Long-Run Growth Forecasting [Paperback]

This book explores how to set up an empirical model that helps with forecasting long-term economic growth. GDP forecasts for the years 2006 to 2020 for 40 countries are derived in a transparent way. Offering a systematic approach to models of potential GDP that can also be used for forecasts of more than a decade it fills the wide gap between the high demand for such models by banks, international organizations, 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 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.

The importance of long-run growth analysis.- Assessment of growth theories.- The dependent variable: GDP growth.- Labor input.- Physical capital.- Human capital.- Openness.- Spatial linkages.- Other determinants of GDP.- The theory of forecasting.- The evolution of growth empirics.- Estimation results.- Forecast competitions and 2006-2020 forecasts.- Conclusion and outlook.

From the reviews:

The whole book undoubtedly benefits from Bergheims 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)

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