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DEPARTMENT OF ENERGY 

11o~ss ************************** 

In the Matter of: * 

* 

U.S. DEPT OF ENERGY * 

WORKSHOP ON STANDARDS * 

FOR CLOTHES WASHERS * 

************************** 

Tuesday, 

December 15, 1998 

ORIGINAL U.S. Dept of Energy 

1000 Independence Ave. SW 

Room lE-245 

Washington, DC 20585 

The above-entitled matter came on for 

hearing, pursuant to notice at 9:15 a.m. 

ATTENDEES: 

Bryan Berringer 

Eugene Margolis 

Mike Rivest 

Qonnie Laughlin 

Larry Hawkins 

Steve Nadel 

Dave Goldstein 

Steve Rosenstock 

Wayne Morris 

Earl Jones 

Michael Marsollek 

Glenn Schwantes 

Michael Martin 

Stephen Mariano 

Charlie Stevens 

Al Dietemann 

Chad Neal 

Alan Kessler 

Dick Best 

Dick Stilwell 

Peter Biermayer 

Jim McMahon 

Victoria Nader 

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(Continued) 

Lou Montvoro 

Terry Thiele 

Glen Scheede 

Tommy Holmes 

Thomas Bee 

Stephen Grover 

Tony Gregg 

Dan Barzel 

Ted Pope 

Tom Eckman 

Jack Linard 

Mike Thompson 

Dan Reicher 

Mike McCabe 

Roland Weingartner 

Brian Neal 

Tom Neal 

Dave Modtland 

Anthony Balducci 

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AGENDA 

PRESENTATION: 

Introduction: 

Bryan Berringer 

Agenda Review 

Victoria Nader 

Stephen Mariano 

Jim McMahon 

Peter Biermayer 

Jim McMahon 

Stephen Grover 

Mike Rivest 

Jim McMahon 

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1 M 0 R N I N G S E S S I 0 N 

2 (9:15 A.M.) 

3 MR. BERRINGER: I am Bryan Berringer. 

4 Thanks for everybody coming in close to, this 

5 close to the holidays. This is an important step in 

6 the rulemaking. 

7 I am the team leader for the Clothes Washer 

8 Workshop in the rulemaking. The following people are 

9 also on our team as you were introduced, was Qonnie 

10 Laughlin and Gene Margolis from of the Office of 

11 General Counsel and Mark Friedrichs, who is not here 

12 from the Office of Policy and International Affairs. 

13 On behalf of the Department of Energy I would 

14 like to thank you all for being here today. This being 

15 the fourth public workshop that we have done under the 

16 new process since the process rule of July 15, 1996. 

17 It is has to believe it has been two years, two and a 

18 half years since we have started that process and this 

19 being two years, working on the clothes washer rule. 

20 Copies of the draft reports, the slides 

21 today, if anybody needs, we have the programs that are 

22 on the web site, if you haven't gotten those. See Sandy 

23 at the table. Anything else, we have copies of the TSD 

24 and the actual Federal Register, the publication is 

25 sitting up here on the table also. If you feel 

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1 inclined to have that material. 

2 Anybody attending today will be put on the 

3 mailing list. One of the things we would like to is 

4 probably narrow down our mailing list to people that 

5 are participating. So, we may, you may see a shorter 

6 mailing list. So, if you want to maintain, everybody 

7 that is here and.that was at the last workshop, will 

8 maintain on the mailing list. And we will start new 

9 one, sort of cut it down because we have got a rather 

10 large list. So, if you know anybody that is not here 

11 that would like to remain on our mailing list, either 

12 have them contact with or Brenda Edwards-Jones, as 

~3 identified in the Federal Register . 

14 Comments received here today and those 

15 already submitted during the written comment period 

16 will assist us in developing the notice of proposed 

17 rule, which is planned in November of 1999 publication. 

18 The following procedural items, you have 

19 heard them before, but we will go through them once 

20 more. I will be presiding officer over the workshop. 

21 Victoria Nader is our facilitator for the workshop, 

22 will be setting the guidelines for conducting the 

23 workshop and for providing information as we go along, 

24 parking lots and so forth. _And you may remember 

25 Victoria, she was involved in our first process 

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1 improvement workshop. She was handling one of the 

2 breakout sessions . 

3 In approximately two weeks the transcript 

4 should be available, in the Freedom of Information 

5 room, which is down the hall in lE-190. You can also 

6 make arrangements with the court reporter if you would 

7 like to purchase a copy from them. 

8 To provide the Department with as much 

9 pertinent information that can be viewed and reasonably 

10 obtained and that everybody gets their views, the 

11 workshop will be in accordance with these following 

12 procedures: 

13 Obviously, the focus of this workshop is to 

14 listen to your comments on the supplemental proposed 

15 rulemaking. Receive data information to help the 

16 Department in their analysis, the preliminary analysis 

17 and also receive comments on information pertaining to 

18 the Notice of Proposed Rulemaking, the next steps. We 

19 are going to go over the methodologies and so forth 

20 this afternoon, which is on the agenda. 

21 We will take a lunch break about noon, as 

22 appropriate. There is a snack bar downstairs. There 

23 is the cafeteria down in the West wing of the building. 

24 There is also some restaurants up at L'Enfant Plaza . 

25 Lunch is your own, so we will try, we let Victoria as 

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1 the, as we do our presentations and get. through the 

2 day, we will decide, we will choose a point for, a good 

3 point for lunch. 

4 We would like to reduce interruptions if 

5 everybody would wait to speak, to be recognized by 

6 Victoria. Please remember, this is important for the 

7 court reporter, to speak into the microphone, give your 

8 name and your company for each time that you speak. 

9 Please keep side conversations to a minimum. If you 

10 can, if possible, you can go outside if it becomes a 

11 lengthy discussion. 

12 It may be necessary to cut off topics to 

13 maintain schedule. We have a very full agenda today . 

14 And we have a number of topics that people want to 

15 discuss. So, when we get into that we want, we have 

16 set a list up here, some of the topics that we 

17 received. What we would like to do is see when we get 

18 into that, to prioritize that or if everybody feels 

19 that all the agenda items or the topics are necessary, 

20 we can add that when we go to the agenda review. 

21 This workshop is scheduled to end at 4:00 

22 p.m. today or soon if we get through everything. 

23 Topics that have not been fully discussed can 

24 be addressed in additional comments. The comment 

25 period for this workshop and the notice is February 2 

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1 of 1999. So that will coincide with the supplemental 

2 rulemaking comments. All comments and data submitted 

3 to the Department will be used for the publication of 

4 the Notice of Proposed Rulemaking. 

5 Written comments and data submitted will be 

6 available for the public inspection at the reading 

7 room. If anybody needs the phone number it is (202) 

8 586-6020, and again, it is down the hall in lE-190. 

9 Written comments should be addressed to the Department 

10 of Energy in the Federal Register notice that are 

11 addressed in the notice, supplemental advance Notice of 

12 the Proposed Rulemaking. 

13 We request that 10 copies be submitted of 

14 comments or data. The Department would like if 

15 possible, electronic copies in WordPerfect 6.1. Please 

16 no fax copies. There is something new that we are 

17 accepting, is we will accept electronic copies of 

18 E-mails. We ask that you follow up with a signed hard 

19 copy, so that we have a permanent record and we know 

20 that is your official comment. And that should be 

21 addressed also, there is an E-mail address. You can 

22 address that to myself, send it to the Department and 

23 the addresses are given in the Notice of Proposed, of 

24 the supplemental advance Notice of Proposed Rulemaking . 

Any person submitting information they feel 

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1 is confidential, and exempt by law from public 

2 disclosure, should submit one copy with the information 

3 in it, and 10 copies in which the information claimed 

4 confidential is deleted. In accordance with the 

5 procedures in 10 CFR 1004.11, the Department shall make 

6 its own determination whether the information shall be 

7 exempt from public disclosure. Okay. 

8 And keeping with the regulations of this 

9 building, there is no smoking allowed in the building, 

10 in the restrooms or down the hall, either end of the 

11 hall to the right or left. There are public phones in 

12 the main lobby area. 

13 And again, we appreciate everybody taking the 

14 time and effort in preparing for this meeting and for 

15 this workshop. And we will be glad, glad to receive 

16 comments and opinions. And we have done, we have 

17 already done introductions. And if we would just go 

18 right into agenda review. Victoria? 

19 MS. NADER: Thank you, Bryan. 

20 First let me say thank you to all of you for 

21 being here. I reviewed the record of your last 

22 meeting, and I can see that you have come a tremendous 

23 distance from the place we all started over two and a 

24 half years ago. I am impressed by the technical 

25 expertise you have brought. And I am impressed by your 

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1 ability to work together as a team. And I am aware 

2 that we have a tremendous amount of work to do today, 

3 but I see that you are well organized and you know the 

4 routine. And I will look to you to manage yourselves 

5 to a certain extent. 

6 Just to reenforce the ground rules. Because 

7 we have to have a record of this proceeding, please 

8 speak only one person at a time. We need to have the 

9 recorder be able to hear you. And Recorder, please 

10 signal if there is someone you can't hear, please let 

11 us know. 

12 If you need to have a side conversation with 

13 someone, please go out in the hall to do that . It is 

14 the only way we can continue to hear one another 

15 inside. Please respect yourselves as colleagues. 

16 State your name and your organization each time you 

17 speak. This is very important. Be concise. There is 

18 a tremendous level of detail involved in some of the 

19 work we are doing. We have to use words sparingly and 

20 effectively in order for us to accomplish what we need 

21 to accomplish today. 

22 And again, speak to be heard. Make sure that 

23 you are projecting your voice so that the recorder and 

24 everyone in the room can hear you . 

25 The agenda for today is lengthy. Does 

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1 everyone have a copy of the agenda? We will spend from 

2 9:30 to 11:30 going over the items that you have said 

3 you want to provide information on and the areas that 

4 you have indicated you have questions on. And in just 

5 moment or two, I will go through the list and get an 

6 indication of how many people are interested in which 

7 topics, so that we can be as efficient as possible. 

8 We will work until 11:30 on those questions 

9 and answers. At 11:30 we will review the results of 

10 the Reverse Engineering, Phase II. Approximately 12 

11 and we will look for a convenient breaking point, but 

12 approximately 12 to 1 will be lunch time. As Bryan 

13 said, you are on your own for lunch . 

14 Then beginning at one, we will have a series 

15 of presentations, covering Marginal Energy and Water 

16 Rates, National Energy Savings, approaches to determine 

17 shipment and elasticity. Consumer Survey, update. We 

18 will have a break roughly in the middle of our 

19 afternoon time. And following the break, we will cover 

20 Manufacturer Impact Analysis, Indirect Employment, 

21 Environmental Assessment, Utility Impact Analysis. And 

22 then at four to four-thirty, we will have a summary 

23 discussion and try to cover anything that we have not 

24 touched on earlier in the process . 

25 Okay. Is everyone clear on what we are 

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1 doing? 

2 MR. BERRINGER: Is there anything that we have 

3 eliminated from the agenda that you feel needs to be 

4 addressed? Earl, you have a question? 

5 MR. JONES: -- not elimination, I want to 

6 check them again. 

7 MR. BERRINGER: Please speak in the 

8 microphone, and identify yourself, please. 

9 MR. JONES: Yes, Earl Jones with G.E. 

10 There was, I thought a provision made for 

11 call ins on the consumer survey piece of the consumer 

12 discussion, is that still true and how is that working 

13 on this agenda? 

14 MR. BERRINGER: That is correct. I didn't put 

15 that on the agenda since that was a working group 

16 meeting. That is at 4:30 this afternoon and I do have 

17 the call in number for the working group. 

18 MR. JONES: I thought it was initially set at, 

19 wasn't it set at two or not? No? 

20 MR. BERRINGER: No, 4:30 this afternoon, which 

21 is going to be in the room right across the hall, which 

22 is lE-250. So, as soon as we break up here, if we 

23 break up earlier, we can do that. I can give, if 

24 during the day you need to call somebody, the call in 

25 number is (202) 287-1380. So, we will make that 

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1 available later this afternoon. But, that is starting 

2 at 4:30, following this meeting. 

3 MS. NADER: Anyone else have a question? 

4 Okay. Qonnie has posted on the easel charts 

5 the primary topics that people have said they want to 

6 talk about today. What I would like for you to do, 

7 please, is raise your hand if you are interested in 

8 these particular topics. I want to get a sense of 

9 whether we will be talking about items of general 

10 interest to the whole group of people. And that will 

11 make a determination also as to whether there might be 

12 some issues that could be handled one on one or 

13 otherwise in a smaller setting . 

14 Okay. How many people are here to talk 

15 about product class? 

16 MR. BERRINGER: We were talking about, the 

17 issue here that we were looking at and we can elaborate 

18 that on, is the compact class. There was a comment 

19 from Whirlpool about increasing that product class. 

20 So, that was the main topic that we heard as far as 

21 product class. 

22 Earl, did you have something else to add to 

23 that? 

24 MR. JONES: Oh, you are so generous, Bryan . 

25 MS. NADER: I didn't hear that, Earl. What 

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1 did you say? 

2 MR. JONES: I am complimenting Bryan on his 

3 generosity. Well, of course, a more basic question 

4 then that is in product classes that have been 

5 historically recognized whether they will continue as 

6 they relate to port of access. 

7 MS. NADER: Okay. Yes, sir? 

8 MR. MARTIN: I am Michael Martin, California 

9 Energy Commission. I am a little confused by your 

10 question. You asked whether we want to talk about it 

11 or whether we are interested in it. There are a lot of 

12 things I am very interested in, but I don't wish to 

13 make a statement, but should I raise my hand? 

14 MS. NADER: Thank you for that 

15 MR. MARTIN: I certainly wouldn't want to miss 

16 a word that Earl told me. 

17 MS. NADER: The purpose of asking you to give 

18 me a signal of your, it is a signal of interest, not 

19 just something you want to talk about. Thank you. The 

20 whole purpose here is just to make sure that we are 

21 spending our time on the things that people think are 

22 most important. Okay. 

23 Water and sewer rates? All right. That one 

24 is popular . 

25 Elasticities? Is there even one person in 

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1 the room who wants to talk about elasticities? Okay. 

2 MR. BERRINGER: These, the topics, too, that 

3 we have the asterisks, we will be presenting some this 

4 afternoon, especially water rates and we will be 

5 talking about elasticities, the next topic ·shipments is 

6 also on the agenda for this afternoon. 

7 MS. NADER: How many are interested in the 

8 topic of shipments? Thank you. 

9 Repair and warranty costs? Life cycle costs? 

10 Okay. Thank you. 

11 Life of the appliance in life cycle costs? 

12 Thank you. 

13 Energy, annual energy outlook ''99 forecast 

14 and analysis? Okay. 

15 What else do we need to talk about today? 

16 What are the items that are not yet on the list? 

17 Yes, sir? 

18 MR. SCHEEDE: Glen Scheede. I would just like 

19 to ask Bryan, you asked for comments by December 4th 

20 for items that did not appear to be on the agenda, to 

21 send the comments in to nominate things. And I duly 

22 sent you a number of them and I notice you don't even 

23 bother putting them on the list. Is there some 

24 criteria that you have for selecting things that you 

25 will or will not consider? 

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1 MR. BERRINGER: If you look at the agenda, we 

2 tried to address some of those in the other comments, 

3 about midway down, when we talked about the scenarios. 

4 So, we sort of put those, when we get into discussion, 

5 we put save detergent, additional information. We just 

6 put a handful of them on here. So, if you have 

7 something you strongly feel that is missing from this 

8 list. 

9 MR. SCHEEDE: I can give you another copy of 

10 my December 4th letter. One topic is the general issue 

11 of quality of data, because we have, we are now getting 

12 data from a number of sources, apparently the DOE and 

13 its contractors are using with no information to show 

14 the representativeness, validity or reliability of the 

15 data. We merely are presented results without that 

16 kind of discipline with it. I think that is a general 

17 topic. 

18 MS. NADER: Okay. Thank you. 

19 MR. SCHEEDE: A general topic that needs to be 

20 considered by DOE. 

21 I do have comments on the MAISY data, but 

22 apparently that will be on the agenda. 

23 MS. NADER: Say that last item, please, I 

24 couldn't hear you? 

25 MR. SCHEEDE: MAISY, M-A-I-S-Y. The new 

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1 source of commercial data that DOE proposes to use for 

2 all sorts of decisions . 

3 MS. NADER: Okay. Thank you. 

4 MR. SCHEEDE: That apparently is on the 

5 agenda. You do seem to have, I guess the marginal 

6 costs and taking out the fixed portion of bills is, 

7 will be discussed this afternoon and life of 

8 appliances. So, the main one is this quality of data, 

9 which seems to be missing. Thank you. 

10 MS. NADER: Thank you. 

11 How many people are interested the quality of 

12 data issue? Okay. Thank you, that was a good 

13 addition . 

14 Any other additions? Yes? 

15 MR. NADEL: I am not quite sure where they fit 

16 in, whether it is here or this afternoon, but three 

17 other things, I wasn't clear whether they are on the 

18 list. 

19 One is a question of retail mark-ups. 

20 MR. BERRINGER: Yeah, I think we have skipped 

21 this page right here. We do have alternative, this is 

22 sort of what is in the agenda, alternative scenarios. 

23 MR. NADEL: I just wanted raise, if you have 

24 got it covered, great . 

25 MS. NADER: Thank you. 

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1 MR. BERRINGER: I think these some of your 

2 savings from detergents, information. You had talked 

3 about the cost 40 to 45 percent. 

4 MR. NADEL: Right. 

5 MR. BERRINGER: And retail mark-ups. So, we 

6 did. 

7 MR. NADEL: Okay. 

8 MS. NADER: Thank you. 

9 MR. SCHEEDE: I am sorry, Glenn Scheede again. 

10 Another issue that I should have mentioned is access to 

11 data. This is a problem particularly with MAISY 

12 because apparently it is high cost, anywhere from 20 to 

13 50,000 dollars to get at it. And the question of how 

14 that information will be made available so it can be 

15 evaluated by people interested in participating in this 

16 process. 

17 MS. NADER: Good, thank you. Others? Yes, 

18 sir? 

19 MR. GREGG: Tony Gregg, City of Austin. Just 

20 one thing for the input for the model. I don't know if 

21 it is addressed anywhere, but the reduction in cost to 

22 utilities and electric, all types of utilities and not 

23 having to fund rebate programs after standards are 

24 implemented. I don't know if that is already taken 

25 care of or not. 

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1 MR. BERRINGER: No, I don't think that was 

2 something that we have . 

3 MS. NADER: You said reduction of what, I 

4 couldn't hear you clearly? 

5 MR. GREGG: Reduction in cost for rebate 

6 programs that are currently in effect, to try to 

7 promote efficient technology. 

8 MS. NADER: Thank you. 

9 Okay. Anything else? All right. Hearing no 

10 additional suggestions, let's begin the conversation on 

11 Product Class. 

12 May I ask those who have table tents, a 

13 favor, if would help me a great deal if you could turn 

14 your tents so that I can see your organizations. Thank 

15 you. That is useful. 

16 MR. BERRINGER: If I could, I just had one, 

17 the presentations are there. We probably, in order to 

18 save time, we probably didn't, but one of the things 

19 that was on the agenda was the, as far as the overview 

20 of the schedule. And I would just to like to go 

21 through that briefly before we start getting into the 

22 topics. I just want to put this slide, this is the 

23 fourth workshop that we have had as far as the 

24 analysis, so it has been over the approximately two 

25 years since we had our first kickoff workshop, in the 

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1 process. Just so everybody is on the same schedule 

2 here. We are, basically today we are having our 

3 workshop. Oh, I am sorry, sorry. 

4 MS. NADER: Excuse me, I am having equipment 

5 trouble here. 

6 (Pause.) 

7 MR. BERRINGER: Public workshop today to 

8 address the comments received on the ANOPR.· We 

9 receive, we are looking to receive comments February 

10 2nd of 1999, again, pertaining to this workshop and the 

11 comments to the Supplemental Advance Notice. 

12 We are looking at, if everything goes 

13 appropriately and Mike Rivest will talk about 

14 manufacturing impact later this afternoon, starting, 

15 start some preliminary work in February time frame. 

16 That will coincide with some of the consumer survey 

17 information that will be discussed also today. 

18 We are looking, in November of '99, 

19 publishing the Notice of Proposed Rulemaking and then 

20 holding a public hearing in December of '99 and publish 

21 the final rule, we are looking at September of 2000. 

22 And I have already introduced some of the, I 

23 am team leader, Qonnie Laughlin is also on the team, 

24 Gene Margolis, we also have. A. D. Little is a lead on 

25 engineering and manufacturing. Reverse engineering and 

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1 LB&L is lead on the LCC, and National Benefits 

2 Analysis, which we will be going over this afternoon. 

3 And we have ENRIL/Quantum, which is doing our consumer 

4 research for us. 

5 And as, to the slides we have already gone 

6 through, the slides we have, and address the comments 

7 pertaining to the Supplemental Notice. 

8 So, I think we have can go and get into 

9 discuss as far as the topics and I guess the first one 

10 we would start off would be product class. 

11 One of the, as addressed, one of the comments 

12 to the Advance Notice, the Supplemental Advance Notice 

13 of Proposed Rulemaking, Dan Oprah was the product class 

14 and changing the product class to two cubic feet for 

15 the compact. Is there, does anybody have any further 

16 discussion on the product class on the compact, 

17 pertaining to the compact? Yes? 

18 MR. NEAL: All right. My name is Chad Neal 

19 from Staber Industries. We have a concern about 

20 raising the upper limit of 2.0 cubic feet. We have a 

21 unique top load and tumbler action washer that is 1.93 

22 cubic feet. And --

23 MS. NADER: May I ask you to speak a little 

24 louder, please? 

25 MR. NEAL: Yes, we hold, excuse me, we hold 

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1 the same amount at least or more than a regular washer 

2 at our tub capacity because of its unique top load and 

3 tumbler action design. We are just concerned about it 

4 being raised to 2.0 and putting us into the compact 

5 class, when we are actually a standard washer. So, it 

6 is just the issue of that upper limit of the tub 

7 capacity. 

8 MR. BERRINGER: Does anybody else have 

9 comments pertaining to compact class as far as either 

10 opposed or for or against changing the product class? 

11 MR. WEINGARTNER: Roland Weingartner, Miele 

12 Appliances. I just think that this compact class is 

13 subjective at the very least. And right now if you 

14 change that up to two, you are going to knock out many 

15 of the European washers, because of the horizontal 

16 loading, they are generally smaller drums, although 

17 they can do more laundry because you can fill them to 

18 the top, which you cannot do in a vertical axis. So, I 

19 think, if you make, if you force it up to two, you are 

20 going to force us to market a machine that for years 

21 has been marketed as a standard, because of the load 

22 size. Now you are going to force it to compact class 

23 for different marketing. And also with the average 

24 load, the average wash load_ being between seven and 

25 eight pounds, generally, there is really no need to 

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1 change the compact class up to two. 

2 MR. BERRINGER: Alan? 

3 MR. KESSLER: Bryan, we are not opposed to the 

4 increase in size of the compact washers up· to two. 

5 However, we think that the Department ought to also 

6 look at maybe creating a super capacity or a larger 

7 capacity above the standard size, starting say at 2.9 

8 to 3.2 to create differentiation, because there is a 

9 lot of confusion in the marketplace presently on what 

10 size washers really are, when you get into the larger 

11 sizes. 

12 We want to also make sure that we maintain 

13 the differentiation between what we characterize as 

14 vertical axis and horizontal axis machines as opposed 

15 to top loading versus front loading. There is distinct 

16 technological differences between the machines 

17 regardless of where they are loaded. 

18 MR. BERRINGER: Okay. Thank you. 

19 MS. NADER: Yes? 

20 MR. STEVENS: Charlie Stevens, Oregon Energy 

21 Office. 

22 Could I get somebody here in the room to 

23 explain to everybody else, at least to me, what the 

24 rationale for the change is? 

25 MR. BERRINGER: We had basically a comment, it 

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1 was from Whirlpool, it is dealing with the capacity 

2 that it may eliminate a product class, if maybe, with a 

3 particular, or a particular group, it may be a niche 

4 produce or a small product by, with the test procedures 

5 not being able to, my understanding, to reach the 

6 minimum efficiency standards, when it is categorized at 

7 a low. And maybe Dick Best from Whirlpool may be able 

8 to elaborate on the issue. 

9 MR. BEST: Is this on? 

10 MR. BERRINGER: Yes. 

11 MR. BEST: Yes, just a comment on the 

12 rationale behind this. Traditionally the compact class 

13 in the last rulemakings was set at 1.6 cubic feet. And 

14 the definition was really based on what the industry 

15 was producing during that, during those periods of 

16 time. And there were multiple manufacturers of what 

17 was termed compact washers. But, since that time, the 

18 market has changed and not all producers remained in 

19 that niche market. And at the same time, Whirlpool 

20 became a supplier, even to some of the other industry 

21 members of these products, and it just was not 

22 economically feasible to continue with the style of 

23 compact. At that time it was replaced with one that is 

24 slightly larger, the two cubic feet model. And that, 

25 and we do supply that to other members in the industry 

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1 today as well. So, it is, we are mostly a sole source 

2 on it. There are still small number of the 1.6 cubic 

3 feet models built, but they are built into, again, 

4 unique products such as washer/dryer combination units. 

5 And this whole total market, if you threw all of them 

6 together of these vertical axis, what is basically 

7 compacts, is about one percent of the total market. 

8 But, even today, those two cubic foot are 

9 classified as full size washing machines, but if they 

10 went to a higher efficiency standard, .the practicality 

11 of converting that small product line and adding costs 

12 would basically eliminate that out of the market and 

13 take that away from consumers. And they do have unique 

14 utility as we have pointed out in many of our comments, 

15 many of them are used as portables. Some come with 

16 casters. They are a low in product for speciality 

17 purposes. And that was the whole rationale. 

18 The fact that there are also H Axis machines 

19 that would fall in that category, I think we recognize 

20 that that might be an issue from the marketing side but 

21 there are probably other solutions to that. The term 

22 compact, as it is used today, maybe that needs to be 

23 considered, if that is the right term. But, certainly 

24 the utility issues are there . 

25 MS. NADER: Does that answer the question? 

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1 Good. 

2 Yes? 

3 MR. NEAL: May I make a comment? Brian 

4 Neal, just a consumer. Why can't we just put them all 

5 in one class and look at the efficiencies ourselves and 

6 not have different classes? 

7 MR. BERRINGER: That is the next step, I 

8 think, that Earl brought up as far as port of access. 

9 That is one of the comments that we received in the 

10 notice, is to a have single class. So, maybe at this 

11 point, we can, we had a number of comments talking 

12 about that. 

13 MR. JONES: Well, I am not sure I understood 

14 what the gentleman's comment was, whether he was 

15 addressing the issue of port of access as it relates to 

16 standard machines or whether he was addressing the 

17 compact or the increase of the size of the compact. 

18 So, maybe he can clarify that and maybe --

19 MR. BERRINGER: I am sorry, could you clarify, 

20 sir? Were you referring mainly to only to the compact 

21 versus the standard or are you saying --

22 MR. NEAL: No, what I am saying is as a 

23 consumer if I want to compare machines, why should I 

24 have to look at different lists, put all the machines 

25 down, if I want to wash clothes, see what the 

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1 efficiencies are, whether it is horizontal, vertical, 

2 whether it is 1.6 or 2, just let me see and make my own 

3 decision. 

4 MR. BERRINGER: So, you are saying one class 

5 regardless of size or port of access, just one standard 

6 class, just close washers generically. 

7 MR. NEAL: Y~s. 

8 MS. NADER: Yes? 

9 MR. NADEL: Just getting back to the previous 

10 issues. 

11 MR. BERRINGER: This is Steve Nadel? 

12 MR. NADEL: Steve Nadel, of ACEEE, of the 

13 compact class. I was just curious if the people from 

14 Whirlpool, Staber and Miele, could maybe comment, is 

15 there some value between 1.6 and 2.0. That might work 

16 for everyone. I mean, I don't know, I heard Staber 

17 there, theirs is 1.93. So, I would guess a 1.9 

18 distinction would work. I don't know whether that 

19 would work for Whirlpool, likewise Miele. Is there 

20 some in-between value? 

21 MR. MARSOLLEK: This is Michael Marsollek with 

22 Bosch Group. 

23 First, a comment on your remark there, for 

24 us, 1.9 would not work. But, I also wanted to comment 

25 on that it is, I think it is dangerous to just work 

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1 cubic feet load sizes. Also for the comment that Mr. 

2 Weingartner from Miele before, that the capacity of 

3 horizontal axis machine in terms of load size, is quite 

4 different when you put that in relation to the actual 

5 cubic feet of the size of the drum, drum, because like 

6 a 1, I just grab a number 2.0 cubic feet, horizontal 

7 axis washer, can hold probably the same amount of 

8 laundry and again, I am just taking a number here, as a 

9 3.2 cubic feet top loader or even more laundry. So, 

10 from the consumer side, I think it is much more 

11 interesting to look at the actual load capacity. How 

12 much laundry actually can be washed, reasonably washed 

13 in that machine as opposed to just measuring the 

14 physical size of a tub, not taking into consideration 

15 the actual way the machine works. Thank you. 

16 MS. NADER: Thank you. 

17 The gentleman at the mike. 

18 MR. WEINGARTNER: Roland Weingartner, Miele 

19 Appliances. I think we may be mixing a little bit 

20 apples and oranges, too. We are speaking about here 

21 selling from a marketing point. All of our machines 

22 even though they are under two, I would say more than 

23 95 percent of them already reach or exceed the limits 

24 for standard machines, even though they are compacts, 

25 horizontal axis, I am speaking about. 

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1 But, what I see happening and perhaps Bosch 

2 and Staber is, we have somebody come in and out, since 

3 we are a compact, they market their machine as the most 

4 efficient standard size machine, when in reality our 

5 compacts are more efficient than their standard 

6 machines. So, we are mixing two different issues here, 

7 trying to make one answer out of them. So, you have 

8 got to separate, are we talking about pure energy or 

9 are we talking about marketing also? 

10 MS. NADER: Thank you. Yes? 

11 MR. NEAL: Chad Neal from Staber Industries. 

12 I think the thing that we have to consider here is 

13 usable tub volume, because everybody throws out a 

14 number like 3.4 cubic feet and 2.0 cubic feet, but 

15 there is a difference in cubic feet of the entire tub 

16 and then usable tub volume. That is the thing that 

17 needs to be considered. Maybe you take the entire tub 

18 capacity and subtract out the volume of water and the 

19 volume of the agitator and then you will come up with a 

20 number that is more accurate, not totally accurate, but 

21 more accurate than just a tub volume. 

22 MS. NADER: Thank you. Anyone else on this 

23 topic? 

24 MR. BEST: One more comment from the Whirlpool 

25 Corporation. 

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1 MS. NADER: Say your name, please. 

2 MR. BEST: Richard Best, Whirlpool 

3 Corporation. 

4 MS. NADER: Thank you. 

5 MR. BEST: Our comments and all this really 

6 are not intended to address the marketing issues as 

7 brought up here. I think the whole intent is that 

8 there is a small vertical axis low end product line 

9 that serves a speciality market here in North America. 

10 And that to put a high efficiency or high investment 

11 challenge to this product, would basically eliminate it 

12 from the market. Which as part of the rulemaking says 

13 this is not the intent of the rulemaking is to 

14 eliminate unique utility out of the market. 

15 I agree there are probably some issues 

16 related to the size and where people fall and how they 

17 might label their products. And even in the capacity 

18 measurements as to how you might measure. But, I think 

19 we stand on our comments that 2.0 is the request. It 

20 is based on the product as it exists today. And the 

21 same logic goes along if you are going to make it 1.7 

22 or 1.8, you have to retool the product for a small 

23 niche market, it is probably going to disappear. So, I 

24 think our comments are, maybe there needs to be some 

25 further discussion outside of this meeting as to 

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1 possible solutions to this conflicting issue here. And 

2 it is a mixed issue, but I think our 2.0 is the number 

3 that we would support. 

4 MS. NADER: Thank you. Sir, sir? 

5 MR. NEAL: Tom ~eal, with Staber 

6 Industries. 

7 As a user of a washing machine, you ask a 

8 housewife to use the washing machine or even, ·r use 

9 one, too, don't usually think of doing two cubic feet 

10 of laundry or 12 pounds of laundry. I usually think of 

11 doing my laundry in loads. I did two loads today or 

12 three loads. And if you look at the statistics on 

13 loads, the loads are down around seven pounds. Our 

14 small machine at Staber~s, relatively small machine, 

15 will do the full range of loads that were mentioned in 

16 the Burns Study. And it comfortably does the standard 

17 load that the average housewife that is· doing laundry 

18 uses. And I think maybe we should be thinking in terms 

19 of loads of laundry, standard load of laundry rather 

20 than the cubic feet or the pounds. 

21 MS. NADER: Thank you. Anyone else? 

22 Fine. And staff, do you have what you need 

23 on the -- Oh, I see one more. 

24 

25 

MR. JONES: On what? Do you have what you 

need on what? 

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1 MS. NADER: On the topic of product class. 

2 MR. JONES: No, I thought we were just 

3 exhausting the issue of size of compact versus 

4 standard. 

5 MS. NADER: Size. All right. Thank you. 

6 MR. JONES: There are still other issues to be 

7 addressed. 

8 MR. BERRINGER: Okay. 

9 MS. NADER: Thank you. 

10 MR. STEVENS: Charlie Stevens, Oregon Energy 

11 Office. 

12 Has the Department ever considered in the 

13 past setting the standard for these products like they 

14 set it for refrigerators? With a formula that adjusts 

15 the maximum allowability use to, in this case the 

16 volume? 

17 MR. BERRINGER: I guess we have not considered 

18 that. I guess that maybe a possibility. I am not sure 

19 what the likelihood of that is. 

20 MR. STEVENS: It is one, I mean, it seems to 

21 me that Whirlpool is not just sort of suggseting that a 

22 second class needs to be established at a certain 

23 benchmark, but that a s~parate standard would 

24 ultimately have to, I mean, the goal there is to set a 

25 separate standard for that class. And from the sound 

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1 of it, it would have to be a lower efficiency standard 

2 to accommodate the product that is made today without 

3 substantial changes. And sometimes a sliding scale can 

4 work to accommodate that sort of thing. I don't know, 

5 I have never tried to do it, so I don't how 

6 successfully you could be. But, I might suggest that 

7 the Department give that some thought if there is some 

8 tendency toward a single class. 

9 MR. BERRINGER: Okay. Thank you. 

10 MS. NADER: Thank you. 

11 MR. JONES: Earl Jones here, G.E. 

12 Actually this discussion that we have just 

13 had is a very good lead in to the whole, to the other 

14 part of the product class discussion. And that, of 

15 course, is the more basic one of whether or not the 

16 Department is heading in the right direction in its 

17 proposal or its suggestion, whatever you want to 

18 characterize it as. To eliminate any product class 

19 based on the access of rotation. And of course, we at 

20 G.E. believe that that would be a mistake. And this 

21 continues to be an issue that requires a great deal 

22 more analysis than the Department has done up to this 

23 point in time. It is a little like the cart before the 

24 horse, focusing first on the question of consumer 

25 utility, we have got, you have got a workshop scheduled 

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1 for later today, get, even though you haven't pulled 

2 that data together yet, even though the record is quite 

3 conflicted on this question, you have made quite clear 

4 your intention to proceed. That I think is going to be 

5 a significant roadblock to progress in this rulemaking. 

6 And I think you need to recognize that fact. And let's 

7 just prepare for it. 

8 The discussion we just had, as I said, is a 

9 good predicate for this discussion, because here we 

10 are, now with the last discussion from Oregon 

11 suggesting that a lower efficiency might be appropriate 

12 for an upside compact washer. When based on the 

13 comment we just heard from the people who build those 

14 machines, those are apparently more efficient than 

15 other machines. If the Department is promoting 

16 efficiency, what exactly is your goal? It seems to me 

17 that that the whole question of how you determine these 

18 product classes needs to focus on what guidance is 

19 being provided to consumers. The gentleman's question 

20 back there, I think was an interesting one. Because 

21 there is substantial potential for deception of 

22 consumers an actual value they are receiving. And 

23 performance, both in terms of the energy efficiency, 

24 and operating costs if these classes are merged . 

25 You want to promote efficiency? I say do it 

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1 in a rational way that preserves the ability of 

2 consumers to make an appropriate choice and also 

3 preserves their ability to access utilities and 

4 functionalilties that they have determined in the 

5 market to be critical. Not as the basis of some 

6 rulemaking, not on the basis of some people sitting in 

7 a room somewhere, you know, defining what the answer 

8 should be. But, based upon what the market has 

9 commanded. It is rational, at least in this respect, 

10 that people buy products they want. And for this 

11 process to lead to one which takes products away from 

12 them, makes it is invalid. And also, opens it up to 

13 challenge . 

14 So, let's just understand that this still, it 

15 is a substantial issue. It requires a lot more data 

16 than is in the record. We look forward to working with 

17 the Department on that and meet with the rest of the 

18 parties at this table. But, it is still a substantial 

19 question that needs to be resolved. 

20 MR. BERRINGER: Thank you. 

21 MS. NADER: Thank you. Sounds like G.E. has 

22 additional data to offer and I know they will 

23 appreciate it. 

24 

25 

MR. BERRINGER: Okay .. At that, should we 

move onto the next topic? Does that pretty much 

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1 address the product class? 

2 Phil Manthei? 

3 MR. MANTHEI: Phil Manthei, from the Lyons 

4 Laundry. 

5 Regarding the issue on front loading, top 

6 loading, is the Department going to go out and ask 

7 consumers their preference? 

8 MR. BERRINGER: That is part of the 

9 information we are looking at. The utility issue that 

10 we are looking to get out of the consumer survey. And 

11 that is also, again, we can discuss further in the 

12 working group, what we, we have not, we are just in the 

13 first stages, the first phases of putting together the 

14 consumer analysis, consumer focus groups and so forth. 

15 MS. NADER: Okay. Are we ready to move on? 

16 Water and sewer rates. 

17 MR. BERRINGER: Again, this is going to be 

18 presented later, so there maybe even further discussion 

19 on the sewer and water rates. I think the topic on the 

20 agenda was talking about the, talking specific about 

21 historical trends and information there and may 

22 elaborate. 

23 We can talk about that later this afternoon 

24 and get into more detail. Does anybody have specific 

25 comments on this as far as the data that was collected? 

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1 MR. SCHEEDE: Glenn Scheede. Just at 

2 question, how are you going to get into the issues this 

3 afternoon of how the data were recollected, in detail, 

4 so that we can tell whether the data are 

5 representative, valid and reliable. Will those data, 

6 will those issues be addressed in detail this 

7 afternoon? If they will, fine. 

8 MR. BERRINGER: Yes, they will. 

9 MS. NADER: Thank you. Other questions? 

10 MR. MARTIN: Michael Martin. I would rather 

11 wait until this afternoon when we have this background 

12 to discuss these matters. 

13 MR. BERRINGER: Okay. That will be fine. 

14 There was very little interest on 

15 elasticities, I know. That is something else that we 

16 are trying to again take out of the consumer survey 

17 information. We are trying to get some elasticity 

18 values. So, again that will be. Is there, does 

19 anybody else have a specific comment on the 

20 elasticities, cost elasticities? 

21 Okay, again, we will get into that a little 

22 bit this afternoon. 

23 Shipments, I know there was a lot of interest 

24 as far as the topic of shipments. And I know that is 

25 a, you know, from the standpoint of the analysis, the 

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1 Department is looking to try to get some more 

2 information on shipments. Basically, have information 

3 on the EF, with the new standards in place, there is 

4 very little information on MES. So, that is something 

5 that the Department has proposed. If there is 

6 additional data that can be given to us on that 

7 particular topic, so we can do a more thorough 

8 analysis. Is there --

9 MS. NADER: I saw a number of hands go up 

10 earlier. Were those questions or comments? Let's hear 

11 from you. 

12 MR. JONES: Well, Earl Jones here again, G.E. 

13 When you say you are going to go into 

14 shipments, what exactly is encompassed in that, Bryan? 

15 I mean, this afternoon, is that what, will there be 

16 some presentation on that? 

17 MR. BERRINGER: Yes, this afternoon Lawrence 

18 Berkeley Laboratory was going to talk about shipments. 

19 I think it is more or less the historical trends and 

20 projections, is that correct? I am looking for Jim? 

21 MR. MCMAHON: That is right. 

22 Earl, there is a handout in the package this 

23 morning, if you would like to get a preview. 

24 (Pause.) 

25 MR. JONES: So, do you, Jim, in this 

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1 presentation get into the issue of shipments by any 

2 particular configuration, product configuration or is 

3 this just gross shipments, in particular channels? 

4 MR. MCMAHON: Gross shipments. This is not by 

5 configuration. 

6 MR. JONES: Okay. So, Bryan, can we have 

7 some discussion then on the, I guess it would be the 

8 information that is set forth on page 48 of the ARPR, 

9 on the projected sales of horizontal axis washers 

10 through the year 2030. Whoever is the, whoever 

11 produced that data, can we have some explanation or 

12 discussion of that? And I guess my question is, is 

13 this a statement of aspiration or is it based on some 

14 data which says that this is the trend over X period of 

15 time and indeed we are projecting based on sales or 

16 what is it? 

17 MR. BERRINGER: Are you talking specifically 

18 about the projections of the H Axis? 

19 MR. JONES: Correct, in the middle paragraph 

20 on page 48. 

21 MR. BERRINGER: Yes, I think the .5, is that 

22 what you are looking at, at the .5 percent? 

23 MR. JONES: Yes. 

24 

25 

MR. BERRINGER: Increase per year. I think 

that is just a, yeah, we are looking, if you have 

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1 specific comments on that, whether that is high, low. 

2 MR. JONES: I have a specific question of 

3 where it came from. 

4 MR. BERRINGER: Okay. 

5 MR. JONES: And what role is it playing in 

6 this rulemaking? How is it entering into the 

7 Department's analysis of this rulemaking? 

8 MR. MCMAHON: This is Jim McMahon from 

9 Lawrence Beckley National Lab. 

10 Earl, that was an initial projection based 

11 upon discussions with a number of people involved in 

12 programs promoting horizontal axis machines. It was 

13 put out there as a strawman for comment. We would be 

14 happy to have further data about the current shares as 

15 well as expectations about further shares. 

16 MR. JONES: So, I take it this was their 

17 aspirational goal and that indeed, there is no data to 

18 support this statement. 

19 MR. MCMAHON: This was aspirational goal, I am 

20 not sure exactly how you would find that. 

21 MR. JONES: Well, okay, then maybe, let me put 

22 it in English. I know it won't be possibly in 

23 statistical terms. What I mean is this is a goal they 

24 hope to achieve based on maybe their plans, but indeed 

25 that there is no data, which would say that current 

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1 sales would yield this kind of projection. 

2 MR. MCMAHON: I think that is accurate. I 

3 have not yet received --

4 MR. JONES: Okay, thank you. 

5 MR. MCMAHON: historical trend data about 

6 sales. 

7 MR. JONES: So, then, Bryan, to get back to 

8 the question. So, where does this, how does this 

9 information play into this rulemaking? Are you saying 

10 that we have to challenge this or else it enters into 

11 the body of the rulemaking as an established fact? 

12 MR. BERRINGER: Well, I think we did have the 

13 GRIM training session. It is taking into 

14 consideration, when you take the base case, when you 

15 are looking at, you know, what out there as far as the 

16 market. So, if you.take that, this is being considered 

17 in the analysis. So, if there is conflicting data or 

18 if there is other suggestions, then --

19 MR. JONES: So~ how then does the success of 

20 this product, which is, therefore, going to reduce the 

21 goal that the rulemaking, I assume, needs to achieve, 

22 how is that going to, how is that factoring into the 

23 analysis, then? Yet, you are presumably move for 

24 reduction in the stringency of the standards, isn't 

25 correct? 

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1 MR. BERRINGER: I am not sure what you are 

2 asking as far as --

3 MR. JONES: Well, if market is taking care of 

4 the problem, is my question. 

5 MR. BERRINGER: If it does, if it does, as 

6 projected? 

7 MR. JONES: Yes. 

8 MR. BERRINGER: Then again, it would be 

9 considered in the base -- I am sorry, go ahead, 

10 Michael. 

11 MR. RIVEST: Earl, I can --

12 MS. NADER: Name, please. 

13 MR. RIVEST: Mike Rivest, from ADL . 

14 I can tell you how it is being used now. I 

15 can't really answer the measurement question. The way 

16 it is being used now is energy savings in the future 

17 are being benchmarked against this market penetration 

18 of H Axis. So, the higher the market, the forecasted 

19 market penetration of the H Axis, the lower the energy 

20 savings to the nation of a rule. So, when those energy 

21 savings are weighed against other factors, such as 

22 manufacturing impact, for example. The energy savings 

23 been less, there is less to weigh against. So, it does 

24 come into play in that sense . 

25 I am not sure that fully answers your 

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1 question. 

2 MR. JONES: Yes, it does, thanks. 

3 MR. RIVEST: Okay. 

4 MS. NADER: Next? Yes, sir? 

5 MR. GOLDSTEIN: Dave Goldestein, NRDC. 

6 A follow up question, I think for Jim. As I 

7 was reading this section just now, it seemed to me that 

8 H Axis wasn't being used in a very rigorous sense. And 

9 what you really meant was high efficiency. And you 

10 weren't really trying to specify whether it was high 

11 efficiency, horizontal, vertical, diagonal or some new 

12 technology. Is that correct? 

13 MR. MCMAHON: Jim McMahon from LBL. 

14 That is correct. What is important is what is 

15 the distribution of efficiencies that will be sold in 

16 the base case, in the absence of standards? That is 

17 what we need to know. 

18 MR. GOLDSTEIN: So, those percentages refer to 

19 high efficiency washers with a certain MEF. 

20 MR. MCMAHON: That is correct. 

21 MR. GOLDSTEIN: Thank you. 

22 MS. NADER: Okay. Gentleman from Edison 

23 Electric. 

24 MR. ROSENSTOCK: Steve Rosenstock, Edison 

25 Electric Institute. 

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1 Just as another, in the technical support 

2 document in Chapter 3, it talks about first quarter '98 

3 washer shipments by access. 

4 MS. NADER: May I ask you to speak up a 

5 little, please? 

6 MR. ROSENSTOCK: Steve Rosenstock, EEI. 

7 In the technical support document dated 

8 October '98, in Chapter 3, Table 3.3, washer shipments 

9 by access, first quarter 1998, the source of that, is 

10 the revised draft report on consumer research for 

11 clothes washers, April '98. It said front 

12 load/horizontal had 5.4 percent market share. I guess 

13 that is a national figure. Oh, it says, okay, may not 

14 include all major retailers and therefore has a margin 

15 of error. But, that, just as at least one data, it is 

16 showing that in there, FYI. 

17 MR. BIERMAYER: Peter Biermayer, LBNL. 

18 That number is from a company called, a 

19 marketing company called Intellect. They surveyed, I 

20 believe, a large number, I don't know the exact figure, 

21 of retailers. I believe that doesn't include Circuit 

22 City or Sears. 

23 MR. ROSENSTOCK: Steve Rosenstock. 

24 As a follow-up, but was it a national as 

25 opposed to a regional survey? 

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1 MR. BIERMAYER: Yes, it was a national survey. 

2 MR. ROSENSTOCK: Okay. 

3 MS. NADER: At the mike? 

4 MR. GREGG: Tony Gregg, City of Austin. 

5 I have a comment more on the base case 

6 scenario. It seems like the base case is penalizing 

7 the efforts of those in the industry who are, outside 

8 of the industry actually, in the utility field, who are 

9 promoting the H Axis machines. It is not a given that 

10 utilities will promote H Axis machines indefinitely. I 

11 think most of us are hoping that there will be a 

12 standard earlier rather than later. So, we can invest 

13 our money in other things. So, if .5 percent is the, 

14 if it is a good number or bad number, whatever that 

15 number is, I think we should, there should be a 

16 reduction in that number based on the effectiveness of 

17 the rebate programs that are being promoted by 

18 utilities, so that the standard is not assuming that 

19 those programs will continue. Because I don't think 

20 they will continue indefinitely. The cost of them is 

21 high. And so, anyway, I think the forecasting has to 

22 recognize that and make some allowance for it. Thank 

23 you. 

24 MS. NADER: Thank you . 

25 MR. SCHEEDE: Glen Scheede, again. 

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1 Just a minute ago we had an example of using 

2 data that comes from some place, the organization has 

3 an impressive name, Intellect, but it tells us nothing 

4 about the quality of the data. I think DOE needs to 

5 start getting some discipline in this process. And if 

6 data are cited from some source, details of the manner 

7 in which that data were collected, whether it is really 

8 representative, are needed. Just saying it is a 

9 national survey, tells us absolutely nothing about the 

10 quality of the data. And that is a general problem. 

11 MS. NADER: Thank you. 

12 Yes, sir? 

13 MR. GOLDSTEIN: David Goldstein, NRDC. 

14 I think this is mischaracterizing the problem 

15 a little bit. There are no data concerning the future. 

16 There is data concerning the present or the past. And 

17 the future is projections which have different 

18 methodologies and different assumptions behind them. 

19 I think the broader point that is consistent 

20 with what Mr. Scheede said and a number of other 

21 comments, including the gentleman from Austin, is that 

22 we don't know what the base case. There is uncertainty 

23 in the.base case and that uncertainty ought to be 

24 modeled explicitly because it has different 

25 consequences than any certain outcome. In other words, 

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1 if manufacturers know that the penetration of high 

2 efficiency washers is going to be 15 percent in the 

3 Year 2005, they can make investments based on that, and 

4 be sure of getting a return. If they know that it 

5 might be zero and it might be 100 or it might be 

6 anywhere in-between, there is a great possibility for 

7 stranded costs, or for not being able to meet consumer 

8 demands and having impacts in the other way. And those 

9 are manufacturer impacts of the base case, and they 

10 need to be analyzed. 

11 MS. NADER: Thank you. Glenn? 

12 MR. SCHEEDE: Glenn Scheede, again. 

13 I thought the data we are talking about 

14 related to.the first quarter of '98, and it was, in 

15 fact, historical data that LBNL was referring to. And 

16 if so, I think they have a responsibility, that DOE has 

17 a responsibility to explain in detail where that data 

18 came from. If, in fact, as the gentleman from NRDC 

19 said, it is a forecast, then let's find out what the 

20 methodology is for the forecast and provide that in 

21 detail. But, perhaps LBNL could explain something 

22 about the specific piece of data that was used. 

23 

24 

25 

MS. NADER: Thank you. Yes? 

MR. NADEL: Steve Nadel, ACEEE . 

I had another question, I guess is probably 

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1 for LBNL. In the model used, is that model basically 

2 set up so that it needs kind of a straight line 

3 projection or is it able to deal with differing 

4 projections? I mean, it has come out here that it is 

5 likely and I have heard similar data from other 

6 sources, the market share in 1998 is going to be 

7 greater than the three percent you assumed. On the 

8 other hand, I suspect that, you know, your long figure 

9 maybe reasonable. Can you deal with other shapes of 

10 the saturation curve? 

11 MR. MCMAHON: Jim McMahon from LBNL. 

12 The model is flexible. We can deal with any 

13 projection that you would like . 

14 And with regards to Mr. Scheede's question, 

15 Intellect is a firm that does market research. I 

16 understand that they sell this information to a number 

17 of private entities. And in our search for whatever 

18 data we could find that is used by other people and 

19 viewed as credible by other entities in the industry, 

20 we use them as one source of information. We would be 

21 happy to give you more information about the company 

22 and about their methodologies. 

23 MS. NADER: Thank you. 

24 MR. BERRINGER: And if you have, anybody has 

25 any better information or additional information, you 

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1 know, we definitely would want to do that. We are 

2 doing, research for the best information that we can 

3 find, that is available. 

4 MS. NADER: Thank you. 

5 Anybody else on this subject? 

6 Okay. We are over at alternative 

7 standards scenarios. 

8 MR. BERRINGER: Are were ready to tackle that 

9 one now? 

10 Obviously, we have, this is one of the major 

11 things as far as the rulemaking is concerned, as far as 

12 the scenarios. Again, these are the examples. These 

13 are in no way where the Department has said this is 

14 what we are going to do, this is a starting point for 

15 discussion. And to give an example, there has been 

16 discussions as far as a single phase standard in a 

17 short amount of time, you know, three years. Or a two 

18 phase, a stretch vertical in three years, followed by 

19 five years of a higher efficiency standard levels. 

20 So, some of the preliminary analysis does, 

21 when going through it, justify some of this. Of 

22 course, we are not finished through the analysis. We 

23 still have, in NOPR study we still have to do our 

24 manufacturing impact, a number of other things. And we 

25 will rerun that, rerun the analysis also, based on new 

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1 information. 

2 So, at this point does anybody have any 

3 concerns, recommendations or ideas as far as a 

4 proposal, as far as standard levels or efficiency 

5 levels for the clothes washers? I think we -- No. You 

6 are going to let the Department choose. Okay. 

7 MS. NADER: Yes, David. 

8 MR. GOLDSTEIN: David Goldstein, NRDC. 

9 It is very hard for us as a stakeholder to 

10 make any recommendation on these alternatives, because 

11 we can't connect them to anything in the real world. 

12 That is there are number of products that currently are 

13 at the types of levels that I think you are considering 

14 in the ANOPR. And depending on what the actual MEFs of 

15 those models are, will influence our judgement and I 

16 presume the judgement of a lot of other stakeholders as 

17 to whether the levels make sense. So, it seems to me 

18 that a research that is extremely important, is to 

19 gather MEFs of existing product on the marketplace, at 

20 relatively high efficiencies and publish those, so that 

21 we can see what, how the existing products match up 

22 with potential standard levels. That allows everybody 

23 to make some estimate of how hard of a job is it to 

24 redesign to this level, and what would the impacts of 

25 doing it be. 

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1 MR. BERRINGER: Yes, the Department has done 

2 some MEF testing, but we didn't divulge specifically, 

3 it is in the TSD, the information, what particular 

4 models or manufacturers those represented. But, we did 

5 take top selling machines and test them and to get some 

6 MEF data. 

7 MR. GOLDSTEIN: But, we can't comment 

8 intelligently on it until we share the data. I mean, 

9 this is not priority information. Anyone with enough 

10 money can go out and buy a model and test it, and they 

11 have the MEF, but it is kind of a silly and burdensome 

12 way to have each stakeholder that is interested do 

13 that, when you could have one answer, so the 

14 manufacturers could submit it themselves. I don't 

15 really, it doesn't concern me who is vouching for the 

16 accuracy, as long as it is some trusted source that 

17 says here is what the number is. 

18 MR. BERRINGER: Terry? 

19 MR. THIELE: Terry Thiele with Frigidaire. 

20 I would like to ask the Department a 

21 question, which is what's the Department purpose is in 

22 proposing at this stage in the process these different 

23 final rule outcome scenarios? In other words, what are 

24 you attempting to achieve by throwing these out? Given 

25 the fact that we don't have the analysis done to 

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1 justify any particular combination at the moment. 

2 MR. BERRINGER: Well, we have some preliminary 

3 analysis, as far as the LCC and the NES, as far as --

4 And based on what information was submitted. Again, 

5 these are starting points for discussion. The 

6 information may change but we are trying to see if we 

7 can reach a level that is agreeable by all.the 

8 stakeholders. 

9 MR. THIELE: The observation I would make 

10 though, is that the ultimate outcome of the rulemaking, 

11 whether you have one phase or two phases, two different 

12 standards at different times, or simply a single 

13 standard, will in large part be dictated by your 

14 subgroup analysis. And that to make some sort of macro 

15 cut at this before you have undertaken that sort of 

16 subgroup analysis, may tend to distort the rulemaking 

17 process in a way that maybe you didn't intend. But, 

18 may not, may cause us to have to go back and redo a lot 

19 of work, because the doubles in the detail. And the 

20 earlier conversation on product classes, between 

21 compact and standard, I think is instructive in the 

22 consequences for subgroups of manufacturers of those 

23 macro decisions, are going to ultimately dictate where 

24 your economic feasibility comes out . 

25 So, my thought to the Department might be if 

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1 you are looking for a strawman scenario, or a group of 

2 scenarios to sort of bound your discussion, it might be 

3 more useful to take a low, middle, high approach and 

4 throw out a set of scenarios that maybe less bounded by 

5 your current work to date, as much as giving sort of 

6 extreme examples of what might happen. So, that you 

7 can then differentiate among them from a philosophical 

8 standpoint. And then allow your subgroup analysis to 

9 fill in the detail later on. Because I am just afraid 

10 that you are almost prejudging this absence your 

11 subgroup analysis. 

12 MS. NADER: Thank you. Other comments? Yes? 

13 MR. MARTIN: Michael Martin, California Energy 

14 Commission. 

15 I think I understand the situation about MEF 

16 but let me state what I think and you can correct me. 

17 This is defined in a test method which is not 

18 yet being applied, but has been published and approved, 

19 is that correct? 

20 MR. BERRINGER: That is correct. And the test 

21 procedure, looking that MEF, will not go into effect 

22 until new standards take place. So, there is 

23 information on the market as far as EF, but as far as 

24 MEF and particular models. There is no public 

25 information on that. 

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1 MR. MARTIN: I see. Now, but DOE has done 

2 some testing or paid for some testing . 

3 MR. BERRINGER: We have done a limited number 

4 of tests. 

5 MR. MARTIN: On what basis are you not 

6 identifying what the models that you have, that you 

7 have tested? Is it a confidential thing that might be? 

8 MR. BERRINGER: At this point it is 

9 confidential thing that we didn't want to divulge the 

10 manufacturers. We were doing this more for background 

11 information for ourselves to sort of get what David 

12 Goldstein wants. The thing is, is we started to look 

13 at it and we took hot selling models, that are on the 

14 market. When do you stop testing the models? Do we 

15 test every single model that is on the market, is the 

16 other problem as far as trying to -- And there is an 

17 issue far as confidentiality for information. So, 

18 but that could be something that could be resolved or 

19 discussed. 

20 MR. MARTIN: I find it very, very difficult to 

21 understand why testing a model on the market, using a 

22 published test method, could in any way be 

23 confidential. And I kind of wonder if I was to try 

24 this on DOE, whether your attorneys would tell me that 

25 couldn't be done. 

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1 The other question I would like to say, is if 

2 we, at the Energy Commission, were to have a survey as 

3 to what is available, and we do have a database. It 

4 has some columns input MEF in. And we were to get this 

5 information from you, would you insist that we didn't 

6 divulge it to anybody? 

7 MR. BERRINGER: No, if you were making public 

8 information to that, I mean, at this point, we just 

9 felt --

10 MR. MARTIN: So, you could give it to us and 

11 we could publish it and get you out of this pickle 

12 then? 

13 MR. BERRINGER: That would be something that 

14 we would have to discuss with General Counsel, if we 

15 would release that information. 

16 MR. MARTIN: May I on the record, on behalf of 

17 the California Energy Commission, request that 

18 information from you in order that the database may be 

19 more useful to people? 

20 MS. NADER: So noted. 

21 MR. MARTIN: Thank you. 

22 MS. NADER: Gentleman at the mike. 

23 MR. POPE: Hi, Ted Pope with the Pacific Gas 

24 and Electric . 

25 Just our position is we are anxious to see a 

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1 good aggressive standard that is economically 

2 justified, sooner than later. We have been spending 

3 money on this, in this area since 1991, '92, you know, 

4 and originally we had the expectation there would be a 

5 standard taking effect in probably about this year, I 

6 guess, maybe next year. And I guess our concern is 

7 that things continue to look as if they are going to be 

8 dragged out with these incremental steps. And so, not 

9 yet having been convinced that it is, is solid 

10 justification for going a two phase step, we are at 

11 this time interested in seeing an aggressive step 

12 taken, you know, right clean, whether it is 40 or 45 or 

13 50 percent. I agree with some of the speakers here, 

14 that I am not real clear yet what the answer is and we 

15 look forward to getting more data there. 

16 MS. NADER: Thank you. Yes? 

17 MR. ROSENSTOCK: Another general comment, I 

18 know we will get more specific this afternoon. 

19 MS. NADER: Name, please. 

20 MR. ROSENSTOCK: Steve Rosenstock, Edison 

21 Electric Institute. 

22 Another general comment about the 

23 supplemental ANOPR is, as going through it and also 

24 going through the technical support document, when 

25 looking at, through this on the energy rates for both 

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1 electricity and natural gas. It appears that the full 

2 rate rather than the marginal or even fixed cost for 

3 not taking it out, out of the ranges. So, as a result 

4 the payback shown, as well as some of the life cycle 

5 cost analyses are on the optimistic side. And I will 

6 get more into that later. But, I am saying when you 

7 are doing it over again, I do think that where possible 

8 as approved by the industry advisory committee, that to 

9 use ideally, which is the last step, to get the 

10 marginal energy rates to be used, or in the interim, 

11 for the interim analysis, taking out the fixed cost at 

12 a minimum is really necessary to get the better ranges 

13 of values. And I will talk more about that this 

14 afternoon. But, since you were looking for general 

15 comments, I just wanted to throw that out there. 

16 MS. NADER: Thank you. 

17 MR. ROSENSTOCK: Thank you. 

18 MR. BERRINGER: And as you know we are 

19 pursuing marginal energy rates. And that is part of 

20 the discussion this afternoon. And also in March, we 

21 also did present results for both the fixed, with or 

22 without fixed cost in that March workshop. 

23 MR. ROSENSTOCK: But, but -- Steven 

24 Rosenstock, but in the ANOPR, in the Federal Register, 

25 you did not take out the fixed costs. 

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MR. BERRINGER: That is 

MR. ROSENSTOCK: So, that is why I wanted to 

raise that issue. 

MR. BERRINGER: Thank you. 

MS. NADER: Thank you. 

Steve? 

MR. NADEL: I wanted to ask DOE two questions 

and then I can get some opinions on this issue of 

general direction, or in particular exact numbers. 

The first question, if I am understood 

correctly, Bryan, that you have done some testing of 

MEF of some units. You don't want to identify what 

test results go with what units. Can you at least say 

what test results you have gotten, Unit A, Unit B, 

ignoring what products they are. 

the TSO. 

there. 

mike . 

MR. BERRINGER: That information should be in 

MR. NADEL: Okay. 

MS. NADER: Thank you. 

MR. NADEL: Okay. I will look for it in 

MR. BERRINGER: It is available. 

MS. NADER: Yes, sir, please step to the 

MR. MODTLAND: Dave Modtland, Frigidaire 

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1 Home Products. 

2 The information that is presented in the TSO, 

3 on the MEF equations, it is difficult to tell since the 

4 models are not identified, but I guess to me that data 

5 looks suspect at this time. And as we have had some 

6 discussions in the past, with the facility that has 

7 presented information. They have, themselves, 

8 identified discrepancies in being able to repeatedly 

9 obtain MEF numbers for certain models. And so, there 

10 is, I have got some questions, some of those values 

11 that exist in the TSO, at least in my mind. 

12 MR. BERRINGER: Okay. If I could just follow 

13 up on that. Just, there is some, we have seen some 

14 discrepancies, that information as far as the RMC, so 

15 it does make a difference in some of those results. 

16 And that is something we are further pursuing. So, 

17 there are some possible changes in the numbers that are 

18 presented in that, in the TSO. 

19 MS. NADER: Yes, sir? 

20 MR. NEAL: Tom Neal, Staber Industries, again. 

21 I don't think we would have any difficulty sharing the 

22 data on the MEFs or the EFs, but the problem that we 

23 see is that it is misleading to the consumers. It 

24 tells you a fictitious number, that represents how much 

25 energy they expect to save. Our machine will probably, 

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1 if it was truly rated, would be twice as efficient as 

2 the EF would indicate, simply because of the tub size 

3 factor. I would rather see, I would rather go as a 

4 consumer to an appliance store and ask them how much 

5 water or energy it uses to do a load of laundry rather 

6 than get some factor, getting hard data, and I have 

7 done this, ~ have gone into several appliance stores 

8 and asked them, well, how much water does this machine 

9 use in a load and they don't know. 

10 MS. NADER: Thank you. 

11 Yes, sir? 

12 MR. STEVENS: Charlie Stevens, Oregon Energy 

13 Office . 

14 I just, I can point out just quickly that the 

15 energy guide label does have the energy use on it. So, 

16 the EF is simply for standard compliance purposes. 

17 But, what I am beginning to get here is that 

18 if some of us want data on MEF performance for various 

19 machines, we might as well start making plans to go get 

20 it, ourselves, because the data that you have needs to 

21 be adjusted, redone, some of it anyway. So, even if 

22 you let us know what it was, it isn't exactly what we 

23 would hope for anyway. Is that right? 

24 

25 

MR. BERRINGER: There can be some errors in 

that data, yes. 

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1 MR. JONES: Earl Jones here, G.E. 

2 Come on, Bryan, it is riddled with error. It 

3 is inaccurate. I mean, I don't think you should hold 

4 back in this discussion to say that the data is 

5 unreliable and therefore, the projections about what 

6 machines even today are capable of performing at, 

7 pardon the grammar, and therefore, can be the base on 

8 which we can build, the assumptions are simply wrong. 

9 And the data will have to be retested in order for it 

10 to have any credibility with the people who make the 

11 machines. I mean, is there any doubt about that? 

12 MR. BERRINGER: If the manufacturers are 

13 willing to provide that, we can throw out this data 

14 altogether and then there won't be any question as far 

15 as what was done. That is really, would be the best 

16 information. And then there wouldn't be any question 

17 as far as a testing facility. 

18 And as you stated there is a, there is 

19 something that we are trying to address, as you know 

20 with the RMC, to make sure that 

21 MR. JONES: Exactly. I just 

22 MR. BERRINGER: -- that is resolved. 

23 MR. JONES: With the understanding that 

24 somehow we can tweak it or something . 

25 MR. BERRINGER: No, we are not 

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1 MR. JONES: Okay. 

2 MS. NADER: Thank you. 

3 Yes? 

4 MR. MARTIN: Michael Martin. 

5 How does the data that you got in testing 

6 compare with what was given to you by the 

7 manufacturers? 

8 MR. BERRINGER: We do not have any information 

9 from the manufacturers on MEF at all. 

10 MR. MARTIN: And you don't have any from 

11 anywhere else? 

12 MR. BERRINGER: No. Other than what we 

13 tested . 

14 MR. MARTIN: Then you have the world's best 

15 data. And I challenge the manufacturers to make it 

16 even better. 

17 MS. NADER: Thank you. 

18 Over here? 

19 MR. MONTUORO: Lou Monturo with Amana. 

20 I guess my question is that obviously this 

21 is, the baseline data is controversial. Is there 

22 plans to get, you are going to have to start with the 

23 baseline data to regulate some improvement or we don't 

24 have a baseline, is there plans to get more data, or is 

25 that what we are discussing now? Or are you just going 

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1 to take the numbers that are admittedly have 

2 discrepancies and use those as a baseline? 

3 MR. BERRINGER: These, the data that we did as 

4 far as testing has nothing to do with the baseline. We 

5 were just trying to get our own idea. I mean, the 

6 manufacturers submitted the information on a baseline 

7 unit. Okay, we are just trying to as David Goldstein 

8 had said, try to an idea of what machines might match 

9 up with those efficiency levels that are in the 

10 rulemaking. So, we were doing that more for our 

11 internal knowledge. And it is not part of the baseline 

12 or any of the analysis. This is like a side issue. 

13 MR. MONTUORO: But, isn't the proposal to --

14 MR. BERRINGER: We need you to use the mike so 

15 we can have you recorded. 

16 MR. MONTUORO: Okay. Isn't the proposal to 

17 regulate the MEF number? Yes, no? 

18 MR. RIVEST: Yes, but the cost data that was 

19 provided, which is at the basis of the analysis, has 

20 been provided by manufacturers according to their test 

21 results. Not according to the test results by this 

22 independent lab. 

23 

24 record . 

25 

MS. NADER: Say your name, please, for the 

MR. RIVEST: Mike Rivest of EDL. 

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1 MR. JONES: Well, Earl Jones here. And of 

2 course, Mike, you are right about the cost data, but am 

3 I not right and please correct me if I am not, that the 

4 assumptions which underlie the strawman here, in the, 

5 well, it is in the ANOPR as well, about where the 

6 standard might end up. Is that not based on some 

7 notion of what the MEF performance, that we have today 

8 might yield? 

9 MR. RIVEST: There is no reliance at all on 

10 the data tested. It is all based on the data submittal 

11 from -- members. 

12 MR. JONES: Just on the cost verus the 

13 efficiency? 

14 MR. RIVEST: Right. 

15 MR. BERRINGER: Right. And they have also 

16 seen results. 

17 MR. RIVEST: -- the Department was trying to 

18 do with this testing is to understand what, where the 

19 market is currently as opposed to incremental cost for 

20 achieving these levels. 

21 MS. NADER: Okay. Yes, Steve? 

22 MR. NADEL: I had a second question, which 

23 relates to the three options you set forth as possible 

24 strawmen, if you will. Has the Department looked into 

25 at all with legal counsel, the question of if they do a 

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1 two tier standard, an initial tier, that takes effect 

2 three year, whether the period between those two 

3 standards has to be five years or whether there are 

4 options to, because you are promulgating them at the 

5 same time, the period could be narrowed? 

6 MR. BERRINGER: I will look to Gene Margolis 

7 to see if 

8 MR. MARGOLIS: We have not looked at whether 

9 the period can be less than five years. 

10 MR. NADEL: I would suggest that if you do 

11 want seriously consider that option, that is a very 

12 important issue, at least from our opinion. The way we 

13 see it, the schedule keeps slipping, the latest 

14 schedule you publish isj you hope to have a final rule 

15 in September, which is multiple months from what you 

16 just said a few weeks ago. That, therefore, if we did 

17 a two tier standard, effectively the second tier 

18 wouldn't go into effect until 2009, assuming you were 

19 meet your schedule. And that seems much too late, I 

20 think, basically, unless there are ways to narrow it 

21 down, the schedule from our point of view. These 

22 delays that DOE have basically, in our opinion, ruled 

23 out that two tiered option. 

24 MS. NADER: Thank you. 

25 I am concerned about our time situation. 

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1 There is a lot of work yet to be done in this area. My 

2 question to you is whether we have burning issues that 

3 need to be covered right now? I see a couple of 

4 people, okay. Terry? 

5 MR. THIELE: Well, I guess my question, Terry 

6 Thiele, frigidaire, my question is what the Department 

7 expects to get out of the workshop. If you want to 

8 check the boxes on having covered so many topics, 

9 without necessarily getting a full discussion, then we 

10 can move on ahead. But, I suspect that a lot of the 

11 participants here, that these are material issues that 

12 if you want to bedding of the issue, we take the time 

13 to vent the issue . 

14 I just want to follow up though, a question 

15 to clarify. Did I understand ADL correctly to say that 

16 the scenarios that were being proposed here as 

17 strawmen, were based, were predicated upon manufacturer 

18 data? That that was the source for those numbers? 

19 MS. NADER: Name, please. 

20 MR. RIVEST: Mike Rivest, for ADL. 

21 What you said is sort of a broad statement. 

22 I am not sure I understand what you mean by scenarios, 

23 so let me 

24 MR. THIELE: Well, just to clarify. The three 

25 scenarios that the Department of Energy has proposed as 

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1 the final possible outcome of the rulemaking with 

2 percentages for different tiers. 

3 MR. RIVEST: My, that is just too general a 

4 statement to say that. All I wanted to say was that 

5 the data submittal, the cost data, and the energy 

6 efficiency numbers were based on the data submitted by 

7 manufacturers. To generate the scenarios, there is a 

8 whole slew of assumptions that have nothing to do with 

9 the manufacturer data submittal. 

10 MR. THIELE: Okay. That was the 

11 clarification I wanted. Thank you. 

12 MR. BERRINGER: Thank you. 

13 MS. NADER: Thank you. I saw another hand 

14 over here. 

15 MR. NEAL: This is Chad Neal from Staber 

16 Industries. 

17 We are just looking for a simple solution to 

18 an agreeable number for energy factors, so that the 

19 consumer can go into a store and they want to how 

20 energy efficient Washer A is verus Washer B, at doing a 

21 standard load of laundry. And we are just looking for, 

22 if the standard load is seven pounds as you test, 

23 simply count the gallons of water, how much energy it 

24 is to heat that hot water, and how much energy to 

25 washer's operating motor is using. And that is going 

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1 to be a number for every single washer. How energy 

2 efficient is it at doing an average test load? And 

3 that would be the most agreeable number that consumers 

4 could relate everything equally. 

5 MS. NADER: Okay. 

6 MR. JONES: Earl Jones. 

7 The only problem with the request for 

8 simplicity, is this is a regulatory proceeding. And 

9 that is something of an oxymoron, I guess. 

10 It maybe worth commenting that fortunately or 

11 unfortunately, the way this is, these machines are 

12 going to valued is based on a test procedure, which has 

13 already have been determined. And that is a whole 

14 different can of worms. And I don't know whether or 

15 not you are going to get a lot of support for going 

16 back to that one. So, I just mention that factor here. 

17 MS. NADER: Gentleman at the mike? 

18 MR. GREGG: Tony Gregg, City of Austin. 

19 I just want to bring up the issue of the 

20 water factor analysis, I guess we are going to talk 

21 about that more later, but I think that needs to be one 

22 of the factors considered in part of the labeling 

23 requirements, because consumers are more in tune with 

24 how many gallons of water a machine uses than how many 

25 kilowatts or whatever it uses. So, that needs to be 

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1 part of the analysis. 

2 Secondly, as far as the scenarios, certainly 

3 we would support a more stringent standard and earlier 

4 date rather than drawing it out for eight more years, 

5 when we are many years pass when the rule should have 

6 been adopted already. 

7 At third thing is sort of, you know, 

8 if this process gets dragged out indefinitely, you 

9 know, there is still possibilities that some of the 

10 states might consider their own independent standards. 

11 So, I think it would behoove us all to get a 

12 national standard and get it at an earlier date. 

13 MS. NADER: Thank you . 

14 MR. JONES: Earl Jones. Is that a sentiment 

15 of what Texas might do? Well, I understand there are 

16 some impediments that, not the least of which are just 

17 plain old politics, at least in Texas. 

18 You know, Bryan, I will just one observation, 

19 again, I am not sure what your purpose was in putting 

20 these out, but it seems to me that one benefit that 

21 they might serve is at least in providing some, I 

22 guess, worse case, best case, depending upon your point 

23 of view. 

24 MR. BERRINGER: Right . 

25 MR. JONES: As the proceeding goes on. But, 

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1 it seems to me that it is going to take a lot of work 

2 in this rulemaking to get to the point of making, 

3 providing support, if you will, for anyone of these 

4 solutions and that certainly is going to be true for, I 

5 guess, what is the third scenario, if I am looking at 

6 that right, the so called two phase approach. 

7 I did want to have a question for the follow 

8 up on Steve Nadel's and that was, you may not have 

9 looked, Gene, at the question of whether they had to be 

10 five years. Have you looked at whether it can be a two 

11 staged period with any kind of a lag between the two? 

12 MR. NADEL: Isn't that, to you asking as far 

13 as legally . 

14 MR. JONES: Yes. 

15 MR. NADEL: And I think with refrigerators as 

16 an example of the phase in, that a similar situation. 

17 MS. NADER: Eugene Margolis for the record. 

18 MR. MARGOLIS: I think refrigerators was the 

19 three years, but I don't recall. We have not discussed 

20 how many years we would consider whether it be, say a 

21 lenient standard first and then go three, four or five 

22 years for a more stringent standard. There has been no 

23 discussion. 

24 MR. JONES: So, there is no, I guess, can I 

25 assume that since the Department put out that as a 

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1 possibility, that the Department has determined that 

2 that approach would be lawful? 

3 MR. 'MARGOLIS: Yes. 

4 MR. JONES: Okay. 

5 MS. NADER: Thank you. 

6 Other burning comments? Yes? 

7 MR. BEST: Richard Best, Whirlpool. 

8 Just to comment on some of the issues here 

9 brought up in the last few minutes and particularly 

10 relating to the MEF values and the generation of 

11 databases for that. Several people commented it would 

12 really be great if the manufacturers would just supply 

13 these numbers. I would say from Whirlpool's view 

14 point, we would not be in favor of that for a variety 

15 of reasons. But, one in particular is the MEF numbers 

16 that DOE, themselves, have generated through, you know, 

17 contractors and such, do not seem to hold a lot of 

18 credibility within this group. I am not sure coming 

19 from five or ten manufacturers that the data would be 

20 anymore credible. And particularly, with a standard 

21 that none of us have, have a lot of experience with 

22 other than a few trials and submitting sample database 

23 here or there. 

24 And the other side pf it is basically it is a 

25 real question of if we did that, where would all this 

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1 data end up and what would it ultimately be used for 

2 once it is published, model by model for everybody? 

3 You know, and I guess lastly is we just have 

4 better ways to use our resources at this time. And I 

5 would suggest if somebody really thinks they want to 

6 know the answer, they can go out and spend their money 

7 and do it. 

8 MS. NADER: Thank you. 

9 Anyone else? 

10 (Pause.) 

11 MS. NADER: Yes. 

12 MR. MARTIN: Michael Martin. 

13 I would like to have a clarification of that, 

14 you mean to say you haven't tested these things 

15 yourself. You couldn't be saying that. 

16 MR. BEST: I am saying that. In fact, we are 

17 not going out and pulling our models into our labs and 

18 running all these tests and generating databases of 

19 that nature. 

20 We have some general ideas as to where our 

21 products fall and such and were our competitors fall. 

22 But, certainly we are not spending a lot of time to get 

23 an accurate number that would be published and put out 

24 for everyone to scrutinize and compare with . 

25 MR. MARTIN: So, I guess I am kind of lost 

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1 here, because I shouldn't be lumping you and G.E. 

2 together here. But, as I listen to this, I hear, 

3 saying that DOE's stuff is all wrong. And you saying 

4 we don't know what the answers are. If you don't know 

5 what the answers are, you can't tell me that Bryan is 

6 all wet. 

7 MS. NADER: Richard Best for the record. 

8 MR. BEST: Yes, what we are hearing here is 

9 that there are several people in the room here that are 

10 questioning the accuracy and you know, how great and 

11 good this database is. 

12 MR. MARTIN: Yes. And seems like 

13 Whirlpool 

14 MR. BEST: And at the same time asking us, 

15 well, why don't we supply the data. 

16 MR. MARTIN: Yes. 

17 MR. BEST: The lab that tested that is 

18 probably similar in qualifications to the labs that 

19 many of the manufacturers have. Why would we be even 

20 more credible when all we give you is a sheet of 

21 numbers, and you say, but I need to know exactly how 

22 you got the numbers. We got them by the test 

23 procedure. They got theirs by the test procedure. I 

24 don't see the value added in us spending a lot of our 

25 resources to generate it. It is not really relevant 

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1 here model by model. 

2 MS. NADER: Okay. One more question or 

3 comment and then we have go to break. Eugene? 

4 MR. MARGOLIS: Eugene Margolis, DOE. 

5 This is response to the City of Austin, which 

6 said that they would then, if DOE is still not issuing 

7 standards that the City of Austin may in its wisdom 

8 issue a standard. I would just like to recall to them 

9 that there is the issue of preexemption. And we can, 

10 we in DOE consider that the field is preexempted. 

11 Congress did preexempt this field. 

12 MS. NADER: Okay. Michael? 

13 MR. MARTIN: Yes, I, the similar discussions 

14 are being going on in a lot of states, not just Texas. 

15 And not talking about the city. But, our understanding 

16 of the Act, is that not only is the preexemption, but 

17 there is a means of petitioning for exemption from 

18 preexemption. And that, in fact, when you have no 

19 standard standards, we did petition for exemption from 

20 preexemption and so, it is tedious. We are 

21 preexempted, but there is a way out also. 

22 MR. MARGOLIS: You can petition us for an 

23 exemption from preexemption. That procedure is not the 

24 same procedure that was initially. And the original 

25 procedure was, you might say a straight forward 

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1 procedure and now in reading the language of Section 

2 327, it is much more difficult for the petitioner to 

3 show enough that he could win his case. 

4 MR. MARTIN: We agree with that. 

5 MR. MARGOLIS: And that is the reason I assume 

6 no one has petitioned DOE for an exemption. 

7 MS. NADER: Okay. I see two hands. Steve, 

8 you go first, then you and then --

9 MR. BERRINGER: We have one other. 

10 MS. NADER: And one other. All right, those 

11 three and then we go to break. Thank you. 

12 MR. ROSENSTOCK: Steve Rosenstock, EEI. 

13 And I think if Mr. Margolis is making the 

14 decision, then you might as well save the paper right 

15 now. 

16 MR. MARTIN: I have been working with Mr. 

17 Margolis since the mid'70s. 

18 MS. NADER: Yes. 

19 MR. STEVENS: Charlie Stevens from Oregon. 

20 I just wanted to point out to Gene that as, 

21 it may be a tough case but as each year passing without 

22 a standard, I think it gets a little easier to make the 

23 case. 

24 MS. NADER: Thank you . 

25 MR. MARTIN: We would hope then someone would 

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1 petition DOE. 

2 MS. NADER: Thank you. Okay, gentleman at the 

3 mike. 

4 MR. POPE: Ted Pope, Pacific Gas and 

5 Electric. 

6 Just a clarification for my benefit from DOE, 

7 what was the reason that a normal proposal, one of the 

8 three that I would have expected, which is a something, 

9 I don't know, it is 40 or 45 percent, but the 

10 economically justified standard, you know, within three 

11 years of promulgation, why wasn't that one of the 

12 primary options? Does that make sense? 

13 MR. BERRINGER: I think your question is that 

14 is the first option as soon as, if the rule went into 

15 effect. I think that is sort of the first scenario, 

16 would be three years after the rule went in place, you 

17 look at 2000, 2002, and then it would get in effect in 

18 2005. So, I think that is sort of the first option. 

19 MR. POPE: Except for you have, what to me 

20 looks like a weaker than expected standard. It looks 

21 like it is less than what is economically justified 

22 based on my perusal of the documentation. 

23 MR. JONES: Earl Jones, G.E. 

24 Well, again, that raises the other question, 

25 which Steven mentioned before and again, the one we 

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1 will be getting to this afternoon and that is the, that 

2 is the cost assumptions behind these numbers, which 

3 presumably justify these very stringent standards. It 

4 is far from clear that these levels are justified, 

5 based a real look at the cost and what the projected 

6 savings actually are, or would be. That is, I think, 

7 another issue in which this rulemaking very likely 

8 could fall apart. 

9 MS. NADER: Thank you. 

10 MR. RIVEST: I don't want to speak for my job, 

11 but all the economic analysis has not been done. The 

12 part which is the economic analysis on manufacturers is 

13 not in the record yet. So, it is an incomplete record . 

14 MS. NADER: Thank you. We are overdue for a 

15 break. It is 10 minutes to 11, please take your break 

16 and come back promptly at five after 11. 

17 (Whereupon, a short recess was taken.) 

18 MS. NADER: All right. Let's begin. 

19 MR. BERRINGER: We want to try and finish up 

20 some of these topics. Some of the information like 

21 quality of data, the MAISY and data access, we can 

22 probably cover in this afternoon's presentations. Get 

23 into that. 

24 We do have a few odds and ends that just sort 

25 of fall into the life cycle cost area, the warranty, 

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1 repair warranty cost. I know that was one of your 

2 things, comments, Glenn. At this point we do not have 

3 any data showing that there is a difference between 

4 warranty cost versus energy efficiency. Does anybody 

5 have or know of any type of information that would be 

6 available. I think last workshop, I think it was 

7 possibly G.E., I am not sure, if they had any 

8 information on warranty cost, any type of information 

9 like that. 

10 MR. JONES: We will be following that with our 

11 comments. 

12 MR. BERRINGER: Okay. 

13 MS. NADER: That was Earl Jones, G.E . 

14 Okay, yes, sir? 

15 MR. SCHEEDE: Glenn Scheede again. 

16 MS. NADER: Is that mike on? 

17 MR. SCHEEDE: Does that work better? 

18 MS. NADER: Thank you. 

19 MR. SCHEEDE: I did hear from, I believe it 

20 was AHAM, indicated that there is a trade association 

21 with plans retailers perhaps that might have 

22 information on extended warranty and such agreements. 

23 But, the other point I would like to make 

24 is that the burden should not be on interested parties 

25 in this proceeding, such as consumers to produce the 

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1 data. The burden should be on the Department of Energy 

2 to find the information. You are the ones that are 

3 operating with our tax dollars, and it is your 

4 responsibility to compile, to come up with the data, 

5 not mine. 

6 MS. NADER: Thank you. 

7 MR. BERRINGER: Okay. We have a couple of 

8 topics in the life cycle cost. Also, the life of the 

9 appliance used in the LCC. And was this another one? 

10 To my knowledge there wasn't, I hadn't seen any 

11 comments before as far a the life of the appliance. 

12 MS. NADER: Glenn Scheede. 

13 MR. SCHEEDE: You have -- Glenn Scheede again . 

14 You have my comments that I believe you are 

15 substantially overstating the real useful life of 

16 appliance to the individual, to the initial purchaser 

17 of that appliance. However, I thought you were going 

18 to go into that in more detail with the life cycle 

19 costs discussion this afternoon. 

20 MR. BERRINGER: Well, do not have life cycle 

21 costs on the agenda. I mean, it was presented at the 

22 March workshop. 

23 MR. SCHEEDE: Well, you have my comments. I 

24 noticed you narred them in the Federal Register notice, 

25 but you do have them. They are on the record, I 

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1 believe, that I believe you are overstating the life of 

2 the appliance and that you should be using information 

3 on the time that the purchaser of that appliance is 

4 likely to be using it, not what it might be on a 

5 secondary market. 

6 MS. NADER: Thank you. 

7 MR. BERRINGER: Why don't we just, we will 

8 finish up this list. The AO 99 forecast analysis, I 

9 think we will be using that data. I think we are 

10 incorporating into it. 

11 MR. MCMAHON: We can discuss that in the --

12 MR. BERRINGER: Okay. All right. 

13 Quality data we can definitely address in 

14 the, excessive data when we get into the marginal 

15 energy rate, unless there are some specific, I mean, 

16 any other analysis, unless there are specific comments 

17 pertaining to analysis that has already been done. 

18 MS. NADER: Does anyone have anything on that? 

19 MR. BERRINGER: Okay. I know, Steve, this 

20 was your topic, Steve Nadel, you had talked about, I 

21 think relies, goes back to LCC and also, I think the 

22 next couple of things here. Savings for detergent as 

23 far as LCC. Do you have, again, I am sorry to ask for 

24 information, we don't have, we have information stating 

25 that there, you know, there is not, no change in 

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1 detergents. I mean, as far as what might be for the 

2 efficiency, for the high efficiency as far as offering 

3 the same sort of price range as far as detergents. Do 

4 you have or does anybody can suggest anything as far as 

5 how we want to use the detergents or how they might be 

6 used or your concern as far as do you feel there is a 

7 substantial difference in the price of detergents that 

8 would warrant, to be included in the analysis, I guess 

9 is my question? 

10 MR. NADEL: Steve Nadel, ACEEE. 

11 The point I was making was not is there a 

12 substantial difference in the relative cost of the 

13 detergents. The point I was making that a number of 

14 surveys seem to have found that when people purchase 

15 the high efficiency washers, basically the H Axis 

16 machines at this point in the surveys I have seen, some 

17 of them use the same amount of detergent. But, some of 

18 them use less detergent. And I believe in the Bern 

19 Study, and I believe, Charlie, correct me if I am 

20 wrong, that coming out of the Northwest there is some 

21 survey data indicating how, what proportion of 

22 consumers use less detergent and so on. 

23 Likewise, I don't know, Ed, has PG&E ever 

24 done a survey? 

25 MR. NADEL: Okay. So, basically I was 

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1 arguing that there are some objective data sources that 

2 DOE should use and that that is very important, you 

3 know. If Proctor and Gamble, so far from what I have 

4 seen, they have made statements that they don't think 

5 there are, if they have any specific data on actual 

6 consumers, I would be very interested in seeing that as 

7 well. But, DOE should collect the available data. 

8 They already have the Bern Study, I believe that the 

9 Northwest will be submitting data. Anybody who has 

10 data, they should submit it and DOE should look at the 

11 data that is submitted, not the opinions, but the data 

12 and based on that proceed. 

13 MR. BERRINGER: Okay. Thank you . 

14 MR. JONES: Earl Jones, G.E. 

15 And to the extent that indeed such data is 

16 made available, I would assume that the Department 

17 would look at exactly what the data was. I mean, my 

18 understanding, and those who know, I am sure will weigh 

19 in, that to the extent the consumers have "used less" 

20 detergent in these machine, it is because they haven't 

21 had the detergent formulated for those machines. And 

22 if they use conventional detergents in those machines, 

23 indeed, they have a disaster on their hands. So, they 

24 have learned to use less.- The manufacturers of both 

25 the machines and the detergent do not recommend any 

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1 smaller cost per dose, if you will, but we are 

2 recommending an equivalent dosage for those machines, 

3 for which will have these, the same cost. There is no 

4 evidence of any reduction in cost or consumer savings 

5 associated with changing detergents for these machines. 

6 And that is just the fact, not the -- The anecdotal 

7 information about what wrong detergent people are using 

8 is simply not relevant. 

9 MS. NADER: Thank you. At the mike? 

10 MR. LINARD: Jack Linard, Unilever-HEP. 

11 The Bern Kansas Study has been cited because 

12 on average the amount of detergent usage declined from 

13 Phase 1 to Phase 2. But, if you look at the data, 

14 Phase 1 was an uncontrolled study in which people used 

15 the detergent they were normally using. And in fact, 

16 dosages of up to one and a half to two cups were 

17 reported. That is quite a bit higher than the 

18 recommended dosage for almost any detergent these days. 

19 There are products still on the market, however, which 

20 have very high dosage recommendations. 

21 Phase 2 is a much more controlled study. Most 

22 of the people used one product and dosed it according 

23 to package instructions. In fact, if you look at the 

24 instances of under dosing from Phase 1 to Phase 2, it 

25 decreased I think fairly significantly. So, in fact, 

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1 people were actually dosing the recommended amount of 

2 the appropriate detergent for that machine. Yes, the 

3 average came down simply because we lost a lot of the 

4 people dosing or really overdosing the products. 

5 Earl is exactly correct when he talks about 

6 you have to make sure what your study, your consumer 

7 survey is reporting on. If people, in fact, do use 

8 detergents which are higher foaming then the machine 

9 can actually tolerate, you actually have to cut the 

10 dose to make it work right. But, what we need is 

11 information regarding what happens if you dose the 

12 amount of detergent of a detergent that is specifically 

13 formulated for that machine. And that is exactly what 

14 the Bern Kansas Study did. And in that regard, if you 

15 look at it, people dosed the right amount of detergent. 

16 There was very little overdosing. There was actually 

17 less under dosing. 

18 MS. NADER: Thank you. Other input? Yes? 

19 MR. NEAL: This is Chad Neal from Staber 

20 Industries. 

21 With our current machine with standard 

22 detergent we are saving the consumer on average 75 

23 percent using only a maximum of an ounce, on average. 

24 And therefore, since that is a cost of doing laundry, 

25 we are requesting that be included in the life cycle 

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1 cost, since it is a cost of doing laundry. 

2 MS. NADER: Thank you. Anyone else? 

3 MR. POPE: I have lost a train of what topic 

4 we were restricting ourselves to just now. But, I am 

5 wondering if there has peen some additional thought on 

6 the valuing the prolong life of clothing. You know, I 

7 haven't heard many people in this group argue that 

8 these more efficient washers tend to clean better and 

9 if so, aren't there significant, in fact, most 

10 significant impacts of these new washers is that the 

11 clothing last longer. 

12 MR. BERRINGER: Could you state your name, 

13 please? 

14 MR. POPE: Ted Pope, Pacific Gas and 

15 Electric. 

16 MR. BERRINGER: Thanks. 

17 MS. NADER: Thank you. Do you have. what you 

18 need on the subject? 

19 MR. BERRINGER: I think we have one more. 

20 MS. NADER: Yes, sir? 

21 MR. LINARD: Jack Linard, again, Unilever. 

22 With regard to reducing the level of a high 

23 sudsing detergent, yet, we know you have to do that in 

24 order to keep the suds profile down, but we have done 

25 quite a number of studies which show that your 

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1 potential performance is considerably lowered when you 

2 cut the level of detergent beyond that which we 

3 recommend. And I think other people in the past 

4 workshop in March have stated the same thing, too. So, 

5 yeah, if you do use less your performance is going to 

6 go down. That is the bottom line. 

7 MS. NADER: Thank you. Okay. Shall we move on 

8 to -- Is there one more? 

9 MR. ECKMAN: I don't whether analytically 

10 performance --

11 MS. NADER: Name, please. 

12 MR. ECKMAN: Tom Eckman, Northwest Power 

13 Planning Council . 

14 I don't know whether analytically performance 

15 goes down based on soil chemistry in the clothes, but 

16 from the perspective of the consumer acceptance. The 

17 wash wise consumer satisfaction survey clearly 

18 indicated that even with less detergent use, the 

19 consumers thought that their clothes, thought, 

20 perceived, that their clothes were as clean if not 

21 cleaner than they had before. So, the analytics versus 

22 consumer acceptance question is probably best dealt 

23 with consumer surveys this afternoon, but I don't want 

24 to leave the impression that consumers are unsatisfied 

25 with H Axis machines that are being purchased. 

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1 MS. NADER: Thank you. Anyone else? 

2 MR. BERRINGER: Okay. 

3 MS. NADER: All right. Shall we talk about the 

4 cost of units? 

5 MR. BERRINGER: I think was again, Steve, I 

6 think you had, I think it comes back to you, you still 

7 had a question as far as the difference between the 40 

8 and 45 percent levels as far as the data was concerned. 

9 MR. NADEL: Yes, we had some concerns about 

10 the cost estimates that came to from the data for the 

11 40 and 45 percent. In the previous workshop, we were 

12 told, well, yes, we will be doing some additional 

13 checking on that and particularly the reverse 

14 engineering that provides some useful information. I 

15 believe there is a presentation on that a little later 

16 today. 

17 MR. BERRINGER: Yes. 

18 MR. NADEL: It would be fine to postpone this 

19 discussion until then, hopefully that analysis will 

20 help answer these questions. 

21 MR. BERRINGER: Okay. Thank you. We will 

22 make sure we address that. We will leave these on the 

23 list if we don't, on the board. 

24 Retail markup, I think, was also yours, 

25 Steve. It had to do with, you had a question about 

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1 where, how it was derived. It was also presented at 

2 the last workshop, so I think we should probably --

3 MR. NADEL: Again 

4 MS. NADER: Steve Nadel. 

5 MR. NADEL: Steve Nadel, ACEEE, again. 

6 At the last workshop, there was a statement 

7 on the record from Circuit City regarding what they 

8 perceived to be the typical markups in the industry 

9 which were lower the values -by DOE. We note that in 

10 the NOPR DOE, interpreted those in terms of gross 

11 markup versus net markup, but still came up with a 33 

12 percent markup based on the Circuit City and other 

13 publicly available data, not the 40 percent markup that 

14 DOE used. So, I guess I have a question about given 

15 that latest analysis, which shows a 33 percent markup 

16 makes sense, what is the rationale for 40 percent 

17 markup? But, the other thing is, again, it is as .per 

18 the, request for additional information this issue. 

19 MS. NADER: Do we have any information on that 

20 subject? 

21 MR. RIVEST: What I can add, Steve, is the 

22 data sources that were used in that previous analysis, 

23 I believe, an additional year's data is available now. 

24 And I will make sure that that is incorporated in our 

25 thinking here. That that includes consumer expenditure 

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1 surveys, and current industrial reports, published 

2 government sources . 

3 MS. NADER: Thank you. 

4 MR. BERRINGER: Okay. We have rebates, I 

5 guess was added on to the other thing. And that may be 

6 something we can discuss this afternoon when we talk 

7 about the utility analysis. 

8 Is there anything else that we have missed, 

9 that we feel need to discuss now? 

10 Steve? 

11 MR. ROSENSTOCK: Steve Rosenstock, EEI. 

12 There was one thing about shipments, was that 

13 on the list, I am not sure which list we were working 

14 on. 

15 MR. BERRINGER: Yes, shipments will be 

16 discussed later this afternoon. But, if you have 

17 specific question, then we can go ahead. 

18 MR. ROSENSTOCK: Oh, okay. I didn't know if 

19 it was this morning or this afternoon. So, okay. Then 

20 I will wait until this afternoon. 

21 MR. BERRINGER: Okay. 

22 MS. NADER: Okay. At the mike? 

23 MR. MODTLAND: Dave Modtland for Frigidaire 

24 Home Products . 

25 Just a clarification on this last discussion 

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1 on detergent usage. I think all the Bern studies and 

2 the other Washwise and other studies, when they are 

3 talking about high efficiencies, those were all 

4 relating to horizontal axis, where we were trying to 

5 prevent that separation. So, I don't know if you can 

6 apply some of the same things to high efficiency 

7 products. 

8 MS. NADER: Thank you. Anything more? 

9 MR. BERRINGER: Any additional comments or 

10 concerns? 

11 Okay, well, if we have time, at the end of 

12 the, near the end, we can come back and address or if 

13 there is anything on the parking lot we want to come 

14 back and look at this afternoon. 

15 At this time, we about back on schedule here. 

16 First, Steve Mariano, Arthur B. Little to talk about 

17 the reverse engineering. 

18 (Pause.) 

19 PRESENTATION BY STEVE MARIANO: 

20 MR. MARIANO: Okay. Can everybody hear okay? 

21 Is that all right? 

22 My name is Steve Mariano. Thank you, Bryan, 

23 for introducing me. I am going to talk today about our 

24 manufacturing cost analysis, specifically our Phase 2, 

25 which was to look at differential cost for higher 

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1 efficiency designs. 

2 I have already presented in the past our 

3 Phase 1 which was our baseline cost analysis. I am 

4 going to just touch on the objectives of what we were 

5 doing in Phase 1, also recover some of our assumptions, 

6 just to make sure that we have got a good picture of 

7 where we are with Phase 2. 

8 Phase 1, primarily we look at high volume, 

9 high sales volume, vertical axis washer, currently 

10 available today. We actually looked at two units and 

11 aggregated that data and created a baseline full 

12 production costs for that technology or that currently 

13 available system. And the purpose of doing that was 

14 primarily so that we could then make comparisons using 

15 in our Phase 2 the Whirlpool prototype design that has 

16 been in question as well as some commercially available 

17 H Axis designs. 

18 So, the Phase 1 was to key in establishing 

19 the methodology and how we were going to go about the 

20 analysis as well as generating a differential cost. If 

21 we were to just to an analysis of a higher efficiency 

22 designs, the Phase 2, without having that baseline, we 

23 wouldn't really be comparing apples to apples. We 

24 would be making comparisons to data that may have been 

25 collected differently, may have been generated 

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1 differently, and had different assumptions. So, that 

2 was the main reason for doing a Phase 1 and reviewing 

3 that first. 

4 As I have stated already, the Phase 2 

5 objectives here were to evaluate the prototype 

6 Whirlpool vertical axis, higher efficiency design. One 

7 of the key aspects of this was to maintain 

8 confidentiality of data. And that is why we are going 

9 to be presenting a lot of the results as differentials, 

10 presenting ranges of data, as well as presenting 

11 percentage differences. And that is to keep that 

12 confidentiality and not to present absolute numbers. 

13 And also one of the main objectives is to 

14 obtain comment from the stakeholders relative to this 

15 analysis. 

16 Actually this work has been, we did a lot of 

17 actual physical tear down and analysis back in late 

18 spring, early summer and our analysis has been 

19 essentially complete. We have done some minor 

20 refinements, but the information you have in your 

21 packets today is our completed analysis at this point. 

22 We did two vertical axis machines. And that 

23 is typically the description we used of how we would 

24 characterize those. We also looked at two H Axis 

25 designs that were commercially available. We actually 

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1 purchased units on the market. And then, finally, the 

2 Whirlpool prototype design was provided to us. We had 

3 access to that by Whirlpool. 

4 To reiterate our manufacturing facility 

5 assumptions, we have taken a typical practices plant. 

6 We did visit and talk with all of the manufacturers. 

7 We have reviewed some of this information in Phase 1. 

8 Typically, we looked at, well, one and a half million 

9 units a year and now there are manufacturers that are 

10 more or less. But, we use this as a our baseline. 

11 Again, we are making comparisons of Phase 1 to Phase 2, 

12 so we are keeping the manufacturing facility 

13 assumptions the same. And that is why we did it this 

14 way. 

15 Again, you can see some of those are 

16 Greenfield Investments, so it is complete investment to 

17 manufacture these units and not a differential 

18 investment. It would be a differential from a complete 

19 investment for vertical axis versus a complete 

20 investment for some higher efficiency design. 

21 Again, to reiterate some of our assumptions. 

22 We are looking at full production costs in this 

23 analysis. We have not considered SG&A, the cost 

24 associated with R&D or interest payments that you might 

.25 be making. And there is a lot of variability in that 

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1 from manufacturer to manufacturer. What we focused on 

2 was just production costs, which would include direct 

3 labor and materials, as well as factory overhead. 

4 Overhead associated with operation of a facility or 

5 plant. 

6 Again, just to show you some of the 

7 assumptions we used, again, these are the same 

8 assumptions we have used in Phase 1, so we have carried 

9 these forward into Phase 2, again, to make an apples to 

10 apples comparison. 

11 We presented the data here in a fashion that 

12 allows, again, the confidentiality of data. What we 

13 have done is generated a cost range for these designs . 

14 The range has been generated using our Monte Carlo 

15 simulations as we did in Phase 1. Using those 

16 parameters that I outlined and I will show you some of 

17 those again here, just to reiterate what those were. 

18 But, we generated a cost range. And as you can see the 

19 vertical prototype is well within the range of the 

20 current H Axis units that we looked at. 

21 These were the key parameters that we used in 

22 the Monte Carlo simulations. Basically, what we have 

23 done here is made some variations along labor rate, 

24 plan output, the depreciation life on equipment, 

25 investment. And so you can see those parameters, that 

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1 is describes the probability distribution. I will show 

2 you what those mean as well as the range that we used 

3 and if, for triangle distributions, the most likely 

4 value. So, this was sort of the basis of our 

5 simulation to cre~te that range. And this corresponds 

6 to our Phase 1 analysis, which we did as well on these 

7 same parameters. 

8 Just to explain what those distributions are. 

9 Using a uniform distribution, what we are saying there 

10 is that the probability that the, in this case, the 

11 labor rate is between 17 and 28 dollars is equal. That 

12 it could be anywhere between there. We actually in the 

13 baseline used $24.00, but we are saying that it could 

14 be anywhere in that range. While triangle 

15 distribution, we are using a most likely value, and 

16 then a range around that. And what that says is the 

17 most likely value is a high probability that that is 

18 the number that is most likely. And that that overall 

19 range is possible. 

20 To give you some more information on our 

21 analysis, rather than just give you a number, I wanted 

22 to try to explain what was driving some of those costs, 

23 that differential costs. And I am going to give you 

24 some information here, mostly on a percentage basis. 

25 Again, to protect the individual manufacturers. We 

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1 have also aggregated the H Axis designs as we had done 

2 before. We have costed those individually, but then by 

3 using the Monte Carlo simulation, and taking averages, 

4 we have aggregated those together. And so, we are 

5 going to show you that here. 

6 As you can see here, one of the major 

7 differentiaters or cost drivers in the higher 

8 efficiency designs, is the sophisticated controls they 

9 use. And you can see that their cost grows as an 

10 overall percentage of the total cost to that product. 

11 In some cases, nearly double the percentage in the 

12 vertical axis baseline units that we looked at in Phase 

13 1 . 

14 We also generated investment estimates for 

15 these designs. I think the major thing to see here is 

16 that they are all within the same range. Again, I 

17 remind you that this is a Greenfield investment, so it 

18 is not the cost to change over a factory, but it is a 

19 cost to build a factory from scratch, basically. And 

20 you can see that they fall within the same range for 

21 those two, well, actually for the, all three of the 

22 different design concepts. 

23 Now to spite those falling in the same range, 

24 I am not saying that they are the same, and that the 

25 investment is the same. Our analysis is to show the 

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1 investment shifts into different types of manufacturing 

2 processes. For the V axis, there is a large of 

3 percentage of the manufacturing was machine components, 

4 while in the aggregated H axis and V axis prototypes, 

5 that shift has changed. There is less machining 

6 operations but there is more either injection molding 

7 in one case or more stamping and bending operations in 

8 the other. So, really you have just shift in the 

9 manufacturing processes for each of those designs. 

10 And actually that is evidenced in the average 

11 depreciation life as well, where they have gone up for 

12 H Axis and the vertical axis prototype. And that is 

13 primarily because the injection molding and stamping 

14 equipment is of longer life. Now, our average 

15 depreciation life is based on both the tax life of 

16 equipment as well as its useful life. We factored both 

17 of those in. 

18 For more information on sort of a percentage 

19 basis, this shows the percentage breakdown of 

20 materials, direct labor and overhead. It shows for 

21 baseline vertical axis, we are looking at about 60 

22 percent of the cost is in materials, that is 60 percent 

23 of the full production cost. While in the higher 

24 efficiency, it averages more like 75 percent. So it is 

25 a larger percentage of the cost. So, it is not only 

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1 that the unit is more expensive, the materials are also 

2 encompassing a greater percentage. And materials 

3 include both raw materials as well as purchased 

4 components. 

5 With regard to overhead, we saw that the 

6 average of the higher efficiency designs is a similar 

7 overhead structure as the baseline vertical axis 

8 washers. Which would follow from the manufacturing 

9 processes and operations and plant assumptions that we 

10 have made. It shouldn't change very much. 

11 So, in summary, our Phase 2 results, we 

12 looked at three, three units, two H axis, commercially 

13 available machines, as well as the Whirlpool prototype . 

14 We did a complete tear down of those and generated 

15 manufacturing of full production costs, using the same 

16 methodology we did in Phase 1 and the same assumptions 

17 that we have used in Phase 1 for manufacturing 

18 processes, materials, etc. And then generated that 

19 differential cost. And as I presented in the range, if 

20 you looked at all of these high efficiency designs, 

21 they average from $75.00 to 190.00, using our Monte 

22 Carlo simulation. And that would be the differential 

23 cost that we estimated. 

24 Obviously, that cost is driven by product 

25 features, and performance and not strictly by 

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1 efficiency. I wanted to iterate that what we have done 

2 is taken actual units, actual product. We have not 

3 tried to design a higher efficiency unit. Have not 

4 made any assumptions about what could be or can't be 

5 removed from a product to defeature it. We have taken 

6 exactly what exists today, and generated our cost 

7 analysis around that, our differential cost. 

8 So, if there is any questions, I will be 

9 happy to answer those. 

10 MR. BERRINGER: Questions? 

11 MS. NADER: Yes? 

12 MR. MORRIS: Wayne Morris with AHAM. 

13 I would just like to go back, if I could, 

14 Steve, to chart number 8 or page 8, I think. It is the 

15 bar graph of the, it is titled "Differential 

16 Manufacturing Cost Estimates, the V-axis prototype 

17 differential cost is well within the range of the H 

18 axis designs. It looks like this one, if you are 

19 looking for it. You have got it, okay, yes. 

20 The title says that these are differential 

21 cost, but the V axis prototype, is that a differential 

22 cost or is that the absolute cost? 

23 MR. MARIANO: No, that is a differential cost 

24 over our Phase 1 baseline, aggregated baseline. 

25 MR. MORRIS: Okay . 

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1 MS. NADER: Other questions? Yes. 

2 MR. GOLDSTEIN: In doing this analysis of the 

3 Whirlpool design, tell me if I am correct in assuming 

4 that you had a chance to look at the product, but you 

5 did not have a chance to look at the manufacturing 

6 facility that Whirlpool was using to produce this? 

7 MR. MARIANO: In our Phase 1 analysis, we have 

8 actually visited all of the major manufacturers, five 

9 to be exact. And reviewed their manufacturing 

10 operations and discussed manufacturing processes that 

11 are typically used in their plants. Then what we had 

12 done is, for the vertical axis prototype, the Whirlpool· 

13 prototype, we actually reviewed a prototype product, 

14 did tear down and built cost estimates based on actual, 

15 on that actual product, with the assumption that it 

16 would be built in this Greenfield site that would use 

17 similar manufacturing processes as is currently 

18 available in the industry. 

19 MR. GOLDSTEIN: Okay. But, you had no 

20 information on what manufacturing process or equipment 

21 they might have used to give you that prototype, is 

22 that correct? 

23 MR. MARIANO: Well, what we have done is we 

24 have looked at manufacturing processes that would be 

25 typical and would be needed to make those components 

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1 and high volume. And that is the assumptions we used. 

2 MR. GOLDSTEIN: Okay. But, based on your 

3 judgement, not based on what they have done. 

4 MR. MARIANO: We did not base it on what they 

5 actually, how they actually made the part. No, we 

6 based it on how you would actually make it in 

7 production. 

8 MS. NADER: Other questions? 

9 MR. NADEL: I have three questions. First, 

10 with this graph here. You show ranges, when you do a 

11 sample of a thousand you are going to get some real 

12 extreme values. You are going to get a real tendency 

13 toward the mean. Does this show the full extremes or 

14 is there some confidence, the 95 percent confidence, 

15 and you eliminated the five percent. I am just trying 

16 to characterize this distribution. 

17 MR. MARIANO: Yes, no, we actually took, 

18 typically the simulations we ran, there are some 

19 outliers, but they would in the neighborhood of less 

20 than one percent. Those were eliminated, so this does 

21 represent a full range of cost that you would see. 

22 MR. NADEL: But, am I correct in assuming that 

23 the values at the extreme top and bottom of each range 

24 are much less likely than the values toward to the 

25 middle of the range? 

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1 MR. MARIANO: Yes, I would, and I can show 

2 you, in our Phase 1 analysis, the typical simulations 

3 we ran, yes, you are getting somewhat of a bell shaped 

4 curve. There isn't any sort of strange things going on 

5 at the ends. I will say that the range in the H axis 

6 is really an overlap of two simulations. And so, if 

7 you were to take sort of right in the middle of that, 

8 it may be sort of two peaks in that range rather than 

9 one single peak. 

10 MS. NADER: That question was from Steve 

11 Nadel, for the record. Other questions? 

12 MR. NADEL: I had three. 

13 MS. NADER: Oh, you had three . 

14 MR. NADEL: I had three questions. 

15 A second and this gets to the issue that we 

16 discussed briefly earlier, which is in part this 

17 analysis is designed to be a check on the data that was 

18 provided by AHAM. How would you characterize these 

19 models as percent savings relative to the baseline, 

20 just so we can, supposedly these are to be used, to 

21 correlate and to check them. 

22 MR. MARIANO: I am not sure I understand what 

23 you are asking. 

24 MR. RIVEST: I understand the question. 

25 Mike Rivest. Given the controversy and the 

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1 results of testing we have, I can't give you a definite 

2 answer. And the controversy places it well within the 

3 range where it wouldn't be meaningful to give you the 

4 numbers. In other words, is this a 40 or 45? Because 

5 I know that your concern is there. And I can't, we 

6 really couldn't answer that question right now. 

7 MR. GOLDSTEIN: Could you give us a range? 

8 MR. RIVEST: I think I just did in a way. 

9 MR. NADEL: Let me than ask 

10 MR. RIVEST: I mean, it could be 35 or 45, but 

11 it is, you know. 

12 MR. NADEL: What are DOE and AOL's plans for 

13 narrowing this down and allowing us to have this data 

14 as a comparison? What are you planning on doing? Are 

15 you just saying, well, gee, we can't do it, and 

16 therefore, there is no comparison? Or what are your 

17 specific plans for providing --

18 MR. RIVEST: I just, I do want to point out a 

19 difference here between this and the data that was 

20 submitted and make the statement that it is not, this 

21 is not exactly comparable data. In the data submittal 

22 you had manufacturers whose production, annual 

23 production is much lower tha~ 1.4 million. You also 

24 had one manufacturer, at ~east.one anyway, that had 

25 greater than that. So, I wouldn't anticipated that the 

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1 range of the data submittal from manufacturers would be 

2 greater than this. First caveat . 

3 Also, this based on a Greenfield site. Now, 

4 how one considers the interactions between existing 

5 assets. How much of those are transferable, how many 

6 of those are stranded, that will shift you, either one 

7 way or the other. I mean, if you are going to ·a 

8 technology that is very similar, that may help you. If 

9 you are going to a technology that is radically 

10 different, and you have recent investments and that the 

11 existing technology, then your differential would be 

12 greater. 

13 So, there is just a caveat there. Before you 

14 start preparing these as being one and the same. 

15 I think they are useful because, you know, 

16 they are useful and not being benchmarked. The 

17 inherent costliness of these designs. 

18 MS. NADER: Did that answer your question? 

19 MR. NADEL: Not fully. We can have some 

20 further discussions later and we can submit some 

21 comments. But, I think is very important that this 

22 whole process was based on collective data from AHAM, 

23 but then having some independent ways to check and 

24 verify those. And I hope DOE is going to continue to 

25 allow that to happen. To just say, well, gee, we can't 

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1 really do that, I think is setting a very bad 

2 precedent, particularly, or at least I interpret this 

3 data, it tends to support the comments that we have 

4 made, about the 45 percent cost are too high. We will 

5 provide comments to that effect. 

6 Final question. Your final conclusion talks 

7 about performance and features are driving cost. And 

8 you said, well, you haven't done any work to say, what 

9 features could be removed that do not affect 

10 efficiency? I was wondering how complicated would it 

11 be to try to do that type of an analysis because, 

12 again, getting back to the issue that we are trying to 

13 provide a check on the AHAM data, we want to, the AHAM 

14 data, as I understand it, is based, is estimates of how 

15 much it would cost to meet certain basic performance 

16 energy levels without lots of extra bells and whistles, 

17 to the extent these units have bells and whistles, that 

18 inflates the cost. So, I was wondering how complicated 

19 would it be for you to estimate a cost without bells 

20 and whistles? 

21 MR. MARIANO: I think the issue there is, 

22 these machines are, it is a system design. And so, 

23 there are constant tradeoffs that are being made. And 

24 if you wanted to take features out, there may be 

25 tradeoffs in performance, maintainability, reliability, 

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1 that I think are very difficult to undertake in a small 

2 paper analysis. What needs to be done is actual 

3 product needs to be built. It needs to be evaluated. 

4 If you were to say I want to replace a component with a 

5 less expensive one, that unit would have to be actually 

6 built or that component would have to be put into a 

7 unit and actually tested to see what the impact would 

8 be on performance. There would be assessments of its 

9 ieliability. In long term, will it last 10 or 12 or 13 

10 years without failing? Or is it going to fail in two? 

11 All of those issues, I think make it a very complicated 

12 thing to do. 

13 MS. NADER: Okay . The gentleman at the mike. 

14 MR. GREGG: Tony Gregg, from Austin. 

15 MS. NADER: Say your name again, I couldn't 

16 hear you. 

17 MR. GREGG: Tony Gregg. 

18 MS. NADER: Thank you. 

19 MR. GREGG: Along the same line. I guess we 

20 are not disclosing what machines were tested, is that 

21 true? 

22 MR. MARIANO: Yes. 

23 MR. GREGG: Can we make a big assumption about 

24 that or what? 

25 MR. MARIANO: Other then the Whirlpool 

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1 prototype. 

2 MR. GREGG: But, on the other two, the H axis 

3 ones, we don't know which those are? 

4 MR. MARIANO: Well, at this point I guess DOE 

5 has decided not to reveal that. 

6 MR. GREGG: Okay. 

7 MR. MARIANO: And the primary reason for us 

8 not doing that is to actually, we have actually torn 

9 down product and evaluated its cost and generated cost 

10 estimates for that product. 

11 MR. GREGG: Okay. 

12 MR. MARIANO: The issue was is providing that 

13 to the industry. I think there is some question of 

14 confidentiality of that information. It is not that 

15 anybody else couldn't do it. Somebody else could buy a 

16 machine. Manufacturers have data on their competitors, 

17 have done this, but it is being, actually providing 

18 that information to everyone is an issue. 

19 MR. GREGG: Okay. Related to that, though, 

20 were the H axis machines and this relates to the 

21 previous question, similar in feature to the vertical 

22 axis machines? Because, I mean, most of the H axis 

23 machines, I assume you tested, are basically fully 

24 featured models, with extra controls and stuff like 

25 that for all the different cycles. 

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1 MR. MARIANO: Yes. 

2 MR. GREGG: Was that an impact at all in the 

3 price differential? 

4 MR. MARIANO: Yes. 

5 MR. GREGG: Because they had more features 

6 than the vertical axis machine. 

7 MR. MARIANO: That is correct. The units that 

8 we evaluated were either commercially available or the 

9 Whirlpool prototype that had more product features than 

10 was sort of typically what you would expect in the 

11 standard washing machine or the baseline that we looked 

12 at. They definitely had more features than the 

13 baseline. The reason we did that is we couldn't create 

14 a unit. 

15 MR. GREGG: Right. 

16 MR. MARIANO: So, what we did was took units 

17 that were currently available, that were higher 

18 efficiency, they also had some additional features. 

19 MR. GREGG: And the answer is still the same, 

20 you can't determine what the difference between a unit 

21 without all of those features and one with all those 

22 features would be without reconstructing it or trying 

23 to modify it? 

24 

25 

MR. MARIANO: Right. In essence, if you are 

asking me to say can I create a defeatured version of 

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1 these, there is a considerable amount of effort and it 

2 is complicated. I can't say that the range of data 

3 that we have seen, say for the H axis, represents 

4 different features in the product. And different 

5 levels of features. And so, you can't say that that 

6 range can be somewhat attributed to features. 

7 MR. GREGG: Okay. And one final thing. Just 

8 in manufacturing in general, and this wasn't probably 

9 part of the, your analysis, but over time, as a new 

10 product such an H axis is introduced, wouldn't there be 

11 a declining cost in producing that product as the 

12 manufacturers found ways to produce a component 

13 cheaper, mass producing in larger quantities. And may 

14 also not be reflected in this analysis? 

15 MR. MARIANO: There is a element of that. Our 

16 approach was to look at high volume, standard 

17 manufacturing processes that are used today and scale, 

18 relatively relied scale. So, we did try to accommodate 

19 for that. In other words we weren't costing a low 

20 volume product in comparing it to a high volume 

21 vertical axis baseline. We were looking at high volume 

22 production of these. 

23 If you are asking can a manufacturer through 

24 a learning curve, in a product, reduce cost, yes, that 

25 is done and it is primarily driven though, through 

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1 design changes, lower cost design options and/or 

2 product of component developments that are really 

3 driving those things rather than efficiencies and 

4 manufacturing process. I would say that would have a 

5 less of an impact on these numbers. 

6 MR. GREGG: Okay. Thank you. 

7 MS. NADER: Steve? 

8 MR. ROSENSTOCK: Steve Rosenstock, Edison 

9 Electric Institute. 

10 But, it also seems based on your analysis 

11 that a key component is the sophisticated controls, is 

12 the primary, obviously is the primary reason for the 

13 incremental cost. So, those can't be defeatured 

14 without ruining the equipment. That is what it seems 

15 like, just kind of looking at the data that you have 

16 presented. I mean, it is the controls, and you need 

17 those controls for the higher efficiency. That is what 

18 it seems like. 

19 MR. MARIANO: I would, I can't really say that 

20 you need those controls for the higher efficiency. I 

21 know that you need those controls for this product to 

22 perform as it does. Whether those are controls 

23 specifically for efficiency, or whether they 

24 accommodate certain performance features that their 

25 customer looks for in that product, it is hard to 

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1 separate those. 

2 MR. ROSENSTOCK: Okay . 

3 MR. MARIANO: But, these products built the 

4 way they are, need those controls. 

5 MR. ROSENSTOCK: Okay. Steve Rosenstock. 

6 But, one of the end results of the more 

7 sophisticated controls is a higher efficiency. Would 

8 you accept that? 

9 MR. MARIANO: Yes. That is part of it. 

10 MR. ROSENSTOCK: Okay. 

11 MS. NADER: Other questions. 

12 MR. KESSLER: I have got a question. You did 

13 such a fine job on your earlier analysis, where you 

14 took the baseline vertical axis unit. 

15 MS. NADER: Excuse me, give us your name. 

16 MR. KESSLER: Alan Kessler, Amana. 

17 Broken down labor, overhead and material and 

18 the assumptions, and why aren't we doing that for these 

19 models that we know? 

20 MR. MARIANO: Primarily the main driver behind 

21 this is, well, one of the reasons we didn't want to, we 

22 couldn't go into as much detail, is because of the 

23 nature of these products. Primarily, the vertical axis 

24 prototype. Being able to do that made it very 

25 difficult for us to say, expose a lot of that 

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1 information about what components or sub assemblies 

2 were driving the cost. And so, in essence, if we 

3 couldn't do that for the vertical axis prototype, we 

4 felt that if we did for the H axis, you are not really 

5 getting a good comparison of those. And that is the 

6 reason we did the H axis, was to compare it to, to give 

7 you sort a comparison of this prototype. 

8 MS. NADER: Other questions? 

9 (Pause.) 

10 MS. NADER: No further questions? Thank you, 

11 Steve. 

12 Thank you, all of you for your hard work this 

13 morning. We will take an hour break. Does everyone 

14 know where to find lunch? Does anyone need information 

15 about where to get lunch? Okay. You are old hands at 

16 this. 

17 We will break now and please be back exactly 

18 at one. We have a full agenda this afternoon as well. 

19 Enjoy your lunch. 

20 (Whereupon, at 11:55 a.m., the meeting was 

21 recessed, to reconvene at 1:00 p.m., this same day, 

22 Tuesday, December 15, 1998.) 

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1 A F T E R N 0 0 N S E S S I 0 N 

2 (1:14 P.M.) 

3 MS. NADER: Thank you very much for your hard 

4 work this morning. You have all worked hard and well 

5 together. We are going to go ahead and start our 

6 presentations, even though there are a few people who 

7 haven't come back yet. 

8 Thanks very much to those of you who did come 

9 back on time. 

10 The first person who is going to make a 

11 presentation is Jim McMahon. Jim, are you ready? 

12 (Pause.) 

13 MS. NADER: Okay. Jim McMahon, Consumer 

14 Marginal Energy Rates. 

15 PRESENTATION BY JIM MCMAHON: 

16 MR. MCMAHON: Thank you, good afternoon. I am 

17 Jim McMahon from Lawrence Berkeley National Laboratory. 

18 I am going to give you a brief presentation on the 

19 methodology for consumer marginal energy rates. 

20 The first definitions, what are average and 

21 marginally rates? Average rates, average prices as 

22 used in the past, are the ratio of the total annual 

23 energy bill, by the total annual energy use. This can 

24 apply to whatever energy source, whether it is electric 

25 or gas, residential or commercial. Historically this 

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1 has been the data reported by utilities, that is total 

2 revenues received from residential customers, divided 

3 by electricity sales for residential customers, for 

4 example: 

5 Marginal prices on the other hand, are the 

6 change in the bill divided by the change in the energy 

7 consumption. 

8 Now, down at the bottom, point number three, 

9 the difference between marginal and average we are 

10 defining as epsilon. Some of the folks back at LBNL 

11 are using shorthand to use this as the percent 

12 difference between marginal and average price. It is 

13 just an easier way to think about it for those folks 

14 who are used to thinking about average prices. 

15 What is changing? Previously the consumer 

16 energy bill savings and we are now talking about the 

17 life cycle cost calculation, were estimated using 

18 average energy prices. For clothes washers, those were 

19 national average value, something like eight cents per 

20 kilowatt hour for electricity. 

21 The new approach is to estimate consumer 

22 marginal energy rates in calculating the energy bill 

23 savings. So, these are estimated by the household. 

24 The energy savings will be valued at the margin, not at 

25 the average. And it is important to know that when you 

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1 go to marginal rates, these are household specific. It 

2 depends upon the consumption of the household, and the 

3 specific tariff or rate structure that the household is 

4 facing. 

5 What is the methodology? We are going to 

6 obtain a database of individual customers or building, 

7 in fact, we have already done that. And I will tell 

8 you in a moment what the databases are. We are going 

9 to design a nationally represented sample of customers. 

10 I will tell you what I have said in the other workshops 

11 to date, we do not plan to simulate every house in the 

12 country. That would be practically impossible. But, 

13 we do intend to get a sample that does represent 

14 different regions, different types of household, 

15 different types of consumer demographics and behaviors, 

16 so that we can account for those differences. 

17 We have in mind something on the order of the 

18 size of the RECS sample, which is several thousand 

19 households and is a nationally represented sample. 

20 But, this will be a new sample. 

21 Third bullet, we are going to collect tariff 

22 information. By that I mean, we are going to gather 

23 information of the specific rates schedules that 

24 customers face in differept utilities around the 

25 country. That is already underway . 

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1 We are going to develop and test the method 

2 for matching the tariffs with the customers. There is 

3 no existing data set that has both a population of 

4 individual customers with their energy using 

5 characteristics and of the tariffs that they are 

6 paying. So, this is new work. 

7 Finally, we will calculate the marginal rates 

8 for the sample of buildings and use that sample of 

9 estimates of the total population for the country. 

10 Before I go on to the next slide, are there 

11 questions on the methodology at this point? 

12 MS. NADER: Name, please? 

13 MR. SCHEEDE: Glenn Scheede . 

14 Can you tell us, do I gather from this that 

15 you sort of dropped the RECS data from your new 

16 procedure now? Is RECS no longer in this, the EI RECS 

17 survey? 

18 MR. MCMAHON: Our plan right now is to in the 

19 future do less cost from a new national sample of 

20 buildings, not from the RECS and the reason for that is 

21 that the RECS households are not identified in fine of 

22 geographic detail for us to assign them to utilities 

23 and to rate schedules. It would be nice if we could 

24 simply assign marginal rates to the RECS households, 

25 but, there is no simple to do that. 

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1 As a caveat, some of the RECS surveys do have 

2 specific month by month utilities bills for the 

3 households. And we are looking at those to see if we 

4 can pull out of those some marginal rates. And then we 

5 would have the RECS sample as another national sample 

6 to look at. But, I am not sure whether that will be 

7 successful or not. 

8 MR. SCHEEDE: Okay. Could you tell us either 

9 now or whenever it is appropriate in your presentation 

10 of what information you are going to make available to 

11 interested parties, concerning all the databases you 

12 have got, including the commercial database that you 

13 are buying. And where do we get information to know 

14 whether that, whether those data are representative, 

15 valid and reliable? 

16 MR. MCMAHON: A couple of slides from now, I 

17 am going to list the databases. I will be happy to 

18 answer your questions about that. 

19 MR. SCHEEDE: Thank you. 

20 MR. ROSENSTOCK: Steve Rosenstock, Edison 

21 Electric Institute. 

22 Part of this also is that you, since for both 

23 gas and electricity on the commercial industrial side, 

24 that they might be, you know, choosing different 

25 suppliers for different terms for their generation or 

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1 production, depending on the fuel source for the 

2 portion of the bill. You are going to be, part of 

3 this effort is to get information from the customers, 

4 correct? Will some of the data be from the customers 

5 as well, just as a backup? 

6 MR. MCMAHON: In the long term, that is 

7 correct. And we have a couple of short term 

8 deliverables. Between now and February, which is when 

9 I promised to complete this work, we expect to get 

10 information from utilities. We do understand that with 

11 restructuring, there are other suppliers coming into 

12 the market. Right now there have small market share, 

13 but they are gaining. The intent is that in the long 

14 term, the Energy Information Administration surveys, 

15 both for residential and commercial, will gather price 

16 information or rather bill information directly from 

17 the individual customers, so that whoever their 

18 supplier is, whether it is a utility or someone else, 

19 we will have that information. 

20 MR. ROSENSTOCK: Steve Rosenstock. I think 

21 that is a good approach to use because of the fact 

22 that, you know, with multiple suppliers out there and 

23 especially different terms of contracts, that will be 

24 a very useful piece, data set to have . 

25 MS. NADER: Glenn? 

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1 MR. SCHEEDE: Glenn Scheede, again. 

2 Does this mean that DOE is committing to use 

3 marginal energy rates in the future steps in this 

4 rulemaking? I noticed in the ANOPR, they have not used 

5 marginal energy rates. Does this mean they will from 

6 now on? 

7 MR. MCMAHON: My understanding is that the 

8 Department intends to use marginal rates in the next 

9 round of life cycle cost. 

10 Bryan? 

11 MR. BERRINGER: That is correct, based on the 

12 Advisory Committee recommendations we will be using 

13 marginal energy rates . 

14 MR. BALDUCCI: Anthony Balducci with NEMA. 

15 Along those same lines with marginal rates, 

16 are they going to be used across all the rulemaking 

17 that is in process? Specifically, ballast. 

18 MS. NADER: Could you repeat the question, 

19 please? 

20 MR. BALDUCCI: For marginal energy rates, 

21 people have mentioned commercial as well as industrial 

22 and residential. I know this is only residential. Is 

23 DOE planning on using marginal energy rates for the 

24 other rulemakings, specifically the ballast rulemaking? 

25 MR. MARGOLIS: This is Eugene Margolis. We 

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1 are here on clothes washers. 

2 MR. BALDUCCI: I understand that, Gene. 

3 MR. MARGOLIS: And that is what --

4 MR. BALDUCCI: But, this is more 

5 MR. MARGOLIS: But, the answer was yes for 

6 clothes washers. When we go to another rulemaking, 

7 then we will talk about the products at that time. 

8 MR. BALDUCCI: Well, I am just, this is more 

9 of a general across the board thing. It is not product 

10 specific marginal energy rates. That is why I have 

11 that concern. I think the Department should be 

12 consistent in their approaches with each rulemaking. 

13 And that is my only comment . 

14 MR. MARGOLIS: Okay. Thank you for your 

15 comment. 

16 MR. MCMAHON: Okay. The next slide is how do 

17 we extract the consumer marginal energy rates. Each 

18 sample building has a baseline energy use and can be 

19 assigned a tariff. We will calculate monthly energy 

20 bills for each of these households. These are 

21 baseline, without new standards. Then calculate annual 

22 energy savings due to standards. Desegregate those 

23 annual savings across the month, this is going to be 

24 very important for some products more than others. At 

25 this point I don't know the extent to which there are 

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1 seasonality in clothes washer usage, but we intend to 

2 research that . 

3 Calculate the monthly energy bills for the 

4 sample, with standards, and have a parathetical here. 

5 We are aware that some customers have hourly time of 

6 use rates. It is a very small sample of the 

7 population, but there are some. In those cases, we 

8 will need to go to something more like hourly profiles 

9 of energy consumption. And we are planning to do that 

10 where necessary. 

11 Finally, we will use the sample marginal 

12 rates as estimates of the national marginal and 

13 calculate the bill savings . 

14 The question has arisen about the data 

15 sources. We have purchased a data source, a database 

16 called MAISY, M-A-I-S-Y. You can find information on 

17 the web at wwww.Maisy.com. This is not a commercial, 

18 just trying to provide the information. This is a data 

19 set that was developed by Jackson and Associates in 

20 North Carolina. It comprises over 90,000 commercial 

21 customers and 60,000 residential customers. These are 

22 stratified by state. And it provides energy related 

23 customer characteristics. There are also household 

24 load profiles in this database. 

25 The database was built up by Jackson 

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1 Associates starting with the EIA surveys, the RECS and 

2 CBET surveys. And then bringing in city and county 

3 databases as well as census information. And there is 

4 some information on the web site. And we can refer you 

5 to Jackson Associates for more information. And the 

6 TSO will describe how we utilized this data. 

7 The second set of -- Glenn? 

8 MR. SCHEEDE: I visited the MAISY website and 

9 there is relatively little information there that would 

10 give one comfort in knowing how the data are really, 

11 where they come from and again, their 

12 representativeness, whether, the reliability and how 

13 they are put together. There is very little 

14 information there. So, what you would be forcing 

15 interested parties into doing is buying the database. 

16 And I don't think that is an acceptable way for DOE to 

17 proceed. If DOE plans on using this data, they should 

18 make it available in detail, so it can be reviewed by 

19 interested parties, particularly those of us who don't 

20 have access to taxpayer dollars, to fund our activities 

21 or to, all the money that Earl Jones has. 

22 MR. MCMAHON: Let me respond to that. 

23 MR. JONES: Thank you. I hope, Jim, you 

24 will respond on G.E., too . 

25 MR. MCMAHON: I am not going to respond on 

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1 behalf of Earl. I don't know how much money he has. 

2 On behalf of why we did this, in the past we 

3 have used the RECS data, which you are familiar with, 

4 Glenn, and you have your own concerns about. Given the 

5 importance of trying to get this rulemaking out without 

6 undue delay, it did not seem wise to have the 

7 Government devise a national survey that is 10 times as 

8 big as the existing one and to go out and do that on 

9 public dollars, when there is a commercial product that 

10 is available, that is used by a very large number of 

11 utilities. And I can give you a customer list, if you 

12 would like, of people who are using this database. 

13 It seemed prudent to purchase this database 

14 as a commercial product. But, since it is a commercial 

15 product, I can't give the entire database to you, 

16 obviously. It is a commercial product. So, I am sorry 

17 that we can't do that, but I am happy to answer your 

18 questions about the contents of the database. I just 

19 can't give away a free commercial product that they 

20 have for sale. 

21 Earl, did you want to respond on your behalf? 

22 MR. JONES: Well, actually, no, actually, I 

23 don't. My money is all committed. 

24 But, I did want just pursue this particular 

25 question on the statement. Now, if indeed DOE is going 

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1 to be relying upon these data, is there no obligation 

2 to make it available? 

3 MR. MCMAHON: I will turn to DOE for the 

4 answer to that. 

5 MR. MARGOLIS: We have not investigated that. 

6 We will and report back at the next committee. 

7 MR. JONES: Yes. Thank you, Gene. Because I 

8 do understand Jim's point about not wanting to reinvent 

9 the wheel if there is a good data source out there. 

10 But, by the same token, if that is what you are 

11 adopting, then it seems to me that you really should 

12 make it available. 

13 And that really brings back the other 

14 question I wanted to ask Bryan. It is my understanding 

15 that there was a recommendation for a, well, at least 

16 to me, a more simple, simplified approach to this 

17 issue. Which was proposed by the Advisory Committee. 

18 Which I didn't understand to involve pulling together a 

19 new data source here. But, a very simple way of taking 

20 out fixed costs. And I guess my question is what is 

21 the, where does that stand in this rulemaking? What 

22 are you making of that recommendation? Is this an 

23 alternative that recommendation or indeed they make two 

24 recommendations? 

25 MR. BERRINGER: Based on the Advisory 

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1 Committee, their recommendation, that came from Dan, 

2 was to use the marginal energy rates, which are being 

3 developed for this rulemaking. The fixed costs were 

4 talked about in the letter that Dan Ranker had 

5 addressed and we were not going to pursue without fixed 

6 cost. We are looking at, as far as marginal energy 

7 rates, some other possible alternatives for 

8 information. 

9 MR. MCMAHON: If I could supplement that 

10 answer? If I may. My understanding of what the 

11 Advisory Committee recommended was that marginal energy 

12 rates be used. And that the average less fixed costs 

13 be used as a temporary stock gap until the marginal 

14 rates were developed. 

15 MR. JONES: Okay. Then that leads to my next 

16 question, then. 

17 MR. MCMAHON: So, the intention is to not 

18 waste resources on the temporary stock gap, but to go 

19 and solve the problem. 

20 MR. JONES: Okay. I understand. What 

21 process, what was then used to come up with the life 

22 cycle costs here? 

23 MR. BERRINGER: Full cost. 

24 

25 

MR. JONES: Full cost. So, you went with, you 

didn't go with the temporary stock gap either, then, 

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1 for that purpose? 

2 MR. MCMAHON: In th1~ March workshop, both the 

3 average price and the average less fixed were 

4 presented. In the documentation here, only the 

5 average was presented because in the interim the 

6 Department had decided that they were not going to use 

7 the average minus fixed in future. 

8 MR. JONES: So, when will we have an 

9 opportunity to see these numbers recasted with data, 

10 better data from one source or another, or calculate 

11 one way or another? 

12 MR. MCMAHON: When the marginal rates are 

13 developed, these will be fed into life cycle cost for 

14 the next set of calculations. 

15 MR. JONES: And that, and that, we have no 

16 timetable for that, is what you are saying? 

17 MR. MCMAHON: Bryan has a timetable. 

18 MR. JONES: Oh. 

19 MR. BERRINGER: Yes, we are looking at in the 

20 March time frame, getting the results as far as 

21 marginal energy rates, so, you know, in the, probably a 

22 data will be available like say April, May time frame. 

23 

24 

25 

MR. JONES: Okay. Thank you. 

MR. BERRINGER: But, that is our next step to 

use the marginal energy rates. 

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1 MR. MCMAHON: If I could address the issue of 

2 the availability of data. One thing that we thought 

3 about doing and we have had preliminary conversations 

4 with Jackson Associates about this, is to develop a 

5 national subset, so not his full data set of 60,000 

6 households, but rather something like five to ten 

7 thousand households that are a national sample, without 

8 all of the detail that is in his data set, but only the 

9 relevant variables used in this rulemaking and make 

10 that available. That is, I can't promise yet that we 

11 are going to do that, but we are in negotiations to 

12 make that available. 

13 MS. NADER: Okay . At the mike? 

14 MR. NEAL: Yes, this was the previous slide, 

15 you stated about whethei season had anything to with 

16 the normal load. I would think that it may from a 

17 practical standpoint being that you wear heavier 

18 clothing in a cold climate or colder season. So, that 

19 may be a factor. 

20 MR. MCMAHON: Okay. Are you aware of any 

21 data sources on that? 

22 

23 

24 

25 

MR. NEAL: No, I am not. 

MS. NADER: Could we have your name, please? 

MR. NEAL: Brian Neal. 

MR. ECKMAN: Tom Eckman, Northwest Power 

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1 Plant Council. 

2 We have got regional data at the hourly 

3 level. 

4 MS. NADER: Thank you. Steve Rosenstock. 

5 MR. ROSENSTOCK: Steve Rosenstock, EEI. 

6 Since MAISY is a commercial product, I mean, 

7 it doesn't, it doesn't seem, I mean, if I was selling a 

8 product, I wouldn't want DOE to give it to everybody 

9 else, all the stakeholders. That is kind of you are 

10 hurting your sales there. Maybe some extracts might be 

11 of use, you know, that Jackson Associates would agree 

12 to, just to show some of the extracts for a limited 

13 sample, that they are not, you know, giving away the 

14 store as it were for their database. But, you know, 

15 you were saying five or ten thousand, that is, that is 

16 fine, it almost sounds like overkill just, I mean, I 

17 would say work with the vendor on that, that whatever 

18 they feel comfortable with in providing, I think is a, 

19 would be reasonable. Or you could also say, I don't 

20 know, just if DOE here would have the complete set, 

21 that people if they wanted to look at it here on site, 

22 they couldn't obviously take away. They could view it 

23 or look at the database here, just for their, you know, 

24 again preserve confidentiality and that way you are 

25 not, you know, no one is getting a free software 

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1 product, basically. 

2 Also I wanted to, I am glad Mr. Jones brought 

3 it up, in terms of using the average cost in the 

4 technical support document. The Advisory Committee, 

5 you know, said, take out the fixed cost as an interim 

6 step. And what concerns me is that in the technical 

7 support document as well as the announcement in the 

8 Federal Register, that since fixed cost were not taken 

9 out, it, it gives the impression, it leads to, there 

10 could be some vastly different numbers that could 

11 happen when you get the NOPR stage. I mean, we have 

12 the conclusions here, what appear to be conclusions. 

13 And I don't want to, I want to make sure that that 

14 people realize that these are just preliminary numbers 

15 from a preliminary analysis, that NOPR numbers, the 

16 final modified energy factor, might be completely 

17 different based on the new data that DOE is going to 

18 get. Have I mischaracterized that? 

19 MR. BERRINGER: No. 

20 MR. ROSENSTOCK: Thank you. 

21 MR. SCHEEDE: Glenn Scheede, again. I just 

22 wanted to disagree with Mr. Rosenstock on being very 

23 comfortable with data that happens to be available from 

24 a commercial source. There are lots of products 

25 available from commercial sources that are very good. 

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1 There are others that aren't worth a darn. And just 

2 having you list people who have brought them, and I 

3 recognize that is on the MAISY website. I have worked 

4 for lots of different organizations, who buy lots of 

5 products, data products, some you use, some you don't. 

6 But, you need to be able to evaluate them. And just 

7 saying they are commercial product, doesn't carry any 

8 weight. You need to find out how the product was 

9 developed. And I am just not nearly as comfortable 

10 with saying, fine, let's grab this as Mr. Rosenstock 

11 is. 

12 MS. NADER: Thank you. 

13 MR. JONES: Earl Jones, G.E. here . 

14 Just to comment on both, on two things. One, 

15 it seems to me that Jim is proceeding down the right 

16 road by trying to come up with a, something from these 

17 people who got data, that could fit the needs here and 

18 be made available. And then it would seem also that 

19 you would be in the position, Jim, to explain or defend 

20 or at least help us better understand exactly what was 

21 in there whenever the time might come that we have 

22 another meeting. 

23 And the other point was that having done 

24 these calculations with the average costs in there, I 

25 guess I wanted, it raises questions and if one were 

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1 concerned about, let's say the bona fides of this 

2 proceeding, which I am not, you would wonder why these 

3 numbers were put in there. What is the objective of 

4 doing that? I mean, you either are raising false 

5 expectations or you are trying to leverage people into 

6 a result which they are otherwise not prepared to 

7 accept. I really would caution you to, against doing 

8 that in the future and say, if you committed to a 

9 process, which says you are going to take certain costs 

10 out, then produce numbers which are more realistically 

11 based upon that commitment, as opposed to putting up 

12 strawmen, which can only fuel controversy in this 

13 rulemaking. I just don't understand why that was done. 

14 MS. NADER: Thank you for those comments. I 

15 think we should let Jim continue his presentation and 

16 see if some of the questions aren't answered in his 

17 presentation. 

18 Go ahead, Jim. 

19 MR. MCMAHON: Okay. I was describing the 

20 databases. The first one is the buildings database. 

21 The second is the tariffs. We are gathering 

22 information from several sources. We have perused the 

23 websites of the trade associations that are listed here 

24 for the utilities. We have looked at commercial 

25 vendors of data sets of tariffs. Public utility 

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1 commissions have this information. It is very 

2 laborious to go and retrieve it, but it does exist in 

3 the public, in publicly accessible form. And in some 

4 cases we are contacting individual utilities. 

5 The third data set is monthly end use load 

6 profiles. Which we are getting from the published 

7 literature. There was quite a bit of work done, 

8 starting in the 1970s and continuing in some places 

9 today. And there are still some utilities studies 

10 available. And I welcome the offers of data from the 

11 Northwest and anywhere else. 

12 Okay. Now let me come back to this issue of 

13 average minus fixed costs. This is not in your 

14 handout. It was something that I put together this 

15 morning. This is representation of estimates of 

16 electricity price, using one particular tariff from one 

17 particular utility. And I am trying to illustrate why 

18 it made sense to drop the average minus fixed cost in 

19 this example. What you are seeing here on the vertical 

20 axis is the cost per kilowatt hour. The scale goes from 

21 zero to 30 cents. And on the horizontal axis kilowatt 

22 hours per month, from zero to 600 kilowatt hours. 

23 There are three lines drawn here. The one that is in 

24 blue, that looks like two rectangles is labeled 

25 marginal price. This is actually the tariff schedule, 

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1 12 cents a kilowatt hour in this range, up to 273 and 

2 14 cents a kilowatt hour above 273 kilowatts hours . 

3 So, if you all go home and look at your utility bills, 

4 you may see something that has a block structure, 

5 something like that, with different prices. 

6 The green line coming down here is the 

7 average. This particular utility has a fixed charge. 

8 And so you are going to pay that charge whether you use 

9 energy or not. So, your first kilowatt hour is very 

10 expensive, because you are paying $2.00 a month, 

11 whether or not you use electricity. After that, as you 

12 use more electricity, it averages in and you begin to 

13 approach the 12 cents a kilowatt hour, then step up to 

14 14 cents and this slopes upwards. So, this is what the 

15 average price would be as a function of kilowatts hours 

16 per month. 

17 Average minus fixed, if we take off that 

18 $2.00 minimum charge, it looks like this. So, it 

19 starts being very low. There is a small anomaly here 

20 because it is a complex tariff and there is a three 

21 cents per kilowatt hour basic fee that shows up for 

22 very low consumption. But, basically, without the 

23 fixed charge, you pay very little at the low end. You 

24 come up to 12 cents and eventually start moving . 

25 The point of this is that the average is 

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1 sometimes high and sometimes low. But, it is a better 

2 representation of the marginal, than the average minus 

3 fixed, which is always low. Now, I understand this is 

4 one tariff and you can come up with other tariffs, but 

5 we have looked at a number of them, and we believe that 

6 the average minus fixed is bias to low. And that is 

7 why the average was a better representation for this 

8 one case as a stock gap until we can get to the 

9 marginal prices, themselves. 

10 MS. NADER: Steve? 

11 MR. ROSENSTOCK: Steve Rosenstock, Edison 

12 Electric Institute. 

13 EEI collected data as well as Oregon Energy 

14 Office, that I think we showed, especially, well, among 

15 investment utilities, the difference was the fixed cost 

16 were about seven and a half percent. And among 

17 municipals and coops, at least of some of the limited 

18 data that I saw, some of the values were higher because 

19 you have fewer customers for distribution line mile. 

20 And since, you know, municipals and coops are about 25 

21 percent of the population. Since we are going to 

22 marginal energy rates for the next round of the 

23 analysis and I know this is preliminary, I still, the 

24 Advisory Committee still said as an interim step, that 

25 we agreed that to take out as the interim step, take 

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1 out the fixed cost where we could. So, I am just a 

2 little concerned and I know you examined the data but I 

3 still think that you are kind of skirting around what 

4 the Advisory Committee said. That is kind of my 

5 interpretation of it. But, since it is preliminary, 

6 it, I am okay with it right now. But, I am just saying 

7 for the future, if for whatever reason, depending on 

8 the timetable, that you don't have all the marginal 

9 energy rates, I would say that that it would be a 

10 better procedure to take out the fixed costs, 

11 otherwise, again, in my. opinion that some of the 

12 economics would be, the economics might be a little bit 

13 overstated. Thank you . 

14 MS. NADER: Glenn Scheede. 

15 MR. SCHEEDE: Glenn Scheede, again. 

16 Since you have already done this analysis on 

17 some utilities, could you bundle that information up 

18 and make it available to us, so we can see which 

19 utilities you looked at and what the results were, the 

20 study that you said you just, have already done to look 

21 at marginal versus average rates? 

22 MR. MCMAHON: I can provide you, not at this 

23 moment, but I can provide you with information about 

24 what utilities we have contacted and how many tariffs 

25 we have from those utilities. 

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1 In terms of showing you quantitative results 

2 like this for all, that is not possible at this time, 

3 because 

4 MR. SCHEEDE: Just the ones that you have 

5 looked at to reach the conclusion that you did. You 

6 said you reached a conclusion that there were enough of 

7 them where the marginal rates were higher than the 

8 average rates. That you thought that was not the right 

9 way to go. So, I say, can we just see the data, see 

10 the analysis you have done, since it is already done, 

11 just bundle it up and let's see it and see what 

12 MR. MCMAHON: I am showing you an example, 

13 Glenn. I would be happy to 

14 MR. SCHEEDE: No, I don't mean the example. I 

15 mean, the whole works. The one example doesn't provide 

16 the basis for you to reach a conclusion, I assume. 

17 Because you said you have done it on a number of 

18 utilities. 

19 MR. MCMAHON: I have looked at a number of 

20 tariffs and similar result. It is very clear that when 

21 you subtract a fixed charge from the average, you are 

22 going to get a lower number. It is very clear from 

23 what Edison Electric Institute did, that marginal rates 

24 maybe higher or lower than average. They are not 

25 consistently lower. And, therefore, the average minus 

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1 fixed charge is bias low. To the extent that we have 

2 documentation written up, I am happy to provide to you, 

3 however, our resources right now are dedicated to 

4 developing the marginal rates. And I really don't have 

5 the time or the resources to write another report in 

6 the interim. 

7 MR. SCHEEDE: I wasn't lopking for any new 

8 analysis, just the EEI provided a whole lot of data and 

9 you said you came up with data that suggested that is 

10 bias on the low side. What I am saying, I want to see 

11 the data that you have already put together, just make 

12 that available to us, not, it doesn't have to anything 

13 fancy, just let's see the data . 

14 MR. MCMAHON: Okay. 

15 MS. NADER: Okay. 

16 MR. MCMAHON: It won't be fancy. 

17 MS. NADER: Steve Rosenstock. 

18 MR. ROSENSTOCK: Steve Rosenstock, EEI. 

19 Going into the technical support document, it 

20 talks about, it is Chapter 7 talking about the prices 

21 and the approach, this is for both electricity and 

22 natural gas. The RECS 1993 data is used and then to 

23 adjust it to 1997 dollars and please correct me if I am 

24 misstating this, it is the values from 1993 were 

25 multiplied by the CPI, Consumer Price Index, Global 

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1 U.S. Consumer Price Index to bring it, that is part of 

2 the equations, so it is those values times the '93 to 

3 '97 CPI. Then it is multiplied again by the, I will 

4 say an energy price scale for that same time period. 

5 Is that, am I stating that correctly? 

6 MR. MCMAHON: That is correct. 

7 MR. ROSEN~TOCK: Okay. I am just kind of 

8 curious, I am having, I guess I am having a little 

9 trouble with that because let's just use, it is a 

10 dollar per unit of energy in 1993 and the price didn't 

11 change in 1997. So that, the energy scale, there is 

12 1.0, but the price, the Consumer Price Index went up 10 

13 percent. So, it would be 1.0 times 1.1 for Consumer 

14 Price Index, times 1.0, which would mean that the '93 

15 price would be shown as 1.1 in the graph, when really 

16 you have other data that shows that was actually 1.0. 

17 MR. MCMAHON: No, that is not what happened. 

18 What we did was replicate the 1997 prices. The 

19 adjustments are there to make sure that in 1997 we are 

20 characterizing the energy price correctly, not using 

21 1993 values. 

22 MR. ROSENSTOCK: Okay. But, but, since there 

23 is census data on the actual energy prices, you know, 

24 whether it is electricity, it might be electricity and 

25 natural gas, and oil. I know, I am pretty sure the 

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1 Commerce Department does have some energy, you know, 

2 they do food and they also do energy. They break out 

3 oil from electricity and gas. Is that CPI component 

4 really needed in there to do that adjustment? That was 

5 just, I am just kind of curious about that. 

6 MR. MCMAHON: You are proposing alternative 

7 methodology where we do one scaling. We take 1993 

8 prices and '93 dollars and scale 1997 and 1997 dollars. 

9 But, we didn't separate that into two components. But, 

10 you have the same result. 

11 MR. SCHEEDE: Glenn Scheede, again. 

12 Electricity prices between '93 and '97 did 

13 not increase at the same rate as CPI. If you will look 

14 in monthly energy reviews, you will see EIA has a table 

15 in there that compares the two. Electricity prices 

16 didn't go up as far, as far as CPI. So, it is not a 

17 correct adjustment. 

18 MR. MCMAHON: I agree with you, it did not. 

19 And the scale in 1997 dollars, from '93 to '97 prices 

20 accounts for that. 

21 MS. NADER: Okay. I am going to ask that we 

22 move on. If we have additional time, at the end of the 

23 afternoon, we can return to some of these subjects. We 

24 have a number of presentations yet . 

25 MR. MCMAHON: Okay. So, Peter, do you want 

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1 to? 

2 MS. NADER: Oh, you are through . 

3 MR. MCMAHON: Yeah, we are going to do that 

4 water rates, next. 

5 MS. NADER: Thank you. 

6 Peter Biermayer, also of Lawrence Berkeley 

7 Lab. 

8 PRESENTATION BY PETER BIERMAYER: 

9 MR. BIERMAYER: Okay. I am going to talk 

10 about the analysis of water and waste water rates. By 

11 waste water, we mean sewerage basically. 

12 Okay. We had two objectives in this task. 

13 And one was to find what the distribution of current 

14 rates are, so we can have a price for the current rate 

15 of water. And also to see how it escalates. 

16 So, to get the distribution, first of all we 

17 used Raftelis data and that is the latest survey data 

18 that we know of. And it was taken in 1998. And we 

19 converted it to 1997 dollars. And what we did with 

20 that data is we took the cost of water for a thousand 

21 cubic feet and subtracted out the base charge for zero 

22 consumption. And so, that is, then divided that by the 

23 thousand cubic feet, so we get dollars per cubic feet. 

24 And that is sort of a marginal rate. It is different 

25 than a marginal rate than Jim talked about in the way 

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1 it was done, but it is, that was the intent. 

2 We also corrected using all urban consumer 

3 price index to convert to 1997 dollars, since all the 

4 rest of the analysis is in 1997 dollars. And this data 

5 was going to be used in two places. One was in the LCC 

6 spreadsheet, where we would use the distribution. And 

7 also in the NES spreadsheet, where we would use a 

8 single value, but it would be a marginal rate, a single 

9 marginal rate cost of water. 

10 The database for the distribution or the 

11 number for the current rate was based on 115 service 

12 areas, and service areas pretty much correspond to 

13 cities. They represent population of 56 million. And 

14 that is people, not households. And to give you an 

15 idea of what that number is representative of, 86 

16 percent of the country is on a water utility and 77 

17 percent have a waste water utility. Meaning, the rest 

18 have, are connected to private wells, septic tanks. 

19 This chart here shows us the, it is just a 

20 graph of the database I was describing. Basically I 

21 have, on this side is just the weighting. We weighted 

22 all these, these, this price data according to the 

23 population served. So, you can see over here, we have 

24 New York City, I believe this is Detroit, that is L. A . 

25 And it shows you the distribution of water rates, 

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1 marginal water rates. 

2 MR. JONES: Peter, Earl Jones here . 

3 How did you select these cities? 

4 MR. BIERMAYER: They were on the database, put 

5 together by an organization, by Mr. Raftelis. 

6 MR. JONES: Who is he? 

7 MR. BIERMAYER: He is, he is well known in the 

8 water business. He is the only person I know of that 

9 puts together a comprehensive survey on water. And --

10 MR. JONES: So, it is not population weighted 

11 or --

12 MR. BIERMAYER: This is -- for population. 

13 What he did is he asked them what the number of people 

14 each water utility served, and then these were weighted 

15 by the population. That is what the wide axis shows is 

16 distribution. 

17 MR. JONES: Yeah, maybe I asked the wrong 

18 question. What I meant was, what percent, were the 

19 selection of 115 cities .based in any respect on their 

20 populations and what that represented by way of the 

21 U.S. population? Or is it just 115 cities for whatever 

22 reason? 

23 MR. MCMAHON: Earl, maybe I can help. This is 

24 Jim McMahon . 

25 We contacted the Trade Association, the 

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1 American Waterworks Association and asked them where 

2 the best data was. They referred us to Mr. Raftelis, 

3 who has a consulting organization. And this is the 

4 most comprehensive data set that exists. These are the 

5 only 115 cities that are surveyed. So, there is no 

6 selection here. We took all of the data that was 

7 available. 

8 MR. JONES: Okay. Thank you. 

9 MR. MORRIS: This is Wayne Morris of the AHAM. 

10 Jim, when you look at this data from 

11 Raftelis, did he not break this down into, I believe 

12 large cities, medium cities and small cities? Some 

13 kind of a distribution in which he had a selection of 

14 some of the largest cities in the U.S.A., some of the 

15 medium sizes and some of the smaller. I thought that 

16 that is what I remember. 

17 MR. MCMAHON: This is the full set. There are 

18 large cities, medium cities and small cities included. 

19 And you can see that in the population distribution by 

20 the height of bar. 

21 MR. BIERMAYER: I can get you the exact cities 

22 if you are interested. It is just a list of cities and 

23 we called Raftelis and he said it was okay to share it 

24 with whoever wanted it . 

25 MS. NADER: Glenn Scheede. 

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1 MR. SCHEEDE: Two questions. Will the data be 

2 made available so that we can see them? 

3 MR. BIERMAYER: Yes. 

4 MR. SCHEEDE: The detailed data? 

5 MR. BIERMAYER: Yes. 

6 MR. SCHEEDE: Okay. Second question. To 

7 what extent are the data for the 115 cities and the 56 

8 million people representative of the nation as a whole? 

9 MR. BIERMAYER: Well, 2.3 people per 

10 household, would give you the percentage. Let me see. 

11 It is about 22 percent of the national population. 

12 MR. SCHEEDE: Yes, I can do that arithmetic, 

13 too. But, to what extent do know these 115 cities 

14 represent, are representative of the nation as a whole? 

15 Particularly, in rural areas where people don't rely on 

16 municipal sewer and water? 

17 MR. BIERMAYER: Yeah, at this time we don't 

18 have information on what the cost is if you have a 

19 private well and a private septic tank system. From 

20 people that I have talked to in the water business, 

21 they tell me that if given a choice, people would, will 

22 hook up to city water and city sewerage, meaning there 

23 is some benefit to having that rather than having your 

24 own well and pump. I don't have exact numbers on what 

25 it costs, but there are costs of course~ You know, you 

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1 have to have your septic tank pumped out, you have to 

2 maintain your pumps. There are costs to having a 

3 private system. We don't have detailed data on that. 

4 We expect it to be higher. 

5 MR. SCHEEDE: Do you expect to get those data, 

6 so that we know what the 

7 MR. BIERMAYER: We intend to try and get some 

8 information on that, yes. 

9 MR. SCHEEDE: Because this seems like a bias 

10 sample to metropolitan areas, and large, and I don't 

11 know whether they large or not. 

12 MR. BIERMAYER: Yes, what the water experts 

13 tell me is that actually the water prices are less 

14 expensive in the large cities. So, if you are saying 

15 that my prices are too low, you are probably correct. 

16 MR. SCHEEDE: No, I don't know whether they 

17 are too low or too high. I am looking for the data so 

18 I can see. 

19 MR. BIERMAYER: Okay. If anybody has data on 

20 that, please send it to me. We are trying to get that. 

21 MR. SCHEEDE: Well, no, no, let's not try to 

22 shift the burden here. Obviously --

23 MR. BIERMAYER: No, if it is possibly, 

24 possible to get it, we will get it. 

25 MR. SCHEEDE: Okay . But, it is DOE'S 

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1 responsibility to collect and provide the data, not 

2 interested parties to collect it . 

3 MR. BIERMAYER: I am just saying, we will 

4 welcome your contributions. 

5 MS. NADER: Steve Rosenstock and then over 

6 there, and then I will suggest that Peter continue with 

7 his presentation. 

8 MR. ROSENSTOCK: Steve Rosenstock, Edison 

9 Electric Institute. 

10 These are just a couple of quick questions. 

11 These are residential rates only, they are not small 

12 commercial or anything. 

13 MR. BIERMAYER: Right, residential . 

14 MR. ROSENSTOCK: Residential. 

15 Number two, did any of them, just out of 

16 curiosity, did any of them have any sort of block 

17 rates, either increasing or decreasing? 

18 MR. BIERMAYER: Yes, they did. 

19 MR. ROSENSTOCK: Okay. 

20 MR. BIERMAYER: We have other data on that. 

21 think about, I don't know the exact numbers but the 

22 most popular for water is the inclining block rate, 

23 with a declining block rate being second and then a 

24 flat rate. And with sewerage it is mostly, I think it 

25 is 80 percent flat rate. 

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1 MR. ROSENSTOCK: So, when, so when you created 

2 these values, were you looking at a, were you looking 

3 at the first block or second block, you know, 

4 regardless of what it was? I am just kind of 

5 MR. BIERMAYER: No, we, I don't have the 

6 breakdown on the blocks. It was just for one thousand 

7 cubic feet, what were the costs. 

8 MR. ROSENSTOCK: Which is the average --

9 MR. BIERMAYER: Right. 

10 MR. ROSENSTOCK: Per month. 

11 MR. BIERMAYER: Right. 

12 MR. ROSENSTOCK: Okay. 

13 MS. NADER: Okay. Question over there? 

14 MR. STEVENS: Charlie Stevens from the Oregon 

15 Energy Office. I would just like to take issue with 

16 Mr. Scheede here, momentarily. I think DOE has 

17 collected the only data there is. I have been out 

18 there collecting some of this data myself. I don't 

19 think it is necessarily incumbent on DOE to do more 

20 than collect all the data there is. I think it is 

21 incumbent upon stakeholders who find issues with it, to 

22 put some concrete reasons on the table as to why this 

23 data is inadequate and usually that is done by having 

24 some other data that shows some other case. So, in the 

25 absence of that I think they have done a pretty good 

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1 job of gathering data. 

2 MS. NADER: Okay. Thank you. 

3 MR. SCHEEDE: Glenn Scheede, if I were 

4 subsidized by DOE to collect data, the way some of the 

5 state energy offices are, perhaps I could do it. 

6 MS. NADER: Thank you. 

7 Peter, please continue with your 

8 presentation. 

9 MR. BIERMAYER: Okay. The second objective 

10 was to determine a price escalation for water. And 

11 these were the first of the data we went to look for, 

12 for data in for both the cost and for the escalation. 

13 We got some data from American Water Works 

14 Association. As I said before, got information from 

15 Raftelis, Al Dietemann, who is here, did some work in 

16 1994, giving population weights to other data that was 

17 collected from Raftelis and Ernst and Young. And what 

18 we did is because each of these surveys didn't always 

19 have consistent cities, the same cities weren't 

20 surveyed in every survey, what we did is we called up 

21 cities to fill in missing gaps. And what we came up 

22 with for 1986 and 1998 was 38 cities where we can have 

23 the same cities both in 1986 and 1998, so we can make a 

24 comparison . 

25. We also tried to, we called utilities and we 

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1 asked them what they forecasted for the future? We 

2 didn't get a whole lot of response. We got six people 

3 who responded, utilities that responded on that. And 

4 they kind of, it wasn't very consistent data. 

5 Also we, there was some comments to DOE, 

6 which I will talk about later, regarding the escalation 

7 of water prices. And then we also have opinions of 

8 experts from Raftelis, Al Dietemann, American Water 

9 Works. 

10 This is a map that shows the cities of the 

11 38, of 38 cities that we used in predicting a price, or 

12 looking a historical trend for price escalation of 

13 water. So, you can see they are distributed around the 

14 United States. 

15 Okay. This chart here, shows the, it is a 

16 bar chart one, color is 1998. That tends to be the 

17 higher bar chart, showing that it is more expensive 

18 than in 1986. This is also in 1997 dollars, corrected 

19 using CPI, Consumer Price Index. 

20 Okay. This chart here shows the 38 

21 individual cities and the distribution of their percent 

22 change in water prices from '86 to '98. So, you can 

23 see there is a few that are negative, there are some on 

24 the right. And tbe~e are indiyidual cities, and it 

25 shows you basically the population. 

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1 Steve? 

2 MR. ROSENSTOCK: Steve Rosenstock, EEI. 

3 On this chart it says median of 1.86 percent. 

4 That is over years without any CPI adjustments, right? 

5 That is just from, you know --

6 MR. BIERMAYER: No, that is, everything has 

7 been adjusted to 1997 dollars. 

8 MR. ROSENSTOCK: But, the --

9 MR. BIERMAYER: That represents unweighted. 

10 Those are unweighted figures. 

11 MR. ROSENSTOCK: Okay. 

12 MR. BIERMAYER: That is an unweighted average. 

13 And, well, the median is just of those cities. It is 

14 just, you know, it doesn't need to be weighted. 

15 MR. ROSENSTOCK: Right. But, what I am saying 

16 is that it was, you know, it was like $4.00 one year 

17 and then $5.00 10 years later and you are just the 

18 annual percentage. Did you assume --

19 MR. BIERMAYER: Oh, right. 

20 MR. ROSENSTOCK: Did you assume a constant 

21 slow between the two data points? 

22 MR. BIERMAYER: No, what we did is, we used 

23 the concept of a compound interest basically. Where 

24 if, we looked at the, let's see if I can explain this 

25 without paper . 

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1 We looked at the numbers in 1986, the cost in 

2 1986 in 1987 dollars, I mean, 1997 dollars, and looked 

3 at the cost in 1998, and converted that to 1997 

4 dollars. Then we used an equation showing that, well, 

5 basically that, what the rate would be assuming they 

6 had a rate change every year and how that would 

7 compound. What the equivalent interest rate would be, 

8 yearly interest rate increase would be if they changed 

9 the rate every year. And a certain percent rate, to 

10 get the -- dollars. 

11 MR. ROSENSTOCK: It is derived percentage 

12 changes. 

13 MR. BIERMAYER: Yes . 

14 MR. ROSENSTOCK: And it is constant, you are 

15 assuming constant change throughout the 12 years. 

16 MR. BIERMAYER: Yes. 

17 MR. ROSENSTOCK: But, it is still like a one 

18 percent and then one percent, you know, it is still 

19 that --

20 MR. BIERMAYER: It doesn't, as you might 

21 guess, it doesn't change the same percentage every 

22 year. This is sort of an average percentage change per 

23 year. 

24 MR. ROSENSTOCK: But, the first, for the 

25 original adjustment, from '86 to '97, was again using 

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1 the Global Consumer Price Index. 

2 MR. BIERMAYER: It is all Urban Consumer Price 

3 index. 

4 MR. ROSENSTOCK: The Urban, okay, but 

5 MR. BIERMAYER: Which I think is the standard 

6 CPI number. 

7 MR. ROSENSTOCK: Okay. 

8 MR. BIERMAYER: Okay. So, the results, we 

9 got $3.20, we converted it to gallons, instead of cubic 

10 feet, $3.20 per gallon, that is for 1998, Raftelis 

11 data, 1997 dollars, includes water and wastewater 

12 rates, 115 cities. And as I already explained, 56 

13 million people. The escalation rate we got was 3.1 

14 percent real. These are all marginal rates, based on 

15 38 service territories and 27 million people. 

16 And how does this compare with the 

17 stakeholders. We have some comments, Whirlpool 

18 mentioned the same people that we got data from. And 

19 made a general observation that prices have been 

20 increasing. 

21 ACEEE referred to Osann and Young study. 

22 They also looked at future improvements in 

23 infrastructure required by the government and how that 

24 would affect future prices. And they also did the and 

25 they got a range of 1.1 to 2.7 percent real. 

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1 Anticipating the question why we got 

2 something different than Osann and Young. Osann and 

3 Young came up with the 2.6 percent real. And the 

4 difference in the analysis there was that we used the 

5 years from '86 and '98. They used '86 to '96. So, we 

6 have one more year's worth of data. 

7 We adjusted for marginal rates, and they 

8 didn't. We used 38 cities, and the same cities in both 

9 years. They used a larger data set, Ernst and Young 

10 and Raftelis data surveys, but those surveys don't 

11 always have the same cities every year. So, we want to 

12 make sure we are using the same cities both years. 

13 And I guess that is it. Any questions? 

14 MS. NADER: No questions? Peter, thank you. 

15 MR. BIERMAYER: Thank you. 

16 MS. NADER: Jim McMahon is going to 

17 MR. JONES: Well, Earl Jones here. I did have 

18 one question. You said you contacted departments, 

19 water works and to find out what their plans were and 

20 you got responses from six. So, my question 

21 MR. BIERMAYER: Oh, no, the, we called up 

22 utilities and asked them and we had six responses. 

23 MR. JONES: Yes, I thought, well, okay. 

24 How does that figure into this analysis? 

25 MR. BIERMAYER: We are not using it because 

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1 there was not much response. 

2 MR. JONES: Not enough data . 

3 MR. BIERMAYER: But, since how we made the 

4 effort, we were asking them for it and we didn't get 

5 any response, basically. 

6 MR. JONES: So, then what assumption do you 

7 make about what happens in the future? 

8 MR. BIERMAYER: Three, point two percent, the 

9 3. --

10 MR. JONES: How about infrastructure? 

11 MR. BIERMAYER: Oh, about the infrastructure? 

12 MR. JONES: Yes. And the cost of that? 

13 MR. BIERMAYER: Well, basically we assume 

14 that, you know, it will, the cost of water will 

15 increase faster than the rate of inflation. So, we 

16 didn't, this analysis I did here, was just based on 

17 historical basically. And we got some input from some 

18 of the experts saying that basically they would expect 

19 the price to increase. But, our analysis isn't based 

20 on, is based on just historical cost. It is not based 

21 on future infrastructure costs. 

22 MR. JONES: Okay. 

23 MS. NADER: Gentleman at the mike. 

24 MR. HOLMES: Hi, I am Tommy Holmes, American 

25 Waterworks. 

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1 Sorry, more utilities didn't response 

2 directly. But, I can assure you your water bills will 

3 go ,up in an increasing rate because of a variety of 

4 factors. One we have falling water tables across the 

5 country. Two, we have an aging infrastructure that is 

6 screaming for replacement. And Congress recognized 

7 this in creating the State Revolving Loan Fund, in the 

8 Safe Drinking Water Act. And we have more and more 

9 regulations coming on line. The Safe Drinking Water 

10 Act was last amended in 1996. And those amendments 

11 are, the regulations stemming from those amendments are 

12 just beginning to come on line. Just last week 

13 President Clinton announced the new regulation from 

14 Microbial and Disinfection By-products. And that is a 

15 whole new layer of water treatment to lower your 

16 exposure to bugs, like cryptosperida(ph), and 

17 consequently also lower your exposure to the by18 products from disinfection practices. 

19 Also we have to admit drinking water 

20 utilities are tremendous consumers of electricity. And 

21 in our comments we sent to DOE in 1995, we had a study 

22 saying it was estimated that drinking water utilities 

23 consume seven percent of the nation's electricity. I 

24 would imagine that is pretty conservative nowadays, 

25 especially if you have utilities moving toward 

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1 ozoneization(ph), reverse osmosis(ph) and 

2 decelerization(ph). Those aren't wide practices yet . 

3 But, even our own backyard, Fairfax County Water is 

4 moving to ozone treatment. So, I think, 3.2 percent is 

5 a good baseline, but I would say it is probably pretty 

6 conservative. 

7 MS. NADER: Thank you. Steve? 

8 MR. ROSENSTOCK: Steve Rosenstock. 

9 Does your organization track it? What has 

10 been happening the last few years, just out of 

11 curiosity, in terms of some of these rates? 

12 MR. HOLMES: In rates? . You know, we haven't 

13 done a lot of work tracking utilities rates. The 

14 NARORC(ph} has done a lot that stuff. Our concern 

15 mainly has been in water quality and water treatment 

16 and on the legislative and regulatory side. But, we 

17 haven't done a lot of tracking at rates. 

18 MS. NADER: Okay. Any more questions for 

19 Peter? 

20 MR. DIETERMANN: I have got a follow up to 

21 that. My name is Al Dietermann. I am with Seattle 

22 Public Utilities. 

23 For those that don't know George Raftelis is 

24 chair of Rates and Finance Committee for American 

25 Waterworks Association. The references here are tied 

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1 into the Raftelis survey. He is a private rate 

2 consultant. He doesn't get paid by AWWA to do these 

3 survey work. But, there is a logical tie in there and 

4 he is extremely knowledge individual about rates across 

5 the country for both water and wastewater. 

6 MS. NADER: Thank you. Anyone else, for 

7 Peter? Steve? 

8 MR. NADEL: Steve Nadel, ACEEE. I am very 

9 glad that DOE and LBL has gone forward and actually 

10 done this analysis. The data we provided before was 

11 saying, was to address the fact that before you assumed 

12 a zero percent escalation, is take the best data that 

13 we could find at that point in time. But, you have 

14 clearly gotten a lot more data. You have done a lot 

15 more to clean it up, and I think it is a pretty good 

16 analysis. 

17 The one other thing I would point out is as 

18 you noted the difference between the 2.6 and 3.1 

19 percent, what the differences were, the low end of our 

20 range was based on some of the data from Osann and 

21 Young in terms of future cost. That data is a couple 

22 of years old. And we apply certain assumptions to that. 

23 So, that is not especially rigorous. We supply that to 

24 indicate that there is a great likelihood that that 

25 rates would increase in the future, to argue against 

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1 the preassumption that rates were going to be flat. 

2 But, I wouldn't read too much in, particularly the 

3 lower -- If someone wanted to look at infrastructure 

4 cost, they will need to do a lot more. They would 

5 first need to update that database and do a lot more 

6 looking into some of the key driving assumptions about 

7 the average life and interest rate and so on, in order 

8 to do that. 

9 MS. NADER: Thank you. Thank you, Peter. 

10 Jim McMahon is going to talk to us about 

11 energy savings. 

12 MR. MCMAHON: So much research, so little 

13 time . 

14 MR. JONES: Jim, before we leave the prior 

15 discussion, one more time, if you could. And I 

16 probably missed this and I apologize. But, the 3.1 

17 factor or 3.2 or whatever it was. Peter, is over what 

18 period of time? Is that annual? Is that over the 

19 MR. BIERMAYER: That is average per year 

20 increase from 1986 to 1998. 

21 MR. JONES: And how is that number being used 

22 going forward now? 

23 MR. BIERMAYER: How is it being used, how? 

24 MR. JONES: Yes, going forward . 

25 MR. BIERMAYER: Oh, okay. That will be used 

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1 in the life cycle cost spreadsheet and also the NES 

2 spreadsheet . 

3 MR. JONES: Okay. 

4 MR. BIERMAYER: National Energy Savings 

5 spreadsheet. 

6 MR. JONES: Okay. And how does that number 

7 different from the other numbers which are cited in 

8 your last page? The analysis by the other folks you 

9 looked at. The other data that you came up with, how 

10 does this number compare with others? I see that ACEEE 

11 suggested a number. That is on here somewhere. 

12 MR. BIERMAYER: Yes. 

13 MR. JONES: Right. And I guess my question 

14 was what other, what other numbers, what other factors 

15 were suggested by· these other, by anybody else you 

16 looked at? 

17 MR. BIERMAYER: Those, those are the main 

18 people I looked at. There are some other papers on 

19 there that I don't have with me and I don't, I don't 

20 have any of the information with me on --

21 1 MR. JONES: So, you don't know what the Ernst 

22 and Young suggested or Raftelis? 

23 MR. BIERMAYER: Oh, they just, they are in the 

24 business of collecting the surveys. They are not in 

25 the business of --

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1 MR. JONES: Making projections. 

2 MR. BIERMAYER: Projections. 

3 MR. JONES: And so, the only projection that 

4 is in your information or that you had access to, is 

5 the one that Steve provided to you, is that what I am 

6 hearing? 

7 MR. MCMAHON: No, there is a misunderstanding 

8 here. Maybe I can help, Earl. 

9 MR. JONES: Okay. 

10 MR. MCMAHON: Ernst and Young was the firm 

11 that did the surveys from 1986 up until, 1994, is that 

12 correct? And then Raftelis has done the surveys since 

13 then . 

14 MR. BIERMAYER: Yes. 

15 MR. MCMAHON: Okay. 

16 MR. BIERMAYER: I would like to add actually 

17 that Raftelis did this for Ernst and Young before he 

18 opened his own consulting practice. So, it is really 

19 the same person. 

20 MR. MCMAHON: So, we have used all of that 

21 data that is available from Ernst and Young and from 

22 Raftelis, from 1986 to the present. 

23 MR. JONES: Right, but they are not in the 

24 business of making projections, right? You used their 

25 data to come up with the projection of what the annual 

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1 inflation would be going forward. Am I --

2 MR. MCMAHON: I believe that Raftelis does 

3 provide, I mean, Al can_ answer that question whether 

4 George Raftelis provides projections. 

5 MR. DIETERMANN: Well, he works for the 

6 individual utilities to forecast based on their 

7 specific geographic and future needs. But, not for the 

8 whole nation. 

9 Ernst and Young did provide information in 

10 the '94 study, which showed and tracked their work in 

11 terms of rate increases over time. And that is 

12 available but of course it stops at '94, when their 

13 work was concluded . 

14 MR. JONES: Okay. And who is Osann? Who is 

15 Osann? 

16 MS. NADER: Al what is your last name? 

17 MR. DIETERMANN: Al Dietermann, Seattle Public 

18 Utilities. 

19 Osann is a private consultant at this point. 

20 He has done considerable work developing information 

21 associated with the Conberg(ph) Bill, which is before 

22 Congress now. 

23 MR. JONES: Okay. And so then my question, 

24 Peter, then is how did you, it says here that these 

25 studies and I guess Osann and Young is another company 

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1 or consulting firm, is that correct? 

2 MR. BIERMAYER: Okay. The reason that was 

3 mentioned is because ACEEE sent a comment to the 

4 Department of Energy, they attached the Osann and Young 

5 report and referred to it. That is why I am comparing 

6 what we did at LBL, with what a comment was that Steve 

7 Nadel supplied. 

8 MR. JONES: Okay. So, then tell me again, 

9 what was wrong with Steve's data? I want it on the 

10 record. 

11 MR. BIERMAYER: Steve -- Well, I outlined what 

12 we did differently, you know, I don't want to say what 

13 they did was wrong, I am just saying what we did was 

14 different. We used the same cities in '86 and in '98. 

15 And they also, they stopped in the year 1996. We added 

16 one more year, because we used the latest data. We 

17 corrected from marginal rates. They did not correct 

18 for marginal rates. That is what was different, and 

19 that is why we got different numbers. 

20 MR. JONES: And that would explain what seems 

21 to me rather substantial difference. 

22 MR. BIERMAYER: Yes. 

23 MS. NADER: Okay. One more question in the 

24 back. Did I see a hand? No. All right . 

25 Carry on, Jim. 

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1 PRESENTATION BY JIM MCMAHON: 

2 MR. MCMAHON: Thank you. 

3 Jim McMahon from LBL. I am going to speak 

4 about clothes washer shipments. 

5 The approach that I have taken here is to try 

6 to give the simplest approach possible and then add 

7 more factors as it becomes necessary. 

8 The maj?r drivers of shipments are two, 

9 replacements of existing clothes washers and new 

10 housing construction. 

11 In addition, our economic factors, in 

12 principal washer prices and operating expenses should 

13 influence shipments as well . 

14 What I am going to do is deal with the first 

15 two, just by accounting for those without worrying 

16 about the economic factors and then discuss the 

17 economic factors later. 

18 New housing construction has been between one 

19 and two million housing units a year in recent history. 

20 Seventy-four to 90 percent of new housing units have 

21 residential clothes washers, depending upon the house 

22 vintage, it has increased over time. Here referring to 

23 the period from 1980 to 1993. 

24 We estimate that new housing accounts for 

25 about 1 to 1.6 million residential clothes washers 

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1 shipped each year. Again, it depends upon the year. 

2 If we compare those numbers to the total shipments, 

3 that is about 19 to 33 percent of annual shipments. 

4 In terms of replacements, the life expectancy 

5 of clothes washers, we are taking numbers of 12 to 16 

6 years. This is from Appliance Magazine, September of 

7 1998, with a 14 year average. 

8 Using that distribution of lifetime expressed 

9 as a triangular distribution, and the record of 

10 historical shipments, we can calculate the replacements 

11 and we estimate those to have account for 63 to 85 

12 percent of total shipments, depending upon the year. 

13 If I add those two together, I can compare 

14 these estimates to the total shipments reported by the 

15 industry. And that is shown on this picture on page 

16 five. The bottom shaded in blue is the replacement 

17 market. The white section is the new housing 

18 construction. And the dashed line is total shipments, 

19 actual. And you can see we get fair agreement from 

20 about 1981 up to the early 1990s, and not as good 

21 agreement the last few years. 

22 Expressing that same data a different way, I 

23 turned the actual shipments each year into 100 percent 

24 and we express the replacement and new as shares of 100 

25 percent. Since those estimates are done independently, 

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1 they don't always add to 100 percent, only when we get 

2 it exactly right. And you can see that depending upon 

3 the year, it is pretty close. The worse error is 11 

4 percent that the estimates differ from the actual. 

5 So, that is fairly reasonable agreement without 

6 accounting for any economic factors. 

7 We recognize that there are economic factors. 

8 Purchase expenses for washers are about $420.00 retail. 

9 These are the same numbers that are used elsewhere in 

10 the analysis. 

11 The operating expenses, we estimate average 

12 about $126.00 per year on a national average. Those 

13 are broken down into energy expenses, of about $78.00 

14 per year. This includes water heating and clothes . 

15 drying, averaged over the different fuel types. And 

16 let me be clear about the average over, we are actually 

17 adding up the individual ones and then dividing by the 

18 population. So, each household has one fuel type or 

19 another. And then we put them together to get the 

20 national totals. 

21 The water expenses, we estimate average 

22 $48.00 per year and that includes both the water and 

23 the wastewater rates. 

24 

25 

Let me just go to elasticities. In order to 

bring the economic factors into the projection of . 

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1 shipments, one way to do that is to express things in 

2 terms of the elasticities . 

3 An elasticity is the percent change in a 

4 quantity such as shipments or market share, associated 

5 with a percent change in a driving factor, like the 

6 washer price. 

7 Previous research has indicated that for 

8 white goods, specifically refrigerators have elasticity 

9 of about minus .2. That means that a 10 percent 

10 increase in price would cause a two percent decrease in 

11 shipments. 

12 Now, we don't have good data on elasticities 

13 for clothes washers. Further analysis is needed and 

14 there is going to be a discussion of the consumer 

15 analysis later this afternoon and how that is going to 

16 be used to attempt to get elasticities. 

17 So, the interim results are that using just 

18 the accounting, projections are within 11 percent of 

19 historical total shipments based upon replacements and 

20 new housing construction. 

21 The new factors will be to include the 

22 economic factors through the elasticities. To factor 

23 in future energy prices. And the effect of new 

24 standards. 

25 The graphic on page 11 shows the projection 

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1 of clothes washer shipments. It is in the current 

2 spreadsheet. You can find this on DOE's website and 

3 download the shipments spreadsheet. And I put on here, 

4 to the left, the historical data. You will notice that 

5 started the forecast in 1981. This was a way for us to 

6 check whether the model was any good, whether it was 

7 tracking recent history or not. And it tracked the 

8 '80s pretty well. It is a little bit off at the 

9 current time. And then we have the future projections. 

10 Conclusions: Accounting for the replacement 

11 sales and new housing provides projections of future 

12 shipments. And I would add that they within about 10 

13 percent of actuals. And economic factors will need to 

14 be addressed and we propose to do that. 

15 Questions? 

16 MS. NADER: At the mike? 

17 MR. THIELE: Terry Thiele with Frigidaire. 

18 Did you have any explanation for that 11 

19 percent discrepancy in the most recent year? 

20 MR. MCMAHON: I don't. I would have to 

21 speculate. Clearly there is changes in sales from year 

22 to year, due to economic conditions. And we have not 

23 attempted to explicitly model those. 

24 MR. THIELE: Have you looked explicitly at 

25 exports? 

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1 MR. MCMAHON: Exports are excluded from this. 

2 This is domestic . 

3 MR. THIELE: All right. Well, but what I am 

4 saying is when you are taking total shipments, you are 

5 saying those are domestic shipments, those aren't 

6 shipments that --

7 MR. MCMAHON: That is correct. 

8 MR. THIELE: Shipments that involve Canada or 

9 Mexico or 

10 MR. MCMAHON: That is right. 

11 MR. THIELE: Okay. 

12 MS. NADER: Steve? 

13 MR. ROSENSTOCK: Steve Rosenstock, Edison 

14 Electric Institute. 

15 In terms of this also, there is another, in 

16 the technical support document there is also kind of 

17 the range of forecast. It is a nice chart showing the 

18 different ones, page 815. On the projection, I am 

19 looking at the projection and then I am also looking at 

20 the National Energy Savings spreadsheets. On, it looks 

21 like for both base case and the standard case, in terms 

22 of the column called new shipments, it is a flat 

23 increasing slope in the spreadsheet versus on this 

24 projection, a rise and then a plateau or slight 

25 decrease and then a rise plateau. It looks like as a 

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1 result, in the spreadsheet by 2030, it shows 9.08 

2 million units versus the projection here of about 8.2 

3 million. I hope I get ·that right or 8.3 million, 

4 maybe. So, there does seem to be a little bit of 

5 discrepancy in terms of the spreadsheet versus this 

6 graphic here. 

7 MR. MCMAHON: Let me, I am not sure about 

8 that. Let me check that with you. 

9 MR. ROSENSTOCK: Okay. 

10 MR. MCMAHON.: The intention is to eventually 

11 substitute it for whatever the best shipment 

12 projections are into the NES spreadsheet, once we have 

13 the economic factors in. So, we will be happy to 

14 correct that if there is an error there. 

15 MR. ROSENSTOCK: Yes. Spreadsheet shows flat 

16 increasing, it looks like the same, you know, steadily 

17 increasing slope versus projection of high and then 

18 flat or decline. 

19 MR. JONES: Earl Jones here, G.E. 

20 So, how will you use, well, first, do I 

21 understand that you are going to get information on 

22 consumer price sensitivity in these, the consumer 

23 exercise that begins this afternoon? 

24 MR. MCMAHON: That is correct. 

25 MR. JONES: Or at least part of the process . 

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1 MR. MCMAHON: Yes. 

2 MR. JONES: And then how do you bring that 

3 back into, into this shipment analysis? 

4 MR. MCMAHON: The intention is from that work 

5 to devise the elasticities, so, the sensitivity to 

6 purchase price and operating expenses. And then to use 

7 those elasticities together with, what the expected 

8 purchase price and operating costs will be in a base 

9 case and a standards case. 

10 MS. NADER: Any other questions? Yes? 

11 MR. BEST: Richard Best, Whirlpool. 

12 Jim, just some clarification here. You know, 

13 some interesting things have been happening in the 

14 markets the last two or three years. And you have 

15 mentioned refrigeration, that you had done a elasticity 

16 study and came out with a minus .2. I think it would 

17 be interesting to note that most people here would 

18 probably have noticed that in the market the real price 

19 refrigerators has been dropping over the past few 

20 years. Although, there has not been a great surge in 

21 volume of those products from the manufacturing side. 

22 And also that, there is something happening within that 

23 scenario in that people may not be actually paying a 

24 lot less, they may be shifting their purchases from 

25 what were lower featured models a few years ago, to 

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1 higher featured models today at the same price they 

2 would have paid, have paid a few years ago . 

3 MR. MCMAHON: Yes. 

4 MR. BEST: It is a little complicated to say 

5 that you are really comparing price change versus 

6 selection totally on apples to apples basis here. And 

7 I wonder if that had been considered when you did this, 

8 because certainly there is a lot of strange things have 

9 happened in the last recent period anyway. 

10 MR. MCMAHON: Yes, I agree with that comment. 

11 We have not done that kind of a study for clothes 

12 washers as yet. And we are looking forward to seeing 

13 what happens with the consumer analysis. For 

14 refrigerators we did do a retrospective study. It was 

15 published in 1997, looking back to the period from 1987 

16 to '93. The first two sets of National Standards for 

17 refrigerators. And, in fact, the prices did decline in 

18 real terms. And the quality and future of the product 

19 increased. So, I agree with what you are saying. And 

20 those things should be taken into account as best 

21 possible. 

22 MS. NADER: Yes. 

23 MR. BEE: Are we going to be studying or --

24 MR. BERRINGER: Microphone, please. 

25 MS. NADER: Speak up, please . 

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1 MR. BEE: Tom Bee, Staber Industries. 

2 I don't know if you are going to, if I missed 

3 something here, but are we going to go into more detail 

4 on the consumer economic factors that you have on page 

5 seven of your presentation? 

6 MR. MCMAHON: Not at this time. The intention 

7 is to discuss that in the consumer analysis later this 

8 afternoon. 

9 MR. BEE: Okay. 

10 MS. NADER: Okay. Thank you. 

11 Anymore questions for Jim? Jim, thank you 

12 very much. 

13 MR. MCMAHON: Okay. Did we want to address 

14 the issues of the energy price, future energy prices at 

15 this time? 

16 MS. NADER: Bryan, what was your thinking? 

17 MR. MCMAHON: Future energy prices, the energy 

18 price scenarios and in the '99. In the context of 

19 National Energy Savings Study. 

20 MS. NADER: Okay. 

21 Who had questions or comments on the National 

22 

23 

24 

25 

Energy Study? Is that what we are talking about now? 

MR. BERRINGER: Yes. 

MS. NADER: Yes. Okay. A number of people 

raised their hands earlier today as having interest in 

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1 the subject. Where are you now? 

2 MR. ROSENSTOCK: Wait, on the National Energy 

3 Savings spreadsheet. Steve Rosenstock, EEI. Or what, 

4 what topic are you --

5 MS. NADER: Somebody with a mike restate that, 

6 please. 

7 MR. NADEL: Bryan was just noting that we had 

8 raised some questions about AEO '98. The AEO '99 has 

9 just come out. We want to take a look at it, but we do 

10 have some concerns that, at least the AEO '98 has 

11 overestimated the decline to be expected in the 

12 residential energy prices that effectively, technically 

13 the same decline in residential, commercial and 

14 industrial prices when most observers, most we have 

15 seen on electricity prices, project greater declines in 

16 the commercial and industrial and smaller declines in 

17 ihe residential. We have not had time to look at the 

18 AEO Year '99. We just got it a couple of days ago. 

19 But, I hear through the grapevine that some, it started 

20 to address those problems, but there may still be. We 

21 will look 

22 

23 on that? 

24 

25 questions 

at it further and comment later. 

I 

MS. NADER: Okay. Thank you. Anything 

All right. Thank you. 

MR. MCMAHON: I am trying to address 

that I think were raised earlier. 

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1 does AEO '99 compare to AEO '98? And the other is what 

2 is the range of scenarios for future energy prices that 

3 ought to be used? And the Advisory Committee suggested 

4 that at least three scenarios, a high, low and mid, 

5 ought to be used. 

6 What we have done is assembly data from a 

7 variety of source of energy priced projections for the 

8 future. These are residential electric prices. They 

9 have all been turned into 1996 cent per kilowatt hour. 

10 This starts in the Year 2000 and goes out to 2015. And 

11 let's see what I can pick out in here. 

12 AEO '99 is blue with a circle. They are all 

13 clustered tightly together here. It runs through here . 

14 There is the dot there, runs through the middle and 

15 ends here. And AEO '98 is the close triangles. It is 

16 very close. The values are very similar, all the way 

17 through. 

18 So, AEO '99 is not significantly different 

19 from AEO '98. It is a little bit higher but very 

20 small. And obviously, these numbers are available. We 

21 can give them to you. 

22 The rest of the forecast from AEO high and 

23 low, economic growth, AGA forecast and GRI's forecast 

24 all fairly tightly clustered here together. Not much 

25 difference. 

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1 The two that are very different are from 

2 different parts of the Department of Energy. This is a 

3 policy office analysis of a high competition case for 

4 restructuring. And the other one is EIA, at the 

5 request of a committee of Congress, was asked to look 

6 at a carbon tax scenario, very high carbon tax. And 

7 that imposed a very high prices on the consumers. So, 

8 this is the set of projections that I think are 

9 currently on the table for consideration to select 

10 scenarios for the future. The Department has not come 

11 to any decision about what to do. And I don't know if 

12 you want to say anything more about that. I guess at 

13 this point it is open to comment . 

14 MS. NADER: Glenn Scheede. 

15 MR. SCHEEDE: I may have misunderstood, Mr. 

16 Nadel's comment, but I did want to point out that EIA 

17 for once on residential prices has been pretty accurate 

18 as far as their 1998 forecast on residential prices. 

19 Residential prices have come down in '98 for the first 

20 eight months by an excessive three percent compared to 

21 the comparable period, previous year. Residential 

22 prices are coming down even faster than commercial and 

23 industrial, so far in 1998. 

24 So, for once, EIA and residential is about 

25 right, for '98. 

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1 MR. MCMAHON: Could you repeat that, Glenn. 

2 You said that for once EIA is correct? 

3 MR. SCHEEDE: On residential. However, they 

4 managed to overestimate or excuse me, underestimate the 

5 rate of decline in commercial and industrial rates. 

6 Again, they have, they basically expect a one percent 

7 per year decline in the rates over a long period of 

8 time. However, they did correctly forecast that the 

9 rates for residential would drop sharply in '98 

10 compared to '97, because they looked at what is 

11 happening in California and the Northeast. 

12 MS. NADER: Okay. Steve? 

13 MR. ROSENSTOCK: Steve Rosenstock, Edison 

14 Electric Institute. 

15 I can't count from here, it looks there is 

16 about eight or nine different pricing scenarios on 

17 that. 

18 MR. MCMAHON: There are nine. 

19 MR. ROSENSTOCK: There are nine, okay. 

20 Thanks. 

21 Am I to assume that you are going to try to 

22 include all nine on the future, on the future life 

23 cycle cost spreadsheets? Because right now they are 

24 four, AEO, GRI, I forget the other two, high growth, 

25 low growth, you know, right now there is like four 

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1 default ones on the, as I recall on the spreadsheets. 

2 Are you going to try to include all nine on future 

3 ones? 

4 MR. MCMAHON: Steve, I am just the contractor. 

5 It is up to the Department to decide which scenarios 

6 are going to go on there. 

7 MR. ROSENSTOCK: Okay. Question to the 

8 Department of Energy, I guess, it goes for as well as 

9 gas and oil prices, too, are you going to try to 

10 include for electricity, gas, and oil, like nine 

11 different defaults scenarios? I will just call that 

12 for lack of better, nine different defaults projections 

13 for each fuel source? 

14 MR. BERRINGER: No, we have no intentions of 

15 running all the scenarios, just choosing one of the 

16 best, best ones to run. They are representative. 

17 MR. ROSENSTOCK: And when we will hear about 

18 which ones are "the best onesu. Steve Rosenstock, EEI. 

19 MR. BERRINGER: And also as -- stated, the 

20 high and low, so you have a range. 

21 MR. ROSENSTOCK: So, Steven Rosenstock. Am I 

22 to assume that what EIA has shown is going to be the 

23 high end of the range for electricity, gas and oil 

24 assuming the carbon taxes over the next, you know, 20 

25 years or so? 

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1 MR. BERRINGER: There is no decision, no 

2 decision has been made at this time, but that is, I 

3 mean, it would be, I guess how likely that carbon tax 

4 would be, if consider an all likelihood. 

5 MR. ROSENSTOCK: Okay. Thank you. 

6 MS. NADER: Thank you. 

7 Anything more before we let Jim sit down? 

8 Thank you, thank you, Jim. 

9 Our next presenter is Steve Grover, who is 

10 with Quantum Consulting. He is going to talk to us 

11 about the Consumer Survey he is undertaking. I have 

12 suggested to him that he go through his entire 

13 presentation and any questions that come up beyond just 

14 a few, we should probably defer to later this· 

15 afternoon, between 4:30 and 6:30. Steve will be 

16 available and will have time to go through, go into 

17 much more detail. 

18 PRESENTATION BY STEPHEN GROVER: 

19 MR. GROVER: All right. Thank you. 

20 All right. Well, this is the first time I 

21 have been in front of this workshop discussing what we 

22 are planning on doing for the long awaited consumer 

23 analysis portion of the study. 

24 In the objectives of the consumer portion of 

25 the analysis are to, the first is that we want to 

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' 1 determine which attributes are viewed by consumers as 

2 being the most important in selecting a clothes washer . 

3 Once we determine which attributes are most important, 

4 then we can move on to the next phase, which is 

5 examining how will changes in these attributes affect 

6 the decision to make a clothes washer purchase. Or how 

7 will changes in these attributes shift purchases from 

8 standard efficiency to high efficiency. 

9 Along with this objective then, is an effort 

10 to focus also on those attributes that are most likely 

11 to be affected by the standard and also we are 

12 designing this, looking forward to being able to 

13 calculate elasticities which will then be used down the 

14 road in some of the work that LBL is doing. 

15 What we have then is basically a two prong or 

16 a two method approach here for gathering data. All 

17 right. So, again with the objective of looking at 

18 customers and determining their attributes, what we 

19 want then is a nation wide sample of customers, 

20 ordinary customers and what we want to do is first look 

21 at focus groups to elicit from them what are the 

22 attributes that are most important. What are they 

23 really look at when they are making a decision to make 

24 a purchase. Once we whittle this down to the most 

25 important, we are looking at six to eight features, 

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1 perhaps. Those attributes will be fed into the 

2 Conjoint Analysis. And the Conjoint Analysis will be 

3 used ultimately for a statistical analysis to determine 

4 the elasticities and some of the marginal effects of 

5 changes of attributes. So, I am going to go through 

6 both what is going on with the Focus Groups, as well as 

7 describe in more detail what goes on with the Conjoint 

8 Analysis, which I am guessing not as many people are 

9 familiar with Conjoint as they are with Focus Groups. 

10 But, to start off with the Focus Groups, we 

11 are looking at holding focus groups in five distinct 

12 geographic areas. We want to focus on a national 

13 representative sample of different regions in the 

14 country. And focus groups involved recruiting people, 

15 having them come together. There is a moderator. What 

16 this moderator will do is lead a discussion on what is 

17 important in picking out a clothes washer. All right. 

18 So, the group will start with the moderator guiding the 

19 discussion, trying to get unsolicited opinions on what 

20 is important to clothes washers. So, basically the 

21 first part of the session will be groups are allowed to 

22 decide what is important. 

23 At the end of that time, once it appears that 

24 most of the unsolicited characteristics have come, have 

25 been presented, the moderator will suggest other 

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1 characteristics that haven't come up. You know, for 

2 example, if we go for an hour and nobody brings up the 

3 issue of top loading versus front loading, for example. 

4 The moderator will throw that out and give, let the 

5 group gauge their opinion. 

6 At the end of this time, we will have each 

7 person within the focus group list out of all the 

8 characteristics that have come up, rank the list, so we 

9 can get an order, rank order of what is important. 

10 The way that we have designed this, then, is 

11 we are looking at 10 different groups, with somewhere 

12 between eight and 12 participants. We are looking at 

13 doing 10 sessions, two in each city selected in the 

14 country. We have chosen five cities here, Washington, 

15 these are our initial cities, anyway, Washington, 

16 Madison, or Milwaukee area, Wisconsin, Dallas, San 

17 Francisco and Miami. To get a nice spread across the 

18 regions. 

19 We will be looking at collecting a diverse 

20 group of samples, diverse group of respondents to be in 

21 the sample, all right. So, we want to get a broad 

22 range of demographics, things like age, income, and 

23 participants will also be paid $50.00 a piece. All 

24 right. So, this will be taking place in January. Once 

25 we determine then from this, by looking at the 

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1 sessions, we will have a total of 100 people, more or 

2 less for the focus groups used to feed into the 

3 Conjoint Analysis. Okay. And what Conjoint Analysis 

4 is, it is somewhat similar to focus groups, in that 

5 people are recruited and they come to a session, and 

6 they are given a deck of cards to sort through. And I 

7 have a set here. I have a set with me, anyway, I 

8 should say. But, the deck of cards is each card 

9 represents a different washing machine. And on each 

10 card the characteristics are listed that are determined 

11 from the focus groups. All right. So, what respondents 

12 do is take these cards and rank them in the order of 

13 their preference. They are told that they should sort 

14 through the cards as if they are definitely going to 

15 purchase a washing machine and now they are sorting 

16 through their available options at the store. All 

17 right. So, the most preferred one goes on the top, the 

18 least preferred goes on the bottom. And so, again, 

19 each washer is described by washer characteristics 

20 determined by the focus groups. So, for example, if 

21 the focus group's determination was that a price 

22 savings, horizontal versus vertical axis orientation 

23 and clothes washing temperatures are, you know, say the 

24 foremost important, each of those characteristics would 

25 be on each card with varying levels os price, savings, 

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1 axis orientation listed. And what people would do 

2 then, is rank. And what this forces people to do then 

3 is to evaluate which characteristics are important. 

4 That as they would when they go to the store, 

5 and they look at issues where, you know, I need this 

6 higher capacity, I would like to save money on my 

7 electricity and my water bills, but this is going to 

8 cost me more. All right, so what is my cutoff point? 

9 What is my tradeoff point? 

10 Well, in the meantime, I found my cards. 

11 These will be available for people to look 

12 at. This is mock up of just some attributes. These 

13 ranges are just meant for an example. So, please, if 

14 you look at these, do not think by any means that this 

15 what the study is going to look like, but it will give 

16 you an example of what people have to do to sort 

17 through the cards. 

18 Okay. So, there is a variety of 

19 characteristics listed on the card. People, the value 

20 of Conjoint is that people have to trade off against 

21 different equipment characteristics. 

22 Once they have ranked the cards, then we ask 

23 the question, given your situation today, given the 

24 situation in your home, which of these options would 

25 you actually purchase. And then they are given an 

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1 additional card that we call purchase card, where 

2 people make a cutoff at the ranked cards, to show which 

3 ones given their situation today, they would actually 

4 purchase a washing machine. So, for example, if you 

5 just purchased one the day before you went to the 

6 Conjoint session, you probably won't purchase any of 

7 the other ones today. If you are thinking about 

8 purchasing one in your future, some of tpese options 

9 would be attractive. 

10 And this gives an idea of some of the 

11 potential demand, which becomes important later on. 

12 As with the focus groups, we are looking for 

13 a national sample here. We are going to be recruiting 

14 400 people across four different cities. We would like 

15 the cities to coincide with the ones that are being 

16 done in the focus group, minus one city. But, this 

17 helps, you know, preserves the regional nature of the 

18 data. So, we are looking for 100 participants across 

19 four cities, Washington, Madison, San Francisco, and 

20 Dallas. 

21 We will be recruiting people by phone. 

22 People may be familiar with kind of mall incept 

23 Conjoint. We will be doing it by phone. It allows us 

24 to control a bit more of the sample. It ensures a 

25 random sample. One thing I do want to make clear is 

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1 that we are not looking for representative sample of 

2 the population. But, we are having a random sample 

3 that will be stratified perhaps depending on what comes 

4 out of the focus groups, but we are going to be looking 

5 at getting a good representative sample among some key 

6 demographics. Perhaps, income, age, getting a good 

7 male, female mix for the sample. And this will allow 

8 us along with the regional data, to try and do some 

9 analysis across key demographic groups, to see if there 

10 is any variation there. 

11 Also included in the sample will be at least 

12 a portion of the people that recently purchased a 

13 clothes washer. And what this, what this will do is 

14 get input from people that have recently gone through 

15 the spot process. And this will be fresh in their mind 

16 and they will understand, you know, well, I just did 

17 this, what was important to me when I was at the store. 

18 We can't have an entire sample of this, because in one 

19 sense we are using this data to at least get a sense of 

20 the likelihood of making a purchase. So, we can't have 

21 an entire sample of people who have just made a 

22 purchase. 

23 With the, as with the focus groups, Conjoint 

24 participants will be paid a $50.00 incentive to 

25 participate as well. And these are anticipated to be 

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1 conducted in February. 

2 Now, a little bit about the Conjoint and I 

3 apologize if I race through, what exactly goes on in a 

4 Conjoint session, but I will be more than happy to 

5 discuss it later. There are several different 

6 advantages of Conjoint that makes it a very attractive 

7 for this situation. 

8 The first is that Conjoint is the one state 

9 preference technique that really lays out different 

10 equipment characteristics at the same time. And this 

11 mirrors as closely as possible the type of decision 

12 process that people go through in the store. All 

13 right. And this is contrast to more of your, more 

14 familiar survey questions where the phrased question 

15 is, you know, would you be willing to be pay $800.00 

16 for a clothes washer that saved you, you know, $50.00 a 

17 year on your electricity and water bills? Or would you 

18 be willing to pay an extra $100.00 if you knew that 

19 this washer would save you $20.00 a year in your 

20 electricity and water bills? Those are kind of a take 

21 it or leave approach and they are somewhat removed from 

22 reality when they are done over the phone. In this 

23 context when people do Conjoint, when they are given 

24 the time to really sit down and think about it, as if 

25 they were actually purchasing a washer. And my 

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1 experience has been that this has helped provide 

2 accurate results when we have used the results to try 

3 and predicate purchases of appliances, especially 

4 compared with actual market data. 

5 Another good advantage of Conjoint is that it 

6 allows a wide range of statistical techniques to be 

7 used on the data later on. In general what is done is 

8 that in the statistical model, the rankings of the 

9 cards are regressed against the card characteristics. 

10 So, if we had the same characteristics, price, savings, 

11 axis orientation, and water temperature, as your four 

12 characteristics, we can model how changes in those 

13 characteristics change the rankings of the cards on the 

14 individual level. 

15 And what this allows us to do then later is 

16 to use this, these estimates of the effect of these 

17 attributes, can be used in a variety of ways. We can 

18 look at what is the likelihood that somebody is going 

19 to purchase a clothes washer? We can estimate the 

20 probability of given that, they decided to purchase a 

21 clothes washer, what is the likelihood that they will 

22 choose a standard efficiency versus high efficiency 

23 option. We can develop a choice set of all different 

24 types of clothes washers, different capacities, 

25 different axis orientation, different prices, different 

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1 savings estimates. Whatever, whatever the 

2 characteristics that were used in the Conjoint, could 

3 be used to develop choice set. And we can look and 

4 estimate purchases or estimate the likelihood of making 

5 a purchase of all these different characteristics. 

6 So it really does provide a wide range of 

7 opportunities. 

8 And finally, once we estimate a purchase 

9 probabilities, these can be calibrated to some of the 

10 actual market data. So, what we can look at is we can 

11 take the stated preference nature of the data, and join 

12 it with some of the actual observed market behavior. 

13 And so, what we are taking, in essence what this is, is 

14 that we are not asking the stated preference data to do 

15 too much. That we are taking away the tradeoff nature 

16 that we learned, from the controls experiment and we 

17 are grounding in real market data, and real purchase 

18 estimates. So, we can get a sense of where we are 

19 starting in the market. So, we have a baseline 

20 starting point that is ground in real market data. And 

21 then we move forward from there. 

22 Ultimately, as I alluded to, the Conjoint 

23 Analysis will be used to estimate 

24 

25 

Have I not changed this in the last three? I 

am sorry, I apologize. 

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1 We are on the last slide, by the way. Off 

2 in my own world up here. 

3 The Conjoint data will be used to estimate 

4 purchase probabilities. As I mentioned, both the 

5 likelihood of making any clothes washer purchase as 

6 well as we can look at high versus standard efficiency 

7 or we can take any one clothes washer configuration, 

8 based on the characteristics in the Conjoint, and 

9 estimate the probability that that washer will be 

10 chosen. 

11 Once these probabilities are estimated, then 

12 we can look at how the likelihood of purchases will 

13 change in a variety of different methods. And, again, 

14 there is a lot of flexibility here. 

15 One is we will be looking at calculating 

16 elasticities to feed in some of the work that LBL is 

17 doing. The other is just looking at the estimated 

18 probabilities and asking the question, well, if there 

19 are two ways to meet the standard, one is an axis 

20 orientation, versus one is some combination of capacity 

21 or water temperature, let's look at two comparable 

22 equipment configurations that both meet the standard, 

23 and what are, is there any difference and effect on 

24 purchases, or estimated likelihood of purchase. All 

25 right. So, we can address those types of questions. 

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1 We can also look at just individual 

2 attributes. You know, how much do changes and axis 

3 orientation effect purchases. How much does estimated 

4 savings alone change purchases? How much does dropping 

5 the hot water option change purchases? These things 

6 will be evaluated individually. 

7 Ultimately, we can also look at holding price 

8 constant. That in a scenario where if there 

9 presumably, how to phrase this. If price increases off 

10 the board, across the board for all options, then what 

11 we might want to do is hold price constant or drop 

12 price from the equation and just look at how do changes 

13 in probability, how do changes in other attributes 

14 affect this probability. All right, so we will look at 

15 it two ways. One an absolute change, when we take into 

16 account a change in price. And second, holding price 

17 constant across choices, and just looking at how 

18 changes in the other attributes that need to be changed 

19 to meet the efficiency standard. How will those 

20 changes affect the likelihood of making a purchase? 

21 And which are the more sensitive issues? So, all these 

22 things can be taken out from the Conjoint data. 

23 Okay. So, that is a brief overview. There 

24 is more of a detailed description included in there for 

25 the technical approach, that I would encourage you to 

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1 read.· And then later on, I will be available to answer 

2 things as well . 

3 MS. NADER: Thank you, Steve. 

4 Steve will be available in the room across 

5 the hall from 4:30 to 6:30. And so, I ask that any 

6 questions you have or comments you save until then. 

7 We are running a little bit behind schedule. 

8 MR. BERRINGER: Address any comments in this, 

9 that is just a working group. Everybody is --

10 MS. NADER: Oh, all right. 

11 MR. BERRINGER: For the record, I think they 

12 should have their questions addressed now. 

13 MS. NADER: Okay. Briefly, then, please. 

14 MR. SCHEEDE: I was going to ask a procedural 

15 question. Will there be official record of that 

16 meeting or if there will be, then I will save my 

17 question until then, if not, I would like to get two on 

18 the record now. 

19 MR. BERRINGER: We were not planning to have a 

20 court reporter or anything at that meeting. So, this is 

21 the opportunity if you want to put it on the record. 

22 MR. SCHEEDE: Okay. Two questions. 

23 First one, how will the stage be set, what 

24 kind of data will you be providing in terms of telling 

25 the people in the focus groups, and in the Conjoint 

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1 Analysis, what their expectations should be as far as 

2 energy cost savings or water cost savings. How do you 

3 set the stage for that, and what kind of data will you 

4 be using to set the stage for that? How much of, how 

5 are you going to predict savings? 

6 MR. GROVER: Right. It is an interesting 

7 question because on one hand you need to inform 

8 consumers, especially if you are trying to recreate 

9 what is going on in the market. And on the other hand, 

10 you don't want to guide the discussion too much. We 

11 will be providing both with, if cost and savings are 

12 used as attributes, we will have probably three, maybe 

13 four different levels of savings levels and price 

14 levels. Basically, these levels are chosen to run the 

15 range of standard efficiency to high efficiency. So, 

16 what we want to do is provide a price range, and a 

17 savings range that bound all the realistic options with 

18 a little bit of an overlap, just to be safe. So, you 

19 know, savings would be, the maximum, the zero savings 

20 would be for standard ·efficiency and the maximum 

21 savings would be, you know, whatever the highest 

22 estimated savings you could anticipate under any 

23 situation for a clothes washer. 

24 MR. SCHEEDE: Well, you will do something for 

25 those of us who are worried about the average cost, you 

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1 are not reflecting marginal costs, thinking that is too 

2 high. Are you going to have some low end of the range 

3 in terms of what the savings should be expected? 

4 MR. GROVER: The low end of the range of 

5 savings would be zero. It is going to be savings 

6 relative to purchasing a standard efficiency. So, we 

7 need to include standard efficiency characteristics in 

8 the Conjoint as well as high efficiency 

9 characteristics, because that still would be an option. 

10 And we need, what we want to do ultimately is gauge 

11 what is the effect of the standard? So, the study has 

12 to be set up to include both standard efficiency and 

13 high efficiency equipment designs . 

14 MR. SCHEEDE: Okay. I will save the rest of 

15 that one for later. 

16 The other question, what kind of data do you 

17 have available to show that the findings from this kind 

18 of an analysis reflects the real world? And closely 

19 related to that, is this the kind of analysis that 

20 appliance manufacturers and retailers actually use to 

21 do market analysis? Could you comment just on those 

22 two things? 

23 MR. GROVER: Yes, this is something, there 

24 is a broad range of literature available on this. Also 

25 I have done some work with the utility evaluating 

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1 appliances, specifically air conditioners, using the 

2 same thing, has predicted very well. But, this is 

3 something, another advantage of Conjoint is that when. 

4 you do these cards, you can include features and 

5 characteristics that do not exist. That, for example, 

6 assume that there is, there was there horizontal axis 

7 machines available, we could put that into the Conjoint 

8 and still gauge people's opinion about these things and 

9 figure out the trade off. And so, for that reason, it 

10 is very popular for companies to test products that 

11 haven't existed, that don't exist yet, that they are 

12 thinking about introducing. 

13 MS. NADER: Okay . At the mike? 

14 MR. GREGG: Yes, Tony Gregg, City of Austin. 

15 I am not really that familiar with this 

16 analysis, so I just had a couple of questions. 

17 One, the five areas you have picked, appear 

18 to be areas, at least from my knowledge, that don't 

19 have any aggressive marketing efforts by utilities. I 

20 might be wrong on one maybe. But, at least four of 

21 them don't appear to. So, my sense is if you picked a 

22 population from those cities, will you be getting, the 

23 people will not have had the benefit of maybe some of 

24 the other reasons to buy H axis machines, if that is· 

25 the intent of this survey. And I am wondering, you 

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1 know, should you be going to someplace like Seattle, as 

2 a separate experience to see what the difference there 

3 between Seattle and say somewhere, where there is no 

4 program or several places. 

5 MR. GROVER: Well, two things. First, is 

6 that we will be presenting information to people, 

7 especially at the Conjoint, giving them some background 

8 on, you know, the pros and cons of the high efficiency 

9 designs. So, they will have some information available 

10 addressing that. 

11 As far as the cities go, they have been 

12 picked primarily to make sure that we have a good 

13 spread across five different regions. And they have 

14 also been picked to help maximize our resources since 

15 we have familiarity in these areas. And we have people 

16 working those areas. 

17 My understanding also was that it is desired, 

18 that there was some work done in the Northwest already 

19 and we wanted to move towards more of a national 

20 sample. Relative merits of one city versus another. 

21 You know, we are not wedded to these particular cities. 

22 But, we want to make sure that it is a national sample, 

23 though. 

24 MR. GREGG: I guess, I mean, related to that 

25 is why do people buy H axis machines and I guess I am a 

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1 little concerned that that might _not come out just if 

2 you look at features and costs. Yeah, that is the 

3 primary selling point, but you know wash wise in the 

4 Northwest, you know, it is, I forget what one of the 

5 slogans is but it is good for the environment, a better 

6 world. Clearly, people buy and the Maytag is an 

7 excellent machine, but they are not buying it probably 

8 for the cost savings or people who buy Frigidaire might 

9 be. So, I mean, there are other, I am not trying to 

10 put -- I am just saying the price is lower. 

11 MR. GROVER: One thing that we want to 

12 emphasize in the Conjoint, is that brand names will not 

13 be used. They will be driven just by the physical 

14 characteristics of the washing machine. And we are 

15 going to rely on the focus groups. And one thing about 

16 this, is, you know, it would be relatively easy for us 

17 to, I believe come up with six or eight attributes that 

18 we think should be important, but, you know, assuming 

19 that people go and have some degree of awareness and we 

20 inform them on, you know, environmental, the 

21 environmental benefits of this, the savings. You know, 

22 we don't want to dictate to them that they should be 

23 purchasing this because it is friendly to the 

24 environment, if they, you know, either they will know 

25 that from looking at the savings or they won't. But, 

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1 we have to be careful not to, you know, kind of skew 

2 the results . 

3 MR. GREGG: Well, you know, I am not trying, 

4 yeah, I am just saying that the outside influence may 

5 not be there just depending on what, it may be 

6 different if you get something· from your city or if you 

7 believe in the energy star program or something like, 

8 some marketing effort that is going on. It is 

9 different if they have already gotten that from an 

10 outside party, then maybe they hear for the first time, 

11 you know, what are some of the environmental benefits. 

12 I am just saying maybe there would be a way to do a 

13 little bit in both markets . 

14 MR. GROVER: Right. Okay. We will 

15 definitely. 

16 MS. NADER: Thank you. Bryan? 

17 MR. BERRINGER: I would just like to follow up 

18 on what you are stating. What came out of the last 

19 workshop, we have done a lot of research. It has 

20 already been done. Obviously, there is Thelma, Bern, 

21 and Washwise. So, we have been given those results. 

22 What was commented at the last workshop is specifically 

23 those are areas that have received rebates or they have 

24 given the machines free. So, we are looking to do a 

25 more national sample of an average consumer. And we are 

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1 not looking in particular rebate being one. But, 

2 obviously the focus groups, you know, we are not trying 

3 to bias the focus groups at all. We want them to tell 

4 us what is important to them. 

5 MS. NADER: Thank you. 

6 Steve and then the gentleman at the mike. 

7 MR. BERRINGER: He was first. 

8 MS. NADER: Oh, thank you. Correct, my 

9 apology. 

10 MR. BARZEL: Dan Barzel, Circuit City. 

11 Bryan, I support your premise that it is 

12 better to have an objective sample and to spite your 

13 argument, Gentleman from Austin, you are not going to 

14 get a true picture if you sample people who have been 

15 marketed on a particular product. So, you are better 

16 off, I think, with a more objective sample that hasn't 

17 been marketed in a city that hasn't had a program 

18 going, because it is going to give you a better 

19 indicator. 

20 One of the questions Glenn asked was do 

21 retailers and manufacturers use Conjoint Analysis. I 

22 have seen manufacturers use Conjoint Analysis to 

23 develop what people will pay for particular features 

24 and the trade offs among features. And generally 

25 speaking, I would say, it is better to approach the 

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1 problem of what people will pay and whether they will 

2 pay money for a feature, through an objective study 

3 like trade off, than it is not to have any data or to 

4 use conjecture or to use bias sorts of samples, where 

5 you ask The most difficult thing to determine when 

6 you are in the situation is when the person is standing 

7 at the cash register, ready to buy, will they actually 

8 take the money out of their wallet? And because you 

9 can't really measure that unless you are in the 

10 position that we are in, which is actually making the 

11 sale. You have to use the next best thing, and I would 

12 say that this is probably, if it is done properly, and 

13 objectively, and use a big enough sample, and you are 

14 doing it across enough tjifferent areas, this is 

15 probably the next best thing. 

16 And whether, the question of whether 

17 retailers use it or not, probably not. Because people 

18 who buy this product and watch sales rates, can play 

19 with the elasticity every day. We can drop prices on 

20 products and raise prices on products independently and 

21 see what happens to the elasticity or the volume. So, 

22 we don't do any and I doubt that a lot of retailers do, 

23 maybe one or two do it. But, it is a fairly expensive 

24 thing to do when you can get it virtually for free by 

25 playing retail pricing across markets or across the 

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1 country. 

2 But, I think done properly, your approach 

3 seems to be appropriate. 

4 MR. BERRINGER: Thank you. 

5 MS. NADER: Thank you. Steve? 

6 MR. ROSENSTOCK: Steve Rosenstock, Edison 

7 Electric Institute. 

8 Just to comment on the cities that I would 

9 have to say, just kind of from my recollections, 

10 Madison, Wisconsin, well, I know that San Francisco, 

11 California, Pacific Gas and Electric, please correct me 

12 if I am wrong, I am pretty sure they are currently 

13 issuing rebates for high efficiency washing machines . 

14 Ted, is that correct? 

15 MR. GREGG: Yeah, in San Francisco. 

16 MR. ROSENSTOCK: In San Francisco. 

17 MR. GREGG: Plus 

18 MR. ROSENSTOCK: Include San Francisco. 

19 MR. BERRINGER: Excuse me, could you make your 

20 comments to the mike, please? 

21 MR. ROSENSTOCK: Sorry. 

22 MR. GREGG: Yes, PGE does provide rebates for 

23 purchasing an efficient clothes washers. And 

24 additionally, some of the water utilities within our 

25 service territory also provide additional funding, as 

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1 well as outreach in marketing. 

2 MR. ROSENSTOCK: So, in that case, it is kind 

3 of a double whammy of both energy utilities as well as 

4 the water utility marketing and promoting certain 

5 product. I am just talking in terms of potential 

6 consumer knowledge or bias in the focus groups. 

7 I don't, it might be in Wisconsin. I don't 

8 know if the utilities there. T know the, in the past 

9 the utility in Wisconsin had a pretty aggressive, 

10 again, man type manager programs, whether they included 

11 washing machines, I am not exactly sure. But, I 

12 wouldn't be surprised in Wisconsin that if they did. 

13 In Washington, D.C., they did not. They had 

14 aggressive programs, Pepco did, but they did not 

15 include washing machines. 

16 I just wanted to address that in terms of, 

17 you know, in terms of city selection that, two out of 

18 the five cities had or have aggressive programs 

19 addressing -- Definitely one possibly, probably two had 

20 aggressive programs for this product. 

21 MS. NADER: Thank you. At the mike? 

22 MR. ECKMAN: Tom Eckman, Northwest Power 

23 Plant Council. 

24 

25 

Two comments. Coming from the Northwest, 

maybe this is going to sound a little parochial, but I 

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1 think it would be at least interesting and probably and 

2 of merit to test the differences between an area that 

3 has advocated these types of machines for some period 

4 of time, and areas where they haven't, to see whether 

5 there are differences in the values associated with 

6 various characteristics of the machines. 

7 And secondly, I think Dan Barzel's suggestion 

8 that they do price elasticity tests weekly, in every 

9 Sunday ad, would be a really good way to get this 

10 information with the empirical data, because I think 

11 that is probably the right place to test it. So, maybe 

12 something can be worked out with some of the retailers 

13 to get that information . 

14 MR. GROVER: One comment about the cities. 

15 I mean, in one sense when we get to the Conjoint 

16 session, there will be information provided that in 

17 essence will level the playing field as far as people 

18 that have, came to the meeting aware, unaware of the 

19 benefits of high efficiency. 

20 And the second is that given the amount of 

21 promotion that has been going on nationally, that 

22 awareness is not going to go away. And it maybe useful 

23 to look at, you know, if that is a substantial part of 

24 the population, then you know, it maybe useful to look 

25 at them in the Conjoint session as well. 

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1 But, that is definitely something we will 

2 take into consideration . 

3 MS. NADER: Okay. I saw a hand over here. 

4 Yes, Richard? 

5 MR. BEST: Richard Best, Whirlpool 

6 Corporation. 

7 Since this is the only chance we have to, you 

8 know, publicly comment on this and I hope, you know, 

9 following your session later, we will still be able to 

10 input to DOE on this. But, I hope we are not losing 

11 focus of the whole intent behind this. And the intent 

12 of this whole price elasticity issue is to determine 

13 whether that price effect is on shipment volumes and 

14 other attributes of this rule, when the rule takes 

15 effect. And that is going to be in the absence of 

16 incentive programs. So, I think some of the comments 

17 here were well in line with that issue. Maybe it would 

18 be nice to know, but when we have a rule, it is going 

19 to be based on a non incentive market, the rule itself 

20 and those effects. 

21 And the second is I have a concern, our 

22 company does a lot of these type of studies and 

23 analysis and we know very well the benefits as well as 

24 the pitfalls of conducting these types of studies and 

25 surveys. And one of the biggest pitfalls is not 

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1 looking correctly at the right attributes. And in this 

2 case, the attributes are important, are those that 

3 affect this rulemaking, not the manufacturers' design 

4 decision on how to meet those rules. And so, if you 

5 are asking consumers do they want to pay more, $50.00 

6 more or $100.00 more for the door in the front or the 

7 top, or what size knob they have or whether it should 

8 be 22 inches wide or 28 inches wide, I think you are 

9 missing the boat. The attributes will be met by 

10 manufacturers in different ways. And what we do in our 

11 studies as to what, what the consumer really is willing 

12 to pay for from the feature side. So, I would just 

13 like to make that comment . 

14 I think it is very important that this next 

15 hour or two in your session that the manufacturers and 

16 others convey their intent here and also convey to you 

17 what those attributes are. 

18 MR. GROVER: Yeah, one comment about that is 

19 with the Conjoint, our experience has been that the 

20 best tradeoff information, the most accurate tradeoff 

21 information is, as you said, you need to include the 

22 attributes that are important to the consumer, in 

23 making the decision. And if, I would anticipate that 

24 those would generally be in line with the attributes 

25 that are likely to be affected by the standard. But, 

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1 in the sense that they diverge, if one of the 

2 attributes that is being changed, such as perhaps knob 

3 size, or, you know, whatever. Say, if that was meant, 

4 you know, something that people don't care about, but 

5 has a price effect, if we have to, if we include that 

6 in the study and drop something that is important, more 

7 important to the consumer, we are going to get suspect 

8 tradeoff information. And it is going to make it less 

9 accurate. 

10 MS. NADER: Richard? 

11 MR. BEST: Just to reply to that. I think 

12 early on in this rulemaking we moved away from the 

13 design option approach to writing the rule. And all of 

14 the data that was input for the analysis was put in, in 

15 a form with aggregated data, but not with design 

16 options. And a lot of this attribute study seems to be 

17 moving back towards the design pption approach. No 

18 one, there is no intent that I know of in this rule to 

19 dictate to manufacturers how they would meet a rule. 

20 MS. NADER: Thank you. Bryan? 

21 MR. BERRINGER: Just to follow up, Dick, two 

22 things. There will still be an opportunity to comment 

23 up to February 2nd. 

24 Second is we are not, we are looking at the 

25 utility issues from that standpoint, too. And since 

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1 that is a major thing, and the price. So, I mean, it 

2 is really, it is not to get to the design option. That 

3 is not our intent. And our intent is to answer the 

4 questions that have been brought up as far as the 

5 utility issue more or less. And also as far as the 

6 price elasticity. 

7 MS. NADER: Okay. At the mike? 

8 MR. POPE: Yes, Ted Pope with PG&E. 

9 A few years back when we had the Thelma 

10 Research Project, we did sort of a quasi Conjoint 

11 analysis as well as focus groups. And that data is 

12 available. 

13 But, I guess, Bryan is sort of confirming my 

14 question, the results of this will be used not only to 

15 understand purchase intent but also to try and 

16 characterize consumer utilities, is that correct? 

17 MR. BERRINGER: Yes. 

18 MR. POPE: Okay. Just, one little nitty 

19 thing that could be a bigger issue and that is we found 

20 that in the focus groups and we had a demonstration 

21 where people came in one by one and were able to use 

22 certain front loading machines for an hour. That their 

23 perception of convenience, i.e. bending over, changed 

24 radically in a very short period of time. And was more 

25 negative when they had no idea of what a horizontal 

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1 axis front loading machine looked like. And when they 

2 had a little bit experience, in the case, a real owner 

3 who is determining his utility over time, that opinion 

4 changed pretty dramatically. And so, I am hoping there 

5 is some way that factor could be accounted for, if in 

6 fact, during the focus groups, you know, front loading, 

7 horizontal axis comes up as, you know, key attribute. 

8 So, that is a real time sensitive factor there. 

9 MS. NADER: Okay. David? 

10 MR. GOLDSTEIN: David Goldstein, NRDC. 

11 Another possible issue with the Conjoint 

12 Analysis. You could use it for a lot of things in this 

13 rulemaking. One of the things you could use it for is 

14 to analyze what consume~s would do after a standard is 

15 in place. And it is important that the consumers come 

16 in with polluted perspective in the sense of being 

17 exposed to options that aren't going to be there after 

18 the standard really exists. In other words, it is one 

19 thing to ask what would you do if you had a choice 

20 between a low efficiency and a high efficiency model, 

21 and that clues you that there is a low efficiency, 

22 cheaper model that exists. And someone after a 

23 standard and is going to walk into the showroom, they 

24 probably haven't looked at a washer since the last time 

25 they brought one 15 years ago, they won't know what the 

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1 price of the low efficiency model was, and they won't 

2 know what it looked like. And you can probably handle 

3 this through the study design, but it is important that 

4 phantom choices not be available. Because choices 

5 aren't transient. You can have weird situations where 

6 if the choice is between A and B, a consumer chooses A 

7 but if you expand the choice to include A, B and C, the 

8 consumer prefers B. 

9 MR. GROVER: One comment about that is that 

10 the Conjoint is designed so we can estimate a tradeoff 

11 of say price versus other attributes. And what we do 

12 is provide a range of prices that are likely to 

13 correspond what they will see after the standard. So, 

14 if we have A, B and C, you know, A is the low, and C is 

15 the high price, as long as the prices that we use in 

16 our model are between A and C, then we have already, 

17 through the analysis, have already covered, you know, 

18 how people react to prices within this range. And then 

19 when we go to construct a choice set later on, you 

20 know, that has in sense already been taken care of 

21 through the process. Where we get in trouble, is if we 

22 plan for a range of A to C and then have D, which is 

23 higher, you know, outside this range. And then we get 

24 into more shaky ground trying to estimate outside of 

25 what the study was designed for. 

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1 MS. NADER: At the mike? 

2 MR. LINARD: Jack Linard. 

3 I find it amazing that you have given this 

4 whole presentation and not once mentioned the 

5 performance of the machine. The idea is to clean 

6 clothes and care for clothes. Nowhere do you indicate 

7 whether any of these design options actually will 

8 change that performance. I can tell you right now, 

9 some of them you have already mentioned, will, in fact, 

10 change the performance but for better or worse. As an 

11 example, we have known for years if eliminate hot water 

12 inlets in the washing machines) you get great energy 

13 figures, but your cleaning performance is really 

14 horrible in many cases. So, I was just wondering what 

15 you are going to do to give an indication of what the 

16 tradeoff would be in terms of performance. 

17 MR. GROVER: That is a tricky issue that we 

18 have discussed about how to approach this in the focus 

19 groups. I mean, certainly that is not going to be 

20 brought up during the unsolicited part of the focus 

21 group. But, it will be covered during the discussion. 

22 And in one sense, that customers have a 

23 certain presumed .idea that I am going to go to the 

24 store and these will probably all clean my clothes, you 

25 know, and hold that as a constant. And then look at 

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1 the other attributes. 

2 To the extent that we can look at adding an 

3 attribute in the Conjoint that has some measure of 

4 cleanliness, my concern would be that that would just 

5 be a real hot button, that might bias things more than 

6 if it was left out. But, that is my initial. 

7 MS. NADER: Okay. Steve? 

8 MR. NADEL: Steve Nadel, ACEEE. 

9 I had a couple of questions and a couple of 

10 comments. I think you started getting to the first 

11 one, which is to what extent will this Conjoint 

12 Analysis give you such things as ability to clean 

13 clothes, wear and tear on clothes. Those are some key 

14 attributes for some of the high efficiency machines. 

15 And if you ignore them, you know, you are significantly 

16 I think bias in your results in one way. 

17 MR. GROVER: The Conjoint is going to be 

18 restricted to the most important attributes. And as we 

19 add attributes and levels of attributes, then the 

20 number of cards that people have to sort though, 

21 quickly becomes overwhelming. So, we like to limit it 

22 to probably about, you know, four to six 

23 characteristics with 16 cards. And then we can also 

24 add a separate trade, linking the trades together. 

25 There are techniques for that, where we can incorporate 

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1 additional attributes. 

2 But, again, the intention of this is to, you 

3 know, once, once customers are made aware of during the 

4 focus groups, we don't want to dictate, you know, we 

5 don't want to dictate what attributes they view as 

6 important. And if they are aware that, you know, the 

7 high efficiency design will make clothes last longer, 

8 once they are given that information, if they rank that 

9 20th, then we, you know, that is the point of the focus 

10 group, that, okay, they acknowledged that it is 

11 important, but it is not nearly as important as other 

12 things, then it won't make it to the Conjoint. 

13 MR. NADEL: So, if I understand you, you said 

14 you are open to the consumers if they say cleanliness, 

15 or wear on clothes, that will include it. 

16 MR. GROVER: Yes. Definitely, that is the 

17 whole reason for the focus group. 

18 MR. NADEL: Right and likewise, there is going 

19 to be a whole list of factors that you are going to 

20 mention at the end, to see whether they are important? 

21 MR. GROVER: Just, anything that is left 

22 out, we will have like, a universal choice set, and you 

23 know, I think it is conceivable that we might get 

24 through a focus group where people don't consider top, 

25 you know, horizontal versus vertical. And that is 

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1 obviously key. And it needs to be brought out. 

2 MR. NADEL: Okay. A second question, is have 

3 you read the Thelma Study results and as Ted pointed 

4 out, the impacts of consumer familiarity with the high 

5 efficiency machines on their, their acceptance of 

6 different designs. And how do you plan to address 

7 those things? Do you think a basic explanation will be 

8 adequate to address that factor or is something more 

9 going to be needed? 

10 MR. GROVER: As far as familiarity with the 

11 designs, we want to have photographs of the different 

12 designs as well as, ideally it would be nice to have, 

13 you know, the actual machines so they could look at . 

14 But, given the five areas that is, I believe, going to 

15 be prohibitively expensive. But, a close second to 

16 that w9uld be having photographs available as well as 

17 pointing out some of the more obvious advantages and 

18 disadvantages, for example, of horizontal axis, you are 

19 not ieally able to soak your clothes, that type of 

20 thing or add clothes in the middle. 

21 MS. NADER: Okay. We are running seriously 

22 short of time. And so, I want to ask if any of the 

23 questions and comments that you still hold, are things 

24 that we could cover in the session with Steve, that 

25 begins at 4:30? 

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1 Yes. Bryan, you have been standing there for 

2 awhile . 

3 MR. THOMPSON: Just a definition. 

4 In some of the public information I see 

5 horizontal axis and front loading being the same thing 

6 and I think there is at least one, maybe more machines 

7 that do top load and are horizontal axis. So, I think 

8 definition there needs cleaned up a little bit in some 

9 of the public information. 

10 MS. NADER: Thank you. Anything else burning 

11 that can't wait until 4:30? 

12 Okay, great, thank you. Oh, I was almost 

13 there . 

14 MR. THOMPSON: This is just a question 

15 regarding, you are going to be doing, this is Mike 

16 Thompson, Whirlpool. 

17 You are going to doing two analysis, it 

18 sounds like. You are a focus group and you doing a 

19 Conjoint, is that correct? 

20 MR. GROVER: The focus group is the pre cursor 

21 to the Conjoint. So, there is two, two analysis, but 

22 really the focus group is only being done to feed the 

23 Conjoint Analysis. 

24 

25 

MR. THOMPSON: So, is only being done to what? 

MR. GROVER: To feed into the Conjoint 

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1 Analysis, to help dictate which attributes are going to 

2 be used . 

3 MR. THOMPSON: What I was leading up to, is 

4 then, so one supplements the other. It is not a 

5 waiting process, I am going to give more weight to one 

6 side of this analysis as far as the focus group over a 

7 Conjoint analysis? 

8 MR. GROVER: No, it is, the focus groups are 

9 just designed to trim down that list, without, you 

10 know, letting the average customer decide what is 

11 important. So, we are not really guiding the analysis 

12 forward that way. 

13 MR. THOMPSON: So, what you going to be left 

14 with is a list of attributes after the focus groups 

15 have finished. 

16 MR. GROVER: Right. 

17 MR. THOMPSON: Okay. That answer the 

18 question. 

19 I had one other comment, and I agree with the 

20 gentleman in the back of the room, from Unilever, that 

21 attributes ultimately are performance. There is stain 

22 removal, there is soil removal, there are lint removal, 

23 they are gentleness on clothes. I am going to presume 

24 that that is going to come out somehow in this focus 

25 group. 

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1 MR. GROVER: Yeah, to the extent that we can 

2 categorize the differences of performan6e, we will 

3 definitely be bringing that out. We want, again, what 

4 we want to do is, you know, have as much of a hands off 

5 approach as possible for these focus groups. And the 

6 only role of the moderator is going to be make sure at 

7 the end of the focus group, that nothing has been left 

8 out. 

9 MS. NADER: Okay. So -- This really can't 

10 wait until 4:30. 

11 MR. ROSENSTOCK: Just a process question. 

12 Will stakeholders be allowed to view them, to be in 

13 the, behind the one way mirror? 

14 MR. GROVER: Yes, one of the reasons why we 

15 choose Washington was to have an opportunity for people 

16 to at least, you know, OCS, and what not, to observe. 

17 And to the extent that people are located in any of 

18 the, want to travel to the other cities, you are more 

19 than welcome for both Conjoint and focus groups. 

20 MS. NADER: Okay. Great. Thank you. 

21 MR. GROVER: All right. 

22 MS. NADER: What an interesting topic. 

23 We are going to take a break. I am going to 

24 ask that if it can be a brief break. We are running 

25 behind. And we have several other topics to cover in 

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1 the last hour or so of our program. 

2 Traditionally it is a 15 minute break, can we 

3 get away with a 10 minute break here? 

4 (Whereupon, a short recess was taken.) 

5 MS. NADER: We have a great deal yet to do. 

6 Mike Rivest of Arthur D. Little is going to talk to us 

7 about manufacturer impact analysis. 

8 PRESENTATION BY MIKE RIVEST: 

9 MR. RIVEST: Thank you. I apologize to those 

10 of you who were here yesterday and have to heard me 

11 again. Yesterday afternoon I covered the GRIM 

12 spreadsheet in great detail. And what I plan on doing 

13 this afternoon is more talking about some of the 

14 objectives of the manufacturing impact analysis and 

15 also some of the methodologies and the overall process. 

16 And I will not be focusing so much on the GRIM 

17 spreadsheet. 

18 My presentation has five sections. Quickly 

19 an overview of the framework. Talking a little bit 

20 about the industry profile, the industry cash flow, a 

21 subgroup impact analysis, which is included as part of 

22 the analysis. And I will be concluding with some next 

23 steps in terms of what it is we will be doing in the 

24 upcoming months . 

25 To be able to save time I would ask that you 

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1 . keep your questions to the end of each of these 

2 sections . 

3 Just a reminder, the Manufacturers Impact 

4 Analysis has its eye on two major elements. First of 

5 all, we are interested in looking at the impacts of the 

6 rule on the manufacturers of the products. Also, we are 

7 interested in working closely with the Department of 

8 Justice and relating to them any information that we 

9 gather during our analysis with regards to the 

10 competitive impacts of the rule. 

11 The Manufacturer Impact Analysis is really a 

12 three step process, if you will. And it is very 

13 closely interlinked with every section of the analysis . 

14 We have been working on the industry profile for quite 

15 some time now. We have, yesterday I presented with the 

16 GRIM Spreadsheet some preliminary industry cash flows. 

17 And we will be working through an interview process on 

18 a subgroup analysis and doing some more subgroup level 

19 analysis. 

20 The industry profile is not per se discreet 

21 tasks. It is a matter of gathering data that is 

22 relevant to the rulemaking, as the sections and as the 

23 information is needed into the analysis. There is some 

24 information on the industry that is presented in 

25 Chapter 3 of the TSO. But, also the industry profile 

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1 was arrived at, at determining such things as the 

2 industry cost structure, which we used in setting some 

3 of the cost parameters inside the GRIM model. Some of 

4 the shipments data, historical shipments, that Jim will 

5 be using as a starting point for forecasting future 

6 shipments. We have also done, used the industry 

7 profile to arrive at baseline manufacturer and retail 

8 prices and mark-ups. And some product characteristics 

9 and market shares, which are discussed in Chapter 3. 

10 The industry cash flow is based on the GRIM 

11 model. The GRIM model is a very conventional 

12 evaluation tool that is used for evaluating whole 

13 companies, or capital investment decisions. And the 

14 conclusions of the cash flow analysis are presenting a 

15 before standards and after standards industry value in 

16 terms of a net present value. 

17 I like to think of the GRIM as simply a 

18 sophisticated calculator that takes a series of 

19 manufacturing costs, shipments, prices and financial 

20 information, to compute cash flows. And this is done 

21 both for a base case and for standards cases, for each 

22 standard level under consideration. So, for the 

23 present time, since all efficiency levels are under 

24 consideration, the GRIM that we have prepared has all 

25 efficiency levels. 

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1 In our preliminary base case industry value, 

2 if you will, that I used to set up the GRIM, we 

3 obtained information on the existing manufacture price 

4 of clothes washers from the AHAM fact book and the 

5 current industrial reports. Manufacturing costs were 

6 reverse calculated from the prices, using industry cost 

7 structures that we were able to do, using Census and 

8 manufacturer and lO(k)s. 

9 Similarly, we developed financial information 

10 representative of the overall industry from financial 

11 information that is publicly available. 

12 Very important consideration is the shipments 

13 forecast. For the present time we have shipments 

14 forecast which is basically a slow growth of 2.3 

15 percent. Eventually, our purpose here is to make sure 

16 that the same shipment assumptions that are used in the 

17 National Energy spreadsheet, are also used in the GRIM 

18 model. 

19 As I mentioned before, we were able to obtain 

20 manufacturer prices from both the AHAM Fact Book and 

21 the Census, the current industrial reports. We see 

22 that the prices are very flat for many years. And 

23 these are nominal dollars. So in real dollars they 

24 would be going down. 

25 We have the industry cost structure from the 

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1 prices. We allocated the cost in the base case, based 

2 on our analysis of the industry . 

3 Our financial information was also obtained 

4 from the study of financial information. And these are 

5 the values that are being used currently in the GRIM 

6 model for the base case. And I reviewed these 

7 yesterday with the people present. 

8 For my preliminary base case, if you will, I 

9 just created a scenario with a small increase of 2.3 

10 percent, just a straight regression over the past. I 

11 wanted to create a scenario and start running some 

12 parametric evaluations on it, just to see what kind of 

13 numbers we are coming at . 

14 Eventually the intent is that the GRIM 

15 spreadsheet will be linked directly to the NES. So, 

16 the assumptions we make about shipments, before and 

17 after standards, any assumptions we would like to make 

18 about, for example, the percentage of high efficiency 

19 clothes washers and the baseline would translated 

20 directly from the NES to the GRIM spreadsheet. 

21 Order of magnitude number, well, better than 

22 order of magnitude, a good first cut in industry value 

23 we obtained is that the industry is currently valued at 

24 about $885 million. I think this is significant in 

25 that when we look later at the investments we are 

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1 talking about, to reach some of the high, higher 

2 efficiency levels, we will see the comparative to the 

3 industry value. The investment required are as large. 

4 So, we are talking here about investing as much as the 

5 business is already worth. 

6 To adapt the GRIM for this clothes washer 

7 rulemaking, we have made some modifications and some 

8 enhancements, if you will. And most of those were done 

9 primarily to account for change in shipments, to 

10 account for growth, finally. 

11 And some of the assumptions that were changed 

12 from the original GRIM are that the SG&A now is a 

13 function of revenues. It is not fixed. Depreciation 

14 and ordinary capital expenditures to the base case are 

15 also allowed to fluctuate with revenues. 

16 And also the data gathering exercise that was 

17 done, that done on per unit costs. And we have to make 

18 sure that when our actual investments are made, that 

19 the precise shipment numbers are used in the given year 

20 that the investments are made. So, if the rule is 

21 implemented in 2003, then the number of shipments, it 

22 will no longer be seven million. So, the investment of 

23 800 million, for example, is scaled to the number, to 

24 the actual shipments in that year. 

25 For the standards case, we created 

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1 incremental costs using the AHAM data submittal. 

2 Manufacturer prices, after standards manufacturer 

3 prices are obtained by putting a mark-up on full 

4 production costs. And we ran scenarios at various 

5 markups and I will show some of the preliminary 

6 results. 

7 Financial information, the industry 

8 statistics for standards case are the same as the base 

9 case. 

10 And also very important to note, in all the 

11 results I will show you, we are assuming that there 

12 will be no decrease in shipments if the price of, if 

13 there is an increase price of higher equipment, higher 

14 efficiency equipment. Now, we know that is wrong. So, 

15 when we have results of the elasticity values from the 

16 consumer survey, the new shipments values will reflect 

17 these elasticity values. And we know that can be quite 

18 significant. I was looking at the analysis that was 

19 prepared for the earlier rulemaking and for an increase 

20 in price of about $200.00 shipment fell, shipments fell 

21 by about 10 percent. So, that is quite considerable. 

22 These are just showing the portion of the 

23 GRIM spreadsheet that contains the AHAM data submittal. 

24 Four our baseline model, we calculated 

25 currently the industry applies and mark-up of 1.35 over 

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1 the full production cost. For the after the standard 

2 scenario on the incremental cost of meeting the 

3 standard, we have applied a number of different 

4 scenarios. A number of different mark-ups. Some of 

5 them, want to point out that a mark-up of 1.18 was 

6 used to calculate the life cycle costs and I ran this 

7 preliminary model at 1.18 to see what would be the 

8 situation for the industry, if that was, in fact, the 

9 mark-up that was obtained. 

10 Currently, as I mentioned earlier, some of, 

11 one of the assumptions that we change is, that SG&A 

12 will now be allowed to track the growth in the 

13 business, if you will, the growth in revenues . 

14 Another assumption that is very critical and 

15 very sensitive to the timing or the delay in 

16 introducing a standard, is how the capital assets are, 

17 how many is expended for the new capital assets. And 

18 there is a table in the GRIM which shows for any given 

19 number of years, between the actual announcement of the 

20 standard, and the year that the standard becomes into 

21 effect, how the money, the capital expenditures are 

22 spent. And I would just like to point out that this is 

23 the table from the original GRIM. And I would like to 

24 have comments on how I can, if change the schedule of 

25 cash out lays. Just from looking at it, and I don't 

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1 want to go in great detail right now, it seems that a 

2 manufacturer who has eight years to build up his 

3 capacity, to meet the standard, would probably not 

4 spend 16 percent of that capital, one, two, three, 

5 four, five, six years, before the standard is in 

6 effect. So, I am just questioning some of the original 

7 assumptions in the GRIM and trying to see if we can 

8 improve on them. 

9 That is also true of R&D expense. 

10 I ran the current version of the GRIM to see 

11 what sort of mark-ups we needed on the incremental 

12 manufacturing costs in order to accomplish certain 

13 outcomes. And here I wanted to see what would be the 

14 mark-up I would need at the different efficiency 

15 levels, to recuperate, to maintain the exact same 

16 industry value of 880 million. And what I noticed in 

17 running these scenarios is that the mark-up needed is 

18 very sensitive to the proportion of fixed costs 

19 relative to the total costs. So, that is really what 

20 we are seeing here. And I graphed the ratio of fixed 

21 to variable cost to the change, to the required mark-up 

22 to maintain the industry value. 

23 I also tried to see if we could put abound, a 

24 bound on the manufacturer mark-up, back calculating 

25 from some potential outcomes. One of those outcomes 

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1 being what sort of mark-up would we need to maintain 

2 our NPV, if you will. That might be our higher bound . 

3 There would be absolutely no manufacturing impact from 

4 a higher standard. And the lower bound, which would 

5 represent the mark-up we would need, just, the mark-up 

6 that would result in the industry, losing all of the 

7 capital expenditures to meet this rule. 

8 And what I want to show here, this is the 

9 magnitude of the investments to meet the efficiency 

10 levels. So, for example, it costs about 800 million 

11 dollars to meet efficiency, in fixed cost, to meet 

12 efficiency levels eight and nine. And the mark-up you 

13 would need on your incremental production cost is in 

14 the area of 1.25. 

15 I am pointing this out because we ran the 

16 life cycle costs at 1.18. And what this is saying is 

17 at 1.25, we lose all of our investments. And ran the 

18 model at different mark-up assumptions, 1.18, 1.27 and 

19 1.35. So, 1.35 represents what we are currently 

20 observing as the mark-up over full production costs. 

21 And we see that the reduction in the industry value is 

22 really proportionally, is really tracking the 

23 proportion of fixed to variable costs. And then I ran 

24 the model at 1.18, and looked at the industry value. 

25 And as you can see, as you get more stringent, the 

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1 industry value drops dramatically, to an unsustainable, 

2 you know, much below zero industry value. 

3 We have created a second venison of the GRIM, 

4 which is able to analyze the manufacturing effects of a 

5 two tier standard. One of the caveats there is that 

6 the assumption is that the costs of meeting those 

7 standards would be additive. So, when you do an 

8 analysis with the two step, the two step GRIM, we have 

9 limited your choices as a first choice in the zero to 

10 25 range, and a second choice in the 35 to 50 range. 

11 And the GRIM assumes that the investments done to meet 

12 the 20 percent efficiency standards will be depreciated 

13 over the length of time that that first phase is in 

14 effect. And that all new investments will have to be 

15 made to recover, all new investments will have to be 

16 made to have that second standard be met. 

17 It is our intention that we will use the full 

18 range of data that was submitted for manufacturing 

19 .costs. We will be preparing a revised version of the 

20 GRIM, that instead of having only the shipment weighted 

21 averages, we will have all the percentile values. That 

22 will allow us to do scenario analysis, comparing the 

23 impacts of 25 percentile costs fixed or variable, with 

24 shipment weighted or 75 percentile. So, we will get an 

25 idea of the potential distribution of those impacts. 

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1 Also we would like to work with AHAM to be 

2 able to run full Monte Carlo analysis on the actual 

3 data submittal and present the results. But, we would 

4 be doing that only once we have the shipments from Jim, 

5 that will be used, the final shipments from the NES 

6 model, just to cut down on the burden. 

7 And this figure just shows how we would be 

8 using the cost and shipments which are residing at 

9 AHAM, calculating the manufacturing impact separately 

10 for each manufacturer and aggregating those into an 

11 industry cash flow, which would then be part of the 

12 public record. 

13 Are there any questions on the last series of 

14 slides or observations or is it too much, did I rush 

15 through it too quickly? 

16 I will push on. 

17 Now, the second phase, if you will, of this 

18 analysis is to take the industry cash flow that we have 

19 produced and to visit each manufacturer individually 

20 and get a sense of how representative that industry 

21 cash flow is to each of their particular situations. 

22 And to be able to do that we will be equipped 

23 with two tools. We will have the industry cash flow 

24 and we will also have an interview questionnaire. And 

25 we have provided a draft of the interview 

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1 questionnaire, with the materials to this workshop. 

2 And what we are hoping to do within this comment 

3 period, and in the subsequent weeks, is to refine the 

4 questionnaire. What we are trying to do is capture 

5 all, as many of the potential issues as possible in the 

6 questionnaire. So, then when I am conducting the 

7 interviews, we cover all potential and important 

8 issues. 

9 MS. NADER: Mike, I am sorry to interrupt, but 

10 we have an opportunity here. Dan Reicher is with us 

11 and has a very short period of time that he can spend 

12 with us. So, may I ask your indulgence and take a 

13 break from your presentation for just a few minutes? 

14 MR. REICHER: Yes, I apologize to break in 

15 right now, but wanted to 

16 MR. BERRINGER: Could you step at the podium, 

17 please, the microphone. 

18 MR. REICHER: Yes. I am Dan Reicher, 

19 Department of Energy. 

20 I apologize for breaking into the meeting. I 

21 am the Assistant Secretary for Efficiency and Renewals 

22 and I, first of all, wanted to thank you for coming 

23 today. I know it has been a long, but I hear it has 

24 been quite a fruitful meeting. And I wanted to 

25 emphasize to you how much we appreciate this input 

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1 because as you all know, we are in the midst of 

2 reinventing this process and this is one of the early 

3 rulemakings out of that reinvention box. And we want 

4 to make sure that we take the right steps that will 

5 lead to what we are very committed to, which is putting 

6 out this rule by September of 2000. We are very much 

7 committed to that, committed to that schedule. And we 

8 will do all we can to get there. We are working on 

9 both the policy side and the budget side to make that 

10 happen. And it is meetings like.this where we can 

11 ventilate issues early, we can get them resolved and we 

12 can move forward. That I think is extremely important. 

13 I think that the role of the Advisory 

14 Committee on appliance efficiency standards, which some 

15 of you are members of and many of you have attend the 

16 meetings, also has helped us move this forward and help 

17 shape some of what is being discussed today. I know 

18 there are some issues that come out of that Advisory 

19 Committee that you are taking up today, and I know 

20 there are some differences of opinion, but from what I 

21 am told, we are making some progress. And people, 

22 increasingly, are comfortable with the process that we 

23 have put in place to try to move this standard setting 

24 forward, along with the other three major ones that we 

25 are working on. 

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1 So, I am, again, thank you for being here. 

2 Thank you for your commitment to this. Our commitment 

3 to you is to run a very fair and very open process, to 

4 take all points of views, to do as much analysis as we 

5 can realistically do to get answers to things, and to 

6 be timely in how we conduct ourselves and stick to our 

7 schedule, so that we can put out a standard that has 

8 got as much support as it possibly get by September of 

9 the Year 2000. 

10 So, thank you. 

11 MS. NADER: Thank you. 

12 MR. REICHER: And happy holidays to you all. 

13 MR. THOMPSON: I will just quickly review 

14 some of the main topics of the interview questionnaire. 

15 We will be interested in having a better understanding 

16 of the current organizational characteristics of the 

17 various firms, understanding the industry 

18 infrastructure, buyers, suppliers. And in any way in 

19 which these might be influenced or impacted by the 

20 rule. 

21 We will be conducting or comparing the 

22 manufacturing cash flow analysis performed for the 

23 industry, with any differences or significant variances 

24 with particular situations, existing at different 

25 manufacturers. 

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1 We will, we are interested in understanding 

2 any competitive impacts that the rule may have on 

3 various firms. 

4 The big issue in the ballast, I am not so 

5 sure here, the employment impact assessment, how would 

6 the decision to go to a more stringent standard impact 

7 manufacturing in certain facilities, potentially 

8 closing some or opening others. 

9 Also looking at the impacts of the rule on 

10 any of your current assets. Would some of your current 

11 assets be somehow stranded as a result of this rule? 

12 And this could apply also to of your major suppliers. 

13 The next few slides only detail a little bit, 

14 each of the topics that I just brought up for the 

15 survey. And I invite you read them at your leisure. 

16 But, most of all, to comment back on how I can improve 

17 that questionnaire. 

18 One very important distinction, or very 

19 important element of the subgroup analysis is to be 

20 able to report back how some manufacturers may be 

21 impacted more or less or just differently from other 

22 manufacturers. And in so doing, I hope to be working 

23 with the various groups of manufacturers to be able to 

24 report those impacts in a way that preserves 

25 confidentiality, but shows a clear signal to DOE's 

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1 decision makers, as to how that average manufacturer, 

2 how that average industry impact may, in fact, fall 

3 more heavily on some groups rather than others. 

4 MR. JONES: Yes, Michael, Earl Jones here, 

5 G.E. 

6 Do I understand that in this section or this 

7 section of your presentation, focuses on sort of 

8 qualitative issues? 

9 MR. THOMPSON: That is correct. 

10 MR. JONES: That this results in some kind of 

11 a narrative. 

12 MR. THOMPSON: Absolutely. 

13 MR. JONES: With supplements, what comes out 

14 of the first piece. 

15 MR. THOMPSON: Right. The first piece is 

16 strictly by the numbers. And we are looking at overall 

17 industry aggregate impacts in terms of number of total 

18 investments in dollars. And the potential impacts on 

19 dollars for the overall industry. 

20 The second phase we move into one on one 

21 interviews, and then we explore how those impacts may 

22 be different, the quantitative impacts may be different 

23 for them. But, more than that, we would like to get 

24 into more qualitative impacts or assessments. Such as 

25 decisions to invest or not to invest in new product 

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1 lines, you know, leave the business entirely, things 

2 like that. And the result will be, the reported impacts 

3 would be the industry cash flow analysis. If we can do 

4 it without confidentiality issues, we could report a 

5 cash flow analysis for a subgroup of manufacturers, 

6 which would be impacted differently. And then there 

7 would be a narrative which would follow the outline of 

8 the questionnaire. And that is why I urge you to spend 

9 considerable time making sure that the questionnaire 

10 covers all the issues. 

11 David? 

12 MR. GOLDSTEIN: Yes, David Goldstein, NRVC. 

13 Hopefully your discussions with manufacturers 

14 can help to reconcile quantitatively a disconnect that 

15 seems to be coming up from the preliminary work that 

16 you have presented, which is that your preliminary 

17 analysis suggests that the industry is worse off by 

18 producing lots of products at a high efficiency level. 

19 Yet, companies that are producing moderate amounts, the 

20 same products, at the same efficiency levels, are 

21 reporting to Wall Street that they are making lots of 

22 money on that. 

23 MR. THOMPSON: Let me give you my two second 

24 explanation for that . 

25 The manufacturers will invest where there is 

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1 a competitive advantage to be gained. And that may be 

2 very short lived competitive advantage. But, to invest 

3 in only meeting the bare minimum, I think it is 

4 different. So, I don't think there is a disconnect 

5 ihere. I think there is just a different phenomena. Do 

6 you understand? I mean, there are --

7 MR. GOLDSTEIN: I don't think that is a 

8 sufficient explanation. I think that if anything it 

9 should cut the other way, because if you have a 

10 standard, a manufacturer can count on his market share 

11 being relatively predictable, relatively the same 

12 levels, and so that you know that if you make an 

13 investment, you can predict production levels and you 

14 will get it right. Whereas, in this market place, you 

15 make an investment, you are taking a wild guess at 

16 production levels. You could be way off, and being way 

17 off by over optimistic hurts you. 

18 So, the additional certainty in standards 

19 would make that actually more profitable. So, there 

20 are factors that cut both ways. It is not the same 

21 situation, but I think the interviews might be able to 

22 help you look at the quantitative analysis. That is 

23 you ought to be able to start off with the industry 

24 quantitative analysis, and turn a couple of levers and 

25 knobs to be able to predict what has already happened 

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1 out of the models. And then --

2 MR. THOMPSON: I agree with your general 

3 statement that there is a lot of value in the interview 

4 process, which will help to understand a lot of the 

5 quantitative phenomenon. In terms of the exact 

6 example, I guess we could got a great length. 

7 MR. GOLDSTEIN: Yes, the example was 

8 MR. THOMPSON: Okay. 

9 MR. GOLDSTEIN: I wasn't trying to get too 

10 specific. 

11 MR. THOMPSON:. Right. 

12 MR. GOLDSTEIN: The other issue concerns, you 

13 have analyzed the impacts of the standard as if it were 

14 real simple. You set a standard in a given date, 

15 everyone gears up right before it, they meet the 

16 standard that is all that happens. This product isn't 

17 going to work that way. Because a couple of companies 

18 have already made investments that at least, partially, 

19 I would claim, are in anticipation of their being a 

20 standard. 

21 MR. THOMPSON: Have you been talking to 

22 Charlie Stevens? 

23 MR. GOLDSTEIN: No, sometimes ideas are just 

24 so obviously right, that people --

25 MR. THOMPSON: No, we -- David, we will --

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1 MR. GOLDSTEIN: There are issues of 

2 uncertainty about investment and stranded investments 

3 that are bigger, unquestionably bigger in the base 

4 case, that need to be analyzed here. If you have a 

5 company that is making an investment based on a project 

6 of growth in high efficiency products, and the 

7 utilities drop out of the game in five years, which 

8 they may or may not do, and the voluntary programs like 

9 Energy Start, don't work or aren't funded, which isn't 

10 a surety, but it is a possibility. That is an impact 

11 of the base case. And in order to be even handed, you 

12 need to look at that in the distribution functions, 

13 just as you are looking at the impacts of standards . 

14 And I think you also need to look at the 

15 question of what if manufacturers find that it is more 

16 to their benefit to gear up slowly, piece by piece for 

17 a standard and try to work with the voluntary programs 

18 to sell those products on a non regulated basis in the 

19 first, in the third year, the fourth year, before the 

20 standard goes into effect. 

21 MR. THOMPSON: There are some element of 

22 what you said that definitely will be captured in that 

23 we will have, we will be tracking the shipments and the 

24 growth in shipments of higher efficiency products, you 

25 know, linking with the NES. 

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1 So, those investments will be made and 

2 tracked. So, that will moderate, if you will, the size 

3 of the step function. But, I am not sure that we can 

4 capture all of what you said. That is why the 

5 qualitative discussions, I think will be important. 

6 MR. GOLDSTEIN: The point I am making is that 

7 given the size of this investment, your analysis is 

8 already pointing out this is an unusually large 

9 investment for appliance efficiency standard. It seems 

10 to me that many manufacturers will choose not to make 

11 that in a lumpy fashion. But, will rather try to make 

12 it early and make some profit on the product before it 

13 is required, perhaps by marking it up more and 

14 differentiating themselves as current manufacturers are 

15 doing. That is something that needs to be in there, in 

16 the standards case. 

17 And in addition, or separately from that, the 

18 base case has to incorporate the reality that you 

19 cannot predict saturation of high efficiency machines 

20 relative to low efficiency ones. And that uncertainty 

21 is a business risk and it is not cost free. 

22 MR. THOMPSON: But, it may be symmetrical in 

23 that higher risk has higher potential payoffs. 

24 But, we are really getting into analytical 

25 details, I think, that I will be happy to talk to you 

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1 about. 

2 As I have mentioned, we have already, DOE and 

3 myself, met with the Department of Justice on two 

4 occasions, concerning this and other rules. And they 

5 plan on playing a very active role in helping us, for 

6 example, develop the interview questionnaire, and they 

7 will be monitoring, if you will, the analysis and 

8 making sure that their data needs are met to the extent 

9 possible, to facilitate their own tasks when they have 

10 to do their DOJ review. 

11 Just to move on to the next steps. This, as 

12 I mentioned, this analysis is really very closely 

13 linked with all other sections, all over sections of 

14 the analysis. And the current sequence is that the 

15 consumer analysis will give us some idea of the 

16 customers willingness to pay, if you will, or the 

17 elasticity. Those elasticity values will be used by 

18 Jim to develop shipment forecasts. And the shipment 

19 forecast developed for the NES spreadsheet, will then 

20 be used in the GRIM. 

21 So, the sequence of events, I plan on 

22 initiating dialogue with manufacturers on the one to 

23 one basis, during the winter. And to begin, first of 

24 all, making sure that we have the best possible 

25 instrument that we can, begin getting a grasp on some 

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1 of the major issues. 

2 Once we obtain the shipments from NES, that 

3 is when we will finalize our scenarios for the industry 

4 cash flow. And visit the manufacturers with that, those 

5 cash flow scenarios and with our interview guide and 

6 report back, we will be beginning the interviews in the 

7 Spring. 

8 Any questions on the schedule, the time line 

9 as it --

10 MR. HAWKINS: This is Larry Hawkins, G.E. 

11 Your handout package, Michael, has a 

12 different first bullet date, February the 2nd versus 

13 January 15th . 

14 MR. THOMPSON: I am sorry, what happened 

15 there is that I had taken 30 days as a comment period 

16 for this workshop, and we just heard that the workshop 

17 will be made to coincide with the ANOPR comment period. 

18 So, the February 2nd is the correct date. 

19 That completes this presentation. I will be 

20 standing around after the meeting and I will be happy 

21 to talk to any of you about this in more detail. 

22 MS. NADER: Thank you very much. 

23 MR. MONTUORO: I have a comment. I am Lou 

24 Monturo with Amana Appliances. And we presented data 

25 earlier that, on a cost tear down analysis of two H 

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1 axis machines in another high energy, efficiency 

2 machine . 

3 MR. THOMPSON: Yes. 

4 MR. MONTUORO: Will that data be, will that be 

5 additional data to be incorporated into GRIM or is 

6 there going to be some type of reconciliation done with 

7 that data, with what AHAM initially has supplied? 

8 MR. THOMPSON: No, that data was, I am not 

9 sure what data you got, so -- The data that we will be 

10 using is data that was supplied to AHAM. You may have 

11 supplied data directly to Steve for the purpose of the 

12 reverse engineering. I don't have that data. 

13 MR. MONTUORO: No, I just mean we analyzed, we 

14 did a tear down of the two H axis machines and the 

15 Whirlpool prototype. Is that financial information 

16 that was generated to be incorporated into this model? 

17 MR. THOMPSON: Not as such. I mean, one way 

18 that we can, for example, model the impacts no lower 

19 volume manufacturers would be to take the production 

20 model that Steve prepared, and run the model at lower 

21 volumes in slightly different production configuration 

22 and get an idea of what sort of costs are involved in, 

23 differential costs between high and low production 

24 manufacturers. So, that is one way we could use the 

25 model. But, the information per se is not part of the 

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1 GRIM. 

2 MS. NADER: Thank you, Mike . 

3 I know there may be other questions and 

4 comments and I regret that we simply don't have any 

5 more time for that now. And would encourage you to 

6 talk to Mike in the next few minutes when, since he has 

7 said he will continue to be available. 

8 MR. BERRINGER: Or an opportunity to submit 

9 written comments also. 

10 MS. NADER: Yes. Thank you. 

11 Jim McMahon, patient soul that he is, now has 

12 three additional areas he is going to cover. Indirect 

13 employment, environmental assessment, and utility 

14 impact analysis. And Jim, I am sorry the time is so 

15 constrained. 

16 PRESENTATION BY JIM MCMAHON: 

17 MR. MCMAHON: Okay. The first topic is 

18 indirect employment impacts. 

19 Okay. Indirect employment impacts. 

20 Standards could effect consumer spending in two ways. 

21 We expect that standards will increase the purchase 

22 price of regulated products and decrease consumer 

23 energy and water expenditures. 

24 The direct employment impacts have just been 

25 described by Mike Rivest and those will be analyzed in 

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1 the manufacturer impact analysis. 

2 There are 'also indirect employment impacts by 

3 which we mean net jobs, created or eliminated in the 

4 U.S. population at large, as a consequence of new 

5 energy efficiency standards. 

6 Currently residential energy consumption, 

7 energy expenditures, this is for 1995, were 129 billion 

8 dollars. Possible energy efficiency standards are 

9 expected to reduce those expenditures. And as the life 

10 cycle cost demonstrates, usually the projected increase 

11 in equipment prices is overcome by decreases in energy 

12 expenditures over time. 

13 The proposal is to use an input, output model 

14 to estimate the effects on other sectors of the economy 

15 from the changes in consumer spending. 

16 In this case, the model is a model called 

17 Inbuilt. This is based upon a commercial product 

18 called Inplan, which is available for purchase. 

19 However, you will be happy to hear that in this case, 

20 the Department of Energy has taken the commercial 

21 product, developed a spreadsheet version of it that is 

22 simpler, and is able to give away the spreadsheet 

23 version of it. So it is fully available and 

24 documented. 

25 This was done by Pacific Northwest 

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1 Laboratory. I believe there are two volumes of 

2 documentation and we will be happy to have those put on 

3 the record. 

4 The U.S. Economy is characterized as 

5 interconnection among 35 sectors. The 35 are those 

6 that are important to building energy consumption. The 

7 other sectors are the economy that are not expected to 

8 be affected, have been aggregated. 

9 The input into the model are shifts in 

10 expenditures due to standards. There are two of those. 

11 The equipment expenditures and the interview 

12 expenditures. These will come from the National Energy 

13 Savings spreadsheet . 

14 And then the output will be the change in 

15 employment by sector as a consequence of the new 

16 standards. 

17 What do we expect to find? We expect there 

18 will be reduced spending for energy and water. That 

19 may cause reductions in employment in the energy and 

20 water supply sectors. There will also be a shift of 

21 spending away from energy toward other sectors, and 

22 that could potentially create jobs in those other 

23 sectors. So, the net result will be the net job 

24 creation or elimination by sector will be estimated . 

25 Are there questions on this? 

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1 MS. NADER: Richard? 

2 MR. BEST: Yes, Richard Best, Whirlpool. 

3 Are you going onto another topic from here? 

4 MR. MCMAHON: Yes. 

5 MR. BEST: Okay. Because I do have a comment 

6 here and I think it is relevant to going in the record 

7 here.· 

8 When you are looking at indirect employment 

9 impacts, it seems as though the model is basically one 

10 of, within the contents of the United States. And my 

11 comments are related to this. You know, the U.S. 

12 appliance industry is unique. And one thing unique 

13 about it, is over the past generation most of us 

14 watched as the American auto industry was basically 

15 dismantled. We watched our consumer electronic 

16 industries move overseas. But, through it all the 

17 appliance industry remained in tact and fairly healthy. 

18 And we did it through invocation, cost, and 

19 productivity and passing those things onto the 

20 consumer. The prices of appliances today are basically 

21 at the same price they were a generation ago, even 

22 without inflation. 

23 I think the issue here is one that this rule 

24 will force a lot of investment on the manufacturers and 

25 significant changes to the products we are going to 

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1 produce. The question is how much investment, how soon 

2 and how significant will the changes be? And my 

3 comments are that from a global perspective, we have 

4 another employment potential impact here, that needs to 

5 be considered in the rulemaking. First of all, the 

6 appliance industry, global competitive posture is going 

7 to be threatened just by the diversion of major 

8 technical and financial resources during this rule 

9 making period. 

10 The second is that this, the playing field in 

11 the U.S. will be level for all competitors on a global 

12 basis if it is a major change to our markets. And most 

13 of the productivity gains made over the years by U.S . 

14 companies, could be wiped out by these change overs to 

15 new products and processes if there is not sufficient 

16 time to allow the transition in a smooth manner. And 

17 for us to reestablish our global competitive leadership 

18 that we have worked on for the last several decades. 

19 And the last point is that global pricing, or 

20 competitive pricing on these products could double or 

21 triple as pointed out many times in these arguments, 

22 and that just rises the probability of an import market 

23 taking place. Thank you. 

24 

25 

MS. NADER: Thank you. 

MR. MCMAHON: Thank you, Dick . 

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1 (Pause.) 

2 MR. MCMAHON: Okay. Moving to the next topic 

3 on the agenda. You have a handout called Methodology 

4 for Utility and Environmental Analysis. These are 

5 combined into the one handout. 

6 MR. JONES: Oh, excuse me, Jim. Earl Jones 

7 here. I was just trying to digest some of the previous 

8 comments. You know, I don't understand what this 

9 employment impact, what it will do? Did I miss that? 

10 Or how does this thing work? Are you telling me that 

11 you are going to do something, but you don't know what, 

12 how it will be done? Is that what I understood? 

13 MR. MCMAHON: No, that is not what I said. 

14 MR. JONES: Okay. So, what then, what did 

15 you say? 

16 MR. MCMAHON: Let me try and restate it. 

17 The methodology here is an input, output 

18 model. That divides the U.S. economy into sectors, and 

19 specifies the flow between one sector and another. And 

20 what we are saying is that the standards will 

21 presumably affect consumer expenditures in two ways. 

22 They will 

23 MR. JONES: Well, I understand that. I 

24 understand everything you have on this paper, because I 

25 think it is fairly good English. But, I still don't 

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1 what the hell it means at the end of the day. In other 

2 words, what, what will, what is this analysis going to 

3 provide? It is going to somehow determine, and I guess 

4 I can't understand from what is here, how it is going 

5 to determine that, what is going to be the net addition 

6 or gain? And how, what information will go into 

7 deciding what, whether it is up or down? 

8 MR. MCMAHON: In simplest terms, if there are 

9 increased expenditures into a sector, if consumers~ for 

10 example, hypothetically, were to purchase some other 

11 product ~ith the money that they saved in energy, then ~ 

12 presumably that sector would respond by selling that 

13 product to the consumer. And that increase in sales 

14 might lead to increased employment in that sector. 

15 MR. JONES: Yes. 

16 MR. MCMAHON: So, what the model is doing, is 

17 taking a snapshot of the current economy, and what the 

18 current flows are, and then we are imposing upon that a 

19 probation where we say, instead of this money being 

20 spent on energy, it is now spent on other things. 

21 MR. JONES: Right. And how will you, what are 

22 the assumptions which say that those are additional 

23 dollars represent X or Y jobs? 

24 MR. MCMAHON: Associated with production in 

25 each sector are workers. And the idea is that if 

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1 production increases there will need to be more 

2 workers . 

3 MR. JONES: And there is some formula based on 

4 the particular industry which says that in the, in the 

5 entertainment industry or the travel industry or the 

6 construction industry, if people spend more or less in 

7 those areas, there is a differential number of jobs 

8 added or lost? Or is there just a number that applies 

9 across the economy? 

10 MR. MCMAHON: The former. 

11 MR. JONES: The former. So, then, so and the 

12 information which says what the impact is by particular 

13 sector, is something which you all are developing or is 

14 available otherwise? 

15 MR. MCMAHON: We have not developed it. It 

16 has been developed. There are good accounts of the 

17 National Economy already developed. This is using a 

18 model that already exists. 

19 MR. JONES: Okay. So, then, totally aside 

20 from the question of energy and the impact of 

21 standards, you are saying that there exist a model 

22 somewhere which says, that if expenditures increase in 

23 a particular segment, or sector of the economy, that 

24 equals X or Y jobs? 

25 MR. MCMAHON: Yes. That is correct. 

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1 MR. JONES: Okay. And you are going to 

2 piggyback on that by saying if we divert the expenses, 

3 the expenditures previously used for energy and water, 

4 and move them over here, then it will have the same 

5 impact? 

6 MR. MCMAHON: That is correct. 

7 MR. JONES: Okay. Thank you. 

8 MS. NADER: Carry on. 

9 MR. MCMAHON: The next topic is utility 

10 analysis. The purpose of the utility analysis and we 

11 have used the utility in a couple of different places. 

12 In this case we are meaning energy supply sector, the 

13 utilities that supply electricity and gas . 

14 The purpose is to estimate the effects on 

15 those utilities from reduced energy sales due to the 

16 new standards. The method is to use the NEMS model, 

17 the Department of Energy, Energy Information 

18 Administration, National Energy Modeling System. We 

19 are calling it NEMS-NAECA, because EIA is very 

20 proprietary about their model. If anyone else uses it, 

21 we have to rename it, so that it is not confused with 

22 the official DOE model. So, we are calling it NEMS23 NAECA. It is an exact copy of the official DOE model. 

24 

25 

It is an integrated model of the U.S. Energy 

sector. It includes all supply and demand. It is 

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1 publicly available. And it contains a forecast through 

2 the Year 2020. There are also extrapolations done out 

3 to 2030 for FEMP. And we intend to use the Department's 

4 extrapolations rather than our own. 

5 The current basis to date has been the annual 

6 energy outlook 1998, within the last month, the annual 

7 energy outlook for 1999 has been made public, over the 

8 Thanksgiving weekend. One of our staff came to the 

9 Department and captured a copy of the 1999 model and 

10 brought that back to LBL. So, we will be using that 

11 one in the future. 

12 The inputs to the analysis are annual energy 

13 consumption and savings by fuel type from the National 

14 Energy Savings spreadsheet. All the other inputs will 

15 be consistent with those used by the Department of 

16 Energy. 

17 The output, the model as I have said, balance 

18 all supply and demand. So, it will be given the 

19 savings from the standards and then it will conduct its 

20 balance. That balance will potentially affect price as 

21 well as the supply of energy. And we will report back 

22 then the change in energy sales and price by fuel type 

23 and by region. We can also report back the change in 

24 the mix of electricity generation, if any. And the 

25 change in new capacity construction, if any. 

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1 MR. ROSENSTOCK: Could I comment? 

2 MR. MCMAHON: Yes . 

3 MR. ROSENSTOCK: Steve Rosenstock, Edison 

4 Electric Institute. 

5 Maybe more of a nomen clature than anything 

6 else. This kind of model is still kind of working on 

7 the assumption of, at least as far as I see, vertically 

8 integrated entities, whether it is gas or electric. 

9 And since we are projecting forward in the future, when 

10 you are doing this type of an analysis, when you are 

11 get right down to it, how is it going to affect the 

12 electric generation companies, the natural gas 

13 suppliers, production companies, the electric 

14 distribution companies, and the natural gas 

15 distribution companies? I will leave oil out as a 

16 separate kind of entity, since it has been deregulated. 

17 I would propose those kind of four categories, because 

18 basic, or these distribution companies, because there 

19 are going to be different view points, depending on 

20 what part of the sector you might be in. And I think 

21 that, as just a generation supplier versus a 

22 distribution company, there might be different 

23 attitudes in terms of, or different impacts on, from 

24 new standards. 

25 So, part of is that. And I guess the other 

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1 thing I wanted to state was, the other item was, the 

2 fact that with a lot of the new technologies, with the 

3 new merchant plans going on line, especially in New 

4 England, and California and actually in several parts 

5 of the country, the impact of merchant plans and the 

6 wild card especially of distributed generation. Well, 

7 increase emphasis on combined heat and power systems, 

8 and distributed generation, which is really, let me get 

9 right down to it, you know, on site generation systems 

10 and the fact that several large companies are investing 

11 capital to, you know, sell and service the systems 

12 throughout the United States. I think there is going 

13 to be a lot more, I will say wild· cards, for lack of a 

14 better word, in terms of this type of analysis that I 

15 am not, you know, again, I am not, I am partially 

16 familiar with it, I am not totally familiar with it, 

17 but I think they are going to have a significant 

18 impact. And they will have an impact in terms of, you 

19 know, what, you know, customer self generation, I 

20 guess is the other word to say it. All of these 

21 factors are going to, you know, play into NEMS a~d 

22 ideally they will be accounted for, because they will 

23 have an impact when you get down to heat rate 

24 conversions as well, you know, onsite electrical or 

25 natural gas type of usage . 

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1 I mean, well, especially on the commercial 

2 side. Even residential, for example, if you are 

3 generating electricity on site, some of the, I will 

4 call it the waste heat, might be used for thermal 

5 applications, base heating or water heating. Well, if 

6 you reduce your, if you are having, if you are 

7 producing it on site and you are reducing the usage of 

8 the water heater or clothes washer, are you, what 

9 exactly are you saving, if it is just basically, I will 

10 say "waste heat." I don't want, you know, it is not 

11 necessarily waste heat, but r· will just say it, it is a 

12 generation process. It could be considered extract 

13 heat . 

14 So, I mean, this is just some of the issues 

15 that ideally could be, need to be addressed in this 

16 type of analysis. Because it will, it will have an 

17 impact on your final numbers when you get to the 

18 National Energy Savings. Thank you. 

19 MS. NADER: Thank you. At the mike? 

20 MR. ECKMAN: Tom Eckman, Northwest Power 

21 Plant Council. 

22 Jim, does the NEMS model take into account 

23 the reduced energy consumption due to the water 

24 savings, at the treatment facility? 

25 MR. MCMAHON: I don't know the answer to that. 

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1 I have not checked. We will check that. 

2 MS. NADER: Yes. 

3 MR. MORRIS: Wayne Morris with AHAM. 

4 I have a question, Jim, in terms of the 

5 utility impact situation. 

6 In the ANOPR, it states that you are looking 

7 at an utility analysis in terms for a baseline versus a 

8 standards case kind of scenario, I believe. Does the 

9 baseline assume the impact of the most recent 

10 refrigerator rule and the room air conditioner rule in 

11 terms of this, since they will be also taken into 

12 account when you do or at least the Department will be 

13 taking them into account when you do the multiple 

14 scenarios of standards cases on manufacturers. 

15 MR. MCMAHON: Are you talking about the rules 

16 that have already been finalized? 

17 MR. MORRIS: Yes. 

18 MR. MCMAHON: Yes, it does. 

19 MR. MORRIS: Thank you. 

20 MS. NADER: Thank you. Glenn? 

21 MR. SCHEEDE: Glenn Scheede. I just think 

22 that if people are not familiar with the NEMS model, 

23 and how this thing is developed, you ought to get 

24 familiar with it, and you ought to recognize that it is 

25 fundamentally behind what is happening in the industry. 

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1 It is always a couple of years behind, because the 

2 industry is changing a lot and the NEMS model is 

3 heavily based on historic data and historic 

4 relationships and historic algorithms. 

5 So, if you are assuming that this is a good 

6 predictor model, it is, they try, they try hard to do 

7 it, but it is inherently behind. And if you are 

8 concerned about some of the things that Steve ta~.ked 

9 about, you ought to get familiar with the assumptions 

10 that drive that model, because they are not necessarily 

11 up to date. 

12 MS. NADER: Thank you. 

13 MR. JONES: Earl Jones, here. Again, I have 

14 a question. I just want to know, again, Jim, with 

15 respect to both these analysis or models, that you just 

16 presented. How much of the data is available to the 

17 people who are in this room? 

18 MR. MCMAHON: All of the data. 

19 MR. JONES: All of it is. 

20 So, if you wanted to find the information 

21 that supports this indirect employment impact, where 

22 would you find that? Where is that? Is that in --

23 MR. MCMAHON: There are two reports from the 

24 Pacific Northwest Laboratory. 

25 MR. JONES: I am sorry? 

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1 MR. MCMAHON: There are two reports from the 

2 Pacific Northwest National Laboratory, that are 

3 available. 

4 MR. JONES: They are not in any documents 

5 provided so far, are they? 

6 MR. MCMAHON: I don't believe so. 

7 MR. JONES: Okay. And I am just curious, 

8 Bryan, is it the Department's intention to somehow put 

9 those in the record or are we suppose to go get them 

10 from the lab? 

11 MR. BERRINGER: If they are publicly 

12 available, we will get copies of them. We will make 

13 sure, you know, anybody that requests them, we will get 

14 a copy to you. 

15 MR. JONES: So, is this a request or do you 

16 want me do to something other than make it now? 

17 MR. BERRINGER: No. 

18 MR. JONES: Okay. Thank you. 

19 And then what about the second one, the NEMS, f 

20 that is a DOE developed, if I understood, model. 

21 MR. MCMAHON: That is correct. 

22 MR. JONES: Which is available where? 

23 MR. MCMAHON: From the Energy Information 

24 Administration in this building. 

25 MR. JONES: Okay . 

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1 MS. NADER: Thank you. Other questions? 

2 Additional comments? 

3 MR. MONTUORO: Lou Montuoro, Amana Appliances. 

4 I need to go on the record with a couple of 

5 comments. 

6 Number 1, Amana would like to officially 

7 request an extension to the February 2nd comment 

8 period, for two months, to go from Groundhog Day to 

9 April Fools Day. As our friends in Whirlpool so 

10 elegantly put, this is an important issue. We are 

11 doing the best we can to understand the model, how it 

12 affects our company. And we will be able to give you 

13 better quality of feedback back . 

14 I think this was, it was, it happened, you 

15 know, the ANOPR came out right before Thanksgiving. It 

16 comes during corporate holiday time. I think it was 

17 probably delayed because of the complexity of the 

18 situation. 

19 So, we are officially requesting that. 

20 And the second item, there was some cost 

21 information, I wasn't sure if it was sensitive or not, 

22 on tear down analysis of the H axis machines, not the 

23 prototype. And we would like to obtain the data from 

24 that, if that is publicly available. Al and I think 

25 that is public data and we should be able to get that. 

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1 MR. BERRINGER: And the reason you say you 

2 need two months for the extension of the comment period 

3 were reasons of holiday, is that an absolute necessity? 

4 MR. MONTUORO: Well, the question is how much 

5 time we have to analyze the impact on our company and 

6 give you a response with data. And right now we are 

7 looking at a February 2nd date. And it is very 

8 important to our company and we are working on it, but 

9 obviously we will be able give you better information, 

10 better feedbacks if given more time. The question is 

11 what is reasonable? So, we think it is reasonable 

12 to ask for a two month extension. 

13 MR. BERRINGER: Okay. And does anybody have 

14 a calendar as far as when that would be? 

15 MR. MONTUORO: April 1st. Two months. That 

16 would be a Thursday, April 1st. 

17 MR. BERRINGER: Were you finished? 

18 MR. MONTUORO: Yes. 

19 MR. BERRINGER: Okay. 

20 MS. NADER: Yes, Mike? 

21 MR. MCCABE: This is Michael McCabe with the 

22 Department of Energy. 

23 The follow up question, Lou, with respect to 

24 additional time, if you could be more specific as to 

25 what parts of the analysis that you would need 

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1 additional time, because for example, with what Mike 

2 Rivest of AOL had presented on the manufacturer impact 

3 analysis, there are going to be a series of one on one 

4 meetings that will be taking place. And if you need 

5 additional time to provide input on the manufacturer 

6 impact analysis, there will be that exchange during the 

7 February and March time frame. If it is additional 

8 time to comment on the NES analysis or life cycle cost 

9 analysis, we would appreciate some of those specifics. 

10 The request will be considered by the Department as Dan 

11 Reicher indicated, he is committed to issuing a final 

12 rule by September of 2000. And that any request for an 

13 extension of the comment period, you know, that he will 

14 evaluate as to what impact that will have on the 

15 schedule and would be interested in others, in what 

16 they would have to say as far as what the additional 

17 time would be of value to them. But, particular with 

18 your request, you know, if you could provide some more 

19· specifics as to the areas of the analysis that you 

20 needed the additional time. 

21 MR. MONTUORO: Sure. Right now, of course, 

22 what is important to us is do our financial models 

23 represent our small manufacturer. We are doing the 

24 best we can to understand that. We understand there 

25 was aggregate data provided by AHAM. So, we would 

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1 understand that along with our options. The ANOPR, I 

2 think delineates, I think it is about 11 items, for 

3 comment on, including some of the things we have 

4 covered, the product class size, the detail on retail 

5 mark-up assumptions, information the elasticities. I 

6 thought the ANOPR was asking for responses to those 

7 items. And to give, to give response to those items 

8 and the work on those, those are the basic items that 

9 we talked about before this meeting. Since coming 

10 yesterday, I found out that there is going to be some 

11 additional interviewing processes with our company, 

12 which is good. But, nonetheless, to respond to the 

13 ANOPR and all the items that are listed in the ANOPR, 

14 all the complexities that we are talking about here, we 

15 are asking for an extension from February 2nd. 

16 MS. NADER: Mike, do you have anything else? 

17 MR. MCCABE: I will stay here because I 

18 suspect that there will be some more. 

19 MS. NADER: Okay. Thank you. Yes? 

20 MR. MORRIS: Wayne Morris with AHAM. 

21 We polled our members and a majority, not a 

22 unanimous position but the majority of the members did 

23 ask for an extension of time to respond to the items 

24 

25 

that are in the ANOPR. It is a particularly difficult 

time period with the holidays. A number of trade shows 

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1 that do come about in January and February of this 

2 year, with the International Housewares show in Colgna . 

3 As Lou pointed out, there are quite a lengthy period 

4 of, amount of materials. in the ANOPR that are asked for 

5 responses to. Our members did feel that additional 

6 time is necessary. 

7 The amount of time seems to vary between 90 

8 days and 60 days, 45 days. But, I think Lou's proposal 

9 of 60 days is probably in the ballpark of where the 

10 majority of companies that wish an extension to be. As 

11 I said, this is not an unanimous opinion by any means, 

12 but it was a majority of the companies that we polled. 

13 MS. NADER: Thank you. Steve Nadel? 

14 MR. NADEL: Thank you. I guess we have 

15 substantial problems, as no one would be surprised, 

16 with a request for extension. When the process 

17 improvement rule came out, rules were suppose to be 

18 completed within three years. This rule is suppose to 

19 be an accelerated rule because it already started. We 

20 are now more than three years into it, at least two 

21 years to go. Now, we want to extend it further? I 

22 think a iradeoff was made during the process 

23 improvement, that basically said, we are going to have 

24 more frequent reviews, but we are going to have shorter 

25 reviews. If we are going to have more frequent reviews 

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1 than longer reviews, it just doesn't work. So, I think 

2 people have to make a basic decision, do they want a 

3 few long reviews or more short reviews? 

4 I would ask the gentleman from Amana, you 

5 know, on top of DOE's request, what particular things 

6 they do, if he sees some particular areas subsequently 

7 in this schedule, where, gee, if you take two months 

8 here, we can cut a month here and a month here. That 

9 is reasonable, I think. It would be very helpful to 

10 have those suggestions. 

11 I had also observed that, at least from my 

12 reading of the ANOPR, most of the issues that are here 

13 are just a restatement of things that we came up with 

14 during the last workshop. I don't see very much new 

15 material. The only real significant new material is 

16 the reverse engineering on a few more models. But, I 

17 mean, when I reviewed it, my thing was, gee, maybe we 

18 shouldn't have had that last workshop and comment 

19 period. We are just repeating that. I would think the 

20 time would be better spent elsewhere. But, if people 

21 want more comments now and then we will just go 

22 straight to ANOPR, short period and then straight to 

23 final rule, we can. But, I don't think this is the 

24 place where the time is best spent. 

25 MS. NADER: Thank you . 

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1 MR. THOMPSON: Mike Thompson, Whirlpool 

2 Corporation. 

3 We are one of the companies that did object 

4 to an extension of the comment period. We all know 

5 that DOE is years behind on promulgation of a final 

6 rule on clothes washers. We all know that DOE 

7 continually has allowed the rulemaking to slip time 

8 line wise. The last thing that I knew it was going to 

9 be a July extension. This morning I walked in, 

10 surprised to see another two months slip by. So, at 

11 this point in time, we vehemently oppose any further 

12 extensions. 

13 MS. NADER: Thank you. Steve? 

14 MR. ROSENSTOCK: Just a quick question. Steve 

15 Rosenstock, EEI. 

16 It says publish ANOPR in November of '99 and 

17 then final rule in September 2000. I guess that is 

18 about a nine month in-between. What is the reason? 

19 Was that increased or decreased or I am just kind of 

20 curious, it sounds like some people think that it would 

21 maybe increase for some reason, and maybe that is a 

22 period where you could shrink it. You know, add a 

23 little period here for the comments and then shrink it 

24 back at that final end. Is that, because OMB or 

25 Justice Department reviews are going to take longer or 

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1 what? 

2 MS. NADER: Yes, sir. 

3 MR. ROSENSTOCK: That was for DOE, by the way. 

4 That was a question for DOE. 

5 MR. MCCABE: Yes, Michael McCabe, DOE. 

6 The changes in the schedule that are there 

7 reflect some additional analysis that upon review could 

8 not be done in parallel but are done in sequence and 

9 series. Particularly, the work that is, discussions 

10 going on or about to start, on the consumer survey, 

11 because that is going to be feeding into the energy 

12 savings analysis, which it had not been fully captured 

13 in some of the earlier schedules. Also, the, some of 

14 the time periods for some of the steps in the analysis 

15 or in the process, had been unrealistically short. The 

16 Secretary and OMB reviewed concurrent and lessen time 

17 than what has been done in the past. So, that this is 

18 a schedule that I feel is now, has all the bugs ironed 

19 out and is reasonable and obtainable. 

20 In looking at the request, one of the things 

21 which I will be looking at in making my recommendations 

22 to Dan Reicher, you know, is again, how will it affect 

23 the overall schedule. We have some analysis that is 

24 underway. Any delays of 90 days, for example, would 

25 affect that analysis. A delay, a shorter delay may not 

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1 affect it, but I am not sure how short of an extension 

2 we have to get to where it will not affect it. So, be 

3 looking at that. And that is one of the reasons why I 

4 am asking for specifics in order to be able to try to 

5 break up the comments and some different parts to get 

6 some in earlier. And some of the other, later, which 

7 may not be on the critical path. 

8 MS. NADER: Thank you. Yes? 

9 MR. MARTIN: Michael Martin, California Energy 

10 Commission. 

11 We at the Energy Commission have supported in 

12 good faith NECA, the Energy Policy Act, this changing 

13 of procedures and we desperately want to keep out of 

14 getting into this preexemption and petitioning and all 

15 the rest of it. And my commissioners would be very 

16 upset if I was to come back and say that this has 

17 slipped yet another couple of months, you know. We 

18 have acted in good faith on this, this, these various 

19 different steps. And we need to stick with this, with 

20 what we have, the schedule we have here. 

21 MR. JONES: Earl Jones, here. G.E. 

22 I think everybody, I hope has acted in good 

23 faith, and I think certainly the manufacturers have. 

24 These requests for extensions, are not for the purpose 

25 of delaying this rulemaking if you had to collect the 

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1 data and do the analysis, you would understand the 

2 complexity of what you are asking us to go through. We 

3 have lost a month in that process through the holidays. 

4 That is just gone. A request for the additional time 

5 is not unwarranted. There is no delay in this process 

6 that you can lay at our doorsteps. If you want to make 

7 adjustments in the schedule internally, I mean, I don't 

8 see any problem with that. And DOE, you know, have 

9 added, whatever your best guess on that is. But, I 

10 don't think, nobody should for any moment suggest that 

11 any part of the delay in this schedule, the slippage is 

12 caused by the manufacturers. It has not been. It is 

13 principally been caused by the Department's own 

14 internal deliberations. And do not put that on our 

15 doorstep. If there is a problem here, look inside the 

16 Department to fix it. 

17 Certainly, this request is reasonable and 

18 there is no reason why anybody should deny it or cast 

19 dispersions on the people who are requesting it, for 

20 making it. 

21 I do want to make other comments about the 

22 rulemaking generally, when you get into the point, but 

23 I suppose if you are still on the question of the time 

24 table, I will defer those. 

25 MS. NADER: Thank you. Other comments on the 

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1 time period? 

2 MR. ROSENSTOCK: Not on the time period. Jim, 

3 are you going to talk about the environmental analysis 

4 now? That was the last step. 

5 MS. NADER: Let me just check with Bryan, who 

6 is our leader here. I am concerned about the time. We 

7 were suppose to finish at 4:30 and it is almost 10 to 

8 five now. 

9 MR. BERRINGER: Yeah, we have the people on 

10 hold over, that we are going to call in on the consumer 

11 groups. To let them know that we are running behind. 

12 And as Michael said, we will evaluate the comment 

13 period time. And obviously, we will have to a Federal 

14 Register notice to extend, do an extension. So, we 

15 will consider that and get back with everybody on that. 

16 MR. MORRIS: Wayne Morris. Bryan, just, not 

17 to belabor this, but is it possible to get an answer to 

18 that before the holidays? 

19 MR. BERRINGER: We will try to get you an 

20 answer before the holidays. 

21 MR. MCCABE: Michael McCabe. We have got a 

22 meeting 

23 will get 

24 least at 

25 

with Dan early next week, so that hopefully 

his call by then and get it out informally 

that time. 

MS. NADER: Thank you . 

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1 MR. MCMAHON: The last presentation is the 

2 environmental analysis. It is on the last slide of 

3 that handout. The purpose is to estimate the impacts 

4 from the standards on U.S. emissions of oxides of 

5 carbon, nitrogen and sulphur. The methodology is to 

6 get the power plant emissions from NEMS, when we do the 

7 utility analysis, the emissions will also come out of 

8 the same model. There are two things that NEMS does 

9 not cover that we will add with spreadsheet estimates. 

10 One of those is sulphur oxide emissions from oil fired 

11 water heaters and the other is noxide emissions from 

12 gas fired water heaters in the home. 

13 Are there any questions? 

14 MS. NADER: Steve? 

15 MR. ROSENSTOCK: Steve Rosenstock, Edison 

16 Electric Institute. 

17 Looking at the technical support document, at 

18 Table 12.1, MT/A, what does that refer to? I wasn't 

19 sure what that, was that metric --

20 MR. MCMAHON: I believe that is million tons 

21 per year. 

22 MR. ROSENSTOCK: Is that million --

23 MR. MCMAHON: Per anna. 

24 MR. ROSENSTOCK: For anna, million metric 

25 tons? 

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1 MR. MCMAHON: Yes. 

2 MR. ROSENSTOCK: Okay. Okay, it says, .well, 

3 again, I still get, I have some problems with this just 

4 because, whether it is really, you know, it is an 

5 energy impact, not an environmental because a lot of 

6 the issues that I said before, about the changing, 

7 especially the changing electric industry, spills over 

8 into this, because as residential customers have 

9 choices of suppliers, and the fact that they might be 

10 able to change suppliers. on a yearly or monthly basis, 

11 some of these numbers get very, very interesting. I 

12 mean, it is, you know, with choice there could be some 

13 quite dramatic changes over the 30 years, is what I am 

14 saying. So, that the C02, NOX and S02 numbers could 

15 vary widely from household to household. It is not 

16 just the regional model anymore. That is number one. 

17 Especially with on site generation and distributed 

18 generation. And those impacts could also play quite the 

19 role. 

20 Also, as a criticism, if you are doing this, 

21 you are neglecting carbon monoxide. And particularly 

22 organic compounds in the in house combustion. Which do 

23 have impacts, which are emissions or pollutants, 

24 whatever the word you want to use. 

25 The other thing I was going to say is in 

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1 terms of both the natural gas and oil, it seems that, 

2 you know, the boundary of the system is a household and 

3 that is it. Whereas, for electricity, you take it from 

4 outside the house ·to the power plant or generation 

5 source. I don't want to get in -- versus source. You 

6 know, I don't want the arrows thrown at me, but if it 

7 is going to be consistent, then you have to take into 

8 account transmission production losses for natural gas, 

9 as well as fuel oil. I mean, that is, you know, if, if 

10 you want to do that and if you want to, you know, 

11 because there are transmission losses for natural gas. 

12 There are losses for oil as well as production in 

13 transmission . 

14 So, I just wanted to put those out there and 

15 especially that, you know, again, assuming, you know, I 

16 think there are going to be a lot of changes in the 

17 power sector, especially when people choose their power 

18 plants. And it going to have quite a dramatic impact 

19 when you look outside the house for some of the actual, 

20 what is the environmental impact of the future Energy 

21 Standards. 

22 So, those are my comments. I am glad I made 

23 them late in the day, when some people are tired not to 

24 kill me. Thank you. 

25 MS. NADER: Thank you. Yes, sir? 

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1 MR. GREGG: Tony Gregg, City of Austin. 

2 I think this is similar to the other issue of 

3 where they would be emissions savings also from the 

4 electric savings at water utility plants. So, I would 

5 like to see if we could, if they are not factored, if 

6 they could also be factored. Thank you. 

7 MS. NADER: Thank you. 

8 (Pause.) 

9 MS. NADER: Earl, do you say that you had some 

10 comments? 

11 MR. JONES: Yes. Just a minute, please. 

12 MS. NADER: I would ask that they be very 

13 brief . 

14 MR. JONES: They will be. 

15 Well, I just wanted to sort of leave my 

16 comments on the workshop. I still continue to be very 

17 ·impressed by the progress that DOE has made in the 

18 process improvements. And I really mean that. That is 

19 the positive introduction. And I mean that the 

20 But, seriously, Bryan, I mean, a lot of 

21 effort has been put into this and I can see the work 

22 and a lot of it is much more understandable. Which is 

23 very important for me, at least. But, I am, when I 

24 come to the workshops, and this one is similar in that 

25 ~espect, I have this sense of progress two steps 

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1 forward and one step back. Because at the same time we 

2 are making these great strides towards understanding 

3 and transparency, at least, speaking in English, etc. 

4 There is a whole another half of this rulemaking which 

5 is still very much in the black box. And that I am 

6 afraid is these analysis and these models, which we 

7 don't, I do not understand how it is going to finally 

8 impact this rulemaking. But, I have this awful feeling 

9 that to spite all the positive things that are 

10 ·happening, there is this thing waiting out there and it 

11 is going to bounce. 

12 So, there is a real credibility problem with 

13 the rulemaking. And I just want to stress the 

14 importance between now ~nd the next phase, getting 

15 through the NOP~ to try to close that gap to increase 

16 the ability of the participants to understand where 

17 the, how the data is being used, how it is going to 

18 impact, how it is going to, how the second half, if you 

19 will, is going to now come back into the picture. And 

20 affect the, what I consider a very good analysis having 

21 been done to date. This is a very serious question. 

22 There is a real issue of being able to make this 

23 process work. Let's understand that we understand, 

24 that we know that everybody is not going to be pleased 

25 the way this thing works out. That is the way the 

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1 process works and that is just the way it falls. 

2 But, in the process of doing that, people 

3 should have clear understanding of how they are going 

4 to be impacted. And there should be few surprises. 

5 And I am concerned that there will be more surprises in 

6 the wings. And I think I would like to try to avoid 

7 them as much as possible. Thank you. 

8 MS. NADER: Thank you. Anything else, 

9 anyone must say before we call it a day? Okay. Thank 

10 you. You all have worked very hard. I appreciate your 

11 active engagement. 

12 Bryan, would you like to say the last few 

13 words? 

14 MR. BERRINGER: I would just like to thank 

15 everybody for sticking around. We will probably, take 

16 a couple of minutes and then we will go over to -- The 

17 people that want to stay for the consumer working group 

18 it is right across the hall. We have the phone hooked 

19 up, so people, everybody is welcome to that, come to 

20 that meeting. It is open. If people want to stay here 

21 and they will have some time if they want discuss other 

22 things. 

23 Again, thank you very much. 

24 (Whereupon, at 5:10 p.m., the meeting was 

25 concluded.) 

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REPORTER'S CERTIFICATE 

This is to certify that the attached 

proceedings before: U.S. DOE 

In the Matter of: WASHER WORKSHOP 

were held as herein appears and that this is the 

original transcript thereof for the file of the 

Depart!llent, Commission, Administrative Law Judge 

or the Agency. 

Dated: 12t15-98 

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