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 Board (SAB) Advisory on EPA’s draft Guidelines for 

Preparing Economic Analyses (2008)

Dear Administrator Jackson: 

 EPA’s National Center for Environmental Economics requested that the SAB 

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

Guidelines, originally issued in 2000 and recently updated, represent Agency policy on 

the preparation of economic analysis required by legislative and administrative mandates 

and are intended to provide technical 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 coverage of many topics. In the enclosed 

report, we provide responses to EPA’s charge 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 variety 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 liability, 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 analysis can identify superior policy 

options, EPA’s legal authority defines its menu of choices. This might be done quite 

effectively by using examples from legislation to make the limitations 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 policy choices but this 

framework is nearly irrelevant to contemporary water pollution problems. The section on 

subsidies does not acknowledge that many subsidies in agriculture, car manufacturing, oil 

and gas, etc. are not designed to correct externalities but may in fact worsen them. 

Examples, such as the perverse incentives created by federal subsidies for corn-derived 

ethanol, are needed to illustrate these issues. 

 

 The Guidelines provide scant coverage of the long-standing issue in benefit-cost 

analysis of valuing the benefits of protecting ecological systems and services. 

Monetizing ecosystem services remains an area of significant challenge. The Guidelines

should discuss situations where “non-monetized” benefits are expected to be a significant 

portion of the regulatory outcome including advice for practitioners in this case and 

noting that adherence to formal dollar-based benefit-cost analysis 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 revealed preference methods, stated 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 incentives) 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 location to value changes at another), but readers 

would benefit substantively from a concrete real world example. The Guidelines

enumerate a step-by-step approach for economic impact analysis but again, readers would 

benefit from a specific example from 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 releases from point sources to air and water. 

Given the emergence of climate change as the preeminent environmental threat, EPA will 

need more complex, interdisciplinary analysis to address greenhouse gas mitigation 

including information from the bio-physical sciences, economics and atmospheric 

sciences. Computable general equilibrium (CGE) models, a subject covered well in the 

Guidelines, will be of critical importance but CGE models will likely be wedged in a 

portfolio of models tracking complex processes. EPA’s greenhouse gas lifecycle analysis 

of various fuels (required by Congress in the Energy independence and Security Act of 

2007) is an early example of the daunting analytic 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. 

ii 
 By providing thorough and consistent technical advice regarding the application 

of benefit cost analysis to environmental problems, the Guidelines significantly elevate 

the quality and transparency of the information upon which environmental decisions are 

made. We again applaud EPA for developing these Guidelines and the Agency’s 

commitment to continually revise and improve them. Indeed, we believe these 

Guidelines could serve as a successful model for all state and federal agencies who 

undertake benefit-cost analysis in support of environmental decision making. We greatly 

appreciate the opportunity to provide 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 

iii 
U.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 leave 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, Department of Economics, University of Chicago, Chicago, IL 

Dr. James Opaluch, Professor, Department of Environmental and Natural Resource 

Economics, College of the Environment and Life 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 Professor, 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. 

iv 
Dr. David Zilberman, Professor, Agriculture 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-Director, Environmental Health 

Sciences and Water Resources Center, University 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 Management 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, The Ohio State University, Columbus, OH 

Dr. Thomas Burke, Professor, Department of Health Policy and Management, Johns 

Hopkins Bloomberg School of Public Health, 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, University 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 Engineering, 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 

vi 
Dr. Baruch Fischhoff, Howard Heinz University Professor, Department of Social and 

Decision Sciences, Department of Engineering 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, Lovelace 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 Nuclear and Radiological Engineering 

Program and Director, Environmental Radiation Center, School of Mechanical 

Engineering, Georgia Institute of Technology, Atlanta, GA 

Dr. Agnes Kane, Professor and Chair, Department 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 Pediatrics, Director, Center for Childhood 

Neurotoxicology, Robert Wood Johnson Medical School-UMDNJ, Belle Mead, NJ 

Dr. Jill Lipoti, Director, Division of Environmental 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 Professor Emeritus, University of 

Georgia, Lopez Island, WA 

vii 
Dr. 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 Health, Emory University, Atlanta, GA 

Dr. M. Granger Morgan, Lord Chair Professor in Engineering, Department of 

Engineering and Public Policy, Carnegie 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 Physiological Sciences, Director, 

Center for Environmental and Human Toxicology, University of Florida, Gainesville, FL 

Dr. Joan B. Rose, Professor and Homer Nowlin Chair for Water Research, Department 

of Fisheries and Wildlife, Michigan State University, East Lansing, MI 

Dr. Jonathan M. Samet, Professor and Chair, Department 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 Professor, Department of Civil and 

Environmental Engineering, Co-Director, Center for Global and Regional 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 Economics , Department of Economics , 

W.P Carey School of Business , Arizona 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 

viii 
Systems Engineering, Georgia Institute 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, Stanford 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, California Environmental Protection 

Agency, Oakland, CA 

SCIENCE ADVISORY BOARD STAFF 

Mr. Thomas Miller, Designated Federal Officer, Environmental Protection Agency, 

Washington, D.C. 

ix 
x 

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 Administrator and other officials of the Environmental Protection 

Agency. The SAB is structured to provide balanced, expert assessment of scientific 

matters related to problems facing the Agency. 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........................................................................................................................ 41 
Executive 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. Originally 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 empirical literature support the statements in 

the guidance document on the merits and limitations of the different regulatory and 

non-regulatory approaches discussed in Chapter 4: Regulatory and Non-Regulatory 

Approaches to Pollution Control? 

Yes, the chapter is supported by economic literature; however it too closely 

mimics textbook expositions of environmental economics. In order to make it 

more useful for EPA analysts, we recommend that EPA clarify and discuss the 

specific role that EPA has in policy design and implementation and provide 

guidance for economic analysis done specifically within that context. We also 

recommend a better distinction between efficiency and cost-effectiveness, 

improvements to the discussion of “cap and trade,” a better definition of design 

standards and technology based performance standards and the inclusion of recent 

literature on voluntary approaches and the observability of information. 

2. Do the published economic theory and empirical 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 comprehensive guiding principles for specifying 

the baseline scenario to identify the incremental benefits and costs associated with 

a policy. We recommend that EPA consider 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 than more) scenarios that can provide 

benchmarks for policy analysis. 

3. Do the published economic theory and empirical literature support the statements in 

the guidance document on the treatment of discounting benefits and costs discussed in 

Chapter 6: Discounting Future Benefits and Costs in the following circumstances: 

a. Are the descriptions of fundamental social discounting approaches, 

conceptual conclusions and recommendations consistent with the 

appropriate economic literature on social discounting? Are the correct 

ES-1 
conclusions drawn from the respective literatures on discounting for 

public projects (government spending) and discounting for regulations 

(government-mandated spending)? 

Yes, the descriptions of fundamental discounting approaches, 

conceptual conclusions and recommendations are consistent with 

the appropriate economics literature. We do not believe there are 

significant differences in the approach 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 discounting 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 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 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 quantitative significance 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 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 data 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-2 
d. 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 particular 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 literature? 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 present values using the Newell & 

Pizer approach can be used as one of several alternatives 

(complemented by appropriate caveats 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 some 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 generally 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: those that may have a quantitatively 

significant effect on the conclusions of analysis. 

4. Do the published economic theory and empirical literature support the statements in 

Chapter 7: Analyzing Benefits on the merits and limitations of different valuation 

approaches for the measurement of social benefits 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 and the 

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

amount of recent literature on recreation demand models, combining revealed and 

stated preference, validity and reliability, 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 efforts to update its mortality risk valuation 

ES-3 
approach. 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 complete. In the interim, we recommend EPA 

consider expanding its literature review and discontinue use of old, discredited 

wage-risk studies. 

6. Does Chapter 8: Analyzing Costs contain an objective and reasonable presentation of 

the published economic theory, empirical literature, 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, balanced and reasonable presentation of the 

published economic theory, empirical 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 parameterization of CGE models as well 

as a few minor revisions as discussed in our detailed comments. 

8. Does Chapter 9: Distributional Analyses: Economic Impact Analyses and Equity 

Assessment contain an objective and reasonable 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 changes in market prices, 

profits, facility closure and bankruptcy rates, employment, market structure, 

innovation and economic growth, regional 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 presentation 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? 

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

limitation is that the main distributional issues 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 associated with both benefits and costs are 

ES-4 
ES-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 foundations underlying benefit cost analyses. 

Does Appendix A summarize the relevant literature in an objective and meaningful 

way? Are there topics that warrant (more) discussion in this appendix that were 

otherwise missed? 

The Appendix provides a good discussion of core economic principles. As 

suggestions for improvements, we recommend 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 provide further elaboration. Also, please 

identify any definitions provided in the new glossary that are inaccurate or that 

otherwise need revision. 

In general, we would like to see broader discussion of a number of cross-cutting 

issues. For example, we’d like to see a discussion of the need for transparency in 

making assumptions and judgments and a discussion 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 constraints, imperfect competition and market 

distortions created by taxes and other government policies. The Guidelines sorely 

need case studies and examples to illustrate 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 environmental 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 analysis 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 the SAB EEAC review the revised document. 

The SAB EEAC met on October 23 – 24, 2008 to review draft Guidelines (September 

2008) and respond to NCEE’s specific charge questions. 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 quality review in a 

public teleconference. 

In addition to offering specific responses to charge questions, this Advisory also 

presents some general advice and cross-cutting 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 explain why a benefit-cost analysis is a valuable 

undertaking (other than to satisfy a regulation) and why economic impact and equity 

analyses can be important supplements to benefit-cost analysis, etc. Readers need to see 

a definition of economic efficiency (allocative and technical, which will help in 

explaining the relationship between cost effectiveness and benefit-cost analysis) and an 

explanation of the relationship between economic efficiency, benefit-cost analysis, and 

cost-effectiveness. We also suggest defining social costs and benefits (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 issues. Environmental policy analysis is 

inherently an integrated assessment process in which results from different sciences are 

combined to predict environmental outcomes and their economic consequences. 

Realistically, a great deal of judgment will have 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 efficiency message could be sent. Care should 

also be taken to avoid multiple counting of benefits and costs when there are overlapping 

1 
regulatory initiatives. Clarity and transparency in the specification of the baseline, 

including the regulatory initiatives already 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 for 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 analysis 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-regulatory approach can be as much informed by 

economic analysis as those that are 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 benefit-cost analysis. Although OMB Circular A-4 

does not require that all economic benefits of a policy be monetized, it does require some 

scientific characterization of those 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 cases of unbalanced information). In addition, 

a strong recommendation should be made to provide quantitative measures of ecological 

impacts and a qualitative characterization of ecological 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 Ecological Systems and Services, 2009). The 

SAB report covers a wide range of alternative 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 throughout. It would be 

useful to point out that uncertainty extends not only to economic information, but to 

environmental data and modeling. Uncertainty in environmental modeling can be as 

much or more a source of errors than imperfections 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 that 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 the possibility of 

ensemble modeling (e.g. hydrology and ecology) and the use of a “weight of evidence” 

approach, especially for the case of non-monetized ecological effects. 

2 
 The 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 leading cause of the 

nation’s water quality problems, yet it is less observable than emissions from points 

sources and far more stochastic. Consequently, 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 regulated 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 allocation 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 regulation’s impact. Analysis of the costs of a 

small project may emphasize simple partial equilibrium analysis, while a larger one may 

employ both partial equilibrium and CGE models. Similarly, the selection 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 individual 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 has the potential to change the regulatory 

decision while a study on the impacts of a smaller 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 may be trivial in comparison to potential 

increases in net benefits if the information results in a change to the final regulation or 

policy decision. 

 The Guidelines should discuss the analytic challenges posed by emerging 

environmental problems, particularly 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 processes, invasive 

species, etc. would give the Guidelines a more contemporary and forward looking view. 

The Guidelines should point out (and perhaps demonstrate) 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 based on its calculation of lifecycle greenhouse 

gas emissions for various fuels. This lifecycle 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 

3 
Guidelines could reference this specific example as well as discuss generally the 

interdisciplinary challenges posed by climate change and other global issues. Given the 

specter of climate change and other global processes, 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 revisions will be made easier with NCEE’s adoption 

of a loose leaf format to update chapters as appropriate. 

 

4 
Question 1: Policy Options

Do the published economic theory and empirical literature support the statements in the 

guidance document on the merits and limitations of the different regulatory and nonregulatory approaches discussed in Chapter 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 published 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 role 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 EPA often does not have 

the discretion to choose this option, e.g. when “best available technology” standards are 

required by law. Similarly, after demonstrating that social welfare is maximized by 

choosing the level of pollution that equates marginal 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 involve stating where EPA has discretion to 

make decisions in the context of the larger policy arena and then discussing the rationale 

for the different approaches actually used. That is, EPA primarily issues regulations and 

those regulations are typically highly prescribed by Congressional 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 described here, but clarifying 

EPA’s discretion in setting policy (even if it varies from statute 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 usual treatment of an 

environmental economics text and make it directly relevant to the agency. One way to 

explain EPA’s role is to show some examples 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 for discussion in this chapter is the issue 

of asymmetric information between the regulator (EPA) and the regulated (consumers 

and industry). This issue has ramifications for the design and efficiency of many kinds of 

environmental regulations and its importance should be mentioned. 

Along these same lines, the chapter discusses maximizing welfare without noting 

5 
that in most cases EPA is charged with implementing laws that specify criteria EPA must 

use. EPA’s regulations are not typically based on a calculation of an “optimal” E*, but 

are more tied to legally-defined criteria. Again, the chapter would be improved by 

clarifying how EPA’s actual authority fits into this paradigm. 

This latter point could be nicely integrated into Section 4-1 which could be 

improved by distinguishing efficiency from cost effectiveness. By dividing the section 

into two parts: (i) Efficient Level of Pollution (MD = MACaggregate )∗and (ii) CostEffective Allocation of Pollution – equalize marginal cost across sources (MAC1= 

MAC2= ... = MACn), the distinction between optimality of pollution levels and least cost 

approaches for implementation can be distinguished. Each section will need a supporting 

graph and should be integrated by showing how aggregate MAC is derived from 

individual MACs. See Field and Field (2008) and Baumol and Oates (1988) for dividing 

the discussion this way. Also, in the discussion of the efficient level of pollution, it is 

important to define social welfare using the underpinnings of Pareto Optimality. 

The suggestion in the previous paragraph 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 the 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 the permit allocation is efficient (MD=MAC). 

Use the same approach for the tax in Section 4.3.2. Again, these points can be illustrated 

with the point that EPA typically does not set the optimal level of emissions, but can help 

design and implement instruments to achieve least 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 the 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 technology-based performance standards using the 

cost-effectiveness graph introduced in the previous section. Uniform standards are 

generally not cost effective but have a low information burden (since one need not know 

MACs). Technology-based performance standards 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 important 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 elsewhere? In principle it should be placed 

on damages (a true Pigouvian tax), but administrative and monitoring costs may suggest 

targeting the tax elsewhere. Taxing gas may be much easier and probably as effective as 

 

∗

 MD = marginal damages. MAC = marginal abatement cost 

6 
taxing damages from auto emissions. Similar 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 policy makers can not observe actual pollution 

levels, but inputs and practices that cause pollution can be observed and there are 

reasonable estimates on the relationship between the input, technology 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 policy 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 heterogeneity relative to uniform policies (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 taxation based on annual pollution rather than 

imputed pollution. Policy makers should reassess policy design and implementation as 

technology progresses. (See Xabadia et. al., 2008) as one example. There are many other 

papers that demonstrate the efficiency 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 second best solutions in the relevant sections 

and refer readers to the material in the cross cutting issues discussion. Examples include 

monopoly, price supports in agriculture, pre-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 least costly, have a low information burden on 

regulators, provide incentives for technological advancement, and so forth. Monitoring 

and enforcement costs and other administrative costs, of course, can favor direct 

regulation. 

It would be helpful to mention that information disclosure strategies can allow the 

market to create incentives for pollution control (following Coase) with the victims 

directly signaling their preferences to firms. But these are most likely to work when there 

are contractual obligations between polluting firms and affected parties (e.g. 

consumers/workers) and more difficult to work when they affect third parties (see 

Tietenberg, 1998). Also it should 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 

7 
those in agriculture, car manufacturing, oil and gas, forestry, and so forth, are not 

corrective subsidies designed to correct externalities 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 articles). These should be noted 

and made a part of the section on voluntary controls. 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 program 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 achieve the same level of pollution 

control would be valuable for assessing the cost-effectiveness of voluntary approaches. 

8 
Question 2: Baselines 

Do the published economic theory and empirical 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 chapter provides very 

comprehensive guiding principles for specifying the baseline scenario to identify the 

incremental benefits and costs 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 comparison. It suggests that in 

some cases it may be appropriate to specify multiple baseline scenarios to describe the 

state of the world in the absence 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 certainty, 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 appropriate to use probabilistic 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. Although 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 included in the baseline. Some policies can have 

pecuniary effects that will affect the opportunity costs of implementing 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 with the existing and newly enacted 

regulations does not appear realistic. Instead, compliance rates in the baseline should be 

based on available factual evidence. Assumptions about compliance 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 distinguishing the induced 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 distinguish between its strong form and weak form. 

The strong form of the Porter Hypothesis states that regulations can induce innovations 

that can lead to cost savings that are larger than the costs of the innovation and 

compliance. The weak form of the Porter Hypothesis simply states that environmental 

regulations lead to innovation. We agree with the statement that there is only limited 

evidence of the strong version of the Porter Hypothesis; some references to the literature 

providing situations in which it might hold (such as in the presence of imperfect 

information, high search costs, etc.) could be added. There is much more evidence to 

9 
support the weak form of the Porter Hypothesis (which is similar to the induced 

innovation hypothesis) and this should be made clear. 

10 
Question 3: Discounting 

Do the published economic theory and empirical literature support the statements in the 

guidance document on the treatment of discounting benefits and costs discussed in 

Chapter 6: Discounting Future Benefits and Costs? (sub parts for this charge are copied 

below) 

Overall, the chapter provides a clear and comprehensive discussion of 

discounting. This chapter has been updated to reflect much of the current thinking on 

discounting in the context of environmental 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, and 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 they 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 run (“intra-generational”) and long run (“intergenerational”) discounting that arise in part because inter-generational contexts 

necessarily involve a greater distributional aspect and future generations are not 

represented in markets; (b) sensitivity of results to choice of discounting approach and 

discount rate; (c) distinction (and frequent confounding) of efficiency and distributional 

issues; (d) distinction between utility vs. consumption discount rates; (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) discounting approaches; and (perhaps) (g) future changes in 

relative prices that imply different consumption discount rates for different goods. 

Although it is implicit in the text, the distinction between discounting to reflect 

differences in timing of consequences and discounting to adjust for 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 rate depends on the inflation 

adjuster that is used.) 

There is much confusion in the literature (and in policy discussion) about the 

determinants of the discount rate, e.g., whether it is a result of preferences for 

consumption sooner rather than later or of the productivity of capital investment. At least 

for “intra-generational” discounting, 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 

11 
present 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 consumption so that their indifference curves for 

current and future consumption are tangent to the market opportunities for shifting 

consumption through time (determined by the interest rate). As noted in the chapter, a 

variety of interest rates exist (associated with 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 interest rates for periods longer 

than about 30 years rarely exist and future generations’ do not directly 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., descriptive) 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 attempts 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, economic evaluation is also sometimes justified as identifying 

policies that produce potential Pareto improvements, i.e., policies such that all members 

of the affected population would prefer to the alternative policy (if combined with 

appropriate compensation payments). Policies that increase social welfare are not 

necessarily potential Pareto improvements, that those that are potential Pareto 

improvements need not increase social welfare. Moreover, individual behavior that is 

inconsistent with maximization of individual utility (e.g., behavior that is dynamically 

inconsistent, perhaps because it accords with hyperbolic discounting) creates a tension 

between these perspectives and raises questions about how to conduct the analysis. See 

Hammitt (2009, 2002) and Portney (1992). 

 

a. Are the descriptions of fundamental social discounting approaches, conceptual 

conclusions and recommendations consistent with the appropriate economic literature on 

social discounting? Are the correct conclusions drawn from the respective literatures on 

discounting for public projects (government spending) and discounting for regulations 

(government-mandated spending)? 

The descriptions of fundamental social discounting approaches, conceptual 

conclusions and recommendations are consistent with the appropriate economics 

literature. We do not believe there are significant differences in the approach to 

discounting for public projects (government spending) and discounting for regulations 

(government-mandated spending) – in both cases, there can be a need to account for 

differences in timing of benefits and costs and the relevant conceptual basis is social 

valuation of consequences at different points in time. 

12 
b. The Guidelines do not draw a firm conclusion 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 situations where these adjustments would be 

necessary or unnecessary? 

As noted in the chapter, the shadow-price of capital approach is viewed as 

theoretically correct, but the quantitative significance 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 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 data or methods for estimating a consumptionbased discount rate, and doubt that alternative credible estimates would differ 

dramatically from the 3% 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. 

d. 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 particular 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 literature? More specifically, is the recommendation to 

use a random walk model as a default reasonable 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-generational discounting. Since the declining discount 

rates under this approach are sensitive to modeling assumptions, transparency in the 

assumptions underlying the determination of the discount rates used will 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 the 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 discount 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 

13 
the two discount factors may be small, but as t becomes arbitrarily large the expected 

discount factor approaches the discount factor corresponding to the minimum possible 

value of r weighted by the probability assigned to that minimum value. Weitzman 

developed a distribution for r by polling economists and derived a corresponding 

schedule of certainty-equivalent discount rates (the discount rate associated with the 

expected discount factor); Newell and Pizer built on his work by conducting an empirical 

analysis of historical interest rates. Their results are naturally sensitive to modeling 

choices about the intertemporal correlation of rates. 

Our concern about this approach is the following. In a world with no uncertainty 

about the discount rate, one can compare streams of consequences in terms of their 

present values or their future values at any future date. The choice between these 

perspectives has no effect on the ranking: because the present value of a policy is simply 

the present value of the policy’s future value (i.e., the future value discounted to the 

present), whichever policy has the larger present 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 largest possible values of 

r). This dependence of the evaluation 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 investigation (Gollier, 2004; Hepburn and Groom, 2007). Given this 

concern, we urge caution in interpretation of results calculated using the Newell and Pizer 

approach and encourage further investigation. 

e. EPA has struggled with the question of the length of time an analysis should 

capture and has arrived at some 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? 

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: those that 

may have a quantitatively significant effect on the conclusions of analysis (as noted in 

Section 6.1.6.3). With positive discounting, the influence of consequences decreases with 

their temporal distance; unless 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 whether 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 often sufficient. As noted in the text, many 

exogenous factors are likely to influence the date at which the effects of the policy 

become negligible (e.g., technological innovation or policy change). 

14 
Question 4: Benefits

Do the published economic theory and empirical literature support the statements in 

Chapter 7: Analyzing Benefits on the merits and limitations of different valuation 

approaches for the measurement of social benefits 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 regulations, and of the methods used to estimate them. The 

chapter might flow better if the discussion of the main categories of benefits was more 

concise, and more details about the valuation 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 pages, we identify a number of areas where the 

literature of the past decade or so is not adequately reflected in the chapter. We have not 

made an effort to be exhaustive in recommending 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, identification 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 Guidelines 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 Stated 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 performance of welfare estimators. On the 

theoretical front, Herriges and Kling, (1999) raise the question of whether revealed 

preferences can ever accurately 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 preference 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 

15 
mitigate these effects are successful remain important researchable questions. 

Considerable work on this question has been 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 question. 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 specifically 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 choice experiment-based studies are not 

conducted in ways that would preserve incentive compatibility, some limited 

evidence exists suggesting little 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 studies 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 existing estimates of morbidity benefits. Is 

the usual approach—symptom days—still judged acceptable? Likewise, this 

section points out that frequently used approaches, 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, even for minor acute respiratory illnesses (as 

in Alberini and Krupnick’s case). 

6. Ecosystem Services and Benefits Assessment. The literature review is outdated, 

and there are no examples of recent studies that attempted to place a value on 

ecosystems and ecosystem services. It would 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. 

16 
Ecosystem services encompass a broad array of goods and services, 

ranging from standard market goods like 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 policy of interest to the direct 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 context of policy decisions that 

EPA needs to make. A variety of techniques 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 approaches include cost effectiveness 

analyses, choice-based methods (e.g., Opaluch 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 can 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 qualitative characterization of ecological effects. These 

quantitative measures and qualitative descriptions are needed whether or not 

benefits can be monetized. We note that EPA’s Office of Research and 

Development has an extensive Ecosystem Services 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 ecosystem and ecosystem services and map 

those effects to services or attributes that the public values (Valuing the 

Protection of Ecological Systems and Services, SAB, 2009). The SAB report 

17 
covers a wide range of alternative 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 

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 economic benefits,” not “total benefits.” 

We believe the SAB report provides other 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 (page 7-41) as the basis for choosing among 

studies for inclusion in a benefit-cost analysis, but the treatment of the validity and 

reliability of estimation methods is uneven. Much 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 preference methods should be scrutinized for quality 

and validity, as should CGE models. 

The material in Sections 7.4.2.3 “Considerations 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 convergent) discussed on 7-41 – 7-42 apply to all 

types of studies, not just stated preference, as do various biases associated with survey 

non-response (7-42 – 7-43). Other validity concepts that should be discussed include: 

• Internal Validity: is there plausibly exogenous variation in the variable of 

interest (the one capturing health risks or environmental quality)? 

• External Validity: Can the study’s results 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 treatment relevant for the program that is 

under consideration? 

• Theoretical Validity: Can the study’s results 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 should note that flaws of both stated preference 

(SP) and revealed preference (RP) should be considered when evaluating studies and 

performing regulatory analysis. For example, most hedonic properties, compensating 

wage differentials and other revealed preference studies assume, without testing, that 

people know the correct risks or level of environmental quality. 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, validity questions related to stated preference 

studies are a limitation that should be not disguised or diminished. It would be useful to 

emphasize that judgment is essential to good analysis and that the results from stated (and 

revealed) preference studies should be carefully assessed with economics and commonsense basics. For example, is WTP for a change in environmental quality a reasonable 

18 
fraction 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 assumptions. 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 population of beneficiaries to which we are 

applying the transfer has potentially 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 transfer” 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 that 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: similarity of environmental good valued in original study to 

environmental good being valued in benefits transfer; 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 experts 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 values, 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. 

 

19 
Question 5: Mortality Risk Valuation 

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 efforts to update its mortality risk valuation approach. In 

the interim, are the discussions provided in Chapter 7 and Appendix B clear and 

balanced? 

We will refrain from extensive comments on mortality risk valuation until the 

Agency’s update is complete. In the meantime, 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 mortality 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, and stated preference). It also does a good job 

discussing factors—such as age and pre-existing conditions—that matter with 

environmental exposures and may affect the VSL. The chapter does, however, overlook 

Viscusi and Aldy (2007), who look at age and the VSL in a wage-risk context. It could 

also include discussion of alternative methods for estimating VSL such as the “chained” 

approach linking WTP to reduce non-fatal injury 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 data, i.e., risk levels 

that are no longer likely to exist and obsolete preferences for risk and income; they are 

based on cross sections of data, do not control 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 better risk measures are Kneisner, 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 illnesses (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 studies 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), Ashenfelter and Greenstone (2004), Gayer et al. 

(2000)) and others. Likewise, there are newer stated preference studies that infer values 

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

examples). 

In several places, the Agency refers to the importance of “the impacts of risk and 

population characteristics” on valuation estimates (e.g., p. 7-6, line 36; p. 7-8, line 31-43; 

p. B-4, lines 29-32), yet the discussion is generally focused on population characteristics. 

The agency should consider adding more discussion about the impact of risk 

characteristics on valuation, the newer literature valuing the events of relevance to 

environmental policy, and relate these issues to its recommended default value. 

 

21 
Question 6: Social Costs 

Does Chapter 8: Analyzing Costs contain an objective and reasonable presentation of the 

published economic theory, empirical literature, and analytic tools associated with 

estimating social costs? 

In general, the Chapter does contain an objective and reasonable 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 reflects the industry’s cost of capital.” While this quote is 

correct, we fear that it could be misinterpreted to suggest that costs and benefits might be 

legitimately discounted at different rates within 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 decision would be reversed, implying a form of 

time inconsistency. The Guidance should be written 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 estimating 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 anticipated, but in practice deviations from expected 

outcomes often mean higher than anticipated costs. These challenges can be exacerbated 

since industry often has more information about costs than regulators 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, page 8-5). For example, the report could 

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

22 
how multimarket analyses should be carried out. The Just, Hueth and Schmitz textbook 

provides a thorough treatment of these issues, and could be both the source of 

information for the document summary and an excellent reference for further 

information. 

It is important to note that it is not simply 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 adequate. Indeed, the first example under CGE 

(Sec 8.1.2) is of a single but large market (electric 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 markets 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 with 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 likely be spent on abatement-related purchases from 

other industries – and is thus not necessarily a loss to society – in this market, the 

deadweight loss resulting from the regulation is lost completely.” It should be made clear 

that expenditures in other markets are losses to society except for the portion that is a 

quasi-rent. We are concerned this passage could 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 appropriate 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 best” conditions in the Guidelines. With respect to costs, 

results will differ significantly in a non-competitive market, or in a market where there 

are other distortions. In general, a complex game theoretic formulation is needed to 

assess effects in markets that are not perfectly competitive. 

23 
Question 7: CGE Models 

Does Chapter 8 contain an objective, balanced and reasonable presentation of the 

published economic theory, empirical 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 weaknesses, 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 equilibrium 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 historical record. A paragraph on 

parameterization should be added to the section. A brief discussion of parameterization 

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

Secondly, the Guidelines’ discussions of CGE modeling in general and the 

concept of general equilibrium welfare analysis in particular should be expanded to 

address the role of models that introduce pollution (or equivalently environmental 

services) in non-separable specifications for consumer preferences. Such specifications 

introduce the prospect for feedback effects where policies to reduce externalities lead to 

changes in the demand for market goods and then 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 continue with the models describing systems 

where the market and non-market interactions affect the ultimate market equilibrium. It is 

important to draw distinctions between sorting models with multiple markets and what 

might be described as extended partial equilibrium analyses and CGE models. Recent 

advances in both types of models 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 minor revisions as well. First, the 

discussion at the beginning of Section 8.1.2 should emphasize 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 significant effects in a single market, but if the 

market is large enough (the labor market, for example), general equilibrium analysis 

would still be warranted. Similarly, a policy affecting a large number of very small 

markets might be adequately addressed by partial equilibrium analysis. 

24 
 A second minor revision is that the discussion of the benefits of dynamic models 

should be expanded slightly. Not only are such 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 effects: changes in 

behavior occurring when policies are announced that 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 expanded slightly and the conclusion 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 substitution elasticities that reflect medium to long 

run behavior. However, those are characteristics 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, models 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 CGE models are not designed for analyzing 

short-run transitional costs, rather than it being a problem inherent in the methodology. 

Finally, because CGE models differ considerably from one another in design and 

parameterization, it is valuable to use multiple models when possible, especially for 

policies expected to have very large effects 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 reliability 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. 

25 
Question 8: Distributional Analyses 

Does Chapter 9: Distributional Analyses: Economic Impact Analyses and Equity 

Assessment contain an objective and reasonable 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 changes in market prices, profits, facility 

closure and bankruptcy rates, employment, market structure, innovation and economic 

growth, regional economies, and foreign trade. 

Chapter 9 contains an objective presentation of many of the aspects of economic 

impact analyses (EIA). It tackles market prices, profits, facility closures, unemployment, 

market structure, innovation, and growth. Although Chapter 9 contains information on 

estimating the economic impact of policies, discussing three approaches 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 and CGE may further the reader’s understanding 

of why these are more effective than the direct compliance costs. Also, augmenting the 

warning of the complexity of CGE modeling may be worthwhile. 

While there is attention to the implementation 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 benefits chapter is the "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 economic benefits and costs. In addition, it 

might be pointed out that I-O models ignore opportunity cost of resources, implicitly 

assuming that inputs used in some new activity 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 induced effects of an activity. A proper measure 

of benefits would account for the opportunity costs 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. 

26 
Question 9: Measuring Equity Effects 

Does this chapter contain a reasonable presentation 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 reasonably 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 understanding 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 information 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 chapter 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 aspects 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 distributional issues that are discussed in 

this chapter relate to the cost side: i) direct compliance expenditures (p. 9-17), ii) indirect 

costs (taking into account multipliers, GE effects, etc.), and iii) enforcement costs. The 

bulk of the chapter relates to direct compliance 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 considering the distributional 

effects of benefits of an environmental change. The costs of identifying the distribution of 

benefits may be much more data intensive and costly than identifying 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 associated with both benefits 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. 

27 
Question 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 literature in an objective and meaningful way? Are 

there topics that warrant (more) discussion in this appendix that were otherwise missed? 

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

foundations relevant to benefit-cost analysis with two exceptions. First, a discussion 

explaining the distinction between stock and flow pollutants should be added. A stock 

pollutant is an unwanted byproduct of production 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 pollutant and does not consider the general case where the 

damage comes the accumulated stock of the pollutant. This distinction can be important 

when undertaking benefit-cost analysis for pollution reduction as the form of the damage 

function differs. Since greenhouse gases are a prominent and potentially catastrophic 

stock pollutant, this is an especially 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 resource. 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. 

28 
Question 11: Omissions 

Please identify and enumerate any inconsistencies you may find across chapters and 

other issues/topics on which we should provide 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 nonmarket goods is not adequately covered in 

the Guidelines. The discussion of costs, for example, generally assumes a closed 

economy without international competition. The discussion of policy instruments 

focuses exclusively on the management of “internal” externalities. 

Dynamics are another issue receiving inadequate attention in the Guidelines, 

although dynamic models are discussed in the CGE chapter. Dynamics become relevant 

to policy analysis, and to estimation of benefits and costs in several contexts. One 

context is stock pollution problems, climate change being the leading example. Another 

is when the costs of pollution control or the benefits of pollution 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 damaged by pollution have capital adjustment costs 

in adapting to environmental conditions, and when environmental conditions induce 

innovations among those who are damaged. Dynamics in these contexts are important in 

benefit and cost estimation. 

29 
Appendix: 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 for 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 discusses merits of various approaches. 

Section 4.1: Divide this section into two parts: (i) Efficient 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 derived 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 underpinnings of Pareto 

Optimality. In the discussion of efficient level 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 and (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 introduced in previous section. Uniform standards are not 

cost effective but have a low information burden (do not need to know MACs) and 

technology-based performance standards are cost effective in principle but have a high 

information burden (need to know MACs). 

Page 4-6, Lines 2-4: Definition of Command 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 directly 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 incorrect. 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: they tend to be least costly, have a low 

information burden on regulators, and provide incentives for technological advancement. 

Monitoring and enforcement costs and other administrative costs, of course, can favor 

direct regulation. 

30 
Page 4-8, Coase Box: Even when the conditions mentioned in the opening sentence of 

the third paragraph of the Coase Box are met, the Coasian solution may not be reached 

due to asymmetric information and bargaining strategies (ala principle-agent theory) 

followed by the parties to the transaction. Please 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 meant 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. Also, 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 targeting the tax. Do you target the tax on the 

pollutant, input, process, or elsewhere? In principle you should place it on damages, but 

administrative and monitoring costs may suggest targeting elsewhere. Taxing gas is much 

easier and probably as effective as taxing damages from auto emissions. 

Somewhat related to the previous point, please note that policy design is dependent on 

observable and available information. For example if the policy makers can not observe 

actual pollution levels but inputs and practices that cause pollution can be observed and 

there are reasonable estimates on relationship 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 knowledge. 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 policy 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). Availability of new sources of or means to obtain 

information may lead to redesign of policies – for example, availability of a technology 

31 
of cheap monitoring of pollution may lead to regulation on taxation based on annual 

pollution rather than imputed pollution. Policy makers should reassess policy design and 

implementation as technology progresses. See Xabadia, Angels, Goetz, Renan-Ulrich and 

Zilberman, David, “The Gains from Differentiated 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 and (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 “However, 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 other 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 information disclosure strategies can allow the market create 

incentives for pollution control (following Coase) with the victims directly signaling their 

preferences to firms. But these are most likely to work when there are contractual 

obligations between polluting firms and affected parties (e.g. consumers/workers) and 

more difficult to work when they affect third parties (see Tietenberg, “Disclosure 

Strategies for Pollution Control,” Environmental 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 disclosure 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 section into the market incentive 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 shows the types of firms that had incentives 

to improve environmental performance following negative stock market returns is 

Khanna, M., W. Quimio, and D. Bojilova, “Toxic 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 than it does information disclosure. It has 

not really been mentioned until now and is different than information disclosure. 

Consider bringing information provision into chapter. There may be a under provision of 

32 
information 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, then 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 section. Also, the “degree of uncertainty” is 

given as a factor in choosing among policies. This is not technically 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 incorrect 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 say that most voluntary programs set goals (line 

37). They also do not make it simpler to monitor and measure if participants are meeting 

the goal – most voluntary programs do not require firms to provide emissions data to the 

EPA (for a review of these issues and comparison of programs see Khanna, M. and D.T. 

Ramirez, “Effectiveness of Voluntary Approaches: 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 are a little outdated. A 

more recent and updated citation on motivations to participate in different types of 

voluntary programs, challenges in evaluating their effectiveness and evidence about their 

effectiveness is Khanna, M. and K. Brouhle, “Effectiveness of Voluntary 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 think there is merit to these documents, I have 

reservations about fully endorsing them because there is economically flawed advice 

about some design elements. This box also misses an opportunity to discuss the 

importance of economic science to the design of markets. Contemporary water quality 

markets fail to achieve the promise of trading because of participation and coordination 

failures that occur in part because of flaws in market design and development. On 

balance, I recommend dropping the box. 

 

Page 5-2, Line 29: Recommending that the analyst 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 and future state of economic variables that are 

relevant for the analysis. 

33 
Page 5-8, Lines 1-4. The Guidelines mention that regulations can lead to innovation 

(which may not occur in the baseline) 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 assuming differing rates of technological innovation 

based on regulatory stringency. That last statement (line 4) is incorrect and should be 

deleted. Instead there should be a brief discussion about the potential for induced 

innovation due to environmental regulations. Regulations can create incentives for 

technological innovation that lower 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 correction, 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 that 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). This is understandable (as 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 mentions 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-fatal 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., medical care expenses paid by insurance 

or public sources). The existence of externally paid costs does not mean the individual 

“understates” own WTP. 

Page 7-17, Lines 2-4: I guess this statement 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 

34 
don’t want to make too much of the analytic cost point – seems to me that analytic costs 

are very small compared with B and C of the major regulations we’re mostly considering 

(e.g., >100 M/yr for many years). 

Page 7-19, Lines 15-16: It would 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 reduce 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 subcomponents). In other cases 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 recreational site is 

itself enjoyable? After all, in some cases much of the benefit of travel 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 sentence. We have no compelling evidence that 

instantaneous workplace deaths reflect the same tradeoffs that individuals 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 Kniesner (2003) uses only risk measures 

known be fraught with measurement errors (even the “best” data was based on 

inconsistent reporting of deaths (see Drudi, 1997) and aggregated in a manner that creates 

serious endogeneity problems (see Leigh, 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 studies needs to be updated with recent results by 

Kniesner et al. (2007) and Viscusi and Aldy (2007). 

Page 7-28: Text on hedonics. What’s the point of placing the discussion 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 sources and of the level of resolution of the 

workplace risk data. 

Page 7-28: Disagree with “Further, 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 compensating wage differentials required by workers 

to accept riskier jobs have grown, while workplace risks have declined, resulting in VSLs 

that have grown over time. Liu and Hammitt (1997) have likewise found that the 

compensating wage differentials have grown in Taiwan over 16 years, resulting in 

progressively larger VSLs. 

35 
Page 7-29, line 18 – 19: The Ashenfelter and Greenstone (2004) study 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 following sentence: “For example, if 

perceived risks are found to be lower than expert risk estimates, then WTP can be 

estimated with the lower, perceived risk (Blomquist, 2004).” 

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

Page 7-39, Line 29: change “experience, especially...” 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 information available in the data; it is not for 

comparing different datasets. 

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

Page 7-40, Lines 37-41: Suggesting that choice 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 without proper citations to supporting evidence 

(e.g., page 7-39, lines 27-36, lines 31-33, and lines 34-36). 

Page 7-42, Lines 2-10: The section on Criterion validity over-simplifies the issues. First, 

for public goods, what is meant by market data? (voluntary contributions markets? 

political markets?) One should note that theoretically 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 much more difficult. There have been some 

studies which compare hypothetical voting on a public good to later actual referenda on 

36 
such 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 studies 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 researcher). 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 provision. (This comment 

essentially reiterates the comment above for lines 2-10 on the same page.) 

Page 7-43: Survey non-response bias is “created 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 stronger grounds having several 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 reality, deadweight losses already exist in many if not most 

markets as a result of taxes, regulations, and 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 loss” here is not really a loss if you are 

considering policies designed to correct externalities. Although the report recognizes that 

benefits of pollution reduction need to be considered, the term “loss” 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 partial 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 the upstream firm. For a simple example, 

consider a fuel policy affecting both a delivery business and a local production business. 

If one of the local business inputs comes from the delivery business and the policies 

impact on the local business through this input is including in the partial equilibrium 

adjustment for the local business, any partial 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 “economic impacts” since that term generally 

refers to Economic Impact Analysis, so the term might be incorrectly interpreted. Why 

not “economic effects”. 

37 
Section 8.2.1: Alternative Concepts of Cost. The discussion in this section is confusing. 

If I understand it correctly, these are not alternative concepts of costs, but rather are 

categories of cost. If properly defined, these categories are simply decompositions of 

social cost, not “alternative concepts”. Does 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 distributional consequences? 

EPA either needs to explain how these categories are useful, or if they are not useful the 

discussion could simply be dropped. 

Section 8.3.2.1: The report should be more consistent 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 there is no true distinction between costs and 

negative benefits (e.g., irreversible environmental impacts), the report has separate 

sections on costs and benefits, and the discussion should be kept consistent 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 economic costs. We recommend that the 

discussion be moved to Chapter 9 given its close connection to Economic Impact 

Analysis and distribution across sectors. Note that Input-Output Analysis does not 

provide a measure of economic costs and benefits, 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 Section refer to “Distribution of Costs” rather than 

“Distributional Costs” 

Page. 9-1. Footnote 179—avoiding 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 information 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 United States. Covering only manufacturing 

companies, it strives for a complete representation 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. 

38 
Page 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 equipment 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 document can update FN 204 by including work of 

Copeland and Taylor and Greenstone. 

Page 9-16, Lines 10-12: Another indicator that could be considered at the community 

level is the foreclosure rate. 

Page 9-18, Lines 1-8: This gets us back to the proper counterfactual. In this example 

they merely discuss the direct cost of the 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 the new capital is more 

productive than old capital. But a key consideration is whether, and to what extent, the 

displacement of investment leads this new capital to be less productive 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 sections 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 households are not home owners, they may be left 

out of the gain in benefits if market forces result in disadvantage populations moving 

because the gains remain attached to home 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 intergenerational 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 variation 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. 

39 
Page 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: “Benefit-cost analysis can also be SEEN as a 

type of...” 

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

Figure A.6: The demand curve could be labeled in the figure directly (especially given 

there is no title for the figure). 

Page A-12, line 32: Change “correct monetary measures of utility 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 axis from “Regulation” to 

“Pollution Abatement” or something similar. 

40 
References 

Adamowicz, W., P. Boxall, M. Williams, and J. Louviere. (1998) “Stated preference 

approaches for measuring passive use values: Choice experiments and contingent 

valuation”. American Journal of Agricultural Economics 80:64-75. 

Alberini, Anna and Alan Krupnick. (2000) “Cost-of-Illness and WTP Estimates of the 

Benefits of Improved Air Quality: Evidence from Taiwan,” Land Economics 76(1), 37-

53. 

Alberini, Anna and Aline Chiabai. (2007) “Urban Environmental Health and Sensitive 

Populations: How Much Are the Italians Willing to Pay to Reduce their Risks?” Regional 

Science and Urban Economics 37(2), 239-258. 

Ashenfelter, O. and M. Greenstone. (2004) “Estimating the Value of a Statistical Life: 

The Importance of Omitted Variables and Publication Bias,” American Economic Review 

Papers and Proceedings 94(2). 

Baumol, William J. and Wallace E. Oates. (1975) The Theory of Environmental Policy. 

Englewood Cliffs, NJ: Prentice Hall. 

Bayer, Patrick, Nathaniel Keohane, and Christopher Timmins. 2009. "Migration and 

Hedonic Valuation: The Case of Air Quality." Journal of Environmental Economics and 

Management, 58(1). 

Bayer, Patrick, Robert McMillan, and Kim Reuben. 2004. "An Equilibrium Model of 

Sorting in an Urban Housing Market." NBER Working Paper. 

Bayer, Patrick and Christopher Timmins. 2005. "On the Equilibrium Properties of 

Locational Sorting Models." Journal of Urban Economics, 57(3): 462-77. 

Bayer, Patrick and Christopher Timmins. 2007. "Estimating Equilibrium Models of 

Sorting across Locations." The Economic Journal, 117(518): 353-74. 

 

Bishop, R. and T. Heberlein. (1979) "Measuring Values of Extra-Market Goods: Are 

Indirect Measures Biased?" American Journal of Agricultural Economics 61: 926-930. 

Bishop, Richard C., Thomas A. Heberlein and Mary Jo Kealy. (1983) “Contingent 

Valuation of Environmental Assets: Comparison with a Simulated Market,” Natural 

Resources Journal 23(2), 619-633. 

Black, Dan A. and Thomas J. Kniesner. (2003) “On the Measurement of Job Risk in 

Hedonic Wage Models.” Journal of Risk and Uncertaint, 27(3): 205-220. 

41 
Boardman, A., D. Greenberg, A. Vining and D. Weimer. (2006) Cost Benefit Analysis: 

Concepts and Practice. Prentice Hall. 

Bockstael, N.E. and K. E. McConnell. (2008) Environmental and Resource Valuation 

with Revealed Preferences: A Theoretical Guide to Empirical Models. Springer. 

Bohm, P. (1972) "Estimating Demand for Public Goods: An experiment" European 

Economics Review Vol. 3. 

Brouhle, K. and M. Khanna. (2007) “Information and the Provision of QualityDifferentiated Goods,” Economic Inquiry 45(2): 377-395. 

Carbone, Jared C. and V. Kerry Smith “Evaluating Policy Interventions with General 

Equilibrium Externalities” Journal of Public Economics, June 2008 . 

Carlsson, F. and P. Martinsson. (2001) “Do Hypothetical and Actual Marginal 

Willingness to Pay Differ in Choice Experiments?” Journal of Environmental Economics 

and Management 41: 179-92. 

Carson, R. T. (2007) The Stated Preference Approach to Environmental Valuation Vol. IIII. Ashgate: the International Library of Environmental Economics and Policy. 

Carthy, Trevor, Susan Chilton, Judith Covey, Lorraine Hopkins, Michael Jones-Lee, 

Graham Loomes, Nick Pidgeon, and Anne Spencer. (1999) “On the Contingent Valuation 

of Safety and the Safety of Contingent Valuation: Part 2— The CV/ SG “chained” 

Approach”, Journal of Risk & Uncertainty 17: 187-213. 

Chestnut. L. G.. S. Colome. L. R. Keller, W. Lampert. R. Rowe, and S. L. 

Wojciechowski. (1988) "Heart Disease Patients' Averting Behavior. Costs of illness, and 

Willingness to Pay to Avoid Angina Episodes." EPA Report 230-10-88-042. 

Washington: EPA. Office of Policy Analysis. 

Champ, P.A., K.J. Boyle, and T.C. Brown, Eds. (2003) A Primer on Non-Market 

Valuation. Kluwer Academic Press. 

Costa, Dora L., and Matthew E. Kahn. (2004) “Changes in the value of life, 1940-1980”, 

Journal of Risk & Uncertainty 29: 159-180. 

Cummings, R. and L. Taylor. (1999) "Unbiased Value Estimates for Environmental 

Goods: A Cheap Talk Design for the Contingent Valuation Method," American 

Economic Review 89: 649-665. 

Cummings, R., S. Elliott, G. Harrison, and J. Murphy. (1997) “Are Hypothetical 

Referenda Incentive Compatible?” Journal of Political Economy 105: 609-621. 

Davis, L. (2004) “The effect of health risk on housing values: evidence from a cancer 

cluster,” American Economic Review 94:1693-1704. 

42 
Drudi, D. (1997) “A Century-Long Quest for Meaningful and Accurate Occupational 

Injury and Illness Statistics”. BLS Compensation and Working Conditions Winter 19-27. 

Duffield, J. and J. Patterson. (1992) "Field Testing Existence Values: An Instream Flow 

Trust Fund for Montana Rivers" manuscript. 

Duffield, John W. and David A. Patterson. (1991) “Inference and Optimal Design for a 

Welfare Measure in Dichotomous Choice Contingent Valuation,” Land Economics 67(2), 

255-239. 

Eeckhoudt, L.R., and J.K. Hammitt. (2001) Background Risks and the Value of a 

Statistical Life, Journal of Risk and Uncertainty 23: 261-279. 

Ellickson, Bryan. 1971. "Jurisdictional Fragmentation and Residential Choice." American 

Economic Review, 61(2): 334-39. 

Environmental Protection Agency Science Advisory Board. (2009) Valuing the 

Protection of Ecological Systems and Services. 

Epple, Dennis and Holger Sieg. 1999. "Estimating Equilibrium Models of Local 

Jurisdiction." Journal of Political Economy, 107(4): 645-81 

Espinosa, J. Andres and V. Kerry Smith "Measuring the Environmental Consequences of 

Trade Policy: A Non-Market CGE Analysis," American Journal of Agricultural 

Economics, August 1995. 

Evans, Mary F., and V. Kerry Smith. (2006) “Do we really understand age-VSL 

relationship?” Resource and Energy Economics 28: 242-261. 

Field, Barry C. and Martha K. Field. (2009) Environmental Economics: An Introduction. 

New York: McGraw-Hill Publishing. 

Gayer, Ted, James T. Hamilton, and W. Kip Viscusi. (2000) “Private Values of Risk 

Tradeoffs at Superfund Sites: Housing Market Evidence on Learning About Risks,” 

Review of Economics and Statistics 82(3), 439-451. 

Gayer, Ted, James T. Hamilton, and W. Kip Viscusi. (2002) “The Market Value of 

Reducing Cancer Risk: Hedonic Housing Prices with Changing Information,” Southern 

Economic Journal 69(2), 266-289. 

Gollier, Christian. (2004). “Maximising the Expected Net Future Value as an Alternative 

Strategy to Gamma Discounting,” Finance Research Letters 1: 85-89. 

Goulder, Lawrence H. and Ian W. H. Parry. (2008) "Instrument Choice in Environmental 

Policy", Review of Environmental Economics and Policy 2(2): 154 - 174. 

43 
Greenstone, Michael and Justin Gallagher. (2008) “Does Hazardous Waste Matter? 

Evidence from the Housing Market and the Superfund Program”, Quarterly Journal of 

Economics 123(3):951-1003. 

Hammitt, J.K., and J.-T. Liu. (2004) “Effects of Disease Type and Latency on the Value 

of Mortality Risk,” Journal of Risk and Uncertainty 28: 73-95,. 

Hammitt, J.K., J.-T. Liu, and J.-L. Liu. (2000) “Survival is a Luxury Good: The 

Increasing Value of a Statistical Life,” manuscript, August 2000. 

Hammitt, James K. (2002) “QALYs versus WTP,” Risk Analysis 22(5): 985-1001. 

Hammitt, James K. (2009) “Saving Lives: Benefit-Cost Analysis and Distribution,” 

University of Pennsylvania Law Review Pennumbra 157: 189-199. 

Hepburn, Cameron, and Ben Groom. (2007). “Gamma Discounting and Expected Net 

Future Value,” Journal of Environmental Economics and Management 53: 99-109. 

Herriges, Joseph and Catherine Kling (Eds.). (1999) Valuing Recreation and the 

Environment: Revealed Preference Methods in Theory and Practice, Darmstadt, 

Germany: Springer. 

Herriges, Joseph and Cathering Kling (Eds.) (2008) Revealed Preferences Approaches to 

Environmental Valuation, Ashgate, 

Hintermann, Beat, Anna Alberini, and Anil Markandya. (2008) “Estimating the Value of 

Safety with Labor Market Data: Are the Results Trustworthy?” forthcoming in Applied 

Economics, available at 

http://www.informaworld.com/smpp/title~content=g769588680~db=all~tab=forthcoming

?stem=3#messages. 

Johannesson, M., and B. Jonsson. (1991). “Willingness to Pay for Antihypertensive 

Therapy--Results of a Swedish Pilot Study,” Journal of Health Economics 10: 461-474. 

Johannesson, M., et al. (1993) “Willingness to Pay for Antihypertensive Therapy--

Further Results,” Journal of Health Economics 12: 95-108. 

Johannesson, Magnus, Bengt Jonsson and Lars Borquist. (1991), “Willingness to Pay for 

Antihypertensive Therapy—Results for a Swedish Pilot Study” Journal of Health 

Economics 10:461–474. 

Johnston, Robert J. (2006) “Is hypothetical bias universal? Validating contingent 

valuation responses using a binding public referendum” Journal of Environmental 

Economics and Management 52(1): 469-48. 

Just, Richard E., Andrew Schmitz, and Darrell L. Hueth. (2005) Welfare Economics of 

Public Policy: A Practical Approach to Project and Policy Evaluation Edward Elgar 

Publishing. 

44 
Khanna, M. and D.T. Ramirez. (2004) “Effectiveness of Voluntary Approaches: 

Implications for Climate Change Mitigation,” in Voluntary Agreements in Climate 

Policy, edited by A. Baranzini and P. Thalmann, Edward Elgar Publishers, pp. 31-66. 

Khanna, M. and K. Brouhle. (forthcoming) “Effectiveness of Voluntary Environmental 

Initiatives,” Chapter 6 in Governing the Environment: Interdisciplinary Perspectives, ed. 

By M. Delmas and O. Young, Cambridge University Press, Cambridge, U.K. 

Khanna, M. (2007) “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. 

Khanna, M., W. Quimio, and D. Bojilova. (1998) “Toxic Release Information: A Policy 

Tool for Environmental Protection,” Journal of Environmental Economics and 

Management 36 (3): 243-266,. 

Kniesner, T.J., W.K. Viscusi, and J.P. Ziliak. (2006) “Life-cycle Consumption and the 

Age-Adjusted Value of Life, Contributions to Economic Analysis and Policy 5(1) article 

4. 

Kochi, I. (2008) “Endogeneity and Estimates of the Value of a Statistical Life,” Colorado 

State University working paper. 

Kokoski, Mary and V. Kerry Smith "A General Equilibrium Analysis of Partial 

Equilibrium Welfare Measures: The Case of Climate Change," American Economic 

Review, June 1987; reprinted in H. Kunreuther and A.Rose, editors, The Economics of 

Natural Hazards (Cheltenham, U.K.: Edward Elgar, 2004). 

Krupnick, Alan. “Mortality-Risk Valuation and Age: Stated Preference Evidence,” 

Review of Environmental Economics and Policy (2007): 216-282. 

Lavin, M. R. (1992) Business Information: How to Find It, How to Use It, 2nd ed. Oryx 

Press, Phoenix. 

Leigh, J.P. (1995) “Compensating Wages, Value of a Statistical Life, and Inter-industry 

Differentials”, Journal of Environmental Economics and Management 28: 83-97. 

List, John A. (2006) “Using Choice Experiments to Value Non-Market Goods and 

Services: Evidence from Field Experiments” The B.E. Journal of Economic Analysis and 

Policy 6 (2). 

Lusk, Jayson L. and F. Bailey Norwood. (2005) “Effect of Experimental Design on 

choice-Based Conjoint Valuation Estimates” American Journal of Agricultural 

Economics 87(3):771-785. 

45 
List, John A. and Craig A. Gallet. (2001) “What Experimental Protocol Influence 

Disparities between Actual and Hypothetical Stated Values? Environmental and 

Resource Economics 20(3):241-254 

List, John. (2001) “Do Explicit Warnings Eliminate the Hypothetical Bias in Elicitation 

Procedures? Evidence from Field Auctions for Sportscards,” American Economic Review 

91 (5):1498-1507. 

Lusk, J., D. Fields, and W. Prevatt. (2008) “An Incentive Compatible Conjoint Ranking 

Mechanism,” American Journal of Agricultural Economics 90: 487-98. 

Mariah D. Ehmke, Jay son L. Lusk, and John A. List. (2008) “Is Hypothetical Bias a 

Universal Phenomenon? A Multinational Investigation,” Land Economics, 84(3), 489-

500 

Morgenstern, Richard and William Pizer. (2007) Reality Check: The Nature and 

Performance of Voluntary Environmental Programs in the United States, Europe, and 

Japan. Resources for the Future, RFF press. 

Mrozek, Janus R., and Laura O. Taylor. (2002) “What determines the value of life? A 

meta-analysis”, Journal of Policy Analysis and Management 21: 253-270. 

National Research Council. (2004) Valuing ecosystem services; toward better 

environmental decision-making. Washington, DC: National Academies Press. 

National Research Council. (2002) New Tools for Environmental Protection, National 

Academy Press. 

Neill, H., R. Cummings, P. Garderton, G. Harrison, and T. McGuckin. (1994) 

"Hypothetical Surveys and Real Economic Commitments," Land Economics 70(145-154. 

Newell, R.G. and William Pizer. (2003) Discounting the Distant Future: How Much do 

Uncertain Rates Increase Valuations? Journal of Environmental Economics and 

Management 46(1): 43-59. 

Opaluch, James J., Stephen K. Swallow, Thomas Weaver, Christopher Wessells and 

Dennis Wichelns. (1993) "Evaluating Impacts from Noxious Facilities: Including Public 

Preferences in Current Siting Mechanisms" Journal of Environmental Economics and 

Management 24(1). 

Portney, P. (1992) Trouble in Happyville, Journal of Policy Analysis and Management

11: 131-132. 

Herriges, J.A. and Cathy L. Kling, Eds. (2008) Revealed Preferences Approaches to 

Environmental Valuation. The International Library of Environmental Economics and 

Policy, Volumes I and II, Ashgate Publishing. 

46 
Rowe, R. D.. and L. G. Chestnut. (1985) "Oxidants and Asthma in Los Angeles: A 

Benefit Analysis. EPA Report 230-07-85-010. Washington, DC . Office of Policy 

Analysis. 

Segerson, Kathleen and Thomas Miceli. (1998) "Voluntary Environmental Agreements: 

Good or Bad News for Environmental Protection?" Journal of Environmental Economics 

and Management 36(2): 109-30. 

Segerson, Kathleen. (1994) "Property Transfers and Environmental Pollution: Incentive 

Effects of Alternative Policies." Land Economics 70(3): 261-72. 

Sieg, Holger, V. Kerry Smith, H. Spencer Banzhaf, and Randy Walsh. 2002. 

"Interjurisdictional Housing Prices in Location Equilibrium." Journal of Urban 

Economics, 52(1): 131-53. 

Sieg, Holger, V. Kerry Smith, H. Spencer Banzhaf, and Randy Walsh. 2004. "Estimating 

the General Equilibrium Benefits of Large Changes in Spatially Delineated Public 

Goods." International Economic Review, 45(4): 1047-77. 

Smith, V. Kerry, Holger Sieg, H. Spencer Banzhaf, and Randy Walsh. 2004. "General 

Equilibrium Benefits for Environmental Improvements: Projected Ozone Reductions 

under EPA’s Prospective Analysis for the Los Angeles Air Basin." Journal of 

Environmental Economics and Management, 47(3): 559-84. 

Smith, V. Kerry and J Andres Espinosa"Environmental and Trade Policies: Some 

Methodological Lessons," Environment and Development Economics, February 1996; 

reprinted in A.A. Batabyal and H. Beladi, editors, The Economics of International Trade 

and the Environment (New York: Lewis Publishers, 2001). 

Smith, V. Kerry and Jared C. Carbone “Environmental Economics and the “Curse” of the 

Circular Flow” in Jun Jie Wu, P. Barkley, and B. Weber, editors, Frontiers of Rural and 

Resource Economics, (Washington, D.C.: Resources for the Future, 2008) 

Sunstein, C.R. & R.H. Thaler. (2003) Libertarian Paternalism, AER Papers & 

Proceedings 93: 175-179. 

Sunstein, Cass. (1997) “Bad Deaths” Journal of Risk and Uncertainty 14: 259-282,. 

Tietenberg, Tom. (2008) “Disclosure Strategies for Pollution Control,” Environmental 

and Resource Economics11(3-4): 587-602. 

Unsworth, R.E., and R.C. Bishop. (1994) “Assessing Natural Resource Damages Using 

Environmental Annuities .” Ecological Economics 11:35–41. 

Viscusi, W. Kip, and Joseph E. Aldy. (2007) Labor Market Estimates of the Senior 

Discount for the Value of Statistical Life, Journal of Environmental Economics and 

Management 53: 377-392. 

47 
48 

Viscusi, W.Kip. (2004) “The Value of life: Estimates with Risks by Occupation and 

Industry.” Economic Inquiry 42: 29-48. 

Walsh, Randall L. 2007. "Endogenous Open Space Amenities in a Locational 

Equilibrium." Journal of Urban Economics, 61(2): 319-44. 

Weitzman, Martin L. (2001) Gamma discounting, American Economic Review 91: 261-

271. 

Weitzman, Martin L. (1998) “Why the Far-Distant Future Should be Discounted at its 

Lowest Possible Rate” Journal of Environmental Economics and Management 36: 201-

208. 

Whitehead, J.C., S.K. Pattanayak, and B.R.Gelso. (2008) "Combining Revealed and 

Stated Preference Data to Estimate the Nonmarket Value of Ecological Services: An 

Assessment of the State of the Science" Journal of Economic Surveys 22(5):872-908. 

Xabadia, Angels, Renan-Ulrich Goetz, and David Zilberman. (2008) “The Gains from 

Differentiated Policies to Control Stock Pollution When Producers are Heterogeneous”. 

American Journal of Agricultural Economics 90(4):1059-1063.