Treatment effects without multicollinearity? Temporal order and the Gram-Schmidt process in causal inference
处理效应能否摆脱多重共线性?因果推断中的时间顺序与 Gram–Schmidt 正交化
This paper incorporates information about the temporal order of regressors to estimate orthogonal and economically interpretable regression coefficients. We establish new finite sample properties for the Gram-Schmidt orthogonalization process. Coefficients are unbiased and stable with lower standard errors than those from Ordinary Least Squares. We provide conditions under which coefficients represent average total treatment effects on the treated and extend the model to…