UNITED STATES ENVIRONMENTAL PROTECTION AGENCY
WASHINGTON D.C. 20460

OFFICE OF THE ADMINISTRATOR

SCIENCE ADVISORY BOARD September 24, 2009

EPA-SAB-09-018

The Honorable Lisa P. Jackson

Administrator U.S. Environmental Protection Agency 1200 Pennsylvania Avenue, N.W. Washington, D.C. 20460

Subject: Science Advisory Boar d (SAB) Advisory on EPA’s draft Guidelines for Preparing Economic Analyses (2008)

Dear Administrator Jackson:

EPA’s National Center for Environmen tal Economics requested that the SAB

review EPA’s draft Guidelines for Preparing Economic Analyses (2008). The

Guidelines , originally issued in 2000 and recen tly updated, represent Agency policy on the preparation of economic analysis require d by legislative and administrative mandates and are intended to provide te chnical guidance to analysts on the economic analysis of environmental policy. The SAB Environmental Economics Advisory was impressed with many facets of the updated Guidelines . We applaud EPA for a number of carefully revised chapters and substantively improved c overage of many topics. In the enclosed report, we provide responses to EPA’s ch arge questions and recommendations for additional improvements. In this letter , we provide highlights of our overarching

comments.

The current draft of the Guidelines could be improved by clearly identifying

EPA’s role and discretion in setting environmental policy. Specifically, policy options

are described in the Guidelines in a manner that could allow the reader to infer that EPA

has the discretion to choose from a variet y of policy instruments (e.g., regulations or taxes) to achieve environmental targets. In reality, of course, only the legislative branch has the power to tax, subsidize or assign li ability, and both the Clean Water Act and the Clean Air Act very clearly specify what kinds of regulations EPA may promulgate. The

Guidelines should make clear that while economic an alysis can identify superior policy options, EPA’s legal authority defines its me nu of choices. This might be done quite effectively by using examples from legisl ation to make the li mitations concrete.

In addition to clarifying EPA’s role in policy, the Guidelines should be grounded in the realities of information and political constraints, as well as market distortions,either market induced or created by government interventions --- so named “second best” conditions. For example, the theory section focuses on first-best pol icy choices but this framework is nearly irrelevant to contempor ary water pollution problems. The section on subsidies does not acknowledge that many s ubsidies in agriculture , car manufacturing, oil and gas, etc. are not designed to correct ex ternalities but may in fact worsen them. Examples, such as the perverse incentives cr eated by federal subsidies for corn-derived ethanol, are needed to illustrate these issues.

The Guidelines provide scant coverage of the lo ng-standing issue in benefit-cost analysis of valuing the benefits of pr otecting ecological systems and services. Monetizing ecosystem services remains an area of significant challenge. The Guidelines

should discuss situations where “non-monetized” benefits are e xpected to be a significant portion of the regulatory outcome including ad vice for practitioners in this case and noting that adherence to formal dollar-based benefit-cost anal ysis can lead to incorrect efficiency signals. We note that the recent SAB report on Valuing the Protection of Ecological Systems and Services (2009) provides useful insights on this topic.

The literature cited in the Guidelines needs to be updated. In its coverage of economic valuation methods for benefits analysis, the Guidelines did not incorporate numerous new studies using re vealed preference methods, st ated preference, approaches combining the two, and experiments in the lab and field. Other areas in which the literature needs updating include mortality benefits valuation, empirical work on the limited effectiveness of voluntary approaches (without financial in centives) and water quality trading.

The Guidelines could also be strengthened with case studies. For example, the

Guidelines identify the basic steps involved in “benefits transfer” (using values of environmental quality estimates for one locati on to value changes at another), but readers would benefit substantively from a c oncrete real world example. The Guidelines enumerate a step-by-step approach for economic impact analysis but again, readers would benefit from a specific example fr om EPA’s own experience. The Guidelines’ discussion of environmental equity impacts would be greatly enriched with a case study.

Finally, the Guidelines are focused on economic analysis needed for “traditional” environmental problems, e.g., chemical releas es from point sources to air and water. Given the emergence of climate change as the preeminent environmental threat, EPA will need more complex, interdisciplinary anal ysis to address greenhouse gas mitigation including information from the bio-physic al sciences, economics and atmospheric sciences. Computable general equilibrium (CGE) models, a subject covered well in the

Guidelines , will be of critical importance but CG E models will likely be wedged in a portfolio of models tracking complex processe s. EPA’s greenhouse ga s lifecycle analysis of various fuels (required by Congress in th e Energy independence and Security Act of 2007) is an early example of the daunting anal ytic challenges associated with forecasting greenhouse gas emissions under various policies. The Guidelines should anticipate a changing role for economics amidst the extraordinary complexity posed by climate change and other global processes.

iiBy providing thorough and consistent t echnical advice regarding the application of benefit cost analysis to environmental problems, the Guidelines significantly elevate the quality and transparency of the inform ation upon which environmental decisions are made. We again applaud EPA for developing these Guidelines and the Agency’s commitment to continually revise and im prove them. Indeed, we believe these

Guidelines could serve as a successful model fo r all state and federal agencies who undertake benefit-cost analysis in support of environmental decision making. We greatly appreciate the opportunity to prov ide advice on this draft of the Guidelines and look forward to the Agency’s response.

Sincerely,

/Signed/ /Signed/

Dr. Deborah L. Swackhamer, Chair EPA Science Advisory Board Dr. Catherine Kling, Chair SAB Environmental Economics Advisory

Committee

Enclosure

iiiU.S. Environmental Protection Agency Science Advisory Board Environmental Economics Advisory Committee

CHAIR Dr. Catherine Kling, Professor, Department of Economics, Iowa State University, Ames,

IA

MEMBERS Dr. Anna Alberini, Associate Professor, Department of Agricultural and Resource Economics, University of Maryland, College Park, MD

Dr. Michael Greenstone, ∗ 3M Professor of Environmental Economics, Massachusetts Institute of Technology, Boston, MA. On l eave to the Council of Economic Advisors (2009).

Dr. James K. Hammitt, Professor, Center for Risk Analysis, Harvard University, Boston,

MA

Dr. Madhu Khanna, Professor, Department of Agricultural and Consumer Economics, University of Illinois at Urbana-Champaign, Urbana, IL

Dr. John List, Professor, Depa rtment of Economics, Universi ty of Chicago, Chicago, IL

Dr. James Opaluch, Professor, Department of Environmental and Natural Resource Economics, College of the Environment and Li fe Sciences, University of Rhode Island, Kingston, RI

Dr. George Parsons, Professor, Department of Economics, College of Marine and Earth Studies, University of Delaware, Newark, DE

Dr. James Shortle, Professor, Agricultural Economics and Rural Sociology, Pennsylvania State University, University Park, PA

Dr. Laura Taylor, Director, Center for Environmental and Resource Economics and Department of Agriculture and Resource Economics, North Carolina State University, Raleigh, NC

Dr. Peter J. Wilcoxen, Associate Professo r, Economics and Public Administration, Syracuse University, Syracuse, NY

∗ In order to serve on the Council of Economic Advisors, Dr. Greenstone resigned from the Environmental Economics Advisory Committee in February of 2009 and hence was not involved in writing this Advisory

thereafter.

ivDr. David Zilberman, Professor, Agricultur e Resource Economics Department, College of Natural Resources, University of California, Berkeley, CA

SCIENCE ADVISORY BOARD STAFF Dr. Holly Stallworth, Designated Federal Officer, Environmental Protection Agency, Washington, D.C.

v

### U.S. Environmental Protection Agency Science Advisory Board

BOARD

CHAIR

Dr. Deborah L. Swackhamer , Professor and Co-Directo r, Environmental Health Sciences and Water Resources Center, Un iversity of Minnesota, St. Paul, MN

SAB MEMBERS

Dr. David T. Allen , Professor, Department of Chemical Engineering, University of Texas, Austin, TX

Dr. John Balbus , Chief Health Scientist, Environmental Health Program, Environmental Defense Fund, Washington , DC

Dr. Gregory Biddinger , Coordinator, Natural Land Ma nagement Programs, Toxicology and Environmental Sciences, ExxonMobil Biomedical Sciences, Inc., Houston, TX

Dr. Timothy Buckley , Associate Professor and Chair, Division of Environmental Health Sciences, College of Public Health, Th e Ohio State University, Columbus, OH

Dr. Thomas Burke , Professor, Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Healt h, Johns Hopkins University, Baltimore, MD

Dr. James Bus , Director of External Technology , Toxicology and Environmental Research and Consulting, The Dow Chemical Company, Midland, MI

Dr. Deborah Cory-Slechta , Professor, Department of Environmental Medicine, School of Medicine and Dentistry, Univers ity of Rochester, Rochester, NY

Dr. Terry Daniel , Professor of Psychology and Natural Resources, Department of Psychology, School of Natural Resources, University of Arizona, Tucson, AZ

Dr. Otto C. Doering III , Professor, Department of Agricultural Economics, Purdue University, W. Lafayette, IN

Dr. David A. Dzombak , Walter J. Blenko Sr. Professor of Environmental Engineering, Department of Civil and Environmental Engi neering, College of Engineering, Carnegie Mellon University, Pittsburgh, PA

Dr. T. Taylor Eighmy , Vice President for Research, Office of the Vice President for Research, Texas Tech University, Lubbock, TX

viDr. Baruch Fischhoff , Howard Heinz University Profe ssor, Department of Social and Decision Sciences, Department of Engineer ing and Public Policy, Carnegie Mellon University, Pittsburgh, PA

Dr. James Galloway , Sidman P. Poole Professor of Environmental Sciences Associate Dean for the Sciences, College and Graduate School of Arts and Sciences, University of Virginia, Charlottesville, VA

Dr. John P. Giesy , Professor and Canada Research Chair, Veterinary Biomedical Sciences and Toxicology Centre, University of Saskatchewan, Saskatoon, Saskatchewan,

Canada

Dr. James K. Hammitt , Professor, Center for Risk Analysis, Harvard University, Boston, MA

Dr. Rogene Henderson , Senior Scientist Emeritus, L ovelace Respiratory Research Institute, Albuquerque, NM

Dr. James H. Johnson , Professor and Dean, College of Engineering, Architecture & Computer Sciences, Howard University, Washington, DC

Dr. Bernd Kahn , Professor Emeritus of the Nucl ear and Radiological Engineering Program and Director, Envi ronmental Radiation Center, School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA

Dr. Agnes Kane , Professor and Chair, Departme nt of Pathology and Laboratory Medicine, Brown University, Providence, RI

Dr. Meryl Karol , Professor Emerita, Graduate School of Public Health , University of Pittsburgh, Pittsburgh, PA

Dr. Catherine Kling , Professor, Department of Economics, Iowa State University, Ames, IA

Dr. George Lambert , Associate Professor of Pediatri cs, Director, Center for Childhood Neurotoxicology, Robert Wood Johnson Me dical School-UMDNJ, Belle Mead, NJ

Dr. Jill Lipoti , Director, Division of Environmenta l Safety and Health, New Jersey Department of Environmental Protection, Trenton, NJ

Dr. Lee D. McMullen , Water Resources Practice Leader, Snyder & Associates, Inc., Ankeny, IA

Dr. Judith L. Meyer , Distinguished Research Profe ssor Emeritus, University of Georgia, Lopez Island, WA

viiDr. Jana Milford , Professor, Department of Mechanical Engineering, University of Colorado, Boulder, CO

Dr. Christine Moe , Eugene J. Gangarosa Professor, Hubert Department of Global Health, Rollins School of Public H ealth, Emory University, Atlanta, GA

Dr. M. Granger Morgan , Lord Chair Professor in Engineering, Department of Engineering and Public Policy, Carneg ie Mellon University, Pittsburgh, PA

Dr. Duncan Patten , Research Professor , Department of Land Resources and Environmental Sciences, Montana State University, Bozeman, MT

Mr. David Rejeski , Director, Foresight and Governance Project , Woodrow Wilson

International Center for Scholars, Washington, DC

Dr. Stephen M. Roberts , Professor, Department of P hysiological Sciences, Director, Center for Environmental and Human Toxicolog y, University of Florida, Gainesville, FL

Dr. Joan B. Rose , Professor and Homer Nowlin Chai r for Water Research, Department of Fisheries and Wildlife, Michigan State University, East Lansing, MI

Dr. Jonathan M. Samet , Professor and Chair, Departme nt of Preventive Medicine, University of Southern California, Los Angeles, CA

Dr. James Sanders , Director and Professor, Skidaway Institute of Oceanography, Savannah, GA

Dr. Jerald Schnoor , Allen S. Henry Chair Professo r, Department of Civil and Environmental Engineering, Co-Director, Ce nter for Global and Re gional Environmental Research, University of Iowa, Iowa City, IA

Dr. Kathleen Segerson , Professor, Department of Economics, University of Connecticut, Storrs, CT

Dr. Kristin Shrader-Frechette , O'Neil Professor of Philosophy, Department of Biological Sciences and Philosophy Department , University of Notre Dame, Notre Dame,

IN

Dr. V. Kerry Smith , W.P. Carey Professor of Economi cs , Department of Economics , W.P Carey School of Business , Ariz ona State University, Tempe, AZ

Dr. Thomas L. Theis , Director, Institute for Environmental Science and Policy, University of Illinois at Chicago, Chicago, IL

Dr. Valerie Thomas , Anderson Interface Associate Professor, School of Industrial and

viiiSystems Engineering, Georgia Inst itute of Technology, Atlanta, GA

Dr. Barton H. (Buzz) Thompson, Jr. , Robert E. Paradise Professor of Natural

Resources Law at the Stanford Law School and Perry L. McCarty Director, Woods Institute for the Environment, St anford University, Stanford, CA

Dr. Robert Twiss , Professor Emeritus, University of California-Berkeley, Ross, CA

Dr. Thomas S. Wallsten , Professor and Chair, Department of Psychology, University of Maryland, College Park, MD

Dr. Lauren Zeise , Chief, Reproductive and Cancer Hazard Assessment Branch, Office of Environmental Health Hazard Assessment, Californi a Environmental Protection Agency, Oakland, CA

SCIENCE ADVISORY BOARD STAFF

Mr. Thomas Miller , Designated Federal Officer, E nvironmental Protection Agency, Washington, D.C.

ixx NOTICE

This report has been written as part of the activities of the EPA Science Advisory Board (SAB), a public advisory committee providing extramural scientific information and

advice to the EPA Administra tor and other officials of the Environmental Protection Agency. The SAB is structured to provide balanced, expert asse ssment of scientific matters related to problems facing the Agenc y. This report does not reflect the policies and views of the EPA nor of other agencies in the Executive Branch of the federal government. Mention of trade names or commercial products do not constitute a recommendation for use. Reports of EPA SAB are posted at http://www.epa.gov/sab

.Enclosure

Advisory on EPA’s Guidelines for Preparing Economic Analyses by the Science Advisory Board Environmental Economics Advisory Committee

Executive Summary .................................................................................................... ES-1 Crosscutting Issues ............................................................................................................ 1 Question 1: Policy Options ............................................................................................. 5 Question 2: Baselines ...................................................................................................... 9 Question 3: Discounting ............................................................................................... 11 Question 4: Benefits ...................................................................................................... 15 Question 5: Mortality Risk Valuation ......................................................................... 20 Question 6: Social Costs ............................................................................................... 22 Question 7: CGE Models .............................................................................................. 24 Question 8: Distributional Analyses ............................................................................ 26 Question 10: Economic Literature ................................................................................ 28 Question 11: Omissions .................................................................................................. 29 Appendix: Compilation of Line by Line Comments from Individual Members ..... 30

References ........................................................................................................................ 41Executive Summary

The goal of EPA’s Guidelines for Preparing Economic Analyses is to establish a sound scientific framework for performing economic analyses of environmental regulations and policies. Or iginally issued in 2000, the Guidelines are intended to reflect Agency policy and guide Agency practice on the preparation of economic analyses. EPA’s National Center for Environmental Economics recently updated the Guidelines (September 2008) and asked the Science Advisory Board for its input. The SAB Environmental Economics Committee (EEAC) met on October 23-24, 2008 to address the Agency’s charge questions on the Guidelines . The Background section of this report discusses some crosscutting issues. Below we provide specific responses to each charge question.

1. Do the published economic theory and empiri cal literature support the statements in the guidance document on the merits and limitat ions of the differ ent regulatory and non-regulatory approaches discussed in C hapter 4: Regulatory and Non-Regulatory Approaches to Pollution Control?

Yes, the chapter is supported by econom ic literature; howev er it too closely mimics textbook expositions of environmental economics. In order to make it more useful for EPA analysts, we reco mmend that EPA clarify and discuss the specific role that EPA has in policy design and implementation and provide guidance for economic analysis done specifica lly within that context. We also

recommend a better distinction between efficiency and cost-effectiveness, improvements to the discussion of “cap a nd trade,” a better definition of design standards and technology based performance standards and the inclusion of recent literature on voluntary approaches and th e observability of information.

2. Do the published economic theory and empiri cal literature support the statements in the guidance document on the consideration of the baseline discussed in Chapter 5: Establishing a Baseline?

Yes, this chapter provides very comprehe nsive guiding principles for specifying

the baseline scenario to iden tify the incremental benefits and costs associated with a policy. We recommend that EPA consid er the key dimensions of the economic analysis and any phenomena in the baseline about which there is uncertainty and to construct two or three (rather th an more) scenarios that can provide benchmarks for policy analysis.

3. Do the published economic theory and empiri cal literature support the statements in the guidance document on the trea tment of discounting benefits and costs discussed in Chapter 6: Discounting Future Benefits and Costs in the following circumstances:

a. Are the descriptions of fundamenta l social discounting approaches, conceptual conclusions and reco mmendations consistent with the appropriate economic literature on soci al discounting? Are the correct

ES-1conclusions drawn from the respec tive literatures on discounting for public projects (government spendi ng) and discounting for regulations (government-mandated spending)?

Yes, the descriptions of funda mental discounting approaches, conceptual conclusions and recomm endations are consistent with the appropriate economics literature . We do not believe there are significant differences in the a pproach to discounting for public projects (government spending) and discounting for regulations (government mandated spending). We suggest that the chapter should begin with acknowledgment of the many controversies and complications associated with di scounting and orient readers to where in the chapter these are discussed.

b. The Guidelines do not draw a firm conclusion on the extent to which shadow price of capital adjustments ar e likely to be necessary for most EPA policy analyses. The issue depends gr eatly on the elasticity of capital supply and EPA plans to pursue additional research on this issue, as noted in the draft Guidelines. Does EPA’s conclusion reflect the sense of the literature or can a firmer conclusion be drawn? Does the Committee have suggestions regarding situations where these adjustments would be necessary or unnecessary?

Yes, the EPA conclusion does reflect the sense of the literature. As noted in the chapter, the shadow -price of capital approach is theoretically correct, but the quantita tive significance of adjusting for this shadow price is critically dependent on the extent to which EPA regulations displace other i nvestment. In an economy that is open to foreign investment, there may be minimal displacement and so adjustment for the shadow price of investment is negligible. We are pleased to learn that EPA is investigating the elasticity of investment to environmental regulation.

c. While EPA concludes that a rate of 3% is generally consistent with estimates from low-risk government securities, the Agency would like to more firmly establish a rigorous basis for a consumption-based rate. What data and methods would the committee suggest EPA pursue?

We are unable to suggest better da ta or methods for estimating a consumption-based discount rate , and doubt that alternative credible estimates would differ dramatically from the 3% real rate specified by OMB in Circular A-4. Given the benefits of harmonization of parameter values among federal agencies, we do not encourage EPA to move away from this rate.

ES-2d. Chapter 6 recommends adopting an approach to long term discounting based on the work of Newell & Pizer (2003). While EPA recognizes that data may not clearly support a particu lar statistical model over other alternatives (e.g., random walk vs. mean-reverting), the Chapter

concludes that the recommended approach is an improvement over constant discounting. Does the committee believe this is a reasonable conclusion from the economics litera ture? More specifically, is the

recommendation to use a random walk model as a default reasonable given the state of the literature?

No, we believe that calculating pr esent values using the Newell & Pizer approach can be used as one of several alternatives (complemented by appropriate cav eats and discussion of the theoretical and empirical issues), but we do not believe it should be relied upon exclusively for reasons provided in the Advisory.

e. EPA has struggled with the question of the length of time an analysis should capture and has arrived at so me practical recommendations (see Section 6.1.6.3 and 6.4). Are these recommendations consistent with good economic practices? Does the committee have additional recommendations or insights on this subject?

Yes, the recommendations are ge nerally consistent with good practice. In considering the time horizon an analysis should cover, there is no general answer beyond the answer to the question of what consequences to include: t hose that may have a quantitatively significant effect on the c onclusions of analysis.

4. Do the published economic theory and empiri cal literature support the statements in Chapter 7: Analyzing Benefits on the mer its and limitations of different valuation approaches for the measurement of social be nefits from reductions in human health risks and improvements in ecological c onditions attributable to environmental policies?

This chapter provides good coverage of th e main categories of benefits and the

methods used for their estimation. Howeve r, it fails to capture a significant

amount of recent literature on recreation demand models, combining revealed and stated preference, validity and reliabi lity, valuing mortality and morbidity and ecosystem services. In particular, we urge the Agency to vastly expand its guidance on characterizing and valuing non-monetized ecosystem systems and services. We also recommend expanding the discussion of evaluating studies and

data.

5. Chapter 7 includes a brief discussion of the Agency’s current approach to mortality risk valuation with more details provided in Appendix B. These sections will be updated when the Agency concludes its effo rts to update its mortal ity risk valuation

ES-3approach. In the interim, are the discussions provided in Chapter 7 and Appendix B

clear and balanced?

We will refrain from detailed comments on EPA’s approach to valuing mortality risk until the Agency’s update is comple te. In the interim, we recommend EPA consider expanding its litera ture review and discontinue use of old, discredited wage-risk studies.

6. Does Chapter 8: Analyzing Costs contai n an objective and reasonable presentation of the published economic theory, empirical lit erature, and analytic tools associated with estimating social costs?

Yes. As a suggestion for improvement, we recommend covering non-competitive markets where results can be significantly different. Our detailed comments offer suggestions for other revisions, such as examining three cases: single market analyses, multiple market analyses and general equilibrium analyses.

7. Does Chapter 8 contain an objective, balan ced and reasonable presentation of the published economic theory, empi rical literature, and analytic tools associated with computable general equilibrium (CGE) models? Is the description of the relevance of these models for economic analyses performed by the EPA reasonable?

Yes. We recommend discussion of the pa rameterization of CGE models as well

as a few minor revisions as discus sed in our detailed comments.

8. Does Chapter 9: Distributional Analyses : Economic Impact Analyses and Equity Assessment contain an objective and reasonabl e presentation of the measurement of economic impacts, including approaches suitable to estimate impacts of environmental regulations on the private se ctor, public sector and households? This discussion includes, for example, the meas urement of changes in market prices, profits, facility closure and bankruptcy rates, employment, market structure, innovation and economic growth, regi onal economies, and foreign trade.

Yes, this chapter contains an objective presentation of many aspects of economic impact analyses. In our detailed comments, we offer suggestions for minor improvements.

9. Does Chapter 9 contain a reasonable pres entation and set of recommendations on the selection of economic vari ables and data sources used to measure the equity dimensions identified as poten tially relevant to envir onmental policy analysis?

Yes, the main items in assessment equity issues are correctly identified. One

limitation is that the main distributional i ssues discussed in the chapter relate to costs, not benefits. Although it may be more difficult to identify the distribution of benefits, it would seem appropriate to at least represent the ideal case as one in which the equity and impacts associat ed with both benefits and costs are

ES-4ES-5 considered. We suggest that EPA consider creation of a website to catalog all the

data sources.

10. Appendix A: Economic Theory was prepared for those readers who wished to have a better understanding of the economic foundatio ns underlying benefit cost analyses. Does Appendix A summarize the relevant literature in an objective and meaningful way? Are there topics that warrant (mor e) discussion in this appendix that were

otherwise missed?

The Appendix provides a good discussion of core economic principles. As suggestions for improvements, we reco mmend distinguishing between stock and flow pollutants and inclusion of the concept of “user costs.”

11. Please identify and enumerate any inconsistencies you may find across chapters and other issues/topics on which we should pr ovide further elaboration. Also, please identify any definitions provided in the ne w glossary that are inaccurate or that

otherwise need revision.

In general, we would like to see broade r discussion of a number of cross-cutting issues. For example, we’d like to see a di scussion of the need for transparency in making assumptions and judgments and a di scussion of the ways in which biases

and errors will matter the most. The Guidelines should more frankly acknowledge the “second best” world of most environmental policy problems due to information constraints, political cons traints, imperfect competition and market distortions created by taxes and other government policies. The Guidelines sorely need case studies and examples to illustr ate and make concepts concrete. We underscore our recommendation to provide guidance to analysts for exploring a range of ecological indicators and conceptual models of ecosystems and services.Background

EPA’s National Center for Environmental Economics (NCEE) oversees the Agency’s economic analysis of environm ental issues. NCEE guides research and development on economic methods, produces EPA’s major economic reports and issues guidance for performing economic analysis at the Agency. In this later role, NCEE

issued Guidelines for Performing Economic Analysis in 2000. These Guidelines are meant to provide guidance on economic analys is for those performing or using such analysis, including policy makers , analysts and contractors providing economic reports to the EPA. In 2008, NCEE updated the Guidelines to incorporate the most recent advances

in environmental economics and asked that th e SAB EEAC review the revised document.

The SAB EEAC met on Octobe r 23 – 24, 2008 to review draft Guidelines (September 2008) and respond to NCEE’s specific charge qu estions. This face-to-face meeting was followed by a public teleconference on March 4, 2009 to discuss and amend a preliminary draft Advisory. On August 6, 2009, the SAB provided a qua lity review in a public teleconference.

In addition to offering specific responses to charge questions, this Advisory also presents some general advice and cross-cut ting recommendations. We first identify and discuss these cross-cutting issues below and then proceed to the specific charge questions.

Crosscutting Issues

In general, EEAC would like to see more upfront discussion of the “whys”

associated with the material in the Guidelines , perhaps in the form of a conceptual overview chapter. It would be useful to expl ain why a benefit-cost an alysis is a valuable undertaking (other than to satisfy a regulat ion) and why economic impact and equity analyses can be important supplements to benef it-cost analysis, etc. Readers need to see a definition of economic efficiency (allo cative and technical, which will help in explaining the relationship between cost effec tiveness and benefit-co st analysis) and an explanation of the re lationship between economic efficien cy, benefit-cost analysis, and cost-effectiveness. We also suggest defining social costs and benef its (as distinct from private costs/benefits), with examples.

In addition to introducing these basic concepts, EEAC would like to see discussion of a number of cross-cutting i ssues. Environmental policy analysis is inherently an integrated assessment process in which results from different sciences are combined to predict environmental outco mes and their economic consequences. Realistically, a great deal of judgment will ha ve to be exercised by analysts. Given this,

the Guidelines should discuss the need for transparency in making assumptions and judgments and the ways in which biases and errors will matter the most. For example, if all benefits and costs are understated by about the same amount, the “answer” of whether the benefits exceed the costs will not likely change, however if the costs are biased up and the benefits biased down, the wrong effici ency message could be sent. Care should also be taken to avoid multiple counting of benefits and costs when there are overlapping

1regulatory initiatives. Clarity and transparency in the spec ification of the baseline, including the regulatory initiatives alrea dy in place, will enable more accurate identification of the incremental effects of a regulatory initiative.

The Guidelines should not underemphasize the value of economic analysis for deregulatory and/or non regulatory purposes. The statement in the Guidelines that “formal economic analysis is not required fo r the selection and implementation of a nonregulatory approach,” is true and probably an important point to make. However, the statement could also suggest that economic analys is is less valuable or informative in this case. It is not. Non-regulatory approaches can bring both sizeable costs and benefits and the same can be said for deregulatory decisions. The Guidelines should indicate that decisions to deregulate or adopt a non-regulat ory approach can be as much informed by economic analysis as those that ar e purely regulatory in nature.

We recommend that the Guidelines incorporate the concept of ecosystem services and its various components, as outlined in the Millennium Ecosystem Assessment (MA) Synthesis Report (2005) and highlight the issue of properly valuing and characterizing ecological systems and services in a benef it-cost analysis. Alt hough OMB Circular A-4 does not require that all economic benefits of a policy be monetized, it does require some

scientific characterization of t hose contributions. Users of the Guidelines should be warned that an inappropriate focus only on impacts that can be monetized can provide misleading policy guidance (as with other case s of unbalanced information). In addition, a strong recommendation should be made to provide quantita tive measures of ecological impacts and a qualitative characterization of eco logical effects. We urge EPA to consider the SAB’s recent recommendation to begin with a conceptual model of the relevant ecosystem and ecosystem services and map those effects to services or attributes that the public values ( Valuing the Protection of Ec ological Systems and Services , 2009). The SAB report covers a wide range of alterna tive methods for characterizing, valuing and gauging ecological impacts. We urge EPA to evaluate and determine the appropriate use of these alternative methods and provide much more guidance on characterizing nonmonetized effects.

We understand that EPA is developing a separate chapter dedicated entirely to uncertainty (which we applaud), but the topic is important enough to merit some discussion in the conceptual overview or as a cross cutting issue th roughout. It would be useful to point out that uncertainty extends not only to economic information, but to environmental data and modeling. Uncertain ty in environmental modeling can be as much or more a source of errors than impe rfections in economic assumptions and data. In addition, analysts will be confronted with heterogeneity of data for various reasons (geographic, economic, cultural etc). Recognizing the sources of heterogeneity and deciding how to address them are major analytic decisions. Given th at analysts usually face asymmetric information (e.g. on costs vis-à-vis benefits), advice is needed on how to

address these information deficiencies. The Guidelines might discuss th e possibility of ensemble modeling (e.g. hydrology and ecology) and the use of a “w eight of evidence” approach, especially for the case of non-monetized ecological effects.

2The literature on environmental policy increasingly emphasizes that realizable outcomes will be “second best” due to information constraints, political constraints, imperfect competition, and market distortions created by tax and other government interventions. This emphasis is not adequately reflected in the Guidelines . For example, the theory section focuses on first-best optimal regulation, a framework that provides a

baseline but is of limited relevance to regulation of contemporary environmental problems. For example, agricultural nonpoint pollution is now the l eading cause of the nation’s water quality problems, yet it is le ss observable than emissions from points sources and far more stochastic. Conseque ntly, the emissions based policies emphasized

in the Guidelines are irrelevant inasmuch as they are targeted to conventional point sources. Agriculture is subject to multiple non-environmental policy distortions that must

be considered in the measurement of the social benefits and costs of regulating agriculture. Further, agriculture is a source of multiple externalities, some that are positive, some that are negative, that are regul ated to varying degree (including not at all) by multiple authorities. The Guidelines should be more adapted to the complexities of contemporary environmental problems.

Given that economics needs to apply to economic analysis, we believe some

discussion should be devoted to the allocati on of EPA resources in undertaking economic analyses. Where possible, the Agency should consider tailoring the resources spent on the analysis with the size of the proposed regul ation’s impact. Analysis of the costs of a small project may emphasize simple partial eq uilibrium analysis, while a larger one may employ both partial equilibrium and CGE models . Similarly, the se lection of the number and identity, of say, products or markets to be included in an analysis should consider the benefits and costs from the adding each indi vidual market or product. The evaluation of a large project may justify conducting a new study on willingness to pay (WTP) for the amenities it provides if such information ha s the potential to change the regulatory decision while a study on the impacts of a sma ller project may rely on a benefit transfer analysis if the regulatory impacts are expected to be small. For large regulations with significant impacts, the costs of analysis ma y be trivial in comparison to potential

increases in net benefits if the information re sults in a change to the final regulation or policy decision.

The Guidelines should discuss the analytic challenges posed by emerging environmental problems, partic ularly climate change. The Guidelines are implicitly focused on conventional point source pollutants. Attention to emerging challenges from nonpoint pollutants, changes in carbon and other biogeochemical pr ocesses, invasive species, etc. would give the Guidelines a more contemporary and forward looking view.

The Guidelines should point out (and perhaps demonstr ate) that the analysis needed for policy decisions to address greenhouse gas emissions will necessarily draw from a complex interdisciplinary suite of studies, data and models. A case in point is the Congressional requirement in the Energy Independence and Security Act of 2007 for

EPA to issue a Renewable Fuel Standard base d on its calculation of lifecycle greenhouse gas emissions for various fuels. This lifecycl e analysis covers the full fuel lifecycle from production to consumption and hence requires an extraordinary synthesis of tools and information from the bio-physical sciences , economics and atmospheric modeling. The

3Guidelines could reference this specific exam ple as well as discuss generally the interdisciplinary challenges posed by climat e change and other global issues. Given the specter of climate change and other global proc esses, we expect that future revisions of

the Guidelines will need to be broader, describing a kind of regulatory analysis that draws

from all the sciences. We note that revisi ons will be made easier with NCEE’s adoption of a loose leaf format to update chapters as appropriate.

4Question 1: Policy Options

Do the published economic theory and empirical literature support the statements in the guidance document on the merits and limitati ons of the differen t regulatory and nonregulatory approaches discussed in C hapter 4: Regulatory and Non-Regulatory Approaches to Pollution Control?

With a few exceptions, the presentation in Chapter 4 is supported by economic theory and empirical evidence in the publishe d literature. We commend the Agency on a good chapter and offer the suggestions below for improvement.

This chapter provides a good description of policy instruments, much in the same way that a good environmental economics text might. In this regard, we suggest that EPA clarify and discuss the specific ro le that EPA has in policy design and implementation. For example, the Guidelines point out the efficiencies that can accrue with performance-based standards, but do not tell the reader that EP A often does not have the discretion to choose this option, e.g. wh en “best available t echnology” standards are required by law. Similarly, after demonstra ting that social welfare is maximized by choosing the level of pollution that equates ma rginal costs with marginal benefits, the

Guidelines do not inform the reader that EPA is often explicitly prevented from setting standards by this criterion.

We suggest that EPA clarify and discuss the Agency’s specific role in policy design and implementation. This would invol ve stating where EPA has discretion to make decisions in the context of the larger policy arena and then di scussing the rationale for the different approaches act ually used. That is, EPA prim arily issues regulations and those regulations are typically highly prescribed by Congres sional mandates as well as the courts' interpretation of environmental laws. On the other hand, EPA analysis can inform the design of future environmental programs by Congress so it is important to

retain the discussion of the full suite of policy options describe d here, but clarifying EPA’s discretion in setting polic y (even if it varies from st atute to statute) would be beneficial. To this end, we recommend that the chapter be organized in two parts: (1) standard treatment of policy options similar to what is currently covered in the Guidelines and (2) discussion of EPA’s actual discretion highlighting how economic analysis is used

in this narrower context. This would take the chapter beyond the us ual treatment of an

environmental economics text and make it dire ctly relevant to the agency. One way to explain EPA’s role is to show some exam ples of specific actions (e.g. how design or performance standards are set and/or EPA’s role in voluntary programs).

Another topic that would be well suited fo r discussion in this chapter is the issue of asymmetric information between the re gulator (EPA) and the regulated (consumers and industry). This issue has ramifications fo r the design and efficien cy of many kinds of environmental regulations and its importance should be mentioned.

Along these same lines, the chapter disc usses maximizing welfare without noting

5that in most cases EPA is charged with impl ementing laws that specify criteria EPA must use. EPA’s regulations are not typically based on a calcula tion of an “optimal” E*, but are more tied to legally-defined criteria . Again, the chapter would be improved by clarifying how EPA’s actual authorit y fits into this paradigm.

This latter point could be nicely integrated into Section 4-1 which could be improved by distinguishing efficiency from co st effectiveness. By dividing the section into two parts: (i) Efficien t Level of Pollution (MD = MAC aggregate ) ∗ and (ii) CostEffective Allocation of Pollution – equa lize marginal cost across sources (MAC 1 = MAC 2 = ... = MAC

n ), the distinction between optimality of pollution levels and least cost approaches for implementation can be disti nguished. Each section will need a supporting graph and should be integr ated by showing how aggregate MAC is derived from

individual MACs. See Field and Field (2008) and Baumol a nd Oates (1988) for dividing the discussion this way. Also, in the discussi on of the efficient le vel of pollution, it is important to define social welfare usi ng the underpinnings of Pareto Optimality.

The suggestion in the previous paragra ph will allow the use a cost-effectiveness graph to tell the cap and trade story demonstrating its property as a least-cost instrument. Likewise, instead of telling the cap and trade story assuming an optimal level of aggregate pollution for permit allocations, tell th e story from the standpoint that a cap and

trade can achieve any aggregate level of emissions at least cost. Then, point out that the efficient solution is a special case where th e permit allocation is efficient (MD=MAC). Use the same approach for the tax in Secti on 4.3.2. Again, these points can be illustrated with the point that EPA typically does not se t the optimal level of emissions, but can help design and implement instruments to achieve l east cost solutions. This discussion can be linked to the asymmetric information issues mentioned earlier by noting that the least cost solution can be achieved, even if th e regulator knows nothing about the individual

firm costs.

The discussion in Section 4-2 should be clear about the difference between design standards (technology forcing) and technology based performance standards. This could be accomplished by dividing Section 4-2 by (i ) design standards and (ii) performance standards and discussing uniform and technol ogy-based performance standards using the cost-effectiveness graph intr oduced in the previous sect ion. Uniform standards are generally not cost effective but have a low information burden (since one need not know MACs). Technology-based performance standard s can be cost effective in principle but have a high information burden (need to know MACs). Regardless of the form of standard, it is always importa nt to recognize that different options may yield different levels of environmental improvement which need to be adequately accounted for in analysis that compares design with performance standards.

We recommend the section on taxes include some discussion of what is taxed: the pollutant, an input, a process, or something el sewhere? In principl e it should be placed on damages (a true Pigouvian tax), but admi nistrative and monitoring costs may suggest targeting the tax elsewhere. Taxing gas may be much easier and probably as effective as

∗ MD = marginal damages. MA C = marginal abatement cost

6taxing damages from auto emissions. Simila r principles apply to permit trading, so although EPA lacks the legal authority to levy a tax, a discussion of targeting would have broad application.

On this point more generally, note that policy design is dependent on observable and available information. For example if pol icy makers can not obs erve actual pollution levels, but inputs and practices that cause pollution can be observed and there are reasonable estimates on the relationship be tween the input, te chnology use and the pollution level, then taxes or regulations may be based on the imputed pollution levels. Policies should be designed to best take advantage of the available knowledge. In particular identifying sources of heterogeneity among users and knowing how they affect pollution levels can be central to polic y design. The proliferation of geographic information systems and remote systems to obtain data provide new opportunities for policy design. Studies suggest that there is a significant efficiency gains from policies that adjust to observed hetero geneity relative to uniform po licies (Xabadia et. al., 2008). Availability of new sources of or means to obtain information may lead to redesign of policies – for example, availability of a technology that allows cheap monitoring of pollution may lead to regulation on taxati on based on annual pollution rather than imputed pollution. Policy makers should r eassess policy design and implementation as technology progresses. (See Xaba dia et. al., 2008) as one example. There are many other papers that demonstrate the efficien cy gains from increased targeting.

As noted in the cross cutting issues discussion earlier, we suggest adding discussion of second best solutions covering imperfect markets, pre-existing policies, asymmetric information, and so forth. In this chapter, EPA could incorporate the implications of imperfect markets and other se cond best solutions in the relevant sections

and refer readers to the material in the cro ss cutting issues discussion. Examples include monopoly, price supports in agriculture, pr e-existing environmental policy, recent biofuels legislation, etc.

When the section on market based regulations is introduced, it would be helpful to explain that these controls tend to be l east costly, have a low information burden on regulators, provide incentives for technological advancement, and so forth. Monitoring

and enforcement costs and other administra tive costs, of course , can favor direct regulation.

It would be helpful to men tion that information disclosure strategies can allow the market to create incentives for pollution c ontrol (following Coase) with the victims directly signaling their preferen ces to firms. But these are mo st likely to work when there are contractual obligations between po lluting firms and affected parties (e.g. consumers/workers) and more difficult to wo rk when they affect third parties (see Tietenberg, 1998). Also it shoul d be mentioned that credibility of information is important. Information disclosure can lead to inefficient outcomes when information is not credible (see Brouhle, K. and M. Khanna, 2007).

The section on subsidies should mention that many subsidies in existence, such as

7those in agriculture, car manu facturing, oil and gas, forest ry, and so forth, are not corrective subsidies designed to correct external ities and may in fact worsen externalities.

This could also be discussed in the second best discussion.

An area of omission is the relatively new literature regarding the effectiveness (or lack there of) of voluntary approaches ( Morgenstern and Pizer, 2007 and National Research Council, 2002, as well as a number of journal articl es). These should be noted and made a part of the section on voluntary c ontrols. Assessment of the effectiveness of a voluntary program in the literature has been based on estimates of participation rates and the reduction in pollution achieved by the pr ogram relative to that in the absence of the program. A comparison of the costs of pollution control under a voluntary program

relative to that under alternative policy options to achie ve the same level of pollution

control would be valuable fo r assessing the cost-effectiven ess of voluntary approaches.

8Question 2: Baselines

Do the published economic theory and empiri cal literature support statements in the guidance document on the consideration of the baseline discussed in Chapter 5: Establishing a Baseline?

Yes, the approach described in the Guidelines to establish a baseline is supported by economic theory and empirical literature in this area. This ch apter provides very comprehensive guiding principles for specifyi ng the baseline scenario to identify the

incremental benefits and cost s associated with a policy. It describes the methods for defining a scenario that does not include the policy (baseline scenario) and one that does include the policy; that is, a ‘with’ and ‘without’ policy comp arison. It suggests that in some cases it may be appropriate to specify multiple baseline scenarios to describe the

state of the world in the ab sence of a regulation. While we agree with the need to

consider more than one baseline when it is difficult to define a unique state of the world in the absence of the policy with a high degree of certain ty, the number of baselines

constructed should be limited to as few as possible that cover the reasonable baseline alternatives. In some cases it may also be a ppropriate to use probabi listic analysis with a continuum of baselines to provide the benchmark for policy analysis.

Additionally, in defining the baseline scenario, analysts need to consider which

sectors should be included. A lthough the direct effects of the policy may be focused on a few sectors, indirect impacts can be significant and should be measured. It is therefore important to establish which other sectors of the economy may be affected, directly or indirectly, by a policy and should be include d in the baseline. Some policies can have pecuniary effects that will affect the opportuni ty costs of implemen ting that policy. This is particularly relevant when the pecuniary costs occur in inefficient markets; in such cases the opportunity costs of a policy can differ from the monetary costs of the policy (see Boardman et al., 2006).

The assumption of full compliance w ith the existing and newly enacted regulations does not appear r ealistic. Instead, compliance ra tes in the baseline should be

based on available factual evid ence. Assumptions about co mpliance rates in the policy

scenario should also be based on a realistic assessment. These rates are likely to depend on how stringently the policy is implemented and enforced.

We also suggest including a text box di stinguishing the indu ced innovation effects of regulation from the Porter Hypothesis. It would be useful to clarify what the Porter hypothesis is (i.e., define it) and to distingu ish between its strong form and weak form. The strong form of the Porter Hypothesis st ates that regulations can induce innovations that can lead to cost savings that are la rger than the costs of the innovation and compliance. The weak form of the Porter H ypothesis simply states that environmental regulations lead to innovati on. We agree with the statement that there is only limited evidence of the strong version of the Porter Hy pothesis; some referenc es to the literature providing situations in whic h it might hold (such as in the presence of imperfect information, high search costs, etc.) could be added. There is much more evidence to

9support the weak form of th e Porter Hypothesis (which is similar to the induced innovation hypothesis) and this should be made clear.

10Question 3: Discounting

Do the published economic theory and empirical literature support the statements in the guidance document on the treatment of disc ounting benefits and costs discussed in Chapter 6: Discounting Future Benefits and Cost s? (sub parts for this charge are copied below)

Overall, the chapter provides a cl ear and comprehensive discussion of discounting. This chapter has been updated to reflect much of the current thinking on discounting in the context of environmenta l decision making and we applaud EPA for doing so. We begin with some general comments then respond to each of the subparts of the charge question below.

Discounting is an important, complicated, a nd controversial topic. The results of an economic evaluation can be extremely sensitive to the discounting approach that is used, especially for projects where significant benefits and costs are incurred at widely disparate times (e.g., climate change mitigation; nuclear-and hazardous-waste storage). We suggest that the chapter begin with an acknowledgement of these issues and orient readers to the parts of the chapter in which th ey are discussed. (At present, readers must wade through the necessary but less interesting section on mechanics of discounting before grappling with these topics). Some of the issues that could be highlighted include: (a) differences between relatively short r un (“intra-generational” ) and long run (“intergenerational”) discounting that arise in pa rt because inter-generational contexts necessarily involve a greate r distributional aspect and future generations are not represented in markets; (b) se nsitivity of results to choi ce of discounting approach and discount rate; (c) distinction (and frequent confounding) of e fficiency and distributional issues; (d) distinction between utility vs. c onsumption discount rate s; (e) “ethical” or prescriptive vs. descriptive approaches to selecting a discounting approach; (f) uncertainty about future economic growth and other conditions; (g) constant vs. nonconstant (e.g., hyperbolic) disc ounting approaches; and (perhaps) (g) future changes in relative prices that imply different cons umption discount rates for different goods.

Although it is implicit in the text, the di stinction between di scounting to reflect differences in timing of consequences and di scounting to adjust fo r inflation should be emphasized. It is conventional (and recommended) to measure effects in real dollars and

use a real rather than nominal discount rate to account for differences in timing. (Note

that if inflation rates differ across goods, the real discount ra te depends on the inflation adjuster that is used.)

There is much confusion in the literat ure (and in policy di scussion) about the determinants of the discount rate, e.g., wh ether it is a result of preferences for consumption sooner rather than later or of th e productivity of capital investment. At least for “intra-generational” discount ing, the (consumption) discount rate (or rates) is best understood as being determined by a price (or prices) – the interest rate(s) at which consumption can be shifted through time (e .g., consumers may shift consumption to the future by consuming less and investing more, and may shift consumption toward the

11present by saving less or borrowing). The interest rate is determined, like other prices, as a market equilibrium between agents who wish to shift resources through time. Consumers adjust current and future consump tion so that their indifference curves for current and future consumption are tangent to the market oppor tunities for shifting consumption through time (determined by the inte rest rate). As noted in the chapter, a variety of interest rates exist (associated w ith riskiness of investment and time horizon) and there are wedges between private returns associated with taxation of investment

returns and other factors. For longer-term “inter-generational” issues, the interpretation of the discount rate as a price is less natural, because market inte rest rates for periods longer than about 30 years rarely exist and future generations’ do not dire ctly participate in current markets, so their preferences may not be adequately represented.

In the discounting chapter or elsewhere, it may be useful to highlight the distinction between positive (i.e., descri ptive) and normative perspectives (i.e., prescriptive) justifications for economic evaluation and the tension between these.

Economic evaluation is normative in that it is conducted in order to compare alternative policies, yet it is positive in that it attemp ts to identify the policy that maximizes the perceived welfare of the affected population. Behavior that differs from Economic evaluation is sometimes justified as identifying policies to maximize (or at least increase) social welfare, which is normative because it is based on an assumed social welfare function. In contrast, economi c evaluation is also someti mes justified as identifying policies that produce potential Pa reto improvements, i.e., poli cies such that all members of the affected population would prefer to the alternative policy (if combined with appropriate compensation payments). Policie s that increase social welfare are not necessarily potential Pareto improvements, that those that are potential Pareto improvements need not increase social welfar e. Moreover, individua l behavior that is

inconsistent with maximization of individual utility (e.g., behavior that is dynamically inconsistent, perhaps because it accords with hyperbolic discounti ng) creates a tension between these perspectives and raises quest ions about how to conduct the analysis. See Hammitt (2009, 2002) and Portney (1992).

a. Are the descriptions of fundamental so cial discounting approaches, conceptual

conclusions and recommendations consistent with the appropria te economic literature on social discounting? Are the co rrect conclusions drawn from the respective literatures on discounting for public project s (government spending) and discounting for regulations (government-mandated spending)?

The descriptions of fundamental soci al discounting approaches, conceptual

conclusions and recommendations are consis tent with the appropriate economics

literature. We do not believe there are si gnificant differences in the approach to discounting for public projects (government spending) and discounting for regulations (government-mandated spending) – in both cas es, there can be a need to account for differences in timing of benefits and costs a nd the relevant conceptual basis is social valuation of consequences at different points in time.

12b. The Guidelines do not draw a firm conc lusion on the extent to which shadow price of capital adjustments are likely to be necessary for most EPA policy analyses. The issue depends greatly on the elasticity of capital supply and EPA plans to pursue additional research on this issue, as noted in the draft Guidelines. Does EPA’s conclusion reflect the sense of the literature or can a firmer conclusion be drawn? Does the Committee have suggestions regarding situ ations where these ad justments would be necessary or unnecessary?

As noted in the chapter, the shadow-pri ce of capital approach is viewed as theoretically correct, but the quantitative signif icance of adjusting for this shadow price is critically dependent on the extent to which EPA regulations displace other investment. In an economy that is open to foreign investme nt, there may be minimal displacement and so adjustment for the shadow price of invest ment is negligible. We are pleased to learn that EPA is investigating the elasticity of investment to environmental regulation.

c. While EPA concludes that a rate of 3% is generally consistent with estimates from low-risk government securities, the Agency w ould like to more firmly establish a rigorous basis for a consumption-based rate. W hat data and methods would the committee suggest EPA pursue?

We are unable to suggest better data ormethods for estimating a consumptionbased discount rate, and doubt that alte rnative credible estimates would differ dramatically from the 3% rate specified by OMB in Circular A-4. Gi ven the benefits of harmonization of parameter values among fede ral agencies, we do not encourage EPA to move away from this rate.

d. Chapter 6 recommends adopting an approac h to long term discounting based on the work of Newell & Pizer (2003). Whil e EPA recognizes that data may not clearly support a particular statistical model over other alternatives (e.g., random walk vs. mean-reverting), the Chapter conclude s that the recommended approach is an improvement over constant discounting. Does the committee believe this is a reasonable conclusion from the economics literature? More specifically, is the recommendation to use a random walk model as a default reas onable given the state of the literature?

We do not recommend using the Newell and Pizer approach as a default but as one of the alternatives for inter-generati onal discounting. Since the declining discount rates under this approach ar e sensitive to modeling assump tions, transparency in the assumptions underlying the determination of the discount rates used wi ll be important as will comparisons with other alternatives.

The conceptual idea, identified by Weitzman (1998, 2001), should be clearly stated in the chapter: uncertainty about th e appropriate discount rate to use has a

nonlinear effect on the discount factor that varies with the time horizon. Specifically, because the discount factor for time t, [1/(1 + r)] t , is a nonlinear function of the discount rate r, the expected disco unt factor is not equal to the discount factor obtained by substituting the expected value of r in this formula. For small t, the difference between

13the two discount factors may be small, but as t becomes arbitraril y large the expected discount factor approaches the discount factor correspond ing to the minimum possible value of r weighted by the probability a ssigned to that minimum value. Weitzman developed a distribution fo r r by polling economists and derived a corresponding schedule of certainty-equivalen t discount rates (the discount rate associated with the expected discount factor); Ne well and Pizer built on his wo rk by conducting an empirical analysis of historical intere st rates. Their results are na turally sensitive to modeling choices about the intertempor al correlation of rates.

Our concern about this approach is the following. In a world with no uncertainty about the discount rate, one can compare str eams of consequences in terms of their present values or their future values at any future date. Th e choice between these perspectives has no effect on th e ranking: because the present value of a policy is simply the present value of the policy’s future valu e (i.e., the future va lue discounted to the present), whichever policy has the larger presen t value will also have the larger future

value.

In contrast, when the discount rate is uncertain, the rank ordering of policies by present values and future value may differ. As shown by Weitzman, for large t the present value is dominated by the small discount rates. But the future value is dominated by the large discount rates (i.e., the expected value of the factor used to convert present consequences to their future value, (1 + r) t , is dominated by the larg est possible values of r). This dependence of the ev aluation on what appears to be an arbitrary choice of perspective suggests a problem with the analysis that urges caution in its application and invites further investigat ion (Gollier, 2004; Hepburn a nd Groom, 2007). Given this concern, we urge caution in interpretation of results calculated using the Newell and Pizer approach and encourage fu rther investigation.

e. EPA has struggled with the question of the length of time an analysis should capture and has arrived at some practic al recommendations (see Section 6.1.6.3 and 6.4). Are these recommendations consistent with good economic practices? Does the

committee have additional recommendations or insights on this subject?

In considering the time horizon an analys is should cover, there is no general answer beyond the answer to th e question of what consequen ces to include: those that may have a quantitatively signi ficant effect on the conclusion s of analysis (as noted in Section 6.1.6.3). With positive discounting, the in fluence of consequences decreases with their temporal distance; unl ess the probability-weighted magnitudes of consequences grow sufficiently rapidly with time, their effect on the analysis will become negligible. In general, there is no method for knowing wh ether a consequence may be sufficiently important to merit inclusion except by including it and testing for its effect. For this purpose, a rough estimate or upper bound is ofte n sufficient. As noted in the text, many exogenous factors are likely to influence th e date at which the effects of the policy become negligible (e.g., technologi cal innovation or policy change).

14Question 4: Benefits

Do the published economic theory and empiri cal literature support the statements in Chapter 7: Analyzing Benefits on the mer its and limitations of different valuation approaches for the measurement of social benef its from reductions in human health risks and improvements in ecological conditions attributable to environmental policies?

This chapter provides good coverage of the main categories of benefits of environmental policies and regul ations, and of the methods used to estimate them. The chapter might flow better if th e discussion of the main cate gories of benefits was more concise, and more details about the valuat ion of these impacts were offered in the overview at the end of the chapter.

Chapter 7 falls significantly short of capturing a considerable amount of recent literature on benefits. In the following page s, we identify a number of areas where the literature of the past decade or so is not adequately reflecte d in the chapter. We have not

made an effort to be exhaustive in recommendi ng additions, but rather to identify areas as obvious omissions. In general, the Handbook of Environmental Economics published by North Holland in 2005 would be an excellent starting place. More specifically, the literature in the following areas needs to be updated:

1. Recreation Demand Models. A great deal of work published in the last decade on random utility maximization (RUM) and Kuhn-Tucker models have taken these approaches beyond the descriptions provided in the Guidelines. Updated approaches to valuing the opportunity cost of time, iden tification of choice sets, and other aspects of recreation demand should also be included. Potentially useful sources for journal

research that should be reflected in the Gu idelines can be found in the collection of articles in Herriges and Kling, (2008), among other works. In addition to covering methods for valuing natural resources that have recreational use, this volume is also a good source for articles related to hedonics and locational equilibrium models. For

more theoretical treatment cite Bockstael and McConnell , ( 2008). For more practical discussion cite Champ et. al. ( 2003).

2. Combining Revealed Preference (RP) and Stat ed Preference (SP). A revised draft of this chapter should discuss work over the past decade that has sought to combine revealed and stated preference methods. This has been an area of significant interest as researchers have attempted to understand how the strengths of each approach might be combined to improve the perf ormance of welfare estimators. On the theoretical front, Herriges and Kling, (1999) raise the question of whether revealed preferences can ever accurat ely estimate welfare for quality changes when weak complementarity cannot be assured.

3. Stated Preferences: Validity and Reliability. A significant amount of recent work related to stated preferen ce approaches is not reflected in the Guidelines. Understanding whether people over- or under- state their actual preferences for a nonmarketed good when asked a hypothetical question and whether approaches to

15mitigate these effects are successful rema in important researchable questions. Considerable work on this question has b een undertaken beginning with studies such as Bohm’s (1972) experimental lab study which compared bids in hypothetical and real experimental markets that elicited subjects’ stated value to sneak preview a Swedish television show. His results suggest that people moderately overstate their real values when asked a hypothetical questi on. Other early work includes the studies by Bishop and Heberlein, (1979), Duffield and Patterson, (1992), and others who compared stated preference estimates to those obtained from actual transactions.

Subsequent research has included both field and laboratory experiments. For instance, List and Gallet ( 2001) report the results of a meta-analysis to determine whether important experimental parameters systematically affect the relationship between hypothetical and real responses, concluding that certain elicitation methods that yield less hypothetical bias than others. Others (e.g., Cummings and Taylor, (1999), List, (2001), Lusk and Prevant, ( 2008), etc.) have studied hypothetical bias and incentive compatibility focusing sp ecifically on the dichotomous choice elicitation format in contingent valuation. These and other references addressing this

literature should be discussed in the Guidelines . Remaining research questions and

needs should also be identified.

A final area in which SP validity and reliability research has appeared is in the arena of choice experiments. Although many choi ce experiment-based studies are not conducted in ways that would preserve incentive compatibility, some limited evidence exists suggesting lit tle or no hypothetical bias when estimating marginal attribute values (see List et al., 2006, and Lusk and Norwood, 2005)

4. Valuing Mortality. There are a number of st udies that need to be updated in this area, please see charge question #5 for specifics.

5. Valuing Morbidity. The Guidelines should provide a sense as to whether the research community is satisfied with exis ting estimates of morbidity benefits. Is the usual approach—symptom days—still judged acceptable? Likewise, this section points out that frequently used a pproaches, such as the cost-of-illness or averting expenditures, do not capture the full WTP to avoid an episode of illness.

It would be useful to note that some studies (e.g., Rowe and Chestnut, 1985, and Alberini and Krupnick, 2000) have estimated that total WTP can be two to four times as large as the cost of illness, ev en for minor acute respiratory illnesses (as in Alberini and Krupnick’s case).

6. Ecosystem Services and Benefits Assessment. The literature re view is outdated, and there are no examples of recent studi es that attempted to place a value on ecosystems and ecosystem services. It w ould be useful to know which measures of ecological system function was used in those studies, whether market or nonmarket valuation approaches were used, and what the strengths or shortcomings

of these studies were.

16Ecosystem services encompass a broad array of goods and services, ranging from standard market goods lik e agricultural products to far more complex and less well identified services such as nutrient cycling. Valuing the more complex ecosystem services is very challenging because it requires sequential linkages from the pol icy of interest to the dire ct effects on organisms to the associated indirect effects through changes in the functioning of ecosystems to the resulting changes in services and finally to the associated social values. Our understanding of each of these elements is rudimentary in some cases. Yet, we need to develop analyses to support policy decisions in spite of the many

uncertainties.

This document should provide more extensive guidance on how to carry out valuation of ecosystem services within the contex t of policy decisions that EPA needs to make. A variety of technique s are available that can provide useful input to policy within the context of less than complete knowledge. In addition to standard cost-benefit methods, these a pproaches include cost effectiveness analyses, choice-based methods (e.g., Opal uch et al, 1993; Unsworth and Bishop, 1994; Adamowicz et al, 1998), etc. The report should also draw from recent reviews, including EPA SAB (2009) and the National Research Council (2004).

The report should address important challenges facing the practitioner, including: What does valuation of effects on ecological systems share with

valuation of other benefits? In what way is it different? What are unique difficulties when valuing ecosystems or ecosystem services? What approaches

are available in face of the many uncertainties?

As mentioned in the discussion of cross-cutting issues, we urge the Agency to vastly expand its guidance on characterizing non-monetized benefits.

We recommend that the Guidelines incorporate the concept of ecosystem services and its various components, as outlined in the Millennium Ecosystem Assessment (MA) Synthesis Report (2005) and highlight treatment of ecological systems and services in benefit-cost analysis. Users of the Guidelines should be warned that an inappropriate focus only on impacts that can be monetized ca n provide misleading policy guidance (as with other cases of unbalanced information). In addition, a strong recommendation should be made to provide quantitative measures of ecological impacts and a qualita tive characterization of eco logical effects. These quantitative measures and qualitative de scriptions are needed whether or not

benefits can be monetized. We note that EPA’s Office of Research and Development has an extensive Ecosystem Se rvices Research Program that may be

an excellent resource for economists who need information ecosystem impacts for economic analysis.

We urge EPA to consider the SAB’ s recent recommendation to begin with a conceptual model of the relevant eco system and ecosystem services and map

those effects to services or attr ibutes that the public values ( Valuing the Protection of Ecologica l Systems and Services , SAB, 2009). The SAB report

17covers a wide range of alternative me thods for characterizing, valuing and gauging ecological impacts. We urge EPA to evaluate and determine the appropriate use of these alternative me thods and provide much more guidance characterizing non-monetized effects. Another recommendation from the SAB report that could be appropriated for the Guidelines is to label aggregate

monetized benefits as “total monetized econom ic benefits,” not “total benefits.” We believe the SAB report provides othe r useful examples relevant to the

Guidelines

.

In addition to updating the literature in the area just enumerated, we recommend expended treatment of the discussion about assessing studies and data. We applaud EPA’s discussion of validity concepts (p age 7-41) as the basis for choosing among

studies for inclusion in a benefit-cost anal ysis, but the treatment of the validity and reliability of estimation methods is uneven. Mu ch of the discussion about validity centers on stated preference methods. However, we feel that due to (usually untested) assumptions that they make about individuals ’ perceptions of environmental quality and identification of effects, revealed prefer ence methods should be scrutinized for quality and validity, as should CGE models.

The material in Sections 7.4.2.3 “Considera tions in Evaluating Stated Preference Results” and 7.4.3 “Benefits Transfer,” could be used as a starting point. For example, the validity tests (content, criterion and conve rgent) discussed on 7-41 – 7-42 apply to all types of studies, not just stat ed preference, as do various biases associated with survey non-response (7-42 – 7-43). Other validity conc epts that should be discussed include:

• Internal Validity: is there plausibly ex ogenous variation in the variable of interest (the one capturing health risks or environmental quality)?

• External Validity: Can the study’s resu lts be generalized to the overall population of interest? Can the study’ s results be generalized to the time period of interest? Is the study’s treatm ent relevant for the program that is

under consideration?

• Theoretical Validity: Can the study’s re sults be interpreted as a measure of willingness-to-pay (WTP) (or a bound on WTP)?

A discussion of the trade-offs between revealed and stated preference approaches could be very helpful to readers. EPA shoul d note that flaws of both stated preference (SP) and revealed preference (RP) should be considered when evaluating studies and performing regulatory analysis. For exampl e, most hedonic properties, compensating wage differentials and other revealed pref erence studies assume, without testing, that people know the correct risks or level of environmental quali ty. These studies will often estimate the willingness to pay or accept for changes that do not match well the policy change under consideration. In contrast, validi ty questions related to stated preference

studies are a limitation that shoul d be not disguised or diminish ed. It would be useful to emphasize that judgment is essential to good anal ysis and that the results from stated (and revealed) preference studies should be car efully assessed with economics and commonsense basics. For example, is WTP for a ch ange in environmental quality a reasonable

18fraction of one’s income? Does it increase in predictable ways as income increases, and are the estimates of income elasticity of WTP reasonable and consistent with other

evidence?

Chapter 7 states that the Agency should use benefit transfer only as a last resort, when time and budget constraints do not allow original benefit estimation. We agree, but the reality appears to be that benefits transfer is the most common approach to completing a benefit-cost analysis. If correct, this should be acknowledged. Further, the exposition of the possible benefit transfer techniques reads somewhat mechanically and does not clearly discuss the underlying assump tions. For example, unit value transfer presumes that the original good, the characteristics and the tastes of its population of beneficiaries are the same as the policy good /locale. When a value function transfer is done, it is implicitly assumed that the populat ion of beneficiaries to which we are applying the transfer has potenti ally different characteristics , but similar tastes, as the original one.

EPA should distinguish the criterion used to evaluate an original study from those that can be used to evaluate a study for use in benefits transfer. Given the importance of the process of “benefits transf er” in benefit-cost analysis performed for EPA, separate guidelines for analysts on to how to evaluate studies to use in a benefits transfer is warranted. In doing so, we note that there is an extensive literature that provides guidance on benefits transfer th at the Agency can draw upon such as the special issues in Ecological Economics . Some issues that are likely to belong in such a set of

considerations include: si milarity of environmental good valued in original study to environmental good being valued in benefits tr ansfer; similarity of original study sample to population of interest in the policy/regulatory setting; and overall quality of the original study benefits (i.e., the set of considerations in the above list “benefits – original studies”).

The document discusses meta-analysis as one way of conducting benefit transfer. Almost two years ago, two meta-analysis expe rts briefed the EEAC about meta-analysis. They reminded us that a meta-analysis seeks, at best, to establish whether certain aspects of study design and execution influenced final va lues, and its results should be interpreted with caution. They offered a number of recommendations, warning against the “ecological fallacy” and against pooling values from studies conducted with extremely different methods. The chapter would benefit from reviewing the main lessons from that presentation.

19Question 5: Mortality Risk Valuation

Chapter 7 includes a brief discussion of th e Agency’s current approach to mortality risk valuation with more details provided in Appendix B. These sections will be updated when the Agency concludes its efforts to update its mortality risk valuation approach. In the interim, are the discussions provid ed in Chapter 7 and Appendix B clear and

balanced?

We will refrain from extensive comment s on mortality risk valuation until the Agency’s update is complete. In the m eantime, we recommend the Agency consider expanding discussion in the following manner to improve the balance in the current

version of this section.

The literature review about methods used for valuing mortality risks should be updated. Generally, the Chapter does a good job recognizing the advantages and limitations of using the two main metrics in mo rtality benefits valuation (the VSL and the VSLY) and of the different methods used for estimating them (revealed preference, usually in the context of occupational risk, a nd stated preference). It also does a good job discussing factors—such as age and pr e-existing conditions —that matter with environmental exposures and may affect th e VSL. The chapter does, however, overlook Viscusi and Aldy (2007), who look at age and th e VSL in a wage-risk context. It could

also include discussion of a lternative methods for estimati ng VSL such as the “chained” approach linking WTP to reduce non-fatal inju ry with risk tradeoffs between fatal and non-fatal injury (Carthy et al., 1999).

Despite its careful discussion of the limitations implicit in using the VSL estimated from compensating wage studies when valuing mortality risks associated with environmental exposures, Appendix B and much of EPA’s current practice continue to rely on old wage-risk studies. All of these wage -risk studies use old da ta, i.e., risk levels that are no longer likely to exist and obsolet e preferences for risk and income; they are based on cross sections of data, do not contro l for self-selection into risky jobs and for heterogeneity in preferences for risk and income, and contain a massive measurement

error in the risk variable. Better studies to discuss that control for unobserved heterogeneity as well as use be tter risk measures are Knei sner, et al. (2006), Viscusi (2004), Kochi (2008), among others.

The Guidelines should discuss the research concerning the VSL for specific

causes of death that are associated with environmental exposures—cancer and cardioand cerebro-vascular illne sses (e.g., Gayer et al., 2000, 2002; Davis, 2004; Johannesson and Jonsson, 1991; Alberini and Chiabai, 2007). The Guidelines should also discuss

research needs in this area. A number of st udies using revealed preference methods infer values for risks related to the agency’s policies (e.g., Davis, 2004, Gayer et al. 2002, Greenstone and Gallagher (2008), Ashenfe lter and Greenstone (2004), Gayer et al. (2000)) and others. Likewise, there are newer st ated preference studies that infer values

20for risks related to agency’s policies that should be referenced (see Krupnick (2007) for examples).

In several places, the Agency refers to th e importance of “the impacts of risk and population characteristics” on valuation estim ates (e.g., p. 7-6, line 36; p. 7-8, line 31-43; p. B-4, lines 29-32), yet the discussion is gene rally focused on population characteristics. The agency should consider adding more discussion about the impact of risk characteristics on valuation, the newer litera ture valuing the events of relevance to environmental policy, and rela te these issues to its recommended default value.

21Question 6: Social Costs

Does Chapter 8: Analyzing Costs contain an objective and reasonable presentation of the published economic theory, empi rical literature, and analytic tools associated with estimating social costs?

In general, the Chapter does contain an objective and reasonab le presentation of economic theory, literature and analytical tools. While generally quite well done, we found several areas where improvements could be made.

At the end of Section 8.3.1.3 Discounting, the Guidelines state “In calculating firms’ private costs, e.g. the internal cost of capital used for pollution abatement, analysts

should use a discount rate that re flects the industry’s cost of ca pital.” While this quote is correct, we fear that it could be misinterpreted to suggest th at costs and benefits might be legitimately discounted at different rates with in a single analysis. Doing so could lead practitioners to make significant errors. For example, an analysis with different discount rates applied to public and private costs could justify a project whose private costs greatly exceed its public cost savings when both occur at the same time period in the distant future. Yet, as the time approaches, this de cision would be reversed, implying a form of time inconsistency. The Guidance should be wr itten to make clear that such a practice would not be appropriate.

The beginning of the chapter indicates that costs are usually viewed as straightforward to estimate, but in fact es timating costs presents many challenges. For example, estimating costs of new regulations requires forecasts many years into the future. As pollution control technologies are implemented over time, firms can learn from experience and the development of new technologies may reduce the cost of achieving the standards. At the same time, ex ante cost estimates may be based on the assumption that everything works as anticipate d, but in practice deviations from expected outcomes often mean higher than anticipated co sts. These challenges can be exacerbated since industry often has more information abou t costs than regulator s and are likely to

have the incentive to overstate their costs. All these arguments reinforce the report’s indication that measuring costs are not at all straightforward, nor are cost estimates

“hard” numbers.

The report differentiates between partial equilibrium analyses which model a single market or a small number of markets, versus general equilibrium analyses that model the entire economy. The Chapter might be better organized by examining three cases: single market analyses, multiple market analyses and general equilibrium analyses. Significantly different challenges are faced when carrying out multi-market partial equilibrium models than single market models, and it might make the explanation

more clear.

Also, some additional guidance would be helpful on carrying out multimarket partial equilibrium models (e.g., Section 8.1.2, pa ge 8-5). For example, the report could

indicate the conditions under which multimarke t models are likely to be necessary, and

22how multimarket analyses should be carried out. The Just, Hueth and Schmitz textbook provides a thorough treatment of these issu es, and could be both the source of information for the document summary a nd an excellent reference for further

information.

It is important to note that it is not simp ly the number of markets that are affected directly by a regulation, but also their size and influence on the economy that determine whether partial equilibrium analysis is ad equate. Indeed, the first example under CGE (Sec 8.1.2) is of a single but large market (e lectric utilities). Similarly, a partial equilibrium analysis of a significant change in “the labor market” is unlikely to be adequate, given its influence on nearly all mark ets in the economy. It might also be worth noting that definition of “a market” is not always clear cut. Is “the labor market” one or a large collection of segregated markets w ith somewhat permeable boundaries, by age, education, experience, geography, etc.?

On page 8-4, immediately below the figure, the text states “While in reality at least part of the compliance cost will likel y be spent on abatement-related purchases from

other industries – and is thus not necessarily a loss to so ciety – in this market, the deadweight loss resulting from th e regulation is lost completely.” It should be made clear that expenditures in other ma rkets are losses to society ex cept for the portion that is a quasi-rent. We are concerned this passage c ould be interpreted as expenditure per se in other markets are not losses to society. Again, the Just, Hueth, and Schmitz (2005) textbook is an excellent source for appropria te accounting of multimarket effects.

In general, the treatment in the report focuses too much on perfectly competitive markets, and provides too little discussion of non-competitive market environments. In our introductory comments and in response to Charge Question 1, we discuss the need to incorporate real world “second be st” conditions in the Guidelines. With respect to costs, results will differ significantly in a non-comp etitive market, or in a market where there are other distortions. In general, a comple x game theoretic formulation is needed to assess effects in markets that are not perfectly competitive.

23Question 7: CGE Models

Does Chapter 8 contain an objective, balan ced and reasonable presentation of the published economic theory, empi rical literature, and analytic tools associated with computable general equilibrium (CGE) models? Is the description of the relevance of these models for economic analyses performed by the EPA reasonable?

Overall, the discussion of the structure and use of computable general equilibrium models in Chapter 8 is concise and very good. It clearly summarizes the design and structure of CGE models, their strengths and we aknesses, and the role of such models in economic analysis at EPA.

The only major topic the section does not discuss is the parameterization of CGE models. Some use behavioral parameters estimated econometrically from extensive timeseries data, while other models use parameters calibrated to a single input-output table or taken from the literature. Estimation is clearly preferable where adequate data exist. One of the principal benefits of general equilibri um modeling over input-output analysis is its ability to capture substitution in production and consumption, so it is important that the

relevant elasticities be tied as closely as possible to the hist orical record. A paragraph on parameterization should be added to the sec tion. A brief discussion of parameterization

should be added to Section 8.4.4 on I nput-Output analysis as well.

Secondly, the Guidelines ’ discussions of CGE mode ling in general and the concept of general equilibrium welfare anal ysis in particular should be expanded to

address the role of models that introdu ce pollution (or equivalently environmental services) in non-separable specifications fo r consumer preferences. Such specifications introduce the prospect for feedback effects wh ere policies to reduce externalities lead to changes in the demand for market goods and th en in turn the amount of pollution giving rise to the externalities. These responses “feedback” and affect the demands for market goods. The process can be expected to cont inue with the models describing systems where the market and non-market interactions affect the ultimate market equilibrium. It is important to draw distinctions between sort ing models with multiple markets and what might be described as extended partial e quilibrium analyses and CGE models. Recent advances in both types of mode ls allow EPA to consider using these structures to assess when the changes associated with their policies would be large enough that conventional practices that assume away general equilibrium effects need to be modified or at least qualified. There is sufficient research that the Guidelines can begin to introduce candidate procedures for addressing these issues.

The section would benefit from a few mi nor revisions as well. First, the discussion at the beginning of Section 8.1.2 s hould em phasize that the need for general equilibrium analysis depends on the scope of the policy’s effects rather than just the

number of markets. A policy might have sign ificant effects in a si ngle market, but if the market is large enough (the labor market, for example), general equilibrium analysis

would still be warranted. Similarly, a polic y affecting a large nu mber of very small markets might be adequately addresse d by partial equilibrium analysis.

24A second minor revision is that the disc ussion of the benefits of dynamic models should be expanded slightly. Not only are su ch models useful for capturing saving and investment effects, they can also be used to examine policies that themselves change over time—becoming more stringent, for example. In addition, models based on intertemporal optimization by the underlying agents can also capture anticipation e ffects: changes in behavior occurring when policies are announced th at don’t take effect until some point in

the future.

A third minor point is that the discussion of the ability of CGE models to capture transition costs should be expa nded slightly and the conclusi on that they cannot capture such costs should be refined. It is true that many models are inappropriate for short run analysis because they assume that capital and labor are completely mobile between sectors, and because they typically use subst itution elasticities that reflect medium to long run behavior. However, those are characteri stics of existing models rather than the methodology itself. Models that use sector -specific capital stocks and costs of adjustment in investment are able to capture important short-run costs due to misallocation of capital. In principle, mode ls with adjustment costs in labor demand could capture additional short-run costs due to labor misallocation as well. It would be most accurate to say that many existing CG E models are not de signed for analyzing short-run transitional costs, rather than it being a problem inherent in the methodology. Finally, because CGE models differ consid erably from one another in design and parameterization, it is valuable to use multip le models when possible, especially for policies expected to have very large e ffects on the economy. When EPA uses CGE analysis, it often does use multiple models and it would be very useful to note that in the

text.

Finally, the issues of validity and relia bility mentioned in other areas of the Advisory are equally relevant to CGE models . We suggest EPA make this point in this chapter and refer readers to the broader discussion of these issues elsewhere.

25Question 8: Distributional Analyses

Does Chapter 9: Distributional Analyses : Economic Impact Analyses and Equity Assessment contain an objective and reasonabl e presentation of the measurement of economic impacts, including approaches suitable to estimate impacts of environmental regulations on the private sector, public sector and households? This discussion includes, for example, the measurement of c hanges in market prices, profits, facility closure and bankruptcy rates, employment, ma rket structure, i nnovation and economic growth, regional economi es, and foreign trade.

Chapter 9 contains an objective presentati on of many of the aspects of economic impact analyses (EIA). It t ackles market prices, profits, f acility closures, unemployment, market structure, innovation, and growth. Although Chapter 9 contains information on estimating the economic impact of policies, di scussing three approach es briefly: Direct Compliance Costs, Partial Equilibrium and Computable General Equilibrium (CGE), it points to Chapter 8 for more details. To make Chapter 9 stand alone, developing brief examples from chapter 8 for both partial a nd CGE may further the reader’s understanding of why these are more effective than the di rect compliance costs. Also, augmenting the warning of the complexity of CGE modeling may be worthwhile.

While there is attention to the implemen tation of CGE models, the discussion of partial equilibrium models basically directs the reader to find supply and demand curves or elasticities, but there are multiple ways of implementing partial equilibrium models. One which would tie this chapter to the be nefits chapter is th e "production function" approach. More discussion concerning implementation would be valuable.

The Guidelines acknowledge that input-output (I-O) models have important conceptual shortcomings as measures of ec onomic benefits and co sts. In addition, it might be pointed out that I-O models ignor e opportunity cost of resources, implicitly assuming that inputs used in some new activ ity would otherwise go be idle and have no opportunity cost. For example, I-O analyses frequently use multipliers to calculate jobs “created” due to the direct, indirect and indu ced effects of an activ ity. A proper measure of benefits would account for the opportunity co sts by subtracting the value of labor in its

next best use.

Some other miscellaneous points to consider:

• Linear programming (LP) is more of an optimization method than an economic concept or model.

• There should be some discussion of the marginal cost of public funds as a cost of policies. This may belong in Chapter 8 rather than Chapter 9.

There should be a discussion of the implications of distortions other than taxes for costs, such as imperfect competition and rent seeking public interventions.

26Question 9: Measuring Equity Effects

Does this chapter contain a reasonable pr esentation and set of recommendations on the selection of economic variables and data sources used to measure the equity dimensions identified as potentially relevant to environmental policy analysis?

Data sources for both items are reasonab ly well addressed in Chapter 9. For information on the former, the U.S Census (household and economic) provides a majority of the data while industry rating agencies provide a deeper u nderstanding on which industries are susceptible as described in the document (9.5.2 - 9.5.4). However, there is some uncertainty in how to obtain inform ation on government entities as only accessing data through “community or state finance agencies” is mentioned (9.5.2.2). Information on assessing how the populations of interest are being affected can be found via various environmental sources pointed out in Section 9.8.4. Overall, the chap ter contains all the relevant economic variables necessary in an equity analysis. To support analysts, EPA might consider creation of a website to catalog all of the data sources.

The chapter also provides a reasonable discussion of what the analyst should consider in measuring the distributional as pects of regulations. The main items in assessing equity issues are correctly identifying the populations of concern and accounting for how the populations of interest are being affected. In doing so, it is important to balance data acquisition costs against the value of accuracy.

One limitation we note is that the main dist ributional issues that are discussed in this chapter relate to the cost side: i) dire ct compliance expenditures (p. 9-17), ii) indirect costs (taking into account multipliers, GE effect s, etc.), and iii) enforcement costs. The bulk of the chapter relates to direct co mpliance expenditures, and discusses how regulation influences prices, through changes in the composition of industry for example. This focus on the cost side misses many important issues related to environmental justice. EPA should note that there may be just as much interest in consider ing the distributional

effects of benefits of an environmental cha nge. The costs of identif ying the distribution of benefits may be much more data intensive a nd costly than identifyi ng the distribution of costs. Nonetheless, it would seem appropriate for this document to represent the ideal case as one in which the equity and impacts a ssociated with both be nefits and costs are

considered.

In the context of describing the benefits, costs, or net benefits distribution across populations, it would be useful to describe how the concepts of Lorenz curves and/or

Gini coefficients could be used.

27Question 10: Economic Literature

Appendix A: Economic Theory was prepared for those readers who wished to have a better understanding of the economic foundations underlying benefit cost analyses. Does Appendix A summarize the relevant literatu re in an objective and me aningful way? Are there topics that warrant (m ore) discussion in this appendi x that were otherwise missed?

The Appendix provides a thorough and clean discussion of the core economic

foundations relevant to benefit- cost analysis with two excep tions. First, a discussion explaining the distinction between stock and flow pollutants should be added. A stock pollutant is an unwanted byproduct of produc tion or consumption that accumulates through time whereas a flow pollutant does not accumulate. Much of the Guidelines deals only with a special case where the damage from pollution comes exclusively from the one-period flow of the po llutant and does not consider the general case where the damage comes the accumulated stock of the pol lutant. This distinction can be important when undertaking benefit-cost analysis for po llution reduction as the form of the damage function differs. Since greenhouse gases are a prominent and potentially catastrophic stock pollutant, this is an esp ecially important topic for the Guidelines to address.

Second, the concept of “user cost” should be defined and explained. User cost relates to forgone future benefits of a resour ce. That is, exhaustible resources used today

will not be available for future use. Benefit- cost analysis related to resource stocks will

often need to consider and estimate user costs so its inclusion is important.

28Question 11: Omissions

Please identify and enumerate any inconsistencies you may find across chapters and other issues/topics on which we should provid e further elaboration. Also, please identify any definitions provided in the new glossary that are inaccurate or that otherwise need

revision.

Most of our advice on cross-cutting issues is provided in the Introduction to this Advisory. Below are a few additional ideas that merit consideration.

First and foremost, the Guidelines sorely need case studies and examples to illustrate and make concepts concrete and meaningful.

International trade in market and nonmark et goods is not adequately covered in

the Guidelines . The discussion of costs, for example, generally assumes a closed economy without internationa l competition. The discus sion of policy instruments focuses exclusively on the management of “internal” externalities.

Dynamics are another issue receiv ing inadequate attention in the Guidelines

, although dynamic models are discussed in the CGE chapter. Dynamics become relevant to policy analysis, and to estimation of bene fits and costs in several contexts. One context is stock pollution probl ems, climate change being th e leading example. Another is when the costs of pollution control or the benefits of po llution reductions have dynamic elements. The costs of pollution control have dynamic elements when there are capital adjustment costs and when there is induced technological change – both features of the

“real world.” Benefits of pollution reductions have dynamic elements when pollutants are stock pollutants, and when those damage d by pollution have capital adjustment costs in adapting to environmental conditions, and when environmental conditions induce innovations among those who are damaged. Dynami cs in these contexts are important in

benefit and cost estimation.

29Appendix: Compilation of Line by Line Comments from Individual Members

The following comments are suggested edits from individual panelists. As these

comments were minor and not considered fo r full panel deliberation, they are listed separately here for the Agency’s consideration.

Page 4-3, Line 13: Drop statement “... does not attempt to detail the relative merits of putting them into practice ...” . Report disc usses merits of various approaches.

Section 4.1: Divide this sec tion into two parts: (i) Effi cient Level of Pollution (MD = MACaggregate) and (ii) Cost-Effective Level of Pollution – minimize cost across sources (MAC1= MAC2= ... = MACn). Each will need a supporting graph and should be integrated by showing aggregate MAC is de rived from individual MACs. See Field and Field textbook for dividing the discussion in this way. Also, in discussion of efficient level of pollution be sure to define social welfare using underp innings of Pareto Optimality. In the discussion of efficient leve l of pollution note that in the presence of uncertainly, one may prefer to think of the efficient level of pollution as a distribution

about E*.

Section 4.2: Divide this section by (i) design standards a nd (ii) performance standards for clarity. They seem to bump up against each other in the discussion. Be clear about the difference between design standards (technology forcing) and technology based performance standards. Show uniform and technology-based performance standards using cost-effectiveness graph in troduced in previous section. Uniform standards are not

cost effective but have a low informati on burden (do not need to know MACs) and technology-based performance standards are co st effective in principle but have a high information burden (need to know MACs).

Page 4-6, Lines 2-4: Definition of Comma nd and Control (CAC) is not quite right. CAC sets requirements on specific firms . Please clarify. Also, consider dropping the terminology CAC. Simply refer to these dir ectly as design and performance standards.

Page 4-6, Lines 28-29: Drop “...firms are not responsive to price signals ...” and “... random events and emergencies ...”. Emergency argument for standards is ok but it can be applied in the context of any regulatory approach including market-based approaches.

Page 4-6, Lines 31-32: This sentence is inco rrect. Polluters may have face different design or performance standards under CAC regulations.

Section 4.3: When the section on market based regulations is introduced, state why economists tend to prefer these controls: th ey tend to be least costly, have a low information burden on regulators, and provide incentives for technolog ical advancement. Monitoring and enforcement costs and other ad ministrative costs, of course, can favor direct regulation.

30Page 4-8, Coase Box: Even when the conditi ons mentioned in the opening sentence of the third paragraph of the Co ase Box are met, the Coasian solution may not be reached due to asymmetric information and bargaini ng strategies (ala principle-agent theory) followed by the parties to the transaction. Pl ease qualify the statement accordingly. Also, full information is not a necessary condition for a bargain, even a socially efficient bargain, to take place.

Page 4-9, Line 31: Not sure what is mean t by “...when only one permit price exists.” When would more exist? Please clarify or drop.

Section 4.3.1.1: Use cost-effectiveness graph to tell the cap & trade story demonstrating its property as a least costly instrument. Al so, instead of telling the cap and trade story assuming an efficient level for permit allocations from the start, tell the story that for any aggregate level of emission there exists a cap and trade will be least costly. Then point out that the efficient solution is a special case where the permit allocation is efficient (MD=MAC).

Page 4-11, Lines 23-24: Mention an ambient- based trading scheme directly for dealing with non-uniform mixing (hot spots) and then explain why, due to administrative costs, something intermediate (zones) between emissions based scheme and ambient base scheme maybe efficient.

Section 4.3.2: Expand the discussion of the revenue raising property of the tax and how it can be used to displace other distortionary taxes.

Section 4.3.2: Again, separate cost effectiveness for any given level of emission from efficient (Pigouvian) for special case.

Section 4.3.2: Include some discussion of targ eting the tax. Do you ta rget the tax on the pollutant, input, process, or el sewhere? In principle you shou ld place it on damages, but administrative and monitoring costs may suggest targeting elsewhere. Taxing gas is much easier and probably as effective as ta xing damages from auto emissions.

Somewhat related to the previous point, pl ease note that policy de sign is dependent on

observable and available information. For ex ample if the policy makers can not observe actual pollution levels but input s and practices that cause pollution can be observed and

there are reasonable estimates on relationshi p between the input and technology use and the pollution level, then taxes or regulations or fees are based on the imputed pollution levels. Policy makers should be aware of the available information and design policies to best take advantage of the available knowle dge. In particular identifying sources of heterogeneity among users and knowing how they affect pollution levels is crucial to policy design. The proliferation of geographic information systems and remote systems to obtain data provide new opportunities for polic y design. Studies suggest that there is a significant efficiency gain from policies that adjust to observed heterogeneity relative to uniform policies (Xabadia et-al 2008). Availabil ity of new sources of or means to obtain information may lead to redesign of policies – for example, availability of a technology

31of cheap monitoring of pollution may lead to regulation on taxation based on annual pollution rather than imputed pollution. Po licy makers should r eassess policy design and implementation as technology progresses. See Xabadia, Angels, Goet z, Renan-Ulrich and Zilberman, David, “The Gains from Differen tiated Policies to Control Stock Pollution When Producers are Heterogeneous”. American Journal of Agricultural Economics, Vol. 90, No. 4, pp. 1059-1063.

Section 4.3.3: Divide section by (i) subsidy per unit emission a nd (ii) other subsidies. It more or less falls out that way now , but a clear separation would help.

Page 4-14, Lines 2-4: Drop “H owever, there may be cases in which a subsidy is more

feasible than an emissions tax especially when it is difficult to identify polluters, or when research and development activities relevant to emission abatement would otherwise be under-funded.” First part of sentence is handled elsewhere and what does “Underfunded” mean? Is there a market failure here?

Page 4-18, Lines 20-24: Drop this passage. A more meaningful distinction between liability rules and othe r regulations is that they are ex post regulations usually used in cases of accidents or episodic environmental events, not typical flow pollutant cases.

Section 4.4.2: Mention that in formation disclosure strategies can allow the market create incentives for pollution control (following Coase) with the vi ctims directly signaling their preferences to firms. But these are most likely to work when there are contractual obligations between polluting fi rms and affected parties (e .g. consumers/workers) and more difficult to work when they affect third parties (see Tiet enberg, “Disclosure Strategies for Pollution Control,” Environm ental and Resource Economics, April-June 1998, v. 11, iss. 3-4, pp. 587-602. Also it should be mentioned that credibility of information is important. Information disclosu re can lead to inefficient outcomes when information is not credible (see Brouhle, K. and M. Khanna, “Information and the Provision of Quality-Differentiated Goods,” Economic Inquiry: 45(2): 377-395, April, 2007).

Section 4.4.3: Move this s ection into the market incen tive sections and expand the discussion to include issues of limited assets, activity level incentives, courts costs and so forth. See Segerson (1995) for a nice summary.

Page 4-18, Footnote 54: Another study that s hows the types of firms that had incentives to improve environmental performance follo wing negative stock market returns is Khanna, M., W. Quimio, and D. Bojilova, “Toxi c Release Information: A Policy Tool for Environmental Protection,” Journal of Environmental Economics and Management , 36 (3): 243-266, November 1998.

Page 4-19, Line 19: “...information on investment options ..” This speaks more to the public goods property of information provision th an it does information disclosure. It has not really been mentioned until now and is different than information disclosure. Consider bringing information provision into ch apter. There may be a under provision of

32information on technology following a public goods argument. See Goulder and Parry (2008).

Section 4.5.3: Weitzman argument. When MAC’s are uncertain, and if MD is believed to be constant or flat, th en favor a price instrument. If MD is believed to have thresholds or be vertical then favor a quantity instrument. This avoids making costly mistakes. This message does not come across clearly in this se ction. Also, the “degre e of uncertainty” is given as a factor in choosing among policies. This is not techni cally correct. For example, large uncertainty about emissions is of no policy consequence if the marginal damage cost is constant.

Page 4-22, Line 31: It is incorrec t to say that voluntary programs require firms to set goals (also see line 38) or to say that they definitely achieve environmental improvements. Also, it is not accurate to sa y that most voluntary pr ograms set goals (line 37). They also do not make it simpler to mon itor and measure if participants are meeting the goal – most voluntary programs do not requir e firms to provide emissions data to the EPA (for a review of these issues and comp arison of programs see Khanna, M. and D.T. Ramirez, “Effectiveness of Voluntary Appr oaches: Implications for Climate Change Mitigation,” in Voluntary Agreements in Climate Policy , edited by A. Baranzini and P. Thalmann, Edward Elgar Publishers, pp. 31-66, 2004.)

Page 4-23, Footnote 63: The references on voluntary programs ar e a little outdated. A more recent and updated citation on motivations to participate in different types of voluntary programs, challenges in evaluating th eir effectiveness and evidence about their effectiveness is Khanna, M. and K. Brouhle, “Effectiveness of Vo luntary Environmental Initiatives,” Chapter 6 in Governing the Environment: Interdisciplinary Perspectives , ed. By M. Delmas and O. Young, Cambridge University Press, Cambridge, U.K. (forthcoming). Khanna, M., “The 33/50 program: Program Design and Effectiveness,” in Reality Check: The Nature and Performance of Voluntary Environmental Programs in the United States, Europe and Japan edited by R. D. Morgenstern and W. Pizer, RFF Press, Washington DC, 15-42, 2007.

Page 4-24: The box on water quality trading directs people to certain EPA guidance on the design of trading programs. While we thi nk there is merit to these documents, I have reservations about fully endorsing them b ecause there is economically flawed advice about some design elements. This box also misses an opportunity to discuss the importance of economic science to the desi gn of markets. Contemporary water quality markets fail to achieve the promise of tradi ng because of participation and coordination failures that occur in part because of flaw s in market design and development. On balance, I recommend dropping the box.

Page 5-2, Line 29: Recommending that the an alyst provide “ A clear written statement

about the current state of the economy ..” is too broad and may be unnecessary. Instead it is important to clearly specify the current a nd future state of econo mic variables that are relevant for the analysis.

33Page 5-8, Lines 1-4. The Guidelines mention that regulations can lead to innovation (which may not occur in the ba seline) which can lead to cost savings. They also mention

that there is no statistical evidence supporting this claim of cost savings. Hence they suggest that analysts should avoid assumi ng differing rates of technological innovation based on regulatory stringency. That last st atement (line 4) is in correct and should be

deleted. Instead there should be a brief di scussion about the potential for induced innovation due to environmental regulations . Regulations can create incentives for technological innovation that lowe r the cost of compliance. It should also be recognized that regulations may also discourage innovation in some cases or crowd out other

innovations.

Page 6-2, Line 21: NEARLY “any policy”

Page 6-2, Line 37: Can do half-cycle correc tion, i.e., assume effects occur at mid-year.

Page 6-2, Footnote 73: refers to exponential fn that was apparently deleted from draft

Page 6-4, Line 25 : Note NPV = NFV /(1+r)T.

Page 6-7, Lines 18-20: Text is duplicative

Page 6-10, Footnote 80: Qualify th at result requires rate of return > consumption interest

rate.

Page 6-15, Section 6.3. Although this section on “intergenerational discounting” is concerned with long time horizon problems, much of the text refers to climate change (e.g., paragraph beginning Page 6-16, Line 6). Th is is understandable (a s that is the most prominent long-horizon problem) but the text could be revised to avoid the impression that it is only about climate change.

Page 7-9, Lines 33-34: The text here me ntions possible approaches for valuing morbidity—ex ante and ex post. Please note that studies have also varied in whether they controlled for the opportunity to mitigate the illness (e.g., before or after taking medication).

Page 7-9, Lines 9-10: Recommend not listing fetal loss as a non-fata l health effect – some people would disagree.

Page 7-11, Line 20: Better to say that social costs include private costs (reflected in individual WTP) and external/ public costs (e.g., me dical care expenses paid by insurance or public sources). The existen ce of externally paid costs do es not mean the individual

“understates” own WTP.

Page 7-17, Lines 2-4: I guess this statemen t is true, but a tighter bound would be one

shouldn’t include effect for which cost of gathering information exceeds expected improvement in net benefits from choosing a better policy given this information. But I

34don’t want to make too much of the analytic co st point – seems to me that analytic costs are very small compared with B and C of th e major regulations we’re mostly considering (e.g., >100 M/yr for many years).

Page 7-19, Lines 15-16: It woul d help to clarify discussion of when multiple methods are substitutes or complements. In some cases different components will be captured by different methods (e.g., private WTP to redu ce health risk, public cost of illness of treating illness), in which case it is appropriate to use both methods and add results (making sure they do not double-count subcom ponents). In other ca ses where different methods provide alternative estimates of the same component, multiple estimates may be useful to triangulate on most accurate value, but should not be added.

Page 7-26, Line 22: Re opportunity cost of time, what if driving to the recrea tional site is itself enjoyable? After all, in some cases much of the benefit of trav el is the journey, not

the destination. I’m sure this is discussed in travel cost literature, but I don’t follow it.

Page 7-28, Lines 9-11: Strike this senten ce. We have no compelling evidence that instantaneous workplace deaths reflect the same tradeoffs that indivi duals are willing to

make over environmental risks.

Page 7-28, line 17: replace “believe” with “assume.”

Page 7-28, line 21: the work by Black and Kn iesner (2003) uses only risk measures known be fraught with measurement errors (even the “best” data was based on inconsistent reporting of deat hs (see Drudi, 1997) and aggregat ed in a manner that creates serious endogeneity problems (see Lei gh, 1995 (JEEM) and Mrozek and Taylor, 2002 (JPAM)). The discussion here could place Black and Kniesner in this context and then

look forward to the newer literature.

Page 7-28: The discussion of wage-risk studie s needs to be updated with recent results by Kniesner et al. (2007) an d Viscusi and Aldy (2007).

Page 7-28: Text on hedonics. What’s the po int of placing the discus sion of the source of workplace risk data where they are now? It ’s a non-sequitur, and the text does not elaborate on the implications of these sour ces and of the level of resolution of the workplace risk data.

Page 7-28: Disagree with “Fur ther, while estimates from the hedonic literature have been relatively consistent over the years, questions persist about...” Au contraire, Costa and Kahn (2004) find that in the US the compensa ting wage differentials required by workers to accept riskier jobs have grown, while workpl ace risks have declined, resulting in VSLs that have grown over time. Liu and Ha mmitt (1997) have likewise found that the compensating wage differentials have grow n in Taiwan over 16 years, resulting in progressively larger VSLs.

35Page 7-29, line 18 – 19: The Ashenfelter a nd Greenstone (2004) st udy is not a hedonics type of study! It’s a revealed preference study of agency choices from which a VSL is

inferred.

Page 7-30, lines 1-10: Would this section be more appropriate in the valuation of mortality/morbidity section?

Page 7-30: Sources of Risk, first paragraph. It would be useful to cite Eeckhoudt and Hammitt (2001) and also Evans and Smith (2006) who expanded on the notion of competing v. specific risks.

Page 7-31, Lines 36-38: Please explain the fo llowing sentence: “For example, if perceived risks are found to be lower than expert risk estimates, then WTP can be estimated with the lower, perc eived risk (Blomquist, 2004).”

Page 7-35, Line 44: strike “with minimal additional assumptions”.

Page 7-39, Line 29: change “experience, espe cially...” to read “experience in postedprice markets, especially...”

Page 7-39, Line 12: John Quiggin prefers to spell his last name “Quiggin” and not “Quiggen.”

Page 7-39, Lines 2-5: Better to say statistical precision than efficiency. As I understand it, efficiency refers to making most use of info rmation available in the data; it is not for comparing different datasets.

Page 7-39, Lines 38-42: Can you pl ease provide some more recen t applications of statedpreference studies using “multi-attribute choice questions?”

Page 7-40, Lines 37-41: Suggesting that ch oice questions allow someone to “express support for a program” is counter to the goal of using this method to estimate an actual WTP (not some general notion of “support”).

Pages 7-40 to 7-43: Much of the material feels old and outdated... Assertions about the properties of SP data and the influence of survey design on SP responses are introduced throughout the stated preference section wit hout proper citations to supporting evidence (e.g., page 7-39, lines 27-36, lin es 31-33, and lines 34-36).

Page 7-42, Lines 2-10: The sect ion on Criterion validity over-simp lifies the issues. First, for public goods, what is meant by market da ta? (voluntary cont ributions markets? political markets?) One should note that theo retically demand revealing mechanisms for public goods are difficult to implement (e.g., Groves-Ledyard), which makes testing the validity of SP surveys for public goods that mu ch more difficult. There have been some studies which compare hypothetical voting on a public good to later actual referenda on

36such goods (e.g. Johnston, 2006,) – but this type of criterion test will not generally be available for the policy outcomes being considered by the EPA.

Page 7-42, lines 12-28: For st udies that focus on policy-relevant outcomes for the EPA, convergent validity tests will generally not be available (since the goods being considered are not actually “deliverable” by the resear cher). Even if similar goods could be delivered, if they are public goods it will be difficult to assure the RP (actual transaction)

data are free from biases associated with public good provi sion. (This comment essentially reiterates the comment above for lines 2-10 on the same page.)

Page 7-43: Survey non-response bias is “creat ed by those who refuse to take the survey” only if their WTP is systematically different from that of those persons who did take the survey. Please make this point clear.

Page 7-44, Line 14, etc.: I don’t like the emphasis on doing a new study for each endpoint, since I think that RP & SP studies have so many validity/reliability concerns. On the contrary, I think we are on much st ronger grounds having seve ral studies that are relevant from which we can transfer estimates. This may depend on endpoint – for VSL, I want to know what multiple studies say; for some unique ecosystem, I would not care so much about estimated values for effects on other ecosystems.

Page 8-5, Line 44: “In real ity, deadweight losses already exist in many if not most markets as a result of taxes, regulations, a nd other distortions” But presumably, in many cases the regulation will have the goal of correcting existing distortions, such as external costs of pollution. The term “deadweight lo ss” here is not rea lly a loss if you are considering policies designed to correct externalities. Althou gh the report recognizes that benefits of pollution reduction need to be considered, the term “l oss” is not really appropriate here. This is more an issue of terminology, rather than substance.

Section 8.1.1: One of the down sides of par tial equilibrium approaches is the possibility of "double counting" impacts. To this end, a clear warning or explanation of doubling counting should be included in the discussion in chapter 9 or chapter 8. Double counting occurs if the outputs from firms operating upstream and downstream are both impacted by the new policy and the impacts are considered separately. The impact on the downstream firm is typically passed on to th e upstream firm. For a simple example, consider a fuel policy affecting both a deliv ery business and a loca l production business.

If one of the local busine ss inputs comes from the deliv ery business and the policies impact on the local business through this input is including in the partial equilibrium adjustment for the local business, any part ial equilibrium analysis for the delivery business should account for this. This warning is especially of interest because the apparent interest in CGE analysis may lead an analyst to estimate multiple partial equilibrium models in place of a CGE due to their relative difficulty.

Section 8.1.3: I wouldn’t use the term “ec onomic impacts” since that term generally refers to Economic Impact Analysis, so the term might be incorrectly interpreted. Why

not “economic effects”.

37Section 8.2.1: Alternative Con cepts of Cost. The discussion in this section is confusing. If I understand it correctly, thes e are not alternative concepts of costs, but rather are categories of cost. If properly defined, th ese categories are simply decompositions of social cost, not “alternative concepts”. Do es this Section intend to indicate that, for efficiency purposes, only total social costs matter, but decompositions of social cost could provide information on the incidence of costs or the distribut ional consequences? EPA either needs to explain how these categorie s are useful, or if th ey are not useful the discussion could simply be dropped.

Section 8.3.2.1: The report should be more c onsistent in differentiating between benefits and costs. For example, this section refers to things like “irreversible environmental impacts” as a cost. While it is true that th ere is no true distinction between costs and negative benefits (e.g., irreve rsible environmental impact s), the report has separate sections on costs and benefits, and the discus sion should be kept c onsistent by including

environmental values in the benefits section.

Section 8.4.4: Input-Output analysis doesn’t really belong in this section, since it does not provide a well defined measure of ec onomic costs. We recommend that the discussion be moved to Chapter 9 given its close connection to Economic Impact Analysis and distribution acro ss sectors. Note that Input-Output Analysis does not provide a measure of economic costs and benefi ts, but output from an I-O analysis could provide some information on how economic effects are distributed across sectors of the

economy.

Section 8.2.3. Shouldn’t this Se ction refer to “Distributi on of Costs” rather than

“Distributional Costs”

Page. 9-1. Footnote 179—avoidi ng double-counting likely needs more discussion and an example to illuminate the issue.

Page 9-7 and Table 2: Data sources for profiles I would like to add The Thomas Registry is another data source. The Thomas Register , which dates back to 1906, is used primarily by purchasing agents. Lavin [1992] states that the Thomas Register is the best example of a directory which provides informa tion on manufacturers by focusing on products. According to Lavin, “The Thomas Register is a comprehensive, detailed guide to the full range of products manufactured in the Un ited States. Covering only manufacturing companies, it strives for a complete represen tation within that scope.” The EPA should also see the many other types of sources of business information discussed in Lavin, M. R., 1992, Business Information: How to Find It, How to Use It, 2nd ed. (Oryx Press, Phoenix).

Page 9-9, Line 15. They basically punt on pass-through. Perhaps more direction on what

to do when basic elasticities are not available.

38Page 9-9, Lines 41-42. Is this a cost or benefit? I see it as a net benefit that should be

estimated somehow.

Page 9-9, Footnote 192: This then leads to the producers of e quipment to dig out the coal being hurt. Be clear about how far down the chain we go.

Page 9-12, Lines 20-22: Regional analysis. Lacks a thorough discussion of regional economies and trade. In this way the doc ument can update FN 204 by including work of Copeland and Taylor and Greenstone.

Page 9-16, Lines 10-12: Anothe r indicator that could be co nsidered at the community

level is the foreclosure rate.

Page 9-18, Lines 1-8: This ge ts us back to the proper coun terfactual. In this example they merely discuss the direct cost of th e regulation without recognizing that these expenditures have other benefits and costs. For example, they confer tax breaks (complying with regulations is a deductible expense) and that th e new capital is more productive than old capital. But a key consider ation is whether, and to what extent, the displacement of investment leads this new cap ital to be less produc tive than innovation that it displaced.

Page 9-18 - 9-20: Some mention should concern temporal aspects of benefits and costs. For example, the entirety of Ch. 9 contains s ections on equity issues for an analysis to consider. In addition to this, a discussion of household movement (Tiebout sorting) may be of interest to account for the long-term equitable distribution. That is, although there may be short run benefits for socially or economically disadvantaged populations, they may not hold in the long run. If these househol ds are not home owners, they may be left out of the gain in benefits if market fo rces result in disadvantage populations moving because the gains remain attached to ho me or land and therefore the owner.

Page 9-23: Textbox “2” should be “9.2”.

Page 9-26: Extra period in box 9.3.

Page 9-29: What is the definition of poor? What about gender? This seems to be a relatively ad hoc list of equity factors, are there other identifying characteristics that might be relevant? What about intergenerationa l equity? .

Page B-4, Footnote 293: Sunstein (1997) and Hammitt and Liu (2004) are more recent

citations.

Page B-7, Footnote 309: Adjustments in the VSL for population characteristics “does imply” (not “may imply”) support for vari ation in protection across the population.

Page A-2, line 4: change “y” to “P” and “x” to “Qd” to be consistent with Figure A.1.

39Page A-2, line 19: insert language so sentence reads “The total WTP is equal to the SUM OF THE marginal WTP for each unit up to Q4”

Figure A.3: “P” on the vertical axis needs a “m ” subscript to be consistent with the text.

Page A-8, line 7: Change sentence to read: “B enefit-cost analysis can also be SEEN as a type of...”

Page A-8, line 8: We suggest st riking “that economists strive to avoid” from the sentence.

Figure A.6: The demand curve could be labele d in the figure direc tly (especially given there is no title for the figure).

Page A-12, line 32: Change “corr ect monetary measures of ut ility change” to read “exact monetary measures of utility change” to be consistent with standard language found in

the literature.

Page A-15, line 12: Strike “However,” -- it is out of place given the preceding sentence.

Figure A.10: Consider changing the title on the horizontal ax is from “Regulation” to “Pollution Abatement” or something similar.

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