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The use of Fuzzy Decision Tree Analysis in Monitoring a Minimum Wage

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  • Malcolm Beynon, Keith Whitfield

Abstract

Effective monitoring of a minimum wage, requires that establishments potentially paying low wages are effectively identified. This paper investigates the identification of establishments paying low wages prior to the introduction of the British National Minimum Wage in 1999, through the utilization of fuzzy decision trees. Incorporating a fuzzy aspect within this problem (using membership functions) enables the judgements to be made with linguistic scales. An intelligent technique for constructing the required membership functions is introduced, which greatly reduces the necessity of any expert opinion within their construction. The Parzen windows method of estimating a probability distribution and the FUSINTER method of continuous variable discretisation are incorporated in this technique. An illustration of the utilization of the constructed fuzzy 'if ÷ then ÷' rules is included.

Suggested Citation

  • Malcolm Beynon, Keith Whitfield, 2001. "The use of Fuzzy Decision Tree Analysis in Monitoring a Minimum Wage," Computing in Economics and Finance 2001 101, Society for Computational Economics.
    • Handle: RePEc:sce:scecf1:101
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    More about this item

    Keywords

    FUSINTER; Fuzzy decision trees; Labour economics; Low pay; Membership functions; Parzen windows;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials

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