python-causality-handbook

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Hi, It is not clear to me what are the conditions on the data used to train meta-learners. The text says: `This time, we will use non-random data to train...

agourlaouen-tf

15 - Synthetic Control We got calif_weights from regression from un-treatment data before year 1989. And we got calif_synth by below: calif_synth = cigar.query("~california").pivot(index='year', columns="state")["cigsale"].values.dot(calif_weights) My question is the data...

iamdengjie

There is an issue on chapter 19, in the following paragraph For example, if the cumulative sensitivity is, say -0.5 at 40%, we will end up with -0.2 (-0.5 *...

anle9371

There is a (possible) issue on chapter 1, in the following paragraph Now, let's add and subtract . This is a counterfactual outcome. It tells what would have been the...

dwanev

rename "Prince" to "Price" and "lifecicle" to "lifecycle"

MustaphaU

There is an issue on chapter 25, in the following paragraph [Diff-in-Diff Revisited] It should be [suggestion here]

Wuyanan520

There is an issue on chapter 15, in the following paragraph > To do this with linear regression, we will find the weight using OLS. We will minimise the square...

ellisp

Right after the formula for \kappa, the following sentence reads "where ~T is the residual from a regression of all other covariates X_1i+...X_ki on T." I think it should be...

illiapolovnikov

Hi @matheusfacure, thanks for this awesome book! I am currently reading Chapter 22, and am curious about the interpretation for the non-parametric double machine learning here: https://matheusfacure.github.io/python-causality-handbook/22-Debiased-Orthogonal-Machine-Learning.html#what-is-non-parametric-about. Here it says...

jfklahdgha

There is an issue on chapter 6, in the following paragraph ``` and \beta is the difference in means or the ATE in the case of random data \beta =...

WillTirone