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Title:A hierarchical decision-making approach to resource management and valuation: The case of conjunctive water use
Author(s):Muralidaran, Vijay
Doctoral Committee Chair(s):Onal, Hayri
Department / Program:Agricultural and Consumer Economics
Discipline:Agricultural and Consumer Economics
Degree Granting Institution:University of Illinois at Urbana-Champaign
Subject(s):Economics, Agricultural
Sociology, Public and Social Welfare
Environmental Sciences
Operations Research
Abstract:This study demonstrates that Pigouvian taxes derived from the socially optimum shadow prices of shared resources may result in serious deviations between users' response and the socially optimal resource use when the users' profit motive is not shared by the social planner and the resultant objectives differ structurally or parametrically. These concepts are applied to the optimum management of conjunctive use of surface and ground water. Irrigation water pricing reform to improve efficiency and also to increase labor demand are seen as critical issues in India. Therefore, two alternative policy objective (welfare) specifications are considered: (i) maximizing net return to water and land (profit) and (ii) aggregate value added (which includes gross returns to labor). Farmers are assumed to maximize temporal profit in both cases. The inadequacy of the single level conventional (shadow pricing) approach is demonstrated for the latter specification. An alternative bilevel optimization framework is proposed to address the issue. In this approach, the hierarchical decision making, water prices and the profit maximizing behavior of the farmers are incorporated explicitly, for alternative global objective specifications.
The pricing problems are formulated first in a static (steady state) and then a dynamic framework. Linear programming is used to solve the static conventional single level formulation to derive the shadow prices. The static bilevel program is transformed into a mixed integer program to solve directly for the appropriate prices to maintain steady state. In the dynamic analysis, the critical empirical issue is to determine the optimum transition path for reaching a target level of water table. This is accomplished by a dynamic programming methodology, which combines linear and bilevel programming submodels depending on the choice of the social objective function.
The results obtained from both static and dynamic analysis indicate that a significantly higher social welfare and employment can be obtained by inducing a switch to a crop pattern with increased acreage of high-value-added crops. The bilevel model solutions also indicate that both surface and ground water prices would be lower than the shadow prices of the conventional solutions. This is necessary to induce farmers to use more water and select more labor intensive crops. The dynamic bilevel optimization results converge to the single level optimization results for specific empirical conditions, although the objectives of the two decision makers may differ. While the conventional formulation implies a pricing strategy with seasonal variation, annual prices can be obtained from the bilevel formulation.
The major contributions of this study are that it (i) identifies the specific conditions in resource valuation problems, where bilievel programming offers an improvement over conventional approaches, (ii) develops a novel dynamic bilevel optimization framework to solve for the dynamic optimum pricing strategy, and furthermore offers a substantive empirical application.
Issue Date:1996
Rights Information:Copyright 1996 Muralidaran, Vijay
Date Available in IDEALS:2011-05-07
Identifier in Online Catalog:AAI9702618
OCLC Identifier:(UMI)AAI9702618

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