"Evaluating Pollution Control Policies Using a Farm-level Dynamic Model," with Jingjing Wang, University of California at Riverside

Abstract: Animal waste from concentrated animal feeding operations (CAFOs) is a significant contributor to the nitrate contamination of groundwater. Some manure also contains heavy metals and salts that may build up either in cropland or groundwater. To find cost-effective policies for pollution reduction at the farm level, an environmental-economic modeling framework for representative CAFOs is developed, where the owner of the operation is a profit-maximizer subject to environmental regulations. Our model incorporates various components including herd management, manure handling system, waste water, waste nitrogen, waste salt, waste disposal option, crop rotation, irrigation system, water application rate, water source, and nitrate cycling. We also include herd dynamics and the dynamics of soil characteristics as well as the spatial heterogeneity of the irrigation system. Novel crop response functions are derived from simulated data to account for the effects of interactions and feedback mechanisms in the whole plant-water-nitrogen-salinity system. The spatial heterogeneity of water and nitrogen application over the field, combined with the integrated effects of water, nitrogen, and salinity on crop yield and nitrate leaching, has been shown to have significant effects on both the pattern and the total amount of field emission. Modeling of the temporal and spatial dynamics of soil characteristics is necessary to account for these factors and should be incorporated in future research. In addition to the existing regulation (Nutrient Management Plans), the model is utilized to simulate the effects of three other policy instruments: field emission limit, field emission charge, and surface water tax. Empirical results suggest that direct quantity restrictions of emission or incentive-based emission policies are much more cost-effective than quantity controls of inputs. Policies targeting emissions create incentives for the operator to examine the effects of other management practices to reduce pollution in addition to controlling polluting inputs.

Jingjing Wang is a PhD Candidate in Environmental Economics and Policy at the University of California at Riverside. She has a B.E. in Environmental Engineering from Tsinghua University (China) and an M.S. in Environmental Science from the University of California at Riverside. Her research interests are environmental & resource economics, agricultural economics, water resource economics, and computational economics. She is also interested in interdisciplinary research for answering practical policy questions and has been collaborating with scientists outside her field. She works as a student intern in the Santa Ana Regional Water Quality Control Board of California.

"Valuing the Wind: Renewable Energy Policies and Air Pollution Avoided," with Kevin Novan, University of California at San Diego

Abstract: This paper estimates the variation over time in the quantity of pollution avoided by renewable electricity. Taking advantage of the natural experiment presented by changes in hourly wind speeds, I identify the amount of CO2, NOx, and SO2 reduced by electricity supplied from wind turbines in the Texas electricity market. The results provide clear evidence that renewable generation in the region offsets significant amounts of each of the pollutants examined. However, because different conventional generators are on the margin at different levels of demand, I find the amount of pollution avoided by a unit of renewable electricity varies substantially with the quantity of electricity demanded. As a result, renewable generators in separate locations, producing electricity at varying points in time, will provide very different reductions in pollution. By failing to account for these differences in the emissions avoided, policies equally subsidizing each unit of renewable electricity will not ensure efficient investment decisions are made.

Kevin Novan is a Ph.D. candidate in the Economics Department at the University of California, San Diego. His research focuses on the intersection of environmental and energy economics, with an emphasis on the electricity sector. Electricity generation is a major source of a variety of pollutants. To achieve significant reductions in the level of pollution emitted, substantial changes will need to be made in the way electricity is produced and consumed. Kevin's research explores how policies can induce more efficient use of the available energy resources.

"Conspicuous Conservation: The Prius Halo and Willingness to Pay for Environmental Bona Fides," with Steve Novan, University of California at Berkeley

Abstract: A considerable literature on conspicuous consumption has relied on status-seeking motives to explain anomalies in consumer behavior, such as upward sloping demand curves and persistent demand for luxury brand items that provide the same functionality as cheaper alternatives. This paper develops a theory of conspicuous conservation, a phenomenon attributable to increasing concern about environmental damage and climate change in which individuals seek status through displays of austerity rather than ostentation. We test for the presence of a conspicuous conservation effect in vehicle purchase decisions and estimate the willingness to pay for the “green” signal generated by the Toyota Prius, which until 2010 was the only hybrid vehicle on the road that provided standard amenities and a unique and recognizable model design. Using observed variation in model ownership rates across communities in Colorado and Washington, we identify a statistically and economically significant conspicuous conservation effect and estimate a mean willingness to pay for the green signal in the range of $430 to $1,300 in Washington and $1,400 to $4,200 in Colorado. We relate these findings to a growing literature on green markets and consider the implications of signaling motives for the private provision of public goods and for achieving efficient investment in conservation projects.

Steven Sexton is a PhD Candidate in agricultural and resource economics at UC Berkeley. His research focuses on addressing major sustainability challenges at the intersection of agriculture, energy, and the environment and has appeared in the Annual Review of Resource Economics, the Journal of Agricultural and Resource Economics, Environmental Research Letters, and the Journal of Agricultural and Food Industrial Organization, among other peer-reviewed and popular publications. He is also a regular contributor to the Freakonomics blog.

"Optimal Management of a Stochastic Stock Pollutant with Non-convex Feedback: An Application to Climate Change," with Charles Seguin, University of California at Berkeley

Charles Seguin is an environmental and resource economist, who will graduate in May 2012 from the department of Agricultural and Resource Economics at the University of California, Berkeley. Before his doctoral studies, he obtained a B.Com at McGill University and an M.A. at Queen’s University. He also worked as a consultant for Daniel Arbour & Associés in Montreal.

Seguin's research interests are mainly in dynamic models focusing on climate change and sustainability. His research extends the economic literature in these areas by introducing elements of non-convexities and hysteresis into models, and by using modern numerical techniques to calibrate models to current issues.

Abstract: Non-convexities in feedback processes are increasingly found to be im- portant in the climate system. To evaluate their impact on the optimal greenhouse gas (GHG) abatement policy, I introduce non-convex feedbacks in a stochastic pollution control model. I numerically calibrate the model to represent the mitigation of greenhouse gas (GHG) emissions contribut- ing to global climate change. This approach makes two contributions to the literature. First, it develops a framework to tackle stochastic non-convex pollution management problems. Second, it applies this framework to the problem of climate change. This approach is in contrast to most of the eco- nomic literature on climate change that focuses either on linear feedbacks or environmental thresholds. I find that non-convex feedbacks lead to a decision threshold in the optimal mitigation policy, and I characterize how this threshold depends on feedback parameters and stochasticity.

"International recessions," with Fabrizio Perri, University of Minnesota

Fabrizio Perri (www.fperri.net) is an associate professor of economics at the University of Minnesota and a consultant at the Federal Reserve Bank of Minneapolis. Prior to his current position, he was Berkley Professor of Economics and Business at New York University. He graduated from Universitá Bocconi in Milan, Italy, and received his Ph.D. from the University of Pennsylvania. He is also an affiliate of the National Bureau of Economic Research and the Centre for Economic Policy Research. He is an associate editor at the American economic Review, the Journal of the European Economic Association , Quantitative Economics and the Review of Economic Dynamics.

Fabrizio’s research is in macroeconomics and international macroeconomics, and he is interested in understanding risk sharing possibilities among individuals and countries.

Abstract: The 2007-2009 crisis was characterized by an unprecedented degree of international synchronization as all major industrialized countries experienced large macroeconomic contractions around the date of Lehman bankruptcy. At the same time countries also experienced large and synchronized tightening of credit conditions. We present a twocountry model with nancial market frictions where a credit tightening can emerge as a self-ful lling equilibrium caused by pessimistic but fully rational expectations. As a result of the credit tightening, countries experience large and endogenously synchronized declines in asset prices and economic activity (international recessions). The model suggests that these recessions are more severe if they happen after a prolonged period of credit expansion.

"A meeting of the minds: contracts and social norms," Erin Krupka, University of Michigan

Abstract: In this paper we demonstrate that incomplete contracts induce specific social norms of obligation. We employ a new experimental method to measure social norms directly via an incentive-compatible mechanism that exploits a key feature of norms: they are collectively help perceptions of the appropriateness of behavior. We find that handshake agreements substantially change the social norm in three ways. First, taking the promised action becomes substantially more appropriate, and all other actions become less appropriate. Second, the handshake agreement increases the consensus across individuals about which action is the most appropriate. Third, in the Bertrand Game the handshake agreement replaces a norm of risk minimization with a norm of obligation. Our results shed new light on one mechanism by which incomplete contracts persist and can outperform complete contracts. Finally we combine choice data for these games with the social norms elicited using the incentive compatible norm elicitation technique to predict changes in behavior across conditions and games. We show that a utility model that includes social norms as an additional motivation does much better predicting behavior than models which include only monetary utility and social preferences for fairness.

Erin Krupka is an assistant professor at the School of Information. She is an experimental behavioral economist who explores the ways in which social incentives and environmental factors influence behavior, using both laboratory and field experiments. Before joining the School of Information as an assistant professor at the University of Michigan in 2009, Dr. Krupka graduated from Carnegie Mellon University and joined IZA (a Labor Economics Research Institute) in Bonn, Germany, as a post doc.

Though firmly grounded in economics, one of the hallmarks of her research agenda is the synthesis of theory and findings stemming from social science multiple disciplines. Her research on social norms suggests why individuals might engage in behaviors that appear inconsistent with self-interest and suggests why trivial modifications to a decision context can change behavior significantly. In addition, she has developed a new protocol for measuring and identifying social norms that researchers and practitioners can use to answer important questions regarding the emergence, maintenance, content and transmission of social norms. Broadly, her work contributes to the emerging literature that models the sway of non-wealth factors on choice, by using social norms to raise the “psychological cost” of selfishness. This work is directly relevant to the incentive-centered design of information systems, an approach pioneered by faculty at the School of Information.

Bob R. Holdren was born September 13, 1922, in Pendleton, Indiana. He received his BA degree in 1948 and his M.A. degree in 1948 from Indiana University. In 1959 he received his PhD from Yale University. His PhD dissertation on "The Structure of a Retail Market and the Market Behavior of Retail Units" won an award from the Ford Foundation as an outstanding dissertation on the problems of business.

Prof. Holdren joined the Iowa State University staff in 1958. He served as a visiting professor at Indiana University in 1961, received a Ford Foundation Faculty Fellowship for 1966-1967, and was a consultant and expert witness for the Federal Trade Commission from 1973 to 1978.

With a commitment to good teaching, Professor Holdren displayed a genuine interest in both undergraduate and graduate students. We are honored to dedicate this lecture in his memory.