Estimating Household Consumption Insurance

Arpita Chatterjee, James Morley and Aarti Singh

No 2017-04, Working Papers from University of Sydney, School of Economics

Abstract: Blundell, Pistaferri, and Preston (American Economic Review, 2008, 98(5), 1887-1921) report an estimate of household consumption insurance with respect to permanent income shocks of 36%. Their estimate is imprecise and not robust to weighting scheme for GMM. We propose instead to use quasi maximum likelihood estimation (QMLE). It produces a more precise and significantly higher estimate of consumption insurance at 55%. For sub-groups by age and education, the differences between estimates are even more pronounced. Monte Carlo experiments with non-Normal shocks demonstrate that QMLE is more accurate than GMM.

Keywords: consumption insurance; weighting schemes; quasi maximum likelihood. (search for similar items in EconPapers)
Date: 2017-02, Revised 2019-07
New Economics Papers: this item is included in nep-ecm
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Journal Article: Estimating household consumption insurance (2021)
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