MORE TARGETING, LESS REDISTRIBUTION? AN ENQUIRY INTO THE ROLE OF POLICY DESIGN IVE MARX, LINA...
-
Upload
grant-greer -
Category
Documents
-
view
212 -
download
0
Transcript of MORE TARGETING, LESS REDISTRIBUTION? AN ENQUIRY INTO THE ROLE OF POLICY DESIGN IVE MARX, LINA...
1
MORE TARGETING, LESS REDISTRIBUTION? AN ENQUIRY INTO THE ROLE OF POLICY
DESIGN
I V E M A R X , L I N A S A L A N A U S KA I T E , G E R L I N D E V E R B I S T
C E N T R U M VO O R S O C I A A L B E L E I D H E R M A N D E L E E C K ,
U N I V E R S I T E I T A N T W E R P E N
October 2, 2013 Lisbon, Portugal
EUROMOD Research Workshop
2
Outline
Background & aimMethodologyResults Conclusions
3
BACKGROUND & AIM
4
Paradox of redistribution
Korpi and Palme (1998) : “the more we target benefits at the poor... [], the less likely we are to reduce poverty and inequality”.
Recent contests of this observation: Kenworthy (2011), Brady and Bostic (2012), Marx et al. (2013).
Source: Kenworthy (2011)
5
Targeting: concept
Targeting = a policy design instrument Korpi and Palme (1998):
targeting = “excluding the better-off citizens” Kenworthy (2011),
“targeted transfers are directed [] to those with low incomes and assets, whereas universal transfers are provided to most or all citizens”.
Whiteford (2010): “a means of determining either eligibility for benefits or
the level of entitlements for those eligible”.....
6
Targeting: measurement
Korpi and Palme (1998): The degree of low-income targeting or “Index of the degree of targeting of transfers” , also called “ Index of targeting of transfer income”
= the extent to which budgets used for redistribution go to those defined as poor.
= "index of concentration”.
Concentration coefficient: twice the area between the concentration curve and the
line of equality (the 45-degree line); similar to GINI, but its ranking variable (e.g. disposable
income) and the variable of interest (e.g. social transfers) are different.
7
Concentration coefficient
Bounded between –1 and 1; some thresholds: -1.0 - the poorest person (based on the chosen income distribution)
gets all the transfer income; 0 – everybody gets equal absolute amounts of transfers; [-1; 0] – a strong pro-poor distribution of social transfers; = GINI index value - all individuals get the same proportion of
transfers; [0; GINI index value] - weakly pro-poor distribution of transfers; > GINI index value - pro-rich distribution of social transfers; +1.0 –the richest person gets all the transfer income.
Some properties: Unless ranking is affected, a change in the degree of income
inequality does not affect the concentration index measure. Invariant to multiplication by any scalar; however sensitive to
changes based on any linear (i.e; adding a constant to the variable) transformation of the variable of interest.
8
Redistribution
Absolute reduction in income inequality: GINImarket-GINIdisposable
Relative reduction in income inequality: (GINImarket-GINIdisposable)/GINImarket
9
Targeting and redistribution
Korpi and Palme (1998): “Without specifying the functional form or all other
relevant factors, []… final redistribution is a function of : degree of low-income targeting x redistributive
budget size; Trade-off: the greater the degree of low-income
targeting, the smaller the redistributive budget. Paradox of Redistribution.
Note: properties of concentration coefficient.
10
Aim
1. How do changes in concentration coefficient of social transfers relate to redistribution?
2. To what extent could we place an equality sign between the concentration coefficient and targeting as a policy design instrument?
Two first focus countries: Ireland and LithuaniaYears: 2007-2012.
Today’s presentation: selected results.
11
METHODOLOGY
12
ATBE
CY
CZDEDK
EEES
FIFR
GR
HUIE
IS
ITLT
LU
LV
NL
NOPL
PT
SE SI
SKUK
20
30
40
50
Re
dis
trib
utio
n in
de
x
-.2 -.1 0 .1 .2
Targeting (Concentration index, ranking on disposable income)
Country selection: EU-SILC data
ATBE
CY
CZDE
DK
EEES
FI
FR
GR
HU
IE
IS
IT
LT
LU
LV
NLNO
PL PT
SE SI
SKUK
20
30
40
50
Re
dis
trib
utio
n in
de
x
-.2 -.1 0 .1 .2
Targeting (Concentration index, ranking on disposable income)
2006 2010
13
Targeting and redistribution
A link between GINI and CI: Using Rao (1969) decomposition of income inequality, GINI=sum(s*CI) sum of “contributions” of diverse
concentration coefficients to the overall inequality. Redistribution (absolute reduction):
RE = GINIMI-GINIDI
= GINIMI - sst*CIST - smi*CIMI-stax*CITAX
where s is a relative share of income component in disposable income, so that ∑ si = 1.
14
Methodology
Empirical analysis: We use microsimulation model EUROMOD (version
F6.36), in order to assess: policy design change impact on redistribution and
concentration coefficient of social transfers; the redistribution impact of changing market income
distribution and changing socio-demographic structures.
Simulation scenarios: Ireland: 2008 dataset, plus 2007-2011 policies
(baselines and reformed policies); Lithuania: 2008 and 2010 datasets, plus 2007-2012
policies (baselines and reformed policies).
15
SELECTED RESULTS
16
2008 data, policy years 2007-2012
2010 data, policy years 2009-2012
Lithuanian baselines
20072008
2009
2010
20112012
.145
.15
.155
.16
RE
(ab
solu
te)
0 .02 .04 .06 .08
CI
2009
2010
2011
2012.175
.18
.185
.19
RE
(ab
solu
te)
.07 .08 .09 .1 .11
CI
17
Ireland baselines
2007
2008
20092010
2011
2012
.24
.25
.26
.27
RE
(ab
solu
te)
-.06 -.05 -.04 -.03 -.02
CI
Data: 2008
18
RE: decomposition by factors (1)
Here and further on: focus on two years 2008 & 2009. Overall observations:
Higher redistribution level in Ireland than in Lithuania: both due to GINIMI > in Ireland; and GINIDI < in Ireland.
Progressivity of market income is rather similar in both countries. Stronger pro-poor distribution of social transfers and taxes in
Ireland. Lithuania RE GINI_m
i GINI_di CI_tr s_tr / di CI_mi s_mi / di CI_tax s_tax
I08, P08 0.149 0.482 0.334 0.057 0.236 0.427 1.007 0.453 -0.243
I08, P09 0.161 0.483 0.322 0.072 0.254 0.416 0.964 0.444 -0.218
Ireland RE GINI_mi GINI_di CI_tr s_tr / di CI_mi s_mi /
di CI_tax s_tax
I08, P08 0.243 0.514 0.272 -0.055 0.308 0.467 0.902 0.631 -0.210
I08, P09 0.265 0.515 0.250 -0.026 0.337 0.452 0.937 0.601 -0.274
19
RE: decomposition by factors (2)
Changes from 2008 to 2009: Redistribution increases in both countries decrease in GINIDI (market
income distribution remains stable). GINIDI component changes: Similar changes regarding progressivity and relative shares of social
transfers – CI reduces, whereas the relative share of social transfers increases;
Similar slight drop in CI of market income and taxes; Diverging roles of relative shares of market income and taxes: a small
drop in Lithuania, but an increase in Ireland. Lithuani
aRE GINI_m
i GINI_di CI_tr s_tr / di CI_mi s_mi / di CI_tax s_tax
I08, P08 0.149 0.482 0.334 0.057 0.236 0.427 1.007 0.453 -0.243
I08, P09 0.161 0.483 0.322 0.072 0.254 0.416 0.964 0.444 -0.218
Ireland RE GINI_mi GINI_di CI_tr s_tr / di CI_mi s_mi /
di CI_tax s_tax
I08, P08 0.243 0.514 0.272 -0.055 0.308 0.467 0.902 0.631 -0.210
I08, P09 0.265 0.515 0.250 -0.026 0.337 0.452 0.937 0.601 -0.274
20
More detailed look - Lithuania
What policy changes are the main triggers of lower targeting degree? A reminder: CI increases to 0.072 from 2008 to 2009 (data the same). Increased targeting is due to the universal child benefit becoming
means-tested (Sc. 1). No other big influences by changes in other transfers (Sc. 2).
Loweered targeting due to changes in tax and SIC structures (Sc. 3).
Influence of uprating factors – a major jump in a few dimensions (Sc. 4).
Policy design and targeting: country’s social transfers become more targeted, however other policy changes are main drivers of reducing targeting degree.
Lithuania
RE GINI_mi GINI_di CI_tr s_tr / di CI_mi s_mi /
di CI_tax s_tax
Sc. 1 0.151 0.482 0.332 0.048 0.235 0.427 1.009 0.452 -0.244
Sc. 2 0.151 0.482 0.330 0.045 0.236 0.427 1.007 0.452 -0.243
2008 0.149 0.334 0.057 0.236 0.427 1.007 0.453 -0.243
Sc. 3 0.140 0.482 0.341 0.068 0.223 0.427 1.005 0.454 -0.228
Sc. 4 0.157 0.483 0.327 0.093 0.255 0.415 0.982 0.442 -0.237
21
More detailed look - Ireland
What policy changes are the main triggers of becoming more universal? A reminder: CI increases from -0.055 to - 0.026 given a change in policies
from 2008 to 2009 (same data). No big influence by changes in means-tested or non means-tested
benefits. Biggest CI increase driven by “Public Sector Pension Related
Deduction” (Sc. 1). Even bigger role is played by changes in the tax policy: e.g. an
introduction of a special income levy (Sc. 2). Uprating factors also have a strong role (Sc. 3). Policy design and targeting: the change in targeting degree is not
directly related to means-testing of benefits.Ireland RE GINI_m
i GINI_di CI_tr s_tr / di CI_mi s_mi / di CI_tax s_tax
2008 0.243 0.272 -0.055 0.308 0.467 0.902 0.631 -0.210
Sc. 1 0.2558 0.5144 0.2586 -0.042 0.3205 0.4595 0.9374 0.6152 -0.2579
Sc. 2 0.2550 0.5144 0.2594 -0.041 0.3213 0.4599 0.9395 0.6111 -0.2608
Sc. 3 0.2456 0.5151 0.2695 -0.048 0.3155 0.4650 0.8875 0.6303 -0.2031
22
Some extras - Lithuania
2007 to 2008 : a big jump in CIst in Lithuania is mainly caused by: Changes in non-means tested benefits, and particularly parental leave
policies. Interestingly: a change in replacement rate ratio has a CI lowering,
whereas other changes in the rules (i.e. benefit duration) has a CI value increasing effect.
An expanded provision of a universal child benefit higher targeting! Tax policy change (reduced flat rate tariff) higher targeting. The influence of uprating factors is strong and of CI increasing value.
2009-2010: none of the implemented partial policy changes seem to have a major influence on CI only their interactive effect makes a difference. This shows how interactive and complex policy changes are.
2011 – 2012: no major role of uprating factors.
Puzzle: a change in constants (i.e. pension age, CYI, maximum limit on contributory parental benefits) has a lowering effect on GINImi.
23
Conclusions
24
Conclusions
Targeting and redistribution: An increase in CI of social transfers does not necessarily have a
the same directional effect – and if any - on the RE index. Other components could be of higher importance: e.g. CI of market incomes, changing structure of disposable incomes, etc.
A move in CI of social transfers and redistribution could also be due to changing socio-economic structures, not policy changes.
CI indication of lower or higher targeting is not necessarily linked to targeting – as policy design instrument. Actually, reverse effects could be observed: e.g. an expansion of
the universal child benefit provision in Lithuania associated with higher targeting, as indicated by CI.
Country effects are highly diverse.
25
FURTHER RESEARCH IS ON THE WAY….
THANK YOU!