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《非线性世界中的动态因果效应》讨论AI 解读

This comment discusses Kolesár and Plagbord-Møller finding that the standard linear local projection (LP) estimator recovers the average marginal effect (AME) even in nonlinear settings. We apply and discuss a subset their results using a simple nonlinear time series model, emphasizing the role of the weighting function and the impact of nonlinearities on small-sample properties.

局部投影的偏差AI 解读

Local projections (LPs) are a popular tool in macroeconomic research. We show that LPs are often used with very small samples in the time dimension and, consequently, that LP point estimates can be severely biased. Under regularity conditions, we derive simple expressions to approximate this bias and propose a way to correct for bias in LPs. Using a medium-scale macroeconomic time-series model, we demonstrate that the bias in point estimates can be economically meaningful.…