Econometric Modeling & Forecasting with Python: Applied Methods for Causal Inference, Time Series, and Predictive Economic Analytics (Quantitative Economics & Python Series Book 3)
English | December 11, 2025 | ASIN: B0G6GLF1P5 | 588 pages | Epub | 654.81 KB
Reactive PublishingEconometric Modeling & Forecasting with Python provides a comprehensive, practice-oriented guide to modern econometrics, bridging classical statistical methods with contemporary computational tools. Designed for economists, analysts, researchers, and data scientists, this volume equips readers with the quantitative skills and Python workflows needed to analyze economic data, test hypotheses, and generate reliable forecasts.Building from foundational regression techniques to advanced causal inference and machine-learning-enhanced forecasting, the book emphasizes real-world applicability, modeling clarity, and fully reproducible code. Readers learn not just how econometric models work, but how to implement, evaluate, and interpret them in a modern data environment.Through step-by-step explanations and extensive Python examples, readers will learn to:* Conduct robust linear, generalized, and nonlinear regression analysis* Build and interpret panel data models for cross-sectional and longitudinal studies* Apply causal inference tools including difference-in-differences, IV, RDD, and synthetic controls* Develop and evaluate time series forecasting models such as ARIMA, VAR, VECM, and machine learning approaches* Use Bayesian techniques for estimation and uncertainty quantification* Integrate large-scale, real-world economic datasets into efficient Python workflows* Translate statistical output into actionable insights for research, policy, or strategyThis volume provides both the conceptual foundation and technical depth needed to practice econometrics at a professional or graduate level. It serves as a bridge between traditional textbooks and the modern computational toolkit demanded in today's analytical landscape.Part of the Quantitative Economics & Python Series, this book forms the core of applied economic analysis, positioned between foundational microeconomic simulation and advanced macroeconomic policy modeling.
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