Title
Households Disposable Income
License
Public Domain (PD)
+ Works in the public domain may be used freely without the permission of the former copyright owner.

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Abstract

The Layer shows the households disposable income at the nation level for the household. The frequency is annual. The Unit of measure is GINI.
GINI is a measure of statistical dispersion intended to represent the income inequality or wealth inequality within a nation or any other group of people.
The Gini coefficient measures the inequality among values of a frequency distribution (for example, levels of income).
A Gini coefficient of zero expresses perfect equality, where all values are the same (for example, where everyone has the same income). A Gini coefficient of one (or 100%) expresses maximal inequality among values (e.g., for a large number of people where only one person has all the income or consumption and all others have none, the Gini coefficient will be nearly one).

Publication Date
Type
Vector Data
Keywords
GINI , households , income
Category
Society
characteristics of society and cultures. Examples: settlements, anthropology, archaeology, education, traditional beliefs, manners and customs, demographic data, recreational areas and activities, social impact assessments, crime and justice, census information
Regions
Europe
Responsible
Group
CULTURAL-E
More info
-
Maintenance Frequency
Frequency Of Maintenance For The Data Is Not Known
Restrictions
No Restrictions
Language
English
Temporal Extent
Jan. 1, 2010, 11:08 a.m. - Dec. 31, 2019, 11:08 a.m.
Data Quality
Dataset available on Eurostat portal 'https://ec.europa.eu/eurostat/web/products-datasets/-/ilc_di12' The table is merged with the NUTS0 layer.
Supplemental Information

Title: 'Gini coefficient of equivalised disposable income -EU-SILC survey','
Time frequency: 'Annual' ,
Scale:’GINI coefficient 0-100'

Spatial Representation Type
vector data is used to represent geographic data

Layer WMS GetCapabilities document

Attribute Name Label Description
fid
CNTR_CODE
NUTS_NAME
_2010
_2011
_2012
_2013
_2014
_2015
_2016
_2017
_2018
_2019

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