AMERICAN STATISTICAL ASSOCIATION (ASA)

                                    MEETING OF

                        THE AMERICAN STATISTICAL ASSOCIATION

                           COMMITTEE ON ENERGY STATISTICS

                                      WITH THE

                      ENERGY INFORMATION ADMINISTRATION (EIA)

                                      DAY TWO

                                  Washington, D.C.

                              Friday, October 6, 2006


                                                          2

           1                   P R O C E E D I N G S

           2                                             (8:41 a.m.)

           3              MR. HENGARTNER:  Good morning,

           4    ladies and gentlemen.  Welcome back to

           5    another exciting session of the ASA Committee

           6    to the EIA.  And I guarantee you that this is

           7    going to be the last time I'm going to chair

           8    this session.  So --

           9              MR. BURTON:  Well, you fired me

          10    yesterday.

          11              MR. HENGARTNER:  I know.  You, out.

          12    Go.

          13              This morning, we actually have some

          14    really cool stuff on the program.  Harry

          15    Vidas is another contractor, and what EIA

          16    wants us to do is exactly look and interact a

          17    little bit with the contractors, because they

          18    actually provide some valuable input to the

          19    EIA.  And it's a part that we usually don't

          20    see much.  And so this is an opportunity for

          21    us to see another side of EIA.  And as such,

          22    I think it's a great opportunity.  And so I

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           1    would like to welcome Harry Vidas to the

           2    podium.

           3              SPEAKER:  Might be a good chance to

           4    just --

           5              MR. HENGARTNER:  Oh, yes.  Before

           6    we start, I would like everybody who had not

           7    signed in, or rather, said their name aloud

           8    in the microphone, to do so at this time just

           9    for the record.

          10              MR. STAUB:  John Staub, EIA.

          11              MS. MAYNE:  Lauren Mayne, EIA.

          12              MR. CLINE:  Matt Cline, EIA

          13    contractor.

          14              MR. LADDY:  George Laddy,

          15    contractor.

          16              MR. VIDAS:  And Harry Vidas,

          17    contractor as well.  Good morning, everybody.

          18    My name is Harry Vidas.  And as the

          19    introduction said, I'm a contractor that

          20    occasionally does do work for EIA.  And what

          21    I want to do today is talk about a project

          22    that we did earlier this year to look into

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           1    the possibility of improving the way that the

           2    SAGE model represents non-OPEC oil

           3    production.

           4              The objectives as were given to us

           5    was first to provide a detailed description

           6    of conventional oil resource base, with the

           7    ability to look at alternative resource base

           8    assumptions.  Number two was to develop a

           9    bottom-up estimate of oil discovery,

          10    development, and production cost, and then

          11    having the ability to alter that based on

          12    assumptions about future upstream technology

          13    advances.

          14              Number three is to create an

          15    algorithm that could go into SAGE to allow a

          16    price response to non-OPEC production

          17    forecast for sensitivity analysis, and for

          18    the regular AEO production forecast.  And we

          19    were asked do it in a way that it should be

          20    understandable, traceable, verifiable, and

          21    unburdensome to update.

          22              So the scope of work that we had

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           1    included the following steps that we decided

           2    to try to do.  Number one, we had already

           3    developed a way of looking at oil resource

           4    and natural gas resource base costs to add

           5    into the future using what we call the World

           6    Assessment Unit model which I'll describe in

           7    a minute.  So that gave -- we already had an

           8    ability to look at the long run, what we call

           9    the resource cost of oil and gas production.

          10              And then the second thing was to

          11    try to -- was to develop a standalone model

          12    in Excel that would look at the annual

          13    forecasts of oil production as a function of

          14    the variables we talked about:  Price,

          15    technology, and so on.

          16              And then what we wanted to do was

          17    to be able to extract from that -- it's

          18    called Proof of Concept Model, the parameters

          19    that could then go into SAGE, and to give EIA

          20    a report describing the data methodology and

          21    so on for how to do this, and also what the

          22    data were.  The idea was that it will be

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           1    something that EIA would have to work with

           2    and evaluate and test.  And then they would

           3    have the decision to make as to whether or

           4    not that algorithm or some variation of that

           5    was worthwhile to put into SAGE.  So our work

           6    did not include actually working with the

           7    SAGE model, but to do this Proof of Concept

           8    outside the model in Excel.

           9              We did the work, I guess, starting

          10    earlier this year.  We finished up the model

          11    itself back in February; did a preliminary

          12    version of it, did some testing on it.  And

          13    then produced the final version in March.

          14    And then we delivered a report in April, and

          15    that was finalized in May.  And those of you

          16    who have not seen it yet, it's available on

          17    the website.  And also I think there is some

          18    printouts out in the front of the report.

          19              And the first part of this is what

          20    we call the WAU model.  And what this is is a

          21    model that EIA developed back in 2004

          22    primarily to look at long-term natural gas

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           1    supplies around the world and the ability to

           2    supply the U.S. with LNG.  But at the same

           3    time, it also does the resource cost

           4    calculations for oil, for conventional oil

           5    production.  And what this is is what we call

           6    a kind of bottoms-up calculation of resource

           7    cost looking at what we call a discovery

           8    process model that has within it an

           9    assumption about how many main fields there

          10    are, the field-size distribution of those

          11    fields, and then development cost for those

          12    fields.

          13              And we used algorithms that we

          14    developed in the past in looking at U.S.,

          15    Canadian, and other oil and gas resources

          16    around the world.  So we developed these

          17    costing functions that said here is how much

          18    it costs to drill a well on the onshore at a

          19    certain drilling depth, and here is what it

          20    costs for offshore by different water depths

          21    and different drilling depths and so on.

          22              And therefore, these algorithms

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           1    were then put into this model with a detailed

           2    resource base assumption that came from the

           3    USGS Year 2000 world resource assessments,

           4    with some modifications that I'll talk about.

           5              So therefore, the -- we did -- this

           6    provided EIA then with the bottoms-up

           7    calculations that they were looking for that

           8    allowed them to vary resource base

           9    assumptions like field size distributions,

          10    and to do a very detailed bottom-up cost

          11    calculation based on distributions of field

          12    sizes, locations, onshore/offshore water

          13    depth, drilling depth.  The finding -- that

          14    is to say, the drilling success rates as well

          15    as the financial parameters in terms of

          16    internal rate of return criteria, royalty

          17    rates and so on.

          18              And this was done at what's called

          19    the assessment unit level, which is what the

          20    U.S. Geological Survey used to do their world

          21    resource assessments, and there are about 520

          22    of these assessments units around the world.

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           1    And they represent individual basins, and in

           2    the some cases, certain formations within

           3    those basins.  And then those WAU curves are

           4    then aggregated up into country curves.  So

           5    the 520 WAU units are then added up into

           6    about 92, I think, countries that we have in

           7    the model.

           8              Now, that is the first piece of the

           9    puzzle, which is to say, at any given price

          10    in any given technology assumption, how much

          11    oil and gas is economic at a certain price.

          12    And the second part of the puzzle is, well,

          13    how do I then use that to forecast future

          14    production?

          15              And what we came up with was a kind

          16    of a modification of the Hubbard curve

          17    methodology.  I sometimes call it Hubbard

          18    Light in that it's not really using all of

          19    the assumptions and all of the underlying

          20    assumptions and beliefs that go into a

          21    Hubbard curve.  All it's really doing is

          22    trying to use some kind of function to

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           1    forecast long-run production such that the

           2    area under the curve is equal to the entire

           3    resource base.

           4              Because what we are trying to do in

           5    the first step with the WAU model is answer

           6    the question, at a given price, how much oil

           7    is economic?  And then we are using this part

           8    to say, well how does that get produced over

           9    time?  And even though the SAGE model doesn't

          10    have a 100-year time frame, we wanted to

          11    include in this model a very long time frame,

          12    because we wanted to play out what that

          13    resource base assumption means for a long-run

          14    production for purposes of looking at

          15    consistency, logic.  And also because people

          16    want to know what the long-run potential is

          17    for conventional oil production.

          18              So the basic idea behind this is,

          19    as I said, the Hubbard curve, and within that

          20    Hubbard curve, there's a lot of different

          21    ways of mathematically -- I don't want to go

          22    through all of the details here.  But the

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           1    basic, simple calculation is the production

           2    rate, annual production rate, divided by the

           3    cumulative production, is a linear function,

           4    with an intercept and a slope.

           5              And by starting with that

           6    assumption, you can develop all sorts of

           7    corollary functions that go along with that.

           8    They can then be manipulated in that model.

           9    And without going into the mathematics, what

          10    conceptually we are trying to do is we are

          11    saying, well, we know the historical

          12    production rates.  And we have recent

          13    last-year production rates.  We have from

          14    reserve estimates and from the WAU model an

          15    estimate of how much would be economic to

          16    develop at a given price.

          17              And what we were trying to do in

          18    essence is trying to draw a curve with that

          19    resource base that starts at the historical

          20    production rate that kind of looks like a

          21    smooth Hubbard curve from now forward.  So

          22    therefore, the Hubbard curve aspect of this,

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           1    or the logistic curve, which also what it's

           2    called, is using -- is trying to develop the

           3    shape of the future production, whereas the

           4    WAU model is being used to look at the

           5    economics of how much gas and oil is -- or in

           6    this case, how much oil is available.

           7              So we are not using the logistic

           8    curve or the Hubbard curve to determine the

           9    resource base, which is one of the ways it

          10    has been used in the past.  We are using it

          11    to do the scheduling of the production, not

          12    the resource base itself.  And that's kind of

          13    a modification.

          14              Now, as part of doing that then, we

          15    then have to work backwards and say, well, we

          16    don't know if this is the last year's

          17    production rate.  And we have from the other

          18    source, the resource base, the area under the

          19    curve that we're trying to then use the model

          20    to do that, to draw that function.  And

          21    that's essentially what we're doing here.

          22              Now, another criticism of the

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           1    Hubbard curve or the Hubbard methodology has

           2    to do with the shape of the curve.  And what

           3    we wanted to do here was to allow the model

           4    to look at, either endogenously or through

           5    other assumptions, changing the shape of the

           6    curve.  And this is through -- you'll see in

           7    the report the functional relationship.

           8    Basically the idea is the blue curve is your

           9    symmetric Hubbard curve that you've all seen

          10    in different reports.  And what we said was,

          11    well, you might have a situation where that

          12    production gets accelerated, or in fact

          13    decelerated.

          14              So what we have in the model then

          15    is the ability to change the shape of that

          16    curve based on, in this case, price

          17    function -- although you could do it, as I

          18    said, as just as another assumption.  So that

          19    allows us then to look at what I think

          20    conceptually makes sense, which is at high

          21    oil price situations, you may decrease

          22    drilling levels which may have an

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           1    acceleration affect on production that may

           2    not match necessarily the symmetric Hubbard

           3    curve.

           4              Now, one of the criteria that EIA

           5    gave us was they wanted to be able to update

           6    this frequently.  Well, not frequently, but

           7    once in a while, and not have it be very

           8    burdensome.  So the model relies on public

           9    data, which in many cases is already produced

          10    at EIA.  And then what this does is it allows

          11    you to take those data, put them into the

          12    spreadsheet, and the spreadsheet will

          13    automatically recalculate the parameters that

          14    go into the model.

          15              Cumulative production comes from

          16    the USGS estimates that were put into the

          17    resource assessment for the year 2000, the

          18    year 2000 world assessment.  And that

          19    originally comes from Petro Consultants, and

          20    that gives us the cumes through a certain

          21    date.  And then the production since that

          22    time comes from the EIA website which has

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           1    various sources for that oil production

           2    information.

           3              Now, the reserves in the model also

           4    come from EIA.  And those are reprints of the

           5    Oil & Gas Journal reserve estimates, with

           6    some adjustments for the non-conventional

           7    gas, probably non-conventional one.

           8              We also -- EIA wanted to look at

           9    well counts as well.  So we put into the

          10    model historical well counts and also do a

          11    calculation of what future well counts would

          12    be consistent with the forecast.  And those

          13    come from the Oil & Gas Journal and the World

          14    Oil Magazine that are public information.

          15              Unfortunately, some of that data

          16    is -- you have a long time frame for that

          17    information.  So some of it is only 10 years

          18    worth of data rather than the longer time

          19    that we would want to have.  And then of

          20    course, the key component is the resource

          21    cost curves which come from the WAU model I

          22    described earlier.

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           1              Now, the conceptual idea behind

           2    this was we wanted to use this information in

           3    SAGE.  So you can see on the left-hand side

           4    here that we are using as inputs, of course,

           5    the original USGS resource assessment, our

           6    costing algorithms and assumptions about

           7    financial parameters, technology parameters

           8    and so on.  And those go into the WAU model,

           9    and those produce the cost curves.

          10              And then on the right-hand side, we

          11    have the oil production model, which is the

          12    spreadsheet model I just described.  And that

          13    includes a lot of historical data from the

          14    EIA website, Oil & Gas Journal, World Oil

          15    Magazine and so on, which gives us the

          16    production history of the reserves and so on.

          17    And those calculations are going to the WAU

          18    model with an assumption about the future oil

          19    price.

          20              And you can either run that model

          21    with different oil prices and then get you a

          22    production curve that could be put into SAGE,

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           1    or you can take the algorithms out of the

           2    model and put them into SAGE.  And that's

           3    what EIA is looking at now is, do they like

           4    how that works and how they want to put it

           5    into SAGE and whether or not they want to do

           6    that at all.

           7              So that was the long-run goal.  And

           8    the report discusses how you could do that

           9    and what equations you would take out of it

          10    and so on.  Now, the supply curves

          11    themselves, we represent by a three-point

          12    curve.  And the only reason for doing that is

          13    just for simplicity purposes.  You can have

          14    any kind of recommendation you want in a

          15    long-run curve.  We did it this way so that

          16    you can have a compact representation that

          17    makes it easy to change the resource base; we

          18    don't have to recalculate the supply curve.

          19              And I don't need to go into all the

          20    different parts of it, but essentially, it's

          21    just a -- you take the WAU output and then

          22    fit to a three-point curve.  And then the key

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           1    parameter in the model is the representation

           2    of production at any point in time as a

           3    function of prior production, the prior year

           4    cumulative production, and then the resource

           5    base, which is what is recalculated in the

           6    model.

           7              And then by substituting the supply

           8    curve function for the representation of the

           9    variable resource base, you could then put

          10    together a -- kind of a long equation which

          11    allows you to forecast production as a

          12    function of price for any given period of

          13    time.  And the idea we have is that this

          14    would be done within SAGE as a

          15    pre-calculator.  Within each five-year SAGE

          16    period, you then run the model at different

          17    price steps, and then that curve would

          18    represent the potential production for the

          19    next period in the SAGE model.  And that

          20    would be one way of doing it that would be

          21    very straightforward and easy to implement.

          22              As I mentioned to you, one of the

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           1    criticisms of the Hubbard curve is the

           2    inflexibility of the shape.  And what we did

           3    is we put into the model the ability to do

           4    this shape adjustment, which we put in for

           5    the purpose of testing as a function of price

           6    that allows the model to accelerate

           7    production if prices go up.  And this is the

           8    representation that we have in the model for

           9    that.

          10              And then what we have in the report

          11    is the regional production curves.  And what

          12    these are showing you is just at some

          13    hypothesized pricing levels of $25, $45 and

          14    $65, the price responsiveness of different

          15    regions, and what they would look like at

          16    different price levels.

          17              And again, this is representing

          18    conventional production, not non-conventional

          19    and not tertiary recovery.  Now, any one of

          20    these, as you probably know, was very

          21    controversial in terms of what assumptions go

          22    into it and what the implications are.  And

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           1    what we tried to do in the report -- and also

           2    in discussions with EIA is try to do -- kind

           3    of alert to them what kind of issues there

           4    are in terms of doing these long-run

           5    forecasts, which I'm sure most of you are

           6    familiar with.

           7              One is this question of

           8    technological advances.  How do costs change,

           9    how do recovery factors change in the future,

          10    and if you're doing a long-run forecast, how

          11    do you implement that?  And there are some

          12    ways within the structure that we've just

          13    showed you how to do that.  But the

          14    question's how do you pick those parameters?

          15              Like for example, how do drilling

          16    costs change over time?  Obviously, they are

          17    a function of oil and gas prices -- we can

          18    look historically and determine that.  But it

          19    is also a function of long-run technology,

          20    and how do you determine what that number

          21    should look like.

          22              Other issues.  Just sort of

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           1    modeling questions, like we have the

           2    five-year period in SAGE, what does that

           3    represent in terms of this model.  Is it the

           4    last year, the average year, and how do you

           5    coordinate this model with everything else in

           6    SAGE?

           7              The field size -- the resource base

           8    itself is quite controversial.  One of the

           9    problems is that if you look at, for example,

          10    Canada and the production that's forecast in

          11    Canada, it looks kind of anomalous.  And the

          12    reason you have a very rapid drop-off in

          13    production in Canada is because of the

          14    resource base that went into it based on the

          15    USGS assessment.

          16              If you take, instead using the USGS

          17    resource estimates, the one we came up with

          18    for the NPC back in 2003 when we were -- we

          19    did the big U.S.-Canadian gas study, we also

          20    as part of that did an assessment of oil.

          21    And that has a much different assumption and

          22    would lead to a much different forecast.  So

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           1    one of the questions is how do you take the

           2    USGS information and use it, and to what

           3    degree do you look at these sort of anomalous

           4    production tracks versus what you would

           5    expect or what other people expect to go back

           6    and adjust it?

           7              And I don't know how much leeway

           8    EIA has to make those adjustments, but

           9    they're obviously -- things can look kind of

          10    funny in the -- and you can kind of see them,

          11    and you need to address them.  The other

          12    issue is the growth issue, which is to say

          13    fields don't -- aren't static, that over

          14    time, more reserves are added to those

          15    fields.  And one of the questions is when we

          16    look at the world as a whole, how do we try

          17    to assess how much further growth we're going

          18    to get in the existing fields, because that's

          19    a very large portion of the resource base.

          20              If you look at the original

          21    assessment done by the USGS, that showed

          22    612 billion barrels of growth in existing

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           1    fields expected out into the future.  Now,

           2    for the purpose of the WAU, we made some

           3    adjustments to that based on what we thought

           4    was a reasonable number to have for the

           5    growth.  And we did that as a function of

           6    proven reserves and ultimate recovery.  And

           7    we set up certain constraints, and so we

           8    wouldn't expect the future growth to be much

           9    more than a certain fraction of the known

          10    ultimate recovery.

          11              On the other hand, we wanted to

          12    make sure that it was at least a minimum

          13    amount of proven reserves.  And the problem

          14    why this comes up is twofold.  One is the

          15    USGS does not know the age of all the fields.

          16    And the basic assumption used by USGS was

          17    that there is what's called a growth curve

          18    which will tell you how much reserves are

          19    added to a field based on its age.  So a

          20    field that, let's say, is 10 years old and

          21    has a reserve estimate of 100 million

          22    barrels, is expected to be growing by

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           1    45 percent between its 10th year and let's

           2    say its 80th year, which is the end of its

           3    lifecycle.

           4              So what the USGS does is, they say,

           5    well, based on the U.S. patterns for growth

           6    that they have seen, they're going to apply

           7    that same growth curve to all of these

           8    foreign fields, and we are going to assume

           9    that curves are the same.  And that's what

          10    they did, except for some cases, they didn't

          11    know the age of the fields, so they didn't

          12    actually calculate a growth for that

          13    individual field.  So when you go through the

          14    data, you don't have a growth variable for

          15    certain areas.  So they have to -- I think

          16    they had to extrapolate that, and we had to

          17    do the same kind of thing.

          18              And the way we did it was by

          19    looking at how much reserves there were, how

          20    much ultimate recovery, and assume there to

          21    be a minimum amount.

          22              Well, the problem you have of

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           1    course is that it changes the forecast.  In

           2    other words, if I just put into the model the

           3    USGS assessment of 612 billion barrels of

           4    growth, that delays -- or that allows

           5    production to go much higher out into the

           6    future, as opposed to using our constraint

           7    growth number of 390.  And we can talk about

           8    this more, but obviously, the resource-based

           9    assumption both for the growth and the new

          10    fields is very critical.

          11              And then the other issue is

          12    definitions.  You know, the U.S. has certain

          13    definitions, the EIA has a whole program

          14    devoted to estimating reserves in the U.S.,

          15    and as you all well know, a very elaborate

          16    statistical methodology that they used to

          17    estimate that.  But there isn't one for the

          18    world as a whole.  And therefore, what does a

          19    reserve mean, how do different countries

          20    estimate those reserves?  And, you know, what

          21    should be done to try to be consistent across

          22    different countries?  And also, production is

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           1    not measured the same way in terms of NGLs

           2    and so on.

           3              And then the other issue is that if

           4    you look at the forecast, you see that the

           5    Western Europe has kind of an odd shape to

           6    the forecast, it kind of levels off, then it

           7    comes back up again.  And the reason for that

           8    is there's a lot of Arctic oil assumed in

           9    Greenland in the USGS assessment, a large

          10    resource base there.  And we assume that

          11    starting in some future year, that would

          12    be -- start to be exploited.

          13              Well, obviously it affects the

          14    forecast, depending upon what you think is

          15    going to happen there.  So there are some

          16    countries and some areas that really have not

          17    had any exploitation with large resource base

          18    and then when you put that into the forecast

          19    it could affect it.  So what do you do about

          20    those kinds of errors?

          21              So I think the assessment -- my

          22    conclusion of this is that this methodology

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           1    does make sense.  It allows EIA to try to do

           2    the things we talked about, which is the

           3    current bottoms-up resource-based estimate,

           4    kind of a cost-based assessment of the cost,

           5    with the economic -- it has a pretty

           6    reasonable flexible way of doing an annual

           7    forecast.  But it doesn't really resolve all

           8    these underlying issues, which are primarily

           9    data-driven, definitionally-driven

          10    assessments.

          11              And one of the things I talked to

          12    the EIA about was in the long run, how do you

          13    try to resolve them?  And of course obviously

          14    that's a very difficult thing to do because

          15    of the difficulty of the data.  So those are

          16    my prepared compared remarks.  I'm willing to

          17    take questions or comments.

          18              MR. HENGARTNER:  Can you go to the

          19    microphone please and identify yourself.

          20              MR. BROWN:  Hi.  I'm Bill Brown,

          21    I'm with OIF, the AEO half of the office.

          22    You mentioned in your presentation that you

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           1    have adjustments to accelerate the production

           2    of the Hubbard curve.

           3              MR. VIDAS:  Yes.

           4              MR. BROWN:  I was curious if that

           5    affects -- by pushing it forward, would it

           6    have any effect on the technical recovery of

           7    the different price levels as you go forward

           8    in the forecast.

           9              MR. VIDAS:  The way it's

          10    represented in this model is that the area

          11    under the curve is a function of price.  But

          12    we also allow the price to change the shape.

          13    But in a mathematical sense, they are two

          14    independent factors, although they are

          15    related to each other, so that when you have

          16    higher oil production -- higher prices, you

          17    get both a bigger area under the curve, as

          18    you would expect, plus you get acceleration,

          19    although you could represent it -- you know,

          20    that's what I was saying earlier, that you

          21    could represent -- the shape is a kind of a

          22    different issue.  It could be sort of

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           1    regulatory-related in terms of whether or not

           2    the country is open to foreign investment.

           3    It is necessary to --

           4              MR. BROWN:  You may be missing my

           5    question.  One of the things we observed in

           6    this country was that when lots of

           7    development went in early on, the act of

           8    doing -- sort of accelerating the development

           9    actually reduced the recoverable amount at

          10    any given price.

          11              MR. VIDAS:  Are you talking the

          12    production of too much gas along with oil?

          13              MR. BROWN:  Exactly.

          14              MR. VIDAS:  No, we've not looked

          15    into that, no.  And for, you know -- of

          16    course, there was a lot of ignorance back in

          17    the '20s and '30s in terms of recovery

          18    factors.  And I don't know that that's

          19    happening now; maybe it is.

          20              MR. CLEVELAND:  So the issue of

          21    price is one that I -- so you have prices

          22    skewing the curve at the left, which is

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           1    understandable.  But you also have -- of

           2    course, prices will expand the resource base

           3    as well.  And so it wasn't clear to me from

           4    looking at your document how -- what's the

           5    mechanism by which a higher price environment

           6    increases ultimate recovery?

           7              MR. VIDAS:  That's the purpose of

           8    this other model, which is the cost curve

           9    model.  So what we are literally doing is

          10    taking that other model and playing out the

          11    discovery process and development process and

          12    saying that at a particular price, at $5 per

          13    barrel, $10 per barrel, $15, here's how much

          14    more oil and gas, or in this case oil, we

          15    would expect to be able to get out at that

          16    price level.

          17              MR. CLEVELAND:  So price is an

          18    independent variable in your discovery model?

          19              MR. VIDAS:  Yes, that's right.

          20              MR. CLEVELAND:  So there is some

          21    implied price elasticity there between --

          22              MR. VIDAS:  Right.

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           1              MR. CLEVELAND:  How discoveries

           2    respond to prices.

           3              MR. VIDAS:  Right.  But we've got a

           4    long-run resource base; so in other words, we

           5    have a discovery process model that tells us

           6    for any given level of drilling how many

           7    fields we are going to find.

           8              MR. CLEVELAND:  Right.

           9              MR. VIDAS:  And then there is a

          10    development calculation that says when I do

          11    find it, is it economic to develop.  And you

          12    could essentially create a long-run curve by

          13    cranking through that, and for any given

          14    drilling level, say here's what the minimum

          15    price is for this drilling level, and if I

          16    had that minimum price, here's what I want to

          17    develop.

          18              And then you keep going to the next

          19    increment.  And eventually what you're doing

          20    is you're adding more increments of drilling

          21    at higher price levels and you're developing

          22    smaller and smaller fields.  So you can

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           1    develop a curve which is a time-independent

           2    long-run resource cost curve.  And that's

           3    what you have to put into the model that

           4    tells us how to change the area under the

           5    curve as a function of price.  So it's

           6    essentially an exogenous calculation using it

           7    in every process model to give you the

           8    resource base size as a function of price.

           9    And then this goes in as --

          10              MR. CLEVELAND:  So the parameter

          11    associated with price in that model, how is

          12    that calculated?

          13              MR. VIDAS:  It's literally taking

          14    the different steps.  I don't know if the WAU

          15    model has tabular form.  It says at this

          16    level of drilling, that's a $15 resource base

          17    increment.  You can calculate in the next

          18    increment; that's $11, so on and so on and so

          19    on, until I drill 20,000 wells, exploratory

          20    wells and so many development wells.

          21              And at each increment, I'm adding

          22    more resources at higher price.  That table

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           1    then for simplicity purposes -- let's just

           2    feed it to a three-point function.  And that

           3    three-point function then goes into the WAU

           4    model.  Now, what I was saying was the shape

           5    of this --

           6              COURT REPORTER:  Would you go back

           7    to the mic?

           8              MR. VIDAS:  I'm sorry, that --

           9              MR. HENGARTNER:  The microphone.

          10              COURT REPORTER:  Would you repeat

          11    that please, sir?

          12              MR. VIDAS:  What I said was that

          13    the information on how much of the resource

          14    base is economic at any given price is

          15    calculated in the WAU model.  And it comes

          16    out as a table that says that for each

          17    increment, here is what the marginal resource

          18    cost is and here's what the incremental and

          19    cumulative reserves added of oil would be at

          20    that price.  And then that table of

          21    information, which gives us price-quantity

          22    pairs, goes into the WAU.

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           1              And we could have put it in any way

           2    we wanted to, but we just chose to do as a

           3    three-point function because it allows us to

           4    condense the --

           5              MR. CLEVELAND:  No, I see what

           6    you're doing there and I think that's

           7    reasonable.  The question is I have is that

           8    there is an implied price elasticity in all

           9    that.

          10              MR. VIDAS:  Yes, that's right.

          11              MR. CLEVELAND:  And I'm sort of

          12    wondering where exactly -- like to see -- it

          13    would be interesting to know what exactly

          14    that is.

          15              MR. VIDAS:  Yeah, that would be a

          16    function of -- in terms of how we actually

          17    did the calculation, the cost of the wells,

          18    the cost of developing each of the fields,

          19    and then our discovery process algorithm,

          20    which was based on kind of looking at U.S.

          21    History, because we don't have the full

          22    history of all these different areas.

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           1              MR. CLEVELAND:  Right.

           2              MR. VIDAS:  So it's primarily a

           3    function of those two things, the discovery

           4    process itself, the field size distribution

           5    and then the economies of scale and the

           6    economies of each of the areas.  So for

           7    example, if you take an offshore deepwater

           8    area where you need to spend hundreds of

           9    millions of dollars just for the production

          10    platform, or for a sub-sea production unit,

          11    you're talking about needing 25 to 50 million

          12    barrels to be economic.

          13              So that has a much different

          14    economic cost curve for the field development

          15    than you do onshore, where you are drilling a

          16    3000-foot well, where field size is down to

          17    50,000 barrels and 25,000 barrels is economic

          18    to develop.  So you have your hundreds to one

          19    ratios in terms of the cost depending on

          20    where it is.  So what we've done is we've

          21    taken the WAU units, which are about 520

          22    units, and broken them down, because each one

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           1    of those can have a distribution of drilling

           2    depths, and in the case of offshore, water

           3    depths.

           4              And we've taken those and broken it

           5    down into sub-areas and say that a certain

           6    portion of the resource base is at this

           7    drilling depth, or this water depth, and we

           8    give that part of the resource base its own

           9    economics.  And then that's what goes into

          10    these curves.

          11              Now, what you typically see, if you

          12    look either at the United States,

          13    Canada -- or when we look at the other world

          14    areas, it's a large part of the resource base

          15    is relatively inexpensive.  And there are two

          16    reasons for this.  One is there are huge

          17    economies of scale in field development.  So

          18    if you look at the productivity of wells,

          19    they tend to be related to the size of the

          20    fields.  So large fields tend to have very

          21    thick reservoirs, multiple pay zones and you

          22    get a lot of oil or gas out of each

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           1    individual well.

           2              And the second reason why they tend

           3    to be economic is because the discovery

           4    process tends to favor finding larger fields

           5    earlier, for the simple reason that it's

           6    bigger.  And even if you did random, you're

           7    more likely to find them.  So that's why you

           8    tend to see in any resource curve, if you're

           9    starting from zero exploration, there's going

          10    be a very long bottom part of it.  And that

          11    is true for every area that we ever looked

          12    at.

          13              And then you find smaller and

          14    smaller fields, and that's where you start to

          15    get to the very steep part of the curve, and

          16    eventually get to the point where you only

          17    have very small fields, where incremental

          18    drilling has very tiny amounts of reserves

          19    but has a very sharp cost function.  And that

          20    curve is universal, although the exact

          21    parameters of course are really based on the

          22    economics I had talked about earlier.

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           1              MR. CLEVELAND:  Can I keep going?

           2              MR. HENGARTNER:  Yes, you still

           3    have the floor.

           4              MR. CLEVELAND:  The reserve

           5    growth -- I'm glad to see -- the USGS has

           6    been hammered on this reserve growth thing.

           7    And I think I'm glad to see your -- use the

           8    reserve growth numbers with caution, because

           9    I think that that's appropriate.  But I think

          10    what's an important -- if you guys are going

          11    to use those numbers, the most important

          12    explicit -- implicit assumption is, that as I

          13    think you've surmised, is that those reserve

          14    growth curves are based on U.S. oil and gas

          15    fields.

          16              So when you apply those reserve

          17    growth factors to the rest of the world, you

          18    are assuming that the same level of

          19    technology and know-how is going to be

          20    applied to every other field in the world as

          21    was done in the U.S.; right?

          22              MR. VIDAS:  That's one of the

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           1    assumptions, yes.

           2              MR. CLEVELAND:  And that's a

           3    gargantuan assumption.  And so some regions

           4    that would probably be true, but when you

           5    start getting into Asia and some of

           6    developing nations, there are many reasons to

           7    believe that that would never happen.  So I

           8    think that's important to -- as I think

           9    you've -- you've done to some extent,

          10    acknowledged the important assumptions in

          11    those reserve growth numbers.

          12              MR. VIDAS:  Yeah, the criticisms

          13    that are -- not criticisms, but cautions that

          14    are raised about this methodology is as you

          15    said, one is the technology one.  Although I

          16    would guess that if we are looking out 20 or

          17    30 years, given how the oil and gas industry

          18    has become a service-oriented industry where

          19    there are independent companies that are

          20    doing a lot of development, the world as a

          21    whole is sharing that technology quite a bit.

          22              And that's why I would think that

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           1    would -- although that is true historically

           2    and certainly true in terms of the timing, I

           3    think ultimately, everything that the U.S.

           4    learns in terms of technology is being

           5    applied.  In fact, if you look at offshore

           6    Angola or Nigeria and so on, it's exactly the

           7    same technology that's being been used in

           8    deep water Gulf of Mexico.

           9              If you look at horizontal well

          10    drilling in Saudi Arabia, that came from the

          11    U.S. as well.  So these things do eventually

          12    get there.  So in terms of the long run, it

          13    may not be an issue.

          14              The more problematic part of it is

          15    this very simple question:  What is a

          16    reserve?  And when we talk about reserves in

          17    the U.S., we're not really talking about the

          18    same definitions in other countries.  And as

          19    you know, when OPEC went to a reserve-based

          20    allocation of -- the allocations of

          21    production, that created incentive for the

          22    countries to up their reserve estimates,

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           1    which is what they did.

           2              So are those as valid as otherwise?

           3    Now, there was some work that U.S. Gas has

           4    done, taking the Petro Consultants database

           5    that I talked about earlier and looking at

           6    different vintages of that production,

           7    probably the reserve estimates.  And they did

           8    see that if you look across large fields -- I

           9    think they looked at 170 or 180 giant fields,

          10    that there was in general large amounts of

          11    reserve growth that took place between, I

          12    think it was 1981 and 1996.  So you know,

          13    their claim is they did look at some actual

          14    data.  But they haven't tried to go back and

          15    I don't think tried to fit it or try to see

          16    whether or not that reserve growth pattern is

          17    different than the U.S.

          18              And I wouldn't expect it to be for

          19    the reasons that -- the reasons are

          20    different, and as you're saying that the rate

          21    at which technology is applied is different

          22    historically.

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           1              And then you have this political

           2    factor about how the reserve estimates

           3    themselves tend to be for bragging rights,

           4    and in the case of OPEC allocations, have an

           5    effect as well.  So that's why it's very

           6    difficult to do an apples-to-apples

           7    comparison, and that's why you always -- I'm

           8    afraid cautious has to be the word in every

           9    instance, there's really no way around it as

          10    far as I know.

          11              MR. CLEVELAND:  The representation

          12    of technology and technical change -- so the

          13    way in which it shows up in your model is in

          14    the drilling -- the cost model; correct?

          15              MR. VIDAS:  That's correct.  And

          16    that would be the -- unless you try to put it

          17    into the accelerator, too, but that's a kind

          18    of a -- that would be another way you could

          19    put it in -- in terms of -- that's what I was

          20    saying earlier, that if we said that the

          21    Hubbard curve was the true representation of

          22    reality in the U.S., that would be done under

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           1    historical technology.  But we now have ways

           2    of increasing production rates, in effect.

           3              MR. CLEVELAND:  That has always

           4    been true.  Technology is just -- here's

           5    always been huge innovations in the industry.

           6              MR. VIDAS:  Right, that's what I'm

           7    saying.

           8              MR. CLEVELAND:  Based on the

           9    innovation -- I guess the question is, is the

          10    pace of innovation now so much greater

          11    they're producing some kind of structural

          12    break in the data series?  And I --

          13              MR. VIDAS:  Well, what I'm thinking

          14    is that now when you find a field, you're

          15    using today's technology, whereas in the past

          16    you may have found it in 1920, and used 1920s

          17    technology first, and you're into 1930s.  So

          18    therefore, the historical pattern has

          19    embedded in the certain technology pattern,

          20    whereas today we have a different pattern.

          21    That's all I'm saying.

          22              MR. CLEVELAND:  So in the case of

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           1    your model, the way in which technology

           2    increases ultimate recovery is by lowering

           3    drilling costs --

           4              MR. VIDAS:  That's correct.

           5              MR. CLEVELAND:  And hence

           6    increasing -- so I guess, one question there

           7    is that you've aggregated exploration

           8    development production into one activity.

           9    And it's really -- production certainly is a

          10    different universe than exploration

          11    technology.

          12              MR. VIDAS:  Well, it actually is

          13    two different steps in the WAU.  But for the

          14    purposes of representing it here, we wanted

          15    to have a price-quantity pair.  In fact,

          16    there are two dimensions whenever you

          17    explore, the exploration takes place given a

          18    certain price and technology level.  And then

          19    you have inventory of discoveries, which are

          20    field sizes that have been discovered.  And

          21    you can pick as to what you're going to

          22    develop based on technology, too.

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           1              So you could -- depending on when

           2    you did it and what the prices were, you'd

           3    have a different inventory of discoveries

           4    that you've developed.  And for the purposes

           5    of simplicity in the model, we simply say

           6    we're going to develop a curve by taking the

           7    minimum cost that's possible for every

           8    incremental drilling, which includes

           9    developing every field up to that marginal

          10    cost.  And that way, we can throw in the

          11    fields for each increment as we go up the

          12    curve.

          13              And as you point out, it is kind of

          14    a modeling construct that isn't necessarily

          15    realistic, because you could, for example,

          16    when the prices go up, you can develop a lot

          17    of inventory of discoveries you have already

          18    have -- have developed.  And that would

          19    happen differently than the smooth curve that

          20    we have in the model.

          21              SPEAKER:  Uh-huh.

          22              MR. VIDAS:  So that is correct, but

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           1    it's just an artifact of how we -- I mean,

           2    you could actually put the discovery process

           3    model in SAGE and do it on a real -- on a

           4    time-interval by time-interval basis.  But

           5    then it becomes an unwieldy kind of -- it's

           6    not an easy thing to update, and that's why

           7    we try to do it this way.

           8              MR. HENGARTNER:  One thing that

           9    occurs to me is, the WAU model is very

          10    interesting.  However, in terms of

          11    exploration and the impact in oil discovery,

          12    the price of oil needs to be above a certain

          13    level for quite some time, because there is a

          14    lag, right?  We had a spike of oil going to

          15    what -- 70s maybe?

          16              MR. VIDAS:  Yes.

          17              MR. HENGARTNER:  Did we explore

          18    very much more?  Maybe, maybe not.  The price

          19    is back down, all right, and so the

          20    volatility in price now will have an impact

          21    on how we perceive and want to do exploration

          22    in the future.

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           1              MR. VIDAS:  Right.  And the way

           2    we've done that in the spreadsheet model is

           3    to use an averaging price, so that way you

           4    don't take just this year's price, you take

           5    an average of the last five years and weight

           6    it 30:20, whatever the ratios were to get

           7    around that.  And of course, that's something

           8    you can also vary in the model, too.  But you

           9    wouldn't expect big changes like, you say,

          10    for -- in one year, based on just one year's

          11    worth of price.  And that isn't how we are

          12    the model.

          13              MR. CLEVELAND:  You did see it back

          14    in the first few price shocks, but they

          15    learned their lesson.

          16              MR. HENGARTNER:  Yes.  Exactly.

          17              MR. CLEVELAND:  I guess that will

          18    be the problem is it becomes -- it's price

          19    expectations, not price.  Well, that's why

          20    you go to moving averages to --

          21              MR. VIDAS:  Right.  And then in the

          22    SAGE model, of course, we're trying to set

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           1    this algorithm up to do the next five years

           2    of -- so we're going to have to use that as

           3    part of developing that curve for the next

           4    five-year period.

           5              MR. CLEVELAND:  So in the curves

           6    that you showed with the different prices, is

           7    technological -- that one percent increase in

           8    technology --

           9              MR. VIDAS:  That's correct.

          10              MR. CLEVELAND:  That's embodied in

          11    that.

          12              MR. VIDAS:  Yeah, we didn't change

          13    the technology between that.  Now --

          14              MR. CLEVELAND:  So those curves

          15    that you showed has the assumption of a one

          16    percent --

          17              MR. VIDAS:  Yes.

          18              MR. CLEVELAND:  Per year decline in

          19    the cost of finding and developing oil.

          20              MR. VIDAS:  That's right.  So it's

          21    already built in and it doesn't change based

          22    on price.  So the only thing we are varying

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           1    is the price.

           2              MR. HENGARTNER:  Harry, sorry, I'd

           3    like to get back to you, but I'd like to have

           4    Tom Rutherford add his planned discussion to

           5    mix up a little bit our comments here.  And

           6    then it's going to be your turn.  I won't

           7    forget you.  Thank you.

           8              MR. RUTHERFORD:  I think that I

           9    should first apologize for being a couple of

          10    minutes late; in the rain, I was a little bit

          11    slow.  There is always a challenge -- in

          12    modeling, it's always a cheap complaint to

          13    say, well, you've not done enough, or you've

          14    not looked at this.  So now let us focus on

          15    what we have as a model here, and think about

          16    ways that -- what would -- so what's useful

          17    about this is that we try to be a coherent

          18    framework for talking about resources and

          19    reserves, and the means of connecting to

          20    available geologic information, quantifying

          21    how changes have -- and estimates of those

          22    things and what they mean for the economics.

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           1              So all these things are good,

           2    that's definitely what we want to be moving

           3    forward.  The sort of the downside I see

           4    about the framework is that it's a little bit

           5    patchwork.  So we're taking data from

           6    different places.  I personally -- I'm the

           7    type that I like to have everything sort of

           8    laid out coherently in one framework.  So I

           9    don't have to know that I get stuff from this

          10    model and then run it in that one.  It's a

          11    little bit easier if everything is in one

          12    certain setting.

          13              But that's less of a concern to me

          14    than -- I'm a little bit concerned about the

          15    treatment of the international component.  I

          16    recognize the world is a very diverse place.

          17    And if we start worrying about what the

          18    nature of oil exploration is and all -- there

          19    are lots of different countries, lots of

          20    different contexts -- but I think that for

          21    oil, probably there is not -- if you were to

          22    pick the top ten other locations and focus on

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           1    those, you might -- it is one of these things

           2    where it's a small number of countries that

           3    really have a major impact, and sort of

           4    trying to pay attention to adapting the model

           5    to those contexts to provide -- I'm thinking

           6    about trying to how better improve the

           7    representation of oil extraction or recovery

           8    in other countries.  This could be quite

           9    important.

          10              And if we think about developing

          11    country contexts, or indeed, even Russia or

          12    Kazakhstan or these places, it is not just

          13    oil price, it is also sort of foreign direct

          14    investment, sort of investment climate, cost

          15    of production.

          16              There are a number of other factors

          17    that also I think would affect what your

          18    forecast would be -- in a first order sort of

          19    affect, would be the degree to which those

          20    things -- so I think that a model that's a

          21    little bit more adapted to the specifics of

          22    the major suppliers could be a productive way

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           1    to improve the framework.  And then of

           2    course, the final thing I just raised has to

           3    do with the role of expectations.  Your talk

           4    was much more coherent than -- I've looked at

           5    this model before, and I couldn't quite make

           6    sense.

           7              But your discussion is pretty clear

           8    that you have a clear idea of what the model

           9    is doing.  And so I -- it will be very -- I

          10    would really like to see the model developed

          11    in a framework where you could have it all in

          12    one setting, the equations are all kind of

          13    clear -- stuff comes in, stuff goes out, and

          14    you can sort of make sense of it.  And then

          15    it provides a better framework for thinking

          16    about extensions either to incorporate other

          17    countries, but also when thinking about

          18    dynamics, about what the role of price

          19    expectations are, it's something that

          20    again -- but that's a bigger issue than just

          21    this model.

          22              But this role of sort of recursive

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           1    expectations of prices and the distinction

           2    between what the price is the model is

           3    producing or what the expectations are of the

           4    agents of the model, or something -- I'm a

           5    little bit uncomfortable.

           6              But just a recap, I think the

           7    attempt to try to reconcile resource and

           8    reserve estimates and to be able to draw on

           9    more recent estimates of the actual resource

          10    base to try to provide a framework for

          11    understanding future developments of

          12    world markets, that's truly important.  And I

          13    think there is enough writing on this aspect

          14    of the energy system that some more attention

          15    to international -- specific international

          16    things are definitely important.

          17              MR. CLEVELAND:  Follow-up before we

          18    move on.  Just a general comment following up

          19    on that.  Ten years ago, you never would have

          20    seen EIA doing this, the Hubbard -- the whole

          21    long-run forecasting.  You never -- they

          22    never would have -- they were doing their

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           1    NEMS thing.  And the whole peak oil debate

           2    has gotten so much attention that I think

           3    EIA, and the USGS to a lesser extent, has

           4    been forced to respond.

           5              And I'm happy to see that in fact

           6    you have, because it is important, because

           7    there are a lot of kooks out there mis-using

           8    doing some really rudimentary silly curve

           9    fitting that has confused the debate more

          10    than it has helped.  And I think that

          11    applying -- taking essentially the Hubbard

          12    curve, which a lot of these folks use -- or

          13    some form of it, and trying to introduce some

          14    structure to it, some transparency to it, and

          15    some economic rationality to it, albeit in a

          16    very simple way here, I think is a positive

          17    thing to do.  And so I think it's good that

          18    you're doing this.

          19              MR. BROWN:  It's just simply --

          20              MR. HENGARTNER:  Could you go to

          21    the mic, please?

          22              MR. BROWN:  Oh, sure.

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           1              MR. HENGARTNER:  Okay.

           2              MR. BROWN:  I'm simply curious if

           3    you knew of the next sort of USGS or

           4    equivalent type of agencies' plans for oil

           5    resource assessment.

           6              MR. VIDAS:  Well, the one thing

           7    that's going on now that maybe Howard could

           8    talk about is the NPC study that DOE's asked

           9    the National Petroleum Council to look at

          10    this issue of world oil and gas resources.

          11    And my understanding is that what they are

          12    doing is doing a survey of what's been done,

          13    how different people are modeling oil and gas

          14    production out into the future, what

          15    assumptions they are using, and they are

          16    trying to not necessarily reinvent the wheel,

          17    but to try to provide some expert commentary

          18    on what they like about that -- what their

          19    deficiencies are, and what recommendations

          20    they would give to the government in terms of

          21    how to look at these long-run issues.

          22              And that's -- and I'm sure that

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           1    everybody including different government

           2    agencies were part of that as they were just

           3    part of the gas study that we finished up

           4    three years ago.

           5              MR. HELKIE:  I just had one

           6    question.  I just wondered if you had

           7    investigated that assumption that technology

           8    is kind of independent -- technology -- the

           9    trend of technology is independent of the

          10    price.

          11              MR. VIDAS:  As I was alluding to

          12    earlier, one of the controversies in doing

          13    these long-run forecasts is how do you put in

          14    technology?  And as I was saying earlier, as

          15    the NPC had done a study, both in 2003, that

          16    I was a large part of, and also in 1999,

          17    looking at this technology trends.

          18              And they did it primarily from

          19    expert opinion because they couldn't find any

          20    good way of looking at it mathematically.

          21    Though there have been attempts that have

          22    been done to try to look at, for example,

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           1    drilling costs as a function of activity

           2    levels, prices, and technology trends, or

           3    recovery factors, and so on.  And some of the

           4    numbers just come out to be I think crazy in

           5    terms of what they come up with, given what I

           6    know about technology advances.

           7              So the answer is, I have not seen,

           8    nor have I ever myself done, a rigorous

           9    statistical analysis that I believe that

          10    would give us a look at whether or not high

          11    prices induce technology or retard it,

          12    because people are able to make money with

          13    the existing technology and don't bother to

          14    try to figure out how to develop that field

          15    at $25 -- if the price is $50, they know how

          16    to develop it at 50 bucks and don't have to

          17    bother -- or work at it.

          18              One of the interesting things that

          19    came out of the NPC -- and this -- was the

          20    idea that if you look at what actually is

          21    happening to individual, for example,

          22    material science, information processing

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           1    science, is that a lot of the things that are

           2    happening now are all originating outside the

           3    oil and gas sector, and are being brought in

           4    and adapted to oil and gas technology.  For

           5    example -- composites to do an offshore

           6    platform as opposed to steel, that wasn't

           7    done for that purpose, but it was adapted.

           8              If you look, all this computer

           9    technology has been a big source of

          10    improvement that was brought in from other

          11    sectors.  If you look at things like

          12    measurement while drilling and those kinds of

          13    technology, those sensors and so on weren't

          14    necessarily developed for oil and gas, but

          15    they were adapted.

          16              So all the different

          17    drivers -- really is not sectorially

          18    specific.  It's actually an issue of the

          19    industry -- of the economy as a whole, and

          20    how it advances technology.  And oil and gas

          21    is one of the consumers of the technology,

          22    and that's -- I think the way the 2003 study

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           1    was written, it was talking much more in

           2    terms of technology as being an economy-wide

           3    phenomenon, not necessarily specific to oil

           4    and gas, although obviously there are

           5    individual aspects of it as well.  So it's

           6    still an issue, and I have not resolved it,

           7    because I don't model it for the long run.

           8              MR. HELKIE:  It would seem to me

           9    though that the relevant technology for the

          10    application is not what's laying out in the

          11    field, but what's being applied.  And it

          12    would seem to me that what technology is

          13    applied would be a function of the price,

          14    which is I think what you're saying, right?

          15              MR. VIDAS:  It is, but if you look

          16    at something like -- look at how the big

          17    gas -- most of what we have got is just oil

          18    and natural gas is -- domestic and Canadian

          19    gas.  And if you look at some of the hot

          20    places now, like say, the Barnett shale or

          21    the Fayetteville shale, and the Woodford

          22    shales, and what's being done, and how they

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           1    are advancing, they are using horizontal

           2    drilling technology that has been around for

           3    15 years.  And they are using fracing

           4    techniques that have been around for 30

           5    years.  But they are adapting them and

           6    learning how to apply them to an individual

           7    occasion.  And what's happening is, they are

           8    being driven by the higher prices, but they

           9    are also --

          10              MR. HELKIE:  Exactly, yeah.

          11              MR. VIDAS:  But if you actually

          12    look at the costs here, in some cases they're

          13    coming down.  So in other words, if I looked

          14    at what it was costing to do -- a deep

          15    Bossier field development in the Vernon field

          16    was $10 million per well, now it's down to

          17    like $6.  So it's kind of funny how -- and

          18    people know this is happening.  So they are

          19    actually sometimes doing things that are

          20    uneconomic, with the expectation that they'll

          21    learn enough to make them economic.

          22              So it is really complicated when

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           1    you look at individual locations and what

           2    people are doing.  And as you say, it's

           3    sometimes -- it's the doing that drives down

           4    the price -- it's the actual effort to do it

           5    that causes the price -- the cost to go down.

           6              MR. HELKIE:  No, I think it's

           7    interesting, and this is not a criticism of

           8    your work.  But I just think it's something

           9    that's really worthwhile investigating.  I

          10    mean, we've had this economy-wide

          11    productivity boom, or had it in the '90s.

          12    Nobody has got a clue why it happened.

          13              MR. VIDAS:  Right.

          14              MR. HELKIE:  I mean, they are just

          15    utterly clueless, right?  And --

          16              MR. VIDAS:  Let me suggest that --

          17              MR. HELKIE:  And I think it is just

          18    something that's really worth investigating.

          19              MR. VIDAS:  I think it may be

          20    something as simple as how many scientists

          21    are there.

          22              MR. HELKIE:  I'm sorry?

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           1              MR. VIDAS:  If you look at our

           2    population, in terms of what percent of our

           3    population is scientists, our population is

           4    growing.  The percent of the number of

           5    scientists out there and engineers working on

           6    this is growing.  The number of papers that

           7    are being published is growing.  So we have

           8    a -- it may be a very simple input-output

           9    function.

          10              MR. HELKIE:  That's an interesting

          11    point.  Intuitively, it makes sense.  But the

          12    scientific population outside of the United

          13    States has been growing a lot more from 1985

          14    to 2005 than it did in the U.S.  The

          15    productivity increase has all been in the

          16    U.S. --

          17              MR. VIDAS:  Because of our -- I

          18    think, I finally struck --

          19              MR. HELKIE:  And Canada, and not

          20    elsewhere, right?

          21              MR. VIDAS:  I think it is a --

          22              MR. HELKIE:  And it's just

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           1    really -- this is just one example of where

           2    it is really interesting, but this is the

           3    example we really care about, and --

           4              MR. VIDAS:  Yeah, I think most

           5    economists, and I guess in a roomfull of

           6    economists, I can say this.

           7              MR. HELKIE:  Yeah, but --

           8              MR. VIDAS:  We think it's the

           9    market structure.  I mean, the fact that you

          10    have the incentives.

          11              MR. HELKIE:  But I think in the

          12    long-run application, it's really an

          13    important assumption to say that the

          14    technology advance is independent of the

          15    price.

          16              MR. VIDAS:  So you disagree with

          17    that, you're saying.

          18              MR. HELKIE:  I disagree with it,

          19    yeah.

          20              MR. VIDAS:  Yeah.

          21              MR. HELKIE:  But that doesn't mean

          22    I'm right.  I disagree --

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           1                   (Laughter)

           2              MR. VIDAS:  So having spent hours

           3    and hours with petroleum engineers just

           4    discussing this sort of issue and going

           5    around and around, the more you talk about

           6    specifics, the more hard it is to do

           7    generalities.  I understand why you're saying

           8    that.

           9              MR. CLEVELAND:  Can you put up your

          10    curve for world oil production?

          11              MR. VIDAS:  I think it's the

          12    non-OPEC --

          13              MR. CLEVELAND:  Non-OPEC?  Okay.

          14              MR. VIDAS:  But the report has the

          15    whole lot --

          16              MR. CLEVELAND:  I'm curious as to

          17    what the area under that curve is, and what

          18    that is -- well, what that is what ultimate

          19    recovery is compared to what the USGS raw

          20    numbers.  I mean, how much does your economic

          21    truncation of the things -- do you have any

          22    idea?  Just curious.

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           1              MR. VIDAS:  The whole resource

           2    base, I believe, which is the ultimate

           3    recovery of the weekly USGS is,

           4    3300-something billion barrels.  And ours is

           5    3100.

           6              MR. CLEVELAND:  That's it?  Okay.

           7              MR. VIDAS:  So we've knocked it

           8    down 200 -- just for the --

           9              MR. CLEVELAND:  In other words,

          10    that will be the infinite price -- amount

          11    here.

          12              MR. VIDAS:  Right.

          13              MR. CLEVELAND:  I'm not sure

          14    exactly what this is.  I guess if you could

          15    document that, but it's easily -- it easily

          16    comes out of the model.

          17              MR. HENGARTNER:  Jae.

          18              MR. EDMONDS:  When I first started

          19    doing long-term global energy modeling,

          20    working with colleague Ralph Ruddy (?) who

          21    was very enamored by King-Hubbard.  And he

          22    would -- have he would use these King-Hubbard

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           1    curves, and he was always trying to grapple

           2    with how you reconcile them with historical

           3    data.  And he would add a parameter and then

           4    that wouldn't quite do it.  And maybe add

           5    another parameter.  These things got very

           6    elaborate.  And so we eventually just set

           7    that aside.

           8              And what we did is we just went to

           9    a straight graded resource.  Essentially, on

          10    the previous figure, you have effectively a

          11    graded-resource curve defined by three

          12    points.  What you might want to think about

          13    though is that the potential, that's based on

          14    a notion of what we would call today

          15    conventional oil.

          16              MR. VIDAS:  Right.

          17              MR. EDMONDS:  And as I think you

          18    have already pointed out in a couple of

          19    points here in the talk, that definition kind

          20    of is squishy.  I mean, it is sort of always

          21    moving or -- sort of moving out on you.  So

          22    if you get to these with -- at an infinite

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           1    price, you would be surprised, or you

           2    probably wouldn't be surprised -- but you're

           3    not going to have a cleanly truncated

           4    resource because you get into these shales.

           5    And once you start getting into the shales,

           6    you really have a resource that nobody has

           7    ever gone out looking for.  It's like that's

           8    a bad outcome when you're out there

           9    prospecting.  And so you need a way to

          10    actually have that curve -- rather than just

          11    shut itself down as the price goes to

          12    infinity, you actually need a way for you to

          13    open that up.

          14              And the way we did it was we just

          15    added a few extra points.  And so you

          16    actually weren't constrained by

          17    King-Hubbard's thinking about the problem.

          18    You actually had a graded resource.  And I

          19    think we used five different grades of the

          20    resource.  It makes reconciliation with the

          21    real world just so much easier.  So you may

          22    want to think about that.  And then you take

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           1    your reserves out of the resource phase as

           2    you go out and explore further.  And that

           3    works out pretty well.  And so I just put

           4    that forward as a thought.  You might want to

           5    think about it.

           6              MR. VIDAS:  Yeah, when we discussed

           7    the results with EIA, we talked about that.

           8    And I think EIA is well aware of the

           9    phenomenon of non-conventional resources and

          10    how they might fit in.  And there might be

          11    two things you could think about -- or they

          12    could think about doing.  One would

          13    be -- implicit in this is that there is

          14    something called a conventional oilfield.

          15              It has a certain amount of

          16    production that comes out of a field of a

          17    certain size.  And what that represents in

          18    any hearing census or recovery factor that

          19    says that there is a certain amount of oil in

          20    place, and that with conventional production

          21    techniques and certain well-space of a

          22    certain amount and maybe a water flood you

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           1    can get a certain percent of that oil out.

           2    But you could, in theory, if you had a much

           3    higher price, do surfactant floods, you could

           4    do, you know start recovering with nitrogen

           5    or CO2 --

           6              MR. EDMONDS:  Yeah.

           7              MR. VIDAS:  You could do a

           8    thermo-enhanced oil recovery and so on.  So

           9    there is kind of a technological price for

          10    phenomena, which gives you extraordinary

          11    recovery factors in conventional fields, and

          12    that's kind of in theory part of the growth.

          13    Although if you look historically, some of

          14    it's there, but some of it isn't there.  So

          15    one recommendation that we talked about when

          16    we had our discussion was to a bit more

          17    explicitly deal with this growth in the

          18    conventional fields as a function of -- as

          19    you were saying, price --

          20              MR. GRUENSPECHT:  This

          21    conventional/unconventional thing is

          22    very -- sometimes it is talked about as the

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           1    resource, but there is -- I guess you include

           2    secondary recovery in your sort of what most

           3    people call secondary recovery in a

           4    conventional field that is part of your

           5    conventional thing.  But the question is, is

           6    tertiary area on the lot.

           7              SPEAKER:  Right, got it.

           8              MR. GRUENSPECHT:  In conventional

           9    fields, some people would view that as -- I

          10    think that's not in here now; right?

          11              MR. VIDAS:  Well, that's what the

          12    commission does.

          13              MR. GRUENSPECHT:  How long that --

          14              MR. VIDAS:  When you ask somebody

          15    is it in there or not they would say we're

          16    not really sure because we're trying to look

          17    at historical data.  Obviously, there is

          18    tertiary recovery that has happened in the

          19    U.S.

          20              MR. GRUENSPECHT:  Right, in the

          21    (inaudible) and in other places.

          22              SPEAKER:  International fields.

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           1              MR. CLEVELAND:  But oil -- shale

           2    oil is fundamentally a different geologic --

           3              MR. VIDAS:  Right.  And that's why

           4    we're trying to --

           5              MR. CLEVELAND:  So it's a different

           6    technology.

           7              MR. VIDAS:  Right.  And that's why

           8    I was trying draw the distinction between

           9    looking at the population that presumably is

          10    in here, which is to say conventional fields,

          11    and apply unconventional or new ideas to

          12    those conventional fields.

          13              MR. CLEVELAND:  Right.

          14              MR. GRUENSPECHT:  Right -- fields,

          15    right.

          16              MR. VIDAS:  Which will be

          17    represented as increase in recovery factor.

          18              MR. GRUENSPECHT:  Right, people

          19    kind of look at this thing as conventional

          20    and unconventional, like two box models.  But

          21    I think it's sort of like a third box, which

          22    is -- they sort of -- I don't know where you

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           1    draw the line, but it is a continuum of

           2    technology.  But I think in these kind of

           3    things, again, you raise this issue of

           4    unconventional technology in conventional

           5    resources.

           6              MR. VIDAS:  Right.  And the way the

           7    USGS actually will do it is they'll do it the

           8    way Howard has said, which is that there is a

           9    certain type of reservoir which we're going

          10    to call conventional.  And there is other

          11    types of shales and tar sands and so on which

          12    are a different geologic setting.  And we're

          13    going to give those a different name and

          14    apply different technologies.  Now, there is

          15    no resource assessment, world resource

          16    assessment that the USGS has done for

          17    non-conventional resources.

          18              There are placeholders.  If you

          19    look at their databases, there are

          20    placeholders for them, but they haven't

          21    assessed them.  So if you are really trying

          22    to do this, and in the long run it has to be

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           1    able to do this just to calculate -- not

           2    calculate, but at least have a representation

           3    of those conventional and non-conventional,

           4    and then have within the conventional this

           5    idea of technology and technology advances

           6    which increase recovery factor, and it's

           7    actually the same thing for the

           8    non-conventionals which have the same issues

           9    in terms of recovery factors and prices and

          10    technologies.

          11              MR. HENGARTNER:  Now, all this

          12    discussion suggests actually that in terms of

          13    the Hubbard curve, we made be interested in

          14    not one curve but a mixture of curves.

          15              MR. VIDAS:  For different

          16    resources.  That's right.

          17              MR. HENGARTNER:  Right.

          18              MR. VIDAS:  Right.  And this of

          19    course was just the first step, which is

          20    looking at conventional resources using

          21    historical recovery factors which are what

          22    essentially is in the USGS resource

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           1    assessment.  Like you're saying that -- you

           2    would logically want to do this and then add

           3    to it the non-conventional techniques in

           4    conventional fields, and then have another

           5    resource for the non-conventional, which of

           6    course is a -- actually is in SAGE now, as I

           7    understand it.  And so it is in there in a

           8    structural sense already, but it could be

           9    investigated as you were saying.

          10              MR. HENGARTNER:  Yes.

          11              MR. RUTHERFORD:  If everyone wants

          12    an argument from Y2050 -- projecting the 2050

          13    makes sense, let's say this diagram --

          14              MR. HENGARTNER:  Well, making sense

          15    is a big word.

          16              MR. RUTHERFORD:  I'm not saying we

          17    have statistical precision, but the debate

          18    goes -- conceptually, 2050 is not that far

          19    out.

          20              MR. CLEVELAND:  Yeah, it's

          21    interesting to me and this is -- I'm doing

          22    some work at the Robert Kaufman, whose work

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           1    you probably know.  And we have a

           2    paper -- it's in here somewhere, I don't know

           3    where; where we basically, it's much cruder

           4    than this, where we just take different

           5    estimates, take the range of estimates for

           6    what ultimate recovery is, and just fit a

           7    Hubbard curve and it's remarkable how little

           8    difference it makes about when the peak is,

           9    you know --

          10              MR. VIDAS:  Twenty years, you're

          11    thinking.

          12              MR. CLEVELAND:  Maximum.

          13              MR. VIDAS:  Yeah.

          14              MR. CLEVELAND:  Maximum.

          15              MR. VIDAS:  Peak of what?

          16              MR. CLEVELAND:  World oil

          17    production.

          18              MR. VIDAS:  Conventional --

          19              MR. CLEVELAND:  Conventional oil

          20    production.

          21              MR. VIDAS:  Conventional oil.

          22              MR. CLEVELAND:  Yeah.

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           1              MR. VIDAS:  Conventional -- using

           2    conventional recovery factors or --

           3              MR. CLEVELAND:  For all the

           4    assumptions that are pretty much implied in

           5    this as well.

           6              MR. VIDAS:  Okay.  So -- okay.

           7              MR. CLEVELAND:  You know, all the

           8    assumptions -- so you have people who think

           9    there is X zillion barrels and people will

          10    think production is peak.  And those imply a

          11    huge range of assumptions about technology

          12    and price -- whatever they are, we just took

          13    that full range and fit the curves to it and

          14    its remarkable how little difference it

          15    makes; the die is in some fundamental way

          16    cast.

          17              MR. VIDAS:  Of course, that's five

          18    administrations, right?  Twenty years is five

          19    presidents.

          20              MR. CLEVELAND:  Envision how

          21    little -- sensitivity of price here is very

          22    little.

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           1              MR. VIDAS:  Yeah, and as I was

           2    saying before the talk, it has to do with the

           3    economies of scale in oil production, and

           4    then big fields trying to be economic with

           5    $10 or $15, and they're going to be found

           6    first and developed first.  And that's why

           7    you get that long bottom part of the curve.

           8              MR. CLEVELAND:  Right.

           9              MR. VIDAS:  The cost curve, I mean.

          10    Well, thank you for your attention.  I --

          11              MR. HENGARTNER:  Thank you very

          12    much.

          13              MR. VIDAS:  Thank you.

          14                   (Applause)

          15              MR. HENGARTNER:  I think we will

          16    break now and then reconvene in the break out

          17    session.  The people up here are Johnny

          18    Blair, Moshe Feder, Barbara Forsyth, myself.

          19    No, I'm not here.

          20                   (Laughter)

          21              MR. HENGARTNER:  Walter Hill will

          22    be up here.  And we're going to go

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           1    downstairs, Mark Burton, myself, Cutler

           2    Cleveland, Jae Edmonds and Thom Rutherford

           3    and Susan Sereika.

           4                   (Recess)

           5              SPEAKER:  Good morning.

           6              MR. HILL:  Yeah.  Good morning.

           7    I've been deputized to run this session, the

           8    chair of the break-out session.  I assume we

           9    go until about 11:00, with the usual format.

          10    So your presentator discussing and comments

          11    from horseshoe crab -- people in the

          12    horseshoe crab here in the audience.  You're

          13    on.  Good luck.

          14              MR. LU:  Okay.  Good morning

          15    everybody.  My name is Ruey-Ping Lu.  I'm

          16    from Statistical and Method Group.  I'm going

          17    to present the study results of the weekly

          18    monitoring of stocks of oil from monthly

          19    data.  Okay.  Well, typically we have to put

          20    up the disclaimers, for this is ongoing

          21    project, so just present to you and solicit

          22    your advice, so we can do better job to serve

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           1    the public.

           2              And let me give you a little bit

           3    the story about the stock of crude oils and

           4    the petroleum products.  And EIA published

           5    monthly petroleum -- supply monthly, okay.

           6    That's monthly data.

           7              And the major petroleum products

           8    are the crude oil, motor gasoline, distillate

           9    fuel oil, residual fuel oil, jet fuel,

          10    unfinished oil, propane and other oils.

          11    These are all from surveys from the

          12    refineries, the petroleum supplies, so we

          13    have no problems.  These other oils in the

          14    monthly basis, we have no problem either.

          15    But in the weekly basis, we do have a story.

          16              The problem comes -- thing is we

          17    tried to estimate other oils, the weekly

          18    other oil stock.  And this one is published

          19    in the weekly petroleum status report.  Okay,

          20    this is the latest one.  They published it

          21    last week.  And the one I showed before they

          22    published end of last month, which you will

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           1    see it's September.  And included was the

           2    data for July 2006.  See there is a two-month

           3    lag; I'm going to talk about that.

           4              So here, we want to determine the

           5    best way to estimate weekly stocks of other

           6    oil based on weekly data from the major

           7    petroleum products, plus monthly data for

           8    other products.  And also, we try to evaluate

           9    alternative methods by comparing couple of

          10    different estimates.

          11              In these projects, we use the data

          12    from 1993 to 2005, the monthly stocks, also

          13    the weekly stocks.  You can see weekly stocks

          14    at many other -- major petroleum products.

          15    In -- compared to the monthly and the weekly,

          16    they are two months' lag, that's exactly here

          17    you can see.  Okay?  It published last

          18    month's, but in October, we don't have August

          19    data.  We only have July data, so we still

          20    have to use the July data -- or up to the

          21    July data to help us to estimate the October

          22    weekly numbers.

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           1              See the story here?  Because we

           2    don't have a survey to collect this, the

           3    components of the other oil stocks.  See, the

           4    components of other oil stocks are aviation

           5    gasoline, kerosene, and all these small

           6    pieces.  They add up as not as small pieces.

           7    Okay?  Altogether, and we have a monthly

           8    survey to collect all this, but we don't have

           9    a weekly survey to collect all this.  And our

          10    customer wants weekly number because they can

          11    what, check on the financial market.  We've

          12    those -- some of those components play some

          13    roles in the financial market.

          14              So you can see the components of

          15    all these were about 11 or 12 different

          16    pieces.  And when we displayed the numbers of

          17    the weekly number, okay, check to the

          18    months -- end of the months, and then compare

          19    to the monthly number, the blue one is the

          20    PSM, is the Petroleum Supply Monthly.  Okay,

          21    so two months behind by the blue one.  And

          22    this is the weekly.  I interpret the weekly

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           1    to the end of the months, plot it.  Here

           2    that's above 20 percent difference.  Now, it

           3    looks like it's not much, but if you look at

           4    the scale, okay, that's above 20 percent

           5    discrepancy.  We're now going to say which

           6    is, but generally we'll use this as a

           7    benchmark.  So we would say there is a

           8    discrepancy.

           9              Somehow, there's a story of that is

          10    natural gas price shoot up.  Okay, and the

          11    monthly number goes down, and we didn't catch

          12    that.  But later, yes, we did.  Okay.  So our

          13    front office and the customer noticed this,

          14    so we're going to study is there any way we

          15    can improve the estimate of the weekly

          16    number.  As it caused not this much

          17    discrepancy, because there'll be something

          18    like that.

          19              Next.  Okay, because of the problem

          20    in the 2003, like January to April, in the

          21    first week of April 2004, we start collecting

          22    the weekly propane.  Before, the propane

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           1    number was only collected during the winter

           2    month on a weekly basis, otherwise on a

           3    monthly basis.  And propane is a big

           4    component in the other oil stock, so we try

           5    to solve part of the problems is -- get a

           6    weekly number out of propane.  So we can have

           7    big chunk which is more precise than trying

           8    to estimate the others.  Okay.

           9              So my work is trying to look for

          10    different methodology or alternative methods

          11    to model the weekly stock of the other oils.

          12    So what I did is using the multiple

          13    regression modeling and unobserved components

          14    models.  I don't know you -- I mean, it was

          15    this one -- this was published by Harvey in

          16    the late '80s in British, so that time, it

          17    did not have the computer program, until two

          18    years ago, assess the -- publish a procedure,

          19    which can run -- called UCM, unobserved

          20    components model.

          21              Then we will compare the forecast

          22    or the estimate of the Petroleum Supply

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           1    Monthly number, okay?  I treat the multiple

           2    regression model using the monthly data from

           3    1993 to 2001, and the dependent variable will

           4    be the major petroleum product, but the

           5    stocks.  So you can see those -- model

           6    gasoline, jet fuel, distilled.  And plus, the

           7    months lag and so on.  Okay.  So then we can

           8    predict using the 2002 up to the 2005 monthly

           9    number.

          10              But in doing this, I didn't gather

          11    the weekly number.  Once I get a monthly

          12    projection or the monthly estimate, then I

          13    used that to interpret in the weeklies.

          14    Okay, which means I still can compare the

          15    estimate, but in order to get the weekly

          16    number, I have to do some other

          17    way -- intervals or make the monthly and get

          18    the weekly number.

          19              The unobserved components model is

          20    you have a time series.  You list this time

          21    series as several different components, like

          22    you have a trend, okay?  And you have

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           1    seasonal and you have a cycle, and you have,

           2    auto regressive terms, plus multiple cycles

           3    and other things, which will be sort of the

           4    marriage of ARIMA model and the multiple

           5    regressions.  Okay, the only thing they have

           6    to assume is, oh, these different components

           7    are independent.

           8              Okay?  So you can see here, we can

           9    express the numbers in terms of the

          10    trans-season cycle, auto regressive and the

          11    lag variables plus regression.  That's a

          12    multiple regression piece.  Okay.  So let's

          13    look at the result of that.  And in the

          14    multiple regression, I run two different -- I

          15    run a bunch of models and these two performs,

          16    well, better feet (?) and better prediction.

          17    So you can see it's the range of the mean

          18    absolute present error and also the range.

          19    Unobserved components model is pretty good

          20    compared to the regression.

          21              And we have another division to

          22    the -- we call the STEO, it's a short-term,

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           1    energy outlook.  They did three months ahead

           2    or a month -- a year ahead prediction.  So

           3    they have another different multiple

           4    regression model running.  Okay.  So that's

           5    the number they provided me.  So I compare

           6    that, it's with the same intervals.  And this

           7    is we published.  Weekly petroleum supply

           8    report.  Okay.  And this 24 is the circle we

           9    have to start off this project.  Okay, now,

          10    if we check on the -- what, from year to

          11    another year, to 2002, 2003, 2004, 2005.

          12              Okay, the comparison, you can see

          13    unobserved components model is pretty good

          14    compared to currently used.  Okay?  So if I

          15    give you the picture of this -- this, the

          16    problem we had, okay, 2000, early -- that's

          17    the year, beginning of the -- what, 2003

          18    January to the April 2003, okay?  And look in

          19    the blue ones, okay?  It's -- we see above up

          20    and down 10 percent, I hope -- get to the

          21    what?  5 percent.  That'll be what, ideal, so

          22    we can have better estimate.  The things may

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           1    be used sometimes, when you're free to

           2    unobserved components model.  Some

           3    coefficient may not be, or some variables may

           4    not be significant.  So I have to add more

           5    data into it.  Okay.  So that turns

           6    out -- the model is there whether when you

           7    feed in the numbers or the datas, it may

           8    change a little bit before what you've

           9    forecast.

          10              Okay?  That's the result that we

          11    have, then I would like to have your advice

          12    is, are we ready to use this unobserved

          13    components model or called structural model

          14    to estimate other oil stocks?  Currently, our

          15    petroleum supply division is running 19-20

          16    different models, then they pick up one,

          17    which is plus the expert opinions, say this

          18    is the one, we saw them marketed in your

          19    concern, they put up as a weekly other oil

          20    stocks.

          21              Then it's good, you can see which

          22    is comparable to what I did on the modeling,

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           1    but the only thing is when they pick that,

           2    they have an expert opinion, it may not be

           3    reproducible.  So which is published, okay,

           4    but they may not be reproduced again and

           5    again.  If I have the modeling simply as

           6    adopted then we can rang it to a (inaudible).

           7    And a year later, we checked the model, fit

           8    it, how good is, then we try to adjust that.

           9              And another thing is in the Short

          10    Term Energy Outlook Division or -- that is a

          11    EMEU office, they'll have another number

          12    published, whether that's the monthly number.

          13    So we're trying to reconcile, which is EIA to

          14    publish almost the same number, not to do it

          15    one number and the other one is little bit

          16    different.  They are discrepant each other,

          17    okay.

          18              And that is my presentation.  So I

          19    would like to have your advice how we go on

          20    this.  Yes.

          21              MR. HENGARTNER:  Thank you very

          22    much.

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           1              MR. FEDER:  Actually, I have lots

           2    of questions, so maybe others should ask

           3    first, and I'll ask my questions.

           4              MR. HENGARTNER:  Go ahead.  Oh, you

           5    want to --

           6              MR. FEDER:  No, I'm going last

           7    because I have many questions.

           8              MR. HILL:  I have one

           9    technical -- when you put up your model,

          10    there was a -- it's a regression model.  You

          11    typically worry about the correlation of the

          12    error (?) terms.  Back two screens?

          13              MR. LU:  I think before that, yeah.

          14              This one?

          15              MR. HILL:  Yes.  Let me look at it

          16    again.  Entered into the IID.

          17              MR. LU:  Uh-huh.

          18              MR. HILL:  Usually it's hard often.

          19    Firstly you taught us how to make that

          20    assumptions.

          21              MR. LU:  Yes.

          22              MR. FEDER:  I don't know if you --

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           1              MR. LU:  Generally, they assume

           2    each component is a stochastic.  Okay.  You

           3    can test that, if not then you assume it is

           4    deterministic.

           5              MR. FEDER:  You didn't give a model

           6    for MuT?  What is the model for MuT?

           7              SPEAKER:  They're trying to --

           8              MR. FEDER:  Yeah, yeah, there's a

           9    model for it.  Are you assuming you have a

          10    stochastic?  What is the model for that?  How

          11    do we always say it's a model for the trend?

          12              MR. LU:  Oh, model for MuT is just

          13    the -- it's a number.

          14              MR. FEDER:  It's not because you

          15    don't have the stationary theories.  Usually

          16    we have been -- most of his models, MuT is

          17    given as MuT minus one, plus stochastic

          18    slope, which is around the work.  And I

          19    think -- but I don't know what T is in your

          20    case, but usually there is a model from

          21    MuT --

          22              MR. LU:  MuT is the trend and the

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           1    gamma T is the season.

           2              MR. FEDER:  I know, I know.  Yeah,

           3    but the question is what model used, what is

           4    the stochastic nature of MuT?

           5              MR. LU:  Oh, MuT.

           6              MR. FEDER:  I'm pretty sure what

           7    you've from MuT -- is -- MuT equals MuT minus

           8    one plus stochastic slope, and usually for

           9    the slope, you assume a random block model.

          10              MR. LU:  Yes, I did check it,

          11    whether it's random work or not.  Yes.

          12              MR. FEDER:  From not -- but not

          13    from MuT, for the slope, which is MuT minus

          14    MuT minus one.

          15              MR. LU:  Oh, yes.  We check -- is

          16    the Y T minus Y T --

          17              MR. FEDER:  No, no, not Y T, MuT.

          18              MR. LU:  I know, but when you look

          19    at the Y T and the Y T minus 1 --

          20              MR. FEDER:  Right.

          21              MR. LU:  Then you can have all

          22    those.

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           1              MR. FEDER:  But for that, you

           2    also --

           3              MR. HILL:  Okay, maybe the

           4    question's whether MuT is a constant -- we

           5    suspect it's not -- if you go by the stat --

           6              MR. LU:  Let's go by the T --

           7              SPEAKER:  Because MuT is --

           8              SPEAKER:  Go by the T.

           9              SPEAKER:  It's not a constant, not

          10    a constant.

          11              MR. FEDER:  Not a constant, not a

          12    constant.  And not just -- just independent,

          13    because -- the trend should change slowly

          14    over time.

          15              SPEAKER:  To change --

          16              MR. FEDER:  And to make this -- you

          17    make this -- the difference being a random

          18    log.  But okay, I have a few questions here.

          19    In your modeling what is your -- yeah, Y T.

          20    Do you model also the monthly basis in this

          21    model or you fit this model only to the

          22    weekly --

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           1              MR. LU:  Okay, I have the monthly

           2    number.  Okay.  For the -- for everything.

           3              SPEAKER:  Right.

           4              MR. LU:  Then I convert to the

           5    weekly number for the major product.

           6              MR. FEDER:  So this model is fitted

           7    to both the monthly data and to the total

           8    petroleum stocks and petroleum, I mean, the

           9    weekly data that you have to both, right?

          10              MR. LU:  Yes, I convert everything

          11    to the weekly, then free the weekly numbers,

          12    do the forecast for 14 weeks, because I need

          13    these three months ahead.  Like here we say,

          14    we publish this in the end of September.

          15              MR. FEDER:  Right.

          16              MR. LU:  And I need to estimate or

          17    forecast the October weekly number.  And I

          18    can only use up to the July number.

          19              MR. FEDER:  Yeah.

          20              MR. LU:  Okay?  So I need to focus

          21    August, September, and October.

          22              MR. FEDER:  Yeah --

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           1              MR. LU:  But I will not use

           2    October -- August and September, I only use

           3    October number.

           4              MR. FEDER:  No -- I understand

           5    that, and you said that you use the data

           6    from -- beginning for 1993 to --

           7              MR. LU:  To 2001, yes.

           8              MR. FEDER:  So in -- when you

           9    fitted the model and estimated all those

          10    parameters, did you use all the data that you

          11    had, the converted monthly data and the

          12    weekly data, all of that?

          13              MR. LU:  Yes.

          14              MR. FEDER:  Okay.

          15              MR. LU:  So maybe the weekly base

          16    can go along.

          17              MR. FEDER:  Okay, I --

          18              MR. LU:  And now I have, for

          19    example, forecast the October, I do use the

          20    weekly published major petroleum product in

          21    the model.

          22              MR. FEDER:  In the model?

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           1              MR. LU:  Yes.  If they are in

           2    the -- because they are here.

           3              MR. FEDER:  No, the seasonality, is

           4    it quarterly here or monthly?  What did you

           5    say?

           6              MR. LU:  It's yearly.

           7              MR. FEDER:  No, the seasonality.

           8              MR. LU:  I know.

           9              MR. FEDER:  I know that cycle --

          10    what is -- is it a -- the seasonality terms,

          11    how many seasonal terms did you have there?

          12              MR. LU:  Just one.  Yeah, so I used

          13    it a -- come out with 53 -- 52.  It's 53,

          14    yes.

          15              MR. FEDER:  A week?

          16              MR. LU:  Yes, yes.

          17              MR. FEDER:  Yes, also you have 52

          18    dummies there.

          19              SPEAKER:  That's -- yeah, that

          20    might be over 15.

          21              MR. LU:  Yes, I have a --

          22              MR. FEDER:  You've been able to

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           1    estimate it, okay.

           2              MR. LU:  Well, you find out

           3    seasonality is not significant.  Okay, so

           4    when I run the actual model, some components

           5    are significant, some are not.  Okay, when I

           6    run these -- propane is the one, will be my

           7    regressive.

           8              MR. FEDER:  It may be that your

           9    seasonal terms turn out to be non-significant

          10    because you had weekly seasonality which may

          11    be too much.  If you tried -- actually, I

          12    wrote the --

          13              MR. LU:  The cycle?

          14              MR. FEDER:  I wrote the paper

          15    on -- I used executive same models, actually

          16    Nancy has a copy.

          17              MR. LU:  You mean the UCM, this

          18    one, structure model.

          19              MR. FEDER:  Yeah, but it used that.

          20    It was -- yeah.  Dr. Ferry (?) commented that

          21    trigonometric representation of

          22    seasonality --

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           1              MR. LU:  Yes.

           2              MR. FEDER:  Is better than the

           3    dummy variable in representation.

           4              MR. LU:  Okay, yes.

           5              MR. FEDER:  And I think if you use

           6    that, and if you had just quarterly or maybe

           7    monthly seasonality instead of weekly, you

           8    would get more significant terms of the

           9    seasonal.  I -- this is my guess.  I --

          10              MR. LU:  So you mean I should

          11    use --

          12              MR. FEDER:  Because you have so

          13    many parameters, then getting significance

          14    can be a problem.

          15              MR. LU:  So instead of 53, I should

          16    use 13 weekly?

          17              MR. FEDER:  I would -- 11.

          18              MR. LU:  Yeah.

          19              MR. FEDER:  12 minus 1, yeah.

          20              MR. LU:  Oh, okay.

          21              MR. FEDER:  Monthly -- I think so,

          22    maybe even quarterly.  I'm not familiar with

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           1    the subject matter to say it with certainty,

           2    but I would at least suggest to try.

           3              MR. LU:  Okay.  But if you'll say

           4    11 --

           5              MR. FEDER:  The number -- oh, well,

           6    the number of seasonal terms is number of

           7    periods minus one.  That's the --

           8              MR. LU:  Yeah, but three months

           9    will be 13 weeks, not 12 weeks, right?  Any

          10    places, I didn't know what happened.

          11              MR. FEDER:  I understand as to

          12    what --

          13              MR. LU:  Yeah, quarterly, right?

          14              MR. FEDER:  Twelve months, yeah,

          15    that's what I'm --

          16              MR. LU:  Oh, you go by a month.

          17    Okay, 12 okay.

          18              MR. FEDER:  Just --

          19              MR. LU:  I thought it was a weekly.

          20              MR. FEDER:  No, because your model

          21    has so many parameters.

          22              MR. LU:  Yes.

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           1              MR. FEDER:  That's usually a

           2    problem unless you have a very long series,

           3    and you have only 10 years of data, so --

           4              MR. LU:  Yes, I have 400 something,

           5    yes.  And you did -- I used the 400 -- 440

           6    and 0.2 feet. (?)

           7              MR. FEDER:  It's helped to saying

           8    thus -- actually running it.  You may have

           9    enough data, I'm not sure.

          10              MR. LU:  Yeah, but the full model

          11    won't be good.  So I had to kick out

          12    some -- and make it determinalistic.  So in

          13    this stochastic sense, there are only few of

          14    them.  Yeah, most of the audit, it didn't

          15    come out significant.

          16              MR. FEDER:  Now, you showed us the

          17    time series plots beginning with 2002.  Have

          18    you looked at the entire series from 1993?

          19    Because we didn't see, I mean, that --

          20              MR. LU:  Oh, no.

          21              MR. FEDER:  You might learn

          22    something from it.  I mean, just looking at

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           1    the --

           2              MR. LU:  You mean, I should have --

           3              MR. FEDER:  Yeah --

           4              MR. LU:  Forecast back?

           5              MR. FEDER:  Yeah, yeah, yeah --

           6              MS. FORSYTH:  To evaluate it, it's

           7    like --

           8              MR. FEDER:  Yeah, yeah.  Just to

           9    evaluate the fitness of the model.

          10              MR. LU:  Okay.  You mean, the

          11    monthly or the weekly base?  Because here

          12    it -- we publish weekly numbers knowing we

          13    would never adjust, or just to let it go.

          14    But in monthly, we may, or we have with us

          15    what, annual numbers.

          16              MR. FEDER:  No, I would say for

          17    evaluation purposes, to see how good --

          18              MR. LU:  The model.

          19              MR. FEDER:  Unobserved components.

          20              MR. LU:  Okay.

          21              MR. FEDER:  Yeah, yeah, I think you

          22    are right, you have to do it monthly or

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           1    quarterly, just to get a visual impression of

           2    how good the models are, because there could

           3    be some things that happen where there was a

           4    break in the series for some economic

           5    reasons, so the model might be affected.  The

           6    fitness of the model might be affected by

           7    some spikes in those series and things like

           8    that.

           9              MR. LU:  Yes.  Since you have

          10    experience over the UCM, I once -- this in

          11    some month, the feats are good under the AIC,

          12    Akaike Information Criteria is good.  But in

          13    some months they just -- boom, blow out.  So

          14    what happened?

          15              MR. FEDER:  Yeah.  I don't know.  I

          16    was fortunate to work with series that are

          17    more stable.

          18              SPEAKER:  Oh.

          19              MR. FEDER:  You mentioned that SAS

          20    came out with their procedure two years ago.

          21    I wrote my own procedures.  I didn't -- I

          22    wrote them actually in Gauss, so I --

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           1              MR. LU:  Oh, you used the Gauss,

           2    oh.

           3              MR. FEDER:  Okay, there is actually

           4    also a package that --

           5              MR. LU:  Stem.

           6              MR. FEDER:  Gilbert from the Bank

           7    of Canada wrote for --

           8              MR. LU:  Yes.

           9              MR. FEDER:  That's been around for

          10    a long time.

          11              MR. LU:  But do they have a UCM?

          12              MR. FEDER:  Yeah.

          13              MR. LU:  Oh, then --

          14              MR. FEDER:  It's called --

          15              MR. LU:  If they have (inaudible)

          16    then --

          17              MR. FEDER:  It's called DSM,

          18    Dynamic Structural Models.

          19              MR. LU:  Okay.

          20              MR. FEDER:  You wrote it a long

          21    time ago, it's available for free.

          22              MR. LU:  For free, yes.

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           1              MR. FEDER:  And (inaudible) as

           2    opposed to -- his name is Gilbert, first

           3    name, Paul -- Paul Gilbert.

           4              MR. LU:  Okay.

           5              MR. FEDER:  From Bank of Canada.

           6              MR. LU:  What happened is when I

           7    run it, so many (inaudible) one or two

           8    months.  The feets are terrible and the AIC

           9    numbers are way off.  Then go on and stable

          10    again.  So I'm wondering something missing.

          11              MR. FEDER:  Right.

          12              MR. LU:  That will being

          13    your -- the case, which I have (inaudible)

          14    forecast.

          15              MR. FEDER:  That's a good question.

          16    This is where subject matter people need

          17    to --

          18              MR. LU:  Well, he is the -- Mike is

          19    the manager of the -- this weekly and monthly

          20    production -- publication.

          21              MR. CONNER:  The question

          22    is -- tell me again what the question is.

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           1              MR. FEDER:  Well, he saw some

           2    misfit in some when you go back historically

           3    and you look at the expected -- I mean, what

           4    you do is for every point of time T, you can

           5    use the data up to the time T to predict the

           6    next observation, and then you look at the

           7    difference.  And if the prediction -- that's

           8    called -- the difference is called a

           9    prediction error.  And sometimes that is

          10    small, sometimes it's more than you expect --

          11              SPEAKER:  Yeah.

          12              MR. FEDER:  Which is the model

          13    doesn't give a very good prediction of the

          14    next value.  And that could be because

          15    something happened and the model doesn't

          16    know, but subject matter -- subject matter

          17    people might now.  So this is where we

          18    statisticians have to say, I don't know what

          19    happened here, do you guys know?  But I would

          20    check because I personally don't use SAS

          21    much, and I don't know what those (inaudible)

          22    procedures do.  I prefer -- I think it's

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           1    unnecessary whether to say, but I mean you

           2    have to look and see what the model is and

           3    what the model for the trend is, and what

           4    kind of seasonality they use and compare it

           5    to other packages as well.

           6              Actually I want to say that I like

           7    the unobserved components model and I think

           8    that's the way to go, but maybe even that can

           9    be improved.  And I think Barbara also

          10    mentioned that maybe there is some other

          11    symptomatic variable that you can use in your

          12    regression.

          13              MR. LU:  Oh, okay.

          14              MR. FEDER:  That might improve it;

          15    that can explain the spike -- I can give an

          16    example how we actually did a paper on the

          17    effect of seat belt legislation in Britain on

          18    fatalities, highway fatalities.  And they had

          19    an intervention term which accounted for the

          20    introduction of the legislation.  In your

          21    case, maybe some kind of change in the market

          22    could also be entered into the model to

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           1    explain a big discrepancy between the

           2    observed and the expected or things like

           3    that.  So this is where -- subject where the

           4    people can bring in other variables and other

           5    knowledge into the model.

           6              MR. CONNER:  Yeah, and actually one

           7    of the ones that -- that's always been sort

           8    of my head theory, if you will, is that

           9    there's actually -- we talk about the fact

          10    that we have inventory data in all these

          11    major products.  But we don't have any survey

          12    data on the other oils.

          13              But it's always been -- been my

          14    feeling, just having looked at the data in

          15    sort of an informal way, that there are in

          16    fact relationships between the inventories

          17    for which we do have survey data and the

          18    inventories of the other oils, specifically

          19    because in the refining business, nobody

          20    shows up at the refinery for work and says,

          21    lets make other oils today.  They say, we're

          22    going to make gasoline today.

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           1              And the other oils are large

           2    by-products of the other processes in the

           3    refinery, and therefore, to the extent that

           4    you know the crude runs and the production of

           5    these various other things from the survey

           6    data, there ought to be things that you can

           7    infer about where the other oils inventory

           8    should be going based on that, as well as

           9    other factors, you know?  You obviously got a

          10    lot of --

          11              MR. LU:  The propane is the one

          12    highly correlated with the other oil stocks.

          13              MR. FEDER:  But since you asked

          14    us -- you asked the committee about

          15    recommendation, can I just say -- so maybe

          16    it's not the committee, but my recommendation

          17    would be yes, to go with that.  Consider a

          18    few things in the model, such as including

          19    more variables, including -- look if you can

          20    use -- now you also converted monthly data

          21    into weekly --

          22              MR. LU:  Into weekly, yes.

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           1              MR. FEDER:  Which you can -- you

           2    don't have to do it if you write the

           3    observation equation in the (inaudible)

           4    models in the right way, so maybe you don't

           5    need to do the conversion.  But that's too

           6    technical; we haven't seen enough details to

           7    comment on that.  I would also try to fix

           8    seasonality which is less, shall I say

           9    greedy, not have too many seasonal terms,

          10    just because when models become very big,

          11    their performance become less predictable.

          12              MR. LU:  Okay.  But the -- in fact,

          13    the seasonality is not there.  Or can I use

          14    any cycle?  Even though there's no

          15    seasonality or just cycle, cyclic effect.

          16              MR. FEDER:  The cycle is -- has a

          17    larger -- that's the economic cycle, right?

          18              MR. LU:  No, you can have three or

          19    four, the cycle.

          20              MR. FEDER:  Yeah, I don't know.

          21              MR. LU:  The quarter is in numbers.

          22    Like a --

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           1              MR. FEDER:  But then it becomes a

           2    seasonality, right?  Cycle in this context

           3    usually is a multi-year cycle, I'm not an

           4    economist, but I think that's what

           5    they -- Walter, do you know if the term cycle

           6    here usually used for longer period?

           7    Business cycle, I know that business cycle

           8    usually applies to a longer period.

           9              MR. LU:  Oh, okay.

          10              MR. FEDER:  But I don't know about

          11    SAS -- you calling cycle here.  If this is

          12    less then it's confounded with seasonality,

          13    then you're not going to get anything out of

          14    it.

          15              MR. LU:  You may.  Yeah, you may

          16    confound it.

          17              MR. FEDER:  Yeah, I think you're

          18    talking here about a business cycle, which is

          19    a longer period than the seasonality.

          20              MR. LU:  Yeah, generally you pick

          21    up one or the other.  We either use in cyclic

          22    effect or --

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           1              MR. FEDER:  And again, one more

           2    thing is plot the series beginning from --

           3              MR. LU:  The data I have.

           4              MR. FEDER:  And look at all this

           5    and the subject matter, people should look at

           6    all the big prediction errors to see if

           7    there's an explanation for that.  As a way

           8    of, as Barbara said, to see if how well the

           9    model fits.

          10              MR. LU:  Okay.  Yeah, because we

          11    saw that the biggest problem is in 2003.  So

          12    we'll concentrate on there and go on

          13    (inaudible) whatever happened to before,

          14    because before it's done so we has a -- hey,

          15    here's the problem, we don't want a similar

          16    thing happen in the future, in 2003 -- 2004,

          17    2005 or even this year, you know.  What

          18    happened is end of 2005, we have a little bit

          19    of sense this committee coming out again.

          20              So we generally have to rely on the

          21    experts and say, do you sense any discrepancy

          22    of your weekly and monthly numbers at the end

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           1    of the 2005 or at the beginning of 2006.  Or

           2    a missing market will tell you and we don't

           3    know.  Because so long it was three months

           4    lag.  You know, even we say two months data

           5    available, it's a three months lag.

           6              MR. FEDER:  Yeah.

           7              MR. LU:  A missing happening in

           8    these three months is a big intervention;

           9    right?

          10              MR. FEDER:  Yeah.

          11              MR. LU:  It may give the weekly

          12    number off by a lot.  You know, like I

          13    believe in 2003, there was an embargo from

          14    Venezuela, is that right?

          15              MR. CONNER:  Yeah, there were some

          16    issues with crude production in Venezuela

          17    around that time.

          18              MR. FEDER:  That has to go in to

          19    the model as a fixed -- as opposed to

          20    non-random effect, and that can take care of

          21    it.  I can give you an example

          22    what -- actually, it's in this paper which I

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           1    sent Nancy a couple of years ago when we did

           2    the estimation of -- for households in Canada

           3    from -- and we had data coming from three

           4    different sources.

           5              Like, okay, so you had, one was the

           6    census, which in Canada is every five years,

           7    not every 10 years like here.  The other

           8    source of data was the big source of data

           9    that was the labor force survey, which

          10    is -- which had given us monthly data, and

          11    then we also had the demographic series of

          12    the number of people.  Number of people is

          13    linked to the number of households because

          14    everybody has to live somewhere and so we

          15    used that, too.

          16              And what we did, we wrote, like

          17    yours, unobserved component model, we call it

          18    the --

          19              MR. LU:  Structure.

          20              MR. FEDER:  Structure model, right.

          21              MR. LU:  Yeah, dynamic structure.

          22              MR. FEDER:  And we wrote with the

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           1    observation equation written in such a way

           2    that all the data we had was represented, the

           3    selenium function of the unobserved

           4    components.

           5              MR. LU:  Okay.

           6              MR. FEDER:  And I can tell you that

           7    I did this in -- I did it in 1999 and in 2001

           8    there was a census and I visited in

           9    Canada -- I believe this -- yeah, I was then

          10    in Britain and the demographer that worked on

          11    my data told me that the predictions were

          12    within one percent of the actual numbers.

          13              MR. LU:  Wow.

          14              MR. FEDER:  So, but, we don't have

          15    volatility like that with households --

          16              MR. LU:  Human beings are easier to

          17    observe.

          18              MR. FEDER:  Huge improvement of

          19    what was known before.  And so -- but I know

          20    your data are much more volatile, and you can

          21    see it in the plots.  And we had much better

          22    data.  This -- I also serve in Canada, the

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           1    labor force survey is 70,000 people every

           2    month.

           3              MR. LU:  Yeah, pretty good.

           4              MR. FEDER:  So what I'm saying is

           5    by writing the observation equation in your

           6    states based model correctly, you can capture

           7    all the data that's in your --

           8              MR. LU:  Different components.

           9              MR. FEDER:  In the three sources of

          10    data that you have here.

          11              MR. LU:  Okay.

          12              MR. FEDER:  But yeah, it's not an

          13    easy -- I mean, there's a lot of work that

          14    needs to be done here.  But I think -- and

          15    you can account for the lag, the three months

          16    lag and for the difference in periods,

          17    everything can just go in to the model.  My

          18    only concern is I'm not sure the SAS

          19    procedure has the flexibility in it, you may

          20    need to either write your own procedures or

          21    not then make some compromises, that's all.

          22    I think Gilbert's package may have some

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           1    capabilities, too, that package I mentioned

           2    to you before as --

           3              MR. LU:  Okay.  Yeah, in R --

           4              MR. FEDER:  Yeah, yeah.

           5              MR. LU:  Here, SAS is easier to

           6    input, then you can write and then they tell

           7    you the components.  You can specify the

           8    components in different terms, then you check

           9    the significance of each one.

          10              MR. FEDER:  I don't use SAS enough

          11    to say I don't know.

          12              MR. LU:  Okay.

          13              MR. FEDER:  But maybe, I mean, SAS

          14    is a good product, so maybe they have all

          15    these capabilities, I just don't know.

          16              MR. LU:  But it is an interesting

          17    piece because the whole theory was published

          18    in Britain, to start with.

          19              MR. FEDER:  Yes.

          20              MR. LU:  So British people should

          21    have a better (inaudible) programs to run

          22    this.

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           1              MR. FEDER:  The Bureau of Labor

           2    Statistics is using all its monthly estimates

           3    now based on states based model.

           4              MR. LU:  Okay.

           5              MR. FEDER:  I can --

           6              MS. BLUMBERG:  There were some

           7    papers at the joint staff meetings on that I

           8    went to.

           9              MR. FEDER:  Yes.

          10              MS. BLUMBERG:  I can't --

          11              MR. FEDER:  You can talk to Stuart

          12    Scott, William Bell, and Richard Tiller.  All

          13    these people are using these models and have

          14    written papers on it -- and here in town.

          15              MR. LU:  Okay, can I send you the

          16    e-mail then you'd --

          17              MR. FEDER:  Absolutely.

          18              MR. LU:  Yeah, you tell me, how who

          19    I can contact and get the census.

          20              MR. FEDER:  I can actually -- yeah,

          21    yeah.  But, all the -- I mean, I know the

          22    Bureau of Labor Statistics in fact, they're

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           1    also having an effort now to use benchmarking

           2    procedures built on states based modeling,

           3    which is the same as the unobserved

           4    components model to benchmark the (inaudible)

           5    data to the national estimate.  So, --

           6              MR. LU:  Yeah, there's a --

           7              MR. FEDER:  They're doing a lot of

           8    work on that.  Richard Tiller, T-i-l-l-e-r,

           9    is involved in all these things, so you can

          10    contact him for example.  Stuart Scott and

          11    William Bell used to work on it as well.

          12              MR. LU:  This one have a several

          13    difference.  Some people call dynamic

          14    structure, now you'll see that we'll call it

          15    structural models.

          16              MR. FEDER:  Technically speaking,

          17    that the structural model, the stripes, what

          18    we're assuming about the process, and then

          19    you can represent it at the states based

          20    model.  So technically, the two aspects of

          21    slightly different things, but you're right,

          22    people use different technology and --

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           1              MR. LU:  Yes.

           2              MR. FEDER:  Yeah, but actually,

           3    since how we started that, we've used it in

           4    Canada, I wrote a paper with two

           5    collaborators on Australian data and then, as

           6    I said, actually one of them wrote this

           7    papers with filler here in Washington, I'm

           8    using this method, so it's used here too.

           9              MR. LU:  Okay.

          10              MR. FEDER:  In fact, I'm told that

          11    all the BLS estimates of unemployment are

          12    based on states-based modeling.

          13              MR. LU:  Do they use that to adjust

          14    or do they use that to benchmark?

          15              MR. FEDER:  No, no.  Right now to

          16    adjust but there's a ongoing project to do

          17    benchmarking.

          18              MR. LU:  Okay.

          19              MR. FEDER:  To improve the

          20    precision of those estimates.

          21              MR. LU:  Yeah, because I know they

          22    have a weekly number and they also have a

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           1    monthly number.  You know, the only thing

           2    weekly number they won't coincide is the said

           3    date.  Well, you probably see the monthly and

           4    we may not be probably seeing the weekly

           5    number.  Here we probably see weekly on every

           6    Friday, right Mike?

           7              MR. CONNER:  That's correct.

           8              MR. LU:  And then in the monthly --

           9              MR. CONNER:  I think they're

          10    collected as of Friday, we publish on

          11    Wednesday.

          12              MR. LU:  Yeah, yeah, collected on

          13    Friday and then published on Wednesday.

          14              MR. FEDER:  If you Google the names

          15    of Tiller and Pfefferman, you'll probably hit

          16    the website at Southampton when they have a

          17    working paper on that which you can download

          18    as well.  And you're --

          19              MS. BLUMBERG:  Scott -- Stuart

          20    Scott and Bell both gave papers at -- just go

          21    in because we all got that -- we all got a CD

          22    with all the abstracts on it, so you can just

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           1    pull that off.

           2              MR. FEDER:  Do you mean this

           3    year's?

           4              MS. BLUMBERG:  This year, yes.

           5              MR. FEDER:  From the abstract web

           6    page you can download a lot these papers,

           7    including Pfefferman's papers that he's done

           8    in the 1990s.

           9              MS. BLUMBERG:  And I think I have

          10    one of them, I remember some test, I went to

          11    the session, but -- I'll make a copy and send

          12    it over to you.

          13              MR. LU:  Okay, so 2006, JSM.

          14              MR. FEDER:  Ruey-Pyng, you're

          15    actually right that historically it started

          16    in -- with Harvey and Europeans were doing it

          17    more, but I would say the last 10 years it

          18    become more and more common in this year, and

          19    now the BLS, that's what they use, so

          20    it's -- and now as I learned from you it's

          21    also part of SAS.  And Gilbert in Canada had

          22    written that packages so and so -- it's

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           1    definitely becoming more widely adopted.

           2              MR. LU:  Okay.

           3              MR. FEDER:  But I think if -- I

           4    cannot speak for the committee but for

           5    myself, I endorse this approach, I think it's

           6    great, adjusting that -- you need to keep

           7    working and making sure that those spikes

           8    will be smaller.

           9              MR. LU:  Okay.  But you don't think

          10    I need to convert it to the weekly time

          11    series to work on (inaudible) on the monthly.

          12              MR. FEDER:  I can give you example

          13    from what we did when we needed to use the

          14    demographic series of number of people.

          15    Because the other -- the census numbers and

          16    the labor force numbers were directly the

          17    number of households, so that we did not

          18    conversion, but how do you use the number of

          19    people?  We just wrote an observation

          20    equation, which says the total number of

          21    people is the sum of the following, number of

          22    households of size one plus two times the

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           1    number of households of size two plus three

           2    times the number of households of size

           3    three" -- and so on.

           4              MR. LU:  Uh-huh.

           5              MR. FEDER:  Unfortunately, we

           6    didn't have the number of households of size

           7    10 or whatever so we made some kind of

           8    assumption about households of size four and

           9    bigger.  But essentially we wrote, in the

          10    observation equation, we wrote the fact what

          11    we knew.  And the same thing here.  You have

          12    a monthly series, you say that the monthly

          13    number is equal to the following --

          14              MR. LU:  Components.

          15              MR. FEDER:  Components.  And you

          16    just sum it up.  Again, I'm not sure exactly

          17    how the input into SAS is, so I -- but I know

          18    in theory that's what you have to do.

          19              MR. LU:  Uh-huh, yes, uh-huh.

          20    Okay, yeah.

          21              MR. FEDER:  Yeah.  But conversion

          22    might also work.  I'm not saying it's a

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           1    better provision (inaudible).  All I'm saying

           2    is use as much data as you have, plot the

           3    series starting from 1993 to today, look at

           4    all the differences.  If you see a different

           5    stock -- I'm not sure --

           6              MR. CONNER:  Mike.

           7              MR. FEDER:  Talk to Mike and say,

           8    hey Mike, look at this, why do I have a big

           9    difference in 1994?  And he'll say, oh,

          10    that's because in that year Venezuela decided

          11    to shut down something.  And they said, okay,

          12    I'll edit as a fixed effects in my model, or

          13    whatever and you proceed until you have a

          14    good faith.

          15              MR. LU:  Okay.

          16              MR. FEDER:  So, I'd say good

          17    approach and just --

          18              MR. HILL:  Do you think household

          19    data are much more stable for both?  I don't

          20    know if it's -- probably it's there might be

          21    spikes in here that you wouldn't have in

          22    households.  The price of housing doesn't

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           1    jump suddenly in Toronto overnight.

           2              MR. FEDER:  Exactly.

           3              MR. HILL:  Whereas the oil price

           4    can jump.

           5              MR. FEDER:  Exactly, exactly.

           6              MR. HILL:  And maybe or maybe that

           7    may remain, that may remain.  These are

           8    stockpiles, so I assume it's less sensitive

           9    to short term pricing changes.  But there may

          10    be affects like that in this data series that

          11    you wouldn't find in housing.

          12              MR. FEDER:  Yeah.

          13              MR. LU:  STEO is another office in

          14    EIA, published the prediction numbers

          15    monthly.  And their number is the pink one

          16    here, you can see that, which may not

          17    consider the time series effect, although

          18    regress in the moving everyday pieces.  It's

          19    purely just the --

          20              MR. FEDER:  You just said something

          21    on what --

          22              MR. HILL:  That's the beginning of

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           1    the Gulf War, this Iraq war number two, March

           2    '03.

           3              MR. LU:  No, that's in '02.

           4    January, 2002.  Or was it --

           5              MR. HILL:  I think that's the war,

           6    yes.

           7              MR. FEDER:  Maybe that is to -- I

           8    just want to say but the spikes in the

           9    housing in fact there is something that

          10    happens every year when students go to

          11    college day that the household composition

          12    changes.  So there are some things that --

          13              MR. LU:  Okay.

          14              MR. FEDER:  But, we didn't have a

          15    big effect so we -- and the models somehow

          16    adjusted for it.  But --

          17              MR. HILL:  Seasonality.

          18              MR. FEDER:  You may be right, I

          19    mean, could be some things that happened that

          20    Mike might be able to come up with some

          21    auxiliary data that you can include in your

          22    model.  I mean it's nice that in your model

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           1    you had some fixed effects as well, so you

           2    might be able to find the right variables to

           3    put in the model to explain the discrepancy.

           4              MR. LU:  Okay.

           5              MR. HILL:  That is the start of the

           6    war.  The Iraqi phase of the --

           7              MR. LU:  January --

           8              MR. HILL:  March, it happened

           9    during the spring, I -- we were at spring

          10    vacation, academic spring vacation.

          11              MR. LU:  Spring, 2003?

          12              MR. HILL:  Yes.

          13              MR. LU:  Oh, yeah.  Before that,

          14    it's a -- it started with January, 2003,

          15    right?  That's the --

          16              MR. CONNER:  I think the actual

          17    invasion was when the U.S. actually invaded

          18    Iraq was in March.

          19              MR. LU:  March, yeah.

          20              MR. HILL:  Yes.

          21              MR. CONNER:  I think it was March.

          22    I mean there's probably, you know --

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           1              MR. HILL:  It had some effect on

           2    the oil market and stockpiles, yes, around

           3    the time of the invasion.

           4              MR. LU:  Yeah, I needed to

           5    (inaudible) to that to the PCM and the weekly

           6    number to see how close they are.  That's the

           7    start of they didn't catch up with -- we call

           8    it sudden impact or some intervention

           9    factors.

          10              MR. FEDER:  Can I just ask you

          11    since I'm the -- discussed it, I just want to

          12    make sure I will not say things that are

          13    wrong; the source of the monthly basis series

          14    is stocks in other oils, which has a

          15    two-month lag, right?

          16              MR. LU:  Yes.

          17              MR. FEDER:  Against that it was

          18    publication delays.

          19              MR. LU:  Yes.

          20              MR. FEDER:  And the other sources

          21    of total petroleum stocks and petroleum

          22    products supply both are --

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           1              MR. LU:  Weekly.

           2              MR. FEDER:  Weekly, instantaneously

           3    almost.

           4              MR. LU:  Yes.

           5              MR. FEDER:  But they're more

           6    volatile?

           7              MR. LU:  It depends.  You know,

           8    yeah, it's dependant on the markets.

           9    Sometimes it's, yes, up and down.

          10              MR. FEDER:  Yeah, yeah, okay.

          11              MR. LU:  Yeah.  In this weekly you

          12    can see all those major six components.  So

          13    every week, which was the survey result from

          14    the refinery.  So it's only supply.  Okay?

          15    But in the other components of other oil,

          16    okay, like asphalt and all those other

          17    things.  These are only monthly based.  We

          18    don't have a weekly number, right, Mike?

          19    These are all monthly numbers.

          20              MR. CONNER:  That is true, yes.

          21              MR. LU:  Yeah.  But the -- our

          22    customer needs weekly number of this.

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           1    Especially the weekly stocks of the, you

           2    know -- and right now, you -- if you look at

           3    the monthly publication you may find these

           4    numbers, right?  I just checked, in some of

           5    them you can see, but in the others, not --

           6              MR. FEDER:  Well, you used the

           7    structured models of Harvey to write down

           8    what you think.  But of course, next to this

           9    there's also the observation equation, which

          10    is also always part of the modeling.  And the

          11    observation equation can be written to

          12    reflect all the data that you have, and it

          13    almost work like magic.  You write down

          14    everything, you crank the model, and you get

          15    estimates of the state, which usually behave

          16    quite well.

          17              So, if you have just monthly data,

          18    if you put it correctly in your model, and

          19    you run the model, assuming that the model

          20    performs well, you will get weekly estimates

          21    from the model that should be quite good.

          22    This is what I suspect.  So even if those

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           1    data are available only monthly, since you

           2    have -- also have other weekly data, I think

           3    you can actually write a model to use all the

           4    data and get the estimates that you want.

           5              MR. LU:  Yeah, but they are two

           6    different approach.  One is just using the

           7    monthly -- predict the month's number, then

           8    convert it back to the weekly.

           9              MR. FEDER:  Yeah.

          10              MR. LU:  The other one is convert

          11    everything to the weekly then go ahead

          12    forecast the weekly.

          13              MR. FEDER:  Well, it depends how

          14    correctly the conversion to weekly is.  I

          15    prefer that the model does it.  I mean,

          16    rather than break it down to weekly, it's

          17    like in the explanation, like what I gave

          18    about using the population total to use to

          19    estimate the number of households.  Because

          20    we know that there's this linear relationship

          21    between the population total and the number

          22    of households, I was able to write the

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           1    observation equation and let the model do the

           2    estimate.

           3              MR. LU:  Okay.

           4              MR. FEDER:  Same thing here.  Even

           5    though this is given only as a monthly

           6    aggregate, you know that this is the sum of

           7    the weekly numbers, you can just write it in

           8    the equation and run the model and get the

           9    estimates from the model rather than

          10    disaggregate it like you said.

          11              MR. LU:  Okay.

          12              MR. FEDER:  Because this -- the

          13    model should do it for you.  I mean, the YTD

          14    observation that you have in your model?

          15              MR. LU:  Uh-huh.

          16              MR. FEDER:  Can be written as the

          17    weekly -- I'm sorry, the monthly can be

          18    written as the weekly.

          19              MR. LU:  Yes, uh-huh.

          20              MR. FEDER:  Yeah.

          21              MR. LU:  Okay.

          22              MR. FEDER:  I mean, it requires

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           1    some thought but -- that's what we normally

           2    do in this --

           3              MR. LU:  Okay.

           4              MR. HILL:  All right, I think

           5    we're close to 11:00, if there's -- okay, in

           6    this -- let me end this session, thank you

           7    very much.

           8              MR. LU:  Thank you.

           9              MR. HILL:  And we reconvene here at

          10    11:15.

          11                   (Recess)

          12              MR. HENGARTNER:  All right, let's

          13    get going, please.  We are in our last leg

          14    for this meeting, so what I'd like to do is

          15    have short reports or summaries from the two

          16    break-out sessions.  If Moshe is ready he'll

          17    be first, otherwise I'll go.  Moshe is ready,

          18    so excellent.

          19              MR. FEDER:  I want you to make the

          20    last presentation of last chairmanship, so

          21    I'm going to go first.  Actually, we had a

          22    very interesting discussion here.  Let me

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           1    first describe the issue.  There's a demand

           2    for weekly figures of stocks of other oils.

           3    And the data sources for the stocks in other

           4    oils is a monthly basis data source and

           5    there's also a time lag of about two months

           6    until it's available and three months until

           7    it's actually published.

           8              In addition, there's weekly stocks

           9    in other oils available from total petroleum

          10    stocks and for petroleum product supplied

          11    publications.  So there was a modeling

          12    attempt here to produce weekly estimates of

          13    stocks of other oils that Ruey-Pyng Lu was

          14    talking about.

          15              And of all the methods that he

          16    described, the one that looks very promising

          17    is a what they call unobserved component

          18    model based on these structured models that

          19    have been developed and have been in use now

          20    in many places.  In particular, I would

          21    mention the Bureau of Labor Statistics

          22    estimates a lot of employment figures which

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           1    are now based on that.

           2              Without going into specifics of the

           3    model and what goes into it, roughly, the

           4    assumption is that the observed data is a

           5    linear function of a trend, seasonality and

           6    auto regressive component, some fixed effects

           7    and the random noise, and the team that's

           8    been working on it used a relatively newly

           9    created SAS procedure.  Can someone please

          10    mention the name, I forget, what's the name

          11    of the SAS procedure?

          12              MR. LU:  UCM.

          13              MR. FEDER:  UCM, I guess that's an

          14    acronym for Unobserved Component Model.

          15              MR. LU:  Yes.

          16              MR. FEDER:  To evaluate the method.

          17    And what they did they used data beginning

          18    from January 1993 up to 2002, and used a

          19    fitted model to predict the figures beginning

          20    from 2002 to 2004 and looked at the

          21    prediction error and compared it to other

          22    methods.  And I hope I can speak for the

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           1    entire break-out session group.  We felt that

           2    the method looked promising.  Some things

           3    that we suggested to the speaker to improve

           4    the model, but I think maybe it's the best

           5    way to proceed.

           6              There's a few things that could be

           7    done to improve the model including looking

           8    at the series beginning from 2003 plotting

           9    the series and examination of the one step

          10    ahead prediction errors to see when there's a

          11    large discrepancy, try to see if there are

          12    some effects that could be used to explain

          13    those differences.  We also talked about

          14    perhaps using different seasonality model.

          15              Currently, the seasonality model

          16    assumes weekly effects which amount to 53

          17    parameters which might be an overkill, so we

          18    suggested maybe to try a seasonality based on

          19    a monthly rather than weekly effects.  In

          20    addition, the monthly breakup currently

          21    broken down into weekly data, there's another

          22    way to do it, by just writing the model

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           1    differently without doing this, and I think

           2    this is it.

           3              One thought actually that I had

           4    that I didn't mention is maybe also try

           5    logarithmic scale just because you have data

           6    of a time that may have (inaudible), so maybe

           7    it's also worthwhile to try logarithmic

           8    scale, although I don't know if it will make

           9    big difference.  I think this is it.

          10              MR. HENGARTNER:  Thank you very

          11    much, Moshe.  Okay, I have the pleasure of

          12    attempting to fill in the big shoes that is

          13    Mark Burton's, and summarizing our last

          14    discussion downstairs as -- I kind of agree

          15    with Moshe, no -- we had a very lively

          16    discussion downstairs.  As far as I

          17    understand, we barely got to slide two or

          18    three, and then all hell broke loose, and

          19    that was a good thing, it was a very good

          20    thing.

          21              And the issue was about

          22    forecasting, especially for NEMS model and

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           1    just to give you a context and it took me a

           2    while to understand.  Those NEMS models are

           3    extremely large.  What I mean by large is

           4    they are complicated, have many bells and

           5    whistles, and lo and behold making one run,

           6    one prediction, can take up to eight hours.

           7              And so it's not a matter of

           8    fact -- matter of just making the few runs,

           9    it's easy to make predictions.  It actually

          10    is a time consuming process it turns out that

          11    the models as well as the forecasts in the

          12    past -- I'm going to say 10 years, but maybe

          13    its 15 years have been saved, and there is a

          14    notion that if we could look in our rearview

          15    mirrors we can actually learn something from

          16    what we've thought about the model and about

          17    reality, and it maybe how that mismatch can

          18    teach us what's going on.

          19              And it goes a little bit in what

          20    Tom Rutherford was telling us yesterday,

          21    trying to figure out what the answer is, what

          22    the model is and then try to learn something,

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           1    and in a way that's exactly what we're doing,

           2    by doing this backcasting.  And the thought

           3    is, at least my thought was that this is

           4    extremely important in light of the need of

           5    more analysis at the EIA.

           6              It's very important in this

           7    interplay between data collection analysis to

           8    be able to improve the product, and exactly

           9    it's by being able to look back and

          10    understanding what comes in the future is

          11    that -- that's where the sweet spot is for

          12    that kind of work.

          13              So clearly there is a need for this

          14    and, I think everybody was in roaring

          15    agreement about that.  There were some

          16    notions of how to do this, there was a notion

          17    of a NEMS light model introduced to say, you

          18    know what, we actually can get simplifying

          19    models, we can get statistical models that

          20    quite accurately predict the results of the

          21    NEMS simulations.

          22              And if we actually are able to use

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           1    these models to explore in a fast and dirty

           2    way, and I don't want to use dirty in a bad

           3    way, but at least in a fast way to be able to

           4    understand what's going on then that has a

           5    lot of value for us to understand how things

           6    work.

           7              The other advantage of having this

           8    retrospective look is to actually to bring

           9    together analysts and the modelers in a room

          10    and say, okay, what did we do, what did we do

          11    well, what we did wrong, and somehow be able

          12    to keep the model alive by asking yourself,

          13    did we do a good job?  I mean it's easy to

          14    say, well, these are the last year's numbers,

          15    I kind of forget, but there is value of going

          16    back and thinking and having some

          17    retrospective view of things.

          18              And there are lots of notions and

          19    modeling issues that arose.  I'm just going

          20    to mention two of them.  One had to do with

          21    identifying missed factors or the sensitivity

          22    of specific factors on the predictions.  And

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           1    again, that seems like an obvious thing to

           2    some of us, until we understand that making

           3    one run takes eight hours and we don't have

           4    the luxury of doing those very simple or

           5    things that we statisticians think, oh, that

           6    easy let's get the leverages.

           7              So no, that doesn't work; we have

           8    to be clever, we have to be understanding

           9    about what the challenges are.  And one is

          10    the computational complexity of the models

          11    considered.  The other thing is in terms of

          12    factors in the models, there's a lot of

          13    factors that are included for policy reasons

          14    not for modeling reasons, and being able to

          15    balance these things is of interest.

          16              And there's also a notion that by

          17    going back, we can learn or we have the

          18    opportunity to learn from what we have done

          19    so far, so this was a early stage

          20    presentation, and the committee felt by all

          21    means it should continue, at least I'm

          22    putting words in their mouth, and I hope you

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           1    will corroborate with me on this.

           2              But that was a very worthwhile

           3    endeavor, and by all means should go forward

           4    even if it meant maybe battling some

           5    resistance, and there was discussion of that

           6    too, from -- for political reasons, let's

           7    leave it that way.  This is a summary, and I

           8    invite anybody in my session to please

           9    correct or expand my summary.

          10              MR. FEDER:  I was not in your

          11    break-out session.

          12                   (Laughter)

          13              MR. FEDER:  I do have a comment.

          14    Last week, I attended a meeting at Virginia

          15    Tech where modeling was discussed.  In fact,

          16    there was a brief mention also of EIA, the

          17    speaker was, and I hope I'm saying his name

          18    right, but let me see I can e-mail it to you,

          19    I think it was John Sterman, sorry -- he's

          20    from MIT, and he talked about model

          21    verification, model validation, an extreme

          22    value test that you can apply to models.

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           1              By that, for instance in our case,

           2    if you pushed the value of a barrel of oil to

           3    zero or to 200 you look at the results, and

           4    see if it makes sense or not and that allows

           5    you to check.  So I was thinking perhaps, if

           6    we could in the future, a point in time,

           7    perhaps Nick you won't be in attendance, have

           8    a session devoted to modeling, and maybe we

           9    can have this guy or someone else.

          10              Actually, I have the paper he

          11    wrote, that I can also send to you, and that

          12    was interesting because the discussion was

          13    not just on specific models, but how do you

          14    assess models in terms of verification and

          15    validation.  The difference between the

          16    two -- perhaps I won't go into that, but

          17    those are important issues, I think model

          18    validation is easier than verification, but

          19    both should be done.  So that's all I wanted

          20    to say, even though I wasn't in your

          21    break-out session.

          22              MS. KIRKENDALL:  I'd be real

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           1    interested in the paper, that'll be great.

           2              MR. FEDER:  Yeah, I'll send it, I

           3    have only hardcopy, but I'll send it to you.

           4              MS. KIRKENDALL:  Yeah, you could

           5    fax or whatever.

           6              MR. FEDER:  Yeah, actually I

           7    also -- if I may just take one more

           8    second -- actually, I forgot to mention that

           9    Ruey-Pyng and I talked about this, he

          10    mentioned the fact that the models he was

          11    talking about Emerging Britain by Harvey, and

          12    actually Nancy, you spoke about this

          13    gentleman, I think his name was Smith that

          14    you once presented JSM.

          15              MS. KIRKENDALL:  Black Smith (?).

          16              MR. FEDER:  Yeah, that worked on it

          17    here, I mentioned to him that actually the

          18    BLS is now basing all its modeling, and I

          19    mentioned the names of Richard Tiller, Stuart

          20    Scott, Bill Bell who all worked on this kind

          21    of models, so those are -- and I'm going to

          22    send him some more information.  And Carol

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           1    who was here before, she actually is familiar

           2    with some of those publications and knows

           3    about some JSM papers that have been written

           4    on that, so it's much more value adopted now,

           5    and there is many people in town who know

           6    about it a lot that could also be --

           7              MS. KIRKENDALL:  That was their own

           8    software though, they aren't using the SAS

           9    module.

          10              MR. FEDER:  No, and in fact -- I'm

          11    not sure what capabilities the SAS module has

          12    in terms of writing the equations that are

          13    needed.  Another name that I mentioned here,

          14    is Paul Gilbert from Bank of Canada.  He

          15    created a package called, I think

          16    DSN -- dynamic -- anyway he created a package

          17    that goes with R and S plus which is publicly

          18    available, I downloaded it, and also has this

          19    capability.

          20              It's been there for a while plus

          21    very nice documentation as well, so

          22    you -- Ruey-Pyng is going to look at it and

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           1    I'll send him some more including that paper

           2    that I sent you Nancy, that I wrote on this

           3    subject.  I wrote it, I think, in 2001, it

           4    was a review paper, I'll send e-mail.

           5              MS. KIRKENDALL:  Okay.

           6              MR. FEDER:  Actually, maybe I'll

           7    send it to him as well as the paper that he

           8    will give you.

           9              MS. KIRKENDALL:  That's fine.

          10              MR. FEDER:  Okay, all right, so

          11    I'll send it to you, the paper that this MIT

          12    gentleman wrote.

          13              MS. KIRKENDALL:  Yeah.

          14              MR. FEDER:  Okay.

          15              MS. KIRKENDALL:  Yeah, Ruey-Pyng

          16    can share it.

          17              MR. HENGARTNER:  Any more comments

          18    from Jae, Tom?

          19              SPEAKER:  No.

          20              MR. HENGARTNER:  Cutler?

          21              MS. KIRKENDALL:  Wherever you are.

          22                   (Laughter)

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           1              MR. HENGARTNER:  Okay, so at this

           2    time I'd like to invite additional comments,

           3    and from the committee discussions as well as

           4    from the public audience.  Before

           5    continuing -- public audience?  Good.  What

           6    else is on the agenda, the agenda -- we are

           7    coming to a close.  There's time for comments

           8    and suggestions from the committee.  There's

           9    also probably time to determine the date for

          10    the next meeting.

          11              MR. WEINIG:  I'm not prepared to do

          12    that.

          13              MR. HENGARTNER:  Not prepared to do

          14    that, that's fine, putting Bill on the spot,

          15    that's okay.

          16              MS. KIRKENDALL:  Expect e-mails.

          17              MR. HENGARTNER:  The last thing I

          18    want to do as the outgoing chair, I'd like to

          19    actually take this -- just want to thank the

          20    EIA for what they have done.  I mean, what I

          21    found valuable here is that they've been able

          22    and willing to stick out their neck and

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           1    present things early.  And that is a big risk

           2    because they are unfinished products, they

           3    are products that they are in process of

           4    doing.  These are also the products that

           5    have -- we have the most impact with our

           6    comments.  But it takes really courage to go

           7    and present things that you are not fully

           8    confident about yet.  And I want to thank

           9    Nancy for being able to push this forward

          10    because it's not an easy thing to do.  And I

          11    want to thank the staff of EIA for putting up

          12    with those requests, because again, it's a

          13    tough thing.

          14              Now it takes two to tango, and I

          15    recognize the committee has been very good in

          16    their positive support of this endeavor,

          17    right.  If we'd be overly critical, it

          18    wouldn't have worked either.  So it's very

          19    important for us to give positive feedback

          20    and good feedback, right, but there's a way

          21    of couching it, and I think this committee

          22    has been extremely successful in doing so.

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           1              And it's this partnership that I

           2    think has led to what I would qualify very

           3    good meetings, and I'm just encouraging you

           4    to keep on this tone.  I see a bright future

           5    for this committee in the future, because I

           6    know the people coming on board are

           7    excellent, so I'm actually going home.

           8              I also want to thank the ASA even

           9    if they are not here for the logistical

          10    support.  They've been very good at putting

          11    up with our travel and hotels and whatever

          12    and they should be commended for this.  So,

          13    thank you very much for a very productive six

          14    years.  I've been happy to be a member here,

          15    and now it's time for me to go.  Thank you.

          16              MR. HENGARTNER:  Okay, so, if there

          17    is no other business we want to talk on the

          18    record, let me suggest that we are adjourned

          19    until next time.

          20                   (Whereupon, at 11:40 a.m., the

          21                   MEETING was adjourned.)

          22                       *  *  *  *  *

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