published in: Journal of the Dublin Statistical Society, 2021, 50, 1-15
There are two main sources of data on income distribution. Household based surveys report mainly on inequality in equivalised household level disposable income. Top income shares, on the other hand, focus on the tax unit as the unit of analysis, because administrative records are obtained from such units. Tax return data is typically analysed in terms of unequvalised fiscal income and obtains better coverage of those at the very top of the income distribution.
In this paper, we find that differences in concepts and measures play a very substantial role in accounting for the divergence in the pictures of inequality arising from household and tax return data. Estimates of the share of the top 10% of tax units in fiscal income from the two sources are quite close. Average incomes for the top 1% of the population appear to be substantially higher in tax return data than in SILC - a pattern that has often been observed internationally. We conclude that there is a strong case for examining potential adjustments to survey data to ensure better representation of income levels at the very top of the income distribution.
We use cookies to provide you with an optimal website experience. This includes cookies that are necessary for the operation of the site as well as cookies that are only used for anonymous statistical purposes, for comfort settings or to display personalized content. You can decide for yourself which categories you want to allow. Please note that based on your settings, you may not be able to use all of the site's functions.
Cookie settings
These necessary cookies are required to activate the core functionality of the website. An opt-out from these technologies is not available.
In order to further improve our offer and our website, we collect anonymous data for statistics and analyses. With the help of these cookies we can, for example, determine the number of visitors and the effect of certain pages on our website and optimize our content.