EconometronA Python Library for DSGE Modelling and Multivariate Time Series Analysis

Empowering Economists, Data Scientists, and Researchers with Cutting-Edge Tools

Comprehensive DSGE Modelling

Define, solve, and simulate linear and nonlinear Dynamic Stochastic General Equilibrium models with symbolic and numerical solutions, including Klein's method.

Advanced Time Series Analysis

Native support for classical multivariate models including VAR, VARMA,...and Deep learning models (N-BEATS) and State Space Modeling ,enabling robust forecasting, diagnostics, and local projections for multivariate time series.

Estimation Suite

Perform Regression, MLE, and Bayesian inference with flexible prior specifications. Integrated Kalman filter and smoother for state-space models.

Optimization and Bayesian Sampling Tools

Leverage Genetic Algorithms (GA), Simulated Annealing (SA),and RWMH for parameter estimation and model selection.

Educational and Intuitive

Visual diagnostics, clear error messages, and step-by-step guides make Econometron accessible to both beginners and experts.

🚀 Quickstart

Install Econometron and run your first model in seconds:

pip install econometron

python

from econometron.Models.VectorAutoReg.VAR import VAR
import pandas as pd

# Example: Fit a simple VAR model
df = pd.read_csv('your_data.csv')
var_model = VAR(data=df,max_p=2, criterion='AIC', forecast_horizon=8, plot=True)
var_model.fit()
forecasts = var_model.predict()

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