£142.70

Springer Prediction and Causality in Econometrics - Vol 983

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Description

Understanding how the economy develops and predicting the impact of different policies is the primary goal of economic studies. This book, part of the Studies in Computational Intelligence series, explores the fundamental relationship between prediction and causality in economics. By examining what causes specific economic shifts, researchers can better prepare for future trends. The chapters cover a wide range of topics, applying both traditional methods and innovative techniques, including quantum ideas, to analyze the global and national economy. Whether you are studying international trade and exchange rates or focusing on national indicators like gross domestic product, stock indices, and inflation rates, this text provides the technical framework needed for modern econometric analysis. It serves as a comprehensive resource for those looking to bridge the gap between theoretical causality and practical economic forecasting.

Key Features

Explores the relationship between prediction and causality to help determine how different economic policies might impact future developments.

Covers a wide range of economic indicators including gross domestic product, stock indices, and inflation rates.

Utilizes both traditional econometric methods and innovative techniques, including the application of quantum ideas.

Provides analysis for both global economic factors like international trade and exchange rates, and specific national economic data.

Part of the Studies in Computational Intelligence series (Volume 983) from Springer for advanced academic study.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
27 July 2021
Listed Since
15 August 2020

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