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# Editorial

Matteo G Richiardi¹*

¹Institute for Social and Economic Research, University of Essex, Colchester, United Kingdom

The winter 2023 issue of the International Journal of Microsimulation is published as the International Microsimulation Association heads to its 9th World Congress (Vienna, Austria, 8th - 10th January 2024). The issue contains five articles, covering different microsimulation techniques and applications. The first article, by Karl Widerquist and Georg Arndt, is a static tax-benefit analysis of a Universal Basic Income (UBI) scheme for the United Kingdom (UK). The analysis reflects a growing interest in UBI worldwide, and adds to an active discussion of UBI schemes for the UK in particular (see *Torry, 2023*). The second article, by Montserrat Gonzalez Garibay, contains a review of how retirement decisions are modelled in dynamic microsimulation models (DMSs). The paper fills a gap in the literature, as existing reviews of DMSs (e.g. *O'Donoghue, 2001; Li and O'Donoghue, 2013; O'Donoghue, 2014; O'Donoghue and Dekkers, 2018; Schofield et al., 2018*) generally favour breadth of coverage to depth of modelling insights. The third article, by Edlira Narazani, Ugo Colombino and Bianey Palma, pushes forward the boundaries of tax-benefit modelling by adding both behavioural labour supply effects and endogenous wage adjustments to a static tax-benefit framework. Their model is estimated on all EU member states, but is unfortunately not available outside the European Commission. The fourth article, by Rachel Bacon, George Hodulik, David Voas, Ivan Puga-Gonzalez and Wesley Wildman, confronts with the problem of replicating official population projections in discrete-time DMSs where events like births, deaths, ageing, fertility and migration are simulated in turn - implying that the order of execution matters - while in reality the related risks are competing. The solution envisaged is to "split fertility", attributing half of the risk at the beginning of the simulation period, and the remaining half at the end of the simulation period. The last article, by Tanja Kirn and Gijs Dekkers, is ideally linked to the review by Gonzalez Garibay, illustrating a new DMS for projecting pension entitlements in Switzerland. The model builds on the popular LIAM2/MIDAS simulation frameworks (*de Menten et al., 2014; Dekkers et al., 2022*) to analyse the likely impact of a recent pension reform on the gender pension gap.

## Suggestions for further reding

Microsimulation modelling is becoming increasingly popular in public health research. The short manifesto of *Kopasker et al. (2023)* brings it to the attention of a general audience, identifying "six priority areas particularly suitable for microsimulation analysis in the context of health inequalities": regulatory policies, healthcare policies, social security policies, tax policies, crisis responses, and other policies aimed at improving life opportunities, in particular education and active labour market policies.

If microsimulations are becoming mainstream in the field, de Oliveira et al. (2023) find only few models focused on mental health, with fewer still deemed to be of "high quality". Their critical review will surely help addressing this shortcoming.

## References

Dekkers G, Van den Bosch K, Barslund M, Kirn T, Baumann N, Kump N, Liégeois P, Moreira A, Stropnik N. 2022. How do gendered labour market trends and the pay gap translate into the projected gender pension gap? A comparative analysis of five countries with low, middle and high GPGs. *Social Sciences* **11**: 304. DOI: https://doi.org/10.3390/socsci11070304

<footnote>*For correspondence: matteo.richiardi@essex.ac.uk</footnote>

<footnote>©This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

© 2023, Richiardi.</footnote>
de Menten G, Dekkers G, Bryon G, Liégeois P, O'Donoghue C. 2014. LIAM2: A new open source development tool for discrete-time dynamic microsimulation models. *Journal of Artificial Societies and Social Simulation* **17**: 9. DOI: https://doi.org/10.18564/jasss.2574

de Oliveira C, Matias MA, Jacobs R. 2023. Microsimulation Models on Mental Health: A Critical Review of the Literature. *Value in Health* **8**: S1098-3015(23)06162-4. DOI: https://doi.org/10.1016/j.jval.2023.10.015

Kopasker D, Katikireddi SV, Santos JV, Richiardi M, Bronka P, Rostila M, Cecchini M, Ali S, Emmert-Fees K, Bambra C, Hoven H, Backhaus I, Balaj M, Eikemo TA. 2023. Microsimulation as a flexible tool to evaluate policies and their impact on socioeconomic inequalities in health. *The Lancet Regional Health. Europe* **34**: 100758. DOI: https://doi.org/10.1016/j.lanepe.2023.100758

Li J, O'Donoghue C. 2013. A survey of dynamic microsimulation models: uses, model structure and methodology. *International Journal of Microsimulation* **6**: 3–55. DOI: https://doi.org/10.34196/ijm.00082

O'Donoghue C. 2001. Dynamic microsimulation: A methodological survey. *Brazilian Electronic Journal of Economics* **4**: 77.

O'Donoghue C. 2014. Handbook of microsimulation modelling. *Contributions to Economic Analysis* **293**: 305–343. DOI: https://doi.org/10.1108/S0573-85552014293

O'Donoghue C, Dekkers G. 2018. Increasing the impact of dynamic microsimulation modelling. *International Journal of Microsimulation* **11**: 61–96. DOI: https://doi.org/10.34196/ijm.00174

Schofield DJ, Zeppel MJB, Tan O, Lymer S, Cunich MM, Shrestha RN. 2018 A Brief, Global History of Microsimulation Models in Health: Past Applications, Lessons Learned and Future Directions. *International Journal of Microsimulation* **11**: 97–142. DOI: https://doi.org/10.34196/ijm.00175

TorryM (Ed). 2023. *The Palgrave International Handbook of Basic Income*. 2nd edition. Palgrave Macmillan Cham. p. XLVI–629. DOI: https://doi.org/10.1007/978-3-031-41001-7