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A Multiple-Objective Policy Model: Results of an Application to a Developing Country

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  • Augusto A. Legasto, Jr.

    (Rutgers University)

Abstract

In this paper the results and implications of an application of dynamic simulation modeling to the study of control of social unrest in a developing country are presented. The model demonstrates the use of a multiple-objective, multiple-group objective function designed to monitor the "pressure level" of social unrest in the modeled system. An outline of the model structure is presented and sample relationships are explained in detail to demonstrate the dynamic and feedback nature of the model. The paper then presents some of the recommendations and their managerial and public policy implications derived from a policy analysis of the model. The analysis, for instance, reveals that a program designed to achieve the highest possible economic growth rate could adversely affect the society's stability in the long run. The study, in addition, finds that an extensive income redistribution program, designed to tax the rich more heavily and to substantially increase the minimum income of the poor, proves to be myopic while an extensive wealth redistribution program is shown to bring about a significant and sustained improvement in the system's stability. These results raise serious questions on much of the attitudes that underlie economic development and income redistribution programs in countries like India, Brazil, the Philippines and, to some extent, the United States.

Suggested Citation

  • Augusto A. Legasto, Jr., 1978. "A Multiple-Objective Policy Model: Results of an Application to a Developing Country," Management Science, INFORMS, vol. 24(5), pages 498-509, January.
  • Handle: RePEc:inm:ormnsc:v:24:y:1978:i:5:p:498-509
    DOI: 10.1287/mnsc.24.5.498
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    Cited by:

    1. Martic, Milan & Savic, Gordana, 2001. "An application of DEA for comparative analysis and ranking of regions in Serbia with regards to social-economic development," European Journal of Operational Research, Elsevier, vol. 132(2), pages 343-356, July.

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