Search Results

Adrian Keister provided a great answer. My answer continues his. It took me a while to realize that the 2 different approaches to causal inference (graphical approach and potential outcomes) are compl …

Carlos Cinelli in this great post https://stats.stackexchange.com/a/384460/198058 gives an example of 3 different Data Generating Processes/Causal Models giving rise to the same joint distribution $(X …

Teasing out the causal effect of one variable/treatment on another/outcome by blocking all the Backdoor Paths between treatment and outcome in the corresponding DAG (Directed Acyclic Graph) requires d …

In his book "Introductory Econometrics", Jeffrey Woolridge states "The most we can know about how X affects Y is contained in the conditional distribution of Y given X". Is this statement true? Woul …

There is a more straightforward way to derive the total causal effect to be $P(y|do(x))=\sum\limits_{z_1,z_3}P(Z_1=z_1)P(Z_3=z_3|Z_1=z_1)P(Y=y|Z_1=z_1,Z_3=z_3,X=x)$ Because the set {$Z_1,Z_3$} satisfi …

In this article Chen & Pearl make the following 2 statements: "Identification techniques are available for models in which X is far from satisfying $E(u_i|X_i)=0$" in response to Stock & Watson's sen …

The reason that conditioning on the parents of $X$, irrespective of what the DAG looks like, always satisfies the backdoor criterion relative to $(X,Y)$ is that there is a parent of $X$ on each backdo …

Both of the above PAGs (Partial Ancestral Graph) are generated using the FCI (Fast Causal Inference) algorithm under identical conditions, the only difference being that the one on the right is gener …

Note that this approach is fundamentally different from the traditional approach used in estimating causality in econometrics - Instrumental Variable regressions. …

In prediction, accepting a little more bias in exchange for a lot less variance is the very name of the game - we'll chose the model with minimal test MSE without regard for its composition (bias squa …

On page 1443 of the linked paper, the authors present the following causal DAG (Directed Acyclic Graph) with a latent variable (Profession). On the following page, they present the 2 MAGs below with …

Assuming that the treatment was assigned randomly, after coding Small Business as 0 and Medium Business as 1, the OLS coefficient $\beta_1$ will give you an unbiased estimate of the average causal eff …

In their article, Chen and Pearl (2013), critically examined 6 econometric textbooks, among these the textbooks written by Wooldridge (2009) {the introductory book}, and Stock & Watson (2011). These l …

The causal context of your analysis is a key qualifier in your question. In forecasting, running univariate regressions before multiple regressions in the spirit of the "purposeful selection method" s …