Estimation of Average Derivatives of Latent Regressors: With an Application to Inference on Buffer-Stock Saving
潜在解释变量平均导数的估计：缓冲储蓄推断的应用
This paper proposes a density-weighted average derivative estimator based on two noisy measures of a latent regressor. Both measures have classical errors with possibly asymmetric distributions. We show that the proposed estimator achieves the root-n rate of convergence, and derive its asymptotic normal distribution for statistical inference. Simulation studies demonstrate excellent small-sample performance supporting the root-n asymptotic normality. Based on the proposed…