, but this is -- I think these

data mainly address some questions that haven't been

addressed and, in particular, they -- I think that they

account for couponing.

You know, a typical problem of ours is we've got a

merger involving products that are couponed a lot and the

kind of data that we normally get doesn't have any couponing

and -- in the case of ready-to-eat cereals,

part of the price.

would be a large

So it would be interesting to see what one could

do with the panel data.

It would be a big problem, but there

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are a lot of good economists, so I'm sure they could work

something out.

MR. DENGER:

Mary, could I ask one thing?

MS. COLEMAN:

Sure.

MR. DENGER:

On panel data, I know it's been

requested because I believe we've provided it.

MR. HIGGINS:

Oh, you did.

MR. DENGER:

In fact, we've even provided it in

Oh, okay.

the case Richard was involved in.

But panel data can be useful because they'll

measure what consumer purchases are in a particular point of

time, say a six-month period, and what happens, say, a year

later and you can track brand-switching and elasticities and

look at the changes in price and look at not only couponing,

but other things, and see how particular consumers react to

changes in price or other developments with regard to the

brand.

It can tell you how they move from one type of

outlets to other types of outlets.

example, the degree in which brands are particularly close

competitors of other type -- of other specific brands.

It can tell you, for

So I think it's a very robust type of database in

a lot of industries.

MR. WOODBURY:

MR. DENGER:

Can I disagree?

Sure.

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MR. WOODBURY:

It's not -- I agree that there are

some utilities with that kind of panel data, you know, the

switching analysis that Nielsen and IRI can provide -- and

I'm guessing.

- but I mean, it would be great if you could have access to

the underlying individual data that's contained, because then

you could do -- there are some problems, but you could do,

you know, consumer level demand analysis directly using

individuals, rather than cities, as observations.

I don't want to put words in Richard's mouth -

And as Richard says, the problem with getting

access to the data, as far as I can tell, is -- the hurdles

are unsurmountable because they will never give it out.

We thought occasionally about talking to IRI and

Nielsen about providing a demand analysis, of course, at our

specifications, but we never see the data.

to do it for us.

But we get them

So I mean, we've never gotten that far, but

MR. HIGGINS:

Yes.

I think they've become quite

competitive providing their own analyses and that's one

treasure they have that they're holding close and then

request a particular study to be done.

MR. WOODBURY:

One thing to be leery of, which I

discovered recently, is that if you look at the switching

data, you can actually derive market shares based upon the

data that Nielsen and IRI give you.

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And if you compare those data to the national IRI

and Nielsen data, you will find that there's usually a

substantial difference.

representative, so you have to be really careful about how

you use those data, even in switching studies.

MR. DENGER:

all of that sort of thing in switching data.

that the data can give you some insights.

It turns out those panels are not

And there's also issues as to sample size and

And I agree with, Richard.

But I think

If you're talking

about the underlying IRI/Nielsen data, it wasn't provided.

But there are lots of switching studies, and so forth, based

on that data that can be very useful, I think, at least in

giving certain insights that you might not otherwise draw.

MS. COLEMAN:

In those cases, have you had

documents of Nielsen and IRI to understand what it is that

they did to do the switching studies and information or did

you get the data -- even if it was aggregated, the data in

enough detail yourself to understand what was done?

MR. HIGGINS:

I have had conversations with

business people, marketing people, but I don't think I ever

understood what was done.

MR. WOODBURY:

I mean, we've had direct

conversations.

I mean, I've had direct conversations with

IRI and Nielsen about some of the switching studies so I can

understand, particularly when I discovered that I was getting

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market shares that looked a lot different from national

shares, what I thought was going on and how the sample was

collected, and all of that.

Yeah, but I think -- you know, they're certainly

happy to talk to you about it, about how those samples are

constructed.

MS. COLEMAN:

I think that those -- I do think

those types of data, it's interesting, can be useful to get

at issues, but it encourages helping us to -- you know, as we

get that data, helping us to understand what the collected

data is and how it's collected and how these studies were

done.

MR. DENGER:

But all data has, you know,

limitations --

MS. COLEMAN:

Right.

MR. DENGER:

-- and we all have to be aware of

them and have to understand to effectively use the data.

MR. HIGGINS:

Well, I just -- actually, I'm going

to sit down and let John talk about.

more to say than I do.

MR. WOODBURY:

I know he has a lot

No, no, no, no.

I'm sorry.

shouldn't have -MR. HIGGINS:

No, no, no.

I know you prepared

something.

But before I do, a question I want to ask about

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standard data is are you ever going to ask for it anymore?

MS. COLEMAN:

MR. COWIE:

Yes.

I have one question.

Why do you

disagree with Denger that you have to see if the parties will

use the same -MR. HIGGINS:

Oh, I just think if I were working

for a party that was opposing the merger, however incredible

that may be, that you wouldn't -- they should be able to use

what their client has.

MR. COWIE:

merger and the FTC --

MR. HIGGINS:

But you agree that the parties to the

Yeah, but that means you have to do

it both ways because God knows what the third party will

show.

And the data are different.

John will probably

talk about the geographic areas are different, Nielsen and

IRI, and how they do it.

different results from time to time using the two.

prefer to try to comment on whatever he says.

MS. COLEMAN:

I don't really know, but we do get

Okay.

Well, with that, I guess

we'll move to John who is with CRA.

customer data.

MR. WOODBURY:

He is going talk about

Well, actually, I thought I was

talking about the vulnerable consumers.

MS. COLEMAN:

Right, right.

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MR. WOODBURY:

And how would you use the second

request data to better identify vulnerable consumers.

actually found myself sort of confused for a while, but I

think I worked my way out of the confusion.

And I

What I am going to do is address -- try to address

three points.

First of all, what do we mean by vulnerable

consumers and what might we mean by vulnerable consumers;

second, how does -- the second request process, how can that

be honed to better identify who those vulnerable consumers

are; and third, and frankly and most importantly, from the

policy stand point -- and I know it's not exactly a part of

this -- but what the heck do you do with the vulnerable

consumers when you find them.

In terms of definition I sort of think there are

three categories of vulnerable consumers.

One is an elasticity vulnerability, a second is

an over-aggregation of vulnerability, and the third is, as we

already mentioned, the unmentioned vulnerabilities.

Elasticity vulnerability, I think, is the one that

economists naturally think of when they think about

vulnerable consumers.

undifferentiated product, you know, like you have a product

where there are two groups of consumers.

lower elasticity and then the other group. And then the lower

These are -- think of an

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One of them has the

elasticity consumers are potentially exploitable if a

hypothetical monopolists can discriminate between those two.

He can discriminate between those two with two

conditions.

consumers are which and, second, the monopolists can prevent

-- hypothetical monopolist can prevent an

the two.

One is the monopolists can easily identify which

arbitrage between

So you find yourself in a relatively

undifferentiated industry where there are some groups that

have a relatively low elasticity with product.

thing to do is just basically apply the SSNIP test, the

standard, you know, market definition test to the lower

elasticity group and ask whether they constitute the same --

if they constitute their own antitrust market, so you conduct

a merger analysis on that basis.

possibilities are -- well, I call them over-aggregation

vulnerabilities, but they actually just may be market

definition mistakes.

The first

The other two

In the undifferentiated product context, you might

find that, gee, you know, in looking at a particular input

some materials, you know, some chemical compound, you know,

we might conclude that the demand -- the antitrust markets

all supply us with that compound and all of the customers of

that compound are in the same antitrust market, but it may

turn out that for reasons that may have to do with differing

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technologies, there is some subset of customers that, in

fact, can't use all of the material available, that their

range of choice is much more limited in that case, we've

identified another potentially vulnerable consumer group.

Similarly, if you're talking about geographic

markets, you might think that for some products that most

consumers are able to, say, input purchases or able to

purchase from anywhere in the United States because transfer

costs are relatively low, but in fact, there may be some

subset of purchasers for whom transport costs are pretty

severe and, again, their of alternatives are pretty limited.

And again, I call those over-aggregation mistakes,

but you know, they expose another set of vulnerability.

And the differentiated product contents of the

over-aggregation could arise because of our effort to try to

make the analysis trackable.

retail products, such as, you know, candy or cereals or

shampoo, the number of SKUs, you know, at the market level

can literally be in the hundreds, if not thousands, because

they come in different flavors, they look different, they

smell different, there are different package sizes.

And if you think about some

So in an effort to make the analysis trackable,

you start aggregating up as some sort of mega-brand that

encompasses the whole slew of different package sizes and

different types of products.

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In the process of doing that, we may have hidden

some consumers that were exposed because those consumers have

a relatively low elasticity for some of those products

compared to the average elasticity for that group as a whole.

Another kind of vulnerability that could result

again, and I'm thinking more in the consumer goods market,

suppose that -- suppose, in fact, that there are differences

in elasticities with distribution channels. By aggregating

all of the distribution channels will have hidden that

potentially vulnerable consumer.

Finally, there are these vulnerabilities that we

don't talk about very much.

gee, we're going to let this deal go through because there's

virtually no chance that a price increase will result and,

nonetheless, maybe some consumers are going to be harmed.

Suppose the agency decides that,

If we're talking about a merger between retail

stores, there are some consumers who are going to discover

that post-merger, their favorite retail store is closed and

they have to further or go to a less preferred retail store

to purchase whatever it is they want to purchase.

They may -- again, post-merger there may be some

brands that are withdrawn from the marketplace and

consumers again will have to go to their second preference.

some

And in many cases, we don't talk about who those

consumers are or the fact they're out there, and I'm going to

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come back to this in a second.

Now, the anti-climatic part of this topic, since I

ignored those last vulnerability concerns, the

unmentionables, it seems to me that the second request as it

is now structured is actually a pretty good vehicle for

identifying vulnerable consumers because it solicits the kind

of information that at least lets you initially get a hold of

an estimate of who those consumers might be.

You know, in the three pieces of information, I

think that's solicited by the second request for documents,

they're data that could be used for econometric analyses and

they're surveys.

Let me deal with this briefly one by one.

In the case of documents, this is, you know, the

usual suspects, there are planning documents, there's

strategic documents, they're marketing documents.

documents that may enable the agency, as well as the parties

working for -- the merger parties to identify, you know,

efforts by the firm to segment the

groups.

alternatives available to different consumers.

They're

market into different

And they may highlight, you know, different

They may actually talk about price differences

across what seems to be essentially the same product, but

across different consumer groups.

And it may be that there's enough information in

the information provided to determine whether or not the

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price cost margin differs across those consumer groups.

For undifferentiated goods, we would be looking

for things in the documents that either talk about the

ability to arbitrage between, you know, low elasticity groups

and high elasticity groups or frustration at the inability of

resale from the guys that get it at a low price to the guys

that are going to be victimized by higher prices.

In terms of data -- and the data, again, can come

in a variety of flavors.

talked about which allows for direct estimation of own price

elasticity, but it also enables us to look

concerned about an aggregation, that we've aggregated the

brands too broadly, then you can use econometrics to test

that proposition.

if we're

Again, I'm putting aside the ongoing concerns

One is the standard data that we

about how to interpret results from the scanner analysis.

There's some groups of services that aren't

scanned.

You know, there are other databases with market

data, you know, things like the airline data, and telephone

industry.

you to try to identify the extent to which you have

potentially vulnerable consumers.

There are sample billings all of which go by --

The one thing that isn't covered typically in the

second request, but I think would be useful in identifying

potentially vulnerable consumers are natural experiments.

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In virtually every industry there are

unanticipated events that will affect pricing.

These can be,

you know, the sudden exit of a player, a firm.

It could be

the disruption of a distribution pattern or a temporary plant

shutdown, all of which can generate price increases.

And those allow you to determine, you know, are

there any difference in price effects felt by different

consumer groups; again, a signal that there may be more,

rather than less, vulnerable consumer groups.

Third, and I think this is really the large thing

to differentiate product surveys, surveys of the companies,

the merging parties themselves implement to try to understand

differences between consumer segments and whether or not, in

fact, there are strategies for separating those segments in

pricing differently between them.

All of that, of course, should be followed by

post-second request interviews of, you know, the rival

sellers, of customers, as well as the merging parties walking

them through concrete sales efforts to determine, you know,

exactly what kind of considerations play into this.

Now, once you've identified, of course, the

vulnerable consumer, that is at the end of the analysis, so

you have to ask the question, "Gee, if they pass the SSNIP

test, are there other alternatives that can prevent the

prices from increasing."

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For example, there could be buyer strategies that

could counter any attempts to engage in price discrimination.

But there is still something important, I think,

finance and policy questions, and I don't have any answers,

about how we weight some of these differences.

Let me give you the clearest example.

suppose that there is a merger between an upstream firm

decides to acquire one of its customers and it's that

customer that has been in an undifferentiated market, has

been playing the role of arbitrager between the high

elasticity groups and the low elasticity groups.

I mean,

that

So to eliminate that arbitrager, the upstream firm

acquires the downstream firm.

we'll have higher prices for the low elasticity guys, but

we're going to have lower prices for high elasticity guys.

The question is, well, how do we balance those --

the gains versus the losses and should that play a role in

policy formulation, as opposed to sort of when we go forward

legally in court.

The post-merger effect is that

And to give another example, suppose that there

are two firms that produce, you know, products A and B and

they merge.

variable cost synergies with production of product A.

And as a result of the merger, there are

And as a result, the price falls and the cost

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falls, but they fall in such a way, that the price cost

margin for product A is now higher than it was pre-merger.

Well, now, the merging firm will have an incentive

to raise the price of product B, so as to divert customers

from B to the relatively higher margin of product A.

Now, customers of A, they benefit by the merger;

customers of B are going to lose.

the losses to one group versus the gains of another group.

How do we weigh, you know,

I don't think it's a defense to say that -- you

know, that we never do that merger analysis.

of the time.

ones that occur all of the time.

We do that all

And the unmentionable vulnerabilities are the

So implicitly, there is some balancing of those

losses against the gains to the consumers who benefit from

the merger.

I don't have an answer to the question.

I just

raise it.

be dealing with when they deal with the agencies: how do we

evaluate instances in which mergers will provide clear gains

to some groups of consumers, but the potential of loss is to

other groups.

But I think it's an important one for parties to

Thanks.

MS. COLEMAN:

Thanks, John.

I have one comment on

the second request about natural experiments.

What do you think could be done to improve that to

make sure --

I agree that it can be very useful for a number

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of things.

MR. WOODBURY:

I think it would start to do things

like ask a party to identify -- take a list of potentially

disrupted events, say, plant shutdowns, recent plant

shutdowns, firm exits, sudden shortages of input and supply

and ask questions about have any of these occurred in the

past X-years and that will give you a basis to start.

MS. COLEMAN:

And what kind of data would you

MR. WOODBURY:

Well, if you're doing econometrics,

think --

I mean, you think about doing before and after studies where

we look at the price before and after the event.

But it doesn't have to be econometrics.

simply look at averages because you can learn a lot of other

things.

the outcomes of these natural experiments even in somewhat

statistically more crude terms.

MR. DENGER:

You can

But it would be insightful effort to look at some of

The only thing I would say, Mary, is

you may not ask for it specifically, but I think you pretty

adequately if you understand the second request bring within

the scope these natural experiments and other events in the

marketplace.

You may not know what they are unless you review

the documents, but I think that to the extent that there are

these events in the industry, you will pick them up.

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MR. WOODBURY:

Oh, yeah, that may well be true.

You do it for the second -- if I'm sitting with this guys, I

do a second request.

And you know that we on the other side would be

looking for those things.

MS. COLEMAN:

Does anybody have any --

MS. GEURIN-CALVERT:

I think one of the things,

too, is that this is an area where we're assuming that what

is going on consecutive with the second request is a lot of

meetings between -- or phone calls between the economists and

lawyers within the agency and the economists and lawyers on

behalf of the merging parties.

again, what is useful is to identify events that people think

really are representative natural marketing experiments.

It would seem,

And I think where the -- what I would say as well,

is it is oftentimes very difficult at that point for anybody

to have sufficient data to be doing really good econometrics

in the sense that the merging parties in most industries do

not have a complete data set.

They've got their own data which can give some

insights, but oftentimes is not sufficient.

The agencies probably are not at a point to have

had the full data set either, and so the more people can come

up with what it is they expect the natural market experiment

to be showing, what it is they're looking for and, as a

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result, where information can be brought to bear that is

empirical in terms of actual data analysis, but also

documentary, and so on, would be, I think, be very helpful to

try and potentially reach some closure as to whether or not

the next stage needs to be occurring.

MR. WOODBURY:

think that's absolutely right.

Actually, let me step back.

I focus on experimental -- you know, natural

experimental context for identifying vulnerable consumers.

But obviously, a natural experiments, you need

some referrals including data entry, looking at substitution,

and the like.

And I'm glad you pointed that out.

MS. GEURIN-CALVERT:

One example would be a lot of

manufacturing cases involve hundreds, if not thousands, of

consumers.

It is -- there are some industries where there are

three or four very, very substantial consumers.

typically, it is the case that there are at least a hundred

fairly good-sized consumers.

And if the concern at issue is that certain

customers are more vulnerable to a price increase than

others, I think it's a useful point to lay out, you know, in

terms of -- particularly if the staff has at this point

significant complaints from customers is to identify we

believe from each segment of your customer base, we have at

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least one complaining customer; you know, show us for each

customer grouping in the context of a natural experiment for

others why it is they have a plausible alternative other than

the merging parties.

I think again the more you can move from what

inherently is a customer database to the key issues, it helps

both sides.

MR. DANIEL:

I would -- in a similar framework or

frame of mind, I would hope there would be open dialogue and

frequent dialogue between the agencies and the parties if the

vulnerable consumer issue is at work because it's a little

bit at odds with the Meg's point, which is maybe you can

learn all you need to learn from maybe the top 50 customers.

You can learn a lot from the top 50 customers, but

if there are 200 or 500 customers, you might be able to find

some down there that would not have as many alternatives.

But allowing for those discussions as early and as

frankly and as openly as possible animated with whatever

support you can share with the parties, given the

confidentiality of information, would really be helpful

because oftentimes those vulnerable customers pop up

relatively late in the process and then you try to figure out

how can we analytically track where they are and what their

options are.

MR. DENGER:

That's why the interviews with the

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customers is so important to understand if they feel

potentially victimized or why they feel vulnerable and the

source of that vulnerability.

MS. COLEMAN:

Okay, thank you.

MR. WOODBURY:

Richard.

MR. HIGGINS:

I just want to know what an example

is of a vulnerable customer.

numbers.

MR. WOODBURY:

You must have worked those

I've never found a vulnerable

customer -- no.

You know, it's the usual.

It's the residential

versus business consumer, and for example, a long distance

company.

I mean, at least there's the conventional wisdom

that a residential consumer is more at the mercy of long

distance companies than the business consumer.

It's the leisure versus business travel with the

airlines, you know, those kinds of distinctions.

You know, it's the generic versus brand-named

drugs, those preferring the generic when the generics come

out, then the prices rise.

MR. HIGGINS:

I thought it was something new.

MR. WOODBURY:

No.

MR. HIGGINS:

All right, thank you.

MS. COLEMAN:

Next up is Tim Daniel from NERA He's

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going to talk about a different type of data.

MR. DANIEL:

Thanks, Mary.

Thanks for the

opportunity to be here.

Switching gears a little bit, I guess, and what

Mary has asked me to talk about involves mergers where the

competition arises in bidding- or auction-kind of

environments.

In looking at some of the second requests that

we've worked on where auction or bidding issues have arisen,

the bid specs, if there are such things, they can be pretty

sparse and limited and I don't think that's necessarily a

failure of the second request so much as a recognition, if

you will, that when bidding is involved -- what I'm thinking

of here is not so much bidding in a formal process, as the

government tenders, where you're going to know exactly what

the bid is for, but rather, competition that occurs for a

durable product in the medical business for a CAT scan or a

purchase of electric generation equipment by a utility where

it puts out a request for bid in a less formal sense, but the

competition is very much in that kind of framework where the

sellers are negotiating with the customer, and vice-versa,

and that's how the competition is described.

The data on that kind of competition are often

pretty idiosyncratic to the firm at issue and sometimes even

within the firm are very different qualities of data

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collected across different product lines and divisions and

geographic areas.

And I think that what I would take from that at

least in the process of doing a merger investigation is that

there's even a bigger benefit early on after the parties and

the government sit down and try and understand what data the

companies do, in fact, have when the competition occurs in

that kind of a bidding environment because it can be very

spotty in certain areas, it can be quite incomplete and it

can be quite frustrating down the road.

If the expectations are higher, I mean, I think

that the parties would keep good records on their bidding

competitions, good records on what their rivals are bidding,

good records on why they won or why they lost certain bids,

when, in fact, that's not the case.

One option I think that I would entertain early

on, therefore, is if you do have those dialogues and discuss

what is available in the companies is if you do hone in on a

particularly rich set of data, be it on a limited product

line or a limited time period or a limited geographic area, I

think the discussion could ensue at that point as to whether

or not a careful analyses of the good data might provide

enough of a basis to generalize to the markets what are at

issue.

That's a potentially difficult discussion to have,

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but I think one worth thinking about.

It's essentially the

same, I guess, as to whether you can take a sample of the

data.

If you happen to have data records that might be

complete, but they're on all paper and they're, again,

difficult to deal with, they're not Nielsen data, they're not

IRI data, they are just messy bid records, and you want to go

back five or ten years, or whatever time period you're

interested in, I mean, it might be possible early on to agree

to take a sample of those records.

When I was here at the FTC and doing consumer

protection matters and we talked about discrimination and

lending practices, that was a common occurrence when you had

a large number -- thousands and thousands of applications for

credit to just take a sample of those, work with the parties

to draw up a representative sample and then agree that those

are the data that are going to form the basis of the analysis

or for the decision at least up through the investigative

period.

One issue that I think is particular to an auction

or bidding environment that has to be taken into account is

if you look back at the economic models and ask what is the

likely price effects from a merger when two firms get

together in a bidding situation; is the expected price

increase from a unilateral context.

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It depends critically on

the costs and the offerings of the non-merging parties.

So to get the two low cost firms in a bidding

competition merged, your typical concern is they're going to

raise the price up to the cost of another third-level lowest

cost provider.

What that means is that very often there's an even

bigger asymmetry, I think, between the information available

to the government who can obviously subpoena and gather

information from all of the major players in the market and

the information immediately available to the parties.

That's not a gap that's going to be necessarily

closable, but I think it needs to be recognized and, again,

to me, at least counsels for as much open dialogue and as

much disclosure on the part of the agencies as to what's

animating their concerns, what's driving their analytical

framework and why they came and those competitions in those

situations of merger might be likely to raise prices.

Virtually, everything else I have on my short set

of bullets has been raised already, and so I think I'm going

to leave it there just with an endorsement of what Mike had

said about having open dialogue and discussions with the

agency as early as possible, agreement, if possible, between

the agencies -- agency and the parties regarding what data

will be sufficient to test the hypotheses and, if possible,

early on to agree on the economic model at issue because the

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economic models that underline an auction or bidding

environment are very different from the models underlying

standard differentiated product or homogenous product merger

concerns.

And if those agreements can be reached up front,

yes, indeed, this is the kind of analysis that we need to do,

then that can help to hone in on what information the parties

will have as a matter of course and what part of the

information the parties will not have, particularly on the

cost of their rivals as a matter of course, and then trying

to deal with some of the information and asymmetries that I

think are even more pronounced in these kinds of mergers and

these kinds of investigations that are made.

MS. COLEMAN:

Okay, thank you.

MS. GEURIN-CALVERT:

Does anyone --

I just want to echo what Tim

said about -- I think it is particularly the case where the

evidence to resolve the specific concern does not reside

within the merging parties and is not likely to be readily

available in public form as data on cost, but could only

maybe be inferred from particular things.

It is very important, I would echo his words, to

identify what the specific theory is because one could think

in a bid model a concern that it really is the case that two

merging parties, as Tim expressed, the lowest cost and that

there is no real sense that the non-merging parties may have

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in any way changed their cost position from the last time the

bidding occurred or could not do so somehow post-merger,

there really is a circumstance where there is a reason for

concern.

I think the more it is articulated that the

concern is a cost difference as opposed to, let's say, a

likelihood of somebody even submitting a bid.

One of the things I think that I found both in the

antitrust division and outside is people spend a lot of time

focusing on the wrong question because they thought it was

the correct question, that they thought, you know, the

agency's concern was we want to know about likelihood, as

opposed to we want to know about magnitude or we want to know

about likelihood and magnitude.

And I know that sounds relatively simplistic, but

I think that the more the questions can be articulated very

clearly and early on, the more there is the opportunity to

come back with information.

The other thing is I think it highlights the

circumstance where transactional level data, particularly if

it's old, may or may not be informative of what the post-

merger competitive process will be like.

If it's an industry that -- where the occurrence

of who has won in the past is different from, say, who hasn't

won in the last year, you can end up with a very different

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merger result than if you -- or merger prediction than if

what happened in the last year is almost identical to what

happened in previous years.

So I would respond to Tim's statement a little bit

that in terms of viewing any sampling, it would be worthwhile

to give the parties an opportunity to address whether or not

the past is truly a prologue or not.

MR. DANIEL:

In the natural experiment, again, I

would raise the same point.

A lot of the markets with large durable medical

equipment, electrical equipment have seen a lot of mergers in

the last half dozen years and someone might be able to use

that information and a change in market structure to see

whether or not past mergers, of which this current merger in

front of you may be somewhat similar in appearance, one might

be able to do some kind of prediction with these models.

MS. COLEMAN:

Thank you, Tim.

I'm going to switch

gears a little bit here and move more to the accounting

financial side.

David Painter with LECG, also formerly with the

FTC, is going to talk about some of those key issues that

arise looking at a different type of accounting and financial

data that he worked with.

MR. PAINTER:

And I appreciate this opportunity to

speak to you on this, as well.

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I guess let me reiterate at the outset something

Mike said and I think everybody else has certainly agrees

with and that is that having been here for 30 years, the FTC

is not the enemy.

The facts are the facts.

And I think that while I'm going to speak to

financial and accounting data, it can probably apply to

anything.

that, for merging parties to take is to provide the factual

information they think the Commission is seeking.

And that is the best strategy, if I can call it

I think it behooves the Commission and certainly I

think the merging parties, the lawyers representing merging

parties should make every effort to have a sharing of

theories because, clearly, a sharing of theories, once the

theories are honed in on, allow them to come up with the

accounting, with the factual information of what is financial

and accounting information, the Nielsen information or

anything else.

theories as early as possible is something that would be

essential.

theories are, that it behooves the merging parties through

the lawyers, through retained consultants to provide a

crystal clear road map and analysis that takes that factual

information and melds it into something that presumably comes

up with some conclusion and explain it to the Commission.

So I think that the sharing of

And I think last recognizing what those

With that said, let me just sort of tell you that

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I'm going to limit my focus because so much else has been

said, as well, the use of accounting and financial

information for purposes of preparing an expert analysis,

such as a failing company and efficiencies or for that

matter, econometrics, or anything else.

And I guess I've been on the outside for five

years, but I was with the Commission for 30 and perhaps that

30 years is what's going to drive me to sort of suggest the

conclusion.

It was a long time in trying to get there.

My experience at the Federal Trade Commission, and

it's confirmed I think in large part on the basis of my

experience on the outside, is that the underlying support

that is provided by the merging parties with respect to any

expert analysis is too frequently -- not always, but

frequently incomplete or inadequate for the Commission staff

to try, if they might, to be able to get a complete

understanding of the analysis in a way that says -- allows

them to say it's reliable.

it reliable.

I mean, this is the key thing: is

And that isn't because there is some inadequacy in

the second request.

The second request is as thorough as is

imaginable and, in fact, I just recently right before I came

here looked at the second request, the one that was received

by the merging parties in a case that I worked on, and

essentially it asked for the identification of all experts

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and consultants retained by merging firms and all documents

and data that were provided to such experts and consultants

and also asked for all instructions, programs and other

documents that are necessary to use and interpret the

finished analyses prepared by these consultants and the data

that was used to prepare the finished analyses.

covers it all.

And that

And yet, despite that -- and I'm assuming this

dates back certain years.

was similar when I was here -- expert analyses often are

fruitless.

It wasn't that exact language.

Efforts are made to submit them in a way that's

understandable.

them in a way that allows them to factor it into the

decision.

and my feeling is that what's lacking is the road map.

Efforts are made by the staff to understand

But somewhere along the way, something is lacking,

And I think we all might be able to better

appreciate this if you look at the Efficiencies Amendment,

the Efficiencies Amendment before it came out, before

submitting anything and everything that we could to try to

demonstrate efficiencies.

And we all had a sense that they had

practitioners on the outside, most of us that worked on the

inside what was needed with the Efficiencies Amendment and

sort of laid out a road map as to what is going to count with

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respect to at least the efficiency claim and this could have

been applied.

You could have an econometrics amendment or you

could have failing company amendment in some respects, and so

forth, but the bottom line to it was that -- what it said was

that, look, we know we're requesting everything in the second

request, it gets in everything, but despite that, independent

of the second request, we are going to tell you now that you

have to substantiate the efficiencies in a way that allows

the staff to verify it.

You know, I think it could apply it to anything, I

think, and that's the key.

And so I think that from my standpoint, I think

that there are lots of shortcuts with respect to accounting

information data.

We're all aware of -- that doesn't mean that

they're not -- that they can't be meaningful when put into an

expert analysis.

shortcomings are and what the strengths are and coming to

some sort of a reasoned conclusion that allows the staff to

say yea or nay on it.

It's a matter of explaining what the

I will tell you that if all of you are going to

count on the outside with the submission of boxes and boxes

of documents that underlies the efficiencies claim, it's not

going to do the trick.

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And the staff is not going to be able to uncover

it.

to do that through depositions and investigational hearing.

I mean, I was here for 30 years and we tried desperately

You know, as cooperative as the merging parties

attempt to be and the lawyers representing the merging

parties attempt to be, it's just extremely difficult to sort

of get at the subtleties, get at the sort of fine-tuning of

what these analyses are all about in a way that allows you to

say, hey, it's reliable.

So here is what I am suggesting.

I am suggesting

that the Efficiencies Amendment, whether formally or whether

on the outside, effectively use it as a tool, as a backdrop

for what we submit to the staff on other kinds of analyses

involving accounting and financial data be the -- be an

additional standard, if I can call it that, that standard

being a substantiation that allows the Commission to verify.

And I can tell you having worked on the Staples

case and having worked on the Heinz baby food case that it

isn't a matter of whether you are submitting five boxes of

documents or five hundred boxes of documents to support your

position; it's the road map.

On Staples, I worked, I'm sure, a thousand hours

trying to go through hundreds of boxes of depositions,

hearings, everything else to get to the truth.

And even there, half of the efficiencies were

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effectively dismissed because there was no way of verifying

whether they were valid or not.

On the other hand, I worked on the Heinz baby food

case and there were a fraction, a small fraction of the same

number of documents and -- but there was a road map, I

believe.

Now, that doesn't mean that the Commission

accepted it.

don't think there was a dispute as to the numbers themselves

and what the numbers were saying.

They didn't.

We all know that.

But at least I

There were theories that effectively refuted what

was being presented.

then I think we can make some reasonable arguments for and

against.

And if we can get down to that, I mean,

So I think that if we recognize that what's needed

is a road map, what's needed is really some really crystal

clear explanation, we realize that most of these analyses

that we sent to the Commission were started long before the

initial filing even took place.

We recognized that we have the benefit on the

outside of talking to business people at length, ad nauseam,

you know, time and time again.

We were able to pick and choose based on those

discussions all of the documents we wanted.

these constraints are, time constraints are with respect to

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And we see what

the HSR process.

I think we can better appreciate what the

Commission is faced with and we can better serve our clients

because we have a strong incentive to get this merger to pass

muster, so we have a very strong incentive to make it crystal

clear to the Commission.

We can better serve our clients by getting these

things done in a way that allows them to have -- to be given

some weight.

MR. HIGGINS:

But they never give us their -- the

benefit of their advantage.

MR. PAINTER:

The Commission staff?

MR. HIGGINS:

Yes.

They're sitting there with a

document from Bicardi that talks about whether they're going

to make the pineapple rum or not.

us if they're trying to get a rum deal.

MR. PAINTER:

They're not going to tell

You know, again, I can't speak for

the staff here, but I can tell you that when I was here,

while I may not have named parties and I might not have named

names, I think that, conceptually, the notion was thrown out

that, you know, what would preclude somebody from entering,

you know, by some means -- I mean, it was obvious -- and

maybe those exact historical examples that so many of you

have talked about, you know, were actually identified in a

request and explanation was made.

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Yeah, it may not be an absolute perfect two-way

street, but I don't think that -- since we want this merger

to get through, you know, it's just something we, perhaps,

have to face.

MR. COWIE:

Richard, there are confidentiality

concerns that at times prevent us from telling you what kind

of rum Bicardi is planning to make.

The fact of the matter is it's very difficult to

share third-party information.

MR. HIGGINS:

I've been bluffed by Mr. Newborn

enough times to know there's more to it than that.

suggesting that it is an adversarial situation.

contest and I don't see where we should --

MR. PAINTER:

But I am

It is a

You know, again, I will tell you

from experience, I mean, obviously, this is a short --

everybody has their own view, but if it becomes a contest and

you have an economic analysis that can't be -- you know, that

the staff is unable to sort of discern whether it's reliable

or not, then your best is case is going to court.

That's your best case because I don't think

they're going to accept it and go through, you know, without

an understanding of whether it's really, you know, an expert

analysis that's presumably supporting the arguments that

we're making to the staff and they're not sure if it's

reliable or not.

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So, you know, maybe we can win in court and maybe

-- you know, I may be saying tomorrow the direct opposite,

but if we want to take our chances in court, then obviously

that's something that's factored into the overall strategy

from day one when we make the initial filing.

But again, I don't want to -- I think that's more

the exception than the rule.

I think that the facts are

going to come out.

late, so that the theories -- you know, it's better that the

explanation theory comes out early, so that, in fact, there

are valid considerations on both sides, that they can be

explored.

It's better that they come out early than

MS. COLEMAN:

Okay.

MS. GEURIN-CALVERT:

you.

it is so difficult to do.

Mary.

I in many respects agree with

I have one point of disagreement just because I think

I think your idea of having a clear road map as to

what is the task, how do we do it and to be able to present

it in a form that stays objective and as verifiable as

possible is the best for everyone because I think that's

ultimately, as well, what is going to be presented in court

if it has to get there.

That's the same standard.

I think where it is useful to have this workshop I

think where it is particularly difficult now to apply that

road map, although I think the most effort needs to go -- is

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in large transactions where there is not a Nielsen and an IRI

or an industry database where what you are working with is a

huge number of consumers, very large and messy transactional

or customer databases in the merging parties so that even as

the economists start six months ahead of time working with

the most accommodating client to say let's understand what is

going on here, to the extent -- and this just is picking up

on what John said -- to the extent for whatever reason,

whether it's third-party information, or otherwise, the staff

has a concern about a particular customer group that they

believe has inelastic demands and a particular other group

they view may have more elastic demands.

I think the sooner that that can get articulated

by the staff to say we are particularly concerned about this

kind of set of customer, then I think it is more feasible for

the economists on the outside to try to marshal the data and

put it together in as testable form as possible.

But I think it's frustrating for everyone if the

way a meeting or a set of meetings proceeds as we have an

overall concern about lack of availability of substitutes.

I think the more progressed in the direction is

something you indicate on the efficiency side where everybody

agrees on what are we looking for, the better

industries.

and it's more straightforward for the staff to ask for the

in some

It's very straightforward to do that early on

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information in the second request.

And I would just say where you're having to ask

for huge transactional databases and it's a wide range of

industries it helps everybody to give more guidance from both

sides.

MR. PAINTER:

Absolutely.

MR. DENGER:

If I could add just one thing here

and it transcends data issues, but I think it's really

important.

I think the key thing is everyone wants to get a

sound merger policy and to do that, you have to have dialogue

on the issues that are of concern.

And I agree totally with Dave to the extent that

we can learn from the parties to the mergers with respect to

what the concerns of the agency are early on.

that there are confidentiality concerns that you have to

protect.

And I realize

On the other hand, you have to be careful that you

don't use confidentiality concerns as an excuse for blocking

a dialogue.

think, surface issues oftentimes.

You can protect confidentiality, but still, I

And nothing is more frustrating to a party to a

merger as to make a presentation and not really understand

what the concerns are coming back.

And I would urge the agency -- and I realize

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oftentimes you don't fully understand all of the concerns

early on in the process until you've conducted your

investigation and talked to customers and so forth -- but I

would think that the thing that will make for the best merger

policy for the dialogue is to let's take off our litigation

hats just for a little bit at the beginning and try to have a

dialogue where we can understand the concerns of each side

and try to address them and try to provide the substantiation

if we can and I think that will make for the most

constructive approach in the data areas, as well as others.

MR. WOODBURY:

But if I could echo, you know, a

little bit of Richard's presentation and focus on

econometrics, for example, I know CRA, and working with

Richard on some projects, LCEG has produced you know, pretty

detailed road maps.

But if I can make an analysis given the agency

given the underlying data that -- and frequently they come

back and say well, we ran something a little bit different.

Well, what was it?

Well, it was just a little bit

different, and you get frustrated because you don't

understand what they do, you know, how sensitive.

no idea how different it is.

You have

And this has been an ongoing -- as you probably

all know, an ongoing issue, particularly scanner data

analysis.

In the mass econometric projects, it would be nice

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to have a completely two-way street.

And you're right, you can't win the contest.

We're bound to lose it.

can't understand sometimes what's going on on the other side

in terms of why they find our results, you know, not

credible.

MS. COLEMAN:

But it's just frustrating that we

It's very clear from the discussions

that have been happening that the dialogue process is the key

to all of this and this is something that (inaudible) data

myself, trying to encourage as much as possible and as early

as possible, you know early discussion among the economists

and certainly the lawyers, as well, about the issues in

trying to come to agreement or at least an understanding of

what the theories are and what data tasks and other types of

analyses would be useful.

And also, we'll encourage to the extent we can,

given the confidentiality concerns, potentially where we are

in the process if it's got a very late date, this dialogue,

you know, the results that we're finding in as much detail as

we can so that those types of issues don't arise.

It's clearly something that both Dave and I have -

- are encouraging as much as we can.

continue to encourage that.

And we're going to

Allen, did you have a comment?

ATTENDEE:

One comment from the perspective from

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someone on the inside.

So many times parties have come up with, let's

say, white papers with documentation where the white papers

documentation would have been very effective but they tend to

come after everything has gone to the Commission and at the

last minute they come forth with the arguments.

late.

That's too

The one time I was working on a case where I

thought the expert was most effective was when they received

the materials very early while we were still in the midst of

the investigation and that expert's analysis went a long way

toward resolving the concerns and getting the merger through.

There have been times when I've seen parties come

up with some material that really devastated the case or sort

of devastated the case, but it came up after all of the

memos, including the Directors' memos were forwarded to the

Commission, and it was too late.

MS. COLEMAN:

I would, again, comment that the

later that these types of analyses come in, the less weight

they're going to be given and the less chance that we'll have

to not only look at them and the dialogue back.

That leads me to the question I sort of wanted to

throw out.

We have a few more minutes.

and some of the other workshops point of issues have been

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The timing of data

raised, nature of the data request and how long it takes to

gather the data particularly when we ask for it in ways that

the company's keep it and we end up getting the data

sometimes when the compliance happens and the data ends up

being a waste of everyone's time because by the time we get

the data, when it's that late, we can't do anything with it.

It's just too late in the process.

throw out a question about what can be done to encourage

people to submit data earlier as they get it and to enable

the process to be able to actually gather it early enough.

MS. GEURIN-CALVERT:

So I wanted to

One thing that may not work

in every case, but let's assume we're at the second request

stage or a point where there's been, you know, a voluntary

agreement for data, I think that is exactly the time to sit

down first internally and ask what exactly do we want, what

are we trying to test, what are our highest priority types of

information.

Obviously, in industries you've worked in before,

you know what you're looking for.

worked in before, you're less likely to know. And then to sit

down and have that dialogue with not just the attorneys, but

also the economists on the other side, and to identify as

clearly as possible what kinds of levels of data you're

needing in the highest level of priority and have the

shortest turnaround that you can to get back -- either to

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In industries you haven't

have a discussion just with that group again or to identify

the relevant business people.

effective, both on the outside and in the government, to go

into the equivalent of a plant tour, to go do a data tour and

have people go down and see what are the forms in which the

data exist and that I have found expedites, even if it's on a

rolling production, data as quickly as possible in as

formatted a form as possible to get to you.

I have found it's

And I think that covers also the issue of the

white paper.

not gotten the data either in a form that's really usable

much in advance of the time frame in which the staff gets it;

and so, again, to the extent issues can be identified and the

data identified sooner.

Sometimes it is that the outside parties have

But I think having conference calls and visits

with the data people is one way to expedite it and try as

quickly as possible, Tim's point, if sampling is going to

work, have somebody come up with an agreed-upon method as

quickly as possible if it has to be the universe.

I was in one negotiation a long time back when I

was an assistant chief and it turns out that the parties had

a very small data set that was exactly what we wanted, that

they were able to turn over on a diskette the next day.

But that we never would have found it if we hadn't

been kind of sitting and having that kind of dialogue.

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that's what I would recommend, particularly if you're looking

at large companies that have not done a lot of work in the

industry before.

MR. DENGER:

Let me just add one other thing, that

we have used lots of times, and I think it's very helpful.

The first meeting we come to to negotiate; the

second meeting we use to bring a couple of people who are

very knowledgeable about the data, samples and everything

like that.

And oftentimes, you can say here's what we got

from this person and you say, well, we can't do it that way,

but we can do it this way, and it will cost us X-zillion

dollars to do it this way, but if you can take this, we'll

provide it to you very quickly.

And if you take -- and a lot of people like to

bring very knowledgeable data people to the first meeting.

But I think it oftentimes helps to focus the

request to get it in quickly to weed out a lot of data that's

really not going to be meaningful because even if you've had

it all, there are some limitations to it that effectively

preclude you from using it for the purposes you might want to

use it.

And rather than have the lawyers go back and try

to find people in the company, and so forth, assume you've

got some knowledgeable people, bring them along and let's get

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the dialogue going and here's what we got and here's what we

can do for you and then if we can't do this, what about this

as an alternative.

And I think sometimes the lawyers get in the way

and slow things down by not having the business people there,

and you can bring your accountants -- to tell you we looked

at the data and this won't work.

Give me this type of economic analysis and this

will work and I think that speeds things along and allows a

more meaningful focus earlier in the process.

MS. COLEMAN:

MR. DAGEN:

Does anyone else have any questions?

Just there aren't as many attorneys

here as maybe there might be, but is there a reason why a law

firm wouldn't want to engage in the process you're

describing, Mike?

MR. DENGER:

Yeah, there are a lot of reasons.

One they can think they'll be in litigation with you and they

will think that information flow is a one-way street as you

sit there and you talk and you talk and you talk and you

don't get any dialogue coming back from the concerns.

There are a whole host of reasons why you wouldn't

do it.

You would be worried if you bring some businessman,

there is always a risk that he or she could say something

that you may not wish that they would say and you might

rather have that occur in a context where you can control it

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a little more.

But I think in balance, when you have to weigh

these, I sort of go back to the day that let's not start out

looking at each other as the enemy.

You've got a job to do and we have a transaction

we want to clear and let's try to see if we can have an

informed merging decision.

And the way to do that with the least burden and

the least cost on everybody I think is to step up to the

plate as early on the process.

step-up.

And it's got to be a two-way

The agency has to be -- the personnel have to be

reasonably candid about what their concerns are as soon as

they have them keeping in mind the confidentiality respect.

MS. COLEMAN:

questions or comments?

(No response.)

MS. COLEMAN:

coming.

your input.

Anyone else?

Okay.

Does anyone have any

Well, thank you all for

This wraps up the workshop sessions.

We appreciate

(Whereupon, the proceedings concluded.)

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C E R T I F I C A T I O N

O F

R E P O R T E R

WORKSHOP ON SECOND REQUEST/MERGER

INVESTIGATION BEST PRACTICES

DATE: JULY 10, 2002

I HEREBY CERTIFY that the transcript contained herein

is a full and accurate transcript of the recording/stenomask

taken by me at the hearing on the above cause before the

FEDERAL TRADE COMMISSION to the best of my knowledge and

belief.

DATED:

JULY 10TH, 2002

WANDA L. GRANGER, CVR

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This is a copy of a public record, reproduced as it was published. It is not legal advice, and it may not be the version a court would rely on. Check the official source before you cite it.