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.
Author(s): Peter Fuleky
Series: Advanced Studies In Theoretical And Applied Econometrics Vol. 52
Publisher: Springer
Year: 2020
Language: English
Pages: 716
Tags: Econometrics, Macroeconomic Forecasting, Big Data
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
