A Multiobjective Linear Programming Methodology for Public Sector Tax Planning

James J. Chrisman, Timothy Fry, Gary R. Reeves, Holly S. Lewis and Robert Weinstein
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James J. Chrisman: Department of Management, University of South Carolina, Columbia, South Carolina 29208
Timothy Fry: Department of Management Science, University of South Carolina
Gary R. Reeves: Department of Management Science, University of South Carolina
Holly S. Lewis: Department of Management Science, Pennsylvania State University, University Park, Pennsylvania 16802
Robert Weinstein: College of Business Administration, Bradley University, Peoria, Illinois 61625

Interfaces, 1989, vol. 19, issue 5, 13-22

Abstract: Designing an equitable and efficient tax structure is one of the most important tasks of public sector decision makers. The tax-structuring problem is characterized by many often conflicting objectives, such as maintaining adequate revenue levels, reducing property taxes, and minimizing the burden placed upon low income taxpayers. Using an interactive multiobjective linear programming (MOLP) methodology we were able to provide the city manager of Peoria, Illinois with insights necessary to restructure the city's tax system. After six iterations of the model, the results of our analysis indicated that tax revenues could be maintained and city residents' taxes reduced by shifting some of the burden to noncity residents, many of whom consume the public goods the city offers. To do so, our solution called for increasing the sales taxes on general and durable goods, instituting a gasoline tax, and reducing both property taxes and sales taxes on food and drugs. A major benefit of the MOLP model according to the city manager was its ability to illustrate the trade-offs between the different tax structuring objectives.

Keywords: government: tax policy; programming: multiple criteria (search for similar items in EconPapers)
Date: 1989
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