{"product_id":"machine-learning-for-econometrics-with-python-causal-inference-structural-modeling-and-predictive-methods-for-economic-research-9798252248318","title":"Machine Learning for Econometrics with Python: Causal Inference, Structural Modeling, and Predictive Methods for Economic Research","description":"\u003cp\u003e • Author(s): Alice Schwartz | Hayden Van Der Post | Oliver J. Thatch\u003cbr\u003e • Publisher: Independently Published\u003cbr\u003e • Publisher Imprint: Independently Published\u003cbr\u003e • BISAC: Econometrics\u003c\/p\u003e\u003cp\u003e\u003cb\u003eReactive Publishing\u003c\/b\u003e\u003c\/p\u003e\u003cp\u003eModern econometrics is evolving rapidly as machine learning methods reshape how economists analyze complex data. This book provides a rigorous, practical guide to integrating machine learning techniques with the core tools of econometric analysis using Python.\u003c\/p\u003e\u003cp\u003e\u003cb\u003eMachine Learning for Econometrics with Python\u003c\/b\u003e introduces economists, researchers, and quantitative analysts to the growing intersection between statistical learning and economic modeling. The book focuses on how modern machine learning methods can complement traditional econometric frameworks while preserving interpretability, causal reasoning, and structural insight.\u003c\/p\u003e\u003cp\u003eReaders will learn how to apply machine learning techniques within the context of real economic research problems, including causal estimation, structural modeling, and high-dimensional prediction.\u003c\/p\u003e\u003cp\u003eTopics covered include: \u003c\/p\u003e\u003cul\u003e\n\u003cli\u003e\u003cp\u003eFoundations of machine learning for econometric analysis\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eRegularization methods such as LASSO and Ridge for economic models\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eTree-based methods and ensemble learning for economic forecasting\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eCausal machine learning approaches including double machine learning and orthogonalization\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eHigh-dimensional variable selection in economic datasets\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eStructural econometric models enhanced with machine learning components\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eTime-series forecasting using modern machine learning tools\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eInterpretable machine learning methods for economic research\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eSimulation and empirical workflows using Python\u003c\/p\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eThroughout the book, practical Python examples demonstrate how machine learning techniques can be implemented using widely adopted scientific libraries such as NumPy, pandas, scikit-learn, and PyTorch.\u003c\/p\u003e\u003cp\u003eRather than replacing econometrics, machine learning expands the economist's toolkit. This book shows how both disciplines can work together to address modern research challenges involving large datasets, complex nonlinear relationships, and high-dimensional economic systems.\u003c\/p\u003e\u003cp\u003eIdeal for: \u003c\/p\u003e\u003cul\u003e\n\u003cli\u003e\u003cp\u003eEconomists and quantitative researchers\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eGraduate students in econometrics or applied economics\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eData scientists working with economic or financial datasets\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003ePolicy analysts interested in modern causal modeling techniques\u003c\/p\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003e\u003cb\u003eMachine Learning for Econometrics with Python\u003c\/b\u003e bridges the gap between statistical learning and economic theory, providing a practical framework for applying machine learning methods to modern econometric research.\u003c\/p\u003e","brand":"Independently Published","offers":[{"title":"Paperback","offer_id":47776117260439,"sku":"9798252248318","price":3127.0,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0666\/3471\/1191\/files\/9798252248318.webp?v=1777994370","url":"https:\/\/atlanticbooks.com\/products\/machine-learning-for-econometrics-with-python-causal-inference-structural-modeling-and-predictive-methods-for-economic-research-9798252248318","provider":"Atlantic Books","version":"1.0","type":"link"}