Macroeconomic forecasting in the era of big data : theory and practice

• 其他作者：
  • Fuleky, Peter, editor.
  • SpringerLink (Online service)
• 其他題名：
  • Advanced studies in theoretical and applied econometrics ;
• 出版： Cham : Springer International Publishing :Imprint: Springer
• 叢書名： Advanced studies in theoretical and applied econometrics,volume 52
• 主題： Economic forecasting. , Big data. , Econometrics. , Macroeconomics/Monetary Economics//Financial Economics. , Big Data. , Statistics for Business, Management, Economics, Finance, Insurance. , Big Data/Analytics.
• ISBN： 9783030311506 (electronic bk.) 、 9783030311490 (paper)
• FIND@SFXID: CGU
• 資料類型: 電子書
• 內容註: 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.
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• 摘要註: 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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