There are 138 repositories under econometrics topic.
Statsmodels: statistical modeling and econometrics in Python
Collection of notebooks about quantitative finance, with interactive python code.
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.
Lightning ⚡️ fast forecasting with statistical and econometric models.
Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and causality.
2-2000x faster ML algos, 50% less memory usage, works on all hardware - new and old.
A statistical library designed to fill the void in Python's time series analysis capabilities, including the equivalent of R's auto.arima function.
Notebooks for financial economics. Keywords: Jupyter notebook pandas Federal Reserve FRED Ferbus GDP CPI PCE inflation unemployment wage income debt Case-Shiller housing asset portfolio equities SPX bonds TIPS rates currency FX euro EUR USD JPY yen XAU gold Brent WTI oil Holt-Winters time-series forecasting statistics econometrics
Robyn is an experimental, AI/ML-powered and open sourced Marketing Mix Modeling (MMM) package from Meta Marketing Science. Our mission is to democratise modeling knowledge, inspire the industry through innovation, reduce human bias in the modeling process & build a strong open source marketing science community.
LightweightMMM 🦇 is a lightweight Bayesian Marketing Mix Modeling (MMM) library that allows users to easily train MMMs and obtain channel attribution information.
This repository hosts the code behind the online book, Coding for Economists.
Replication of tables and figures from "Mostly Harmless Econometrics" in Stata, R, Python and Julia.
Probabilistic Hierarchical forecasting 👑 with statistical and econometric methods.
📖An interactive companion to the well-received textbook 'Introduction to Econometrics' by Stock & Watson (2015)
Causal Inference for the Brave and True的中文翻译版。全部代码基于Python,适用于计量经济学、量化社会学、策略评估等领域。英文版原作者:Matheus Facure
DoubleML - Double Machine Learning in Python
Causal Inference for The Brave and True 책의 한국어 번역 자료입니다.
CausalLift: Python package for causality-based Uplift Modeling in real-world business
StateSpaceModels.jl is a Julia package for time-series analysis using state-space models.
Tutorials of econometrics featuring Python programming. This is a crash course for reviewing the most important concepts and techniques of basic econometrics, the theories are presented lightly without hustles of derivation and Python codes are straightforward.
Collection of stats, modeling, and data science tools in Python and R.
The official R data package for "Introductory Econometrics: A Modern Approach". A vignette contains example models from each chapter.
Applied Econometrics Library for Python
A Python package for causal inference using Synthetic Controls
Econ5170@CUHK: Computational Methods in Economics (2020 Spring).
Undergraduate textbook for Econometrics with R
Articles/ Journals and Videos related to Economics:chart_with_upwards_trend: and Data Science :bar_chart:
Vanilla option pricing and visualisation using Black-Scholes model in pure Python
DoubleML - Double Machine Learning in R