Abstract
Most empirical studies of savings behaviour that explicitly take account of the influence of uncertainty consider for identification data that describe the evolution of circumstances observed during an appreciable period of the life-course. Here we report results obtained for a dynamic programming model that has been adapted to permit identification of preference parameters using data observed at a point in time for a given population cross-section. We discuss the advantages of this approach, and our empirical results demonstrate its feasibility in context of contemporary computing technology.
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