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首页> 外文期刊>Review of Income and Wealth >THE LONG RUN EARNINGS DISTRIBUTION IN FIVE COUNTRIES: 'REMARKABLE STABILITY,' U, V OR W?
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THE LONG RUN EARNINGS DISTRIBUTION IN FIVE COUNTRIES: 'REMARKABLE STABILITY,' U, V OR W?

机译：五个国家的长期收益分布：“非凡的稳定性”，U，V或W？

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This Lecture has been concerned with both methodological and substantive issues. On the methodological side, I have suggested that there is a variety of types of evidence about the long-run evolution of the distribution of earnings among individuals. Going back in time typically involves drawing on sources other than household surveys, returning to sources used in the pioneering study of Lydall (1968), and making use of income tax records, as in the recent literature on top incomes stimulated by Piketty (2001, 2003). In using these different sources, I have tried to make explicit the criteria applied when judging the fitness of data for purpose, arguing that data assessment is a responsibility of data users, not just of data compilers. In some cases, data have been rejected (classification C). I have not made use of data on the joint earnings of couples. I have not made use of data on occupational differentials (although this may provide useful background information to the study of individual earnings). In other cases, data are classified as B (acceptable if not ideal), rather than A (most appropriate). Series classified as B include those where the coverage does not allow the whole distribution to be estimated, where interpolation has to be made over wide ranges, or where earnings are tabulated by income, not earnings. To sum up, I have suggested a graded approach to the classification of earnings data. Economists tend to swing between two extreme positions with regard to data quality.
机译：本讲座涉及方法论和实质性问题。在方法论方面，我已经提出了关于个人之间收入分配的长期演变的各种证据。时光倒流通常涉及利用除家庭调查之外的其他来源，返回Lydall（1968）的开创性研究中使用的来源，并利用所得税记录，如有关Piketty（2001， 2003）。在使用这些不同的来源时，我试图明确指出在判断数据是否适合目的时适用的标准，认为数据评估是数据用户的责任，而不仅仅是数据编译者的责任。在某些情况下，数据已被拒绝（分类C）。我没有利用夫妻共同收入的数据。我没有使用有关职业差异的数据（尽管这可能为研究个人收入提供有用的背景信息）。在其他情况下，数据被分类为B（如果不理想，则可以接受），而不是A（最合适）。分类为B的系列包括那些不能覆盖整个范围的估计，必须在较大范围内进行插值，或者收入是按收入而非收入进行列表的那些。综上所述，我建议对收益数据进行分级分类。在数据质量方面，经济学家倾向于在两个极端之间摇摆。

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