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Estimating Household Consumption Insurance

Author

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  • Chatterjee, Arpita
  • Morley, James
  • Singh, Aarti
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.

Suggested Citation

  • Chatterjee, Arpita & Morley, James & Singh, Aarti, 2017. "Estimating Household Consumption Insurance," Working Papers 2017-04, University of Sydney, School of Economics, revised Jul 2019.
    • Handle: RePEc:syd:wpaper:2017-04
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    References listed on IDEAS

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    4. Dirk Krueger & Fulin Li & Harald Uhlig, 2024. "Neoclassical Growth Transition Dynamics with One-Sided Commitment," PIER Working Paper Archive 24-020, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.

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    Keywords

    consumption insurance; weighting schemes; quasi maximum likelihood.;
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