HLEG workshop on Measuring Inequalities of Income and Wealth, 15-16 September 2015, Berlin, Germany, More information at: http://oe.cd/hleg-workshop-inequalities-income-and-wealth

1. MONITORING THE EVOLUTION OF INCOME POVERTY AND REAL
INCOMES OVER TIME
A.B. ATKINSON, A.-C. GUIO AND E. MARLIER
Eric Marlier

2. 2
CONTEXT
• For many years, sharp separation between macro-economic
evaluation of economic policy and analysis of impact of
policy on living standards of hhds
• “Beyond GDP” agenda rightly calls for a more integrated
approach  National income (NA) has to be reconnected
with hhd incomes and with the distrib. of these incomes
• From the side of hhd statistics, increasing recognition that
existing income poverty/ distribution indicators need to be
complemented by measures of “real” incomes  Important
step forward (2014): EU social indicators’ portfolio now
includes an aggregate indicator of (unadjusted) real gross
hhd disposable income [“unadjusted”=STIK excluded]

3. 3
NEED FOR RECONCILIATION  UNDERSTANDING THE DIFFERENCES
• Our focus is on social indicators which are centrally concerned
with distributional issues
• Measures of the evolution of real incomes can be derived
from both NA and surveys  Raises important method. issues
• National accounts are based on aggregate information;
• whereas social indicators are largely derived from hhd surveys (EU-SILC) and, in
a growing number of countries, these surveys largely rely on register data.
• Micro and macro evidence have to be reconciled. They may
differ, for ex in the underlying definitions. We can only have
confidence in the 2 sources if we understand the relation (the
differences) between them

4. 4
NEED FOR RECONCILIATION  UNDERSTANDING THE DIFFERENCES
• Seven EU-27 MSs combine the hhd sector (S14) with the
“Non-Profit Institutions Serving Households” sector (S15),
which includes bodies such as charities, churches, learned
societies, trade unions, political parties and sports clubs: 6
EU-15 MSs (AT, DK, DE, IE, LU, UK) and Malta
• Thus, only nine EU-15 countries provide statistics for the
S14 sector for unadjusted GHDI (where STIK are excluded
in line with the basis for the recently adopted EU social
indicator)

5. 5
NEED FOR RECONCILIATION  UNDERSTANDING THE DIFFERENCES
• Impossibility of separating S14 and S15 problematic for
Unadjusted GHDI. For ex, in France, where there are
separate accounts for S14 and S15: In terms of gross
income before adjustment, NPISH sector around 3% of hhd
sector: €45.5 billion in 2013, compared with €1,326.3
billion… but most of the gross income is used to make STIK
to the hhd sector.  Moving from Unad. GHDI to Ad. GHDI
adds to S14 and subtracts from S15, leaving S15 with only
€2.1 billion.  For Ad. GHDI, including NPISH would make
little difference, but Un. GHDI would be some 3% higher.
 All MSs should provide NA data for the hhd sector S14
excluding S15.

6. Ratio between EU-SILC mean income per capita and NA unadjusted
GHDI per capita (S14), EU15 (9 countries), 2005-2012 (Income years)

7. Ratio between mean income per capita (EU-SILC) and NA Unadjusted GHDI
per capita (S14), 95% confidence interval, 2012 (Income year)
0.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70
0.80
0.90
1.00

8. 8
NEED FOR RECONCILIATION  UNDERSTANDING THE DIFFERENCES
Let’s now compare the real mean income per capita
(EU-SILC) and the unadjusted GHDI (NA) for the period
2005-2012 (2005=100). The years are the income
years.

9. Real mean income per capita (EU-SILC, blue line)
and unadjusted GHDI (NA, red line), 2005-2012
(2005=100, 70-120 scale) (Income years)
70
75
80
85
90
95
100
105
110
115
120
2005 2006 2007 2008 2009 2010 2011 2012
AT
AT AT NA
70
75
80
85
90
95
100
105
110
115
120
2005 2006 2007 2008 2009 2010 2011 2012
BE
BE BENA
70
75
80
85
90
95
100
105
110
115
120
2005 2006 2007 2008 2009 2010 2011 2012
CY
CY CY NA
70
75
80
85
90
95
100
105
110
115
120
2005 2006 2007 2008 2009 2010 2011 2012
CZ
CZ CZ NA
70
75
80
85
90
95
100
105
110
115
120
2005 2006 2007 2008 2009 2010 2011 2012
DK
DK DK NA
70
75
80
85
90
95
100
105
110
115
120
2005 2006 2007 2008 2009 2010 2011 2012
DE
EE EENA
70
75
80
85
90
95
100
105
110
115
120
2005 2006 2007 2008 2009 2010 2011 2012
EL
EL EL NA
70
75
80
85
90
95
100
105
110
115
120
2005 2006 2007 2008 2009 2010 2011 2012
ES
ES ES NA
70
75
80
85
90
95
100
105
110
115
120
2005 2006 2007 2008 2009 2010 2011 2012
FI
FI FINA
70
75
80
85
90
95
100
105
110
115
120
2005 2006 2007 2008 2009 2010 2011 2012
HU
HU HU NA
70
75
80
85
90
95
100
105
110
115
120
2005 2006 2007 2008 2009 2010 2011 2012
IE
IE IE NA
70
75
80
85
90
95
100
105
110
115
120
2005 2006 2007 2008 2009 2010 2011 2012
IT
IT IT NA
70
75
80
85
90
95
100
105
110
115
120
2005 2006 2007 2008 2009 2010 2011 2012
LU
LU LU NA
70
75
80
85
90
95
100
105
110
115
120
2005 2006 2007 2008 2009 2010 2011 2012
NL
NL NL NA
70
75
80
85
90
95
100
105
110
115
120
2005 2006 2007 2008 2009 2010 2011 2012
PT
PT PT NA
70
75
80
85
90
95
100
105
110
115
120
2005 2006 2007 2008 2009 2010 2011 2012
SE
SE SENA
70
75
80
85
90
95
100
105
110
115
120
2005 2006 2007 2008 2009 2010 2011 2012
SI
SI SINA
70
75
80
85
90
95
100
105
110
115
120
2005 2006 2007 2008 2009 2010 2011 2012
UK
UK UK NA

10. Real mean income per capita (EU-SILC, blue line)
and unadjusted GHDI (NA, red line), 2005-2012
(2005=100, 70-190 scale) (Income years)
70
90
110
130
150
170
190
2005 2006 2007 2008 2009 2010 2011 2012
BG
BG BG NA2
70
90
110
130
150
170
190
2005 2006 2007 2008 2009 2010 2011 2012
EE
EE EENA
70
90
110
130
150
170
190
2005 2006 2007 2008 2009 2010 2011 2012
LT
LT LT NA
70
90
110
130
150
170
190
2005 2006 2007 2008 2009 2010 2011 2012
LV
LV LV NA
70
90
110
130
150
170
190
2005 2006 2007 2008 2009 2010 2011 2012
PL
PL PL NA
70
90
110
130
150
170
190
2005 2006 2007 2008 2009 2010 2011 2012
RO
RO RONA
70
90
110
130
150
170
190
2005 2006 2007 2008 2009 2010 2011 2012
SK
SK SKNA

11. 11
CONCLUSIONS
• As we have seen, trends and/or levels diverge a lot in
some countries between EU-SILC and NA . These
differences are of concern both on account of their
magnitude and because there is no systematic pattern.
This warrants further investigation.
• One obstacle when seeking to understand the differences,
is the problem in matching income by category in the 2
sources – esp. for property income and operating surplus.
Priority for further work developing the earlier
comparisons.

12. 12
CONCLUSIONS
• Need to further confront NA and EU-SILC  Pursue recent
important work by the Eurostat and OECD Joint Expert
Group, and the report by Mattonetti (2013) for Eurostat
• A positive note to finish with… The differences between the
2 sources seem to be stable (with certain exceptions). EU-
SILC, in close conjunction with NA, can provide a sound
basis for better monitoring trends over time in poverty and
real incomes… even if further work is required
• An LSE (CASE) Working Paper presents this research in
detail. We would very much welcome your feedback on it as
it is still work in progress. Please kindly send your
feedback to eric.marlier@skynet.be