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The drivers of labour income inequality -- an analysis based on Bayesian Model Averaging

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  • I. Koske
  • I. Wanner

Abstract

Many Organisation for Economic Co-operation and Development (OECD) countries have seen income inequality rising over the past decade, which has led to a renewed interest among researchers and policy makers in understanding the causes of income inequality. To shed light on this issue, this article investigates the determinants of labour income inequality for a sample of 22 OECD countries. As model uncertainty is likely to be a major issue in such an underpinning, the empirical analysis relies on a Bayesian Model Averaging (BMA) technique. The results suggest that in particular labour, education and tax policies have an important influence on the distribution of labour income.

Suggested Citation

  • I. Koske & I. Wanner, 2013. "The drivers of labour income inequality -- an analysis based on Bayesian Model Averaging," Applied Economics Letters, Taylor & Francis Journals, vol. 20(2), pages 123-126, February.
    • Handle: RePEc:taf:apeclt:v:20:y:2013:i:2:p:123-126
    DOI: 10.1080/13504851.2012.683164
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    References listed on IDEAS

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    Cited by:

    1. Enrique Moral-Benito, 2015. "Model Averaging In Economics: An Overview," Journal of Economic Surveys, Wiley Blackwell, vol. 29(1), pages 46-75, February.
    2. Vanesa Jorda & Jose M. Alonso, 2020. "What works to mitigate and reduce relative (and absolute) inequality?: A systematic review," WIDER Working Paper Series wp-2020-152, World Institute for Development Economic Research (UNU-WIDER).

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