Editorial

This issue of the journal contains six articles. The first one, by Ross Richardson et al., presents a dynamic microsimulation model to project labour force participation in six EU member states, five low-participation countries (Italy, Spain, Ireland, Hungary and Greece) and a high-participation benchmark (Sweden). The model provides an alternative to the cohort models widely used at official agencies like the OECD and the European Commission, with all the advantages of a micro perspective (no ecological fallacy of group-level analysis, more controls hence more accurate estimates, possibility of aggregating the results to any group of interest). In particular, the paper focuses on the labour supply of women. The issue of ecological fallacy (Robinson, 1950) is not elaborated upon by the authors, but it is worth mentioning given that this is an important advantage of the microsimulation approach. I do it in Richiardi, Nolan, and Kenworthy (2018), on which the following paragraph is based.

The ecological fallacy arises when aggregate data are used to make inferences about individual level parameters. Many investigators have shown that the aggregate and the individual-level coefficients seldom agree in either magnitude or direction. For instance, it is possible that the individual probability to participate is higher for the majority of individuals in group A, but group B displays a higher aggregate participation rate. Suppose for instance that there are 1,000 individuals in each group. 800 individuals in group A have a probability to participate of 50%, while the remaining 200 individuals have a probability to participate of 0. In group B, 800 individuals have a probability of 40%, and 200 individuals have a probability of 100%. Individuals in group A are more likely to participate than individuals in group B; however, the participation rate is higher in group B (52% versus 40%). Also, a characteristic might negatively impact on the participation rate at the individual level, but display a positive association at the aggregate level. As an example, individual wealth might have a negative impact on participation, but aggregate wealth could affect participation even after controlling for individual wealth. This could happen for instance if people are trying to “catch up with the Joneses”, reacting to relative wealth. If the distribution of wealth is skewed enough, a positive association between wealth and the participation rate would be detected, at the aggregate level. Ecological fallacy is avoided altogether using individual-level analysis, as in microsimulation models.

The second article in the issue, by Concepció Patxot et al. is also a dynamic microsimulation of labour force participation, but with a focus on retirement behaviour in Spain. A survival model is used to adjust retirement decisions and the estimated probabilities are then used to adjust times to retirement within the microsimulation tool. The model allows to analyse the compounded effect of population ageing, increased participation of odler workers and women, and improvements in educational attainments.

The third article, by Ismail Saglam, presents a new heuristics in mate search strategy, based upon an earlier model by Todd and Miller. Mating algorithms are relevant for (dynamic) microsimulations as simulated individuals need to be matched to form new unions over time. Saglam identifies a key shortcoming in the most successful search strategy from the Todd and Miller paper, and develops a new strategy without this shortcoming, but which nevertheless performs well, at least according to one important success criterion.

The fourth article, by Mauri Kotam aki et al., presents an evaluation of a recent reform of unemployment insurance in Finland. The paper builds on a static tax-benefit microsimulation model for Finland, SISU, expanded with a behavioural component.

The fifth article, by Trond Husby et al., addresses an important issue in urban microsimulation — namely how to construct households (or families, or other groupings) from a set of individuals, in a way that retains the structural properties of the data from different sources. The paper presents a new method for synthesizing individuals, households and dwellings in small areas, illustrated using the city of Amsterdam as a case study.

The last contribution is a software review, in which Luca Tiberti and co-authors describe a user-friendly Stata-based toolkit for top-down microsimulation-CGE modelling, where a microsimulation model is used to distribute the results of a standard representative agent CGE model. One of the goals of the International Journal of Microsimulation is to disseminate and document software tools which might be of value for the microsimulation community. The software was developed as part of the activities of the Partnership for Economic Policy (PEP), an international non-profit organization with the goal of enhancing local capacity for policy analysis in developing countries. The toolkit is freely distributed and freely available.