1. Methodology
  2. Dynamic microsimulation
Download icon

A survey of dynamic microsimulation models: Uses, model structure and methodology

  1. Jinjing Li  Is a corresponding author
  2. Cathal O’Donoghue  Is a corresponding author
  1. University of Canberra, Australia
  2. Teagasc Teagasc Rural Economy Research Centre, Ireland
Research article
Cite this article as: J. Li, C. O’Donoghue; 2013; A survey of dynamic microsimulation models: Uses, model structure and methodology; International Journal of Microsimulation; 6(2); 3-55. doi: 10.34196/ijm.00082
3 tables


Table 1
Uses of dynamic microsimulation models.
Model Country Uses
APPSIM Australia Designed to provide answers regarding the future distributional impact of policy change and other issues associated with policy responses to population ageing (Harding, 2007a; Kelly and Percival, 2009)
BRALAMMO Brazil Models the Brazilian labour market for pension welfare analysis (Zylberstajn et al., 2011)
CAPP_DYN Italy Analyses the long term redistributive effects of social policies (Mazzaferro & Morciano, 2008)
CBOLT US Analyses potential reforms to federal entitlement programmes and quantifies the US nation’s long-term fiscal challenges (Oharra et al., 2004)
CORSIM US Models changes occurring within kinship networks, wealth accumulation, patterns of intergenerational mobility, the progressivity and the life course of the current social security system, as well as potential reforms, household wealth accumulation, health status, interstate migration, time and income allocation, and international collaborations (Caldwell et al., 1996; Caldwell et al., 1997)
Czech Republic Model Czech Republic Designed to analyse public pension system and potential reforms in Czech republic (Fialka et al., 2011)
DEMOGEN Canada Models distributional and financial impact of proposals to include homemakers in the Canadian pension plan (Wolfson 1989)
DESTINIE I/II France Models public pensions and intergenerational transfers (Blanchet et al., 2009; Bonnet and Mahieu, 2000; Bonnet et al.,1999)
DYNACAN Canada Models the Canada Pension Plan and its impact on the Canadian population (Morrison, 2000; Osberg & Lethbridge, 1996)
DYNAMITE Italy Models microeconomic issues and the impact of macroeconomic/institutional changes on the distribution of income (Ando and Nicoletti-Altimari, 1999; Ando et al., 2000)
DYNAMOD I & II Australia Models life course policies such as superannuation, age, pensions and education, long-term issues within the labour market, health, aged care and housing policy, future characteristics of the population and the projected impact of policy changes (Antcliff 1993; Antcliff et al., 1996; King et al., 1999a; King et al., 1999b)
DYNASIM I & II US Forecasts the population up to 2030 by employing different assumptions regarding demographic and economic scenarios, and analyses the cost of teenage childbearing to the public sector under alternative policy scenarios, also includes a link to a macro model (Citro & Hanushek, 1991a; Citro & Hanushek, 1991b)
DYNASIM III US Designed to analyse the long-term distributional consequences of retirement and ageing issues (Favreault & Smith, 2004)
DYPENSI (SIPEMM) Slovenia A Slovenia Dynamic Microsimulation Model with the focus on pension system simulation (Majcen, 2011)
FAMSIM Austria Models the demographic behaviour of young women (Lutz, 1997)
FEM US A demographic and economic simulation model designed to predict the future costs and health status of the elderly and to explore what current trends or future shifts might imply for policy, developed by RAND (Goldman et al., 2006; Goldman et al., 2009)
GAMEO France Analyses and assesses the consequences of various higher education policies (Courtioux et al., 2008)
HARDING Australia Analysis of lifetime tax-transfer analysis, for analysis of policy concerning the Higher Education Contribution Scheme and redistributive impact of government health outlays over the lifetime of an individual (Harding, 1993)
HealthPaths Canada Simulate the trajectory of health and life expectancies, and analyses the relative importance of determinants of health-adjusted life expectancy (Wolfson & Rowe, 2013)
IFS Model UK Studies pensioner poverty under a variety of alternative tax and benefit policies (Brewer et al., 2007)
IFSIM Sweden Studies intergenerational transfers and the interdependence between demography and the economy (Baroni et al., 2009)
INAHSIM Japan Simulates demographic and social evolution, able to simulate kinship relationships in detail (Inagaki, 2010)
INFORM UK Developed for forecasting of benefit caseloads and combinations of receipt, designed to incorporate significant benefit reforms planned over the coming years, based entirely on administrative data (Gault, 2009)
Italian Cohort Italy Analyses lifetime income distribution issues (Baldini, 2001)
Japanese Cohort Japan Looks at the impact on household savings of changes in demographic structure (Ando & Moro, 1995; Ando, 1996)
LABORsim Italy Simulates the evolution of the labour force over future decades in Italy (Leombruni, 2006)
LIAM 0 Ireland Models inter-temporal issues relating to the degree of redistribution within the tax-benefit system (O’Donoghue, 2001a; O’Donoghue, 2001b)
LIAM 1 Ireland Evaluates potential reforms to the Irish pensions system in terms of changes to life-cycle incomes (O’Donoghue et al., 2009)
LIFEMOD UK Models the lifetime impact of a welfare state (Falkingham & Lessof, 1992)
LifePaths Canada Models health care treatments, student loans, time-use, public pensions and generational accounts (Rowe & Wolfson, 2000)
Long Term Care Model UK Models long term care reform options (Hancock, 2000)
Melbourne Cohort Australia Analyses income inequality in a lifetime context (Van de Ven, 1998)
MICROHUS Sweden Models dynamic effects of changes to the tax-benefit system on the income distribution and economic-demographic effects of immigration (Klevemarken, 1991; Klevmarken & Olovsson, 1996)
MICSIM Germany Analyses German pension and tax reform (Merz et al., 2002)
MiMESIS Sweden Evaluates Swedish Pension Reform (Mikula et al., 2003)
MIDAS Multi Analyses pension system and social security adequacy (Dekkers & Belloni, 2009)
MIDAS New Zealand Models wealth accumulation and distribution (Stroombergen et al., 1995)
MIND Italy Simulates the economic impact resulting from alternative values of the income growth rate and real interest rate (Vagliasindi et al., 2004)
MINT US Forecasts the distribution of income for the 1931–1960 birth cohorts in retirement, MINT5 extends to the 1926–2018 birth cohorts ((Panis & Lillard, 1999; Smith et al., 2007; Toder et al., 2002)
MOSART 1/2/3 Norway Models the future cost of pensions, undertakes micro level projections of population, education, labour supply and public pensions, incorporates overlapping-generations, models within a dynamic microsimulation framework (Andersson et al., 1992; Fredriksen, 1998)
MOSES Sweden Investigates the micro basis for inflation and the interactions between inflation, economic growth, and profitability (Eliasson, 1977)
NEDYMAS Netherlands Models intergenerational equity and pension reform, the redistributive impact of social security schemes in a lifetime framework (Nelissen, 1996; Nelissen, 1998)
PENMOD Japan Public pension system analysis (Shiraishi, 2008)
PENSIM UK Models the treatment of pensioners by the social security system across the income distribution (Hancock et al. 1992; Curry, 1996)
PENSIM US Analyses lifetime coverage and adequacy issues related to employer-sponsored pension plans in the US (Holmer et al., 2001)
PENSIM2 UK Estimates the future distribution of pensioner incomes to analyse the distributional effects of proposed changes to pension policy (Emmerson et al., 2004)
Pensions Model Belgium Analyses and forecasts the medium term impact of a change to pension regulations (Joyeaux et al., 1996)
POHEM Canada A longitudinal microsimulation model of health and disease, it is used to compare competing health intervention alternatives within a framework that captures the effects of disease interactions (Will, 2001)
POLISIM US Demographic-economic and social security projection for US social security administration (Holmer, 2009; McKay, 2003)
PRISM US Evaluates public and private pensions (Citro & Hanushek, 1991a; Citro & Hanushek, 1991b)
SADNAP Netherlands Evaluates the financial and economic implications of the problem of ageing (Van Sonsbeek, 2009)
SAGE UK Dynamic demographic/tax model for the UK (Zaidi & Rake, 2001; Zaidi & Scott, 2001)
SESIM Sweden Analyses the consequences of population ageing and models budget and distributional impact of inter-temporal policy issues such as student grants, labour supply, savings decisions and pensions (Ericson & Hussenius, 1998; Ericson & Hussenius, 1999; Klevmarken & Lindgren, 2008; Klevmarken, 2010; Pylkkänen, 2001)
Sfb3 Germany Analyses pension reforms, the effect of shortening worker hours, distributional effects of education transfers (Galler & Wagner, 1986; Hain & Hellberger, 1986)
SimBritain UK Simulates urban and regional populations within the UK (Ballas et al., 2005a; Ballas et al., 2005b);
SMILE Ireland Population projections with spatial details for Ireland (Ballas et al., 2005a; O’Donoghue et al., 2011)
SustainCity Multi A dynamic model with a focus on land use simulations (Morand et al., 2010)
SVERIGE Sweden Models human eco-dynamics, e.g. the impact of human cultural and economic systems on the environment (Vencatasawmy et al., 1999)
Swedish Cohort Sweden Models the replacement of social insurance by personal savings accounts and the distribution of lifetime marginal effective tax rates (Fölster, 2001)
Tdymm Italy Analyses the Italian labour market and pension system, with a focus on pension adequacy and related distributional effects (Tedeschi, 2011)
XEcon Canada A model intended for theoretical exploration rather than practical empirical application (Wolfson, 1995)
Table 2
Base dataset selection of dynamic microsimulation models.
Model Country Base Dataset Observation
APPSIM Australia 1% census sample drawn from the 2001 Census 188,013 individuals
CAPP_DYN Italy Survey of Households’ Income and Wealth (SHIW), 2002 21,148 individuals and 8,011 households
CBOLT US Continuous Work History
CORSIM US 0.1% sample drawn from the 1,960 census 180,000 individuals
Czech Republic Model Czech Republic Synthetic age 0 cohort, distribution parameters obtained from multiple sources 119,914 individuals
DEMOGEN Canada Synthetic age 0 cohort 1,000–5,000 individuals
DESTINIE I & II France Financial Assets Survey,1991 37,000 individuals
DYNACAN Canada 1% sample drawn from 1971 census, public use file 212,000 individuals
DYNAMITE Italy Household Income and Wealth, 1993 67,000 households
DYNAMOD I and II Australia 1% sample drawn from the 1986 census 150,000 individuals
DYNASIM I US 1960 Census 1–10,000 Public Use Sample
1970 Census 1–10,000 Public Use Sample
4000 individuals
10000 individuals
DYNASIM II US CPS 1973 matched to Social Security Administration (SSA) data
DYNASIM III US SIPP panels 1990 to 1993 100,000 individuals and 44,000 households
DYPENSI (SIPEMM) Slovenia Administrative dataset by Slovenia Statistical Office (SORS), 2007/2010 115,000 individuals / 40,000 households
FAMSIM Austria Family and Fertility Survey (Austria), 1995–96 4,500 women
FEM US Individual records drawn from the Medicare Current Beneficiary Survey (MCBS), 1992–1998 10,000 individuals
GAMEO France French Labour Force Survey (FLFS), 2003–2005
HARDING Australia Synthetic cohort aged 0 4,000 individuals
IFS Model UK English Longitudinal Study of Ageing (ELSA), 2002–2003 12,100 individuals
IFSIM Sweden Swedish Household Panel Survey (HUS), 1996 3,000 individuals
INAHSIM rev1/2/3 Japan Rev1: 1974 Comprehensive Survey of the Living Conditions of People on Health and Welfare (CSLC) with private household only
Rev2: 2001 CSLC (private household only)
Rev3: 2004 CSLC, aligned with population census
Rev1:32,000 individuals and 10,000 households Rev2: 126,000 individuals and 46,000 households Rev3: 128,000 individuals and 49,000 households
INFORM UK 1% sample drawn from Department for Work and Pensions (DWP) administrative data 110,000 individuals
Italian Cohort Model Italy Synthetic cohort aged 0 4,000 individuals
Japanese Cohort Model Japan Synthetic multiple cohorts (single representative of each cohort type) 4,000 individuals
LABORsim Italy 2003 Rilevazione Trimestrale delle Forze Lavoro (RTFL) 50,000 individuals
LIAM 0 Ireland LII survey, 1994 (Pop.), synthetic cohort aged 0 (Cohort) Around 4,500 households
LIAM 1 Ireland LII survey, 1994–2001 15,000 individuals
LIFEMOD UK Synthetic cohort aged 0 4,000 individuals
LifePaths Canada Synthetic cross-section Varies
Long Term Care Model UK Family Expenditure Surveys, 1993–1996 1,770 individuals
Melbourne Cohort Model Australia Synthetic sample of 20 year olds in 1970 50,000 males and families
MICROHUS Sweden The Swedish Household Panel Survey (HUS), 1984
MIDAS Multi PSBH dataset for Belgium, 2002, GSOEP dataset for Germany,2002, ECHP dataset for Italy, 2001
MIDAS New Zealand Synthetic cross-section based on 1991 Census 10,000 individuals
MIND Italy ISTATA, IRP and SHIW Data, 1995
MINT US SIPP, 1990–93, matched to SSA data, SIPP, 1990–96, matched to SSA data for MINT5 85,000 individuals, expanded in later versions
MOSART 1/2/3 Norway 1% sample drawn from administrative data, 1989, version 3 used a 12% sample drawn from administrative data, 1993 40,000 individuals, 500,000 observations in version 3
NEDYMAS Netherlands Synthetic cross-section based on 1947 census 10,000 individuals
PENMOD Japan Synthetic dataset based on the official aggregate statistics
PENSIM UK Retirement Survey, 1988, Social Change and Economic Life Initiative Survey, 1986 and Family Expenditure Survey, 1988 5,000 benefit units
PENSIM US Synthetic cohort aged 0
Family Resource Survey, British
PENSIM2 UK Household Panel Survey and Lifelong Labour Market Database, 1999–2001
Pensions Model Belgium Synthetic cross-section based on survey data
POHEM Canada Administrative data
POLISIM US A subset (1–10%) of the 1960 US Census Bureau Public use Microdata Sample (PUMS)
PRISM US CPS, March 1978, March and May 1979, matched to SSA data 28,000 adults
PSG US Mixed 100,000 individuals
SADNAP Netherlands Administrative data from Statistics Netherlands (CBS)
10% sample drawn from the
SAGE UK Individual/Household, 1991 anonymised records combined with several survey datasets 54,000 individuals
SESIM Sweden Longitudinal Individual Data Base (LINDA), 1999 100,000 individuals
Sfb3 Cohort Germany Integrated Micro Data File, 1969 (Pop.), synthetic cohort aged 0 (Cohort) 69,000 households / 7,300 individuals
Sfb3 Population Germany Integrated Micro Data File, 1969 (Pop.), synthetic cohort aged 0 (Cohort) 69,000 households / 7,300 individuals
SimBritain UK UK Census and BHPS, 1991
SMILE Ireland Census of Population of Ireland
SustainCity Multi Multiple data sources, including survey datasets and administrative datasets Depends on the end user, 120,000 individuals for the Paris demography module,
Swedish Cohort Sweden Synthetic cohort aged 20 1,000 individuals
  1. Source: see Table 1.

Table 3
An overview of the technical choices made by dynamic microsimulation models.
Model Country Base Pop Cross Type of Time Modelling Open or Closed Model Use of Alignment Algorithms Use of Behavioural Equations
APPSIM Australia D C Y N N
CAPP_DYN Italy Cross D C Y N
DEMOGEN Canada Cohort D O N N
DESTINIE I & II France Cross D C Y N
DYNACAN Canada Cross D C Y N
DYNAMITE Italy Cross D C Y N
DYNAMOD I & II Australia Cross C/D C Y N
FAMSIM Austria Cross D C N N
FEM US Cross D N N
GAMEO France Cross D Y
HARDING Australia Cohort D C N N
IFS Model UK Partial Cross D C Y Y
IFSIM Sweden Cross D C Partial CGE
INAHSIM Japan Cross D C Y N
Italian Cohort Model Italy Cohort D C N N
Japanese Cohort Model Japan Cohort D C Y Y
LABORsim Italy Cohort C C Y N
LIAM 0 Ireland Cohort D C Y Y
LIAM 1 Ireland Cross D C Y Y
LifePaths Canada Cross C O N
Long Term Care Model UK Cross D C Y N
Melbourne Cohort Model Australia Cohort D O N
MICROHUS Sweden Cross D C N Y
MIDAS Multi Cross D C Y Y
MIDAS New Zealand Cross D C N
MIND Italy Cross O Y
MOSART 1/2/3 Norway Cross D C Y N
NEDYMAS Netherlands Cross D C Limited CGE Y
Pensions Model Belgium Cross D C N
POHEM Canada Cohort C N N
PSG US Cohort C O N N
SADNAP Netherlands Cross D C Y Y
SESIM Sweden Cross D C Y Y
Sfb3 Cohort Germany Cohort D O N N
Sfb3 Population Germany Cross D C Y N
SIPEMM Slovenia Cross D C Y Y
SustainCity Switzerland Cross D C Y N
SVERIGE Sweden Cross D C Y N
Swedish Cohort Model Sweden Cohort D C N N
Tdymm Italy Cross D C Y Y
  1. Source: see Table 1.

  2. Key: Cross, cross-sectional, C, continuous, D, discrete, Y, yes, N, No.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Download citations (links to download the citations from this article in formats compatible with various reference manager tools)

Open citations (links to open the citations from this article in various online reference manager services)