Estimating household consumption insurance
复现了Blundell等人关于家庭消费保险的估计，发现原估计因代码错误和加权方法问题存在偏差，并指出准最大似然估计比广义矩估计更准确，尤其适用于子群体分析。
Summary 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%. In replicating findings for their model and data, we find that this estimate is distorted by a code error and is not robust to weighting scheme for generalized method of moments (GMM) or consideration of quasi maximum likelihood estimation (QMLE), which produces a significantly higher estimate of consumption insurance at 55%. For sub‐groups by age and education, the differences between estimates across methods are even more pronounced, and QMLE provides new insights into heterogeneity across households compared to the original study. Monte Carlo experiments using non‐normal shocks suggest that consumption insurance estimates for the model are more accurate for QMLE than GMM, including when correcting for bias and especially given a smaller sample such as is only available when looking at sub‐groups.