Correcting the underestimation of capital incomes in inequality indicators: a UK case study

5 novembre 2020
5 November 2020
Contatti: 
Doctoral School of Social Sciences
via Verdi 26, 38122 - Trento
Tel. 
+39 0461 283756 - 2290
Fax 
+39 0461 282335

Skype: school.socialsciences

Time: 2 PM

Speaker:

 

Abstract

I propose a methodological framework to better incorporate non-labour income into existing indicators of economic inequality. Poor measurement of capital incomes in household surveys has long been acknowledged but attempts to correct for this have remained few. Capital incomes are disproportionately held at the top of the income distribution where measurement error is largest. In recent years, there has been a surge in top income harmonisation methodologies, combining survey and tax data, which are found to have a significant upward effect on the indicators.

The current analysis finds that these methods fail to correct entirely for capital income underestimation and puts forward a capital income adjustment which can be applied to existing top income methodologies. The adjustment accounts for both under-coverage and under-estimation error of capital income across the income distribution, using as benchmark information reported in tax administrative sources. The UK household survey has experienced a significant decline in capital income measurement over the past 20 years (1997-2016).

Therefore, it provides a relevant case study to investigate thoroughly the causes of capital income underestimation combined with an empirical application of the proposed adjustment. The household survey is traditionally used to produce inequality indicators used by governments, statistical offices and policy makers. This marks its societal relevance and the importance of keeping scrutinising all types of biases in household surveys.

The policy implication is that any type of income missing from indicators structurally falls out of inequality debates, which has arguably been the case for capital incomes.
 

Please contact school.socialsciences [at] unitn.it for the link to the Zoom event.

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