1. Autumn School Dynamic MSM16-18 November 2015 | L-Esch-sur-Alzette Slide 1 A gentle introduction to microsimulation Gijs Dekkers

2. Autumn School Dynamic MSM16-18 November 2015 | L-Esch-sur-Alzette Slide 2 What is microsimulation ?  The purpose of any microsimulation model is to impute missing data  Alternative realities  Prospective scenarios  Based on actual or synthetic micro-level datasets n i

3. Autumn School Dynamic MSM16-18 November 2015 | L-Esch-sur-Alzette Slide 3 What is microsimulation (2)  Microsimulation models are used to evaluate the effects of changes (policy, socio-demographics, economic, …); at the level of the decision making units rather than focusing on the aggregate information.  Focus is on the distribution of the target values, rather than on the means or the aggregates.  Estimates of aggregate outcomes can however still be derived by summing up individual predictions.  Units can be individuals, households, firms, bacteria, viruses, etc.

4. Autumn School Dynamic MSM16-18 November 2015 | L-Esch-sur-Alzette Slide 4 A classification of microsimulation models in social sciences Behavioural Dynamic ageing ArithmeticStatic ageing Include a notion of time Behaviour

5. Autumn School Dynamic MSM16-18 November 2015 | L-Esch-sur-Alzette Slide 5 Arithmetic (i.e. no time element, no behavioural equations)  Take individual characteristics and behaviours as exogenous  Evaluate the immediate “overnight” distributional impact of (possible) policy changes on individuals or households  E.g. gross income_2=max(5000, gross income)  Results are presented as counterfactuals or “alternative realities”.  Applications:  Traditional: redistributive and/or budgetary impacts of tax-benefit policy instruments, including income tax, family ad social assistance benefits, austerity measures.  Indirect taxes and Consumption, Housing benefits  Regional disparities from country-wide data

6. Autumn School Dynamic MSM16-18 November 2015 | L-Esch-sur-Alzette Slide 6 Arithmetic (i.e. no time element, no behavioural equations)  The most well-known model of this type is EUROMOD  Openly accessible, uses the EU-SILC  Exists for all 27 EU member states + Serbia, Russia, RSA, China and …?  Based at the Institute for Social and Economic Research, University of Essex.  Other models: STINMOD (AUS), TAXBEN (UK), IZAψMOD (Ger), TRIM (US), MIMOSIS (B), MISIM (B)

7. Autumn School Dynamic MSM16-18 November 2015 | L-Esch-sur-Alzette Slide 7 A classification of microsimulation models in social sciences ArithmeticStatic ageing Behaviour Include a notion of time

8. Autumn School Dynamic MSM16-18 November 2015 | L-Esch-sur-Alzette Slide 8 Static ageing  Transform the weights of a dataset to meet J exogenous marginal distributions describing a (current or projected) population  Deville and Särndal (1992), Creedy and Kalb (2006)  Packages include GREGWT, CALMAR, Clan97 (SAS), Calibrate, Reweight, Sreweight, Gomulka (Stata); see Dekkers, IJM, forthcoming.  “uprate” monetary variables and parameters following a hypothetical evolution  Note that the individual characteristics remain unchanged!

9. Autumn School Dynamic MSM16-18 November 2015 | L-Esch-sur-Alzette Slide 9 A classification of microsimulation models in social sciences Dynamic ageing Static ageing Behaviour Include a notion of time

10. Autumn School Dynamic MSM16-18 November 2015 | L-Esch-sur-Alzette Slide 10 Dynamic ageing M t u < p x u~U(0,1) M t+1 N t+1 Basic principle: Monte-Carlo Simulation

11. Autumn School Dynamic MSM16-18 November 2015 | L-Esch-sur-Alzette Slide 11 Other techniques  Matching  Deterministic simulation  Cloning  Alignment through sorting M t : rank rank < p x % M t+1

12. Autumn School Dynamic MSM16-18 November 2015 | L-Esch-sur-Alzette Slide 12 Dynamic simulation: MIDAS as an example DEMOGRAPHIC MODULE t LABOUR MARKET MODULE t PENSION & BENEFITS MODULE t CONTRIBUTIONS AND TAXATION MODULE t REDISTRIBUTION, POVERTY, INEQUALITY OTHER OUTPUT t=2002 to 2060 MIDAS Starting dataset ± 2.2K2 individuals in 2002

13. Autumn School Dynamic MSM16-18 November 2015 | L-Esch-sur-Alzette Slide 13 MIDAS is working in conjunction with the other models of the FPB Macro model S3BE Semi-aggregate model MALTESE Microsimulation model MIDAS Demographic projections MALTDEMO Parameter changes Numbers/proportions* of individuals in various states Joint social hypothesis Alignment *

14. Autumn School Dynamic MSM16-18 November 2015 | L-Esch-sur-Alzette Slide 14 Applications of dynamic microsimulation  Assess the consequences of the projections and hypotheses of the Study Committee on Ageing on poverty, income inequality  Assess the consequences of the AWG projections and hypotheses on poverty, income inequality.  Assess the consequences of policy, and demographic and economic trends on LWI  Assess the (dynamic) consequences of indexation policy, fiscal policy, social policy (e.g. pension reform, austerity policy)

15. Autumn School Dynamic MSM16-18 November 2015 | L-Esch-sur-Alzette Slide 15 An example: the WGA projections for Belgium (MIDAS) and Sweden (SESIM)

16. Autumn School Dynamic MSM16-18 November 2015 | L-Esch-sur-Alzette Slide 16 What models are there  Static (behavioural) models mainly in academics  Static arithmetic models (EUROMOD) highly popular, both in academics and the government  Static ageing models not very common  Dynamic (reduced-form) behavioural ageing models increasingly popular, but outside academics  SESIM, PENSIM II, MOSES  MIDAS_BE, _LU, _HU, _??  DYNAMOD, APPSIM, INAHSIM  DESTINIE, TRAJECTOIRE  Dynamic arithmetic models (“Markov Chain type”) scarce and structural behavioural models almost non-existent

17. Autumn School Dynamic MSM16-18 November 2015 | L-Esch-sur-Alzette Slide 17 More information ?  O’Donoghue (2015) Handbook of Microsimulation. Emerald  Dekkers, Keegan, O’Donoghue (2014) New Pathways in Microsimulation. Ashgate.

18. Autumn School Dynamic MSM16-18 November 2015 | L-Esch-sur-Alzette Slide 18 Conclusions  Microsimulation is now a well-established part of socio-economic (applied) research and policy evaluation  On the EU-level, especially static ageing is now the standard, but attention is gradually turning to dynamics  Many public or semi-public institutions in EU member states have dynamic models  Still, the MSM research community remains fairly small

19. Autumn School Dynamic MSM16-18 November 2015 | L-Esch-sur-Alzette Slide 19 Now… on to LIAM2 !

20. Autumn School Dynamic MSM16-18 November 2015 | L-Esch-sur-Alzette Slide 20 LIAM2  tool for the development of microsimulation models mostly dynamic models (but static too) cross-sectional ageing  tries to be easy yet flexible and powerful  NOT a model in itself  Developed in Python Very high level and readable language Free & Open source Large community (especially in the scientific world)  Performance scales linearly with the sample size

21. Autumn School Dynamic MSM16-18 November 2015 | L-Esch-sur-Alzette Slide 21 Motivations behind the development of LIAM2  Most existing microsimulation models have been developed by separate (teams of) researchers.  No economies of scale,  No distribution of tacit or codified knowledge  Inefficient  Furthermore, as modellers often are not professional programmers, the result is not necessarily the most efficient in terms of simulation speed.  This is the reason why several partners joined their efforts to develop a dynamic Microsimulation modeling toolbox (“LIAM2”)

22. Autumn School Dynamic MSM16-18 November 2015 | L-Esch-sur-Alzette Slide 22 LIAM2 – a history  Initiative by Gijs Dekkers and Philippe Liégeois; inspiration provided by Cathal O’Donoghue’s LIAM.  Developed through a collaboration between  the Federal Planning Bureau in Brussels (development by Gaëtan de Menten, testing by Raphaël Desmet and Gijs)  LISER and the General Inspectorate of Social Security in Luxembourg (additional testing and complementary funding)  under European funding (MiDaL Project 2009-2011, PROGRESS programme, Grant VS/2009/0569)

23. Autumn School Dynamic MSM16-18 November 2015 | L-Esch-sur-Alzette Slide 23 LIAM2 – a history LIAM MIDAS (Belgium, Italy, Germany) LIAM2 MIDAS (Belgium) T-dymm (Italy) MIDAS (Hungary) MIDAS (Luxembourg) DYNAPOR (Portugal) Individual researchers Or independent teams (T-dymm, IPP, …) 2009 2012 2014 2005

24. Autumn School Dynamic MSM16-18 November 2015 | L-Esch-sur-Alzette Slide 24 And, finally… LIAM2 is free and open source  liam2.plan.be  Documentation  New versions for download  Source code  Google groups