Full Information Estimation of Household Income Risk and Consumption Insurance

Arpita Chatterjee (), James Morley and Aarti Singh ()
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Arpita Chatterjee: UNSW Business School, UNSW
Aarti Singh: University of Sydney

No 2019-07, Discussion Papers from School of Economics, The University of New South Wales

Abstract: Blundell, Pistaferri, and Preston (2008) report an estimate of household consumption insurance with respect to permanent income shocks of 36%. Their estimate is distorted by an error in their code and is not robust to weighting scheme for GMM. We propose instead to use quasi maximum likelihood estimation (QMLE), which produces a more precise and significantly higher estimate of consumption insurance at 55%. For sub-groups by age and education, differences between estimates are even more pronounced. Monte Carlo experiments with non-Normal shocks demonstrate that QMLE is more accurate than GMM, especially given a smaller sample size.

Keywords: consumption insurance; weighting schemes; quasi maximum likelihood (search for similar items in EconPapers)
JEL-codes: C13 C33 E21 (search for similar items in EconPapers)
Pages: 34 pages
Date: 2019-07
New Economics Papers: this item is included in nep-ecm, nep-ias and nep-mac
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