This article models the recreation demand for Iowa wetlands, combining survey data on both actual usage patterns (i.e., revealed preferences (RPs)) and anticipated changes to those patterns under hypothetical increases in trip costs (i.e., stated preferences (SPs)). We formulate and test specific hypotheses concerning potential sources of bias in each approach and discuss what can be learned about the validity of the models from such tests.

In this paper, we examine command-and-control (CAC) policies and market-based instruments (MBI) in the context of the Conservation Reserve Program (CRP). The CRP, an MBI in the form of subsidies, is by far the largest agro-environmental policy implemented to date. We compare the environmental performance of the CRP as implemented to a few counterfactual CAC polices using EPIC (Environmental Policy Integrated Climate), a bio-physical simulation model. In the context of multiple environmental indicators, no policy alternative emerges as a clear winner. The importance of the choice and design of CAC policies is emphasized.

The development of technologies for accurate field-scale carbon assessment allows the implementation of more efficient policies than can be implemented in their absence. We estimate the value of accurate measurement technology by estimating the gains from implementing a more efficient policy, one that targets carbon reductions at the field scale but requires accurate field-scale measurement technology, relative to a practice-based policy that can be implemented in the absence of such technology. We find large cost savings due to improved targeting of conservation tillage subsidies for the state of Iowa. The cost savings depend significantly on the choice of baseline carbon, while the ability of the government to cost discriminate has little impact on the value of accurate measurement technology.

We study the optimal emission standards under uncertain pollution damages and transaction costs associated with policy changes in a dynamic setting. We consider three alternative forms of transactions costs and show that they can lead to different kinds of delays of policy changes or smaller scales of these changes. Thus, policy persistence can be a rational response of forward-looking policy makers to future transaction costs, rather than an inefficient outcome of the current political process.

In a static setting, willingness to pay for an environmental improvement is equal to compensating variation. However, in a dynamic setting characterized by uncertainty, irreversibility, and the potential for learning, willingness to pay may also contain an option value. In this paper, we incorporate the dynamic nature of the value formulation process into a study using a contingent valuation method, designed to measure the value local residents assign to a north-central Iowa lake. Our results show that willingness to pay is highly sensitive to the potential for future learning. Respondents offered the opportunity to delay their purchasing decisions until more information became available were willing to pay significantly less for improved water quality than those who faced a now-or-never decision. The results suggest that welfare analysts should take care to accurately represent the potential for future learning.

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.

In this study, we estimate empirically the multiple benefits of a subsidy policy that would offer payments to farmers in return for the adoption of conservation tillage and compare the outcomes of alternative targeting designs for such a policy. Using data for roughly 12,000 National Resource Inventory (NRI) points, we simulate for the state of Iowa the least-cost policy schemes for offering payment incentives. We use an economic model of conservation tillage adoption to evaluate the costs of adoption, and we use a model that simulates physical processes (Environmental Policy Integrated Climate, or EPIC) to estimate the environmental benefits of adoption at each of the NRI points.

We assess the costs and environmental consequences of two targeting options. The first is a practice-based policy instrument that maximizes the acres of land in conservation tillage, regardless of the level of environmental benefits achieved. The second is a performance-based instrument that yields the highest amount of environmental benefits per dollar spent. We consider four performance-based benefits: carbon sequestration in agricultural soils, reduction in nitrogen runoff, reduction of erosion of soil by wind, and reduction of erosion of soil by water. We find that the practice-based instrument provides high proportions of the four benefits relative to the performance-based instrument, especially at higher budget levels. Similarly, we estimate that targeting one of the four benefits provides high percentages of the other benefits compared to the amounts obtainable if they were targeted directly.

This study advances, and experimentally tests, a new explanation for the disparity between willingness to pay (WTP) and willingness to accept (WTA)—a dynamic neoclassical theory based on the presence of commitment costs. While to date neoclassical models have not explained the observed data patterns well, we find that the commitment cost theory is able to explain adequately the causes and severity of the WTP/WTA value disparity. In particular, using data gathered from an actual marketplace, even the most stringent of our theoretical conjectures—cases where WTP values are predicted to exceed WTA values—oftentimes are met.

The growth in federal conservation programs has created a need for policy modeling frameworks capable of measuring micro-level behavioral responses and macro-level landscape changes. This paper presents an empirical model that predicts crop choices, crop rotations, and conservation tillage adoption as a function of conservation payment levels, profits, and other variables at more than 42,000 agricultural sites of the National Resource Inventory (NRI) in the Upper Mississippi River Basin. Predicted changes in crop choices and tillage practices are then fed into site-specific environmental production functions to determine changes in nitrate runoff and leaching and in water and wind erosion at each NRI site. This policy-scale model is applied to the case of green payments for the adoption of conservation practices (conservation tillage and crop rotations) in the Upper Mississippi River Basin, a region under scrutiny as a significant source of nutrient loadings to the Mississippi River, causing hypoxia in the Gulf of Mexico. Results from this application suggest that payments for conservation tillage and crop rotations increase the use of these conservation practices. However, the acreage response is inelastic and the programs are not likely to be cost effective on their own for addressing the hypoxia problem in the Gulf of Mexico.