عنوان

Macroeconomic forecasting in the era of big data :

(Number (ISBN

3030311503

(Number (ISBN

3030311511

(Number (ISBN

303031152X

(Number (ISBN

9783030311506

(Number (ISBN

9783030311513

(Number (ISBN

9783030311520

Erroneous ISBN

303031149X

Erroneous ISBN

9783030311490

Title Proper

Macroeconomic forecasting in the era of big data :

General Material Designation

[Book]

Other Title Information

theory and practice /

First Statement of Responsibility

Peter Fuleky, editor.

Place of Publication, Distribution, etc.

Cham :

Name of Publisher, Distributor, etc.

Springer,

Date of Publication, Distribution, etc.

2020.

Specific Material Designation and Extent of Item

1 online resource

Series Title

Advanced Studies in Theoretical and Applied Econometrics,

Volume Designation

v. 52

ISSN of Series

1570-5811 ;

Text of Note

Includes bibliographical references.

Text of Note

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.

0

Text of Note

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.

Source for Acquisition/Subscription Address

Springer Nature

Stock Number

com.springer.onix.9783030311506

International Standard Book Number

9783030311490

Big data.

Economic forecasting.

Big data.

Economic forecasting.

BUS021000

KCH

KCH

Number

Edition

Class number

Fuleky, Peter.

Date of Transaction

20200823094209.0

Cataloguing Rules (Descriptive Conventions))

pn

Electronic name

[Book]

Y