Heterogeneity in MPCs and unexplained variation in consumption expenditures
指出分位数回归在估计边际消费倾向（MPC）分布时存在偏差，因为消费支出中的未解释变异可能来自测量误差或家庭事前异质性。通过模拟方法，作者发现真实的MPC分布比分位数回归估计的更为分散。
Quantile regression is a popular method to estimate the dispersion in MPCs in the population. We discuss the challenges that this method faces given the large unexplained variation in consumption expenditures in survey data. We highlight that quantile regression estimates do not recover the distribution of MPCs if either unexplained variation is due to measurement error or if differences in MPCs are partly driven by ex ante heterogeneity across households. To quantify the likely extent of the bias, we propose a simulation-based approach where we back out the underlying distribution of MPCs for a range of calibrations that attribute the unexplained variation to a split between unobserved factors and measurement noise. All results point in the same direction: the true distribution of MPCs is significantly more dispersed than what is estimated by quantile regression.