Econometrics Libraries

5 Components & Libraries

Sortby

Econometrics Libraries

ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.

You can also perform direct policy learning from observational data, using the doubly robust method for offline policy learning. These methods directly predict a recommended treatment, without intern…

ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.

DoubleML - Double Machine Learning in Python

It further can be readily extended with regards to To install DoubleML with pip use DoubleML can be installed from source via If you use the DoubleML package a citation is highly appreciated: Bibtex-…

Introduction to statistics featuring Python. This series of lecture notes aim to walk you through all basic concepts of statistics, such as descriptive statistics, parameter estimations, hypothesis testing, ANOVA and etc. All codes are straightforward to understand.

[Last updated on 19th Aug 2022] This is a series of lecture notes that I prepared in my statistics tutorial (used prepared for one-night new-hire statistical training in hedge fund), which are suppos…

Machine learning based causal inference/uplift in Python

causeinfer can be downloaded from PyPI via pip or sourced directly from this repository: Separate models for treatment and control groups are trained and combined to derive average treatment effects…

Related tags

static-site-generator