Estimating Household Consumption Insurance
22 Pages Posted: 16 Mar 2017 Last revised: 27 Aug 2019
Date Written: July 5, 2019
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 signicantly higher estimate of
consumption insurance at 55%. For sub-groups by age and education, dierences 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
JEL Classification: E21; C13; C33
Suggested Citation: Suggested Citation