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www.lisdatacenter.org
UNDP 10 March 2014
Introduction to LIS: Cross-National Data Center
in Luxembourg
Luxembourg Income Study (LIS) DatabaseLuxembourg Wealth Study (LWS) Database
Janet Gornick, LIS Director
Overview of LIS
LIS was founded in 1983 by two US academics and a team of multi-disciplinary researchers in Europe.
The origin was a 7-country “study” that grew and was institutionalized as the “Luxembourg Income Study”.
In 2010, we shortened the name of our institution to “LIS”.
LIS: an overview
LIS: Cross-National Data Center (Luxembourg)• parent organization • located in Luxembourg• independent, chartered non-profit organization• cross-national, participatory governance• acquires, harmonizes, and disseminates data for research• venue for research, conferences, and user training
LIS Center (New York)• satellite office• located at the Graduate Center of the City University of New York• administrative, managerial, development support to parent office • venue for research, teaching, and graduate student supervision
Our missionTo enable, facilitate, promote, and conduct cross-national comparative research on socio-economic
outcomes and on the institutional factors that shape those outcomes.
What we do
Step 1. We identify appropriate datasets.
Step 2. We negotiate with each data provider.
Step 3. We acquire and harmonize the data.LIS’ data experts harmonize the data into a common, cross-national template. This is very labor-intensive.
Data harmonization at LIS: an overview
Harmonisation
Data harmonization at LIS: an overview
Harmonisation
The ingredients of LIS: the original datasets
Data harmonization at LIS: an overview
Harmonisation
The ingredients of LIS: the original datasets
The harmonization process
Data harmonization at LIS: an overview
Harmonisation
The ingredients of LIS: the original datasets
The harmonization process
The final output: LIS Database,LWS Database
What we do – cont.
Step 4. We check and document the harmonized data.
Step 5. We make the data available to researchers via remote access, and two other user-friendly pathways.
LIS and LWS Databases
Luxembourg Income Study Database (LIS)
• First and largest available database of harmonized income data, available at the household and person levels
• In existence since 1983• Data mostly start in 1980, some go back to the 1960s (recollected every 3-5 years)• 45 countries• ~190 datasets• Used to study: income poverty; income inequality; labor market outcomes; and, in
some datasets, expenditures on consumption
Luxembourg Wealth Study Database (LWS)
• First available database of harmonized wealth data, available at the household level• In existence since 2007• Data going back to 1994• 12 countries• 20 datasets• Used to study: household assets, debt, and expenditures; wealth portfolios
•
Current coverage: 62% of world population
84% of world GDP
Current axis of growth: middle-income countries (now 17 out of 47 countries)
Australia Denmark India Paraguay * Spain
Austria Dominican Republic *
Ireland Poland Sweden
Belgium Egypt * Israel Peru Switzerland
Brazil Estonia Italy Romania Taiwan
Canada Finland Japan Russia United Kingdom
Chile * France Luxembourg Serbia * United States
China Germany Mexico Slovak Republic
Uruguay
Colombia Greece Netherlands Slovenia
Cyprus Guatemala Norway South Africa
Czech Republic
Hungary Panama * South Korea
Users, products, services
Thousands of data users - and growing• remote execution enables use around the
world• free access for students in all countries• free access for data providers and their
staffs
Users, products, services (cont.)
Pedagogical activities• annual training workshops in Luxembourg• local workshops• self-teaching lessons online
Research activities and support• visiting scholar program• working paper series (600+)• research conferences• edited books (new one published in July
2013!)
New LIS Book published July 2013
Income Inequality: Economic Disparities and The Middle Class in Affluent Countries
Edited by Janet C. Gornick and Markus Jäntti
Stanford University Press, Social Inequality Series.
2013
Paperback coming this summer! PAPAPER BACK COMING THIS SUMMERPEhttp://www.eurospanbookstore.com/eu/income-inequality.htmlttp://
www.euhttp
Pathways to the data
Primary PathwayOutput
AccessibilityPublicly available
Registration required
Researchers only
Any advanced statistics
Cross-national descriptive tables
Ready-madeindicators
Key Figures
Web Tabulator
LISSY System
Programming
Remote-execution system (“LISSY”)
This is the primary means of access; it uses a software system that was designed specifically for LIS.
Researchers write programs (in SPSS, SAS, or Stata) and send them to the LIS server; results are returned to the researcher, with an average processing time of under two minutes.
Two other pathways to the LIS data
Web-based tabulator (“the WebTab”).
Our online table maker allows registered users to make tables, using keywords. Users can generate cross-national comparisons without the need for programming. Now, contains most recent LIS data (household-level) only.
Two other pathways to the LIS data (continued)
LIS Key Figures
Inequality and Poverty Key Figures
These include multiple inequality measures (e.g., Gini and Atkinson coefficients, percentile ratios), relative poverty rates for various demographic groups, and median and mean disposable household income. These are constructed for all LIS datasets, in all waves.
Employment Key Figures by Gender
These are a set of national-level indicators presented in ten tables. These figures highlight women’s economic outcomes and gender inequality in poverty and employment. These are available for all datasets in LIS’ Wave V (2000) and VI (2004).
Research!
The research carried out using LIS/LWS data
• assessing income inequality• measuring poverty• comparing employment outcomes• analyzing assets and debt• researching policy impacts
Assessing Income Inequality Inequality Across Households
Denmark
Slove
nia
Swed
en
Slova
k Rep
ublic
Finlan
d
Norway
Czech Rep
ublic
Netherl
ands
Switz
erlan
d
Luxe
mbourg
Beligiu
mFra
nce
Hungary
German
y
Taiw
anKorea
Austria
Irelan
d
Poland
Spain
Canad
a
Greece Ita
ly
United Kingd
om
United St
ates
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
0.40
Inequalit
y In
dic
ato
r: G
ini I
ndex
Source: Luxembourg Income Study Key Figures (publicly available online – www.lisdatacenter.org).
Measuring Poverty - IHousehold Poverty Rates
Denmark
Swed
en
Czech Rep
ublic
Netherl
ands
Finlan
d
Norway
Slove
nia
Hungary
Slova
k Rep
ublic
Switz
erlan
d
Beligiu
mFra
nce
Luxe
mbourg
German
y
Taiw
an
Poland
United Kingd
omGree
ce Italy
Austria
Canad
a
Irelan
dKorea
Spain
United St
ates
0
2
4
6
8
10
12
14
16
18
Pove
rty
Rate
(50%
of
media
n d
isposa
ble
house
hold
in
com
e)
Source: Luxembourg Income Study Key Figures (publicly available online – www.lisdatacenter.org).
Measuring Poverty - II “Real Income Levels” of Children
Note: US children: the rich are richer, and the poor are poorer.
Source: Timothy Smeeding and Lee Rainwater. 2002. Comparing Living Standards Across Nations: Real Incomes at the Top, the Bottom and the Middle, LIS Working Paper 266.
United Kingdom
United States
Australia
Germany
Netherlands
Belgium
Canada
France
Finland
Denmark
Sweden
Switzerland
Norway
0 20 40 60 80 100 120 140 160 180
89
100
103
114
120
126
126
126
131
137
137
146
157
As Percent of Low US Child Income
Sweden
Netherlands
Denmark
Germany
Australia
Norway
United Kingdom
Belgium
Finland
France
Canada
Switzerland
United States
0 20 40 60 80 100 120
54
61
63
68
69
70
71
71
76
77
87
92
100
As Percent of High US Child Income
Comparing Employment Outcomes
Earnings Equality between Women and Men
Source: Luxembourg Income Study Key Figures (publicly available online – www.lisdatacenter.org).
Switz
erlan
dFra
nceSp
ain
Hungary
Taiw
an
German
y
Swed
en
Finlan
d
Austria
Irelan
d
Slove
nia
United Kingd
om
Luxe
mbourg
Denmark
Netherl
ands
Beligiu
m
Canad
a
Slova
k Rep
ublic
United St
ates
Korea
Czech Rep
ublic
Poland
Greece
Norway Ita
ly0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
Ratio o
f W
om
en’s
Earn
ings
to M
en’s
Earn
ings
Analyzing Assets and DebtOlder Women’s Income and Asset Poverty
United States Finland Germany Italy Sweden United Kingdom0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
18
52
4237 34 38
27
12
1315
5
1812
4
54
10
8
43
3141 43
50
36Neither Income nor Asset Poor
Income Poor, NOT Asset Poor
Income Poor AND Asset Poor
Asset Poor, NOT Income Poor
45% As-set Poor
39% In-come Poor
16% In-come Poor 18% In-
come Poor
19% In-come Poor
20% In-come Poor
26% In-come Poor
64% Asset Poor 55%
Asset Poor
52% Asset Poor
39% Asset Poor
56% Asset Poor
Source: Gornick, Janet C., et al. 2009. “The Income and Wealth Packages of Older Women in Cross-National Perspective.” Journal of Gerontology: Social Sciences 64B(3): 402-414.
Researching Policy Impacts Income Inequality and Redistribution
Source: Andrea Brandolini et al, 2007, Inequality in Western Democracies: Cross-Country Differences and Time Changes, LIS Working Paper 458.
Denmark 47%
Finland 36%
Netherlands 36%
Norway 39%
Sweden 45%
Czech Rep. 41%
Germany 43%
Romania 27%
Switzerland 22%
Poland 41%
Taiwan 9%
Canada 28%
Australia 34%
United Kingdom 33%
Israel 33%
United States 23%
23
25
25
25
25
26
28
28
28
29
30
30
32
34
35
37
42
38
39
41
46
44
48
38
36
50
33
42
48
51
52
48
Gini Indices: income before taxes and transfers (upper bars) and after taxes and transfers (lower bars)
Gini index of market income Gini index of disposable income
Reduction in Gini Index
through taxes and transfers
Linking LIS Data with Other DataIncome Inequality and Earnings Mobility
Countries with higher levels of income inequality have lower levels of intergenerational economic mobility.
Source: OECD 2008. Growing Unequal: Income Distribution and Poverty in OECD Countries. Paris: OECD.
Income inequality (from LIS)
Thank you!
