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Research articles · Dec 31, 2019

The Hypothetical Household Tool (HHoT) in EUROMOD: a new instrument for comparative research on tax-benefit policies in Europe

Tine Hufkens, Tim Goedemé, Katrin Gasior, Chrysa Leventi, Kostas Manios, Olga Rastrigina, Pasquale Recchia, Holly Sutherland, Natascha Van Mechelen, Gerlinde Verbist

Herman Deleeck Centre for Social Policy, University of Antwerp, Antwerp, Belgium; European Commission, Joint Research Centre (JRC), Seville, Spain; Department of Social Policy and Intervention, Institute for New Economic Thinking at the Oxford Martin School, University of Oxford, Oxford, UK; Institute for Social and Economic Research, University of Essex, Essex, UK; Organisation for Economic Co-operation and Development (OECD), Paris, France; Bank of Italy, Rome, Italy; Formerly Herman Deleeck Centre for Social Policy, University of Antwerp, Antwerp, Belgium; Federal Public Service Social Security, Brussels, Belgium

Volume 12(3) Winter 2019

Cite as: T. Hufkens, T. Goedemé, K. Gasior, C. Leventi, K. Manios, O. Rastrigina, P. Recchia, H. Sutherland, N. Van Mechelen, G. Verbist; 2019; The Hypothetical Household Tool (HHoT) in EUROMOD: a new instrument for comparative research on tax-benefit policies in Europe; International Journal of Microsimulation; 12(3); 68–85. doi: 10.34196/ijm.00208

Abstract

This paper introduces the Hypothetical Household Tool (HHoT), a new extension of EUROMOD, the tax-benefit microsimulation model for the European Union. With HHoT, users can easily create their own hypothetical data, which enables them to better understand how policies work for households with specific characteristics. The tool creates unique possibilities for an enhanced analysis of taxes and social benefits in Europe by integrating results from population-based microsimulations and hypothetical household simulations in a single modelling framework. Furthermore, the flexibility of HHoT facilitates an advanced use of hypothetical household simulations to create new comparative policy indicators in the context of multi-country and longitudinal analyses. In this paper, we highlight the main features of HHoT, its strengths and limitations, and illustrate how it can be used for comparative policy analysis.

This article contains 6 figures and 8 tables.

Figures

Figure 1. Gross wage needed to reach the at-risk-of-poverty line, as a percentage of the average gross wage per full-year full-time equivalent employee, for a hypothetical family , 2014.
Figure 2. Net income for three household types expressed as a percentage of the net income of a single-person household with the same gross wage, but without children, 2014.
Figure 3. Tax-benefit package for a child in a single parent household, income components expressed as a percentage of the net income of a single parent household without children, 2014.
Figure 4. Tax-benefit package for a child in a couple parent household, income components compared to the net income in a couple household without children, 2014.
Figure 5. Decomposition of average METRs for a single person household at earnings levels from 80% to 120% of average earnings by income component, 2017 policy system.
Figure 6. Decomposition of METRs at different earnings levels in Cyprus, Hungary and Belgium by income component, 2017 policy system.

Tables

Table 1. Summary of hypothetical households used in example 1
Demographic composition Labour market status adults
Couple (2 earners) with child (8 years) Employee – full time at minimum wage Inactive
Single with child (8 years)
Couple (2 earner) with 3 children (5, 8 and 12 years)
Single with 3 children (5, 8 and 12 years)
Table 2. Net disposable income and different income components for four hypothetical households, minimum wage, 2016
Two adults with 1 child One adult with 1 child Two adults with 3 children One adult with 3 children
Baseline Reform Baseline Reform Baseline Reform Baseline Reform
Total Total Total Total Total Total Total Total
Gross earnings 2,947 2,947 1,473 1,473 2,947 2,947 1,473 1,473
Total taxes 220 220 70 70 220 220 70 70
SIC employee 602 602 301 301 602 602 301 301
Means-tested benefits 0 0 0 0 0 0 410 410
Non-means-tested Child Benefit 190 180 190 248 576 540 576 744
Disposable income 2,315 2,305 1,293 1,351 2,701 2,665 2,089 2,257

Source: own calculations based on EUROMOD H1.0+ and HHoT.

Table 3. Net disposable income and different income components for four hypothetical households, inactive, 2016
Two adults with 1 child One adult with 1 child Two adults with 3 children One adult with 3 children
Baseline Reform Baseline Reform Baseline Reform Baseline Reform
Total Total Total Total Total Total Total Total
Gross earnings 0 0 0 0 0 0 0 0
Total taxes 0 0 0 0 0 0 0 0
SIC employee 0 0 0 0 0 0 0 0
Means-tested benefits 1,096 1,106 861 803 1,082 1,118 886 718
Non-means-tested Child benefit 190 180 190 248 576 540 576 744
Disposable income 1,111 1,111 876 876 1,658 1,658 1,462 1,462

Source: own calculations based on EUROMOD H1.0+ and HHoT.

Table 4. At-risk-of-poverty rate of persons living in Germany, by family type, 2016
Baseline Reform Difference
Change Standard error 90% confidence interval
Lower bound Upper bound
Population 15.15 15.19 0.04 0.04 –0.02 0.11
One adult with children 25.04 24.28 –0.75 0.44 –1.48 –0.03
Two adults with children 11.53 11.75 0.21 0.12 0.02 0.41

We use a fixed poverty line at 60% of the median equivalised disposable income in the baseline.

Source: own calculations based on EUROMOD H1.0 and EU-SILC 2014, full sample design information is not available. For estimating the standard errors and confidence intervals, we take account of clustering within households and the covariance between the simulated scenarios (Goedemé, 2013; Goedemé et al., 2013).

Table 5. Summary of hypothetical households used in example 2
Demographic composition Labour market status adults
Single Employee(s), full time, wage varying from 60% to 200% of average gross wage*[
Couple (2 earners) with 2 children (5 and 8 years)

Although we show only one outcome, different combinations of the wages of both partners are possible.

Table 6. Summary of hypothetical households used in example 3
Demographic composition Labour market status adults (one-earner families)
Single Inactive Employee, 50% of average EU-SILC wage Employee, 100% of average EU-SILC wage Employee, 200% of average EU-SILC wage
Couple
Single with child of 10 years old
Couple with child of 10 years old
Table 7. Summary of hypothetical households used in example 4
Household composition Labour market status
Single Employee, full time with between 80% and 120% of the EU-SILC average wage (in 1% steps).
Table A.1. Country specific 2017 average monthly earnings used in Example 4
Country In EUR In national currency
AT 3140.24 –
BE 3500.56 –
BG 601.72 1176.84
CY 1891.30 –
CZ 1024.31 27332.60
DE 3495.43 –
DK 4091.22 30425.57
EE 1363.38 –
EL 1412.15 –
ES 1965.41 –
FI 3167.61 –
FR 2730.09 –
HR 928.85 6913.83
HU 695.74 215012.62
IE 3984.27 –
IT 2251.91 –
LT 893.97 –
LU 4753.80 –
LV 1043.15 –
MT 1881.91 –
NL 3617.86 –
PL 912.65 3891.83
PT 1363.98 –
RO 479.33 2176.91
SE 3350.66 32152.29
SI 1539.31 –
SK 928.29 –
UK 4080.11 3526.11

Source: Own calculation based on EU-SILC 2015 (2014 for UK and DE) data and EM uprating factors and exchange rates.