9798248198641 - structural causal economics with python: models for economic policy: 5 (quantitative economics & python series) de thatch, oliver j. (3 resultados)
Idioma: Inglés
Editorial: Independently published, 2026
Serie: Quantitative Economics & Python Series, Libro 5 de 16. Libro 5 de 16 - Quantitative Economics & Python Series
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Librería: California Books, Miami, FL, Estados Unidos de AmericaCalifornia Books
Contactar con el vendedorVendedor de 4 estrellasCondición: Nuevo
EUR 37,94
Gastos de envío gratisSe envía dentro de Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
Condición: New. Print on Demand.
Idioma: Inglés
Editorial: Independently Published, 2026
Serie: Quantitative Economics & Python Series, Libro 5 de 16. Libro 5 de 16 - Quantitative Economics & Python Series
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Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de AmericaGrand Eagle Retail
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 43,13
Gastos de envío gratisSe envía dentro de Estados Unidos de AmericaCantidad disponible: 1 disponibles
Paperback. Condición: new. Paperback. Reactive PublishingEconomic systems are shaped by complex cause-and-effect relationships that traditional correlation-based models often fail to capture. Structural Causal Economics with Python introduces a rigorous, modern framework for understanding economic mechanisms using structural cau…sal models, graph-based reasoning, and counterfactual simulation.This book bridges the gap between academic causal inference theory and real-world economic modeling. Readers learn how to move beyond prediction into explanation, policy testing, and scenario design using practical Python implementations. The focus is on building models that reflect how economic systems actually behave under intervention, shock, and policy change.Inside, you will learn how to: - Build and interpret causal graphs for economic systems- Design structural models that capture real economic mechanisms- Perform counterfactual analysis to evaluate alternative policy scenarios- Simulate policy interventions and measure downstream effects- Implement causal modeling workflows using modern Python tools- Connect causal inference methods to macroeconomic and microeconomic applicationsRather than treating economic data as purely statistical signals, this book teaches you how to model the underlying structure that generates economic outcomes. The result is more robust forecasting, clearer policy insight, and deeper strategic understanding.Written for quantitative economists, policy analysts, data scientists, and advanced finance professionals, this book assumes familiarity with Python and core economic concepts. It is designed as both a practical implementation guide and a conceptual reference for structural causal economic modeling.If you want economics models that explain why outcomes happen, not just what happens next, this book provides the tools and framework to build them. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Idioma: Inglés
Editorial: Independently Published, 2026
Serie: Quantitative Economics & Python Series, Libro 5 de 16. Libro 5 de 16 - Quantitative Economics & Python Series
- Tapa blanda
- Impresión bajo demanda
Librería: CitiRetail, Stevenage, Reino UnidoCitiRetail
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 42,19
Envío por EUR 43,31Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Paperback. Condición: new. Paperback. Reactive PublishingEconomic systems are shaped by complex cause-and-effect relationships that traditional correlation-based models often fail to capture. Structural Causal Economics with Python introduces a rigorous, modern framework for understanding economic mechanisms using structural cau…sal models, graph-based reasoning, and counterfactual simulation.This book bridges the gap between academic causal inference theory and real-world economic modeling. Readers learn how to move beyond prediction into explanation, policy testing, and scenario design using practical Python implementations. The focus is on building models that reflect how economic systems actually behave under intervention, shock, and policy change.Inside, you will learn how to: - Build and interpret causal graphs for economic systems- Design structural models that capture real economic mechanisms- Perform counterfactual analysis to evaluate alternative policy scenarios- Simulate policy interventions and measure downstream effects- Implement causal modeling workflows using modern Python tools- Connect causal inference methods to macroeconomic and microeconomic applicationsRather than treating economic data as purely statistical signals, this book teaches you how to model the underlying structure that generates economic outcomes. The result is more robust forecasting, clearer policy insight, and deeper strategic understanding.Written for quantitative economists, policy analysts, data scientists, and advanced finance professionals, this book assumes familiarity with Python and core economic concepts. It is designed as both a practical implementation guide and a conceptual reference for structural causal economic modeling.If you want economics models that explain why outcomes happen, not just what happens next, this book provides the tools and framework to build them. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
