instrumental variables

Here is my notes on regression discontinuity from Prof. Ding’s textbook (2024) and Prof. Imai’s lecture notes. Motivation We often cannot run a randomized experiment and have to use/design observational studies to find a setting where credible causal inference is possible.

Motivation Endogeneity: When an explanatory variable (treatment) is correlated with the unobserved error term (e.g., due to omitted variables, measurement error, or simultaneity). Consequence: Standard regression (e.g., OLS) yields biased estimates.

Here’s a overview of instrument-free methods: Latent Instrumental Variable (LIV) Gaussian Copula (GC) The goal is for dealing with endogeneity when no external instruments are available. Motivation Finding good instruments is hard.

Here are my notes on instrumental variables from Stefan’s lecture materials. Motivation How can we identify causal effects $W \rightarrow Y$ when we are in the presence of unobserved confounding $U$?

Hausman-Taylor in R The following example is from here. Example: The fixed effects model, however, does not allow time-invariant variables such as educ or black. Since the problem of the