The last few years have seen a rapid evolution in the sophistication of different kinds of
microsimulation models and a major expansion of their use in social, economic, research and
planning practices. The choice and application of computer-based microsimulation models is
governed by the objectives of the analysis as well as the available resources. Hence,
understanding the application of static microsimulation in different parts of the world and
their contexts helps to inform the successful implementation of the proposed analytical tool
of the study. In addition, assessing experience, use and application of microsimulation
models in different parts of the world further supports the credibility of the tools. As a result,
researchers, practitioners and decision makers will be equipped to make informed decisions
that will account for current and evolving technology.
The countries which are considered here have a variety of static microsimulation models for
the analysis of government policies and illustrate the impact of various taxes and benefit
policies that could be implemented. Despite the history and ‘permanence’ of some of these
arrangements, all systems have undergone, or are undergoing, change. Countries examined
also have different histories and institutional arrangements for the development and
implementation of the static microsimulation models at different levels. In general, the
experiences of other countries suggest that microsimulation models are the key tools for
analysis of the tax and transfer programmes. The following section provides a review of the
122 application of static microsimulation models in different parts of the world and their analysis,
with an overarching focus on existing and future alternatives.
Static microsimulation in the USA
Microsimulation models originated in the United States in the late 1950s and the Urban-
Brookings Tax Policy Center model is a large-scale microsimulation model of the US federal
tax system. The federal statistical system also provides a wide range of micro-data on which
models can draw. For example, static microsimulation models in the United States include
models such as the transfer income model (TRIM), the expanded transfer income model
(TRIM2), reforms in income maintenance (RIM), micro analyses of transfers to households
(MATH), simulated tax and transfer system (STATS), OTA, TAXSIM and HITSM.
According to Merz (1994), RIM was developed at the Urban Institute toward the end of the
1960s. The study was commissioned by the Department of Health, Education and Welfare,
the predecessor of the current Department of Health and Human Services. He added that,
since about 1976, TRIM (transfer income model), an updated version of RIM, and the
expanded TRIM2 are the most widespread static microsimulation models in use in
government agencies as well as in other institutions in the United States. Merz argued that
the TRIM/TRIM2 package allows for an adjustment in the population development (“static
ageing”) in short- and medium-range simulations. It also makes it possible to simulate a
variety of income transfer programmes.
Citro and Hanushek (1991) noted that in the United States, for example, Congress will not
consider any social security or tax legislation without closely examining the distributional
outcomes predicted by microsimulation models. The models calculate tax liability for a
representative sample of households, both under the current rules and under alternative
scenarios. Based on these calculations, the model produces estimates of the revenue
123 consequences of different tax policy choices, as well as their effects on the distribution of tax
liabilities and marginal effective tax rates. The models are also a useful input to research on
the effects of taxation on economic behaviour.
Static microsimulation in Canada
Statistics Canada has developed a number of microsimulation models as well as general-
purpose tools that assist in their construction. The Canadian Department of Finance is also
presently using a static microsimulation model, TTSIM, which simulates the distributional
impacts of tax-transfer programmes such as federal goods and services tax, payroll tax,
elderly benefits, refundable sales tax credit, provincial and federal income taxes, child
benefits, and so on. The model takes into account data from three sources: the Survey of
Consumer Finances, family expenditure data and individual tax data.
As another example, SPSD/M is a detailed cross-sectional microsimulation model of
individuals and families (Statistics Canada, 2009). It is based on a non-confidential annual
database, constructed by using a variety of survey and administrative data sources. SPSD/M
is used for policy development and analysis of federal and provincial tax and transfer
programmes, as well as for analysing issues related to income distribution. It has assisted
those interested in analysing the financial interactions of governments and individuals in
Canada. It can help one to assess the cost implications or income redistributive effects of
changes in the personal taxation and cash-transfer system. The SPSD/M is a non-
confidential, statistically representative database of individuals in their family context, with
enough information on each individual to compute taxes paid to and cash transfers received
from government. The SPSM is a static accounting model which processes each individual
and family on the SPSD, calculates taxes and transfers using legislated or proposed
programmes and algorithms, and reports on the results. It gives the user a high degree of
124 control over the inputs and outputs to the model and can allow the user to modify existing
tax/transfer programmes or test proposals for entirely new programmes. The model can be
run using a visual interface and it comes with full documentation.
Static microsimulation in Australia
Lloyd (2003) noted that STINMOD is NATSEM's static microsimulation model of Australian
income taxes and cash transfers. It is publicly available, runs on a personal computer and can
be accessed via a user-friendly interface. Bremner et al. (2002) remarked that, in essence, STINMOD applies the rules of the income tax and government cash-transfer programmes to
a database of income units representing the Australian population. It helps to analyse the
distributional impact of current tax-transfer policy or to estimate both the fiscal and
distributional impacts of policy reform. Lloyd (2003) and Lutz (1997) showed that
STINMOD can be used to analyse the distributional impact of current tax-transfer policy or
to estimate both the fiscal and distributional impacts of policy reform. The first version of
STINMOD was released in 1994. Since then, the entitlement modules have been largely
rewritten to take account of the major changes to the tax and transfer systems associated with
the introduction of the goods and services tax reform package in July 2000. It is now the
standard model used by the Australian federal government departments for their analyses of
possible budget policy options in this area.
Static microsimulation in Europe
A number of static microsimulation models have been built in Europe. Lietz and Mantovani
(2006) noted that, in the early 1990s, Merz surveyed more than 40 major national models
across Europe (mainly Germany). A few years later, Sutherland described 19 static models
already in use in five countries of the European Union. Examples of such developments of
tax-benefit microsimulation models at the national level in Europe include TAXMOD,
125 POLIMOD, GLADHISPANIA, FAMISIM, MIMOSIS, and TUJA. Most of these models
assess the possibilities of several policy options that ultimately lead to a consolidated
redistribution drive.
Merz (1994) observed that microsimulation models are used mostly in Europe by government
organisations to examine taxation issues that occur in the area of individual income tax.
However, some countries have undertaken to build microsimulation models for corporate
taxes in the business sector as well. Nowadays, almost all European countries have
microsimulation for personal income taxation at their disposal. Brief descriptions of static
microsimulation in Europe for selected countries are presented below:
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Table 4:1 Summary of static microsimulation in Europe for selected countries
Countries Type of static microsimulation Purpose
Belgium MIMOSIS To analyse the effects of policy changes on both the individual and household level and for
different socio-economic and demographic groups
Great Britain TAXMOD, POLIMOD To assess a variety of tax-benefit policies, including the analysis of policy changes on
poverty and inequality in a number of studies
Finland TUJA To analyse the financial and distributional effects of practically all significant tax and benefit
reforms
Italy EconLav To analyse the effects of policy reforms on labour supply (participation versus non-
participation and employment versus self-employment working activities), income distribution, poverty, public budget and tax incidence.
Spain GLADHISPANIA To analyse and explore the effects on redistribution and inequality when the 1999 system was
replaced by a flat tax combined with a vital minimum (i.e. an amount of income that is not taxed) or a basic income (i.e. an amount of money that was given to everyone, independently of the economic status.
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EUROMOD
EUROMOD is a static microsimulation model used in many European Union countries. It was
developed by a team from 18 institutions, co-ordinated by the Microsimulation Unit in the
Department of Applied Economics at the University of Cambridge, with the financial support of
the European Commission programme of Targeted Socio-Economic Research (TSER) (Levy et
al., 2006; Lietz & Mantovani, 2006; Lietz & Sutherland, 2005).
The main purpose for building an integrated European tax-benefit microsimulation model arose
from research questions in public economics and, more precisely, those investigating the
characteristics of tax-benefit systems and the comparative impact of common reforms across
Europe (Lietz & Mantovani, 2006:3). According to Lietz and Mantovani , these very decisive
policy questions led to the need for a more reliable tool in order to undertake cross-country
assessment and make use of tax-benefit microsimulation techniques applied at European level as
microsimulation appeared to be a promising approach. EUROMOD allows research on the
effects of tax-benefit systems by facilitating the measurement of their impact on incomes,
poverty, inequality and social inclusion. Lietz and Mantovani (2006:2) further noted that the
model is designed to answer “What if?” questions about different approaches to policy reform at
European level.
Immervoll et al. (2000:2) explained that “EUROMOD provides a Europe-wide view on social and economic integration policies that are implemented at European, national or regional level. It is also designed to examine, within a constant comparative framework, the impact of national policies on national populations and the differential impact of coordinated European policy on individual Member States”. According to them, tax-benefit models incorporate household
128 micro-data from nationally representative sources and are able to (a) capture the full range of
difference of family circumstance without needing to define what is "typical" or
"representative", (b) predict aggregate effects on the basis of many observations from survey
data that in combination are representative of the national population, (c) assess the effect of
detailed policy measures on disposable incomes -- the models offer distinct "levers to pull" and
"buttons to push" so that simulated changes translate directly into changes to actual policy rules
that governments or other agencies can make, and (d) give a distributional analysis and focus on
particular socially-defined groups of interest.
Immervoll et al. (2000) further indicated that EUROMOD is a static microsimulation model that
generally does not attempt to capture individual behavioural responses to changes in policy.
They also argued that the model has the potential to be used as a platform for particular analyses
of behavioural change. Users of EUROMOD are not constrained to accept particular
behavioural relationships, hard-wired into the model. In principle, they will be able to
implement their own chosen approaches.
Static microsimulation models in Africa: As part of designing Africa’s poverty reduction
strategies, Adelzadeh, (2005) developed a microsimulation model that is accessible on the
internet, where the user can modify certain elements of the existing system and add in a basic
social assistance benefit. His internet-based facility provides user-friendly access to five African
country (Botswana, Cameroon, Nigeria, South Africa and Uganda) microsimulation models.
According to him, it is possible to develop “own” tax and transfer policy scenarios or conduct
“what if?” simulation analysis. Adelzadeh further demonstrated that each model provides the
poverty, distribution, and budgetary impacts of one’s policy choices and compares the simulation
results with the current state or the base scenario. In the context of Namibia, Haarmann and
129 Haarmann (2005) also used a microsimulation model to illustrate the distributional effects in the
highly unequal Namibian society. They argued that the model is able to show the distributional
effects (nationally as well as disaggregated into rural/urban etc.) of the possible policy
intervention of introducing a basic income grant in Namibia.
Static microsimulation models in South Africa: Numerous researchers in the field (Adelzadeh,
2005; Haarman, 2000; Haarmann, & Haarmann, 1998; Haarmann & Haarmann, 2006; Herault,
2005; Samson et al., 2002; Samson et al., 2004; Woolard, 2003) developed and/or worked with
the analytical tool of the microsimulation model to provide an explanation for social welfare
policies and poverty in the context of South Africa. For example, Adelzadeh developed the
South African tax and transfer simulation model (SATTSIM) that is accessible on the internet,
where the user can modify certain elements of the existing system and add in a basic social
assistance benefit (Adelzadeh, 2005). In the context of South Africa, he also used a
microsimulation model of tax and transfers, to compare and contrast the effectiveness of 10
policy scenarios to halve poverty and unemployment by 2015. The Economic and Policy
Research Institute (EPRI), using a microsimulation model, also investigated the social and
economic impact of the existing social benefits in South Africa. The results of this study provide
evidence that the household impacts of South Africa’s social grants are developmental in nature
(Samson et al., 2002; Samson et al., 2004). Woolard’s (2003) microsimualtion model assesses the impact of a basic income grant (BIG) on poverty gap measures, examines the redistributive
impacts of the tax system, and looks at the relationship between social assistance grants and
economic growth. Her model demonstrates the feasibility of combining corporate and personal
income tax increases to recover the cost of the grant. She argued that BIG is the foundation for
all other social grants. Haarman (2000) also modelled the impact of existing social grants on
130 poverty and tested the impact of potential reforms using a microsimulation model. In addition,
research has also been undertaken on linking microsimulation models with computable general
equilibrium models (Herault, 2005). The model developed by Herault examines how macro-
shocks and policy changes lead to macroeconomic changes. However, very few microsimulation
studies have been focused explicitly on child poverty.
Analysis of child poverty using static microsimulation: International experiences
Levy et al. (2006) showed an application of EUROMOD to explore the prospects for a guaranteed income for every child in the European Union and its potential effects on child
poverty. They examined the extent to which existing levels of financial support for children
through national taxes and benefits fall short of a series of illustrative minimum levels of income
corresponding to proportions of median income. Using EUROMOD, they estimated the cost of
bringing the amount of support up to these levels for all children as well as the corresponding
impacts on income poverty among EU children.
Making use of the EUROMOD, another multi-country comparison of tax-benefit systems has
been conducted by Levy et al. (2008). They assess the consequences of the recent reform in Poland and examine the outcome in comparison to child policies in three other European
systems, France, the United Kingdom and Austria. The results of their study show that poverty
reduction would have been more pronounced in Poland if child policies were changed along the
lines of the system in France or the United Kingdom. The Austrian system – relying primarily
on universal benefits – would bring about a similar reduction in the poverty rate but with much
greater reduction in the poverty gap. The findings detailed distributional analysis under the
131 different systems assuming the cost of “importing” each of them to be the same as that of
introducing the 2007 reform.
As another example, in the Southern European context, Matsaganis et al. (2005) undertook a
study on the drive to reduce child poverty, where the subsidiary role of the state in matters of
family policy has implied that programmes of public assistance to poor families with children are
often meagre or not available at all. Their research approach was purely quantitative and,
exclusively using the European microsimulation model, they examined the effect of family
transfers on child poverty in Greece, Italy, Spain and Portugal. Using evidence from the
European microsimulation model, the researchers first assessed the distributional impact of
existing family transfers and then explored the scope for policy reforms. The findings indicated
that the simulated effects of universal child benefit schemes are similar to those in Britain,
Denmark and Sweden. Their report concludes with a discussion of key findings and policy
implications.
From the above review, it is clear that microsimulation models can be used for analysing the
impact of the Child Support Grant on child poverty in South Africa. The static microsimulation
model can be used to illustrate most of the main characteristics of welfare-based principles and
can be used to examine the effectiveness and the extent of social welfare policies of the Child
Support Grant in terms of responding to child poverty. Given the discrimination and inequality
of the past in South Africa, the need for a comprehensive approach to redress this through the
design of acceptable policy and implementation strategy is also crucial. In this regard, it is
argued that the microsimulation model, particularly SAMOD, helps to assess the usefulness of
the existing Child Support Grant in South Africa.
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