{"product_id":"causal-analysis-isbn-9780262545914","title":"Causal Analysis","description":"\u003cb\u003eA comprehensive and cutting-edge introduction to quantitative methods of causal analysis, including new trends in machine learning.\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003eReasoning about cause and effect—the consequence of doing one thing versus another—is an integral part of our lives as human beings. In an increasingly digital and data-driven economy, the importance of sophisticated causal analysis only deepens.  Presenting the most important quantitative methods for evaluating causal effects, this textbook provides graduate students and researchers with a clear and comprehensive introduction to the causal analysis of empirical data. Martin Huber’s accessible approach highlights the intuition and motivation behind various methods while also providing formal discussions of key concepts using statistical notation. \u003ci\u003eCausal Analysis \u003c\/i\u003ecovers several methodological developments not covered in other texts, including new trends in machine learning, the evaluation of interaction or interference effects, and recent research designs such as bunching or kink designs.\u003cbr\u003e\u003cbr\u003e\u003cul\u003e\n\u003cli\u003eMost complete and cutting-edge introduction to causal analysis, including causal machine learning \u003c\/li\u003e\n\u003cli\u003eClean presentation of rigorous material avoids extraneous detail and emphasizes conceptual analogies over statistical notation\u003c\/li\u003e\n\u003cli\u003eSupplies a range of applications and practical examples using R\u003c\/li\u003e\n\u003c\/ul\u003e1 Introduction 1\u003cbr\u003e2 Causality and No Causality 11\u003cbr\u003e3 Social Experiments and Linear Regression 19\u003cbr\u003e4 Selection on Observables 65\u003cbr\u003e5 Casual Machine Learning 137\u003cbr\u003e6 Instrumental Variables 169\u003cbr\u003e7 Difference-in-Differences 195\u003cbr\u003e8 Synthetic Controls 219\u003cbr\u003e9 Regression Discontinuity, Kink, and Bunching Designs 231\u003cbr\u003e10 Partial Identification and Sensitivity Analysis 255\u003cbr\u003e11 Treatment Evaluation under Interference Effects 271\u003cbr\u003e12 Conclusion 285\u003cbr\u003eReferences 287\u003cbr\u003eIndex 311Martin Huber is Professor of Applied Econometrics at the University of Fribourg, Switzerland, where his research comprises both methodological and applied contributions in the fields of causal analysis and policy evaluation, machine learning, statistics, econometrics, and empirical economics.","brand":"The MIT Press","offers":[{"title":"Default Title","offer_id":46302602100965,"sku":"NP9780262545914","price":60.0,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1842\/7735\/files\/9780262545914.jpg?v=1767723504","url":"https:\/\/k12savings.com\/products\/causal-analysis-isbn-9780262545914","provider":"K12savings","version":"1.0","type":"link"}