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2015 | OriginalPaper | Buchkapitel

Energy, Knowledge and Economic Growth

verfasst von : John Foster

Erschienen in: The Evolution of Economic and Innovation Systems

Verlag: Springer International Publishing

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Abstract

It is argued that the explosive growth experienced in much of the World since the middle of the 19th Century is due to the exploitation and use of fossil fuels which, in turn, was made possible by capital good innovations that enabled this source of energy to be used effectively. Economic growth is viewed as the outcome autocatalytic co-evolution of energy use and the application of new knowledge associated with energy use. It is argued that models of economic growth should be built from innovation diffusion processes, unfolding in history, rather than from a timeless aggregate production function. A simple ‘evolutionary macroeconomic’ model of economic growth is developed and tested using almost two centuries of British data. The empirical findings strongly support the hypothesis that growth has been due to the presence of a ‘super-radical innovation diffusion process’ following the industrial deployment of fossil fuels on a large scale in the 19th Century. Also, the evidence suggests that large and sustained movements in energy prices have had a very significant long term role to play.

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Vorheriges Kapitel Introduction: The Evolution of Economic and Innovation Systems

Nächstes Kapitel Metabolic Growth Theory: Market-Share Competition, Learning Uncertainty, and Technology Wavelets

Galor and Michalopoulos (2012) claimed that it is possible to capture entrepreneurship in a neoclassical model. Typically, their highly mathematical model contains many very abstract assumptions that invalidate its relevance to the history that they discuss.

It is instructive that Aghion and Howitt (1998), who hijacked the term ‘Schumpeterian’ for their endogenous growth theorizing, do not even have ‘entrepreneur’ or ‘entrepreneurship’ in the index of their 190 page book.

See, for example, Deane (1969), Harley (1982), Crafts (2005) and Wrigley (2010) for extended discussion concerning the existence, or otherwise, of the first industrial revolution.

Harris (1967) pointed out that steam engines were used extensively in the 18th Century to pump water out of coal mines, even though they were relatively inefficient, because they used ‘waste’ coal fragments that had little commercial value.

Field (2011) has provided convincing evidence that, in the US case, this resulted in a sharp rise in inventive and innovative behaviour in the 1930s.

It has been commonly assumed in a number of neoclassically-based studies of economic growth that the capital-output and/or the capital-labour ratio have been approximately constant. In the British case, the former in 2010 was about 2.5 times greater that it was in 1900 and the latter about 12 times greater.

The two negative blips are caused by the potato famine (1845-1852) and Irish independence (1922).

Interestingly, despite its reputation as a ‘mature’ economy, the UK continued, up to the recession of 2009, to record a labour productivity growth rate that was not only consistently positive but on a continual rising trend, despite the massive shift towards service sector activities.

Stern and Kander (2012) stepped back from the endogenous growth framework, instead, employing a variant of the Solow growth model using a CES production function with time varying elasticities of substitution. They reported that, for Sweden, energy seems to have played an important role in the determination of economic growth over two centuries. Ayres and Warr (2009) also viewed the Cobb-Douglas specification as too restrictive, preferring a more realistic Linex production function to which they add ‘useful work’ to capture energy flow and energy efficiency effects.

There is no particular focus on energy in most endogenous growth models although it does figure in some studies (see Pittel and Rübbelke (2010) for a review).

Howitt and Aghion (1998) also, saw the capital stock as the main conduit for innovation. However, the neoclassically-based theory that they offer is very different, analytically, to the evolutionary macroeconomic one proposed here and it is not operationalisable econometrically.

The results reported using the logistic specification are very similar but the Gompertz results offer a much more plausible representation of the diffusion process at that has been at work.

Since all product innovations are the outcome of the efforts of labour and there are also continual increases in the efficiency of energy use, making it cheaper per joule, a can be viewed as the sum of two connected diffusion coefficients. Thus, it is possible for GDP to grow at a faster rate than these inputs.

Foster and Wild (1999b) provide evidence suggesting that the errors in an innovation diffusion growth model should not be strictly random.

This formulation is similar to the ‘capital stock adjustment principle’ (Matthews 1959), not in a cyclical context where GDP is the main independent variable, but operative over the much longer time scale relevant to economic growth.

Irish independence shifted population and GDP time series for the UK in the Maddison data. The impact of this was checked in the modelling and found not to be a problem.

There has been considerable controversy concerning the reliability of data used by ‘cliometricians’ prior to 1830. See, For example, Allen (2008).

Note that the total energy consumption data used in the modeling was for England and Wales, rather than the UK. So there is an implicit assumption that there is a fixed ratio between the two. Examination of Scottish and UK population statistics suggested that England and Wales, indeed, is a good proxy, especially when it is the rate of growth of total energy consumption that is the explanatory variable used in the modeling.

Instrument List: e _{t
−1}, e _{t
−2}, e _{t
−4}, h _{t
−1}, h _{t
−1}, DUM 184042, DUM 1856, DUM 1919, DUM 1941, DUM 2009, gpop _t, gpop _{t
−1}, gpop _{t
−2}, gpop _{t
−5}, gpop _{t
−6}, gpop _{t
−7}, E _{t
−1}

It should be borne in mind that the presence of measurement error in explanatory variables biases estimated coefficients downwards. This is likely to be the case when using long series of annual data. However, it is not possible to assess the magnitude of such bias except to note that the observed stability of estimated coefficients in different sample periods suggest that such bias is likely to be small.

Energy prices are sourced from Fouquet (2011). It is inadvisable to go further back in history than 1850 because earlier estimates of energy prices, based upon very fragmentary, infrequent and localized data, are notoriously unreliable.

See Gordon (2012) for discussion, using a different perspective, of the prospects of future growth in what is currently the World’s leading economy, the United States.

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Titel: Energy, Knowledge and Economic Growth
verfasst von: John Foster
Verlag: Springer International Publishing
Buch: The Evolution of Economic and Innovation Systems
Print ISBN: 978-3-319-13298-3

Electronic ISBN: 978-3-319-13299-0

Copyright-Jahr: 2015
DOI: https://doi.org/10.1007/978-3-319-13299-0_2

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