Illustration of falling economic growth in developed countries

In this post, we continue analysis of GDP per capita in developed countries and BRIC. It was shown in two previous posts that the evolution of real GDP per capita is rather linear (not exponential) since 1960 and in many cases the growth rate is much lower than its linear potential (so called inertial growth). Extended analsyis was presented in our papers and we would like here just to stress the fact that many developed countiries demonstarte poor performance.

 

Fig. 1. Austria: annual increment of real GDP per capita (upper panel) and the corresponding rate of growth (lower). On average, the annual increment between 1960 and 2015 is $340.  The growth rate has clear negative trend from 1960 to 2015. The current growth rate fluctuates around 1.5% per year.


 

Fig. 2. Same as in Fig. 1 for Belgium. On average, the annual increment between 1960 and 2015 is $326

 

Fig. 2. Same as in Fig. 1 for Denmark. On average, the annual increment between 1960 and 2015 is $282.



 

Fig. 4. Same as in Fig. 1 for Ireland. On average, the annual increment between 1960 and 2015 is $357. There was a period of extremely high growth rate, which ended with a tremendous fall completely compensating the years of growth.

 
Fig. 5. Same as in Fig. 1 for Netherlands. On average, the annual increment between 1960 and 2015 is $304
 

Fig. 6. Same as in Fig. 1 for Norway. On average, the annual increment between 1960 and 2015 is $363

 
Fig. 7. Same as in Fig. 1 for Portugal. On average, the annual increment between 1960 and 2015 is $191

 
Fig. 8. Same as in Fig. 1 for Sweden. On average, the annual increment between 1960 and 2015 is $313

 
Fig. 9. Same as in Fig. 1 for Canada. On average, the annual increment between 1960 and 2015 is $323

 

Fig. 10. Same as in Fig. 1 for Australia. On average, the annual increment between 1960 and 2015 is $338

 

Fig. 11. Same as in Fig. 1 for New Zealand. On average, the annual increment between 1960 and 2015 is $203

 
Fig. 12. Same as in Fig. 1 for Japan. On average, the annual increment between 1960 and 2015 is $345

Decaying economic growth in EU as an economic argument for Brexit

In our previous post, we demonstrated the fall in the rate of economic growth observed in the USA since 1960. Overall, there exists a strong negative trend expressing the fundamental property of economic growth – constant annual increment. Explained in simple words, an economy goes up with steps on constant height, like stairs. This was an example of benign growth, however: the rate of growth follows theoretical predictions. For Europe, however, everything is much worse. Some of the biggest economies demonstrate an accelerated decay.

In the past, we published a number of papers [1, 2, 3] and a book on the evolution of real GDP per capita and explained what does mean inertial economic growth, i.e. the growth with constant steps in real GDP per capita. We have proven that developed economies grow with a constant step, not at a constant rate. Theoretically, the rate of economic growth has to be inversely proportional to the attained level of GDP per capita. Here, we use the estimates of real GDP per capita as listed in the Total Economy Database managed by the Conference Board.

Two figures below update our previous results obtained for Germany, France, Italy, Switzerland, and the UK. Four countries (France, Italy, Spain, and Switzerland) demonstrate extremely poor performance during the past decades. Germany is on par with theoretical predictions and the UK is slightly over the predicted growth rate but still on the negative trends since 1960. The EU is under severe stress in the years to come since the future of economic growth is likely dark. Germany follows its cruise speed and unlikely to spill economic growth over the other biggest economies.

It might be good time for the UK to think about the traction forces associated with the clear features of economic stagnation in EU.

Fig. 1. Evolution of annual increment of GDP per capita, i.e. the difference of the current GDP per capita and that one year ago.

Fig. 2. The rate of growth of the real GDP per capita.

On the decaying rate of economic growth in the USA

We have published a few papers [1, 2, 3] and a book on the evolution of real GDP per capita. The message is very simple – economies grow with a constant step, not a constant rate. Therefore, the rate of economic growth is inversely proportional to the attained level of GDP per capita. Three figures below just update our previous results obtained for the USA using new estimates for the past three years. How dare economists confuse people and authorities with fairy tales that the rate of economic growth will return to that observed in the 1960s. The average rate of 3% per year will never happen again, short term excursions are possible, although. In the long run, the rate of growth will fall from the current 1.6% to 1% per year in 2035.

Fig. 1. Evolution of annual increment of GDP per capita, i.e. the difference of the current GDP per capita and that one year ago.

Fig. 2. Annual increment of the GDP per capita as a function of real GDP per capita.

 

Fig. 3. The rate of growth of the real GDP per capita. Currently, it is about 1.6% per year and will be above 1% another 20 years.

Modeling economic success of Poland and failure in Russia and Ukraine. The 2015 model revision

In 2005, I developed and presented at the Fourth Annual EEFS Conference (Faculty of Economics, University of Coimbra, Portugal 19-22 May 2005) a paper “Modelling the transition from a socialist to capitalist economic system” (Slide Share). An extended and updated version was published in the JAES in 2009.  

My model predicts the measured evolution of real GDP per capita and is based on two fundamental physical laws - the decay of socialist system is similar to radioactive decay and the growth of capitalist system is similar to the process of exponential saturation. The predictive power of the model was extremely high even for the realm of physics and accurately described the transition from socialist to capitalist economic system from 1989 (East Europe) and 1991 (Former Soviet Union) to 2003-2007. Ukraine was an excellent example of the model success. Figure 1 shows the observed and predicted curves with the extension to data available in 2016 (we use the Total Economy database from the Conference Board as data source). Two curves are very close between 1991 and 2006.  In 2007, a slight deviation from the predicted curve starts, which then developed in a catastrophic fall in GDP to the level of 0.802 relative to 1991. Essentially, the level of GDP per capita in Ukraine now resides in the earlier 1970s, i.e. half a century in the past.  The predicted curve implies that the rate of growth had to be 3.65% per year (as observed from 1995) and thus had to be in 2015 at 1.84 (relative to 1991).  Missed opportunity.

Russia (Figure 2) presents an intermediate case with a healthy evolution before 2008, recession in 2009-2010, quick recovery and then stagnation at the level of 1.3 relative to 1991 instead of permanent growth at a rate of 3.5% per year. It has to be at 1.8 in 2015. 

Poland is likely the best performer between the former socialist countries. Poland fully uses its growth potential –  real GDP per capita grows at a rate of 3% per year since 1991. Our model cannot predict total (Ukraine) or partial (Russia) economic failures, which are likely in tight connection with national and international political turmoil, but our model accurately predicts the evolution of GDP per capita when growth potential is used in full. Poland has been chasing developed countries and it is the best example for Ukraine and Russia (and for other former socialist countries), which are hardly to be able to return to the full growth potential any time soon. The gap between them and developed countries rises at a threatening rate. 

Figure 1. Comparison of the observed and predicted evolution of real GDP per capita in Ukraine.

Figure 2. Comparison of the observed and predicted evolution of real GDP per capita in Russia.

 Figure 3. Comparison of the observed and predicted evolution of real GDP per capita in Poland.  The transition started in 1989.

EU, Syria, migrants and Russia

There are some speculations on the effect of  the Russian campaign in Syria on migration in EU.
The EU statistics gives actual numbers to illustrate this effect  - Russia has helped to reduce the monthly rate  of first time asylum applicants.

How universal is the law of income distribution? Cross country comparison (post #777)

This paper could be absolutely amazing  for physicists. It shows that income distribution in four (English Speaking) countries follows a universal law. Incomes are driven by only one(!) external variable - real GDP per capita. All differences in income distribution are defined by the gap in GDP: Canada, New Zealand and the UK exactly follow steps of the USA with a time delay of 15 to 25 years! This is definitely a fundamental result for physics of income evolution as described by our model in the previous post.  

Luckily, this is post #777 in this blog. 

How universal is the law of income distribution? Cross country comparison

Ivan O. Kitov  and Oleg I. Kitov (link to full text on arxiv.org via IDEAS)

The evolution of personal income distribution (PID) in four countries: Canada, New Zealand, the UK, and the USA follows a unique trajectory. We have revealed precise match in the shape of two age-dependent features of the PID: mean income and the portion of people with the highest incomes (2 to 5% of the working age population). Because of the U.S. economic superiority, as expressed by real GDP per head, the curves of mean income and the portion of rich people currently observed in three chasing countries one-to-one reproduce the curves measured in the USA 15 to 25 years before. This result of cross country comparison implies that the driving force behind the PID evolution is the same in four studied countries. Our parsimonious microeconomic model, which links the change in PID only with one exogenous parameter - real GDP per capita, accurately predicts all studied features for the U.S. This study proves that our quantitative model, based on one first-order differential equation, is universal. For example, new observations in Canada, New Zealand, and the UK confirm our previous finding that the age of maximum mean income is defined by the root-square dependence on real GDP per capita.

Gender income disparity in the USA: analysis and dynamic modelling

We have published principal  results of this study as a working paper on arxiv.org. Our model provides an accurate quantiative description of how the difference between men and women evolves since 1962.

Gender income disparity in the USA: analysis and dynamic modelling

Ivan O. Kitov  and Oleg I. Kitov 
(link to full text on arxiv.org via IDEAS)

We analyze and develop a quantitative model describing the evolution of personal income distribution, PID, for males and females in the U.S. between 1930 and 2014. The overall microeconomic model, which we introduced ten years ago, accurately predicts the change in mean income as a function of age as well as the dependence on age of the portion of people distributed according to the Pareto law. As a result, we have precisely described the change in Gini ratio since the start of income measurements in 1947. The overall population consists of two genders, however, which have different income distributions. The difference between incomes earned by male and female population has been experiencing dramatic changes over time. Here, we model the internal dynamics of men and women PIDs separately and then describe their relative contribution to the overall PID. Our original model is refined to match all principal gender-dependent observations. We found that women in the U.S. are deprived of higher job positions. This is the cause of the long term income inequality between males and females in the U.S. It is unjust to women and has a negative effect on real economic growth. Women have been catching up since the 1960s and that improves the performance of the U.S. economy. It will take decades, however, to full income equality between genders. There are no new defining parameters included in the model except the critical age, when people start to lose their incomes, was split into two critical ages for low-middle incomes and the highest incomes, which obey a power law distribution. Such an extension becomes necessary in order to match the observation that the female population in the earlier 1960s was practically not represented in the highest incomes.