Economic growth. It is the key to rising wages and living standards all over the world and the last half a century or so has seen millions of people in developing nations escape poverty and see their living standards soar through the benefits of economic growth, whilst in developed nations such as the United Kingdom, we have been witnessing these effects for more than two centuries, as shown in the graph below.
The figures for economic growth are barely out of the news and are constantly politicised due to their extreme importance to the quality of life within economies. This importance has meant that much macroeconomic theory has been developed with the aim of attempting to explain the key causes of economic growth, with endogenous growth theories being examples which attempt to offer an explanation for one of the most important causes, technological progress due to innovation. The prevailing consensus is that, particularly in the long run, due to the diminishing marginal returns on physical capital and labour in an economy, the key to constant growth comes from improvements in the intellectual capital within an economy via innovation. However, although the above graph seems to suggest growth will continue indefinitely, there is suspicion by many that there is not a limitless amount of technological progress to be made and that all the largest steps forward have been made already, meaning that growth will eventually plateau, seemingly harming the credibility of endogenous growth theories.
Endogenous growth can be defined as long run growth at a rate determined by forces internal to the economic system, especially the forces concerning technological progress and innovation (Hewitt, 2010). Endogenous growth theories came about relatively recently as a response to the previous neoclassical models which had concluded that the long run rate of growth depended on some exogenous, unexplained factor. In the case of the Solow model, which presents a production function:
By taking logarithms and differentiating, we arrive at the conclusion that the Growth Rate of GDP = Growth Rate of Total Factor Productivity (TFP) + Growth Rate of Capital x ⅔ + Growth Rate of Labour x ⅓ yet although TFP is the most important reason for economic growth in this model, it remains an exogenous, unexplained factor.
On the other hand, endogenous growth theories such as the Romer or Schumpeterian models seek to explain the reasons behind growth of total factor productivity, thus providing a better understanding of economic growth.
The Romer model distinguishes between ideas and objects and gives the production function:
showing that output per person is dependent on initial stock of knowledge in the economy as well as the growth rate of ideas given by:
where is the productivity in producing ideas. Meanwhile, the Schumpeterian theory is based on his idea of ‘creative destruction’ where innovation creates new products that render the old ones obsolete, and arrives at the conclusion that:
The major difference between exogenous and endogenous models is that diminishing returns to scale of both physical and human capital in exogenous models means that there is no long run growth, but since endogenous models focus on intellectual capital, there is long run growth due to the non-rivalrous nature of ideas. However, both of these models have problems in that they seem to both assume constant and indefinite long run growth, in Romer’s case because of the assumption that productivity in producing ideas is constant and in Schumpeter’s case because of the assumption that growth will be constant if there is a constant proportion of GDP spent on research and development. Neither model seems to take into account the possibility that much of the largest innovations have already been made, and so productivity in making ideas could fall whilst spending the same proportion of GDP on research may not yield the same results.
Although looking at the last 200 years may give the impression that economic growth has always occurred, looking at a larger proportion of human history shows that it is in fact an unusual occurrence.
As the above diagram shows, growth until around the 1750 was practically non-existent, implying that it is possible that the last 250 years or so could in fact be an unusual ‘blip’ in human history rather than a never-ending occurrence (Gordon, 2012). Furthermore, Gordon (2012) splits economic growth into three industrial revolutions; the first lasting from 1750-1830 through inventions such as the steam engine and railroads; the second lasting from 1870-1900 with its main inventions being electricity, the internal combustion engine, running water, indoor plumbing, chemicals, entertainment and more; and finally the third industrial revolution from 1960 to present day – including things like computers, the internet and mobile phones. Of these, the second industrial revolution had by far the largest effects on living standards accounting for much of the growth from around 1890 to 1970 shown on the graph above. It can be argued that many of these innovations were one off and so once their benefits have been realised, future economic growth cannot be gained from these innovations. For example, advances in things like life expectancy and speed of air travel in the last 40 years or so have been minute compared to the extreme advances made previously in the 20th Century.
It is possible that all the largest innovations such as electricity, the internal combustion engine and indoor plumbing have already been made, meaning that future innovations will be increasingly difficult to create as the ‘low-hanging fruit’ disappears. These diminishing returns are largely ignored by endogenous growth models, which assume that maintaining spending levels on ideas will give constant results, or that productivity in producing these ideas are constant. However, this does not mean that the endogenous models are no longer useful, as they still provide a better insight than exogenous models due to their attempt to explain factors behind productivity growth. Nevertheless, their credibility is certainly harmed when considering declining levels and standards of future innovation, and so an adaptation to these models may be needed if they are to remain relevant in the future.
Written by Miheer Sonwalkar
Edited by Omkar Dixit