Long-Run Growth Forecasting
Buch in deiner Nähe kaufen
Beschreibung
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".
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.
Addresses issues up to now unanswered in the academic literature. GDP forecasts for the years 2006 to 2020 for 40 countries are derived in a transparent way Excellent overview of growth theories and empirical techniques used in the growth literature - with assessments of the strengths and weaknesses in light of the empirical results With pictures of all the underlying data used and illustrations of many of the bilateral relationships between key variables Includes supplementary material: sn.pub/extras
Autor*in
Stefan Bergheim
Themen in »Long-Run Growth Forecasting«
Development Forecasting Panel techniques economic growth growth
Stimmen zu »Long-Run Growth Forecasting«
From the reviews:
"The whole book undoubtedly benefits from Bergheim’s experience as both an analyst and researcher. … his study will prove a veritable treasure especially for young researchers looking for current research themes. … Stefan Bergheim has managed to combine a detailed empirical discussion with the great debates about the pillars of our material well-being. … Well done." (Andre Lieber, Amazon, September, 2008)
()