Overview
- Presents a comprehensive collection of big data tools used in macroeconomic forecasting.
- Surveys the most recent developments in the field.
- Offers algorithmic descriptions of big data techniques for forecasting.
- Useful as a reference, a textbook, and a resource for professional forecasters.
Part of the book series: Advanced Studies in Theoretical and Applied Econometrics (ASTA, volume 52)
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About this book
This book surveys big data tools used in macroeconomic forecasting and addresses related econometric issues, including how to capture dynamic relationships among variables; how to select parsimonious models; how to deal with model uncertainty, instability, non-stationarity, and mixed frequency data; and how to evaluate forecasts, among others. Each chapter is self-contained with references, and provides solid background information, while also reviewing the latest advances in the field. Accordingly, the book offers a valuable resource for researchers, professional forecasters, and students of quantitative economics.
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Keywords
- Big Data
- Macroeconomic forecasting
- Dimension reduction
- Shrinkage
- Model forecast combination
- Dynamic factor models
- Vector autoregressions
- Mixed frequency data sampling regressions
- Estimation of common factors
- Penalized regression
- Variable selection
- Feature screening
- Subspace methods
- Averaging
- Aggregation
- Unit roots
- Cointegration
- Forecasts
- Time varying parameters
Table of contents (21 chapters)
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Front Matter
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Introduction
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Front Matter
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Capturing Dynamic Relationships
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Front Matter
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Seeking Parsimony
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Front Matter
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Dealing with Model Uncertainty
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Front Matter
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Editors and Affiliations
About the editor
Peter Fuleky is an Associate Professor of Economics with a joint appointment at the University of Hawaii Economic Research Organization (UHERO), and the Department of Economics at the University of Hawaii at Manoa. His research focuses on econometrics, time series analysis, and forecasting. He is a co-author of UHERO's quarterly forecast reports on Hawaii's economy. He obtained his Ph.D. degree in Economics at the University of Washington, USA.
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Bibliographic Information
Book Title: Macroeconomic Forecasting in the Era of Big Data
Book Subtitle: Theory and Practice
Editors: Peter Fuleky
Series Title: Advanced Studies in Theoretical and Applied Econometrics
DOI: https://doi.org/10.1007/978-3-030-31150-6
Publisher: Springer Cham
eBook Packages: Economics and Finance, Economics and Finance (R0)
Copyright Information: Springer Nature Switzerland AG 2020
Hardcover ISBN: 978-3-030-31149-0Published: 12 December 2019
Softcover ISBN: 978-3-030-31152-0Published: 19 December 2020
eBook ISBN: 978-3-030-31150-6Published: 28 November 2019
Series ISSN: 1570-5811
Series E-ISSN: 2214-7977
Edition Number: 1
Number of Pages: XIII, 719
Number of Illustrations: 18 b/w illustrations, 62 illustrations in colour
Topics: Econometrics, Macroeconomics/Monetary Economics//Financial Economics, Big Data, Statistics for Business, Management, Economics, Finance, Insurance, Big Data/Analytics