Transcript Effects of flat tax reforms in Western Europe on equity

The distributional impact of in kind public
benefits in five European countries
Alari Paulus
Institute for Social and Economic Research, University of Essex
Holly Sutherland
Institute for Social and Economic Research, University of Essex
and
Panos Tsakloglou
Athens University of Economics and Business and IZA
Paper presented at the conference “European Measures of Income, Poverty, and Social Exclusion:
Recent Developments and Lessons for U.S. Poverty Measurement”
U.S. Census Bureau, University of Maryland School of Public Policy and Association for Public Policy Analysis
and Management, Washington DC, Wednesday, November 4, 2009
Motivation
• Usual practice in empirical distributional studies, as well as EU inequality
and poverty statistics: distributions of disposable monetary income
• But individuals derive utility from the consumption of non-purchased as
well as purchased commodities (privately or publicly provided)
• Implications for inter-temporal, cross-country and some inter-personal
comparisons because of changes/differences in
– extent of public provision
– division into cash and non-cash (both public and private)
• Here we focus on the results of an empirical study estimating the value and
incidence of publicly-provided health care and education and subsidised
social housing in 5 EU countries
• We also consider the welfare interpretation of measures of cash + non-cash
incomes
Background
• Building on previous cross-national comparisons by multi-national teams
(e.g. Smeeding et al. 1993 RIW)
• AIM-AP project (Accurate Income Measurement for the Assessment of
Public Policies) FP6 2006-2009
• Non-cash incomes: one part of a 3-part 11-partner project
– (Non take-up of benefits and tax evasion)
– Indirect taxes
• Private as well as public non-cash: here focus on public components
• 7 countries: here focus on 5 only: BE, DE, EL, IT, UK
• Underlying aim: to improve and broaden scope of EUROMOD analysis:
here focus on basic results and use EUROMOD simulated cash incomes as
starting point
• National “state of the art” methods/analysis + comparable “best possible”
methods/analysis: here focus on the latter
• To find out more: www.iser.essex.ac.uk/research/euromod/aim-ap-project
Methods (1)
Microdata
Reference
time period
for incomes
Taxbenefit
system
Country
Dataset
Date of
collection
BE
Belgium
EU-SILC
2004
2003
2003
DE
Germany German Socio-Economic Panel
2002
2001
2001
EL
Greece
Household Budget Survey
2004/5
2004
2004
IT
Italy
Italian version of EU-SILC
2004
2003
2003
Family Resources Survey
2003/4
2003/4
2003
UK UK
Methods (2)
Estimating values for in kind rent subsidies
Subsidy = Market rent – rent paid
• Rent paid: taken from data (before any HB)
• Market rent estimated as for imputed value of owner
occupation: opportunity cost (rental equivalence) approach
• For private market tenants: gross rents modelled as dependent
variable (using characteristics of dwelling, area and/or
occupants); coefficients used to impute gross market rents for
otherwise similar rented dwellings
• Social tenants: 20% of the households in UK; 7% DE; 5% BE;
concentrated in lower income groups
Methods (3)
Estimating values for education and health care
• Public education
– OECD Education at a glance per student spending by level of
education
– Primary, secondary, tertiary, disregarding other stages (pre-primary,
post-secondary non-tertiary, etc), matched into microdata for students
in non-private education
– Particular issues related to tertiary: part/full time; fees; R&D
expenditure; where do students live and how are they treated in
surveys?
– In all countries: more beneficiaries in lower income groups (varies by
level of education)
• Public health care
– Social expenditures on health care services per capita (SOCX - OECD);
by age see Marical et al. (2006); matched into microdata by age
– Insurance value approach
– In all countries: much higher expenditures at older ages
Methods (4)
General remarks
• Static incidence analysis under the assumption of no
externalities
• Partial short term analysis (taxes and social insurance
contributions given)
• Benefit shared by all household members (“un-spent”
household income)
• No inefficiencies in the production of public services
• Modified OECD equivalence scale
7
Non-cash income components as % of household cash
disposable income: all households
% of disposable income
30
25
20
15
10
5
0
BE
DE
Rent Subsidy
EL
Education
IT
UK
Health
Source: EUROMOD
Non-cash income components as % of household cash
disposable income: bottom quintile
% of disposable income
70
60
50
40
30
20
10
0
BE
DE
Rent Subsidy
EL
Education
IT
UK
Health
Source: EUROMOD
Percentage change in inequality indexes after adding
non-cash benefits
0%
-10%
-20%
-30%
-40%
-50%
-60%
-70%
Belgium
Germany
Gini
Greece
Atkinson (0.5)
Italy
Atkinson (1.5)
UK
Percentage with less than 60% median income
(cash vs cash + non cash)
30
25
20
15
10
5
0
all
children
elderly
all
cash disposable income
BE
children
elderly
cash disposable income + non-cash
transfers
DE
EL
IT
UK
Preliminary conclusions and a qualification
• The methodology adopted in the project is in line with the existing
literature
• In all countries the inclusion of the three non-cash benefits appears to lead
to a substantial decline in measured levels of inequality and poverty
• Broadly similar effects in each country; no re-ranking (except for subgroups)
• Rent subsidies: no doubt that the measured changes have a straightforward
welfare interpretation
• Education and health care: not necessarily so, due to the use of
“conditional” equivalence scales
• The “alternative scenario” (implicitly, paying for the services or insuring
against their costs out of disposable income) changes the institutional
framework: the corresponding needs (for education and health care) should
be taken into account
• Also, public goods theory: provision in equal quantities; not in proportion
to the individuals’ incomes (scale invariance of inequality indices)
Accounting for health care and education needs (1)
• Assuming that
y is household income,
k is the amount of extra needs of the household members
for health and education,
e the OECD scale, and
e’ the new scale,
the following should be valid for the household to remain at
the same welfare level:
y/e = (y+k)/e’
and e’ should be equal to
e’ = e(y+k)/y
• But how to estimate k?
Should it be a function of demographics alone
or demographics and income?
Accounting for health care and education needs (2)
• An empirical approach which simply assumes
needs=expenditure would take us back (almost) to square 1
• Except
– private education, dropouts, (non-compulsory education), (private
health insurance)
– variation in spending across countries: take EU averages (or minima or
maxima) to represent the “in principle” cost of meeting needs
• per capita amounts, adjusted by GDP relative to EU mean
• Crude calculations, sensitivity tested, to illustrate the
implications of the approach
• To be less crude within the same framework requires better,
more detailed, data
Change in Gini coefficient with addition of 3 noncash benefits without equivalence scale adjustment
(Baseline) and with adjustment (Scenarios 1 & 2)
Belgium
Germany
Greece
Italy
UK
Baseline
-22.8
-21.3
-16.5
-20.3
-21.0
Scenario 1
(-0.3)
-4.0
1.5
-2.2
-2.0
Scenario 2
0.2
-2.4
3.1
-0.7
-1.1
E-scale adjustment: k is EU mean heath care per capita +
education per student spending (GDP-adjusted)
Scenario 1: Compulsory education only in needs
Scenario 2: All education levels in needs
Final conclusions
• It is important for comparability to measure the incidence of
non-cash incomes across the cash income distribution
• Importance of this type of analysis in a life-cycle framework
• Housing subsidies (and private imputed rent) should be
included in income, to improve comparability
• A welfare interpretation of adding to cash income the value of
public health care and education requires that needs for health
and education are accounted for in the equivalence scale
• Our crude empirical experiment suggests that the net effect of
adding non-cash benefits would then be small
• The effect could well be larger for comparisons with non-EU
countries
Proportional changes in inequality indices
(Imputed Rent + Education + Health)
0
BE
DE
EL
IR
IT
NL
UK
-10
-20
Gini
-30
Atkinson0.5
Atkinson1.5
-40
-50
-60
Re-ranking effects
BE
DE
EL
IR
IT
NL
UK
M A M A M A M
A M A M A M
A
Gini
2
2
3
4
6
7
4
3
5
6
1
1
7
5
Atkinson0.5
2
2
3
4
5
5
4
3
6
7
1
1
7
6
Atkinson1.5
2
2
3
4
4
5
5
3
7
7
1
1
6
6
FGT0
2
2
3
4
6
6
7
5
5
7
1
1
4
3
FGT1
2
2
3
4
6
6
5
5
7
7
1
1
4
3
FGT2
2
2
4
5
6
4
3
3
7
7
1
1
5
6
M: Monetary
A: Augmented
Importance of consumption of own production
Greece
From own From own
From other
From
farm
non-farm
households employer
production production
Gini
Atkinson0.5
Atkinson1.5
FGT0
FGT1
FGT2
-1.6
-3.3
-3.8
-2.8
-6.8
-9.4
-0.2
-0.5
-0.7
-0.8
-1.1
-2.1
-1.4
-3.0
-3.9
-2.7
-4.4
-7.2
0.1
0.1
0.2
0.0
1.0
1.1
-3.2
-6.6
-7.9
-6.1
-13.1
-18.9
Proportional change in %
Germany
flat.4
flat.8
ALL
pred.wage
Gini
-13.9
-22.8
-18.3
Atkinson 0.5
-25.5
-39.6
-34.0
Atkinson 1.5
-31.5
-44.2
-38.9
FGT0
-18.7
-27.7
-19.9
FGT1
-33.2
-47.0
-41.5
FGT2
-44.4
-60.3
-56.5
Calculation of k (needs)
For each household with n members (i=1,…,n) with
different characteristics (such as age) the needs for
education and health care are assumed to be:


S
S
k   k ENi EEUi  k HNi HEUi 
S ENi
S HNi 
i 1 
n
where kENi and kHNi are, respectively, national spending
for public education and public health care for persons
with characteristics i, SENi and SHNi are national spending
figures for public education and public health care
expressed as a share of the country’s GDP per capita (i.e.
they
are
equal
to
kENi/GDPpcN
and
kEHi/GDPpcN,
respectively) and SEEUi and SHEUi are the corresponding
(unweighted) averages for EU15