Remote monitoring of weak aftershock activity with waveform cross correlation: the case of the DPRK September 9, 2016 underground test

Full text is available on arxiv.org - https://arxiv.org/abs/1611.03055


The method of waveform cross correlation (WCC) allows remote monitoring of weak seismic activity induced by underground tests. This type of monitoring is considered as a principal task of on-site inspection under the Comprehensive nuclear-test-ban treaty. On September 11, 2016, a seismic event with body wave magnitude 2.1 was found in automatic processing near the epicenter of the underground explosion conducted by the DPRK on September 9, 2016. This event occurred approximately two days after the test. Using the WCC method, two array stations of the International Monitoring System (IMS), USRK and KSRS, detected Pn-wave arrivals, which were associated with a unique event. Standard automatic processing at the International Data Centre (IDC) did not create an event hypothesis, but in the following interactive processing based on WCC detections, an IDC analyst was able to create a two-station event . Location and other characteristics of this small seismic source indicate that it is likely an aftershock of the preceding explosion. Building on the success of automatic detection and phase association, we carried out an extended analysis, which included later phases and closest non-IMS stations. The final cross correlation solution uses four stations, including MDJ (China) and SEHB (Republic of Korea), with the epicenter approximately 2 km to north-west from the epicenter of the Sept. 9 test. We also located the aftershock epicenter by standard IDC program LocSAT using the arrival times obtained by cross correlation. The distance between the DPRK and LocSAT aftershock epicenters is 25.5 km, i.e. by an order of magnitude larger than that obtained by the WCC relative location method.


Destructing effect of modern western democracy

Currently, we observe the ultimate effect of western  democracy, when politicians are allowed to compete for political power on a free market with any set of PR tools used against voters. There is no problem, which is not touched by politician  if it can give extra votes. That makes each and every voter to decide which side s/he is thousands of times. This process effectively destructs the raw flesh of society - every person is disjointed from all others by attitude to one or many problems.  The society looses the universal positive perspectives of  future -  it is atomized to the level when only negative reaction matters, like protests or flesh mobs. Democracy is not about common values any more - its is about my own values.

I guess that western democracy has come to dead end. There is no possibility to split people in smaller pieces. And any concept  joining  people will lose on the free electoral  market before the society destruction will come to the level  historical examples like in Italy, Spain, and Germany. In western countries, people are so disordered and confused that many of them trust even Russian propaganda. 


The worthless efforts of the Board of Governors of the Federal Reserve System and investment opportunities

Four years ago, we wrote in this blog about the strict proportionality between the CPI inflation and the actual interest rate defined by the Board of Governors of the Federal Reserve System, R. Briefly, the cumulative interest rate is just the cumulative CPI times 1.4. There are periods when the interest rate deviates from the long term inflation trend, which has been almost linear since 1972. Here, we extend observational dataset and discuss the most probable reason why the FRS actually not controlling inflation by presenting the actual economic force behind price inflation, as we presented in a series of papers [e.g., 1, 2, 3, and 4].  Overall, inflation is a linear lagged function of the change in labor force. The latter is driven by a secular change in the participation rate in labor force (LFPR) together with general increase in working age population. In other words, increasing labor force inflate process and decreasing labor force leads to deflation.
Introducing new data obtained from 2012, we depict in Figure 1the effective rate R divided by a factor of 1.37 (see our previous post for details) and the consumer price inflation. One can see that R lags behind the CPI since 1980, i.e. inflation grows at its own rate and R has to follow up. The idea of interest rate is that a higher R should suppress price inflation when it is high due to the effect expensive money. During deflationary periods with slow economy, low (in some countries negative) R has to channel cheap money into the economic growth. The reaction of inflation is also expected not shortly but with some time lag. The
The cumulative influence of the interest rate should produce a desired effect in the long run and inflation should go in the direction towards acceptable values. Figure 2 displays the cumulative effect, i.e. the cumulative values of the monthly estimates of R and CPI multiplied by 1.37. This is an intriguing plot. In the long run, the R curve fluctuates around the CPI one and returns to it. It is hard to believe that the sign of deviation of R from the 1.37CPI curve affects the behavior of the CPI, which is practically linear. Therefore, the influence of monetary policy is under doubt.
The FRS has tried all means to return the CPI to R without any success and have to return R to the CPI!
We have already described the secular changes in LFPR in 2013, 2014, and 2015. Figure 3 illustrates the evolution of LFPR as measured by the Bureau of Labor Statistics. The LFPR curve is accurately approximated by a simple function: LFPR(t) = 62.7+4.3SIN(2π[t-1978]/T). The period T=74 years and the double amplitude is 8.6, i.e. the largest LFPR change is 8.6%. Currently, the LFPR is strictly in the center of the range and in the middle of the fall from 1996 to 2034.
Our concept is based on the observation that the periods of high inflation are related to accelerated labor force growth. Therefore, we have highlighted the most recent and the next period of accelerated growth as marked red (start) and green (end) vertical lines highlight two periods. These periods of accelerated growth lasts 1/4T =18 years. Figure 4 presents the first and second time LFPR derivatives, which are used to select the accelerated growth, i.e. the period when both derivatives are positive. There is a clear coincidence between the period of two-digit inflation and the peak in the first derivative near 1978.  This is one of many facts supporting our concept of inflation. This is not the purpose of this post, however. Here, we compare the FRS decisions on discount rates and the behavior of the LFPR curve.
Figure 5 compares the difference between the R and 1.37CPI in Figure 2 (red curve) and the product of the LFPR’ and LFPR’’, i.e. the curve representing the change in acceleration. The latter curve is shifted by 6 years back in time (phase shift of approximately -30 degrees for period of 74 years). The peaks in the difference curve are well synchronized with the acceleration curve, which is leading by 6 years.  In reality, FRS decisions are fully driven by the LFPR. Moreover, the FRS is very slow in understanding status quo.
Now, R and 1.37CPI in Figure 2 coincide.  This means that the best R has to be 1.37 of the current CPI, but we all know that R will be retained below this value at least before 2020.  We are thinking now on the investment opportunities resulting from the predictable FRS behavior.

Figure 1. The federal funds rate, R, divided by 1.37 and the rate of consumer price inflation, CPI, between 1955 and 2016.

Figure 2. Cumulative values of the curves in Figure 1.

Figure 3. The rate of participation in labor force (LFPR). LFPR is accurately approximated by a simple function: LFPR(t) = 62.7+4.3SIN([t-1978]/T). The period T=74 years. Red (start) and green (end) vertical lines highlight two periods of accelerated growth. The periods of accelerated growth lasts 1/4T =18 years. The next period will start in 2034.

Figure 4. First and second time derivatives of the approximating SIN function.

Figure 5. The difference between the cumulative sum of effective federal funds rate (monthly, not seasonally adjusted) and the cumulative sum of the monthly rate (y/y) of consumer price inflation compared to the acceleration periods in the LFPR.

Strong leadership or democracy?

The figure below is self-explanatory. This is the cumulative real GDP growth in the former socialist countries (FSC) after 1990 (i.e. the past 25 years) as presented in the Total Economy Database.  The most successful (>60%) countries are Armenia, Azerbaijan, Belarus, Estonia, Kazakhstan, Poland, Slovakia, Turkmenistan, and Uzbekistan. Three to four of them are recognized democracies and the other five are under strong leadership (euphemism for pure economic discussion).  The absolute losers are Tajikistan and Ukraine (the winner with -26.2%), Serbia and Montenegro, with Moldova being still below the 1990 GDP level. All four countries have quite a controversial political configuration. Other FSC are above the zero line ranging from Croatia (4%), Kirgizia (7%) and Georgia (10%) to Latvia (55%), Bulgaria (44%) and Slovenia (43%).
It is hard to deny the general observation that strong leadership was able to create better economic conditions for growth in the countries of the former Soviet Union, except Baltic countries. Political turmoil is not creative, but we know it very well.  
I would not invest in a country without a stable political configuration.

Figure 1. The cumulative real GDP growth between 1990 and 2015 in the former socialist countries

Figure 2. The evolution of real GDP in the FSC


European Union does not grant harmonized solution of demographic problems: part 2

Many European countries are missing in the first part of this post. All they deserve to be presented but we illustrate the diversity of and similarities in population trajectories rather than create a comprehensive view on the development in EU demography. We still use the OECD database which allows covering the century between 1950 and 2050. Here we present a few older EU representatives together with newcomers.  Figure 1 demonstrates that three East European countries: Poland, Bulgaria and Czech Republic and five western countries with longer capitalist economic history.  Germany serves as a watershed for these two groups of countries.

Bulgaria  shows behavior similar to that in Latvia and Lithuania - extremely steep depopulation trajectory after 1990. According to the OECD projection, Bulgaria  will lose from more than  40% of its population measured in 1990.  Depopulation is striking and dangerous for survival as a nation. Poland and Czech Republic are similar to Germany – approximately 5% to 10% fall in total population before 2050.  

Switzerland looks to have all chances to succeed in healthy population growth together with Austria, who also shows gradual growth into the future. Spain, Italy and Holland are a bit controversial but also have hopes for future population rise in the next decades.

Taking into account France and the UK in the previous post one can conclude that East European countries that entered the EU are all are prone to depopulation of varying degree, while the founding members feel much better. 

Figure 1. the evolution of total population in selected EU countries between 1950 and 2050. All curves are normalized to their respective values in 1990.

European Union does not grant harmonized solution of demographic problems

Everybody knows that European Union is not homogeneous. The idea behind unification was to overcome all kinds of disparity by joint efforts. The inherent demographics processes in European countries do not obey the unification plan, however.  The OECD database allows taking a specific look at the past and future of all countries … and found that some countries go wrong way after joining the EU. Figure 1 demonstrates that three Baltic countries have been and extremely steep depopulation trajectory after 1990. In 2015, they were by 15% to 25% smaller in terms of total population when in 1990 (notice that they grew by 30% from 1950 to 1990). According to the OECD projection, three Baltic countries will lose from 35% to 40% of their population relative to 1990. This is rather grim future.
On the other hand, France and UK were, are and continue to be on a healthy growth path with a perspective of 35% larger population in 2015 than it was in 1990.  Russia has stabilized its population around 146 million, i.e. 99% of that in 1990, and will not change much in the future.

The case of Germany is most illustrative for the current political discussion of immigration in Europe. Germany loses now and will be losing its population in the future. The OEDC projection says that the UK will overtake Germany in 2045 and France in 2050. Germany is losing its biggest population position against major European economies. This might be the reason for mercantile Merkel to invite as many immigrants as possible to boost German population and return it on the growing trajectory.  Die Kanzlerin is wise.

All in all, European Union will suffer strong demographic problems, which are related to emergent recognition of fading national identity. 

Figure 1. Total population in selected European countries according to the OECD historical time series and population projections. All curves are normalized to their respective values in 1990. 


Some tricks with real GDP

We have discussed the incompatibility of real GDP data caused by the change in definition of the GDP deflator, dGDP, many times (in the USA - in 1977) [here, here, and here]. Time just strengthen our assumption that the growth of real GDP per capita (rGDPpc) in the USA is a linear function of time. The estimates of rGDPpc borrowed from the Total Economy Database illustrate this finding for all developed countries.
Here, we update (with two new annual estimates) the GDP curves, the original one and that corrected for the difference between the dGDP definition before and after 1977.  Figure 1 shows details of the deviation between the dGDP and the consumer price index, CPI, as expressed by the cumulative inflation rates. Before 1977, the CPI (red) and dGDP (black dotted) lines are absolutely synchronized. Essentially, there is no difference in the GDP price deflator and the CPI. However, since 1978 one can observe that the CPI inflation rate is approximately equal to the rate of the GDP deflator change multiplied by a factor of 1.22, as shown in Figure 1.  The coincidence between the observed CPI and the corrected dGDP (open circles) curves after 1977 is striking with Rsq>0.98.
The reason behind the change is not clear but the problem emerged with the difference between definitions used before and after 1977. (The Bureau of Economic Analysis warns economists that the real GDP time series is incompatible over time.) It is like to use the same nominal speed limit, say 45, after transition from miles to km per hour. By definition, real GDP is nominal GDP reduced by inflation rate. We are sure that it is necessary to use the same definition over time in order to have a real GDP time series without structural breaks. This is not the case in the data reported by the Bureau of Economic Analysis. Fortunately, the factor of 1.22 allows recovering the dGDP time series back in time using the strong statistical link between CPI and dGDP (1.22dGDP = CPI). The dashed line is the estimate of dGPD before 1977 when the same definition is applied as after 1977. We prefer to correct the dGDP time series instead of using the CPI for the period after 1977.
Figure 2 shows real GDP and real GDP per capita in the USA from 1929 to 2013. The latter time series has rather a linear trend since 1929 with Rsq. =0.97. The real GDP series deviates from the long term exponential trend since 2000 – the year then the rate of population growth fell below 1% per year.
In Figure 3, we correct real GDP per capita for the difference between CPI and dGDP after 1977 and compare the original and corrected time series. One can see that the corrected curve has Rsq.=0.98 and does not deviate from the long-term trend. Currently, the corrected growth rate goes exactly the linear long-term trend and strongly deviates from exponential function also shown in Figure 3.

USA will follow linear growth trend, which is identical to the rate of growth falling inversely proportionally to the level of real  GDP per capita. Also, one should not use any data published by the BEA withour corrections.

Figure 1.  Cumulative rates of CPI and dGDP inflation, original and scaled by a factor of 1.22.

Figure 2. Real GDP and real GDP per capita in the USA from 1929 to 2015. The latter time series has rather a linear trend since 1929. The real GDP series deviates from exponential trend since 2000 – the year then the rate of population growth fell below 1% per year.

Figure 3. The real GDP per capita time series corrected for the difference between CPI and dGDP since 1978. Linear trend is obvious in the corrected time series. Currently, the growth rate is slightly below the long-term trend.