Matching and Difference in Difference (DID) are two widespread methods that use pre-treatment outcomes to correct for … values. I find that Matching generally underestimates the average causal effect of the program and gets closer to the true … still performs better than Matching, especially in the middle of the life-cycle. These results are consistent with estimates …

due to mismeasured variables. We consider sample merger by matching on identifiers that may be imperfect in the case that …

-in-differences estimation model combined with an iterative matching approach. The estimation results suggest that community schools are as …

instrumental variables, difference-in-differences estimators, regression discontinuity design, matching methods, panel data methods …

-- Experiments -- Matching -- Instrumental Variables -- Regression Discontinuity Design -- Panel Data and fixed effects -- Difference … packages for specific causal inference techniques like ggdag, Matching, rdrobust, dosearch etc. are used in the book. The book …, matching, panel data, difference-in-differences, regression discontinuity design, instrumental variables and meta …

discussed: traditional regression methods, matching, control function methods, instrumental variable and local instrumental …

uncover the effectiveness at which workers are matched to available jobs. A Spatially augmented matching function is backed by … assuming the process of job matching to be homogenous across space. This study shows that this supposition is not valid for the … matching process. Spatial heterogeneity is additionally found on the level of German macroregions. Though matching efficiency …