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Long-Run Growth Forecasting, by Stefan Bergheim
Download PDF Long-Run Growth Forecasting, by Stefan Bergheim
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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.
- Sales Rank: #12797390 in Books
- Brand: Brand: Springer
- Published on: 2010-10-19
- Released on: 2010-10-19
- Original language: English
- Number of items: 1
- Dimensions: 9.00" h x .47" w x 6.00" l, .66 pounds
- Binding: Paperback
- 189 pages
- Used Book in Good Condition
Review
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)
From the Back Cover
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".
About the Author
The author works for a commercial bank and has been the lead researcher in the bank's project called "Global Growth Centres 2020".
Most helpful customer reviews
0 of 0 people found the following review helpful.
Long-term economic growth in context
By Andre Lieber
Long-term growth forecasts are a bit like wrong weather forecasts. You are always wiser afterwards. Because even institutions such as the International Monetary Fund or the World Bank are still struggling with large discrepancies in their forecasting, Stefan Bergheim took another investigating look at the most widely used forecast models. His knowledgeable and very readable tour d'horizon of recent research on economic growth culminates in the presentation of his own model - a mix of the best from all economic worlds. The whole book undoubtedly benefits from Bergheim's experience as both an analyst and researcher. He consequently follows his credo that economic research should by no means be treated as a solely retrospective matter, but instead as a science that bears reliable information for future developments. In line with this refreshingly undogmatic perspective he repeatedly pays reference to the limits of empirical research on economic growth. To this end, his study will prove a veritable treasure especially for young researchers looking for current research themes. What is the impact of R&D spending or the quality of political institutions on the long-term economic growth of a country? These and other questions highlight the crucial nature and timeless of future research on long-term economic growth. Stefan Bergheim has managed to combine a detailed empirical discussion with the great debates about the pillars of our material well-being. By doing so he followed a principle that he always kept in mind when developing his own economic forecast model: Keep it simple sophistically (KISS). Well done.
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