Estimating long-run income inequality from mixed tabular data: Empirical evidence from Norway, 1875–2017

Abstract

Most evidence on the long-run evolution of income inequality is restricted to top income shares. While this evidence is relevant and important for studying the concentration of economic power, it is incomplete as an informational basis for analysing inequality in the income distribution as a whole. This paper proposes a nonparametric approach for estimating inequality in the overall distribution of income on the basis of tabular data from different sources, some in a highly aggregated form. The proposed approach is applied to Norway, for which rich historical data exist. We find evidence of very high income inequality from the late nineteenth century until the eve of World War II, followed by a rapid equalization until the 1950s. Income inequality remained low during the post-war period but has increased steadily since the 1980s. Estimates of a measure of affluence demonstrate that overall inequality has largely been governed by changes in the top half of the distribution and in the ratio between the mean incomes of the lower and upper halves of the population.

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“…Evidence in Aaberge, Atkinson, and Modalsli (2020) suggest that the overall income inequality in Norway decreased in Norway between late 1890s to around 1905 followed by stability between 1905 and 1914 and a sharp inequality increase during WW1. Unfortunately, lack of data on gender income gaps and income inequality at the local government level precludes more detailed investigation of preference differences between males and female and income groups in the period.…”

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“…Thus, Atkinson (2007) proposes to compute inequality indices by combining estimates for the upper tail from the tax data with estimates for the remainder of the population from survey data. This methodology has been adopted to study inequality in the US (Alvaredo, 2011;Atkinson et al, 2011) and mainly developed countries, from Europe (Burkhauser et al, 2016;Jenkins, 2017;Aaberge et al, 2020) and others compiled in Atkinson and Piketty (2010).…”

“…Consequently, authors such as Lustig (2019) and Aaberge et al (2020) suggest to produce lower and upper bounds of inequality measures, rather than point estimates. Figure 2 reports WID.World top 1% income shares for a diverse selection of countries, for around the early 2000s and around the late 2010s.…”

“…However, tax data are not available for all countries or are costly to update. Also, corrections made to inequality indices are not necessarily trustworthy, while being subject to some degree of uncertainty; hence, the literature calls for a focus on ranges rather than point estimates (Burkhauser et al, 2015;Jenkins, 2017;Auten and Splinter, 2019;Lustig, 2019;Aaberge et al, 2020). This paper offers an accessible simulation method to assess the mismeasurement of the upper tail of the income distribution, and to subsequently adjust the inferences made about income inequality without the need of extra data.…”

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“…Moreover, income fluctuations over time may affect the individual welfare 'per se', and hence need to be accounted for when making welfare comparisons. This has led to a spur of research on inequality and social welfare in long-term income according to the traditional Equality of Outcome view (Bourguignon et al, 2007;Piketty & Saez, 2014;Aaberge & Mogstad, 2015;Aaberge et al, 2020).…”