Poor (Wo)man's Bootstrap
针对复杂计量模型自助法计算缓慢的问题，提出一种仅依赖一维参数估计的替代方法，适用于M估计和GMM估计，并可用于两步估计量的方差估计。
The bootstrap is a convenient tool for calculating standard errors of the parameter estimates of complicated econometric models. Unfortunately, the fact that these models are complicated often makes the bootstrap extremely slow or even practically infeasible. This paper proposes an alternative to the bootstrap that relies only on the estimation of one-dimensional parameters. We introduce the idea in the context of M and GMM estimators. A modification of the approach can be used to estimate the variance of two-step estimators.