Machine Learning for Econometrics is a book for economists seeking to grasp modern machine learning techniques - from their predictive performance to the revolutionary handling of unstructured data - in order to establish causal relationships from data. The volume covers automatic variable selection in various high-dimensional contexts, estimation of treatment effect heterogeneity, natural language processing (NLP) techniques, as well as synthetic control and macroeconomic forecasting. The foundations of machine learning methods are introduced to provide both a thorough theoretical treatment of how they can be used in econometrics and numerous economic applications, and each chapter contains a series of empirical examples, programs, and exercises to facilitate the reader's adoption and implementation of the techniques.
Procurando Machine Learning for Econometrics? Aqui você encontra tudo sobre este livro de Associate Professor Christophe Gaillac, publicado por Oxford University Press em 22 de setembro de 2025. Nesta página estão a descrição da obra, os detalhes da edição (352 páginas) e os formatos disponíveis para baixar: pdf, epub, txt, djvu. Se você gosta de Livros Internacionais, Administração, Negócios e Economia, Economia, Econometria, explore também outros títulos da mesma categoria no Encontrando os melhores livros. Veja ainda as outras obras de Associate Professor Christophe Gaillac em nosso catálogo.
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