In the last last post I gave a brief introduction to systems theory and its relevance to understanding how the economy works. This week I’m going to introduce an area of study known as “systems of innovation” or “national systems of innovation” (NSI). This is empirical research into how innovation happens within an economy and is therefore of great value to anyone wanting to understand how the government can best stimulate and facilitate this.
The term was coined by Bendt-Ake Lundvall and Chris Freeman in 1982. It immediately calls to mind Friedrich List’s classic book The National System of Political Economy (see this post). And this title in turn was a clear reference to the “American System”, the government plan for the economic growth of the USA in the early 19th century.
But the greatest influence on this area of study was Joseph Schumpeter (1883-1950) and occasionally those pursuing this research have been referred to as “neo-schumpeterians”.
Schumpeter’s main contribution was his analysis of why and how innovation happens. This in turn was an attempt to explain the “business cycle” – the continual growth and contraction of the economy. He drew on the work of Soviet economist Nikolai Kondratiev (1892-1938), who suggested that the economy moves in cycles of about 50-60 years – “long waves”. Kondratiev analysed expansion and recession in the 19th century and concluded that one long wave ran from 1790-1850, with a turning point in 1815; another from 1850-1896, with a turning point in 1873; and that a third long wave had started in 1896.
Schumpeter named these waves “Kondratief waves” and set about explaining why they happened. His hypothesis was that innovations driven by entrepreneurs lead to technological revolutions. These transform the methods of production within an economy, leading to the demise of old technologies and industries. Hence, economies grow through the “creative destruction” of the obsolete industries, a term Schumpeter borrowed from Marx and popularised.
Schumpeter placed great emphasis on the role of the entrepreneur in this process – it is very much a story of the “rugged individual” – and for this reason he will be happily referenced by orthodox economists and exponents of capitalism. However, he is essentially a heterodox economist precisely because he focused on innovation. Orthodox economics has no theory on how innovation happens. (Yes, you read that right – mainstream economics makes no effort to explain how the most important driver of economic development actually occurs.)
The concept of systems of innovation emerged from further research that took Schumpeter’s concept of Kondratiev waves as a starting point but then studied the actual empirical reality of how these surges of innovation and technological revolutions took place. It is not really a separate school of economics, rather an area of research. If you want to fit it into a label, it probably belongs with evolutionary economics or evolutionary political economy.
It is worth noting, first of all, the distinct waves that can be identified historically and the technologies associated with them. The table below gives a very simple summary (the various presentations in the literature are much more detailed, I just want to give you a flavour so have simplified it considerably).
|1770s-1840s||Early mechanisation and steam|
|1840s-1890s||Coal power and railways|
|1890s-1940s||Electrical and heavy engineering|
|1940s-1980s||Mass production and oil|
The research literature also identifies how innovation can drive the end of one wave and the beginning of another. A distinction is made between between different types of innovation that have different effects on economic production. To summarise briefly:
Incremental innovations are improvements to existing technologies. These are happening all the time, often through people simply improving what they do rather than conscious research and development. While these increase productivity, they do not have dramatic effects on economic production as a whole.
Radical innovations are new discoveries as a result of deliberate and intense research and development. For example, the invention of nylon could only be made in laboratory – it could never have happened through improvements within the wool or cotton industries. Similarly, nuclear power was a distinct research effort, not one that could emerge from the oil or coal industries. Such technologies and products can have dramatic effects on society but do not bring about structural change to the economy.
Changes of ‘technology system’ occur when radical innovations spread through the economy, possibly giving rise to entirely new sectors, for example the invention of the microchip leads to the development of the personal computer industry.
Changes in ‘techno-economic paradigm’ occur when a new technology system becomes ubiquitous in the production of other goods. So the microchip and ICT industry become a new “wave” not because of their use and impact on consumers, but because of their use in the production of virtually all other goods and services.
This taxonomy of innovation gives us a way to understand how different innovations are likely to impact the economy. Those nations that invest in the next ‘paradigm’ will be the most successful economically in that era. It seems likely that green energy will be a significant driver of the next wave. It is essential to human life because of global warming, will have a transforming effect on the quality of life because of the reduction in pollution of all types, and could greatly reduce the cost of energy for all other sectors of the economy. An Africa that mainly uses solar power is an Africa freed from the need to earn and spend foreign exchange (i.e. US dollars) on purchasing oil.
Okay, so that’s an empirically based analysis of the different types of innovation and how they impact the economy. But how do such innovations take place?
Here the research diverges sharply from Schumpeter and his simplistic focus on individual entrepreneurs. Such innovations take place because the overall social and economic system encourages and supports them. This is where the concepts of systems theory outlined in the last post can help. Innovation can be seen as the “emergent property” of a system of innovation. If the government nurtures the factors that enable such a system, innovations are likely. The government doesn’t need to choose what innovations need to happen, far less plan exactly what the economy will produce and how it will produce it.
As I’ve suggested in previous posts, like a gardener, the government needs to create the conditions that are conducive to growth. The systems of innovation research reveals in considerable detail the lessons from history of how governments can nurture such systems. It is way beyond the scope of this post to systematically summarise the findings (it would need a whole new section of the blog) and my study is not sufficient to do this adequately at present. However, I can highlight a few key features.
First of all the government needs to fund basic and applied research in technologies that seem likely to be significant in the future. They also need to ensure that financial markets are channelling investment into those industries (a repeated theme of the blog, in which I have comprehensively demonstrated why this cannot be left to unregulated free markets).
One element that has repeatedly been found to have an enormous accelerating effect is clustering firms working in innovative industries. This instantly calls to mind my summary of Reinert’s work (I discovered the systems of innovation literature in part by following up references in Reinert’s book).
Underpinning all of this, education and training in a country needs to develop not just the knowledge but the capabilities relevant to the current and the emerging technological paradigms. This applies not just to school-age education, but particularly to advanced education and professional training. There is copious research showing how different approaches to this in different countries has directly impacted on the technological innovation within those economies.
This is just a tiny, woefully inadequate summary of this area of research. Indeed, this is not so much a summary of the research itself, but rather an indication of what is there to be discovered and why I am keen to study it further. (I was about to enthusiastically embark on this study when the coronavirus crisis threw up so much new analysis of financial markets that I’m struggling just to keep up with that.)
A distinction is made in economics between demand-side and supply-side economics. Orthodox economics rejects any need to focus on the demand-side, because that would involve government intervention and redistribution of income. The fallacy of this is addressed in the “Distribution” section of the blog and the need for demand-side economics is summarised in this post.
“Supply-side” economics has therefore become synonymous with laissez-faire, unregulated free markets and with the minimum possible government intervention and expenditure. But in fact this is just one possible approach to stimulating the supply side of the economy. The main purpose of this section of the blog, particularly its opening 9 posts, was to point out that this approach is entirely driven by political ideology rather than scientific, empirical analysis.
The systems of innovation approach is what supply-side economics should be: empirical research into the lessons of history; studying how governments can take conscious, planned action that nurtures economic systems which produce the greatest amount with the least input of energy and labour, enabling a sustainable, green economy, in which people can earn a decent standard of living, in good working conditions, for a reasonable number of hours a week.
As I have emphasised in recent weeks, the economic response to the coronavirus is going to require just such a conscious, planned effort, and we will pay the price as a society for not having developed these skills over the last few decades.
Unfortunately, the influence of this field seems to have waned somewhat since the turn of the century. Three of its major texts were published in the early ’90s: An Evolutionary Theory of Economic Change, by Nelson and Winter, National Systems of Innovation: Toward a Theory of Innovation and Interactive Learning, edited by Lundvall, and National Innovation Systems: A Comparative Analysis, edited by Nelson. Carlota Perez’s 2002 work, Technological Revolutions and Financial Capital: The Dynamics of Bubbles and Golden Ages, seems to be a particularly significant contribution to the literature. For this post I have mostly drawn on a collection of Chris Freeman’s essays, published as Systems of Innovation Selected Essays in Evolutionary Economics, as it gives an overview of the the development of the research over 25 years.
However, having said that its influence has waned, Mariana Mazzucato has certainly built on this programme of research and Perez is currently Honorary Professor at Mazzucato’s Institute for Innovation and Public Purpose (IIPP). Mazzucato is one of the most important and relevant economists right now, and is attracting consistent attention (she is frequently referenced in the blog, particularly in this post). And Lundvall had a new book published in November last year, The Learning Economy and the Economics of Hope, so the originators of this research are still very much active. (Interestingly, his book focuses on learning organisations, something I didn’t find out till after I had written my recent post on this concept.)
This brief introduction to systems of innovation completes the line of argument of this section of the blog. I started by pointing out that the economic conclusions of the previous sections of the blog point strongly to a role for government. Yet “everybody knows” that government intervention in the economy doesn’t work. So in the opening 8 posts I explored where this popular myth comes from and why it is completely wrong. I then pointed out that this is not a simple binary choice between capitalism and socialism. We need a wholly new way to think about the role of government in the economy, for which I have offered the ‘gardener’ analogy used in this post. And because we have no experience in this, we need to learn, as a society, what the role and relationship is between the governing institutions, the community and the individual in creating an economy that provides enough for everyone. And thus we need to consciously think about this process of change as a learning process, and would do well to turn to the research on institutional learning. Finally, the systems of innovation research provides a wealth of empirical knowledge that can guide us in the specifics of how the government can successfully shape and coordinate the economy.
So the next two posts will now draw together everything in the blog into some kind of conclusion (at least, I think it’s going to be two posts – I’ll know when I’ve written it).