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Parameter Evaluation for a Statistical Mechanical Model for Binary Choice with Social Interaction

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  • Alex Akwasi Opoku
  • Godwin Osabutey
  • Charles Kwofie

Abstract

In this paper we use a statistical mechanical model as a paradigm for educational choices when the reference population is partitioned according to the socioeconomic attributes of gender and residence. We study how educational attainment is influenced by socioeconomic attributes of gender and residence for five selected developing countries. The model has a social and a private incentive part with coefficients measuring the influence individuals have on each other and the external influence on individuals, respectively. The methods of partial least squares and the ordinary least squares are, respectively, used to estimate the parameters of the interacting and the noninteracting models. This work differs from the previous work that motivated this work in the following sense: (a) the reference population is divided into subgroups with unequal subgroup sizes, (b) the proportion of individuals in each of the subgroups may depend on the population size , and (c) the method of partial least squares is used for estimating the parameters of the model with social interaction as opposed to the least squares method used in the earlier work.

Suggested Citation

  • Alex Akwasi Opoku & Godwin Osabutey & Charles Kwofie, 2019. "Parameter Evaluation for a Statistical Mechanical Model for Binary Choice with Social Interaction," Journal of Probability and Statistics, Hindawi, vol. 2019, pages 1-10, March.
    • Handle: RePEc:hin:jnljps:3435626
    DOI: 10.1155/2019/3435626
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