Econometrics Python Packages

statsmodels

Statsmodels: statistical modeling and econometrics in Python

pmdarima

A statistical library designed to fill the void in Python's time series analysis capabilities, including the equivalent of R's auto.arima function.

statsforecast

Lightning ⚡️ fast forecasting with statistical and econometric models.

econml

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.

hierarchicalforecast

Probabilistic Hierarchical forecasting 👑 with statistical and econometric methods.

pyfixest

Fast High-Dimensional Fixed Effects Regression in Python following fixest-syntax

spreg

Spatial econometric regression in Python

fedfred

A feature-rich python package for interacting with the Federal Reserve Bank of St. Louis Economic Database: FRED

doubleml

DoubleML - Double Machine Learning in Python

diff-diff

Difference-in-Differences causal inference in Python. Callaway-Sant'Anna, Synthetic DiD, Honest DiD, event studies. sklearn-like API, validated against R.

stata-mcp

Stata-MCP: A MCP server for integrating Stata into your agent loop with a safety-first design.

statspai

StatsPAI is the first Agent-native Python library for causal inference and applied econometrics — unified API, broad cross-method coverage, structured result objects, machine-readable schemas, Skills, an MCP server, and R/Stata parity validation.

ipeadatapy

ipeadatapy is a data and metadata extraction package made in Python using Ipeadata database official API. In it's essence it is an API wrapper.

wooldridge

A Python package containing 111 data sets of Introductory Econometrics: A Modern Approach (7th ed, J.M. Wooldridge)

mcp-stata

A lightweight Model Context Protocol (MCP) server for Stata. Execute commands, inspect data, retrieve stored results (r()/e()), and view graphs in your chat interface. Built for economists who want to integrate LLM assistance into their Stata workflow.

drvarma

drvarma (Python) — exact-ML multivariate VARMA estimation, forecasting, IRF/FEVD and diagnostics. Ships sima, an MCP server for LLM-driven VARMA analysis

puremacro

Browser-runnable empirical macroeconomics in pure Python: VAR/SVAR/LP/GARCH/inference/VFI/DSGE/narrative, with built-in validation & replication galleries (Pyodide-compatible).

symbolicdsge

A first and second-order DSGE engine with a fully symbolic and modifiable model backend. Includes estimation, monte carlo pipeline costruction, and regression-based equation augmentation capabilities

lightweight-mmm

LightweightMMM 🦇 is a lightweight Bayesian Marketing Mix Modeling (MMM) library that allows users to easily train MMMs and obtain channel attribution information.

differences

difference-in-differences in Python

stata-code

Agent-native Stata bridge for empirical research — run DiD/IV/RDD and publication-ready tables from Claude Code, Jupyter, or VS Code on one token-economy result schema, with StatsPAI cross-validation. | 面向实证研究的智能体 Stata 桥接器——在 Claude Code、Jupyter、VS Code 中用一套省 token 的结果格式跑 DiD/IV/RDD 与出版级表格，并支持 StatsPAI 跨栈交叉验证。

atsw

ART (art-tseries) — Box-Jenkins-Treadway model-building toolkit + MCP server; includes the atsw umbrella meta-package. Part of the ATSW suite.

aigroup-econ-mcp

Econometrics MCP server for regression, causal inference, time series, panel data, and statistical analysis workflows.

nextstat

Universal differentiable statistical inference engine (Rust + GPU). High-performance Frequentist & Bayesian modeling, RL environments, and end-to-end optimization for Science, Pharma, and Finance