Grantee Research Project Results

Environmental Policy in Intensively Managed Ecosystems Under Benefit and Cost Uncertainty

EPA Grant Number: F5C10390
Title: Environmental Policy in Intensively Managed Ecosystems Under Benefit and Cost Uncertainty
Investigators: Rabotyagov, Sergey
Institution: Iowa State University
EPA Project Officer: Hahn, Intaek
Project Period: August 1, 2005 through July 1, 2008
Project Amount: $88,886
RFA: STAR Graduate Fellowships (2005) RFA Text |  Recipients Lists
Research Category: Academic Fellowships

Objective:

Intensively managed ecosystems present a challenging set of problems for policymakers, environmental scientists, and environmental economists. They also provide opportunities for providing the public with environmental benefits such as improved water quality, recreational services, and mitigation of greenhouse gas emissions. Often, the task of a policymaker is to procure a particular level of environmental benefits at least cost to society. An important complication is that both the benefits and costs are often uncertain. Furthermore, there are usually several competing options for providing environmental benefits. For example, each land parcel currently in agricultural production can be either retired from production altogether, or an environmentally-friendly production practice can be utilized. Under such conditions, an optimal policy of providing environmental benefits from intensively managed ecosystems must jointly consider both the multiple conservation options and the uncertain nature of benefits and costs. My goal is to develop incentive-based, voluntary mechanisms for the implementation of such policies.

Approach:

I plan to consider the analytical properties of optimal policies using the tools of stochastic programming, as well as to provide an empirical application and demonstration of theoretical results. My main methodological contribution is to provide a framework for finding an optimal spatial allocation of land parcels to specific environmental practices explicitly dealing with uncertainty in both the benefits and program costs. Such a framework may be applicable to policy questions that extend beyond the problems of the environment (e.g., health, education, job training programs). The empirical application will focus on an Iowa watershed in a heavily farmed part of the state. Biophysical simulation models will be used to evaluate the performance of parcel-level alternatives, as well as to generate a distribution of resulting environmental benefits. One result will be minimum cost levels required to achieve various environmental standards in an uncertain environment. The stringency of environmental standards is expected to affect minimum costs significantly.

Rationale:

Intensively managed ecosystems present both environmental challenges and opportunities for reaching environmental goals. Such goals may include water quality improvements, and alleviation of greenhouse gas emissions. Due to inherent uncertainties regarding the effects of environmental programs, environmental goals may not be achievable at all times. Instead, a more realistic strategy is to require these goals to be achieved a high percentage of the time. Also, the costs of certain conservation options may not be known in advance. The aim of this project is to develop recommendations for cost-efficient environmental policy in such circumstances.

Supplemental Keywords:

fellowship, optimal targeting, decision-making under uncertainty, land use changes, stochastic programming, cost efficiency,, RFA, Economic, Social, & Behavioral Science Research Program, Scientific Discipline, ENVIRONMENTAL MANAGEMENT, Geographic Area, POLLUTION PREVENTION, sustainable development, Resources Management, State, decision-making, Ecology and Ecosystems, Economics & Decision Making, Iowa, watershed, environmental decision making, stochastic mechanisms, biophysical model, conservation, cost benefit, environmental policy, incentive based environmental policy, environmental protection, cost-effective ecosysem protection, cost effectiveness, land use

Progress and Final Reports:

2006

2007

Final