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Questions about the impact of social policies cannot be answered solely on the basis of official statistics made available in tabular format. The access to microdata allows policy analysts to answer these questions with a larger set of analytical tools, in particular microsimulation models. This paper examines the interface between survey data and microsimulation models. We review different types of microsimulation models (static and dynamic) and their data requirements. We then restrict the attention to survey-based microdata, and examine issues in survey design, questionnaire content, data quality, and dissemination policy that are important from the perspective of microsimulation.

The 'Mobility Lists' programme handles collective redundancies, and combines income support to eligible dismissed employees with benefits to employers who hire them. Benefits vary according to dismissing firm size and are greater for older workers. We focus on the differential effects of programme treatments on the probability of moving from unemployment into permanent jobs. We specify flexible duration models in order to estimate the profile of differential effects over time. Older workers, enjoying longer packages of benefits, have significantly lower chances of moving to employment. Differential effects vary with time and are higher when younger workers approach the expiry of benefits.

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Current labour force counting relies on general guidelines set by the International Labour Office (ILO) to classify individuals into three labour force states: employment , unemployment and inactivity. However, the resulting statistics are known to be sensitive to slight variations of operational definitions prima facie consistent with the general guidelines. In this paper two alternative classification criteria are considered: a 'strict' criterion followed by Eurostat, which results from a stringent interpretation of the ILO guidelines, and a 'mild' criterion followed by the Italian Statistical Office up to 1992. We first show that the labour force statistics resulting from the two classification criteria differ considerably. We then discuss the relative merits of the two criteria by comparing those individuals whose classification depends on the criterion adopted to individuals whose classification is common across criteria. Similarities are established with respect to characteristics known to be relevant to the labour force state to assess which benchmark group individuals whose state is questionable look like the most. An application is presented to samples of married women from the Italian Labour Force Survey from five survey occasions between 1984 and 2000. Results are neatly in favour of the 'mild' criterion and are rather robust to changes in the business cycle, the participation rate, local labour market conditions and the questionnaire design. Current labour force counting relies on general guidelines set by the International Labour Office to classify individuals into three labour force states: employment, unemployment and inactivity. However, the resulting statistics are known to be sensitive to slight variations of operational definitions prima facie consistent with the general guidelines. It follows that the operational criterion adopted does matter, changing the pattern of unemployment and participation rates over time and attenuating or emphasizing differences across regions. For this reason, the issue of measuring unemployment has been given considerable attention in several countries. For example, the Bureau of Labor Statistics in the United States adopted since the late 70s a set of alternative unemployment indicators, known as U1-U7. The topic has been reconsidered in the mid 90s, when a new set of alternative measures has been introduced. The same problem has been carefully dealt with also in the United Kingdom, with emphasis on the production of survey-based monthly rates. In this paper two alternative classification criteria are considered: a 'strict' criterion followed by Eurostat, which results from a stringent interpretation of the guidelines set by the International Labour Office, and a 'mild' criterion followed by the Italian Statistical Office up to 1992. We first show that the labour force statistics resulting from the two classification criteria differ considerably. We then discuss the relative merits of the two criteria by comparing those individuals whose classification depends on...