@article {10.34196/ijm.00152,
article_type = {journal},
title = {Parameterising a detailed dynamic programming model of savings and labour supply using cross-sectional data},
author = {van de Ven, Justin W.},
volume = 10,
number = 1,
year = 2017,
month = {apr},
pub_date = {2017-04-30},
pages = {135-166},
citation = {IJM 2017;10(1):135-166},
doi = {10.34196/ijm.00152},
url = {https://doi.org/10.34196/ijm.00152},
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},
journal = {IJM},
issn = {1747-5864},
publisher = {International Journal of Microsimulation},
}