vrijdag 15 maart 2013

Innovation and Kondratieff II

Innovation is the true key to a more prosperous world!
   

Kondratieff

In a longer time perspective, western world economy appears to show a sort of returning waves of prosperous economic upswings and deleterious economic down turns. This effect is discovered and described by amongst others Kondratieff [1]. He coupled the economic upswings to major innovation breakthroughs. During the upswing however, somehow the innovative power seems to diminish and only to return in its full potential in the bottom, the winter of the cycle, to start the following cycle.

In the figure below a schematic draft of the last four cycles is presented [5].
 


First K-wave

 The first Kondratieff wave is indicated to be coupled to the rise in steam engines and cotton industry. Well if we plot the number of steam engines used in the USA in a graph with the Kondratieff waves according to the wave patern as suggested by I. Gordon [9], the following image is obtained:


Quite astonishing, the growth in number of steam engines in the USA reached its maximum around 1910, in the middle of the spring of the third Kondratieff wave. The first steam engine was installed around 1776, well before the first kondratieff wave ended. The true rapid growth of steam power emerged beyond 1870, when the second Kondratieff wave was already in its winter period. The extreme and sudden decline of the steam engine from about 1909 was due only to the development of superior alternatives such as the internal combustion engine and the electrical engine. This decline, was a virtual collaps of an entire industry. 

 The collapse came, while the steam engine industry was still in its increasing growth phase and was sudden and severe. Would there have not been any better alternatives the steam engine may have reached saturation around at the earliest in the 1990ies, as is shown in the following image:   


In this figure an S-curve is fitted, with the inflexion point set on 1909, around the year the highest number of steam engines were counted in the USA. Most of these numbers are obtained from old sensus data and are far from being exact. The effects of change of industry are however thus severe, that the inaccuracy in the data is of subordinate nature. 

 What is striking is that the time span of the fitted S-curve from start to saturation easily stretches over all the Kondratieff waves now known to us. 

Second K-wave

 The second Kondratieff wave is indicated to be coupled to the rise of the railway and steel industry. If we plot the total railway mileage in the USA a graph with the Kondratieff waves, the following image emerges:






Although allegedly responsible for the second wave, the greatest expansion of the USA railroad network started around 1880 and occurred only in the winter of the second wave. Furthermore the development of the railroad mileage and the number of steam engines initially developed almost parallel. Like the steam engine, the development of the railroad was strongly impaired by better alternatives, being the internal combustion engine powered road and air transport.  




If an S-curve is fitted on the development of the total milage in the USA, with an inflexion point set at 1895 again the time scale of full the diffusion of the rail roads untill its assumed saturation took from approximately 1830 until aproximately 1950, provided the better alternatives would not have been developed . So the total time span of the diffusion of railroads in the USA is about 120 years, spanning at least two Kondratieff waves.  


 Third K-wave

 The third Kondratieff wave is indicated to be coupled to the rise in the electrical industry and chemistry. If we plot the USA electrical power generation in the Kondratieff wave pattern, the following image can be derived:



Electricity production appears to coincide more with the fourth wave than the third K-wave. Although the first electricity distribution took place in 1882, installed in a power station built by Edison, the biggest growth of electricity production took place in the 1940-70ies. So this technology is more likely to have generated if any the upswing of the fourth Kondratieff wave instead of the third.

If an S-curve is fitted on the electricity production data, the graph below can be generated. From this graph, it appears that electricity is not yet fully diffused throughout the USA. The inflexion point of the fitted S-curve is set to 1988. 





Here again the time span between the first production in 1882 and saturation, estimated to be around 2040, is about 168 years, easily spanning over three K-waves. Remarkably, from 2008 the electricity consumption appears to stabilise or even to shrink.  It appears that yet a better alternative is about to break through and radically change the game. One of the most likely alternatives is solar power [10].
Fourth K-wave

 The fourth Kondratieff wave is indicated to be coupled to the upcoming of automobiles. If we plot the number of licenced motorvehicles in the USA in the Kondratieff waves, the following image emerses:




 ALthough the very first cars were built in the USA around 1895, in the end of the winter of the second K-wave, the biggest growth of the car industry did coincide with the spring and summer of the fourth Kondratieff wave.  

 If an S-curve is fitted on the development of the number of cars, the inflexion point appear to be around 1980. The diffusion of cars throughout the USA is beyond its maximum growth, a full saturation will be reached around 2050.  



Here again the time scale of the diffusion of the technology of internal combustion engine driven road transport only diffuses at a pace slower than the kondratieff waves, it appears to take about 155 years up to full saturation. 

Concluding, undeniably, there are certain upswings and downturns in economy. These are however not so strongly coupled to the upcoming and downturn of innovative technologies as is often believed. The rate of diffusion of most (past) innovative technologies is of a different time scale than that of the Kondratieff cycles. The diffusion of steam engines in the USA up to the full potential is about 133 years, spanning almost three Kondratieff waves, the diffusion of railroads from its introduction in the USA in 1830 to its maximum capacity in 1930 is still 100 years, spanning two Kondratieff waves. The diffusion of road vehicles is from introduction around 1895 until its maximum, which is assumed to be 2050 is 155 years, again almost spanning three Kondratieff waves. Finally, the diffusion of electrical energy is from its start in 1882 till its maximum, likely reached in 2040 a full 168 years. Also spanning at least three Kondratieff waves.

To my opinion, not the innovation itself is the trigger for any economic upswing or downturn, but the valuation of the innovation and with that, the amount of money spend on a certain innovations by investors. Since any innovation appears to follow an S-curve (as long as no better alternative technology shows up), the early projections  of investors are by nature too negative.  Once the inflexion point is passed, the projections of investors are by nature too positive.

 A first very illustrative and recent example of this effect is shown by the investors valuation of Facebook during its IPO. At the time of the public offering, the development of the number of subscribers to Facebook was already past its inflexion point. Linear extrapollation thus showed a far too bright future, and indeed investors were heavily overpaying [11].




Another illustrative example is the heavily underestimated development of the installed photovoltaic cell power production capacity. This because this development at the moment is still several years ahead of its inflexion point. The following figure represents the actually installed PV peak power, together with an S-curve fit and the 2011 and 2012 projections of the IEA, the leading energy research institute:



Facebook investors and highly recognized institutes with seasoned professionals seem to use linear extrapolations to estimate future development of innovations. To my opinion it is this behavior that drives the vast upswings and downturns in economy, not the underlying innovative technology.
Final remarks: The data collected all originate form various USA data sources. It is astonishing how well and how early in time the United States began to collect and publish all kinds of statistical information. Furthermore the USA was through most of the last two centuries the biggest economy on the planet. So not only is the data available from astonishingly early on, it appears to be both accurate enough and numberwise representative enough to sufficiently reflect global economic upswings and downturns of technologies.  

The S-curve fitting of innovation diffusion originates from relative early work of P.F. Verhulst stemming from as early as 1839 when he was describing population growth [12].
literature and sources
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