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Should income be taken for granted as a sole driver of welfare? Bayesian insight on the relevance of non-income drivers of welfare

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  • Wiśniewski Tomasz P.

    (Collegium of World Economy, Warsaw School of Economics, Warsaw, Poland)

Abstract

The paper consists of a discussion on the relevance of non-income drivers of welfare. This discussion is based on a subjective Bayesian reasoning, where welfare perceptions are subjectively rational decisions of individuals, who are, as author suggests, the ultimate decision-makers in respect of what welfare actually means for them. The objective of the paper is to investigate if income should be taken for granted as a sole driver of welfare. The conclusion is drawn from a methodological investigation of this question in a Bayesian concept of probability with a consideration for correlations among income and non-income drivers of welfare. It suggests that income should not be taken for granted as a sole driver of welfare since the non-income factors, which are not correlated with income, appear to be relevantly affecting individuals’ perceptions of welfare with Bayesian probability of almost 65%. Thereby, the paper is a reaffirmation of a need for further research in the area of welfare measures that might constitute an alternative to income-dominated indicators. Its value emanates from unambiguous answer in favour of the relevance of non-income drivers across welfare perceptions, which, without Bayesian reasoning, could remain unsolved at the point of 50% odds for relevance (irrelevance).

Suggested Citation

  • Wiśniewski Tomasz P., 2018. "Should income be taken for granted as a sole driver of welfare? Bayesian insight on the relevance of non-income drivers of welfare," International Journal of Management and Economics, Warsaw School of Economics, Collegium of World Economy, vol. 54(1), pages 58-68, March.
    • Handle: RePEc:vrs:ijomae:v:54:y:2018:i:1:p:58-68:n:6
    DOI: 10.2478/ijme-2018-0006
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    References listed on IDEAS

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    More about this item

    Keywords

    welfare; non-income welfare; subjectivism of welfare; drivers of welfare; welfare perception; welfare measurement; Bayesian probability;
    All these keywords.

    JEL classification:

    • I - Health, Education, and Welfare
    • C - Mathematical and Quantitative Methods

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