# Peer Review for the Report, “How Consumers Value Fuel Economy”

A Literature ReviewEPA-420-S-10-001 April 2010 Assessment and Standards Division Office of Transportation and Air Quality U.S. Environmental Protection Agency 

# Peer Review for the Report, “How Consumers Value Fuel Economy”

A Literature ReviewMarch 30, 2010

MEMORANDUM

SUBJECT: Peer Review for David Greene pape r, “How Consumers Value Fuel Economy: A Literature Review”

FROM: Gloria Helfand, Assessment and Standards Division Office of Transportation and Air Qualit y, U.S. Environmental Protection Agency

In December 2009, EPA contracted with RTI International (RTI) to conduct a peer review of a literature survey conducted by David Greene of Oa k Ridge National laboratory. The draft study, titled “How Consumers Value Fuel Economy: A Lite rature Review,” looked at 22 papers that, in some fashion, provided quantitative estimates of the role of fuel economy in consumer vehicle purchase decisions.

The three peer reviewers selected by RTI were Dr s. Carolyn Fischer of Resources for the Future, Christopher Knittel of the Univer sity of California at Davis, and Walter McManus of the University of Michigan. EPA would like to extend its appreciation to all three reviewers for their efforts in evaluating this survey. The three re viewers brought useful a nd distinctive views in response to the charge questions.

The first section of this document contains the final RTI report summarizing the peer review of David Greene’s literature survey, including the detailed comments of each peer reviewer and an overview of the most significant comments compile d by RTI. The RTI report also contains the peer reviewers’ resumes, the charge letter, and cover letters from each reviewer explaining any real or perceived conflicts of interest. The s econd major section contains our responses to the peer reviewers’ comments. In this section, we repeat the summarized comments provided by RTI and, after each section of comments, prov ide our response. We have retained the organization reflected in RTI’s summary of the comments to aid the reader in moving from the RTI report to our responses.

CONTENTS I. Peer Review of EPA’s Study of Vehicle C hoice Models for Estimating Impacts of Fuel Economy, conducted by RTI International 1. Background 2. Description of Review Process 3. Summary of Review Comments 4. References Appendices A. Resumes of Selected Reviewers B. Charge Questions C. Cover Letters D. Reviews II.. EPA’s Response to Peer Review CommentsTO: Kent Helmer, Gloria Helfand, U.S. Envi ronmental Protection Agency, Office of Transportation and Air Quality (OTAQ)

FROM: Paramita Sinha, RTI

DATE: February 26, 2010

SUBJECT: Peer Review of EPA’s Study of Vehicle Choice Models for Estimating Impacts of Fuel Economy



### 1. Background

The U.S. Environmental Protection Agency’s (E PA’s) Office of Transportation and Air Quality (OTAQ) is involved in expl oring the regulation of CO 2 and other greenhouse gas (GHG) emission control measures in motor vehicles and equipment. An important component of the costs of such regulations is the cost of impr oved technology, while the benefits include, among others, the value of reduced fuel consumpti on. Understanding the role of fuel economy in consumer vehicle purchases will contribute to EP A’s assessment of the impacts of its rules on vehicle sales.
EPA is assessing the use of consumer vehicle c hoice models to analyze the impacts of regulatory programs that affect fuel economy. Coefficients from discrete choice models of consumer vehicle choice are typically used to estimate th e value of improving fuel economy. Other studies use hedonic price methods. These vehicle choice models could help EPA anticipate market responses to vehicle regulations and thus judge the effectiveness of regulations.
EPA is analyzing a set of existing consumer ve hicle choice models to see whether there is a robust estimate of the value of additional fuel economy to consumers. EPA is seeking a peer review of its comparative study of consumer vehicle choice models and what each model may predict for the value of improving vehicle fuel economy at the time of vehicle purchase. This report contains documentation of the peer review process for the vehicle choice study.
Section 2 of this memorandum provides a description of the process for choosing reviewers, administering the review process, and closing the peer review. Section 3 c ontains an overview of the comments made by the panel of reviewers. The appendices to this memorandum provide the resumes of the reviewers; charge letter to the peer reviewers, which describes their task and what was

RTI International is a trade name of Research Triangle InstituteKent Helmer, Gloria Helfand February 26, 2010 Page 2

requested from them in terms of deliverables; and the cover letters and review comments from the panel.



### 2. Description of Review Process

In December 2009, EPA’s OTAQ contacted RTI Internat ional to facilitate the peer review of EPA’s study of vehicle choice models for estimati ng impacts of fuel economy regulations. This study, authored by David L. Greene, is entitl ed “How Consumers Value Fuel Economy: A Literature Review.”
EPA provided a short list of subject matter expe rts from academia and industry (Appendix A of the performance work statement) to RTI, and this served as a “starting point” from which we assembled the list of peer reviewers. RTI selected three independent (as de fined in Sections 1.2.6 and 1.2.7 of EPA’s Peer Review Handbook) subject matter experts to conduct the requested reviews. Subject matter experts fa miliar with economic valuation, di screte choice models and the use of these models for valuat ion, and the use of these models for predicting automobile purchases were selected.
To ensure that the review process was conducte d in a timely manner, RTI contacted potential reviewers within a week of su bmitting the work plan and determined that each reviewer would be able to perform work during the period of performance. To make the review process as credible as possible, RTI did not consult the Agen cy in the final determination of reviewers. RTI obtained the resumes of the se lected reviewers, and these are included in Appendix A.
RTI provided the panel reviewers with the final edited version of the analysis that each subject matter expert was expected to review along with a set of charge quest ions (both provided by EPA) in the first week of January. 1 The memo from RTI to the reviewers with the charge questions is included in A ppendix B of this report.

A teleconference between EPA, th e reviewers, and RTI was organi zed to provide an opportunity to the panel to discuss any ques tions or concerns they may have regarding the material provided and expected deliverables. Completed reviews from the panel were sent to EPA by the requested date. These reviews included the response to the charge questions and any additional comments the reviewer may have had (e.g., margin notes on review materials). From each reviewer, RTI

1 Upon request from one of the reviewers, EPA provided RTI with two examples of previous peer reviews, and these were subsequently forwarded to them. These are entitled “Peer Re view for the RTI Report, Automobile Industry Retail Price Equivalent and Indirect Cost Multipliers (Assessment and Standards Division, Office of Transportation and Air Quality, U.S. Environmental Protection Agency, J une 2009, EPA-420-R-09-004 ) and “Review: Vehicle Greenhouse Gas Emission (VGHG) Emissions Cost and Compliance Model (Jonathan Rubin, January 2010).Kent Helmer, Gloria Helfand February 26, 2010 Page 3

obtained a cover letter sta ting the reviewer’s name; the name a nd address of their organization if applicable; a list of review documents/media r eceived by the reviewer and which were actually reviewed; and a statement of any real or perceive d conflict(s) of interest . The cover letters and reviews are included in Appendi ces C and D, respectively.



### 3. Summary of Review Comments

Carolyn Fischer (Resources for the Future), Christopher Knittel (Dep artment of Economics, University of California at Davis), and Walter McManus (University of Michigan, Transportation Research Institute) review ed “How Consumers Value Fuel Economy: A Literature Review.” This section provides a summary of the comments received from them.



### 3.1 OVERALL APPROACH AND ME THODOLOGY OF THE STUDY
The reviewers are suppor tive of the overall approach and methodology.

Walter: “ The overall approach and methodology are with in the mainstream of critical review practice in economics, and the ex ecution in unexceptionable.” He does comment on the fact that “Greene (2009) adopts a conventional ‘literatur e review’ approach” and “both the conventional approach to reviewing economic research and th e conventional approach to economic research itself do not give much help to decision make rs who are understandably made uncomfortable by the widely differing expert opinions about parameters that are crucial in predicting the impacts of regulations and in choosing between alternatives. An overall criti que of conventional practice is beyond the scope of this review. However, I do ha ve some suggestions for improvements in the methodology for comparing studies and for deali ng with the lack of consensus in expert opinions. (The References section below lists some papers by Edward E. Leamer, a professor at UCLA, in which a critique of c onventional practice is developed along with altern ative practices that would enhance the usefulness of economic research to policy makers.)”
Chris comments that the study does not discuss “ why consumers undervalue gasoline, relative society (if they do indeed underv alue fuel economy). This has im portant implications for which policies are most effective at aligning discount rates.” However, he recognizes that papers dealing with such issues are lacking.Kent Helmer, Gloria Helfand February 26, 2010 Page 4



### 3.2 APPROPRIATENESS OF TH E DATASETS AN D ANY OTHER INPUTS

One reviewer commented that the choice of the papers was comprehensive. Another reviewer recommended including some explanation of how the studies were selected for inclusion in Greene (2009).



### 3.3 DATA ANALYSIS COND UCTED FOR TH E STUDY

Two reviewers comment on the fact that the type of analysis done for the different papers varies greatly.

Chris: “It strikes me that there are two ways to conduct a review su ch as this. One is to report the results of papers with little, or no, discussion of the quality each paper. The other is to both review and critique each paper. I found a lack of uniformity in this regard. For many of the papers, the latter strategy is taken. The report di scusses key weakness of these papers. Still many papers are simply summarized, with little or no discussion of their strengths or weaknesses. This gives the impression that the resu lts in these papers are more accurate. This may actually be the case, but if it is, this should be stated more explicitly.
For example, the first paper (A lcott and Wozny) is simply su mmarized with no editorializing. One possibility is that there are no weaknesses in this paper. But, many of the issues raised later for other papers also relate to this paper. For example, the report correctly states, when discussing the Sawhill paper, that in order to ge t a consistent estimate of how consumers value fuel economy, the author is requir ed to correctly specify how cons umers form expectations about gas prices and drive their vehicles. If any of th ese are incorrectly specified, the estimate will be biased. The same is true for the Alcott a nd Wozny paper. While I find Alcott and Wozny’s specification for how expectations are formed to likely be more accurate, ironically, they assume consumers are hyper-rational in the sense that th ey form their gas price expectations based on NYMEX futures prices. In some ways the myopi a result is inconsistent with this key assumption.”
Walter: “It is difficult for the reader to verify that the same standards are being used to assess each paper, especially since th e amount of discussion by paper va ries greatly. This leads the reader to have less confidence in the reviewer’s opinions of the individual studies (that this or that one had plausible or implausible assumption, methodologies, or results).”Kent Helmer, Gloria Helfand February 26, 2010 Page 5



### 3.4 APPROPRIATENESS OF THE CONCLUSIONS DRAWN
There was general consensus among the reviewers on the major conclusion of the document: that the literature remains mixed as to whether consumers underv alue, overvalue, or approximately value fuel economy.

One reviewer raised doubts that differences in assumptions, opinions, and methods have been sufficiently examined to support even the weak pr oposition that “there do not appear to be clear associations among methods or data sources and the resulting inferences.”
One reviewer expressed doubts abou t what Greene means by “inc orrect models” of consumer decision making about fuel economy but suggest ed efficient markets hypothesis and economic rationality to be a possible in terpretation of this phrase.



### 3.5 RECOMMENDATIONS FOR ALTERNATE DATA AND/OR ANALYSES

3.5.1 Additional Data Two of the reviewers suggested several other stud ies that are relevant for this work. A list of these studies is provided below.
Dreyfus, Mark K. and W. Kip Viscusi (1995) . “Rates of Time Preference and Consumer Valuations of Automobile Safety and Fuel Efficiency.” Journal of Law and Economics 38: 79-98.

Hughes, Jonathan E., Christopher R. Knittel and Daniel Sperling (2008). “Evidence of a Shift in the Short-Run Price Elasticity of Gasoline Demand.” Energy Journal

. Kilian, Lutz and Eric Sims (2006). The Effects of Real Gasoline Prices on Automobile Demand: A Structural Analysis Using Micro Data, Worki ng Paper, University of Michigan (April).

Klier and Linn (2010 working paper) “The Pri ce of Gasoline and New Vehicle Fuel Economy: Evidence from Monthly Sales Data”

Klier, Thomas, and Joshua Linn (2008). “The Price of Gasoline and the Demand for Fuel Efficiency: Evidence from Monthly New Ve hicles Sales Data.” Working Paper, University of Illinois at Chicago (September).

Sallee and West (2009 working paper)Kent Helmer, Gloria Helfand February 26, 2010 Page 6

Sallee, James, and Sarah West (2008). “Testing for Consumer Myopia: The Effect of Gasoline Price Changes on the Demand for Fuel Econom y in Used Vehicles.” Working Paper, Macalester College (December).

West, S. (2008). “The Effect of Gasoline Prices on the Demand for Sport Utility Vehicles.” Working Paper. Macalester College.

3.5.2 Additi onal Analysis The reviewers suggested several additiona l analyses to strengthen the study.

3.5.ii a. The author should take advantage of the summary section to indicate whether some approaches reviewed in the study are likely to be better than others.
3.5.ii b. The analysis to explain the di fference in results could be improved. Carolyn: “First, the discussion interweaves reasons that could explain why we can plausibly believe any of a range of results (e.g., heterogene ous decision rules, uncer tainty) with reasons for why different studies get different results. It would be helpful to separate these discussions, reminding readers of the former, and then focusi ng on the latter, which is the most important contribution. This kind of analysis should help in dicate best practices and directions for future research. Can we suggest some experiments (e .g., new techniques on old data sets, or old techniques on new data sets) th at can help tease out what diffe rences arise from alternative econometric approaches? If most studies have focused on other aspects of vehicle demand, are there better specifications for looking dire ctly at the valuation of fuel economy?”
A summary of key differences in approaches and data and an analysis of their consequences would be useful. These would include

• levels of aggregation;

• time horizons (how useful is information from the 1970s in estimating current demand?);

• incorporation of the supply side;

• details of other attributes and variable definitions;

• allowing for separate responses to MPG and fu el costs (this was raised as lacking in the discussion of Gramlich, but it was not apparent which other studies had done this);

• assumptions of vehicle lifetime, VMT, discount rates, etc.; and

• econometric approach.Kent Helmer, Gloria Helfand February 26, 2010 Page 7

Although Table 10 provides some of these summa ry indicators (model type, data, and time), additional analysis such as th e following would be useful: “Do we observe any trends across classes or time? Within a class of m odels, what drives the differences?”

Walter: “It would be useful to expand Table 10 (or to create a set of tables) to show other differences that could be important sources of di fferences in estimates. The items that could be included would show differences in:

1. Maintained assumptions reported (assumptions that are maintained across any alternative specifications or sensitivities),

2. Reported sensitivity analyses (is one done? wh ich assumptions are varied? how widely?),

3. Econometric challenges and approaches used to address them (Greene (2009) appears to discuss these comprehensiv ely in the text.), and

4. Out-of-sample predictive performance (a re predictions made? about what? are the predictions compared to actual outcome s? how accurate are the predictions?). Adding these additional side-by-side comparisons would increase the reader’s confidence that the same standards are being used to form the reviewer’s opinions about the relative usefulness of each paper to inform decision making by EPA.
My opinion: The additional elements are responsible for more of the variat ion in the estimates of consumer value for fuel economy than are th e elements already included in Table 10.”
He also suggested a measure of researcher/s pecification uncertainty and disagreement to quantitatively assess whether we have made progr ess toward a consensus. He also provides illustrative suggestions on ways to use and interpret this measure. “The idea is to compare the range of parameter estimates to the parame ter value predicted by mainstream theory.”
The metric is called Multiple Extreme Estimates Test (MEET) and is defined as the ratio of the value predicted by theory to the differ ence between the two extreme estimates.
Value Predicted by Theory V MEET = = Largest Estimate - Smallest Estimate R
lim MEET = 0 and lim MEET = ∞ R →∞ R → 0 “Numerically, MEET measures the pr edicted value as a share of the range of expert opinion. The range of expert opinion, R, is a crude and partial measure of the uncertainty or fragility of the estimates due to differences in assumptions, specification, and opinions between researchers. The metric MEET views this fragility compared to the theoretical value of the parameter, V.”Kent Helmer, Gloria Helfand February 26, 2010 Page 8

3.5.ii.c. Though the issue of consumer hete rogeneity has been mentioned in several places, this may be important area for additiona l analysis, both to explain differences and to suggest future research directions.



### 3.6 OVERALL CLARITY OF THE PRESENTATION
The reviewers agreed that the overall clarity of the document was high.
Reviewers had several suggestions about organizing the paper.

i. One reviewer suggested that since the articl es are organized logically by class of data and methods, it would be helpful to review thos e methods at the beginning of each section “including the advantages and drawbacks, as well as key factors or assumptions that can affect the results.”

ii. It has also been suggested that it would be helpful to begin with the seminal papers in each category, “so as to understand the evolut ion and improvements made subsequently.”

iii. Two reviewers agreed that the publication status of papers should be recognized and one reviewer suggested that the review should “focus first on published papers and then second on unpublished papers.”
iv. Chris Knittel: “Many of the papers revi ewed did not focus on measuring the implicit discount rate, or even on the issue of how gas prices affect vehicle demand. If a paper did not focus on either of these two questions, it is difficult to gauge the robustness of their results with respect to these questions, the qua lity of the variation in gas prices in the data, etc. Perhaps a better method would be to first focus on those papers where gas prices and vehicle choice are the central resear ch question, and those papers where this is more a tangential part of the analysis.”
On a related note, another reviewer commented on studies that do not explicitly estimate the value of fuel economy: “Since few econometric st udies have explicitly es timated the value of fuel economy, a significant contribution of the paper is to translate a wide variety of results into more consistent indicators. Yet, they could still be more consistent. In Table 10, can all of the results be converted into the same WTP metric , preferably using the same assumptions about vehicle lifespan, VMT, discounting, etc.?”
Another comment on the presentation of the paper was that “the author’s baseline assumptions need to be stated clearly early in the paper, so careful attention can be given throughout to assumptions that deviate from that baseline. Indeed, the statement made in the Allcott and Wozny analysis (‘Calculating the discounted pres ent value of fuel cost s requires a number of assumptions...’) should be made earlier in a genera l context, so that th e variety and range of assumptions can be understood and explored.”Kent Helmer, Gloria Helfand February 26, 2010 Page 9



### 3.7 OTHER CLARIFICATION COMMENTS
One reviewer provided the follo wing comments to clarify or rephrase certain statements.

1. The authors should “use the phrase ‘at society’s discounted expected value...’ (top of page 5) instead of ‘does the market value fuel economy improvements at the discounted expected value of future fuel savings over the lifetime of the vehicle, or less, or more?’”

2. The statement (on page 5) that “On the othe r hand, if consumers are myopic and consider only the first three years of fuel savings, for example, fuel economy standards can increase welfare even based solely on privat e costs and benefits” should be made clearer.

3. One of the reviewers comment on the statemen t on page 5 that “it is surprising that there is no basic research on how consumers consider fuel economy.” “This is a strange use of the term basic research, which I take to mean research on pure science. Does the author equate basic science with in terviews? I have never heard basic science used in this manner.” Two of the reviewers also provide d several detailed comments on specific paper reviews, Section 2 of the document, and editorial comments and corrections to typographical errors.



### 4. References

Rubin, J. January 2010. “Review: Vehicle Greenhouse Gas Emission (VGHG) Emissions Cost and Compliance Model.”

U.S. Environmental Protection Agency, Office of Transportation and Air Quality, Assessment and Standards Division. June 2009. “Peer Review for the RTI Report, Automobile Industry Retail Price Equivalent and Indi rect Cost Multiplie rs. EPA-420-R-09-004.

### Appendix A: Resumes of Selected Reviewers

## C AROLYN 

## F ISCHER Resources for the Future Phone: (202) 328-5012 1616 P St., NW Fax: (202) 939-3460 Washington, D.C. 20036 E- mail: fischer@rff.org
EDUCATION University of Michigan, Ann Arbor, MI. 1991-97. Ph.D. in Economics with fields in p ublic finance and natural resource economics. M.A. in Economics, 1993. University of Pennsylvania, Philadelphia, PA. 1986-90. B.A. in International Relations with honors (major Valedictorian) and Economics, minor in French, magna cum laude.
PROFESSIONA L EXPERIENCE AND AFFILIATIONS Resources For the Future, Washington, DC. 1997-present. Senior Fellow. Indefinite appointment (tenure) , 2004. Fellow, CESifo Research Network , Energy and Climate Economics Area, 2009- present. Board of Directors, Association of Environmental and Resource Economists, 2008-2010. Editorial Board, Resource and Energy Economics , 2006-2009. Leadership Committee for the Energy Collaborative Analysis Initiative, NREL, 2007- present. Fellow, Center for Advanced Study at the Norwegian Ac ademy of Science and Letters, with the group “Environmental Economics: Policy Instruments, Technology Development, and International Cooperation,” 2005. Johns Hopkins University, 1999. Instructor, Natural Resource and Environmental Economics. Council of Economic Advisors, Washington, DC. 1994-95. Staff economist. The WEFA Group, Philadelphia, PA. 1990-91. Economic analyst in World Service division.
SELECTED PUBLICATIONS
Current Work Fischer, C. and T.P. Lyon (2009 ) “ Competing Environmental Labels .” RFF Work ing Paper. Fischer, C. and C. Coleman (2009) “Imperfect Competition, Consumer Behavior, and the Provision of Fuel Efficiency in Light- Duty Vehicles” Fischer, C. and A. K. Fox (2009 ) “ Comparing Policies to Combat Emissions Leakage: Border Tax Adjustments ve rsus Rebates ” RFF DP 09 -02. (under review at JEEM ) Fischer, C. and A. K. Fox (2009 ) “Combining Rebates with Carbon Taxes: Optimal Strategies for Coping with Emissions Leakage and Tax Interactions” (under review at JPubE ) Fischer, C. and R. Morgenstern (200 8) “ Metrics for Evaluating Policy Commitments in a Fragmented World: The Challenges of Equity and Integrity” Discussion Paper 08-17, Harvard Project on International Climate Agreements. Fischer, C. and T. Sterner (200 8 ) “ Climate Policy, Prudence, and the Role of Technological Innovation.” (under review at JEEM )2

Journal Articles Fischer, C. (forthcoming ) “Does trade help or hinder the conservation of natural resources?” Review of Environmental Economics and Policy

. Fischer, C. (forthcoming ) “When Do Renewa ble Portfolio Standards Lower Electricity Prices? ” The Energy Journal 30 (4). Fischer, C. , R. Morgenstern, and E. Herrnstadt ( forthcoming ) “Understanding Bias in EIA Forecasts of Energy Demand. ” The Energy Journal

. Fischer, C. and R.G. Newell ( 2008 ) “Environmental and Technology Policies for Climate Mitigation ,” Journal of Environmental Economics and Management. 55 (2): 142-162. Fischer, C. (2008 ) “Emissions Pricing, Spillovers, and Public Investment in Environmentally Friendly Technologies,” Energy Economi cs . 30 (2): 487-502. Fischer, C. and A.K . Fox (2007) “Output- Based Allocation of Emissions Permits for Mitigating Tax and Trade Interactions, ” Land Economics . 83: 575-599. Fischer, C. , W. Harrington, and I.W.H. Parry (2007) “ Do Market Failures Justify Tightening Corporate Average Fuel Economy (CAFE) Standards?” The Energy Journal 28 (4): 1-30. Bernard, A.L., C. Fischer, and A.K. Fox (2007) “Is There a Rationale for Output- Based Rebating of Environmental Levies?” Resource & Energy Economics 29 (2): 83-101. Fischer, C. (2005) “On the Importance of the Supply Side in Demand- Side Management,” Energy Economics , 27 (1): 165-180. Margolis, M., J.F. Shogren and Carolyn Fischer (2005) “ How trade politics affect invasive species control, ” Ecological Economics , 52 (3): 305-313. Fischer, C. and R. Laxaminarayan (2005) “Sequential Development and Exploitation of an Exhaustible Resource: Do Monopoly Rights Promote Conservation?” Journal of Environmental Economics and Management . 49 (3): 500-515. Fischer, C. and R. Laxamina rayan (2004) “Monopoly Extraction of an Exhaustible Resource with Two Markets,” Canadian Journal of Economics , 37 (1): 178-188. Fischer, C. (2004) “The Complex Interactions of Markets for Endangered Species Products,” Journal of Environmental Economics and Management , 48 (2): 926-953. Fischer, C., I.W.H. Parry and W.A. Pizer (2003) “Instrument Choice for Environmental Protection when Technological Innovation is Endogenous,” Journal of Environmental Economics and Management 45(3): 523-545. Fischer, C. (2001) “Read This Paper Later: Procrastination with Time

- Consistent Preferences.” Journal of Economic Behavior and Organization , (46)3 pp. 249-269. Recent Policy Briefs : Fischer, C. (2009) “Are Consumers or Fuel Economy Policies Efficient?” in Sperling, Daniel and James S. Cannon, Eds., Reducing Climate Impacts in the Transportation Sector . Springer. Fischer, C. and R.G. Newell (2008) “What’s the Best Way to Promote Green Power? Don’t Forget the Emissions Price. ” Resources , Summer (169): 10-13. Fischer, C. and C. Egenhofer. (2008 ). “ The Critical Role of Technology for International Climate Change Policy,” in Beyond Bali: Strategic Issues for the international climate change negotiations , Brussels, Belgium: CEPS; and Washington, DC: Brookings Institution.

2

### C HRISTOPHER 

### R OLAND 

### K NITTEL University of California, Davis Department of Economics One Shields Ave Davis, CA 95616

Office: 530.302.1032

Fa x : 530.752.9382 crknittel@ucdavis.edu http://www.econ.ucdavis.edu/faculty/knittel

C URRENT A PPOINTMENTS :

2006-present, Associate Professor of Economics, University of California, Davis 2008-present, Chancellor’s Fellow, University of California, Davis

2007-present, Research Associate, National Bureau of Economic Research. Groups: Environmental Economics and Energy, I ndustrial Organization, and Productivity 2003-present, Visiting Research Fellow, University of California Energy Institute 2005-present, Faculty Affiliate, Institute of Transportation Studies, UC Davis 2006-present, Strategy and Policy Thread Leader for STEPS 2006-present, Associate Editor, The Journal of Industrial Economics 2007-present, Associate Editor, American Economic Journal – Economic Policy 2007-present, Associate Editor, The Journal of Energy Markets 2008-present, Member, Economic and Allocation Advisory Committee for AB32’s cap-and

trade program, State of California

P REVIOUS A PPOINTMENTS :

2002-2006, Assistant Professor of Economics, University of California, Davis 2004-2007, Faculty Research Fellow, National Bureau of Economic Research. Groups: Environmental Economics and Energy, Industrial Organization, and Productivity 1999-2002, Assistant Professor of Finance and Economics, School of Management, Boston University 1996-1999, Research Assistant, University of California Energy Institute 1994-1996, Teaching Assistant, University of California, Davis

E DUCATION :

Ph.D., University of California, Berkeley, 1999 (Economics) M.A., University of California, Davis, 1996 (Economics) B.A., California State University, Stanislaus, summa cum laude , 1994 (Economics and Political Science)

P UBLICATIONS :

 Knittel, Christopher R. and Jason J. Lepore. “Tacit Collusion in the Presence of Cyclical Demand and Endogenous Capacity Levels.” Forthcoming in The International Journal of Industrial Organization

.

Version:11/1/09C HRISTOPHER R. K NITTEL

 Stewart, Scott, John J. Neumann, Christopher R. Knittel, and Jeffrey Heisler. “Absence of Value: An Analysis of Investment Allocation Decisions by Institutional Plan Sponsors,” Financial Analyst Journal , 65(6), November/December 2009

.

 Knittel, Christopher R. and Victor Stango. “How Does Incompatibility Affect Prices?: Evidence from ATMs,” The Journal of Industrial Economics , LVII(3), September 2009, pp. 557-582

.

 Holland, Stephen P., Jonathan E. Hughes and Christopher R. Knittel. “Greenhouse Gas Reductions under Low Carbon Fuel Standards?,” The American Economic Journal – Economic Policy, 1(1), February 2009, pp. 106-146

.

 Borenstein, Severin, James Bushnell, Christopher R. Knittel and Catherine Wolfram. “Trading Inefficiencies in California's Electricity Markets,” The Journal of Industrial Economics

, LVI(2), June 2008, pp. 347-378.

 Feenstra, Robert and Christopher R. Knittel. “ Re-Assessing the Quality Adjustment to Computer Prices: Do U.S. Procedures Overstate the Gains?,” forthcoming Price Index Concepts and Measurement , NBER and the Chicago Press.

 Knittel, Christopher R. and Konstantinos Metaxoglou. “Diagnosing Unilateral Market Power in Electricity Reserves Market,” The Journal of Energy Markets , 1(1), Spring 2008.

 Knittel, Christopher R. and Victor Stango. “Incompatibility, Product Attributes and Consumer Welfare: Evidence from ATMs,” The BE Journal of Economic Analysis & Policy, Advances

, 8(1), January 2008. Available at: http://www.bepress.com/bejeap/vol 8/iss1/art1

.

 Hughes, Jonathan E., Christopher R. Knittel and Daniel Sperling. “Evidence of a Shift in the Short-Run Price Elasticity of Gasoline.” The Energy Journal , 29(1), January 2008.

 Heisler, Jeffrey, Christopher R. Knittel, John J. Neumann and Scott Stewart. “Why Do Institutional Plan Sponsors Hire and Fire their Investment Managers?” Best Paper Award for the 31st NBEA Conference. The Journal of Business and Economics Studies , 13(1), Spring 2007, pp. 88-116

.

 Kim, Dae-Wook and Christopher R. Knittel “Biases in Static Oligopoly Models? Evidence from the California Electricity Market,” The Journal of Industrial Economics , LIV(4), December 2006, pp. 451-470.

 Knittel, Christopher R. “The Adoption of State Electricity Regulation: The Role of Interest Groups,” The Journal of Industrial Economics , LIV(2), June 2006.

 Knittel, Christopher R. and Michael R. Roberts. “Financial Models of Deregulated Electricity Prices: An Application to the California Market,” Energy Economics , 27(5), September 2005, pp. 791-817.

 Knittel, Christopher R. “Regulatory Restructuring and Incumbent Price Dynamics: The Case of Local Telephone Markets,” Review of Economics and Statistics, 86(2), May 2004, pp. 614

- 625.

 Knittel, Christopher R. and Victor Stango. “Price Ceilings as Focal Points for Tacit Collusion: Evidence from the Credit Card Market,” The American Economic Review , 93(5), December 2003, pp. 1703-1729.

 Knittel, Christopher R. “Market Structure and the Pricing of Electricity and Natural Gas,” The Journal of Industrial Economics , LI(2), June 2003, pp. 167-191.

 Knittel, Christopher R. “Alternative Regulatory Methods and Firm Efficiency: Stochastic Frontier Evidence the US Electricity Industry,” Review of Economics and Statistics , 84(3), August 2002, pp. 530-540.C HRISTOPHER R. K NITTEL

 Borenstein, Severin, James Bushnell, and Christopher R. Knittel. “Market Power in Electricity Markets: Beyond Concentration Measures,” The Energy Journal

, 20(4), October 1999, pp. 65-88.

 Knittel, Christopher R. “Long Distance Rates: Search Costs, Switching Costs, and Mark et Power,” Review of Industrial Organization , 12(4), August 1997, pp. 519-536.

W ORKING P APERS :

 “Automobiles on Steroids: Product Attribute Trade-offs and Technological Progress in the Automobile Sector” Revisions requested from The American Economic Review

.

 Knittel, Christopher R. and Victor Stango. “Strategic Incompatibility in ATMs.” Revisions requested from The Journal of Banking and Finance

.

 “The Implied Cost of Carbon Dioxide under the Cash for Clunkers Program” Revisions requested from The BE Journal of Economic Analysis & Policy,

.

 Busse, Meghan, Christopher R. Knittel and Florian Zettelmeyer. “Pain at the Pump: How Gasoline Prices Affect Automobile Purchasing.” In submission.

 Knittel, Christopher R. and Konstantinos Metaxoglou. “Estimation of Random Coefficient Demand Models: Challenges, Difficulties and Warnings.” In submission.

 Fowlie, Meredith, Christopher R. Knittel and Catherine Wolfram . “ Sacred Cars: Optimal Regulation of Stationary and Non -stationary Pollution Sources.” In submission.

 Knittel, Christopher R. and Victor Stango. “The Productivity Benefits of IT Outsourcing.”

 Knittel, Christopher R., Douglas Miller, and Nick Sanders. “Caution, Drivers! Children Present. Traffic, Pollution and Infant Health”

 Huckfeldt, Peter, and Christopher R. Knittel. “Patents, Pharmaceutical Use and Pharmaceutical Prices”

A WA RDS , H ONORS , AND G RANTS :

 Chancellor’s Fellowship, UC Davis (one of five faculty members), 2008

 Barry D. McNutt Award for Excellence in Automotive Policy Analysis (with Jonathan Hughes and Dan Sperling), 2008

 National Science Foundation Grant (with Victor Stango), 2008-2010, $240,000

 Chevron Bio-Fuel Research Grant, 2007 -2008, $127,000

 Chevron Bio-Fuel Research Grant, 2007-2008, $77,000

 Chevron Bio-Fuel Research Grant (Co-PI), 2007-2009, $370,000

 Woods Institute for the Environment Leadership Scholar Training, 2007

 Distinguished Paper, 2006 Academy of Finance

 University of California Energy Institute Research Grant, 2005-2006, $50,000

 Best Paper Award for the 31st NBEA Conference

 ASUCD Excellence in Teaching Award, 2004

 University of California Energy Institute Research Grant, 2003

 Faculty Research Grant, UC Davis, 2002, 2003, 20004, 2005, 2006

 Institute of Governmental Affairs Junior Faculty Grant, 2002, 2003, 2004, 2005

 Junior Faculty Research Grant, Boston University, 2001

 Graduate Fellowship, University of California, Berkeley, 1997–1999

 Graduate Fellowship, University of California, Davis, 1994–1996

 Institute of Transportation Fellow, University of California, Davis, 1995–1996

 Student Commencement Speaker, California State University, Stanislaus, 1994C HRISTOPHER R. K NITTEL

R EFEREE S ERVICES :

Agricultural Economics, American Economic Review, Bulletin of Economic Research, Census Bureau, Econometrica, Economic Inquiry, The Economic Journal, Economics Letters, Energy Economics, The Energy Journal, Energy Studies Review, European Economic Review, International Journal of Industrial Organization, International Journal of Power and Energy Systems, Journal of Banking and Finance, The Journal of Business, Journal of Business and Economic Statistics, Journal of Economic Behavior and Organization, Journal of Economic Education, Journal of Economics and Management Strategy, Journal of Futures Markets, Journal of Industrial Economics, Journal Institutional and Theoretical Economics, Journal of Law and Economics, Politics and Economics, Quarterly Journal of Economics, Rand Journal of Economics, Resource and Energy Economics, Review of Economic Studies, Review of Economics and Statistics, Review of Industrial Organization, Review of Net work Economics, Southern Economic Journal, Socio-Economic Planning Sciences, Utilities Policy, University of California Energy Institute Grant Program, NSF Grant Program

R ECENT I NVITED P RESENTATIONS :

 Energy Institute @ Haas, Policy Conference, Sacramento, October 2009

 Institute of Transportation Studies, UC Davis, October 2009

 TREE Seminar, Raleigh/Durham/Chapel Hill, North Carolina, October 2009

 UC Berkeley, ARE, February 2009

 NBER Winter IO Meeting, February 2009

 Iowa State, Economics, January 2009

 NBER Summer EEE Meeting, July 2009

 UC Berkeley IO/Innovation Seminar, November 2008

 UC Berkeley IO/Innovation Seminar, October 2008

 Department of Justice, March 2008

 University Retirement Community, February 2008

 New American Foundation, February 2008

 Tainjin Chinese Delegation at UC Davis

 UCEI Policy Conference, December 2007

 University of California Energy Institute, July 2007

 Institute of Transportation Studies, UC Davis, October 2007

 NBER EEE, Summer Meeting, July 2007

 NBER Winter IO Meetings, January 2008

 UC Berkeley, Department of Economics, November 2007

 University of Alberta and Calgary University Industrial Organization Conference, October 2007

 Washington University, Olin School of Business, November 2007

R EGULATORY F ILINGS :

 Arons, S.M., A.R. Brandt, M.A. Delucchi, A. Eggert, A.E. Farrell, B.K. Haya, J. Hughes, B.M. Jenkins, A.D. Jones, D.M. Kammen, S.R. Kaffka, C.R. Knittel, D.M. Lemoine, E.W. Martin, M.W. Melaina, J.M. Ogden, R.J. Plevin, D. Sperling, B.T. Turner, R.B. Williams, C. Yang, 2007. “A Low-Carbon Fuel Standard for California, Part 1: Technical Analysis.” Available Online: http://www.lcfs.ucdavis.edu

.

 Brandt, A.R., A.E. Farrell, B.K. Haya, J. Hughes, B.M. Jenkins, A.D. Jones, D.M. Kammen, C.R. Knittel, M.W. Melaina , M. O’Hare, R.J. Plevin, D. Sperling, 2007. “A Low-Carbon FuelC HRISTOPHER R. K NITTEL

Standard for California, Part 2: Policy Analysis.” Available Online: http://www.lcfs.ucdavis.edu

.

 Peer Review Comments on AB 1493, California Environmental Protection Agency Air Resource Board, September 2004.

 “Comments on the Use of Computer Models for Merger Analysis in the Electricity Industry,” (Joint with Severin Borenstein and James Bushnell), Federal Energy Regulatory Commission. Docket No. PL98-6-000, June 1998.

 “A Cournot-Nash Equilibrium Analysis of the New Jersey Electricity Market,” December 1997. (Joint with Severin Borenstein and James Bushnell). Filed with the New Jersey Public Utility Commission as testimony on the potential for market power in a deregulated Pennsylvania-Jersey-Maryland Power Pool.

C ONSULTING :

Customers First! Coalition, Energy Information Agency, Korean Electric Power Company, California Air Resource Board, City of West Sacramento

P H .D. C OMMITTEES (F IRST J OB ):

UC Davis: Anson Soderbery (on-going) Nick Sanders (chair, on-going) Chai-Wen Chen (chair, on -going) Jonathan Hughes (chair, University of Colorado, Boulder) Adib Bagh (University of Kentucky, Math and Economics) Seungjoon Lee (Korean Insurance Research Institute) Jason Lepore (chair, Cal Poly) Wei-Min Hu (Peking University) Byeongil Ahn (Gyeongsang University) Konstantinos Metaxoglou (chair, Bates and White LLC) Lan Li (University of Melbourne) Neil Norman (Cornerstone Research) Dae-Wook Kim (chair, Korean Institute for Industrial Economics and Trade) Boston University: Gustavo Genoni (2002, Finance, IAE, School of Business, Universidad Austral) John Neumann (2003, Finance, St. John’s University)

T EACHING :

• UC Davis

o Graduate Empirical Industrial Organization (6 times)

 Ratings: Mean 4.9 (out of 5)

o Transportation Economics ( 4 times)

 Ratings: Mean 4.7

o Intermediate Microeconomics (1 time),

 Ratings: Mean 4.8

o Undergraduate Industrial Organization (9 times)

 Ratings: Mean 4.8

• Boston University

o Modeling Business Decision Making,

 Spring 2000, Spring 2001 and Spring 2002C HRISTOPHER R. K NITTEL

 Ratings: 4.53 (out of 5), 4.77, 4.70

o Modeling Business Decision Making (honors),

 Spring 2001 and Spring 2002

 Ratings: 4.88, 4.70

U NIVERSITY S ERVICE :
UC Davis: 2007-2008, Co-writer (with Jean Vandergehst) of a proposal for a Graduate Program in "Energy Science and Technology" and "Energy Policy and Management" 2006-Present, Member, Energy Institute Steering Committee 2008, Founding Faculty Member, UC Davis Energy Institute 2005-2006, Hiring Committee and Interviewing Committee 2004-2005, Hiring Committee and Interviewing Committee 2002-2003, Hiring Committee and Interviewing Committee 2002-2007, Graduate Advisor Oral committees: Dae -Wook Kim, Konstantinos Metaxoglou, Neil Norman (chair), Seungjoon Lee, Wei-Min Hu, Lan Li (ARE), Sunhwa Lee, Byeongil Ahn (ARE), Michele Amaral, David Ong, Adib Bagh, Jason Lepore, Bei Li, Chenguang Li (ARE), Tina Saitone (ARE), Carlo Russo (ARE), Sandhya Patlolla (ARE), Jon Hughes (TTP), Peter Huckfeldt, Kyungwon Rho, Nick Sanders, Chia-Wen Chen, Joeri de Witt (ARE), In-Sung Lee (TTP), Anson Soderbery, Nils Johnson (TTP), David McCollum (TTP)

Boston University: 2000-2001, Finance Hiring Committee and Interviewing Committee 1999-2000, Finance Hiring Committee

R ECENT M EDIA C ITATIONS :

Print: Alameda Times-Star, Arizona Daily Star, Argus, ATMmarketplace.com, Austin-American Statesman, Boston Globe, Buffalo News, California Aggie, Contra Costa Times, PE.com, bankrate.com

, marketwatch.com , Crain’s Business Report (New York), Credit Card Magazine, Kiosk Marketplace News, LA Observed, LA Times, International Herald Tribune, Northwestern Herald, Oakland Tribune, Oregonian, Philadelphia Inquirer, Providence Journal, New York Times, Sacramento Bee, St. Petersburg Times, Salon.com, San Diego Union Tribune, Salt Lake Tribune, San Diego Union Tribune, SF Chronicle, San Mateo County Times, Santa Rosa Press Democrat, Sarasota Herald-Tribune, Scripps News (DC), Tuscaloosa News Sun Herald, Quad City News (Iowa), Winston-Salem Journal, Worcester Telegram Radio: KQED’s “Forum”, KXJZ, KFBK, KUOP, KCBS, KNX, WHYY with Marty MossCoane, WPR with Kathleen Dunn, Bloomberg Radio, Lambasted by Rush Limbaugh Television: KCRA-3, CBS-13 Sacramento, NBC Nightly News, ABC World News, CBS Evening News, ABC Good Morning America

R EFERENCES :

Severin Borenstein E.T. Grether Professor of Business Administration and Public Policy Haas School of Business University of California at Berkeley borenste@haas.berkeley.eduC HRISTOPHER R. K NITTEL

Michael Greenstone 3M Professor of Environmental Economics Department of Economics Massachusetts Institute of Technology mgreenst@mit.edu

Frank Wolak Professor of Economics Stanford University wolak@zia.stanford.edu

Catherine Wolfram Associate Professor Haas School of Business University of California at Berkeley wolfram@haas.berkeley.eduRésumé Dr. Walter McManus Research Scientist and Director Economics, Energy, and Environment Research Group University of Michigan Tran sportation Research Institute 2901 Baxter Rd. Ann Arbor, MI (248) 821-0493 watsmcm@umich.edu

Biography Dr. Walter McManus is a Research Scientist at the University of Michigan Transportation Research Institute (UMTRI) and Director of the Economic s, Energy, and Environment Research Group. Dr. McManus has been a member of the UMTRI faculty si nce March 2005. Immediatel y prior to that, he was Executive Director of Forecasting an d Analytics at the global marketin g information company, J.D. Power and Associates. His business experience also include s nine years with General Motors in forecasting, marketing analysis and strategy, and new-product de velopment. (He also spen t a year as a production supervisor in a GM manufacturing plant.)

Dr. McManus graduated from Louisiana State Univers ity (BA 1977) and earned a doctorate in economics from the University of California, Los Angeles (PhD 1983). Dr. McManus pursues a research program that is focused on issues arising from the interaction of transportation, society, and the environment. The research program generates knowledge through excelle nt, creative research on the social, economic, and environmental dynamics that are producing change in the automotive transportation energy sphere; with the goal of developing and delivering useful applications of findings to assist policy makers, industry, and stakeholders in anticipatin g future societal needs.

Research Interests Transportation economics, energy, and environment; the automotive industry; adoption and diffusion of clean transportation technologies

Tools Economic analysis (market demand and supply models, strategic behavior of firms, economic history), econometrics, forecasting and simula tion, finance, public speaking

Education PhD, Economics, University of California, Los Angeles, 1983 BA, Economics, Louisiana State University, 1977

Awards 2008 UMTRI Research Excellen ce Award for the article in Business Economics 2007 NABE Abramson Award for the best article published in Business Economics 2007 GM Chairman’s Honors for innovations enhancing performance in new-product development 1991 & 98 Sidney Stern Fellow; University of California, Los Angeles; 1979 – 82

Affiliations Automotive Industry Expert Panel, U.S. Gove rnment Accountability Office, 2009 – present Ceres Stakeholder Committee on Sustainability, Ford Motor Company, 2009 – present Fellow, Michigan Memorial Phoenix Energy Research Institute, 2007 – present Executive Committee, Mi chigan Center for Advancing Safe Transportation throughout the Lifespan, 2007

– present Transportation Energy Committee, Transportation Research Board Transportation Working Group, Energy Futures Coalition, 2003 – 04 American Economic Association National Association for Business Economics Society of Automotive EngineersWalter McManus

Professional History Research Scientist and Director, Economics, Energy, and Environment Research Group, University of Michigan Transportation Research Institute, Mar 2005 - Present

Visiting Scholar and Research Engineer, Transporta tion Sustainability Research Center, Institute of Transportation Studies, University of California, Berkeley, Mar 2009 – Oct 2009

Executive Director of Forecasting and Analytics, J.D. Power and As sociates, Oct 1999 – Jan 2005

Director of Marketing, Textron Automotive Company, Dec 1998 – Sept 1999

Leader, Industry Analysis Group, General Motors Corporation, July 1996 – Nov 1998

Manager, North American Market Analysis, General Motors Corporation, Jan 1994 – June 1996

Economist, Delco Remy Division, General Motors Corporation, Anderson, IN, Aug 1991 – Dec 1993 (Memo: included development assignment as Manufacturing Supervisor, Jan 1993 – Dec 1993)

Economist, General Motors Corporation, Detroit, MI, June 1989 – Aug 1991

Associate Professor of Economics and Fellow, Center for the Study of Business and Government, Baruch College, New York, NY, July 1988– May 1989

Assistant Professor of Economics, University of Florida, Gainesville, FL, July 1983 – June 1988

Testimony and Briefings U.S. EPA and NHTSA Public Hearing, Proposed Rulemaking to Establish Light-Duty Vehicle Greenhouse Gas Emission Standards and Corporate Average Fuel Economy Standards, October 21, 2009

Investor Briefing, Citigroup Investment Research, CAFE Panel Conference Call & Briefing, April 2009.

Testimony, Committee on Assessment of Technologies for Improving Light-Duty Vehicle Fuel Economy, National Research Council, March 16, 2009

Testimony, US EPA, Hearing on California Greenhouse Gas Waiver, March 3, 2009

Testimony, Environmental Regulation Commission Hearing, Greenhouse Gas Emissions Reduction-Florida Clean Car Emission Rule, Florida Department of Environmental Protection, October 29, 2008

US Congressional Briefing, Environmental and Energy Study Institute & Investor Network on Climate Risk, December 4, 2007

Investor Briefing, Citigroup Investment Research, CAFE and the U.S. Auto Industry: A Growing Auto Investor Issue, 2012-2020, October 31, 2007

Public Briefing, National Commission on Energy Policy and the International Council on Clean Transportation, Fuel Economy: Technology Trends and Policy Options, Washington, DC. October 1, 2007.

Congressional Testimony, U.S. Senate Finance Subcommittee on Energy, “Advanced Technology Vehicles: The Road Ahead”, May 1, 2007

Congressional Testimony, U.S. Senate Energy and Natural Resources Committee, “the Consumer Market for Fuel Economy”, January 30, 2007

Publications

2Walter McManus

Rogozhin, A., Gallaher, M., Helfand, G., and McManus, W. (2010 forthcoming), Using indirect cost multipliers to estimate the total cost of adding new technology in the automobile industry, International Journal of Production Economics.

McManus, W., Senter, R., Curtin, R., and Garver, S. (2009), The demographic threat to Detroit’s automakers, Targeting, Measurement and Analysis for Marketing 17:81-92

Senter, R. and McManus, W. (2009), General Motors in an age of corporate restru cturing, in the second automobile revolution: the automobile firms' trajectories at the beginning of the 21st century (Chapter 9), Edited by M. Freyssenet, New York: Palgrave Macmillan

McManus, W. (2007), The link between gasoline prices and vehicle sales: economic theory trumps conventional Detroit wisdom. Business Economics 1.42:54-60

McManus, W. and Griffor, E. (2006), Toward a science of driving: Safety in rules-based versus adaptive self-regulating traffic systems, SAE Convergen ce, 2006-21-0064

McManus, W. (1985), Estimates of the deterrent eff ect of capital punishment: the importance of the researcher's prior beliefs, Journa l of Political Economy 93:417-25

McManus, W. (1985), Labor market assimilation of immigrants: the importance of language skills, Contemporary Economic Policy 3:77-89

McManus, W. (1985), Labor market costs of language disparity: an interpretation of Hispanic earnings differences, American Ec onomic Review 75:818-27

Theil, H., Rosalsky, M., and McManus, W. (1985), Lp-norm estimation of non-linear systems Economics Letters 17(1-2):123-125

McManus, W. and Rosalsky, M. (1985), Are all asymptotic standard errors awful? Economics Letters 17(3):243-245

McManus, W., Gould, W., and Welch, F. (1983), Earnings of Hispanic men: the role of English language proficiency, Journal of Labor Economics 1:101-30

Technical Reports and Working Papers McManus, W. and Senter, R., Market Models for Predicting PHEV Adoption and Diffusion, UMTRI-2009

- 37, August 2009.

McManus, W. and Kleinbaum, R., Fixing Detroit, How Far, How Fast, How Fuel-Efficient, UMTRI-2009

- 26, June 2009

Senter, R. and McManus, W., Reshaping the Big Three, GERPISA, June 2009

Rogozhin, A., Gallaher, M., Helfand, G., and McManus, W., Automobile Industry Retail Price Equivalent and Indirect Cost Multipliers, EPA-420-R-09-003, Feb 2009

McManus, W., The Impact of Attribute-Based Corporate Average Fuel Economy (CAFE) Standards: Preliminary Findings, Automotive Analysis Division, University of Michigan Transportation Research Institute (UMTRI), July 2007

McManus, W., Economic Analysis of Feebates to Reduce Greenhouse Gas Emissions from Light Vehicles for California, Automotive Analysis Division, Univers ity of Michigan Transpor tation Research Institute (UMTRI), May 2007

3Walter McManus

McManus, W., Can Proactive Fuel Economy Strategies Help Automakers Mitigate Fuel-Price Risks? Automotive Analysis Division, University of Mich igan Transportation Resear ch Institute (UMTRI), September 2006

McManus, W., Baum, A., Hwang, R., Luria, D., and Baur a, G., In The Tank – How Oil Prices Threaten Automakers’ Profits and Jobs, Office for the Study of Automotive Transportation, July 2005

McManus, W. and Berman, B., The 2005 OSAT – HybridCars.com Survey of Owners and Shoppers, Office for the Study of Automotive Transportation (OSAT), University of Michigan Transportation Research Institute (UMTRI), 2005.

McManus, W., The Effects of Higher Gasoline Prices on U.S. Light Vehicle Sales, Prices, and Variable Profit by Segment and Manufacturer Group, 2001 and 2004. Office for the Study of Automotive Transportation (OSAT), University of Michigan Transportation Research Institute (UMTRI), June 2005.

Greene, D., Duleep, K., and McManus, W., Future Poten tial of Hybrid and Diesel Powertrains in the US Light-Duty Vehicle Market, Report to Department of Energy, July 2004.

McManus, W., Consumer Acceptance of Alternative Powe rtrains, OE Industry Revi ew. Troy, MI: Original Equipment Suppliers Association, 2004.

McManus, W., “Diesel vs. Hybrid-Electric Powertra ins: Assessing Dependability,” Power Report (July 2004)

McManus, W., “Interest in Diesel Grows—Quietly,” Power Report (June 2004)

McManus, W., Consumer Acceptance of Alternative Powertrains Study. Westlake Village, CA: J.D. Power and Associates, 2004.

Malesh, T. and McManus, W., Clean Diesel Market Acceptance Study. Westlake Village, CA: J.D. Power and Associates, 2003.

McManus, W., Analysis of Tax Credits to Stimulate Consumer Demand for Advanced-Technology FuelEfficient Vehicles: Final Report to Energy Future Coalition Transportation Working Group. Westlake Village, CA: J.D. Power and Associates, 2003.

McManus, W., Generation Y Automotive Market Asse ssment. Westlake Village, CA: J.D. Power and Associates, 2002.

McManus, W., Interaction Between New and Used Vehi cle Sales in the U.S. Market. Westlake Village, CA: J.D. Power and Associates, 2002.

McManus, W., Telematics Forecast. Westlake V illage, CA: J.D. Power and Associates, 2002.

McManus, W., Satellite Radio Forecast. Westlake Village, CA: J.D. Power and Associates, 2002.

McManus, W. and Bussmann, W., Isuzu in the U.S., Westlake Village, CA: J.D. Power and Associates,

McManus, W., Adaptive Cruise Contro l Forecast, Westlake Village, CA: J.D. Power and Associates, 2001

4 2001

### Appendix B: Charge QuestionsTO: Carolyn Fischer Walter McManus Christopher Knittel

FROM: Paramita Sinha

CC: Michael Gallaher

DATE: December 31, 2009

SUBJECT: Charge Questions for Peer Review of EPA’s Study of Vehicle Choice Models

The US EPA’s Office of Transportation and Air Qu ality is currently analyzing a set of existing consumer vehicle choice models to see whether there is a robust estimate of the value of additional fuel economy to consumers. EPA is seek ing a peer review of its comparative study of consumer vehicle choice models and what each model may predict for the value of improving vehicle fuel economy at the time of vehicle purchase. EPA has provided direction and charge questions fo r this review and these are included below. A teleconference call will also be arranged so that EPA can provide technical and/or background information on the analysis. Any future questio ns you may have can be directed back through RTI for resolution with EPA.

The review will involve a written report that includes the response to the charge questions and any additional comments you may have, e.g., ma rgin notes on review materials. Comments should be provided in an enclosure to a cover letter that clearly states the reviewer’s name, the name and address of their organi zation if applicable, which model review documents/media were received by the reviewer and which were actuall y reviewed and a statement of any real or perceived conflict(s) of interest.



### ELEMENTS TO BE ADDRESSED IN THE CHARGE TO THE REVIEWERS OF EPA’S ANALYSIS OF THE VALUE OF ADDITIONAL FUEL ECONOMY TO CONSUMERS EPA’s report on using vehicle choice models to estimate the impacts of fuel economy regulations will inform its analyses of the effects of regulatory programs that affect vehicle fuel economy. This report details an analysis of the value of additional fuel economy to consumers, estimated

RTI International is a trade name of Research Triangle InstituteCarolyn Fischer Walter McManus Christopher Knittel Page 2 December 31, 2009

from consumer vehicle choice models. No independe nt data analysis will be required for this review. Specifically, EPA is seeking the reviewers’ expert opinions on th e data, concepts, and methodologies upon which the analysis relies, whether or not the analysis was conducted correctly, and whether the analysis draws appropria te conclusions. Toward this end, we ask that each subject matter expert review and comment on the following items:

1. overall approach and methodology of the study;

2. appropriateness of the data sets and any other inputs;

3. data analysis conducted for the study;

4. appropriateness of the conclusions drawn;

5. recommendations for alternat e data and/or analyses; and

6. overall clarity of the presentation. In making their comments, the reviewers should distinguish between recommendations for clearly defined improvements that can be readily made based on data or literature reasonably available to EPA, and improvements that are mo re exploratory or dependent on information not readily available to EPA. Any comment should be sufficiently cl ear and detailed to allow a thorough understanding by EPA or other parties fa miliar with the model. EPA requests that the reviewers not release the peer review materials or their comm ents to anyone else until the Agency makes its report and supporting documentation public. If a reviewer has questions about what is required in order to complete this review or need additional background material, please direct the re viewer to contact (RTI project manager/PI). If a reviewer has any questions about the EPA peer review process it self, please have the reviewer contact Ms. Ruth Schenk in EPA’s Quality O ffice, National Vehicle and Fuel Emissions Laboratory by phone (734-214-401 7) or through e-mail ( schenk.ruth@epa.gov

.

### Appendix C: Cover LettersTo: Gloria Helfand US EPA, Assessment and Standards Division (OTAQ) 2000 Traverwood Drive Ann Arbor, Michigan 48105

From: Dr. Carolyn Fischer 3215 Pauline Dr. Chevy Chase, MD 20815

January 27, 2010

Cover Letter to Accompany “Review of Green e ‘How Consumers Value Fuel Economy’”

Greetings:

The documents that I received from EPA (or RT I International) were a memo containing the charge questions and the draft report by Greene (2009). I also furnished versions of some unpublished papers relevant to the report, in cluding Alcott and Wozny (2009); Busse, Knittel, and Zettelmeyer (2009); and Sallee, West, and Fan (2009).
I reviewed all of the documents th at I received in developing my expert opinion as contained in the “Review of Greene ‘How Consumers Valu e Fuel Economy’,” submitted on January 25. I declare that there are no real or perceived conf licts of interest concer ning my involvement in this review for the EPA.

Best regards,

Carolyn Fischer

C-1To: Gloria Helfand US EPA, Assessment and Standards Division (OTAQ) 2000 Traverwood Drive Ann Arbor, Michigan 48105

From: Christopher R. Knittel Department of Economics University of California, Davis Davis, CA 95616

January 27, 2010

Cover Letter to Accompany Review How Cons umers Value Fuel Economy: A Literature Review, by David Greene.

Greetings:

The documents that I received from EPA (or RT I International) were a memo containing the charge questions, the draft report by Greene (200 9), and two unpublished pape rs that are covered in the draft report. The unpublished papers are Alcott and Wozny (2009) and Sallee, West, and Fan (2009).
I reviewed all of the documents th at I received in developing my expert opinion as contained in the enclosed Review of How Consumers Value Fuel Economy: A Literature Review, by David Greene. I declare that there are no real or perceived conf licts of interest concer ning my involvement in this review for the EPA.

Sincerely,

Christopher R. Knittel

C-2To: Gloria Helfand US EPA, Assessment and Standards Division (OTAQ) 2000 Traverwood Drive Ann Arbor, Michigan 48105

From: Walter McManus University of Michigan Tran sportation Research Institute 2901 Baxter Rd. Ann Arbor, MI 48109-2150

January 25, 2010

Cover Letter to Accompany Review of Greene, D.L. (2009) How Consumers Value Fuel Economy: A Literature Review

Greetings:

The documents that I received from EPA (or RT I International) were a memo containing the charge questions, the draft report by Greene ( 2009), and three unpublished papers that are covered in the draft report. The unpublished pape rs are Alcott and Wozny (2009); Busse, Knittel, and Zettelmeyer (2009); and Sallee, West, and Fan (2009).
I reviewed all of the documents th at I received in developing my expert opinion as contained in the enclosed Review of Greene, D.L. (2009) Ho w Consumers Value Fuel Economy: A Literature Review. I declare that there are no real or perceived conf licts of interest concer ning my involvement in this review for the EPA.

Best regards,

Walter McManus

C-3

### Appendix D: Reviews

## Review of Greene “How Consumers Value Fuel Economy” by Carolyn Fischer

David Greene is contributing an in-depth revi ew of the recent literature on the demand for vehicle fuel economy that will be extremely valuable to res earchers and policymakers alike. Although ultimately he is unable answer th e key question—how do consumers value fuel economy?—he does provide considerab le insight into how researcher s have attempted to answer this question and why we see so mu ch variation in the results.

This review is structured to provide feedback and suggestions aimed at improving this work and ultimately enhancing its impact.



### Presentation Overall, the writing is excellent. Some modest changes could help the reader.

The reviewed articles are organi zed logically by class of data a nd methods. At the beginning of each section, it would be helpful to review t hose methods in general fashion, including the advantages and drawbacks, as well as key factors or assumptions th at can affect the results. Also, it might be easier to begin with the seminal pa pers in each category, so as to understand the evolution and improvements made subsequently.

The status of the papers should also be recognized, since many of the important new studies are still unpublished working papers and subject to change.

Since few econometric studies have explicitly es timated the value of fuel economy, a significant contribution of the paper is to translate a wide va riety of results into more consistent indicators. Yet, they could still be more c onsistent. In Table 10, can all of the results be converted into the same WTP metric, preferably using the same assumptions about vehicle lifespan, VMT, discounting, etc.?

Also, the author’s baseline assumptions need to be stated clearly early in the paper, so careful attention can be given throughout to assumptions that deviate from that baseline. Indeed, the statement made in the Allcott and Wozny analysis (“Calculating the disco unted present value of fuel costs requires a number of assumptions...”) s hould be made earlier in a general context, so that the variety and range of assump tions can be understood and explored.


### Additional Analysis The paper reviews many approaches, and the au thor should take advantage of the summary section to indicate whether some approaches are likely to be better than others.

That section does point out some fa ctors that may explain such differe nt results, but this analysis could be improved. First, the discussion interweaves reasons that coul d explain why we can plausibly believe any of a range of results (e.g., heterogeneous decision rules, uncertainty) with

D-1reasons for why different studies get different results. It would be helpful to separate these discussions, reminding readers of the former, and then focusing on the latter, which is the most important contribution. This kind of analysis shou ld help indicate best practices and directions for future research. Can we suggest some experi ments (e.g., new techniques on old data sets, or old techniques on new data sets) that can help tease out what di fferences arise from alternative econometric approaches? If most studies have focused on other aspects of vehicle demand, are there better specifications for looking dire ctly at the valuation of fuel economy?

It would be useful to summari ze key differences in approaches and data and analyze their consequences. Some that we re gleaned along the way:

 levels of aggregation,

 time horizons (how useful is info from the 1970s in estimating current demand?),

 incorporation of the supply side,

 details of other attributes and variable definitions,

 allowing for separate responses to MPG and fuel costs (this was raised as lacking in the discussion of Gramlich, but it wasn’t appare nt what other studies had done this),

 assumptions of vehicle lifetime, VMT, discount rates, etc.

 econometric approach Some of these summary indicators (model type, data, and time) ar e given in Table 10, but some additional analysis would be useful. Do we obser ve any trends across classes or time? Within a class of models, what drives the differences?

The paper raises the issue of cons umer heterogeneity in several places, but the importance of this fact should be pushed further. Fischer (2009) points out that, facing consumers with heterogeneous preferences over fuel economy, ma nufacturers with market power have distorted incentives for providing fuel economy. More ge nerally, failure to capture such consumer heterogeneity can lead to significant errors in pr edicting the distribution of effort in complying with regulation, as well as the calcul ation and distribution of the benefits. 2 Portions of this review highlight certain studies that captured differences in tastes for fuel economy (BLP, Goldberg, Brownstone et al.), wh ile most studies ignored such heterogeneity. This seems like an important area for additional analysis, both to expl ain differences and to suggest future research directions.


### Additional Empirical Literature
I am aware of a few other studies that likely deserve attention as well.

Sallee and West (2009 working pape r) “The Effect of Gasoline Prices on the Demand for Fuel Economy in Used Vehicles: Empirica l Evidence and Policy Implications” Abstract: Fossil fuel consumption and greenhouse gas emissions from the personal transportation sector pose serious challenges to today’s policy-makers. If consumers acknowledge the full value of fuel economy, a tax on gasoline could be as efficient as a tax on greenhouse gas emissions, since the amount of carb on released by a gallon of gasoline is independent of the manner in which it is combusted. If, however, consumers do not sufficiently value fuel economy when

2 Fischer, Carolyn (2009) “Imperfect Comp etition, Consumer Behavior, and the Provi sion of. Fuel Efficiency in Vehicles.” Working Paper, Washington, DC : Resources for the Future.

D-2making the decision about what car to buy, an additional complementary policy, such as a fuel economy standard or a feebate, can be welfar e improving. We use microdata on used vehicle prices and a unique identification strategy based on micro-level vari ation in vehicle odometers to test whether used car prices change by the amount predicted by a fully rational asset pricing model. Our baseline results indicate that used car prices adjust by about 80% of the amount predicted by theory, and sensitiv ity analysis suggests that for a reasonable discount rate, they adjust by the full amount. These results contrast with recent literature, which finds adjustment closer to 25%, and suggest a limited role for complementary policy tools.

Klier and Linn (2010 working paper) “The Pri ce of Gasoline and New Vehicle Fuel Economy: Evidence from Monthly Sales Data” This paper uses a unique data set of monthly new vehicle sales by detailed model from 1978- 2007, and implements a new identification strategy to estimate the effect of the price of gasoline on individual vehicle model sales. We c ontrol for unobserved vehicle and consumer characteristics by using within model-year change s in the price of gasoline and sales. We find a significant sales response, sugge sting that the gasoline price increase from 2002-2007 explains nearly half of the decline in market share of U. S. manufacturers. On the other hand, an increase in the gasoline tax would only mode stly raise average fuel economy. (Their estimate implies that a one dollar increase in the price of gasoline raises average fuel economy by 0.5-1 MPG.)
Dreyfus, Mark K. and W. Kip Viscusi (1995) . “Rates of Time Preference and Consumer Valuations of Automobile Safety and Fuel E fficiency.” Journal of Law and Economics 38: 79

- 98. This seems like an earlier, influential study, of the same era as BLP, so worth some comparison, although fuel economy demand was a s econdary target of interest. Description from Howarth (2004): “Dreyfus and Viscusi (1995) undertook a hedonic price analysis of the U.S. automobile market to assess consumers’ willingness to pay for improved safety and energy efficiency. On the assumption that consumers use a common discount rate in evaluating both safety and fuel economy, the st udy calculates an implic it discount rate that ranges from 11 to 17 percent in alternative speci fications. More tellingly, Dreyfus and Viscusi conclude that only 35 percent of the present- value cost savings provided by improved energy efficiency is capitalized in the purchase price of vehicles.” (derived from coefficients from operating cost and that interacted with weight)

Hughes, Jonathan E., Christopher R. Knittel and Daniel Sperling (2008). “Evidence of a Shift in the Short-Run Price Elasticity of Gasoline Demand.” Energy Journal

. West, S. (2008). “The Effect of Gasoline Prices on the Demand for Sport Utility Vehicles.” Working Paper. Macalester College. (mentioned in Helfand and Wolverton)

D-3

### Other Points
2.0 in the discussion of Turrentine and Kurani, recent research on “The MPG Illusion” may be relevant to mention, suppor ting the difficulty of consumer s in calculating fuel cost savings. Larrick, R. P., & Soll, J. B. (2008). The MPG illusion. Science, 320, 1593-1594. http://faculty.fuqua.duke.edu/~lar rick/bio/Reshighlights.htm

2.1 The author talks about the global vehicle market ; it seems relevant to give the statistics for the U.S. market.

2.2 The review of the literature on the dema nd for energy efficiency should include Gillinham et al., who “review economic concepts underlying consumer decision making in energy efficiency and conservation and examine related empirical literature. In particular, we provide an economic perspectiv e on the range of market barriers, market failures, and behavioral failure s that have been cited in the energy efficiency context.” Gillingham, K.T., R.G. Newell and K.L. Pa lmer (2009). “Energy Efficiency Economics and Policy.” RFF Discussion Paper 09-13, April 2009.

The statement “With the exception of externalitie s, there is little quantitative evidence of the impact of these failures on consumers’ choices of energy using durable goods” seems hard to reconcile with the preceding discus sion. Is there any better (peer-reviewed) support than ACEEE (2007)?

This section also offers the opportunity to introduce other studie s outside the economics literature—are there any documented industry studies on their approach to consumer payback expectations?

Section 3

BLP (1995) is a seminal paper, and should probably be presented first. Is the same critical eye being given to them with respect to omitted vari ables. They used HP/weight to represent power, but what if weight is valued separately, such as for safety concerns in that era?

Dasgupta et al. (2007): this descri ption seems too curt. I had a ha rd time following the structure of the model and the conversion of the results. (Also later in the discussion of McManus, where the coefficient units are interpre ted as discounted lifetime miles).

Bento et al. (2005): I believe the parameter estimates are provided in the Appendix. Are they in a form that can be useful for comparison?

Feng et al. (2005): given the impor tant question raised of the units, it seems worth asking the authors directly.

Brownstone et al. (1996): did any of the identification for WTP for fuel economy come from the demand for alternative fuel opti ons? It wasn’t clear in the di scussion what was done with the

D-4information about alternatives, and whether that is reliable, given the lack of availability of these technologies.

Cambridge Econometrics: if they included both fuel costs and fuel consumption rates, was there some other heterogeneity to distinguish between the two?

Espey and Nair (2005) is referred to before it is discussed; perh aps the order should be reversed. Also, since the gas guzzler tax is mentione d, one should perhaps point out that they mischaracterized the policy in such a way as to affect their consumer price calculations (it is actually paid by producers, not co nsumers), although this is unlikel y to affect their results. The lack of controlling for ma nufacturer may, however. In discussing the differences with the Rosen met hod, the implications for how their results might be biased were unclear.

Bhat and Sen (2006): Table 6 is difficult to interpret.

Busse et al.: p. 32 “These results do no necessa rily imply that new car buyers undervalue fuel economy, since the change in price also depends on the elasticities of supply and demand.” It seems they also depend on the formulation of price expectations.



### Minutiae

p. 8 “Two recent analysis have quantifie d the [potential] impacts of uncertainty...”
p. 10 2 nd para: market imperfect[ion] sales[-]mix (might be preferred)
p. 12 end of the Gramlich discussion is a bit confusing; it was not clear what his model predicted for fuel economy in comparison to the EPA numbers. May just need to be clarified which numbers are being discussed.
p. 12 [reverse order so that citation always begins the paragraph] BLP (1995), in a seminal
paper,... “consumer I” should be “consumer i ” p. 16 last full sentence (“Different influe nces... in econometric analyses of VMT, for example”) could use some citations.
p. 23 top para: “But this is not stated in the report[;] indeed,...
p. 25 figure says “Qin and Rubin” instead of “Fan and Rubin” References please check worki ng papers to update citations p. 36 2 nd para: remove the “,” after “Allcott and Wozny” e.g., Fischer et al. (2007) is Energy Journal 28: 1-29.

D-5Review of: “How Consumers Value Fuel Economy: A Literature Review” by David L. Greene Reviewed by Christopher R. Knittel

January 22, 2010

Dear Sir/Madam:

This report summarizes the literature regardi ng the value that consumers place on fuel economy at the time of purchasing a vehicl e. Understanding this is important for a variety of public policy issues. How consumers trade-off pa ying more for fuel economy with future fuel savings defines

their discount rate. Therefor e, statements such as “consumers undervalue fuel economy” necessarily imply that the consum ers’ discount rate is below soci ety’s discount rate. If consumers do not value fuel economy as much as society-at -large, then gasoline will be over-consumed and policies may improve social welfare.

Equally important, though not analyzed in th is report (it is disc ussed however), is why consumers undervalue gasoline, relative society (if they do indeed undervalue fuel economy). This has important implications for which policies are mo st effective at aligni ng discount rates. For example, do consumers undervalue fuel econo my because capital markets are imperfect? Subsidized loans would likely be the most effe ctive policy. Do they undervalue fuel economy because of a lack of cognitive ability? Education policies and/or information campaigns are likely to be most effective. Papers dealing with these issues are largely lacking, unfortunately.

Bottom line: This is an excellent review. This re view will be an asset to policy makers. I agree

with the conclusion that the lite rature remains mixed as to wh ether consumers full value fuel economy at reasonable discount rate s. I provide some comments th at may improve the review.

Is the goal to summarize, or analyze papers?:

It strikes me that there are two ways to conduct a review such as this. One is to report the results of papers with little, or no, discussion of the quality each paper. The other is to both review and critique each paper. I found a lack of uniformity in this regard. For many of the papers, the latter

D-6strategy is taken. The report di scusses key weakness of these papers. Still many papers are simply summarized, with little or no discussion of their strengths or weaknesses. This gives the impression that the results in these papers are more accurate. This may actually be the case, but if it is, this should be stated more explicitly.

For example, the first paper (Alcott and Wozny) is simply summarized with no editorializing. One possibility is that there are no weaknesses in this paper. But, many of the issues raised later for other papers also relate to this paper. For example, the report correctly states, when discussing the Sawhill paper, that in order to get a consistent estimate of how consumers value fuel economy, the author is requ ired to correctly specify how c onsumers form expectations about gas prices and drive their vehicles. If any of thes e are incorrectly specified , the estimate will be

biased. The same is true for the Alcott and Wozny paper. While I find Alcott and Wozny’s specification for how expectations are formed to likely be more accurate, ironically, they assume consumers are hyper-rational in the sense that they form their gas price expectations based on NYMEX futures prices. In some ways the myopia resu lt is inconsistent with this key assumption.

Differentiating papers by their focus: The author should be commended for reviewing such a diverse set of papers. The report categorizes papers by the data used in the analysis and empirical model (e.g., aggregate data v.

micro-level data and discrete choice v. hedonic pricing model). I propose two alternatives. Many of the papers reviewed did not focus on measurin g the implicit discount rate, or even on the issue of how gas prices affect vehicle demand. If a paper did not focus on either of these two questions, it is difficult to gauge the robustness of thei r results with respect to these questions, the quality of the variation in gas prices in the data, et c. Perhaps a better method would be to first focus on those papers where gas prices and vehicl e choice are the central research question, and those papers where this is more a tangential part of the analysis.

Differentiating papers by their publication status: Many of the papers reviewed have not undergone the peer-review process. While I do not claim that mistakes do not make it through the peer-rev iew process, related to comment above, in some ways a review of an unpublished paper requires a more thorough review of the paper itself. A

D-7second way to organize the review would be to focus first on published papers and then second on unpublished papers. At the very least the fact that a number of the papers are unpublished should be explicitly noted in the text. Many r eaders may never make it to the bibliography.

Comments related to discussion of issues:

The review has an excellent discussion of the issues related to how consumers value fuel economy and the market for fuel economy more gene rally. I enjoyed reading this section. I have
a few comments related to it, however.

At the top of page 5, the author poses: “does th e market value fuel economy improvements at the discounted expected value of future fuel saving s over the lifetime of the vehicle, or less, or

more?”

The author should use the phrase “at society’s discounted expected value...”

In many ways questioning whether the market values fuel economy improvements at the discounted expected value of future fuel savings is simply a tautology. There is always a discount rate that equates how much cons umers are willing to pay for fuel economy improvements given the expected value of the fu ture fuel savings. Therefore, any statement about whether they are willing to pay too little, or too much, is actually a statement about how the consumers’ discount rates compar e with society’s discount rate.

On page 5, the author states, “On the other ha nd, if consumers are myopic and consider only the first three years of fuel savings, for example, fuel economy standards ca n increase welfare even based solely on private costs and benefits.”

If the author is making a statem ent about the consumers’ welfare, and not society’s, then more should be added here. If consumers are myopic becau se their utility function is myopic, then I do not see how fuel economy standards make them bette r off. If my discount rate is actually 20%, because these are my preference s, then I am better off by i nvesting less in fuel economy compared to someone whose discount rate is 10%. Forcing standards does not improve my

D-8welfare. Someone with a 10% discount rate may di sagree with my choice, but there is nothing here that makes my choice non-optimal for me. In contrast, if I behave myopically for reasons outside of my utility function, such as a lack of access to credit or a lack of cognitive ability, then fuel economy standards, as well as subsidized loans and/or in formation campaigns, can improve my welfare. Alternatively, the author can also point to more behavioral economics reasons why this market might fail, for example, because co nsumers have self-control issues. I find many of these reasons to be quite compelli ng. My point is that the author should be more clear here. As it currently reads, it im plies that high discount rates, al one, imply fuel economy standards are welfare improving. This is simply not the case. 3

On page 5 the author states that it is surprisi ng that there is no basic research on how consumers consider fuel economy. This is a strange use of the term basic research, which I take to mean research on pure science. Does the author equate basic science with interviews ? I have never

heard basic science used in this manner.

Comments on specific paper reviews: The reviews of the papers are ve ry well done and the choice of papers very comprehensive. A have a few comments that may improve this disc ussion, as well as a few papers to be added.

Busse, Knittel and Zettelmeyer Unfortunately the discussion of Bu sse et al. on page 32 is incorre ct. The report states that the paper does not control for vehicle attributes. In fact, it controls for an extremely wide set of vehicle attributes through the use of “fixed effects.” In the price equations there are fixed effects for vehicle type, defined as the interaction of make, model, model year, trim level, doors, body type, displacement, cylinders, and transmission. Put in more layman’s terms, the paper is controlling for all vehicle attributes within this vehicle type. That is, th e only way something like horsepower would not be entirely co ntrolled for is if there were two vehicles of the same make, model, model year, trim level, doors, body type, displacement, cylinders, and transmission that had different horsepower levels. So, for example, any attribute that does not vary within 2009

3 I freely admit that the use of “can improve” helps.

D-9Honda Accord four-door EX-L, with a 3.5 lite r, 6-cylinder and an au tomatic transmission vehicles is completely controlled for. The only a ttributes that would not be entirely controlled for are attributes that vary within th is definition, such as color or dealer installed options. Variables such as horsepower likely do not vary within the same make/model/engine size/number of cylinders. Viewed in this way, perhaps this paper is best included in the Hedonic Models section.

In addition, the latest version (NBER Worki ng Paper 15590) also controls for when in the lifecycle of vehicles (both new an d used) the transaction took place. This has cleared up a lot of

the issues that the author rais es at the top of page 32.

The newest version of Busse et al . also is clearer on what is requi red, theoretically, to account for

the differences across new and used car markets. Market power in the new car market is not required. As the author of this report notes, the results simply imply that the supply elasticity in

the new car market is more elastic than in the us ed car market (where a perfectly inelastic supply is likely a good first-order approx imation). Therefore, I would recommend that the author edit or drop the sentence that states “The used car mark et was believed to func tion more efficiently.”

Finally, Table 10 of the report shoul d include the used car results for Busse et al. Without taking into account the results regarding market shares in the new car spec ifications, the used car results

are a more accurate reflection of the shift in de mand from increases in gas prices. So, if only one of the sets of results is to be reported, the us ed car results should be reported. Reporting only the
new car results, without a discussion of the quantity effects, or the us ed car results, is misleading.

Papers that solve for price fr om a discrete choice model A number of papers in the literature, and amon g those reviewed here, argue that if consumers value fuel economy “correctly,” the pric e of a vehicle should rise and fall one-for-one with the vehicle’s lifetime fuel costs. If prices move less than one-for-one, this is taken as evidence that consumers are myopic. These papers typically speci fy utility to be some variant of the logit model (e.g., simple logit, nested logit, etc.) and then solve for the equilibrium price for a vehicle,

conditional on the assumed functional form for utility. The intuition behind this empirical

D-10strategy is best summarized by Alcott and Wozny’s motivating example, where price is expressed as:



### 1 p = (

− γ

G + α

− q ) η

where G is the discounted fuel cost and q the quantity of vehicles available. They note that: “To keep this consumers indifferent between the vehi cles and the most attractive outside option, the overall product price p+G must st ay the same as G changes.” This statement requires that the utility from the outside option doe s not also change with G. For those consumers where the “no car ownership” option is not the mo st attractive outside option this restriction is unlikely to hold.

For example, imagine using this framework to test whether consumers correctly value fuel economy using an ideal experiment and tracking Pr ius prices. In one universe gas prices are $2, in another alternate universe gas prices are $3 . Given the condition above , in order to keep consumers from shifting demand from the Prius to the next best option, whose operating cost is

assumed not to have increased , the price of the Prius must be lower in the $3-universe by the

increase in fuel costs over the li fe of the vehicle. If the price of the Prius falls by less than this amount, estimating the above equation would force you to conclude that consumers undervalue fuel economy.

Now instead imagine that the fuel cost of th e next best option for many Prius owners has increased by more than the Prius, because the next best option is likely to be something like a Camry. In this case, the demand for the Prius actually increases , and prices increase. Thus, we have explained why we concluded that consumer s are myopic in the above regression. Indeed, this is precisely the reason why Busse et al. argues, and shows empirical support for, that the demand, and therefore price, of more fuel effici ent cars will increase when gas prices increase. And, is the reason why these authors focus on th e difference in price changes between high and low fuel economy vehicles.

D-11Of course across all vehicles, the price of some ve hicles will decrease and the price of others will
increase. Therefore, we should not expect the coefficient associated with discounted fuel costs to be negative one, since it will represent the average of these prices changes.

In principle, if one were to specify the correct utility function and dema nd system, then the above empirical strategy would be a valid test of myopia. The most general demand system would imply that the price of a given vehicle is a function of its fuel costs, as well as the fuel costs of all
competitors . This is often intractable. Instead, the profession has migrated to specific demand models that are more parsimonious, such as log it demand models, since the implication of these

demand models is that the ratio of the demand for a particular vehicle to the demand for the outside good is independent of the fuel costs ofother vehicles. However, this is simply a byproduct of the functional form assumptions, and as the Prius example illustrates, is not a general theoretical result, or one that is very intuitive. Insofar as these models are mis-specified, we will

be biased towards findi ng myopic consumers.

A conundrum that may be impossible to solve: As noted by the author in his review of the Sawhill paper, the correct statistical test of consumer myopia requires specifying the present discounted value of future fuel expenditures for each vehicle. This requires assumptions regarding ho w consumers form expectations regarding future gas prices. The available choices for this are limitless, ranging from assuming that consumers view gas prices as a random walk (so today’s pri ce is sufficient to describe the expected value of future gas prices) to models that assume consum ers use some number of recent prices within an autoregressive model, to a hyper-rational mode l where consumers use NYMEX futures on crude oil and a regression model of how ga s prices move with crude oil.

For ordinary least squares to be unbiased, the econometrician mu st have the correct model of how consumers form expectations. Otherwise, the key right hand side variable is measured with

error and the estimated coefficient will be biased towards zero. 4 This typically biases the

statistical test towards concl uding consumers are myopic. Unfortunately, in the end there may

D-12not be a solution to this. Indeed, the irony is th at some papers assume complex ways in which consumers form expectations, but then conclude they are myopic. In some way this strikes me as being inconsistent. If consumers are myopic, then they are also not likel y to use NYMEX futures to form their expectations. Therefore, using NYMEX futures to generate the variable of interest is likely to bias a researcher towards concluding myopia.

Other papers to consider in the review: The paper should consider reviewing the following papers:

Kilian, Lutz and Eric Sims (2006). The Effects of Real Gasoline Prices on Automobile Demand: A Structural Analysis Using Micro Data, Worki ng Paper, University of Michigan (April).

Klier, Thomas, and Joshua Linn (2008). “The Price of Gasoline and the Demand for Fuel Efficiency: Evidence from Monthly New Vehicles Sales Data.” Working Paper, University of Illinois at Chicago (September).

Sallee, James, and Sarah West (2008). “Testing for Consumer Myopia: The Effect of Gasoline Price Changes on the Demand for Fuel Economy in Used Vehicles.” Working Paper, Macalester College (December).

4 This holds when the measurement error is uncorrelated with th e regressor. When the measurement error is correlated with the regressor, the bias can go in either direction.

D-13

### Review of Greene, D.L. (2009) How Consumers Value Fuel Economy: A Literature Review

Walter McManus, University of Michigan Transportation Research Institute
EPA intends to use vehicle choice models to in form the Agency’s analyses of the impacts of regulatory programs that affect vehicle fuel econo my. To adequately predict the ultimate impacts and judge the effectiveness of particular regulatory actions , EPA needs to understand how consumers (and producers) are likely to change their market behavior in response to the regulatory actions. Market choices by producers and consumers of vehi cles and fuels have direct negative impacts on the nation’s air quality and the stratospheri c ozone layer. EPA, which is responsible for protecting and improving air quality and the ozone layer, can in fluence but cannot control the behavior of consumers and producers. Market m odels, including models of consumer vehicle choice and models of producer technology and product decisions, could help EPA anticipate market responses to regulatory actions. This report is a peer review of EPA’s compar ison of recent mainstream economic estimates of the value of additional fuel economy to consumers. The documents that I received from EPA (or RTI International) a memo containing the char ge questions, the draft report by Greene (2009), and three unpublished papers that are covered in the draft report. The unpublished papers are Alcott and Wozny (2009); Busse, Knittel, and Ze ttelmeyer (2009); and Sallee, West, and Fan (2009). I reviewed all of these documents in de veloping my expert opin ion as reported here. 

### Overall approach and methodology of the study

Greene (2009) adopts a conven tional “literature review” a pproach. The question of how consumers value fuel economy in vehicle choice has been the subject of a lively conversation on and off for decades. One appealing feature of th e paper is that the same author conducted a similar review in Greene (1983). Consumers of re search face many temptations to undervalue the retrospective approach, and it is encouraging that EPA’s choice of authors reveals the Agency’s rationality as a consumer of research. The motivation, objectives, and structure of th e paper are described in two paragraphs. “Recent historically high fuel prices, combined with renewed interest in fuel economy and greenhouse gas emissions standards for auto mobiles have engendered a number of new assessments, many specifically aimed at understanding the effects of fuel prices and fuel economy on consumers’ vehicle choices. This paper reviews those studies, published and unpublished, with the objectives of determining whether a consensus now exists on the value consumers place on fuel economy, and of gleaning insights into how consumers use fuel economy information in their car buying decisions. “This paper is organized as follows. Section 2 summarizes views of how the market for fuel economy functions, including both supply and demand . The body of the report is Section 3 which reviews recent empirical estimates of the value of fuel economy based on aggregate and disaggregate data, discrete choice models and hedonic demand analyses. Section 4 discusses the implication of those estimates and Section 5 contains concluding observations.” (page 4)

D-14The overall approach and methodol ogy are within the mainstream of critical review practice in economics, and the execution in unexceptionable. However, both the conventional approach to reviewing economic research and the conventional approach to economic research itself do not give much help to decision makers who are understandably made uncomfortable by the widely differing expert opinions about parameters th at are crucial in pred icting the impacts of regulations and in choosing between alternatives. An overall criti que of conventional practice is beyond the scope of this review. However, I do ha ve some suggestions for improvements in the methodology for comparing studies and for deali ng with the lack of consensus in expert opinions. (The References section below lists some papers by Edward E. Leamer, a professor at UCLA, in which a critique of c onventional practice is developed along with altern ative practices that would enhance the usefulness of economic research to policy makers.) 

### Data analysis conducted for the study

The experts’ papers differ in se veral dimensions that could be responsible for some of the differences in opinions between experts. Green e (2009) helpfully provides a side-by-side comparison for econometric model type, data struct ure, and estimation period. In the text he covers other issues such as the econometric challenges each author faced and the strategies chosen to address the challenges. It is difficult for the reader to verify that the same standards are being used to assess each paper, especially since the amount of discussion by paper varies greatly. This leads the reader to have less confidence in the reviewe r’s opinions of the individual studies (that this or that one ha d plausible or implausible assump tion, methodologies, or results). 

### Recommendations for alternate data and/or analyses

It would be useful to expand Tabl e 10 (or to create a set of tables ) to show other differences that could be important sources of differences in es timates. The items that could be included would show differences in:

1. Maintained assumptions reported (assumptions that are maintained across any alternative specifications or sensitivities),

2. Reported sensitivity analyses (is one done? wh ich assumptions are varied? how widely?),

3. Econometric challenges and approaches used to address them (Greene (2009) appears to discuss these comprehensiv ely in the text.), and

4. Out-of-sample predictive performance (are pred ictions made? about what ? are the predictions compared to actual outcomes? how accurate are the predictions?). Adding these additional side-by-side comparisons would increase the reader’s confidence that the same standards are being used to form the reviewer’s opinions about the relative usefulness of each paper to inform decision making by EPA. My opinion: The additional elements are responsible for more of the variat ion in the estimates of consumer value for fuel economy than are th e elements already included in Table 10. To quantitatively assess whether we have made pr ogress toward a consensus, we need a measure of researcher/specification un certainty and disagreement. The 1983 and 2009 results are not compared quantitatively. Greene (1983) compared estimates of the consumer discount rate, while Greene (2009) compared estimates of consumer willingness to pay for improvements in fuel

D-15economy. The idea is to compare the range of parameter estimates to the parameter value predicted by mainstream theory. For the consumer discount rate the theoretical value is the real discount rate, which is assumed to be 7% the foll owing. For the willingness to pay version, the theoretical value is 100% (or will ing to pay $1 for future fuel cost savings with a discounted present value of $1). The metric, which I call the Multip le Extreme Estimates Test (MEET) , is defined as the ratio of the value predicted by theory to the diffe rence between the two extreme estimates. Value Predicted by Theory V MEET = = Largest Estimate - Smallest Estimate R
lim MEET = 0 and lim MEET = ∞ R →∞ R → 0 Numerically, MEET measures the predicted value as a share of the range of expert opinion. The range of expert opinion, R, is a crude and partial measure of the uncertainty or fragility of the estimates due to differences in assumptions, specification, and opinions between researchers. The metric MEET views this fragility compared to the theoretical value of the parameter, V. If the span of disagreement between experts is large, then MEET is small. The limiting case, infinite disagreement, produces a MEET of 0; there is not a meeting of the minds. If the span of disagreement is very small (compared to the th eoretical value of the parameter), then MEET is large. Complete agreement implies an infinite MEET.



### Multi p le Extreme Estimates Test ( MEET )

(The ratio of the parameter value predicted by theory to the range of extreme parameter estimates.)

Greene Greene Estimates used to compute MEET (1983) (2009)

All studies* 0.002 0.055

All but one "outlier" ** 0.096 0.080 Greene (1983) "plausible" *** 0.194

* 22/22 in 2009 & 8/8 in 1983 ** The 1983 range 0% to 73% is used, based on Table 1. In the text Greene (2009) reports the range for 1983 as 2% to 73%. The MEET for the narrower range is 0.099.
*** In my opinion, this represents Greene's opinion that the plausible range is 4% to 40%. Do the 1983-2009 changes in MEET provide any eviden ce that a meeting of the minds is closer today than it was in 1983? The table shows several al ternative calculations of MEET for Greene (1983) and Greene (2009). The alternatives vary by which of the studies in each year are actually used in computing the metric for that year (b ased on my interpretation of comparisons made by Greene to which are added alternatives th at include all studies in each year). The first thing to observe is th at all of the MEET values are very low, indicating that the disagreement between experts is very large. Us ing all studies each year in the computation of MEET shows an increase from 0.002 to 0.055. This result is driven by th e extreme outliers—the 1983 outlier (-164% to 2840% range for consumer discount rate compared to 7% predicted by

D-16theory) is more of an outlier than is the 2009 outlier (-360% to 1410% range for willingness to pay compared to the 100% predicted by theory). Dropping the outliers (not something I would be comfortable doing if the authors of the 30 studies had reported more informative and thorou gh sensitivity analyses) would result in a drop in MEET from 0.096 in 1983 to 0.080 in 2009. We ar e getting farther away from a consensus, but the backtrack is small in absolute terms. If the meeting of the minds is in Ann Arbor, and there was only one holdout and he was located in Davis (CA) in 1983, instead of beginning the 2,300-mile hike to Ann Arbor (according to Google), he wandered 35 miles in the opposite direction. 

### Appropriateness of the datasets and any other inputs

It is not clear how the studies were selected fo r inclusion in Greene (2009). There needs to be some explanation. 

### Appropriateness of the conclusions drawn

There are two fundamental conclusions made by Greene (2009). Firstly, e xpert opinion remains widely divided about the value of fuel economy to consumers. Despite the improvements in the quality of data about consumer behavior and in econometric tool s, opinion is as widely divided today as it was three decades ago. I agree that th is is the appropriate, di scouraging conclusion to draw. The second fundamental conclusion drawn by Green e (2009) concerns the causes of the wide divisions in expert opinion and what should be done about it. “Although the methodologies or model formulations of a few of the studies are questionable, there do not appear to be clear associations among methods or data sources and the resulting inferences. It is suggested that such conflicting r esults may be attributable to incorrect models of consumer decision making about fuel economy, the statistical problems caused by omitted variables, errors in variables and correlated vari ables, and the complexity of consumers’ vehicle choice decisions. Additional, empirical behavioral research appears to be needed to resolve the issue.” (abstract)
I am not convinced that the differences in assumptions, opinions, and methods have been sufficiently examined to support even the weak pr oposition that “there do not appear to be clear associations among methods or data sources and the resu lting inferences.” See my recommendations on pp. 2-4 above. I am not su re exactly what Greene means by “incorrect models” of consumer decision making about fuel economy, but if he means the efficient markets hypothesis and economic rationality, then I agree. Assuming that it is th is deficiency in our models of consumer behavior th at would be the subject of “beh avioral research,” I agree. 

### Overall clarity of the presentation

The overall clarity of the pr esentation was very high.

D-17

### References

Leamer, E. E. (1983), Let’s take the con out of econometrics, American Economic Review, 73, 31-43. Leamer, E. E. (1985), Sensitivity analyses would help, American Economic Review, 75, 308

- 313. Leamer, E. E. (1987), Econometric metaphors, in T. F. Bewley (ed.), Advances in Econometrics, Cambridge University Press, Cambridge, pp. 1-29. Leamer, E. E. (1989), Planning, Criticism, and Revision, Journal of Applied Econometrics, 4, Supplement, S5-S27. Leamer, E. E. (1992), Bayesian Elicitati on Diagnostics, Econometrica, 60, 919-942.

D-18______________________________________________________________________________ March 30, 2010

MEMORANDUM

SUBJECT: EPA Response to Comments on Da vid Greene paper, “How Consumers Value Fuel Economy: A Literature Review,” by peer reviewers Drs. Carolyn Fischer, Christopher Knittel, and Walter McManus

FROM: Dr. Gloria Helfand, Assessment and Standards Division

Dr. Carolyn Fischer of Resources for the Future, Dr. Christopher Knittel of the Department of Economics of the University of California at Da vis, and Dr. Walter McManus of the University of Michigan Transportation Research Instit ute reviewed David Greene’s paper, “How Consumers Value Fuel Economy: A Lite rature Review,” dated December 29, 2009.

This memo includes a summary of comments prep ared by RTI International, and responses and actions in response to those comments from Dr . David Greene of Oak Ridge National Laboratory and EPA.



### 3.1 OVERALL APPROACH AND ME THODOLOGY OF THE STUDY The reviewers are suppor tive of the overall approach and methodology. Walter: “ The overall approach and methodology are with in the mainstream of critical review practice in economics, and the ex ecution in unexceptionable.” He does comment on the fact that “Greene (2009) adopts a conventional ‘literatur e review’ approach” and “both the conventional approach to reviewing economic research and th e conventional approach to economic research itself do not give much help to decision make rs who are understandably made uncomfortable by the widely differing expert opinions about parameters that are crucial in predicting the impacts of regulations and in choosing between alternatives. An overall criti que of conventional practice is beyond the scope of this review. However, I do ha ve some suggestions for improvements in the methodology for comparing studies and for deali ng with the lack of consensus in expert opinions. (The References section below lists some papers by Edward E. Leamer, a professor at UCLA, in which a critique of c onventional practice is developed along with altern ative practices that would enhance the usefulness of economic research to policy makers.)”

Chris comments that the study does not discuss “ why consumers undervalue gasoline, relative society (if they do indeed underv alue fuel economy). This has im portant implications for which policies are most effective at aligning discount rates.” However, he recognizes that papers dealing with such issues are lacking.

Response: EPA is satisfied with the “conven tional” literature review approach that Dr. Greene has used. If there is a lack of consensus about model paramet ers, this is important information for EPA as it pursues its modeling activities.EPA did not request that Dr. Greene discuss why consumers may undervalue – or, more generally, misestimate the value of -- gasoline. EPA’s initial in terest is learning how consumers consider fuel economy when they are purchasing vehicles. Greene includes some discussion of this topic on p. 8 as well as in the Executi ve Summary and the Conclusion. We agree that understanding why consumers may misestimate this value is an important topic.



### 3.2 APPROPRIATENESS OF TH E DATASETS AN D ANY OTHER INPUTS

One reviewer commented that the choice of the papers was comprehensive. Another reviewer recommended including some explanation of how the studies were selected for inclusion in Greene (2009).

Response: The paper includes a discussion of its selection of papers on p. 2. In particular, it states Dr. Greene’s intent to be comprehensive. The lit erature review includes some of the most well known papers in the field (such as papers by Be rry, Levinsohn, and Pakes and Goldberg) as well as other less well known works and papers in progress. Dr. Greene added additional papers to the review between the initial draft and the final report, in response to reviewers’ suggestions. Dr. Greene notes that he felt it important to include studies not (yet) published in peer reviewed literature because he considered them of publishable quality. EPA’s assessment is that, even if the review may have missed some papers, there do es not appear to be any systematic bias in inclusion or exclusion. In addition, we support the in clusion of gray literature, because it is the most current research being conducted.



### 3.3 DATA ANALYSIS COND UCTED FOR TH E STUDY

Two reviewers comment on the fact that the type of analysis done for the different papers varies greatly.

Chris: “It strikes me that there are two ways to conduct a review su ch as this. One is to report the results of papers with little, or no, discussion of the quality each paper. The other is to both review and critique each paper. I found a lack of uniformity in this regard. For many of the papers, the latter strategy is taken. The report di scusses key weakness of these papers. Still many papers are simply summarized, with little or no discussion of their strengths or weaknesses. This gives the impression that the resu lts in these papers are more accurate. This may actually be the case, but if it is, this should be stated more explicitly.

For example, the first paper (A lcott and Wozny) is simply su mmarized with no editorializing. One possibility is that there are no weaknesses in this paper. But, many of the issues raised later for other papers also relate to this paper. For example, the report correctly states, when discussing the Sawhill paper, that in order to ge t a consistent estimate of how consumers value fuel economy, the author is requir ed to correctly specify how cons umers form expectations about gas prices and drive their vehicles. If any of th ese are incorrectly specified, the estimate will be biased. The same is true for the Alcott a nd Wozny paper. While I find Alcott and Wozny’s specification for how expectations are formed to likely be more accurate, ironically, they assumeconsumers are hyper-rational in the sense that th ey form their gas price expectations based on NYMEX futures prices. In some ways the myopi a result is inconsistent with this key assumption.”

Walter: “It is difficult for the reader to verify that the same standards are being used to assess each paper, especially since th e amount of discussion by paper va ries greatly. This leads the reader to have less confidence in the reviewer’s opinions of the individual studies (that this or that one had plausible or implausible assumption, methodologies, or results).”

Response: As Dr. Greene discusses on p. 2 of the paper, “This review attempts to com pare the inferences of different studies on a consistent basis: a typical consumer’s willingness to pay for a reduction in the present value of fuel cost s through improved fuel economy.” The comments on individual studies are valuable in identifyi ng issues and difficulties that arise in con ducting these studies. These critiques are, to EPA, nevertheless less im portant than a comparison of the estimates of the willingness to pay for fu el economy across studies. T able 12 of the paper (pp. 50-51) provides that comparison.



### 3.4 APPROPRIATENESS OF THE CONCLUSIONS DRAWN There was general consensus among the reviewers on the major conclusion of the document: that the literature remains mixed as to whether consumers underv alue, overvalue, or approximately value fuel economy.

One reviewer raised doubts that differences in assumptions, opinions, and methods have been sufficiently examined to support even the weak pr oposition that “there do not appear to be clear associations among methods or data sources and the resulting inferences.”

One reviewer expressed doubts abou t what Greene means by “inc orrect models” of consumer decision making about fuel economy but suggest ed efficient markets hypothesis and economic rationality to be a possible in terpretation of this phrase.

Response: EPA accepts the general conclusion that the lit erature remains mixed and unsettled on how consumers consider fuel econom y when buying vehicles.

The Executive Summary, the Conclusion, and Tabl e 13 of the report provide new, further identification and assessment of the effects of different factors on modeling results. As Greene notes on p. 55, “There does not appear to be an obvious explanation for the widely divergent results. Neither model type, formulation of the variable representing fuel economy, data type, time period, nor any other readily identifiable factor shows a str ong association with inferences about the values consumers place on fuel economy (Table 13).”

About the comment that there has been insuffic ient examination to support the proposition that “there do not appear to be clear associations among methods or data sources and the resulting inferences:” it is possible that further exami nation may reveal associations between results andunderlying characteristics of the studies, and Greene’s statement leaves open that possibility. In the meantime, Greene was not able to find such patterns.

Greene has modified the “incorrect models” la nguage to refer to “the likelihood that the rational economic consumer model does not ade quately describe th e decision-making of consumers in the real world” (p. xix, the Abstract ; see p. 9 for similarly revised language). This new language appears to correspond to the reviewer’s interpretation.



### 3.5 RECOMMENDATIONS FOR ALTERNATE DATA AND/OR ANALYSES

3.5.1 Additional Data Two of the reviewers suggested several other stud ies that are relevant for this work. A list of these studies is provided below.

Dreyfus, Mark K. and W. Kip Viscusi (1995) . “Rates of Time Preference and Consumer Valuations of Automobile Safety and Fuel Efficiency.” Journal of Law and Economics 38: 79-98. Hughes, Jonathan E., Christopher R. Knittel and Daniel Sperling (2008). “Evidence of a Shift in the Short-Run Price Elasticity of Gasoline Demand.” Energy Journal

. Kilian, Lutz and Eric Sims (2006). The Effects of Real Gasoline Prices on Automobile Demand: A Structural Analysis Using Micro Data, Worki ng Paper, University of Michigan (April). Klier and Linn (2010 working paper) “The Pri ce of Gasoline and New Vehicle Fuel Economy: Evidence from Monthly Sales Data” Klier, Thomas, and Joshua Linn (2008). “The Price of Gasoline and the Demand for Fuel Efficiency: Evidence from Monthly New Ve hicles Sales Data.” Working Paper, University of Illinois at Chicago (September). Sallee and West (2009 working paper) Sallee, James, and Sarah West (2008). “Testing for Consumer Myopia: The Effect of Gasoline Price Changes on the Demand for Fuel Econom y in Used Vehicles.” Working Paper, Macalester College (December). West, S. (2008). “The Effect of Gasoline Prices on the Demand for Sport Utility Vehicles.” Working Paper. Macalester College.

Response: Greene has added 5 papers to the review since the dr aft that the reviewers saw: Kilian and Sims (2006), Klier and Linn (2008), Sallee, West, and Fan (2010), Vance and Mehlin (2009), and Fifer and Bunn (2009). Time lim itations affected his ability to incorporate additional papers.

3.5.2 Additi onal Analysis The reviewers suggested several additiona l analyses to strengthen the study.

3.5.ii a. The author should take advantage of the summary section to indicate whether some approaches reviewed in the study are likely to be better than others.Response: In the Executive Summary, Greene suggests con vening researchers to investigate jointly why results differ so greatly. He also suggests in vestigation of alternatives to the rational economic model as a starting point for the analyses.

The conclusion has some discussion of study characteristics that might be superior to others. As he notes, it is not clear whether studies that had superior characteristics produced more consistent results than studies w ith less ideal characteristics. He suggests several factors (pp. 54-55) that might improve result s: recognition that consumers do not appear to follow “the strict model of rational economic behavior;” c onsideration of consumer heterogeneity; and use of fixed effects.

3.5.ii b. The analysis to explain the di fference in results could be improved.

Carolyn: “First, the discussion interweaves reasons that could explain why we can plausibly believe any of a range of results (e.g., heterogene ous decision rules, uncer tainty) with reasons for why different studies get different results. It would be helpful to separate these discussions, reminding readers of the former, and then focusi ng on the latter, which is the most important contribution. This kind of analysis should help in dicate best practices and directions for future research. Can we suggest some experiments (e .g., new techniques on old data sets, or old techniques on new data sets) th at can help tease out what diffe rences arise from alternative econometric approaches? If most studies have focused on other aspects of vehicle demand, are there better specifications for looking dire ctly at the valuation of fuel economy?” A summary of key differences in approaches and data and an analysis of their consequences would be useful. These would include

• levels of aggregation;

• time horizons (how useful is information from the 1970s in estimating current demand?);

• incorporation of the supply side;

• details of other attributes and variable definitions;

• allowing for separate responses to MPG and fu el costs (this was raised as lacking in the discussion of Gramlich, but it was not apparent which other studies had done this);

• assumptions of vehicle lifetime, VMT, discount rates, etc.; and

• econometric approach.

Although Table 10 provides some of these summa ry indicators (model type, data, and time), additional analysis such as th e following would be useful: “Do we observe any trends across classes or time? Within a class of m odels, what drives the differences?”

Walter: “It would be useful to expand Table 10 (or to create a set of tables) to show other differences that could be important sources of di fferences in estimates. The items that could be included would show differences in:1. Maintained assumptions reported (assumptions that are maintained across any alternative specifications or sensitivities), 2. Reported sensitivity analyses (is one done? wh ich assumptions are varied? how widely?), 3. Econometric challenges and approaches used to address them (Greene (2009) appears to discuss these comprehensiv ely in the text.), and 4. Out-of-sample predictive performance (a re predictions made? about what? are the predictions compared to actual outcome s? how accurate are the predictions?).

Adding these additional side-by-side comparisons would increase the reader’s confidence that the same standards are being used to form the reviewer’s opinions about the relative usefulness of each paper to inform decision making by EPA.

My opinion: The additional elements are responsible for more of the variat ion in the estimates of consumer value for fuel economy than are th e elements already included in Table 10.”

He also suggested a measure of researcher/s pecification uncertainty and disagreement to quantitatively assess whether we have made progr ess toward a consensus. He also provides illustrative suggestions on ways to use and interpret this measure. “The idea is to compare the range of parameter estimates to the parame ter value predicted by mainstream theory.”

The metric is called Multiple Extreme Estimates Test (MEET) and is defined as the ratio of the value predicted by theory to the differ ence between the two extreme estimates.

Value Predicted by Theory V MEET Largest Estimate - Smallest Estimate R
lim MEET 0 and lim MEET
R R 0
“Numerically, MEET measures the pr edicted value as a share of the range of expert opinion. The range of expert opinion, R, is a crude and partial measure of the uncertainty or fragility of the estimates due to differences in assumptions, specification, and opinions between researchers. The metric MEET views this fragility compared to the theoretical value of the parameter, V.”

Response: The Executive Summary, Conclusion, and Table 13 include further identification and assessment of the characteristics that might , in principle, be useful in a meta-analysis: the publication status of the study; the kind of model used; the dependent variable; the type of data; the time period covered; the fuel economy measure; the form of price expecta tions; whether actual transactions prices were used; whether the mode l allowed for heterogeneous tastes; whether the model included both the demand and the supply side; and whether fuel economy standards were included. This list does not incl ude all the variables that the r eviewers cite, but it includes many of them. The discussions of indi vidual papers include some of the ot her factors, such as some of the assumptions of the models. As the Executive Summary and Conclusion indicate, there are no obvious connections among these factors and the model results.With so many variables and not very many studies, a statistical meta-analysi s of these results is unlikely to produce statistically valid results.

The MEET criterion is an interesting way to th ink about the variation in study results. EPA at this time is satisfied with a qualitative disc ussion of the variation of these results.

3.5.ii.c. Though the issue of consumer hete rogeneity has been mentioned in several places, this may be important area for additiona l analysis, both to explain differences and to suggest future research directions.

Response: The issue of modeling consumer hete rogeneity is likely to be important in these models. At this time it is a source of distinction among models : some approaches, especially mixed logit, incorporate this feature. The review at this time does not extend to include a discussion of the “dream” analysis – what would be the ideal data sets, methods, etc. Assessing the state of the literature is a first step to ge t to that discussion, and this re view has focused on that step.



### 3.6 OVERALL CLARITY OF THE PRESENTATION The reviewers agreed that the overall clarity of the document was high.

Reviewers had several suggestions about organizing the paper.

i. One reviewer suggested that since the articl es are organized logically by class of data and methods, it would be helpful to review thos e methods at the beginning of each section “including the advantages and drawbacks, as well as key factors or assumptions that can affect the results.”

Response: Greene has not included this review of methods. EPA agrees that it would be useful information, but such review informati on is available elsewhere.

ii. It has also been suggested that it would be helpful to begin with the seminal papers in each category, “so as to understand the evolut ion and improvements made subsequently.”

Response: Greene has reorganized the presenta tion of the papers. For inst ance, the section on discrete choice models with aggregate data now begins with the paper by Berry, Levinsohn, and Pakes (1995), a widely cited paper.

iii. Two reviewers agreed that the publication status of papers should be recognized and one reviewer suggested that the review should “focus first on published papers and then second on unpublished papers.”

Response:Greene discusses, on p. 2, his reasons for including unpublished papers – in particular, his opinion that “they are of publis hable quality.” The new Table 13 has a column identifying the publication status of al l the studies included.

iv. Chris Knittel: “Many of the papers revi ewed did not focus on measuring the implicit discount rate, or even on the issue of how gas prices affect vehicle demand. If a paper did not focus on either of these two questions, it is difficult to gauge the robustness of their results with respect to these questions, the qua lity of the variation in gas prices in the data, etc. Perhaps a better method would be to first focus on those papers where gas prices and vehicle choice are the central resear ch question, and those papers where this is more a tangential part of the analysis.”

Response: Perhaps the major concern with studies that do no t focus on fuel economy decisions is that there may not have been adequate attent ion to specification of the vari able, or problems with omitted or collinear variables. For those reasons, the studies may not produce robust estimates of the implicit value of fuel economy.

On the other hand, studies that focus on these vari ables may suffer from the attention as well: if the results come out against expectations, there can be a temptation to revise the analysis until the results meet expectations. Only if results to all specifications are reported is it possible to see whether the reported results are robust.

As Greene discusses in the conclusion (p. 55), omitted variables, errors in variables, and correlated variables are likely to be problems that may be difficu lt to overcome in the vehicle choice context. Fixed effects may he lp, but may not solve the problem.

On a related note, another reviewer commented on studies that do not explicitly estimate the value of fuel economy: “Since few econometric st udies have explicitly es timated the value of fuel economy, a significant contribution of the paper is to translate a wide variety of results into more consistent indicators. Yet, they could still be more consistent. In Table 10, can all of the results be converted into the same WTP metric , preferably using the same assumptions about vehicle lifespan, VMT, discounting, etc.?”

Response: Table 12 seeks to translate estim ates from all the papers into bot h a willingness to pay for fuel economy as a percent of the discounted presen t value of fuel savings, and an implied annual discount rate. As Greene discusses in the paper, it is not possible with some of the studies to find the common metric; with others, he has questions about some of the valu es reported that are necessary for the metric. EPA hope s that identifying th ese difficulties may stimulate future researchers to report these values more consistently.

Another comment on the presentation of the paper was that “the author’s baseline assumptions need to be stated clearly early in the paper, so careful attention can be given throughout to assumptions that deviate from that baseline. Indeed, the statement made in the Allcott and Wozny analysis (‘Calculating the discounted pres ent value of fuel cost s requires a number ofassumptions...’) should be made earlier in a genera l context, so that th e variety and range of assumptions can be understood and explored.”

Response: Greene includes his assumptions for a baselin e analysis in the A ppendix to the paper and discusses these assumptions on p. 2.



### 3.7 OTHER CLARIFICATION COMMENTS One reviewer provided the follo wing comments to clarify or rephrase certain statements.

1. The authors should “use the phrase ‘at society’s discounted expected value...’ (top of page 5) instead of ‘does the market value fuel economy improvements at the discounted expected value of future fuel savings over the lifetime of the vehicle, or less, or more?’”

Response: This change has been made.

2. The statement (on page 5) that “On the othe r hand, if consumers are myopic and consider only the first three years of fuel savings, for example, fuel economy standards can increase welfare even based solely on privat e costs and benefits” should be made clearer.

Response: This language continues in its original form.

3. One of the reviewers comment on the statemen t on page 5 that “it is surprising that there is no basic research on how consumers consider fuel economy.” “This is a strange use of the term basic research, which I take to mean research on pure science. Does the author equate basic science with in terviews? I have never heard basic science used in this manner.”

Response: The word “basic” has been changed to “behavioral.”

Two of the reviewers also provide d several detailed comments on specific paper reviews, Section 2 of the document, and editorial comments and corrections to typographical errors.

Response: Greene has incorporated most of these comments into the revision.