woensdag 6 november 2013

Should we abolish our patent systems?

Holland, a most remarkable country!

In the Netherlands, in 1869 it was decided by the then residing government to abolish the entire Dutch patent system. The wave of a liberal spirit through Western Europe came to full expression in this courageous act of folly. In that time, patents were thought to delimit the free trade, to counteract innovation and to provide an unfair position to the holder of the patent. The patent system was believed to reduce economic prosperity [1].

Well did it really? Let us study some statistics to find some answers! 

Only in 1910, again a new Dutch patent law was adopted, which entered into force in 1912, 43 years after its abolision. Let us study the GDP per capita of the Netherlands and of its neighboring countries in this "patent absent era" to find some indicators: These GDP per capita data are meticulously collected by Gapminder [2]:

 In 1860, the GDP/cap in the Netherlands was 10% higher that that of Belgium and 20% higher that that of Germany. In 1913, the GDP/cap in Belgium had surpassed that of the Netherlands by 14%, and the German GDP/cap surpassed that of the Netherlands by 29%. In this period, in the Netherlands GDP/cap grew about 47%, whereas it grew 85% in Belgium and 122% in Germany. 

During the Dutch "patent absent era", the Netherlands had missed a tremendous growth in wealth in comparison to it neighbors. From leading in wealth, it became lagging in wealth.  


So those advocating abolishment of the patent system proved wrong, very wrong indeed! 


[1] "Nederland, een Volk van Struikrovers?", F. Gerzon, den Haag, (1986), p.10-25

[2] Gap Minder: http://www.gapminder.org/data/  Data on GDP/cap in PPP US$ 2005: Gross Domestic Product per capita by Purchasing Power Parities (in international dollars, fixed 2005 prices). The inflation and differences in the cost of living between countries has been taken into account.

Average family size in the Netherlands

Average family size in the Netherlands

The average family size has decreased ever since the end of the war. However, it appears that the average family size is now stabilizing at 2,30 persons per home. If we divide the number of inhabitants in the Netherlands by the number of houses in the Netherlands the following graph can be shown. [1,2]

The war has had a serious effect on family sizes. Home construction came to a stand still during the war, whereas much houses were destroyed. Only around 1980 the prewar trend had been caught up again.

In 2012, the calculated average family size actually slightly increased, from 2,3019 people per home in 2011 to 2,3025 in 2012. This increment however is so small, that it does not show on the graph.....


Families in the Netherlands have virtually stopped shrinking, an equilibrium has apparently been reached. This has quite a significant effect on the demand for homes and thus on the price of houses.


[1] Tweehonderd jaar in statistieken in tijdreeksen 1800-1999:  http://www.cbs.nl/NR/rdonlyres/7934A2DE-B87C-4CDF-8BC7-D34F02225620/0/200jaarstattijdreeksen.pdf

[2] 111 jaar statistiek in tijdreeksen 1899-2010:  http://www.cbs.nl/NR/rdonlyres/76A03E00-8D45-498E-9959-9AB7F9FA2DAC/0/2010111jaartijdreeksenpdf.pdf

woensdag 28 augustus 2013

Predicting population growth

In my earlier blog, I've suggested that population growth can be predicted to a certain extend by previous years unemployment figures. In the Netherlands, according to this relative simple model, the population is predicted to decrease next year:

Just to give this simple and rather bold model some credibility, I have collected some data of some other European countries.


According to this model, Italian population is to decline from an unemployment level of 11,5%. Currently Italian unemployment is about 12,1% sufficient to have a negative population growth, similar to the Netherlands.


In Spain, the threshold for a shrinking population appears to be 25% unemployment, which was surpassed in 2011, and indeed last year (2012), the population in Spain shrunk. The number was spot on the (predicted) fitted line.... For 2013 I again expect shrinkage of the number of Spanish inhabitants, since unemployment is currently at 26,3%.


In Greece, a linear model was difficult to fit before 2010, but here a threshold appears to be around an unemployment rate of about 15%. Last two years, indeed, the population in Greece diminished. It is likely that the number of inhabitants of Greece will again diminish in 2013.  

From this late afternoon comparison with other countries, it appears that the prediction of a shrinking Dutch population is not all that bold.....  Most Dutch people have not yet realized how the world, also in our country is changing.

The figures on which the graphs are based, are from the years 1995 onward, for as far as I could retrieve them from the web.

[1]  Spanish Statistical Office: http://www.ine.es/prensa/np788.pdf

[2] Wikipedia, demographics of Spain: http://en.wikipedia.org/wiki/Demographics_of_Spain

[3] Unemployment figures of Spain: http://www.tradingeconomics.com/spain/unemployment-rate

[4] Population growth figures: http://www.gapminder.org/data/

[5] Unemployment figures of Greece: http://www.tradingeconomics.com/greece/unemployment-rate

[6] Demographics of Italy: http://en.wikipedia.org/wiki/Demographics_of_Italy

maandag 26 augustus 2013

Will the population in the Netherlands shrink next year?

Population growth 

The Dutch population growth recently has become strongly correlated to the economic situation of the Netherlands. If we plot for instance the unemployment ratio to the population growth rate of the consequent year starting from the year 2000, the following figure emerges [1,2,4].

The worse the economy is, the lower the growth rate of the population. It is obvious that both migration and birth rates are effected by the economic situation. People tend to move away from downturn economies to more prosperous places. Young families are more likely to have children when they can be afforded, than when unemployment of any of the parents threatens.

From the fitted line model it may be concluded that when the Dutch unemployment surpasses about 8%, the following year a negative growth of the population emerges. Since the unemployment has reached 8,7% in August this year (2013), and since it is still rising, it may be well possible, that in 2014 the total population in the Netherlands will shrink. A shrinking population has not occurred in the Netherlands ever since the year 1848 [2,3].

Predictions of the CBS, the Dutch Statistical Authority are quite different. The CBS expects first shrinkage only after the year 2030.

Let us see what happens next year, I can't wait....


[1]     CBS Figures on population: http://statline.cbs.nl/StatWeb/publication/?VW=T&DM=SLNL&PA=37943ned&LA=NL (the population growth in 2013 is estimated on doubling first half year growth figure)

[2]     111 Jaar statistiek in tijdreeksen, 1899–2010:

[3]  Tweehonderd jaar statistiek in tijdreeksen 1800-1999:  http://www.cbs.nl/NR/rdonlyres/7934A2DE-B87C-4CDF-8BC7-D34F02225620/0/200jaarstattijdreeksen.pdf

[4] Beroepsbevolking; vanaf 1800: http://statline.cbs.nl/StatWeb/publication/?VW=T&DM=SLNL&PA=71882ned&LA=NL

zondag 21 juli 2013

Innovation drivers

Innovation is the true key to a more prosperous world.

What drives innovation? What enhances human ingenuity, creativity and the persistence to change? Can a government stimulate innovation? To my opinion, any governmental or institutional stimulation of innovation as such is simply impossible. People cannot be forced to innovate, on the contrary, innovation is more likely to flourish when true liberty is provided. Yet, some environments are more likely to evolve into innovation hot spots than others. How come?

Boundary conditions

I am convinced that innovation will evolve only by setting the right boundary conditions. Thus a fertile environment for innovation can be created. if such fertile environment is created, innovation will evolve naturally. It will evolve because it is embedded within our nature as human beings. The following ten conditions may help:

1. Respect of property

Respect of ownership and property is the most important boundary value for innovation and the will and spirit of people to create and enhance their life. If property is seized by any authority without repercussion, any successful initiative will suffer the thread of being seized. Dictatorships that do not respect property are the biggest innovation killers. Fighting these regimes enhances innovation!

2. Personal freedoms

freedom of speech, freedom of travel, freedom of interaction, freedom of religion, freedom of trade, freedom of starting a business, freedom of residence.

These freedoms sound very logical, though we should bear in mind that these freedoms are not that obvious. In western societies, these freedoms predominantly find their roots in the implementation of a trias politica. However, in current (also western) societies, I fear that the trias politica is under severe threat. The power of money is slowly corrupting the legislative and administrative powers and is merging with both of them to become one. This effect induces a thread of a new form of dictatorship, a dictatorship with no face, swallowing substantial amounts of global taxpayers money. This effect implies a severe thread to our most valuable asset: liberty.

The freedom of trade is in a shrinking economy at threat too. Governments trying to safe local manufacturers forget that only global competition urges local manufacturers to innovate and stay ahead. Protection makes any protected industry lazy and reluctant to innovate. In industry a healthy Darwinism is essential for a survival of the fittest, wherein those successful innovations win over the inferior ones.
Freedom of travel is essential for innovative ideas to find fertile soil. By traveling, people spread innovations and thereby enhance the diffusion of innovation. By traveling of people certain hot spots can find new brains, hands, harts and minds needed to reach its full potential.

Freedom to start a business is quite obvious. If one is not allowed to incorporate his innovation, well he will not manage to find investors, employees and most importantly he will not find much clients.

Any restrictions in these freedoms will reduce innovation.

3. Good infrastructure

Throughout historic development, innovative ideas were mostly derived from people sharing knowledge. By interchanging ideas, better ideas evolve. Good communication infrastructure will enhance innovative interaction and help interchange ideas and opinions.

In order to distribute both innovative ideas, innovative services and products based on these innovation a well functioning transport infrastructure is essential. A good infrastructure enhances diffusion of innovation and market penetration.

4. Good education

Without the proper knowledge and insights, obtained in early age, innovators can not come to the best innovations. The knowledge of the state of the art, is essential in obtaining insight in choosing directions for the right innovation. Good education is essential for gathering this knowledge and insights.

Good education is a combination of two things, inspired teachers and motivated pupils. The status of the worlds teaching class needs a serious upgrading, good and inspired teachers are essential for an innovative climate.

5. Innovator role models

In order to inspire young innovators, and to motivate young pupils, successful role models play an important role. They show that innovation can lead to success based on personal performance. Role models innovators can be like Zuckerberg, Mittal, O'leary, Rockefeller.

6. Skill/merit based social hierarchy

If innovators in early stage of their life are confronted with a merit based or skill based social hierarchy, they will incorporate a feeling that investing in knowledge and skills pays off. If a social hierarchy is skill based, future garage type innovators will be inspired and hungry for ascending the social ladder.

7. Poverty and the confidence to change

Poverty is a true innovation booster. As long as the poor innovator sees that by putting efforts in innovating and putting his innovation to the market, he can increase his income level and social status, he most certainly will innovate. If however his situation is hopeless for what ever reasons, because of increasing personal debts, because there is no possibility to start innovating because of lack of one or more personal freedoms, than the innovator is lost.

Not at all rich innovators were starting from a students dormitory or a garage. Now some of them are famous innovation icons.

8. Proper rewards for innovators

A good and functioning reward system for innovators, such as a temporary monopoly is essential for innovators to be able to regain a return on their investments. Temporary monopolies on innovations can encompass copyrights, model protection, patent protection and protection against unfair trade. These rights can temporarily block others from copying the profitable ideas without having to bear the development costs.

9. Fair legal enforcement system for temporary monopolies

If any innovation, being a book, a design a product a theater play becomes successful, others may be seduced to start copying the innovation. A good enforcement system is therefor needed to maintain on a temporary basis the rewards there where they should be, with the innovator.

10. Open markets 

For a good scale up of innovations, an open international market is essential. Innovation will hardly enter any closed market economy.

Any regime, country, state or institution setting these boundary conditions well, will automatically empower innovation, for the benefit of the globe.

dinsdag 25 juni 2013

Patents on solar cells and EU tariffs

Now that the EU has decided to put tariffs on solar cells from China, let us have a look at what is happening in the patent field in the world [1]:

In 2012, the number of published patent applications on solar cells in China was an astonishing 1814 applications, whereas the corresponding number in the USA was 268 and the number of published European Patent applications was only 95. Nowadays, in China, about 20 times as much patent applications are filed on solar cells as in the "European Patent Area" (38 members).

Not only did China take over the global production of solar cells, it appears from these numbers, that China also took over the innovative lead in this technology.

In 2005, when hardly any Chinese patent on solar panels was filed, less than 30% of the solar cells originated from China, now this number is about 60%. Since the intellectual property on this topic has even stronger departed from the western world, we can only expect the Chinese portion of the global solar cell production to increase even more in both absolute and relative quantities.

Putting import tariffs on a solar cell technology from a country that is apparently ahead and gaining speed in in this technology and production is in my opinion counterproductive. Counterproductive in the sense that local USA and European manufacturers are no longer forced to innovate and can remain producing with a less competitive manufacturing techniques. Thus, it is directly against the benefit of a globalized competitive world. In my view it is also heavily unfair to the Chinese manufacturers who do contribute to a more green world by innovative and efficient manufacture.

The consumers of Europe pay a heavy prize, they find their alternative energy costs increasing, to the benefit of the traditional energy generating sector, being fossil and nuclear power generation. This decision is thus directly antagonizing the abatement of carbon dioxide production. Not the road to be taken from an environmental perspective.

The European union, with its ill decision on import tariffs is thus poisoning the innovative climate, is disadvantaging their own inhabitants both money wise and health wise and is endangering the environment by unnecessary stimulating the planet endangering greenhouse effects.

Being a fervent proponent of the European integration, the decision to put up a tariff structure can thus be seen as a pitch dark page in Europe's integration history. It is step back in a technology sense that we, on a global level cant afford ourselves.

Those responsible for this decision: shame on you! SHAME ON YOU!!!

This decision is to be reverted as soon as possible, for the benefit of Western manufacturers, Chinese manufacturers, the European citizens and the inhabitants of the entire Globe.

Sources and literature

[1] http://worldwide.espacenet.com/?locale=en_EP,  numbers based on search hits of applications, comprising the combination of words "solar panel"in title and/or abstract.

[2] http://en.wikipedia.org/wiki/Photovoltaics Wikipedia article on Solar Cell manufacture

donderdag 16 mei 2013

Tomorrows banks are todays crowd funding websites

Innovation is the key to a more prosperous world.

A while ago, I coincidently learned about the extremely rapid pace, at which Dutch crowd funded financing is growing. Apparently, in the Netherlands, for the last two years, each year, the total sum of funded financing has increased with an astonishing factor 5 [1].

What impact will this have on traditional investment?

If crowd funding proves to be the better alternative for traditional investing, which it appears it is, we can roughly estimate the future sums invested by traditional investment institutions. Let me give you a short flash of the future based on some not too bold assumptions. First an historic example of a technology finding its superior alternative is presented:

When a technology finds its better alternative; the sudden and rapid death of the steam engine 

As a reminder, this is what happens to a technology that is confronted with a better alternative. In this case the total number of steam engines deployed in the United States [2].

Compared to their "competition", steam engines were bulky in size, slow to get started, and highly inefficient. More reliable, less bulky, quick starting and more efficient electrical engines and internal combustion engines were in the end completely taking over. An industry had been virtually wiped out!

Traditional investing in the Netherlands

From historic data of the Dutch central bank concerning the total assets (balance totals) of Dutch monetary financial institutions and a "best guess" S-curve fit on the data given, the following graph can be obtained [3]:

These figures are a rough indication for the total invested sum in the Netherlands. In 2008 the total assets of Dutch investment institutions started to deviate from the idealised S-curve fit. For that reason, the inflexion point of the S-curve fit is set to be the year 2008. In order to grasp the figures on the ordinate, the highest number thereon reflects 5 trillion Euro (5 x 10^12) , about half the GDP of the USA. This figure is equalling 5000 billion Euro or 5 million times a million Euro. The saturation of investments in the Netherlands based on this fitted curve appear to be around 4,5 trillion Euro.

Crowd funding in the Netherlands

An S-curve can similarly be fitted on the -rather modest number of only three- data points of the total funds raised through this relative new medium. A further assumption for the fitted S-curve is that the total invested crowd funding sum in a saturated state will be the same as the total assets sum of traditional Dutch investing in its saturated state. Since the crowd funded amounts are relative small compared to the total Dutch investment assets, the S-curve is fitted using a logarithmic scale [1]. The result of the S-curve fit is given by the following graph:

In this graph the saturation of the total invested sum is assumed to equal that of traditional investing and lies around 4,5 trillion Euros. As this graph is plotted in a linear scale, the following image emerges:

It becomes clear that it is rather impossible to fit an S-curve on the data in a linear scaled graph. The numbers are, in a relative sense, that small, that they all seem to coincide with the abcis. In this scale, crowd funding becomes noticeable only after the year 2016, when a sum of 10 billion is crowd funded.

The future of investing in the Netherlands

If we now assume traditional investing finds its better alternative in crowd funding and that the total invested sum remains unchanged, such that there exists an virtual "squeezing out" of the old technology by the new technology, the following picture can be deduced. Please note, this is a calculated result, based upon the herein above stated assumptions.

In this picture, the green dotted line represents the future total invested sum of traditional Dutch investing institutions, when a full replacement by crowd funding occurs.

In this model, in 2017 crowd funding will for the first time induce a noticeable decrement of the sum of traditionally invested money, and by the year 2022 crowd funding has possibly completely wiped out traditional investment.

Is crowd funding truly a better alternative to traditional investment?

In many ways I think it is.

Indeed when crowd funding is compared to the internal combustion engine, some striking similarities can be seen. The light weight system, the speed and the efficiency of crowd funding financing is indeed superior to that of traditional investing, like the internal combustion engine was to the steam enigne. When the predicted graph of the traditional investment institutions is compared with the development of the steam engine, well traditional investment may eventually disappear at a similarly rapid and abrupt way as did the steam engine.

My advice to traditional investment institutions, banks and pension funds therefore can only be: get involved in crowd funding soon or else be prepared for harsh times.

To crowd funding initiatives I can only give my deepest respect. Bringing an alternative to a traditional sector that is heavily depending on governemental support is among the most difficult tasks imaginable:

Ladies and Gentlemen, please carry on, time for change will come, you will become tomorrows banks.

Sources and literature:

[1] http://www.douwenkoren.nl/crowdfunding-groeit-in-nederland-harder-dan-in-andere-landen/

[2] Data points from historical USA sensus data.

[3] Data of DNB, http://www.dnb.nl/en/binaries/sn2003m10_tcm47-147401.pdf

vrijdag 15 maart 2013

Innovation and Kondratieff II

Innovation is the true key to a more prosperous world!


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

donderdag 7 maart 2013

Innovation and kondratieff waves

Innovation is the true key to a more prosperous world. It is believed that global economic waves are virtually induced by innovations in a kind of cyclical motion.    


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].


The Kondratieff wave appears to show four seasons: the spring, representing improvement, built up and construction; the summer: representing prosperity and consolidation; the autumn: representing a recession, the occurrence of a plateau or stabilisation phase and the winter representing a depression, a crisis, wherein severe liquidations occur.

Somehow it appears that we find ourselves in the winter of a Kondratieff cycle, which started according to most internet sources in 2000 with the burst of the internet bubble [1,2,3,4]. Some believe it may last until 2020, so some seven more years to come. Older articles predicted that the Kondratieff wave was to reach its winters end at around 2000. Others are more sceptical about the predictive power of the Kondratieff waves and its frequency. According to Rothbarth, the real business cycle is in no sense periodic, but is a continuing, wave-like motion that varies considerably in length and intensity.[7].

The question is, is this model of Kondratieff so sound? Well for the sake of fun, lets dig in some statistical history.

Alcohol consumption in the Netherlands

The first, very interesting and relative reliable historical statistical data over the timespan of most of the Kondratieff waves are figures on the per capita alcohol consumption in the Netherlands. The alcohol consumption is given by the following figure [8,9]:

Clearly a wave pattern can be distinguished. A first major dip in the consumption of alcohol can be seen around the year 1859, a second major dip in the per head consumption can be seen around approximately 1943. With some imagination, we can see three major peaks in the alcohol consumption, the first being around the year 1832, the second around the year 1890, the last, with more uncertainty since the peak, if any, is still in the making, around 1992. Here the peak and dip years are the ball park estimated mid points of the wave maxima and minima respectively.

From the deep and lasting dip around the 30ies and 40ies, it may be assumed that the alcohol consumption and the economy show a positive correlation. This means on average, with economic upswings, alcohol consumptie increases, with downturns the consumption decreases.

In the later Kondratieff models, for example as depicted below, the year 2000 appears to be the demarcation between autumn and winter. We appear to be somewhere half way wintertime and the true depression is only about to commence. This later Kondratieff model is constructed by I. Gordon of the longwave group, a Canadian financial research institution [12].

If we apply the later model to the alcohol consumption figures, the following combined image can be obtained. The datapoints in the blue field are taken as the exact seasonal turning points in the red wave model line:

Here only the last kondratieff wave seems to coincide with the Dutch alcohol consumption pretty well. With a little fantasy, the first wave somehow coincides somewhat with the consumption figures, though the second and third wave are not representing the historically collected statistical consumption figures.

Apparently, the predictive power of the kondratieff wave for alcohol consumption in the Netherlands is rather poor... 

(Un)employment in the Netherlands

Another very well documented figure is found in the unemployment statistics of the Netherlands. These figures are very likely to be directly coupled to the economic situation in the Netherlands. Since unemployment is supposedly inversely correlated to the economic upswing, the inverse of the unemployment is taken. This is the ratio between the total work force in the Netherlands and the number of unemployed people. This figure, a measurement for the employment varies between a number of about more than 120 and about less than 6 times as much people in the work force as the number of unemployed people. A high value of this indicator thus represents an economic high, whereas a low number represents an economic recession or even depression. These figures do show some wave like behaviour as well. If the Kondratieff low's and high's are inserted, the following combined figure can be obtained [11]:

Well, from this figure, it becomes clear that Kondratieff's model does not apply well to the Dutch (un)employment figures. It is likely, that in the Kondratieff spring and summer the employment should go up, in autumn and especially in winter employment would plummet. In the winter of the fourth wave (i.e. now), indeed employment is rapidly decreasing. For the rest, the Kondratieff  waves do not coincide well with the economic waves as represented by the employment figures.

Silver price in the Netherlands

Another figure to test the Kondratieff's theory is the -again very well documented- historical silver price development. In this figure, the silver price is expressed in guldens, a nowadays extinct currency, though over more than two centuries, the Euro represents only about eleven years. Thus, it makes more sense to recalculate the last eleven years to the gulden than to recalculate 200 years back in the history of the silver price to Euro. In the currency recalculation, a rate of exchange of 2,2 gulden per euro was used.

Since silver has actually been the material, our currency was made of until 1969 the long term development of the silver price was only due to debasement of the gulden, being a silver coin. Up to 1800 it contained 9,61 gram pure silver, from then until 1839 it contained 9,45 gram pure silver, from then until 1919 it contained 7,2 gram of silver, from then untill 1969 it contained only 4,68 gram of silver.  Hereafter, the silver price was decoupled from the gulden, being a mere nickel coin [14].

From the figure above, it can be concluded, that the silver price in the Netherlands does not coincide with the Kondratieff waves. Only the Kondratieff winter we are supposedly in at the moment, represents a strong increment in silver price.

Consequently, the three above statistically sound economic indicators from the Netherlands do not follow the Kondratieff waves at all. Is the Kondratieff theory wrong, well from these few statistical indicators, that conclusion appear to be too strong. The figures above do indicate however, that the Kondratieff model is not that sound as many do make believe....

[1] Essay A. Spits (2002),  http://libertarian.nl/wp/2002/09/de-kondratiev-cyclus/

[2] Essay A. Spits (2008) http://libertarian.nl/wp/2008/12/kondratiev-winter/

[3] Interview D. van den Brink, J. kooistra (06-01-2012)

[4] http://de.wikipedia.org/wiki/Kondratjew-Zyklus

[5] http://nl.wikipedia.org/wiki/Kondratieff-golf

[6] http://faculty.washington.edu/modelski/IPEKWAVE.html

[7] Article by M.N. Rothbart  http://www.lewrockwell.com/rothbard/rothbard44.html

[8] Tweehonderd jaar statistiek in tijdreeksen 1800–1999

[9] Factsheet Alcoholconsumptie:

[10]  D. Lounsbury, Kondratiev Wave Theory Deflation and the Greater Depression http://www.deflationeconomy.com/kondratiev-wave.html

[11] Unemployment figures CBS:

[13] J. Luiten van Zanden e.a., The prices of the most important consumer goods, and indices of wages and the cost of living in the western part of the Netherlands, 1450-1800 http://www.iisg.nl/hpw/data.php#netherlands

donderdag 24 januari 2013

global number of motor vehicles

Innovation is the key to a more prosperous world!

As explained before, most growth of innovation can be mathematically captured by a relative straight forward growth curve. Mostly this growth curve can be properly modelled with an S-curve [1]. Let us now for the sake of fun have a look at the global development of the number of motor vehicles.  The numbers originate from a series of sources [4-12] and the fitted curve is a three parameter S-curve [2].

With fitting the S-curve, two quite bold assumptions were made:

The first assumption is that the final global car-saturation level is assumed to be equal to the 2010 car-penetration level of the USA. This level is about 808 cars per 1000 inhabitants [6].

The second assumptions is that in 2050, the global population is assumed to reach and stabilize at 10 bilion [10 x 10^9] inhabitants.

These assumptions are leading to a global saturation level of about 8.08 billion motor vehicles.

That the world is striving for a wealth comparable with that of the USA is astonishingly showed in the numerous presentations of Hans Rosling [3]. The assumption that in that line of wealth development, the world is striving to a similar penetration level of cars appears not to be too far fetched. Following these assumptions, the global number of motor vehicles will resemble the S-curve presented in the following figure:

In this figure, besides the statistical data available from numerous sources [4-12], two forecasts are given as well. The 2030 forecast in this figure originates from Dargay e.a. [5] and corresponds pretty well with the fitted S-curve. The 2050 forecast in this figure originates from the 2011 OECD international transport forum [4] and appears to be on the conservative side, when compared to the S-curve forecast.

From the assumptions made, we are going to have about eight times as much motor vehicles on the planet as we have now.

Further the number of vehicles on the planet is still growing ever faster, until about 2050, where the fitted curve changes from concave to convex.

Interestingly, these cars are in the future likely not to be all fossil fuel powered, because in fossil fuel production we are about to reach peak production. In the following figure is the yearly produced mineral oil is presented. It can be seen that the production is, though still increasing, is in its convex phase, past its inflexion point [16]. The data from 2012 and 2013 are the forecasts given by the IAE [17]. With a slowing growth of mineral oil production and an increasing growth of the number of vehicles, soon there is simply not enough mineral oil to feed all these vehicles.

So here there is ample space for innovation! More efficient vehicles and alternative energy sources, I cant wait to see them coming!

[1] http://www.slideshare.net/HendrikdeLange/s-curve-presentation-wwwcrowdfundersnl 

[2] The Rise and Fall of Infrastructures, A. Grübler (1990) http://www.iiasa.ac.at/Admin/PUB/Documents/XB-90-704.pdf

[3] http://www.ted.com/talks/view/lang/en//id/1101

[4] http://www.huffingtonpost.ca/2011/08/23/car-population_n_934291.html

[5] http://www.xesc.cat/pashmina/attachments/Imp_Vehicles_per_capita_2030.pdf

[6] http://en.wikipedia.org/wiki/List_of_countries_by_vehicles_per_capita

[7]  http://oica.net/category/production-statistics/

[8]  http://www.nationmaster.com/graph/tra_mot_veh_pro-transportation-motor-vehicle-production&date=2000-01-01

[9]  http://hypertextbook.com/facts/2001/MarinaStasenko.shtml

[10]  http://www.huffingtonpost.ca/2011/08/23/car-population_n_934291.html

[11]  http://www.worldometers.info/cars/

[12]  http://www.car-history.org/the_begining_of_19th_century_in_car_history/

[13]  http://people.hofstra.edu/geotrans/eng/ch6en/conc6en/ch6c1en.html

[14]  http://cta.ornl.gov/data/tedb30/Edition30_Full_Doc.pdf

[15] Analysis  of   Logistic  Growth  Models, A.Tsoularis, Res. Lett. Inf. Math. Sci,  (2001) 2,  23-46

[16] http://www.bp.com/sectionbodycopy.do?categoryId=7500&contentId=7068481

[17] http://www.iea.org/Textbase/npsum/weo2012sum.pdf 

maandag 14 januari 2013


Wie de toekomst wil lezen moet in het verleden bladeren...

Uit het dagblad "de Tijd" 1-1-1894:
De waarde der perceelen, waarop naar verhouding hypotheek werd verstrekt, hield men zoo lang mogelijk hoog, doch eindelijk moest de waarheid beslissen, de natuurlijke waard werd weder besteed, en het tekort was: verlies. Alzoo ging het algemeen vermogen op tweederlei wijze terug, èn dat van den grondeigenaar èn dat van den hypotheekgever. Niemand kan dat weerhouden. Komen er tijden, dat de ondernemingsgeest weder levendiger wordt, dan zal 't tegenovergestelde van het tegenwoordige plaatsvinden, maar deskundigen, die deze geschiedenis met belangstelling medeleven, zullen steeds weten te onderscheiden wat de werkelijke waarde is en wat men besteedt.

Zal het nu anders zijn? Nee, maar er gloort licht aan de horizon!

Met weinig fantasie is er een griezelige gelijkenis te herkennen in een algemene theorie die bubbles beschrijft en de historische ontwikkeling van de gemiddelde huizenprijs in Nederland. Deze theorie kan worden weergegeven met een algemeen diagram. Dit diagram en de onderliggende theorie is in 2008 opgesteld door J.-P. Rodrigue [1]:

Een bubble-scenario vertoont volgens deze theorie een stille fase, een bewustwordingsfase met een "bear trap", een manie-fase met een absolute top en een leegloop-fase met een "bull trap". 

De ontwikkeling van de gemiddelde huizenprijs wordt weergegeven door [2,3,4]:

In dit diagram zijn een bewustwordingsfase met een "bear trap" in het begin van de jaren 80 te herkennen. Vervolgens is een manie-fase te onderscheiden met een top in 2007, en vervolgens een leegloop-fase met een "bull trap" in 2009. 

Zou het scenario van Rodrigue op de huizenprijs worden toegepast, dan zou het toekomstbeeld er ongeveer als volgt kunnen uitzien: 

Een terugval van de gemiddelde huizenprijs tot circa 30 000 euro, waarbij de gemiddelde huizenprijs met ruim 80% daalt. Het dieptepunt ligt in dat geval ergens voorbij het jaar 2020. 

Is dat een reële inschatting, een daling van ruim 80%? Als de huizenprijsontwikkeling in de jaren 20 tot medio jaren 40 in detail wordt weergegeven, ontstaat het volgende beeld [4]: 

Er vond van 1930 tot 1936 een afname van de gemiddelde huizenprijs plaats van meer dan 10 k€ tot 2 k€, ofwel een daling van 80%. pas in 1944 kwam de prijs weer op het niveau van de top van 1930. Met andere woorden, een daling van de gemiddelde huizenprijs van 80% is mogelijk, sterker nog een dergelijke daling heeft zich in de twintigste eeuw al eens voorgedaan. 

In de aanloop naar de piek in 1930 was er weliswaar sprake geweest van een gestegen huizenprijs, maar deze bedroeg slechts rond de 50% ten opzichte van de gemiddelde prijs tussen 1922 en 1928. Dit lijkt in geen geval een bubble, zoals Rodrigue hem beschrijft. Tot 2007 heeft zich daarentegen een onafgebroken stijging van de huizenprijs voorgedaan van gemiddeld 60 k€ in 1983 tot gemiddeld 250 k€ in 2007, ofwel een stijging van ruim 300%. De recente stijging is, in relatieve zin, dus zes keer zo groot als de stijging aan de vooravond van de laatste grote depressie uit de jaren 30.

Is er iets aan te doen om dit scenario af te wenden? 

Ja, door grof geschut in te zetten. Dit kan door drastische belastingverlagingen, wettelijke verlaging van de hypotheekrente tot bijvoorbeeld Euribor of een drastische verruiming van de hypotheekrente-aftrek. Ook een verdere verruiming van de maximum toelaatbare schuld van de koper zou een mogelijkheid kunnen zijn. Verder zouden centrale banken hypotheekportefeuilles van banken kunnen opkopen. Al deze maatregelen hebben een inflatoir karakter en geven weliswaar een uitstel van de leegloop-fase, maar ook een sterke vergroting van de (staats)schuld. Juist een ongeremde verruiming van de (hypotheek)schulden heeft deze bubble veroorzaakt. Het vergroten van de schuld zal dus het probleem slechts tijdelijk opschorten, zeker niet oplossen, eerder nog versterken.  

Thans heeft ons landelijk bestuur om begrijpelijke redenen een andere weg gekozen:
De hypotheekrenteaftrek wordt beperkt en er wordt voor deze aftrek een aflossing binnen 30 jaar vereist. Daarnaast wordt de belastingdruk alleen maar verhoogd en lijken de salarissen te gaan dalen. Ook wordt de financieringsruimte verlaagd naar maximaal 4 maal het brutto jaarsalaris, terwijl eerder tot 6,5 maal het brutto jaarsalaris kon worden gefinancierd. Als laatste zal de financiering van 106% van de verkoopprijs verder worden verkrapt tot onder de 100%. Dit alles verlaagt de financieringsruimte van de koper en heeft een deflatoir karakter. 

Een bijkomend effect, wat deze ontwikkeling nog versterkt is een oplopende werkloosheid. Ook deze stijging heeft een negatief effect op de koopkracht van de Nederlander en verkleind de collectieve financieringsruimte. 

Er blijkt een sterke correlatie te bestaan tussen een dalende huizenprijs en een oplopende werkloosheid. Deze twee effecten lijken elkaar wederzijds te versterken. Tussen 1930 en 1933 daalde de huizenprijs met 60% en steeg de werkloosheid van 4,9% naar 16,9%; meer dan een factor 3. Tussen 1978 en 1982 daalde de huizenprijs met 40% en steeg de werkloosheid van 4,6% naar 10,7%; meer dan een factor twee. Beide stijgingen van de werkloosheid zijn daarnaast de twee sterkste stijgingen in de laatste 200 jaar [5].

Een daling van de huizenprijs van 80% zoals in het bubble-scenario van Rodrigue zou dus gepaard kunnen gaan met een stijging van de werkloosheid met een factor vier. Dit betekent dat het werkloosheidspercentage tot 25% zou kunnen stijgen. Een regelrechte ramp, die in Spanje en Griekenland al werkelijkheid is geworden.

Een ander aspect dat effect op de huizenprijs heeft is de bevolkingsgroei en de daarmee samenhangende toenemende vraag. Ons gevoel zegt dat de prijs wordt gevormd door vraag en aanbod... Voor de prijs van huizen lijkt dit echter niet het geval. De prijs wordt hier thans veeleer gevormd door de financieringsruimte van de koper enerzijds en de bereidheid van de verkoper om verlies te nemen anderzijds.  De financieringsruimte van de koper is al aan het afnemen, de bereidheid van de verkoper om verlies te nemen zal met de tijd gaan stijgen. De groei van de bevolking in Nederland zit bovendien niet in een groeiende hoeveelheid starters, maar in een groeiende hoeveelheid senioren [6]. 

Dat een sterke vraag alleen is niet genoeg is voor een stijging van de huizenprijs, blijkt voorts uit de wegblijvende grote stijging van de huizenprijs aan het eind van de jaren 40 en gedurende de jaren 50.  Er heerste een knellende woningnood, met een veel grotere vraag en een veel geringer aanbod dan nu. Toch gingen toen de prijzen gingen niet door het dak. Er was destijds voor kopers onvoldoende financiering te krijgen.  

Met andere woorden het zoet van de lichtzinnig vergrote financieringsruimte en toegang tot makkelijke kredieten van de periode tussen 1980 en 2010 en de daarmee gepaard gaande inflatie maakt plaats voor het zuur van een krimpende financieringsruimte en de daarmee gepaard gaande deflatie. Het gevolg is dalende huizenprijzen, toenemende restschulden,  oplopende werkloosheid en versterkte persoonlijke gevoelens van falen, mislukken en depressiviteit. Deze laatste gevoelens worden door Rodrigue passend gevangen in de termen "fear", "capitulation" en "dispair". 

In mijn ogen is dit alles de verwijtbare schuld van een generatie politici en bankiers die in de jaren 80 het roer overnam van een generatie die nog echt schrale tijden had gekend. De solvabiliteit van banken werd verkleind, de kredietkranen werden opengedraaid. Alsof ons collectieve geheugen niet verder reikt dan ongeveer 60 jaar, zien wij ons hierdoor overeenkomstig onze grootouders thans opnieuw met een drastische crisis geconfronteerd. Een crisis die zich nog aan het ontvouwen is en waarop nauwelijks een mens een antwoord lijkt te hebben. 

Dit alles terwijl al in 1894 de oplossing lijkt te zijn aangereikt: verlies nemen en ondernemingsgeest tonen. 

In dat licht bezien, is innovatie het juiste antwoord op een dreigende depressie. Innovatie in plaats van inflatie, innovatie in plaats van deflatie. De wereld heeft het geluk dat er een hele grote innovatiegolf in razend tempo op ons af komt. Deze innovatiegolf is er één van een complete omwenteling van fossiele energieopwekking naar fotovoltaïsche energieopwekking [7,8,9]. 

Daadkrachtige leiders tonen lef door niet langer geld te pompen in het overnemen van kredieten van banken. Daadkrachtige leiders tonen lef door niet langer de huizenkoper zijn financieringsruimte af te pakken. Daadkrachtige leiders tonen lef door massaal in te zetten op het investeren in nieuwe energieopwekking en overige innovatieve technologie. Hiervoor is een ondernemingsgeest nodig. Een verdere welvaartssprong die ondernemingsgeest van onze leiders vraagt, is die van het uitbannen van het Europese verbod op het genetisch ontwerpen van hoogproductieve voedselgewassen. Beide innovatieve technologieën genereren nieuwe banen en creëren daarmee welvaart. Beide technologieën hebben bovendien een positief effect op het milieu en verkleinen de uitstoot van broeikasgassen. Deze technologieën vervullen bovendien de belangrijkste basisbehoeftes van de mens: energie en eten. 

Leiders van Europa, toont ondernemingsgeest!  

Bronnen en literatuur

[2] Gegevens van het CBS huizenprijs (teruggerekend uit geïndexeerde gegevens)

[3] Gegevens van de NVM huizenprijs

[4] Deze gemiddelden zijn gegenereerd aan de hand van veilinggegevens en advertenties uit edities van de volgende kranten in de jaren 1922-1944: de Tijd, het Algemeen Handelsblad, de Nieuw Rotterdamse Courant, het Nieuws van den Dag en de Standaard. De jaarlijks gemiddelde prijzen hebben als basis telkens ten minste 50 individuele gegevens. Van de jaren 1945 en 1946 zijn niet genoeg gegevens gevonden om een robuust gemiddelde te genereren. Deze kranten zijn digitaal beschikbaar via de Koninklijke Bibliotheek: http://kranten.kb.nl/

[5] gegevens CBS werkloosheid: 

[6] gegevens CBS bevolkingsopbouw: 

[9] blog: We will innovate our way out of recession