Four essays on environmental policy under uncertainty with applications to water quality and carbon sequestration

In this thesis, I present four essays that deal with several diverse issues in environmental economics, ranging from soil carbon sequestration, to a design of a pollution permit trading program, to proposing watershed-scale solutions to water quality problems, both on state and regional scale.;The first essay is titled Environmental policy under benefit and cost uncertainty: application to soil carbon offsets . I characterize an optimal spatial allocation of land parcels to specific environmental practices explicitly dealing with uncertainty in both the benefits and program costs. The results provide a magnitude of uncertainty discount for soil carbon offsets and the margin of safety necessary in the budget to ensure at the planning stage that the program\u27s costs will not exceed the planned expenditures.;The second essay is titled Optimal design of permit markets with an ex ante pollution target . In this essay, the design of permit trading programs when the objective is to minimize the cost of achieving an ex ante pollution target; that is, one that is defined in expectation rather than an ex post deterministic value, is examined. I demonstrate that to minimize expected abatement costs regulators must use information on the joint distribution of firms\u27 abatement costs, as well as the pollution delivery coefficients. As a result, the optimal trading ratio is a function of the delivery coefficient, as well as the moments of abatement costs, and the total permit allocation deviates from the pollution goal. These findings differ from a typical permit market design, where no cost information is needed to achieve cost-efficiency, the trading ratio is set to the ratio of pollution delivery coefficients, and the permit allocation exactly equals the pollution goal.;The third and the fourth chapters of the thesis build a simulation-optimization modeling framework for the analysis of efficient nonpoint source pollution reduction strategies. These essays integrate modern multi-objective optimization tools with a realistic water quality model to provide decision-makers with sets of cost-efficient pollution reduction solutions.;In the third essay, titled Efficient reductions in local and state-level nonpoint source nutrient pollution: an application to the state of Iowa, I incorporate a water quality model, SWAT, in conjunction with detailed information on conservation practices, into an evolutionary search algorithm to find allocations of conservation practices that minimize the costs of achieving given water quality targets for all the major watersheds in the state of Iowa.;In the final essay, titled Searching for efficiency: least cost nonpoint source pollution control with multiple pollutants, practices, and targets , I examine the policy implications of efficient control of nonpoint source pollution using a spatially explicit model of a large and critically important agricultural region: the Upper Mississippi River Basin in the central U.S. I derive the conservation production possibility frontier that explicitly incorporates the tradeoffs between pollution control costs and water quality benefits, between different pollutants, or between different control targets. The regional scale of the modeling framework facilitates the investigation of relevant policy analyses related to the growing dead zone in the Gulf of Mexico

Unlocking water markets: an experimental approach

water market, experiments, resource economies, Marketing, Resource /Energy Economics and Policy,

Estimation of a Binary Choice Model with Grouped Choice Data

We propose an econometric technique for estimating the parameters of a binary choice model when only aggregated data are available on the choices made. The method performs favorably in applications to both simulated and real world choice data

Experimental Testbeds for ECOSEL: A Market Framework for Private Provision of Forest Ecosystem Services

We attempt to design a market framework (which we call ECOSEL) for private provision of forest ecosystem services. ECOSEL is a non-regulatory framework that uses a voluntary public good provision mechanism (in a form of an auction) in conjunction with a multiobjective optimization algorithm to create a market for forest ecosystem services. It is expected to be attractive to the demand side of the ecosystem service market since only Pareto-efficient bundles of services are offered for auction, and it is expected to be attractive to the supply side as well by creating a source of non-timber income for forest landowners. ECOSEL is capable of flexible response to demand for other relevant dimensions of forest-related environmental amenities such as biodiversity, viewshed or recreational services. Following Roth’s (2002) advice on behavior of economists as “market engineers”, we use both experimental economics to improve the design of the ecosystem services market. Concurrently, we provide experimental evidence on the efficiency and revenue-generating properties of a multi-good subscription game of incomplete information.Environmental Economics and Policy, Marketing,

Optimal Design of Permit Markets with an Ex Ante Pollution Target

In this paper, we examine the design of permit trading programs when the objective is to minimize the cost of achieving an ex ante pollution target, that is, one that is defined in expectation rather than an ex post deterministic value. We consider two potential sources of uncertainty, the presence of either of which can make our model appropriate: incomplete information on abatement costs and uncertain delivery coefficients. In such a setting, we find three distinct features that depart from the well-established results on permit trading: (1) the regulator’s information on firms’ abatement costs can matter; (2) the optimal permit cap is not necessarily equal to the ex ante pollution target; and (3) the optimal trading ratio is not necessarily equal to the delivery coefficient even when it is known with certainty. Intuitively, since the regulator is only required to meet a pollution target on average, she can set the trading ratio and total permit cap such that there will be more pollution when abatement costs are high and less pollution when abatement costs are low. Information on firms’ abatement costs is important in order for the regulator to induce the optimal alignment between pollution level and abatement costs

Reversing the Property Rights: Practice-Based Approaches for Controlling Agricultural Nonpoint-Source Water Pollution When Emissions Aggregate Nonlinearly

Nonpoint-source pollution remains a troubling source of water quality problems despite decades of economics research on the matter. Among the chief difficulties for addressing the issue are the property rights assignments implicit in the current policy environment that favor agricultural nonpoint-source pollution, the unobservability of field-level emissions, and complex fate and transport relationships linking them to ambient water quality. Theoretical and practical considerations lead to the focus on observable abatement actions (conservation practices). Biophysical models are increasingly more capable of linking abatement actions to policy-relevant water quality outcomes. If costs of abatement actions are known, finding the least-cost mix of abatement actions is possible, while incorporating the nonlinearity of the pollution process. When costs are not known or information is incomplete, regulators can rely on flexible incentive-based programs, but the design of such programs is complicated by the complexities of emission aggregation. In this work, we focus on the regulator capable of focusing on nonpoint-source emitters. We address the design and performance of three practice-based approaches, ranging from the command-and-control approach mandating practices, to the more flexible performance standard approach where farmers are free to select the optimal mix of on-farm conservation practices, to a fully flexible approach where credits for conservation practices are freely tradable. We do so by utilizing the representation of the nonlinear emission aggregation (fate and transport) process (the Soil and Water Assessment Tool model), and consider cases ranging from the regulator having perfect information on the costs of conservation practices to no information at all. We show how workable programs utilizing the biophysical models and simulation-optimization approaches can be designed, and assess their performance relative to the efficient case. We find that flexible programs perform well both in terms of cost and water quality goals attainment. In particular, a trading program designed around an approximation of the nonlinear pollution process performs well, relative to first-best under no information on the cost of conservation practices

Optimal Placement of Conservation Practices Using Genetic Algorithm with SWAT

The effectiveness of conservation practices depends on their placement on the fields within the watershed. Cost-effective placement of these practices for maximum water quality benefits on each field requires comparing a very large number of possible land-use scenarios. To address this problem, we combine the tools of evolutionary algorithm with the Soil and Water Assessment Tool (SWAT) model and cost data to develop a trade-off frontier of least cost of achieving nutrient reductions and the corresponding locations of conservation practices. This approach was applied to the Raccoon River Watershed, which drains about 9,400 km2 of an intensive agriculture region in west-central Iowa. Applying genetic algorithm to the calibrated SWAT modeling setup produced multitudes of optimal solutions of achieving nutrient reductions in relation to the total cost of placing these practices. For example, a 30% reduction in nitrate (and a corresponding 53% reduction in phosphorus) at the watershed outlet can be achieved with a cost of $80 million per year. This solution frontier allows policymakers and stakeholders to explicitly see the trade-offs between cost and nutrient reductions

Ecosystem Services under Benefit and Cost Uncertainty: An Application to Soil Carbon Sequestration

Benefit and cost uncertainty in provisioning of ecosystem services are investigated in the context of soil carbon sequestration. Multiple parcel-level carbon sequestration options are considered. Uncertainty has been a widely stated reason for not including soil carbon sequestration in the portfolio of greenhouse gases reduction measures. Biophysical simulation models are used to generate a distribution of resulting environmental benefits. An econometric model of conservation practice adoption is used to generate a distribution of costs. The results provide a magnitude of uncertainty discount for soil carbon offsets and the budget margin of safety, and may assist in formulating carbon sequestration policy.