Macroeconomic Forecasting In The Era Of Big Data: Theory And Practice
Book information
Description
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. Front Matter ....Pages i-xiii Front Matter ....Pages 1-1 Sources and Types of Big Data for Macroeconomic Forecasting (Philip M. E. Garboden)....Pages 3-23 Front Matter ....Pages 25-25 Dynamic Factor Models (Catherine Doz, Peter Fuleky)....Pages 27-64 Factor Augmented Vector Autoregressions, Panel VARs, and Global VARs (Martin Feldkircher, Florian Huber, Michael Pfarrhofer)....Pages 65-93 Large Bayesian Vector Autoregressions (Joshua C. C. Chan)....Pages 95-125 Volatility Forecasting in a Data Rich Environment (Mauro Bernardi, Giovanni Bonaccolto, Massimiliano Caporin, Michele Costola)....Pages 127-160 Neural Networks (Thomas R. Cook)....Pages 161-189 Front Matter ....Pages 191-191 Penalized Time Series Regression (Anders Bredahl Kock, Marcelo Medeiros, Gabriel Vasconcelos)....Pages 193-228 Principal Component and Static Factor Analysis (Jianfei Cao, Chris Gu, Yike Wang)....Pages 229-266 Subspace Methods (Tom Boot, Didier Nibbering)....Pages 267-291 Variable Selection and Feature Screening (Wanjun Liu, Runze Li)....Pages 293-326 Front Matter ....Pages 327-327 Frequentist Averaging (Felix Chan, Laurent Pauwels, Sylvia Soltyk)....Pages 329-357 Bayesian Model Averaging (Paul Hofmarcher, Bettina Grün)....Pages 359-388 Bootstrap Aggregating and Random Forest (Tae-Hwy Lee, Aman Ullah, Ran Wang)....Pages 389-429 Boosting (Jianghao Chu, Tae-Hwy Lee, Aman Ullah, Ran Wang)....Pages 431-463 Density Forecasting (Federico Bassetti, Roberto Casarin, Francesco Ravazzolo)....Pages 465-494 Forecast Evaluation (Mingmian Cheng, Norman R. Swanson, Chun Yao)....Pages 495-537 Front Matter ....Pages 539-539 Unit Roots and Cointegration (Stephan Smeekes, Etienne Wijler)....Pages 541-584 Turning Points and Classification (Jeremy Piger)....Pages 585-624 Robust Methods for High-Dimensional Regression and Covariance Matrix Estimation (Marco Avella-Medina)....Pages 625-653 Frequency Domain (Felix Chan, Marco Reale)....Pages 655-687 Hierarchical Forecasting (George Athanasopoulos, Puwasala Gamakumara, Anastasios Panagiotelis, Rob J. Hyndman, Mohamed Affan)....Pages 689-719
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