Linked Questions

2
votes
1answer
76 views

What's the DGP in causal inference?

This question come from this discussion (Under which assumptions a regression can be interpreted causally? ). That discussion touch too arguments and is not possible to speak about all things there. ...
30
votes
6answers
1k views

Under which assumptions a regression can be interpreted causally?

First, don't panic. Yes, there are many similar question on this site. But I believe none gives a conclusive answer to the question below. Please bear with me. Consider a data generation process $\...
3
votes
1answer
72 views

Are causal effects constant over time?

The possibility that correlations are unstable over time is a matter of fact. Just for example we can consider that models included in these articles: https://www.sciencedirect.com/science/article/abs/...
2
votes
2answers
81 views

Is there a simpler probabilistic causal model that describes this data generating process?

Consider the following data generating process: A person with gender male or female is selected from a population with probability $\alpha$ of selecting female. The person is offered a drug to treat ...
3
votes
0answers
134 views

Mathematical details in the definition of a Structural Causal Model

Pearl defines (see Causality, Judea Pearl, 2nd ed., Definition 7.1.1) a Structural Causal Model (SCM) as a triple $(\mathscr U, \mathscr V, F)$ where $\mathscr U$ is a set of "exogenous variables," $\...
1
vote
1answer
66 views

Can causation be inferred when all possible covariates are included in a multiple regression?

Say we were interested in SAT scores for high school students as our dependent variable in a multiple regression. Now, assume we are God and can include literally all relevant covariates in the model (...
3
votes
1answer
86 views

Relationship between Causal Calculus (in the sense of the Book of Why) and other existing modeling formalisms?

I am watching this video on youtube: https://youtu.be/zvrcyqcN9Wo?t=2896 about Causal Calculus (CC), namely this section on causal graphs, and it seems to me that this theory of causality is not that ...
6
votes
3answers
378 views

Is causal inference only from data possible?

Suppose we are given a dataset but not the capability of performing some AB testing. We do some regression using X as predictor and Y as response and get a model. Can we actually say something about ...
17
votes
3answers
755 views

How is causation defined mathematically?

What is the mathematical definition of a causal relationship between two random variables? Given a sample from the joint distribution of two random variables $X$ and $Y$, when would we say $X$ causes ...
88
votes
7answers
17k views

The Book of Why by Judea Pearl: Why is he bashing statistics?

I am reading The Book of Why by Judea Pearl, and it is getting under my skin1. Specifically, it appears to me that he is unconditionally bashing "classical" statistics by putting up a straw man ...
2
votes
1answer
538 views

non stochastic regressors

In the multiple linear regression analysis if regressors are non-stochastic the causal interpretation of parameters is automatically permitted? I think so, because it seems me that the model can be ...
2
votes
1answer
273 views

non stochastic regressors and causation

Randomized controlled experiment is base case for causality (also) in regression. However currently I’m analyzing the role of causality in linear regression as shown in many econometrics textbook. ...
2
votes
1answer
267 views

regression and causation

In the Chen and Pearl (2013) article there are several critics about econometrics textbooks. Currently I try to understand more about it. In particular the Authors written (pag 4, footnote 5): From ...
13
votes
2answers
937 views

Is a regression causal if there are no omitted variables?

A regression of $y$ on $x$ need not be causal if there are omitted variables which influence both $x$ and $y$. But if not for omitted variables and measurement error, is a regression causal? That is, ...
12
votes
1answer
2k views

Causal effect by back-door and front-door adjustments

If we wanted to calculate the causal effect of $X$ on $Y$ in the causal graph below, we can use both the back-door adjustment and front-Door adjustment theorems, i.e., $$P(y | \textit{do}(X = x)) = \...

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