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Long-Run Growth Forecasting

  • Stefan Bergheim

Table of contents

  1. Front Matter
    Pages i-xiv
  2. Pages 43-50
  3. Pages 51-65
  4. Pages 67-79
  5. Pages 81-94
  6. Pages 95-102
  7. Pages 137-150
  8. Pages 163-164
  9. Back Matter
    Pages 165-180

About this book

Introduction

This book explores how to set up an empirical model that helps with forecasting long-term economic growth in a large number of countries. It offers a systematic approach to models of potential GDP that can also be used for forecasts of more than a decade. It is an attempt to fill the wide gap between the high demand for such models by commercial banks, international organizations, central banks and governments on the one hand and the limited supply on the other hand. Frequent forecast failures in the past (e.g. Japan 1990, Asia 1997) and the heavy economic losses they produced motivated the work. The book assesses the large number of different theories of economic growth, the drivers of economic growth, the available datasets and the empirical methods on offer. A preference is shown for evolutionary models and an augmented Kaldor model. The book uses non-stationary panel techniques to find pair-wise cointegration among GDP per capita and its main correlates such as physical capital, human capital and openness. GDP forecasts for the years 2006 to 2020 for 40 countries are derived in a transparent way.

The author works for a commercial bank and has been the lead researcher in the bank's project called "Global Growth Centres 2020".

Keywords

Development Forecasting Panel techniques economic growth growth

Authors and affiliations

  • Stefan Bergheim
    • 1
  1. 1.60320Germany

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-540-77680-2
  • Copyright Information Springer Berlin Heidelberg 2008
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Business and Economics
  • Print ISBN 978-3-540-77679-6
  • Online ISBN 978-3-540-77680-2
  • Buy this book on publisher's site