Abstract
Forecasting labour market flows is important for budgeting and decision-making in government departments and public administration. Macroeconomic forecasts are normally obtained from time series data. In this article, we follow another approach that uses individual-level statistical analysis to predict the number of exits out of unemployment insurance claims. We present a comparative study of econometric, actuarial and statistical methodologies that base on different data structures. The results with records of the German unemployment insurance suggest that prediction based on individual-level statistical duration analysis constitutes an interesting alternative to aggregate data-based forecasting. In particular, forecasts of up to six months ahead are surprisingly precise and are found to be more precise than considered time series forecasts.
Original language | English |
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Journal | Oxford Bulletin of Economics and Statistics |
Volume | 80 |
Issue number | 4 |
Pages (from-to) | 822-842 |
Number of pages | 21 |
ISSN | 0305-9049 |
DOIs | |
Publication status | Published - Aug 2018 |