Modelling our changing world /

Modelling our changing world /

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Bibliographic Details
Author / Creator:Castle, Jennifer, 1979- author.
Imprint:Cham : Palgrave Macmillan, [2019]
©2019
Description:1 online resource : color illustrations
Language:English
Series:Palgrave texts in econometrics
Palgrave texts in econometrics.
Subject:
Econometrics.
Time-series analysis.
Econometrics.
Time-series analysis.
Electronic books.
Format: E-Resource Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/12626076
Hidden Bibliographic Details
Other authors / contributors:Hendry, David F., author.
ISBN:9783030214326
303021432X
9783030214319
Notes:Includes bibliographical references and indexes.
Open access.
Online resource; title from PDF title page (SpringerLink, viewed September 16, 2019).
Summary:This open access book focuses on the concepts, tools and techniques needed to successfully model ever-changing time-series data. It emphasizes the need for general models to account for the complexities of the modern world and how these can be applied to a range of issues facing Earth, from modelling volcanic eruptions, carbon dioxide emissions and global temperatures, to modelling unemployment rates, wage inflation and population growth. Except where otherwise noted, this book is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0.
Standard no.:10.1007/978-3-030-21432-6
Table of Contents:
  • 1.Introduction
  • Reference
  • 2.Key Concepts: A Series of Primers
  • 2.1.Time Series Data
  • 2.2.Stationarity and Non-stationarity
  • 2.3.Structural Breaks
  • 2.4.Model Selection
  • References
  • 3.Why Is the World Always Changing?
  • 3.1.Major Sources of Changes
  • 3.2.Problems if Incorrectly Modelling Non-stationarity
  • References
  • 4.Making Trends and Breaks Work to Our Advantage
  • 4.1.Potential Solutions to Stochastic Trend Non-stationarity
  • 4.2.Cointegration Between 1(1) Processes
  • 4.3.Location Shifts
  • 4.4.Dynamic-Stochastic General Equilibrium (DSGE) Models
  • 4.5.Handling Location Shifts
  • 4.6.Some Benefits of Non-stationarity
  • References
  • 5.Detectives of Change: Indicator Saturation
  • 5.1.Impulse-Indicator Saturation
  • 5.2.Step-Indicator Saturation
  • 5.3.Designing Indicator Saturation
  • 5.3.1.Trend-Indicator Saturation
  • 5.3.2.Multiplicative-Indicator Saturation
  • 5.3.3.Designed-Break Indicator Saturation
  • 5.4.Outliers and Non-linearity
  • References
  • 6.The Polymath: Combining Theory and Data
  • 6.1.Theory Driven and Data Driven Models
  • 6.2.The Drawbacks of Using Each Approach in Isolation
  • 6.3.A Combined Approach
  • 6.4.Applying the Combined Approach to UK Inflation Data
  • References
  • 7.Seeing into the Future
  • 7.1.Forecasting Ignoring Oudiers and Location Shifts
  • 7.2.Impacts of Stochastic Trends on Forecast Uncertainty
  • 7.3.Impacts of Location Shifts on Forecast Uncertainty
  • 7.4.Differencing Away Our Troubles
  • 7.5.Recommendations When Forecasting Facing Non-stationarity
  • References
  • 8.Conclusions: The Ever-Changing Way Forward
  • References.

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