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Parameterising a detailed dynamic programming model of savings and labour supply using cross-sectional data

Justin van de Ven ()

International Journal of Microsimulation, 2017, vol. 10, issue 1, 135-166

Abstract: Dynamic programming methods are now commonly used to describe behaviour in contexts where uncertainty is likely to have an important bearing on decision making. Using a publicly available structural dynamic microsimulation model, LINDA, this paper provides new insights into how unobservable preference parameters ? particularly those associated with risk aversion ? can be coherently identified on broad-based moments of decision making observed for a population cross-section. Preference parameters identified on UK data are found to be in-line with those reported in the wider econometric literature

Keywords: Dynamic Programming; Savings; Labor Supply; Empirical Identification (search for similar items in EconPapers)
JEL-codes: C51 C61 C63 H31 (search for similar items in EconPapers)
Date: 2017
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Handle: RePEc:ijm:journl:v10:y:2017:i:1:p:135-166