Comparable Indicators of Inequality Across Countries
housing may or may not be included. (Note that this also depends on the tax system which in certain countries al-
ready forces the inclusion of some components into taxable income or earnings.) EU-SILC, for example, includes
estimated values for these as a component of income, but only from 2007 including the income from the private
use of a company car. There is clear potential for non-comparability over time within a country and across national
data sources for different countries in this respect. Another income type that is sometimes omitted and sometimes
included is amounts transferred from one household to another, either on a regular or once-off basis. We return to
these issues in discussing specific data sources below (with particular emphasis on differences in the definition/
measurement of income between ECHP versus EU-SILC) but highlight here the general point that different defini-
tions of income are employed and that such differences may significantly impact on comparability over time and
across countries. Again these need to be made explicit and their effects on key results scrutinised.
It is also important to be aware that in some cases certain sources of income may be based on imputed es-
timates rather than obtained directly. For example, in some data sources gross income is directly measured but
income taxes and social insurance contributions are then estimated on the basis of the relevant tax/contribution
codes and the characteristics of the household. This is true for the Cross-National Equivalent File based on panel
survey data from the US, Germany, Britain, Canada and Australia, and for some countries in EU-SILC.2 A related,
important point is that in EU-SILC individual income components - earnings, self-employment income, transfers
- are reported as gross amounts, whereas in the ECHP the income components were recorded net of income tax
and social insurance contributions.3 EU-SILC is thus better aligned to the analysis of the scale of redistribution
by transfers and direct taxes, often a key variable of interest. Another significant source of variation and potential
non-comparability arises where information is sought but not given by some respondents, where missing values
may be imputed; practices differ across statistical agencies and surveys in this respect, in a manner which is often
not transparent. It is also important to be aware that some sources of income are generally more poorly measured
in household surveys than others, with income from self-employment and from capital prominent examples of
sources that are less well measured; this may bias estimates of the degree and nature of inequality in a particular
country at a given point in time, but since the extent of mis-measurement may also vary across countries and over
time, may be a source of bias in those contexts too. Finally, top-coding of high incomes in some datasets may sig-
2 Eurostat has developed a generic model for net-gross conversion to meet the EU-SILC requirements for the construction of the standard-
ised income variables, named the Siena Micro-Simulation Model (SM2).
3 It gives a net/gross factor though for the household as a whole which applies to all its members.
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