On March 23, 1989, the Exxon Valdez ran aground in Alaska's Prince William Sound and released over 250,000 barrels of crude oil, resulting in 1300 miles of oiled shoreline. The Exxon spill ignited a debate about the appropriate compensation for damages suffered, and among economists, a debate concerning the adequacy of methods to value public goods, particularly when the good in question has limited direct use, such as the pristine natural environment of the spill region. The efficacy of stated preference methods generally, and contingent valuation in particular, is no mere academic debate. Billions of dollars are at stake. An influential symposium appearing in this journal in 1994 provided arguments for and against the credibility of these methods, and an extensive research program published in academic journals has continued to this day. This paper assesses what occurred in this academic literature between the Exxon spill and the BP disaster. We will rely on theoretical developments, neoclassical and behavioral paradigms, empirical and experimental evidence, and a clearer elucidation of validity criteria to provide a framework for readers to ponder the question of the validity of contingent valuation and, more generally, stated preference methods.

This article presents lessons from the rich adoption literature for the nascent research on adaptation. Individuals' adoption choices are affected by profit and risk considerations and by credit and biophysical constraints. New technologies spread gradually, reflecting heterogeneity among potential adopters, processes of learning and technological improvement, and policies and institutions. Adaptation is the response of economic agents and societies to major shocks. We distinguish between reactive and proactive adaptation. The latter is important in the context of climate change and consists of mitigation, reassessment, and innovation that aim to affect the timing and location of shocks. Adaptation strategies also include adoption of innovation and technology transfer across locations, insurance and international trade, and migration and invasions. Recent research emphasizes multidisciplinary collaborations; historical analysis; and the roles of returns to scale of key technologies, social networks, behavioral economics, path dependency, and ex ante adjustment in explaining patterns of adoption and adaptation.

Hicksian welfare theory is static in nature, but many decisions are made in a dynamic environment. We present a dynamic model of an agent's decision to purchase or sell a good under the realistic conditions of uncertainty, irreversibility, and learning over time. Her willingness to pay (WTP) contains both the intrinsic value of the good as in Hicksian theory plus a commitment cost associated with delaying to obtain more information. The Hicksian equivalence between WTP/Willingness to accept (WTA) and compensating and equivalent variations no longer holds. The WTP and WTA divergence may arise and observed WTP values are not always appropriate for welfare analysis.

Because of payoff uncertainties combined with risk aversion and/or real options, farmers may demand a premium in order to adopt conservation tillage practices, over and above the compensation for the expected profit losses (if any). We propose a method of directly estimating the financial incentives for adopting conservation tillage and distinguishing between the expected payoff and premium of adoption based on observed behavior. We find that the premium may play a significant role in farmers' adoption decisions. AbstractBecause of payoff uncertainties combined with risk aversion and/or real options,

We study a farmer's decision to convert traditional crop land into growing dedicated energy crops, taking in account sunk conversion costs, uncertainties in traditional and energy crop returns, and learning. The optimal decision rules differ significantly from the expected net present value rule, which ignores learning, and from real option models that allow only one way conversions into energy crops. These models also predict drastically different patterns of land conversions into and out of energy crops over time. Using corn-soybean rotations and switchgrass as examples, we show that the model predictions are sensitive to assumptions about stochastic processes of the returns. Government policies might have unintended consequences: subsidizing conversion costs into switchgrass reduces proportions of land in switchgrass in the long run.

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We study a farmer's decision to convert traditional crop land into growing dedicated energy crops, taking into account sunk conversion costs, uncertainties in traditional and energy crop returns, and learning. The optimal decision rules differ significantly from the expected net present value rule, which ignores learning, and from real option models that allow only one way conversions into energy crops. These models also predict drastically different patterns of land conversions into and out of energy crops over time. Using corn-soybean rotation and switchgrass as examples, we show that the model predictions are sensitive to assumptions about stochastic processes of the returns.Government policies might have unintended consequences: subsidizing conversion costs into switchgrass reduces proportions of land in switchgrass in the long run.

The often observed empirical divergence between WTA and WTP measures of welfare change continues to be a topic of interest to both theoretical and applied economists. The divergence has particularly important implications for environmental policy. In this paper, we review behavioral and other explanations of the disparity with a focus on their connections to neoclassical welfare theory, and evaluate the empirical evidence of these explanations through the same lens. Some explanations of the disparity are consistent with neoclassical models and some are not. Likewise, some imply that the divergences are attributed to underlying preferences (neoclassical or not) while others suggest the divergences are due to elicitation methods, cognitive limitations, or other non-preference related reasons. We argue that the source of the divergence can inform the choice of which measure, WTP or WTA, to use in a given empirical application.