عنوان

Macroeconomic forecasting in the era of big data :

شابک

3030311503

شابک

3030311511

شابک

303031152X

شابک

9783030311506

شابک

9783030311513

شابک

9783030311520

شابک اشتباه

303031149X

شابک اشتباه

9783030311490

عنوان اصلي

Macroeconomic forecasting in the era of big data :

نام عام مواد

[Book]

ساير اطلاعات عنواني

theory and practice /

نام نخستين پديدآور

Peter Fuleky, editor.

محل نشرو پخش و غیره

Cham :

نام ناشر، پخش کننده و غيره

Springer,

تاریخ نشرو بخش و غیره

2020.

نام خاص و کميت اثر

1 online resource

عنوان فروست

Advanced Studies in Theoretical and Applied Econometrics,

مشخصه جلد

v. 52

شاپا ي ISSN فروست

1570-5811 ;

متن يادداشت

Includes bibliographical references.

متن يادداشت

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.

بدون عنوان

0

متن يادداشت

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.

منبع سفارش / آدرس اشتراک

Springer Nature

شماره انبار

com.springer.onix.9783030311506

شماره استاندارد بين المللي کتاب و موسيقي

9783030311490

موضوع مستند نشده

Big data.

موضوع مستند نشده

Economic forecasting.

موضوع مستند نشده

Big data.

موضوع مستند نشده

Economic forecasting.

موضوع مستند نشده

BUS021000

موضوع مستند نشده

KCH

موضوع مستند نشده

KCH

شماره

ويراست

شماره رده

مستند نام اشخاص تاييد نشده

Fuleky, Peter.

تاريخ عمليات

20200823094209.0

قواعد فهرست نويسي ( بخش توصيفي )

pn

نام الکترونيکي

نوع ماده

[Book]

تكميل شده

Y