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Macroeconomic Forecasting in the Era of Big Data = Theory and Practice /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Macroeconomic Forecasting in the Era of Big Data/ edited by Peter Fuleky.
其他題名:	Theory and Practice /
其他作者:	Fuleky, Peter.
面頁冊數:	XIII, 719 p. 80 illus., 62 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Big Data/Analytics. -
電子資源:	https://doi.org/10.1007/978-3-030-31150-6
ISBN:	9783030311506

Macroeconomic Forecasting in the Era of Big Data = Theory and Practice /
Macroeconomic Forecasting in the Era of Big DataTheory and Practice /[electronic resource] :edited by Peter Fuleky. - 1st ed. 2020. - XIII, 719 p. 80 illus., 62 illus. in color.online resource. - Advanced Studies in Theoretical and Applied Econometrics,521570-5811 ;. - Advanced Studies in Theoretical and Applied Econometrics,48.

Introduction: Sources and Types of Big Data for Macroeconomic Forecasting -- Capturing Dynamic Relationships: Dynamic Factor Models -- Factor Augmented Vector Autoregressions, Panel VARs, and Global VARs -- Large Bayesian Vector Autoregressions -- Volatility Forecasting in a Data Rich Environment -- Neural Networks -- Seeking Parsimony: Penalized Time Series Regression -- Principal Component and Static Factor Analysis -- Subspace Methods -- Variable Selection and Feature Screening -- Dealing with Model Uncertainty: Frequentist Averaging -- Bayesian Model Averaging -- Bootstrap Aggregating and Random Forest -- Boosting -- Density Forecasting -- Forecast Evaluation -- Further Issues: Unit Roots and Cointegration -- Turning Points and Classification -- Robust Methods for High-dimensional Regression and Covariance Matrix Estimation -- Frequency Domain -- Hierarchical Forecasting.

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.

ISBN: 9783030311506

Standard No.: 10.1007/978-3-030-31150-6doiSubjects--Topical Terms:

1106909
Big Data/Analytics.

LC Class. No.: HB139-141

Dewey Class. No.: 330.015195

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