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Social Indicators Research

Erschienen in:

11.10.2018

A Multidimensional Analysis of the EU Regional Inequalities

verfasst von: Francesca Parente

Erschienen in: Social Indicators Research | Ausgabe 3/2019

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Abstract

This article illustrates the steps followed to construct a measure that accounts for multidimensional inequality across European regions in terms of human development. First, a multidimensional index to explore the between inequalities across regions has been produced. Referring to UNDP (Human development report. Technical notes, Oxford University Press, Oxford, 2018. http://hdr.undp.org/sites/default/files/hdr2018_technical_notes.pdf) updated methodology and integrating it with the European Commission (2011, 2014) contributions, a Human Development Index has been calculated for 205 regions in the European Union, within the span of time from 2000 to 2011. These estimates have then been adapted to inequality, based on intra-regional distribution of selected variables following the UNDP methodology to calculate an Inequality-adjusted Human Development Index. This allowed to explore how the human development pattern changes when accounting for within inequalities, and to estimate the Loss in potential human development due to inequality in the society. The latter can serve as a measure for multidimensional inequality. Results show a generally increased level of human development achievements despite a widespread persistent level of inequalities in its distribution, as well as a spatial connotation of both dynamics.

Vorheriger Artikel The Construction of an Integrated and Transparent Index of Wellbeing

Nächster Artikel Channels of Inequality of Opportunity: The Role of Education and Occupation in Europe

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UNDP website provides related sections for both territorial level of analysis. The Measures of America program from the US Social Science Research Council is an example of independent research in the same evaluative framework.

The choice of this period of analysis has been driven by data availability issues. Due to the combination of several different statistical sources and databases, the time interval ensuring wider coverage has been selected. Further details are provided in the “Data and methodology” section as well as in the Annex of Electronic Supplementary Material.

When available as in the European case, disposable household income is a more precise measure than the national aggregate. Tertiary education was instead preferred over years of schooling as a better representative of educational attainments in the case of advanced economies (Bubbico and Dijkstra 2011).

Health: life expectancy and healthy life expectancy, plus infant mortality; Knowledge: NEET and general tertiary education; Income: employment and net adjusted disposable income.

The Alkire and Foster (2010) adaptation of the Foster et al. (2005) method. That is why this index is somewhere also referred to as “FLS IHDI”.

1. Population invariance = the amount of inequality does not depend on the population size; 2. Symmetry (or anonymity) = the amount of inequality does not depend on who has each achievement; 3. Scale invariance = the amount of inequality does not depend on the total achievement; 4. Pigou-Dalton Principle = if there is a regressive transfer, inequality increases (Salvareda et al. 2011).

That is, if inequality in one population subgroup decreases (increases), and inequality in the other population subgroup remains unchanged, overall inequality should decrease (increase).

This case assumes an additive social welfare function, defined itself by a utility function with a constant risk aversion parameter. For a detailed derivation of the formula, see also Alkire and Foster (2010).

From the original French definition: Nomenclature des Unités Territoriales et Statistiques. The higher territorial level in the NUTS hierarchy is 0, which stands for countries. Sub-national levels slightly vary across Member States, adapting to national administrative systems. Generally speaking, level 1 represents macro-regions, level 2 regions and level 3 sub-regional partitions. The classification here used is that from 2010 revision.

The choice of restricting the study to 15 Member States only has been due to data availability and comparability across countries.

Four French, three Spanish and two Portuguese oversea departments (FR91-FR94; ES63, ES64, ES70; PT20, PT30).

Due to the wider coverage it ensures across the considered domains of the analysis.

Life expectancy at given exact age is defined by Eurostat as “the mean number of years still to be lived by a person who has reached a certain exact age, if subjected throughout the rest of his or her life to the current mortality conditions (age-specific probabilities of dying)”.

Min appears to be Norte (PT11) in 1991 with 74 years, and Max is Comunidad de Madrid (ES30) in 2013 with 84.8 years.

Cheshire (UKD6) and Merseyside (UKD7) in 2000/2001; The Netherlands in 2001; Germany in 2000/2001 [Detmold (DEA4) and Arnsberg (DEA5) also until 2009].

Used data represent the percentage of people aged 25-64 with these levels of education, as derived from the Labour Force Survey and provided by Eurostat and available from 2000 to 2016.

The applied estimate is explained in the Annex of Electronic Supplementary Material.

Its data sources are National Institutes for Statistics. Since OECD territorial units’ classification slightly differs from the Eurostat one, some preliminary data processing was needed. Detailed data treatment is reported in the Annex of Electronic Supplementary Material.

PPS are an artificial currency unit derived by dividing any economic aggregate of a country in national currency by its respective purchasing power parities. Here they have been calculated by means of PPP at EU15 = 1 (provided by Eurostat). Original data have been selected in national currency per head at current prices from OECD database. Additional notes on methodology and implications of conversion to PPS are provided in the Annex of Electronic Supplementary Material.

Min appears to be Extremadura (ES43) in 1995 with a 6519 PPS value, and Max is Inner London (UKI1) in 2013 with a 39,577 PPS value.

Which would be foreseen by the latest UNDP methodology (2018).

It has to be noted that UN life tables are abridged ones with five-years age interval, while Eurostat available ones are year-by-year. The used age interval here considered has then been n = 1.

Considered available data range from year 2004 to 2011.

EU-Silc data refer to 1997 classification of International Standard Classification of Education. ISCED were designed by UNESCO in 1970s to ease the comparability of educational attainments across different national educational systems.

See previous paragraph 3.1.

Correspondence has been set to: 0 = two, 1 = seven, 2 = ten, 3 = fourteen, 4 = seventeen, 5 = twenty-two.

Equivalence scales are the parameter by which, in income analysis, members of a household receive different weightings based on their age as the ability to earn and spend the household income. Dividing the total household income by the sum of the assigned weights produces a representative income per person. In the EU-Silc, Eurostat uses the “Modified OECD equivalence scale”, which counts: 1 for the first adult (≥ 14 years); 0.5 for other adults; 0.3 for children < 14.

For more details on the sensitivity analysis of income data, see Kovacevic (2010).

Using the same Eurostat purchasing power parities at EU15 = 1 previously applied to the HDI income indicator.

This will be better shown by related graphical representation in paragraph 4.

Detailed description of applied methodologies are reported in the Annex of Electronic Supplementary Material, along with obtained results of tests.

Six out of ten are above 0.9. Summary of results is provided in the Annex of Electronic Supplementary Material.

EU15 lines displayed in the graphs correspond to median values of the HDI values across regions per year. It counts 0.310 in 2000 and 0.446 in 2011. Simple arithmetic means were also calculated, and variation was minimal: − 0.006 in 2000 (0.304) and − 0.002 in 2011 (0.444).

Maps have been realised per each year, and can be provided upon request.

Here median value is 0.053 in 2000 and 0.048 in 2011. Simple arithmetic mean is instead 0.056 in 2000 and 0.050 in 2011. Average values fluctuates around a percentage loss of 5%.

Min and Max used have been selected among the internal distribution on extended time range, and happen to be respectively: UKI1 Inner London in 2013 with a PPS value of 100,958, and ES43 Extremadura in 1999 with 11,652.

See paragraph 3.1 for further details.

See the “Additional notes on methodology and limits” in the Annex of Electronic Supplementary Material for further details.

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Titel: A Multidimensional Analysis of the EU Regional Inequalities
verfasst von: Francesca Parente
Publikationsdatum: 11.10.2018
Verlag: Springer Netherlands
Erschienen in: Social Indicators Research / Ausgabe 3/2019
Print ISSN: 0303-8300
Elektronische ISSN: 1573-0921
DOI: https://doi.org/10.1007/s11205-018-2000-6

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