Definitions: -Micro simulation as a means of modelling real life events by simulating the actions of the individual units that makes up the system where the events occur. A 'policy simulation' then consists of evaluating the consequences of a change in the economic environment induced by a policy reform on a vector of indicators of the activity and/or welfare for each agent observed in the simulation sample. -Micro simulation is a technique that is particularly suitable for systems where the decision-making occurs at the individual unit level and where the interactions within the system are complex. In such systems, the outcomes produced by altering the system can vary widely for different groups and are often difficult to predict.

The idea of applying micro simulation techniques to socio-economic modelling was pioneered by Guy Orcutt in the United States in the late 50's and early 60's (Orcutt, 1957; Orcutt et al., 1961). However, only with the development of increasingly powerful computer hardware and the greater availability of individual unit record data has microsimulation modelling become a cost-effective and accessible option.

The major advantage of micro simulation models for social and economic policy analysis is that they produce results that can be analysed at the individual level. Thus, the distributional impact of a policy measure across different types of families or different geographical regions can be assessed. At the same time, estimates of the aggregate outcomes can still be derived easily, by summing the individual results. It is these features that led an exhaustive review of microsimulation in the United States to conclude "… that no other type of model can match microsimulation in its potential for flexible, fine-grained analysis of proposed policy changes …" (Citro and Hanushek, 1991, p.115).

A taxonomy of microsimulation models applied to redistribution policies The common structure of msm in redistribution analysis comprises three elements: 1) a micro dataset, containing the economic and socio-demographic characteristics of a sample of individuals or households; 2) the rules of the policies to be simulated - i.e. the budget constraint faced by each agent; 3) a theoretical model of the behavioural response of agents. A clear taxonomy may be established according to: - whether some of these behavioural responses are included or not in the analysis - the time dimension of these responses - the partial versus general equilibrium focus of the analysis.

Arithmetical msm Msm that ignore behavioural responses altogether are sometimes called arithmetical models. -This type of model simply applies the change in the budget constraint that households face because of the reform in redistribution policy without any change in their market income and in their demographic composition. -Based on market incomes and the socio-demographic characteristics of a household, they arithmetically derive its disposable income and net tax payments given the rules for the computation of taxes and benefits in the policy being analysed. -The simplicity of these models is rather appealing.

Behavioural msm Behavioural msm include a detailed representation of the behavioural response of individuals and households to changes in their budget constraint. The type of behaviour taken into account differs across models: consumption and labour supply are the most frequent focus of interest. Given the prices, wages and the shape of the budget constraint, behavioural msm compute the optimal consumption demand and labour supply of each agent. To do so, a model of consumption and labour supply must have been estimated, or calibrated and must be incorporated in the msm framework. They allow for a more detailed analysis of household welfare and the aggregate budget constraint of the redistribution authority.

Static vs Dynamic The time dimension of msm depends on the object of the analysis and the kind of behavioural response that is incorporated in the model. For instance, evaluating the effects of a reform of the income tax that would modify the treatment of children will have little effects on household composition in the short-run. A static msm will then be sufficient. Long-run effects, however, require simulating the impact on fertility decisions of the tax reform. A dynamic framework is then necessary where households are followed over time. Likewise, the microsimulation of changes in the parameters of the tax-benefit system that affect inter- temporal consumption allocation, retirement, training, schooling of the children, etc. must be analysed with dynamic msm rather than the static ones defined earlier.

Partial vs General Equilibrium Partial equilibrium approach: considering that behavioural responses have no impact on the price system. If labour supply effects arising from a reform of the tax-benefit system are large enough, changes in the structure of wages and prices may be expected to take place. Most models ignore these general equilibrium effects and may thus be called 'partial equilibrium' models. Msm that take into account general equilibrium effect are also being developed. Some of them may be related to the now prolific Computable General Equilibrium literature and essentially try to link these sectoral models to a household micro-data base. Others limit themselves to a subset of markets, most often the labour market.

In my opinion, the desirable characteristics of a microsimulation model are: 1.1 It must be an instrument able to characterise the starting situation (estimation stage) and to simulate reforms (simulation stage). 1.2 The tool must be easy enough to be used for anyone; even if computing languages are not a skill owned by the user. This does not mean that necessary information for knowing how everything works is not given. The interested researcher could know all the necessary steps followed to elaborate the final product 1.3 Indicators for measuring the most relevant effects of tax parameters must be incorporated (revenue magnitudes and equity and efficiency analysis for the whole population and for certain groups). 1.4 The input data must incorporate as faithfully as possible the real world.

Important features: Dataset: representativity, underreporting, updating, net to gross. Algorithms: flexibility vs rigidity; policy vs research, Validation Calibration

SimFBBVA Un modelo de micro-simulación para España Programa informático de libre acceso para el análisis de los efectos redistributivos del sistema fiscal Español © Fundación Banco Bilbao Vizcaya Argentaria Autores del modelo: Amedeo Spadaro DELTA (Joint Research Unit CNRS-ENS-EHESS) París y Universitat de les Illes Balears. Xisco Oliver Rullán Universitat de les Illes Balears. Nuria Badenes Plá Universidad Complutense de Madrid.