USA is losing the Malacca strait

On December 19, I published a post discussing the major global powers and the near-future competition between the USA and the implicit China-Russia alliance. I have mentioned the competition for the most important and very narrow straits and channels - Malacca, Panama, and Suez. On December 22, Guardian published an article on the more aggressive protection of the Malacca strait (called the South China Sea in the article) by the US Navy. Psychologically, it is obvious that aggressive behavior (e.g. barking) is a feature of weakness and fear. Stronger dogs bite first and then bark. It seems that the US is losing the strait of Malacca. 

Italy and France have to leave the EU because of negative effects on their real economic growth

 Brexit forces us to think about the future of the EU. We have presented a series of posts analyzing economic growth in selected countries using one invariant - constant annual increment in the real GDP per capita. This invariant defines the inertial part of real economic growth as observed in all large developed economies since the 1950s (no accurate data before).  Statistical analysis demonstrates that this invariant is actually a constant for a given country but varies between the countries. Therefore, it might be used to evaluate the relative performance of a given country.

Figure 1 compares several EU countries and splits the period from 1960 to 2018 into three sub-periods: 1960-1979, 1980-1999, and 2000-2018. Statistically, variations in the annual increment in the GDPpc between these periods are important for the estimates of the linear regression, i.e. the long-term behavior. For example, France and Italy demonstrate a significant decrease in the average increment from around $600 in the first period to $330 in France and $160 in Italy between 2000 and 2018. We have formulated this decay in terms of the gradual loss of economic competitiveness (efficiency) compared to Germany within the EU. This situation is likely fixed and neither Italy nor France is able to get back to the pre-EU level.  The case of the UK, which is also demonstrating lower performance than Germany and the Netherlands, gives a reasonable solution – to leave the EU and fight for the efficiency out of the EU bureaucratic framework which they actually do not control. Portugal and Spain should probably join such a move.  If the EU is a multi-speed union then Italy and Portugal are driving in first gear.

Figure 1 Real GDP per capita (2011 prices) in selected EU countries. Data are obtained from the Maddison Project Database.

Russia and China successfully fight for own piece of the global economic profit. This fight may come to a hot stage

 In our previous posts, we formulated and illustrated the idea that the countries with larger annual increment of the real GDP per capita, GDPpc, are also characterized by the CPI growing faster than the GDP deflator. The most striking examples of such dependence are the USA and Japan. In support of these observations, the most unsuccessful countries with low annual GDPpc increment are characterized by faster growth in the GDP deflator, e.g. Italy.

In this post, we analyze Russia and China within the same framework. Figure 1 compares both countries with Germany for the period between 1995 and 2018. The OECD provides dGDP data for this period and Russia started an independent economic history in 1991. In addition, the drop in real GDP between 1991 and 1998 in Russia was related to the transition from socialism to capitalism. The curves in Figure 1 demonstrate that all three countries were successful in real economic growth since 1995 and can be considered as having “strength” needed to participate in the division of global profit. Obviously, there are several countries fighting for the global/regional economic dominance and the highest benefits in non-equivalent exchange of goods and services, which is called robbery in normal life. Just a few countries have the potential to continue with (nuclear) armed brigandage. In the world of shrinking marginal profit, these countries will likely be the winners in the future Darwinian competition.  

Figure 1. Annual increment of the real GDP per capita in Germany, Russia, and China between 1995 and 2018. The average increments are presented. All three countries belong to the club of successful economies since 1995. 

There is an important signature of a successful economic player – CPI curve above the dGDP one. Figures 2 and 3 present these curves for China and Russia.  Within the limited period since 1993, China has a segment with the dGDP above the CPI curve, but since 2004 the situation is the opposite and the CPI is growing faster. For Russia, the CPI and dGDP were very close before 2004, and then the same pattern as in China and other successful economies is observed. 

Therefore, China and Russia are two countries that definitely joined the club of economies with large enough “strength” to participate in the process of division of global economic profit. The club extension is not welcome by the old club members and we currently observe the fight for dominance. Potentially, it may go to a hot war stage, and nowadays is the best time to check that “gunpowder is dry”. Marx said - “ …100 percent will make it ready to trample on all human laws; 300 percent, and there is not a crime at which it will scruple, nor a risk it will not run, even to the chance of its owner being hanged.”  

Figure 2. CPI and dGDP price growth in China since 1993 (OECD data available)

Figure 3. CPI and dGDP price growth in Russia since 1995 (OECD data available)

 

“ No division can be effected otherwise than in “proportion to strength”, and strength changes with the course of economic development”: Germany

 In this post, we present significant breaks in the linear dependence between the CPI and dGDP (i.e. between two measured time series) in Germany as related to new definitions of inflation. The case of Germany, however, has a very specific meaning – this country is the economic leader of the European Union. In the Annex below, we present an independent opinion on the behavior of economic leaders, including Germany, formulated 105 years ago.

Figure 1 presents 4 panels illustrating the process of the definitional break findings as applied to Germany. Panel a) depicts two inflation curves – for CPI and GDP deflator. One can see that the CPI curve is slightly above the dGDP curve from the mid-1990s. Panel b) presents similar curves, but for cumulative inflation as the running sum of inflation readings. The slightly higher CPI inflation is now producing a significant deviation of the cumulative curves. Pane c) shows the difference between the curves and panel a) and panel b). The difference between the two cumulative curves reveals a break followed by deviation as a linear function of time. Using the slope of the difference, one can calculate the coefficient of the linear correction (1.5) needed to fit the CPI and dGDP curves. Panel d) shows the original CPI curve and the corrected dGDP curve, i.e. the dGDP curve multiplied by a factor of 1.5 since 1997. There is still some deviation between the curves after 2013. It might be a manifestation of a new break. We are going to follow the new deviation and will report on it in the future. The presence of definitional breaks is similar to those observed in different countries. However, timing and circumstances related to the ECB creation win the headquarters in Frankfurt make the case of Germany suspicious. We wrote about the potential benefits of German leadership in previous posts. Here, we are going to support the case.

Figure 2 depicts curves of the real GDP per capita growth in several European countries between 1960 and 1996.  In order to provide a consistent view of the total growth, we normalize all curves to their respective (GDPpc) levels in 1960. Two champions are Spain (ESP) and Portugal (PRT), and this is natural because of the low GDPpc level in 1960 in both countries.  Germany (red line) is close to the bottom together with the Kingdom of the Netherlands (NLD) and the United Kingdom. Figure 3 displays similar curves but for the period between 1997 and 2018. Since 1997, Germany (DEU) is by far the leader of the race. Cumulative GDPpc growth is 1.51 compared to the second place occupied by NLD - 1.42. It is important that the agreement of the ECB was signed in 1997. Instructively, Italy and France are much close to the bottom of the list. The UK is in the middle. As we mentioned in previous posts, the higher is the real GDPpc growth rate the lower is dGDP relative to CPI. Germany, Netherlands, France, and Italy are the best examples.

In Figure 4, I am trying to understand the influence of EU subventions on East European countries. The overall real GDP growth since 1997 is spectacular in Poland, Hungary, and Bulgaria. Their corresponding curves are much above Germany and The Netherlands. One might suggest that the EU financial and other assistance has a positive impact on real economic growth in these countries. However, Serbia demonstrates almost the same growth rate since 1997. It might be an indication that the EU help is not so much effective.

 a)

b)

 c)

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Figure 1. See text for details

 

 

Figure 2. Evolution of GDP per capita normalized to 1960 in selected EU countries between 1960 and 1996.

Figure 3. Evolution of GDP per capita normalized to 1997 in selected EU countries between 1996 and 2018.

 

Figure 4. Evolution of GDP per capita normalized to 1997 in selected EU countries between 1996 and 2018.

 Annex

“A United States of Europe under capitalism is tantamount to an agreement on the partition of colonies. Under capitalism, however, no other basis and no other principle of division are possible except force. A multi-millionaire cannot share the “national income” of a capitalist country with anyone otherwise than “in proportion to the capital invested” (with a bonus thrown in, so that the biggest capital may receive more than its share). Capitalism is private ownership of the means of production, and anarchy in production. To advocate a “just” division of income on such a basis is sheer Proudhonism, stupid philistinism. No division can be effected otherwise than in “proportion to strength”, and strength changes with the course of economic development. Following 1871, the rate of Germany’s accession of strength was three or four times as rapid as that of Britain and France, and of Japan about ten times as rapid as Russia’s. There is and there can be no other way of testing the real might of a capitalist state than by war. War does not contradict the fundamentals of private property —on the contrary, it is a direct and inevitable outcome of those fundamentals. Under capitalism the smooth economic growth of individual enterprises or individual states is impossible. Under capitalism, there are no other means of restoring the periodically disturbed equilibrium than crises in industry and wars in politics.” Lenin V.I., 1915, “On the Slogan for a United States of Europe”.

 

New EU members have no chance to catch up the most developed countries

 In 2005, we published a paper quantitatively describing the transition of the former socialist countries to a new state similar to capitalism.  In 2009, we extended our model and predicted the evolution of real GDP per capita in 27 countries, including two virtual countries: the U.S.S.R and Czechoslovakia. Briefly, despite different social, cultural, ethnical, racial, demographical, religious, and technological histories our model demonstrates general success in the overall prediction between the start point (1989 to 1991) and the year of 2006(7). In all cases, the most accurate prediction is associated with the initial segment of the transition, when socialism was dynamically replaced by capitalism. The initial stage is characterized by the largest changes in the GDP per capita, and thus, provides a wide dynamic range as a crucial condition for accurate modelling. 

At later stages, some exogenous forces, such as economic recession, might disturb the agreement between measured and predicted GDP, and introduce some bias in the estimation of the defining parameters. This later stage, however, is of lower relevance to the transition itself and rather demonstrates the behavior of a regular capitalist economy.

Here, we revisit our old predictions and compare them with actual observations with the real GDP per capita estimates borrowed from the Maddison Project Database. In 2009, we concluded that the transition process has effectively finished in Central and East European countries. Thus, the long-term growth rate of GDP per capita in these countries is limited by the attained level of the GDP per capita, as in developed countries (see this post). Any deviations from the long-term rate can be explained only by inefficient economic performance. In fact, many developed countries are characterized by lower values of an economic trend than that in the U.S. at the same level of GDP per capita. We assume that the future economic growth in the FSC will follow either the potential or current value of the annual GDPpc increment. When no inefficiency is allowed, the best-case scenario of economic growth is realized.

Figure 1 displays Figure 10 from the 2009 paper - the past and future evolution in Hungary and Poland compared to that the U.S. All other FSC have time histories similar to those in Hungary and Poland, but with different initial values and actual slopes. In the current study, all theoretical slopes are equal: A=$370, i.e. annual increment in GDP per capita is $370 (1990 $).

The U.S. theoretical curve with A=$370 is much higher. Before 2008, it had no prominent horizontal or downward segments, as observed in Hungary and Poland. In 2008, the recession moved the US GDPpc curve down and it was below the theoretical curve as Figure 2 shows. In Poland, the stagnation process started in the late 1970s. Hungary is characterized by a shorter period of weak performance. Apparently, the years between 1950 and 1989 are characterized by a lower rate of economic growth with an increasing gap between the FSC and the U.S. The best-case scenario would allow maintaining a constant lag behind the U.S., X. In relative terms, the lag will decrease as a function G_FSC/(X+G_FSC), where G_FSC is the GDP per capita in a given FSC.

Figure 2 compares the predicted and observed GDPpc curves in Hungary. The MPD data (2011 prices) are used instead of the TED. All MPD readings are reduced to 1990$. The drop in the US curve was observed in 2008. The upper panel of Figure 2 shows the 2016 revision with TED data and the lower panel uses the MPD data. There is some discrepancy in the GDP per capita estimates in 2016 and 2020. The observations show that the economic performance in Hungary has been approaching its perfect trajectory with A=$370 (1990$) since 2012. Figure 3 presents the case of Poland, which shows a better performance likely related to the EU financial support. Figure 4 is for Bulgaria.

Overall, our prediction is still valid – the new EU countries lag behind the US and this lag will not be closed any time soon.

  

Figure 1. Upper panel: The evolution of per capita GDP in Hungary compared to that in the U.S. The gap between countries has been increasing since 1950. In the ideal case, when Hungary performs at the theoretical level (A=$370), it will be able to retain the gap. The absolute gap between the U.S. and Hungary can theoretically be constant at the level of $22,000 in the future. Lower panel:  Same as in the upper panel for Poland. The absolute gap between the U.S. and Poland is currently $22,300.

Figure 2. Comparison of predicted and observed GDPpc curves in Hungary. The MPD data (2011 prices) are reduced to 1990$. The drop in the US curve was observed in 2008. The upper panel shows the 2016 revision with TED data and the lower panel uses the MPD data. There is some discrepancy in the GDP per capita estimates in 2016 and 2020. The observations show that the economic performance in Hungary has been approaching its perfect trajectory since 2012.

 

Figure 3. Same as in Figure 2 for Poland

Figure 4. Same as in Figure 2 for Bulgaria

Economic comparison: Ukraine vs Russia. Real GDP per head in Ukraine is still below the 1989 level. Russia doubled the GDP per head

 In 2014, we compared the evolution of real GDP per head in Russia and Ukraine since 1980. The Total Economy Database (TED) of the Conference Board was used. In this post, we revisit our estimates from 2014 with a new dataset – now TED is replaced by the Maddison Project Database (MPD). Three figures below present different sides of the relative evolution. The upper figure shows the absolute GDP per capita values since 1980, and the Russia curve is still much above Ukraine. In 2018, Russia had $24,669 (2011 prices) and Ukraine only $9,813. The growth is absent in Ukraine since 2008 and the level observed in 1989 ($10,082) has to be reached in the future.  The middle (both curves normalized to 1980) and lower (both curves normalized to 1991) figures show that the real GDP per capita in Russia is by a factor of 2.05 larger in 2018 than in 1991 and by a factor of 2.01 compared to 1980. The actual problem is that this lag is forever. 

 

Real GDP is likely not correct as the inflation estimates are weird

 We revisited several times our original post published in 2011 on biased metrology of macroeconomic measurements. New data are needed to validate the original hypothesis or to reject it. It is important to retain in mind that economics as science often fails and gives counterproductive results due to inaccurate or biased measurements of the most basic macroeconomics variables – price inflation, labor force, unemployment, nominal GDP. In one of our previous posts, we focused on the estimates of real GDP in the USA before and after 1979 and here we extend the US case by several other cases. As mentioned before, we have devoted enough efforts to reveal and recover many trivial cases in our book “mecħanomics. Economic as Classical Mechanics”.

Real GDP (see Concepts and Methods of the U.S. NIPA for details) is the difference between nominal GDP and GDP deflator (price index). The latter is not easy to calculate or even evaluate.  In this post, we showed that it is so much a sophisticated problem that before 1980 there was no practical difference between the cumulative inflation values of the CPI and the GDP deflator in the US, as originally was demonstrated in Figure 1 of the 2011 post. (The cumulative inflation, i.e. the cumulative sum of inflation rates, is different from the price index when differently calibrated in the beginning.)

In this post, we are trying to find significant breaks in the linear dependence between the CPI and dGDP (i.e. between two measured time series) as related to new definitions of inflation. It is important that our observation of a linear relationship between CPI and dGDP in the USA is also valid for other studied developed countries. For our model of the linear and lagged relationship between labor force, unemployment, and inflation, such definitional breaks in economic parameters are equivalent to the breaks in the statistically estimated relationship. In other words, the breaks in the general relationship are not related to the change in the economic behavior of the involved parameters. These breaks are fully artificial and induced by major economic agencies (BLS, BEA, etc.) on their eternal way to perfect definitions of economic variables.

Figure 1 presents the case of the USA (here we use the OECD data) : upper panel - CPI and dGDP inflation rates since 1971; middle panel – price change with time relative to 1970 (both variables are normalized to their respective 1970 levels); lower panel – the difference between the curves in the middle panel.  We have changed the reference year for the USA from 1929 to 1970. Effectively, the CPI and dGDP curves in Figure 1 diverge from 1978. As we have already mentioned many times, before 1978 the CPI was used to estimate of the overall price inflation. Since 1978, the GDP deflator has been used. The difference between these two variables cannot be neglected: the cumulative price change between 1978 and 2018 is 1.3 units or 25%. The lower panel of Figure 1 demonstrates that the cumulative CPI and dGDP price change differences is very close to linear dependence. As we reported before, the coefficient of linear dependence is 1.2 for the USA data (BLS and BEA). For the OECD data, the coefficient is 1.26, i.e. another set of definitions is used by the OECD.

Figure 2 presents the same curves as in the middle panel of Figure 1, but the dGDP time-series is multiplied by a factor of 1.26. Now, the fit between the two curves is almost perfect. There is a small deviation from this linear link after 2008. It might be related to the formation of a new link after some change in dGDP definition in 2008. The potential change in the regression coefficient related to the period after 2008 is small and one has to wait for new data to estimate this coefficient statistically. In Figure 3, we present a tentative model with the dGDP additionally (to 1.26) multiplied by 0.8 after 2008. The fit is much better and the total multiplication factor compared to the pre-1978 definition is 1.008, i.e. practically 1. Are we in the pre-1978 definition era again? When analyzing the linear and lagged dependence between labor force, unemployment rate, and the inflation we have to introduce “non-structural” or artificial breaks (structural breaks are equivalent to the change in economic behavior) in 1978 and 2008. 

 

Figure 1. Upper panel: The evolution of the CPI and GDP deflator in the USA since 1970 according to OECD data.  The CPI inflation curve is higher than the GDP inflation one. Middle panel: Cumulative price change according to price indices: CPI and GDP deflator. Lower panel: The difference between curves in the upper (running) and middle (cumulative) panels.

 

Figure 2. The evolution of the cumulative inflation (the sum of annual inflation rates) for the CPI and GDP deflator in the USA since 1970. The dGDP is multiplied by a factor of 1.26.  

 

Figure 3. Same as in Figure 2, but the dGDP after 2008 is additionally multiplied by a factor of 0.8.  In fact, the total multiplication coefficient (1.26*0.8) = 1.0, i.e. the same as before 1978. 

Figure 4 presents the case of the UK. Panel a) repeats the plot published in 2011. We reported the deviation between the CPI and dGDP since 1978 as in the USA. Panel b) presents the same case with the OECD data for the period between 1955 and 2018. One can see a clear kink in the dGDP curve between 1994 and 1996, which is absent in panel a). This is likely a later OECD revision. Interestingly, the dGDP curve is above the CPI one. In the USA, the order is the opposite. The difference between the CPI can be overcome by two corrections: the dGDP is multiplied by a factor of 0.98 since 1978, as shown in panel c), and the kink is corrected by a constant  -0.055 – panel d). As a result, the overall fit since 1955 is excellent and we have to take the break in 1978 into account when assessing our model statistically.

a)

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c) 

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Figure 4. The case of the UK. Described in the text.

Figure 5 presents the case of Austria. The cumulative price change (CPI and dGDP) curves in panel a) demonstrate the start of deviation around 1990. Panel b) shown the running (inflation) and the cumulative difference between the curves in panel a). The pivot point is 1991. We have corrected both time periods – before and after 1991. The pre-1991 period has a very small multiplication factor of 1.005 and the after-1991 period is the best fit with coefficient 1.17 – panel c). The model linking the dGDP inflation with labor characteristics definitely needs a data-driven brake in 1991.

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b) 

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Figure 4. The case of Austria. There is a break in 1991.

 Figure 5 presents the Kingdom of the Netherlands. The CPI curve is above the dGDP one. The relatively good fit between the curves needs three breakpoints – 1982 (coefficient 1.2), 1997 (0.8) (both changes are shown in panel c), and 2009 (2.0)  - panel d).

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Figure 5. The Kingdom of the Netherlands

In Figure 6, we present Japan. The CPI is above the dGDP – panel a). The cumulative difference in panel b) is an almost linear function of time. The multiplication factor between 1974 and 2018 is 1.25, but the CPI is constant after 1996 – panel b). This constant can be fit only with a 0 linear coefficient or a constant added to all dGDP or CPI inflation readings after 1996. In panel d) we added -0.011 to each reading of the CPI inflation since 1997 and obtained a good fit between the CPI and dGDP. We are sure that the Japan Statistics did not add 0.011 to the CPI inflation estimates in order to keep it above 0. It would be a good trick to avoid formal deflation, which is observed in the dGDP since the mid-1990s, but it would be a bad trick for the economic models we have been developing for Japan.

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Figure 6. Japan 

Italy is a perfect case with one constant describing the whole difference between 1970 and 2018. Figure 7 presents the original CPI and dGDP time-series – panel a), the difference – panel b) and the overall fir when the dGDP is corrected by a factor of 0.94. The overall fit is excellent through the studied interval and no breaks are needed in the model. For Italy, the CPI is below the dGDP curve. 

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Figure 7. Italy