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Pareto Models, Top Incomes, and Recent Trends in UK Income Inequality

Author

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  • Jenkins, Stephen P.

    (London School of Economics)

Abstract
I determine UK income inequality levels and trends by combining inequality estimates from tax return data (for the 'rich') and household survey data (for the 'non-rich'), taking advantage of the better coverage of top incomes in tax return data (which I demonstrate) and creating income variables in the survey data with the same definitions as in the tax data to enhance comparability. For top income recipients, I estimate inequality and mean income by fitting Pareto models to the tax data, examining specification issues in depth, notably whether to use Pareto I or Pareto II (generalised Pareto) models, and the choice of income threshold above which the Pareto models apply. The preferred specification is a Pareto II model with a threshold set at the 99th or 95th percentile (depending on year). Conclusions about aggregate UK inequality trends since the mid-1990s are robust to the way in which tax data are employed. The Gini coefficient for gross individual income rose by around 7% or 8% between 1996/97 and 2007/08, with most of the increase occurring after 2003/04. The corresponding estimate based wholly on the survey data is around –5%.

Suggested Citation

  • Jenkins, Stephen P., 2016. "Pareto Models, Top Incomes, and Recent Trends in UK Income Inequality," IZA Discussion Papers 10124, Institute of Labor Economics (IZA).
  • Handle: RePEc:iza:izadps:dp10124
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    References listed on IDEAS

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    More about this item

    Keywords

    inequality; top incomes; Pareto distribution; generalized Pareto distribution; survey under-coverage; HBAI; SPI;
    All these keywords.

    JEL classification:

    • C46 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Specific Distributions
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution

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