The rich rob the poor?

Since the early 2000s, a wave of interest to income inequality has been rising. A few researches found a specific way to prove that the distribution of income has been changing in the US in favor of very rich (top 1%).  Figure 1 is borrowed from an article by Atkinson, Piketty, and Saez (APS) published in the Journal of Economic Literature. Before call for help, let’s consider the source of increasing portion of the richest. It’ll show us that the poor are not robbed.    

Figure 1. The increasing portion of total income for the top 1 % of households.

There are two different sources of the increasing portion of the top income. First, the cake (total income) is not changing in time and the richest take away from the portion of the poor. Second option is the increasing portion of the total income in the GDP without any harm to the 99% of population. Figure 2 demonstrates that   the ratio of gross personal income (GPI) and gross domestic product (GDP) (both borrowed from the bea.gov) repeats the curve in Figure 1 practically one-to-one. In the GPI, all incomes subject to taxes (APS refer to the IRS data for Figure 1) are counted in. We can conclude that the portion of personal incomes in the GDP has been increasing since the 1970s together with the portion of top 1% richest. In other words, the richest people change the proportion of corporate and personal incomes in the GDP, the former falls and the latter rises.  But both likely belong to the same people. Ninety nine percent of population hardly benefits from these corporate incomes, and Figure 3 evidences that the portion of personal income estimated by the Census Bureau in the annual Current Population Surveys has not been changing between 1967 and 2001. (The fall after 2003 is likely artificial introduced by a new questionnaire.)

Conclusion. The redistribution between personal and corporate incomes related to the richest 1% was misinterpreted as the changing income inequality. The richest just put some money from their left pocket into the right pocket. The same money is still with them. The truth is that the other 99% have never been the beneficiaries of the ~50% of the GDP, which belongs to Richie-Rich.  

The richest might rob the poor many-many years ago but the income inequality has been hardly changing ever since. The problem of economists is that they are not able to measure income inequality accurately enough and get in own trap.  As a physicist I can add – never measure aggregate variables using a changing portion (GPI) of a closed system (GDP). The result is always wrong. 

Figure 2. The ratio of gross personal income (GPI)and gross domestic product (GDP) since 1929.

Figure 3. GPI/GDP and the ratio of the personal (money) income measured by the Census Bureau and the GDP.

Oh Dear! Deflation

Eight  years ago we developed an empirical model describing inflation in developed countries and published a forecast for the USA at a ten year horizon in 2006 (Kitov, 2006ab) as a linear and lagged function of labour force. For the USA the model is as follows:

DGDP(t) = 4.0dLF(t-2)/LF(t-2) – 0.03 (1)

where DGDP is the GDP deflator at time t, and LF is the level of labour force two years before, t-2. In equation (1), the slope of linear relationship is 4.0 and intercept is -0.03. With labour force constant (dLF=0), the overall price inflation in the USA would remain negative at the level of -3% per year. For inflation to be sustainable at the level of 2% (the fed’s unannounced target) the growth in labour force of 1.25% per year is required.

Eventually, the link between price inflation and labour force was successfully tested for cointegration (Kitov, Kitov, Dolinskaya, 2007) and validated using 1-D boundary elements methods (Kitov, Kitov, 2010). This links holds for other developed countries as well (Kitov, Kitov, 2010).

Figure 1 illustrates the linear and lagged relationship between inflation (GDP deflator) and the change rate of labour force in the USA for the period between 1960 and 2006. The estimates of the change rate of labour force are shifted by two years ahead in order to synchronize the predicted peaks of inflation with those actually observed in 1975 and 1984. Due to the uncertainty in the labour force (and inflation) measurements the most reliable readings correspond to the changes of the largest magnitude, as described by the BLS. Every sound model of price inflation must explain these peaks.

Figure 1. Measured inflation (GDP deflator) and that predicted from the dLF/LF (shifted 2 years ahead). An agreement is observed throughout the whole period with some short fluctuations in labour force potentially induced by the population corrections implemented by the Census Bureau in the census years.

Figure 2 presents two smoothed inflation curves – the measured and the predicted one. The smoothing was attained by a 7-year moving average, MA(7), with a one-year step. The predicted curve is shifted by 2.5 years (we used two time scales with a half-a-year shift) ahead in order to fit the inflation peak near 1978. The original (not shifted) predicted curve is also shown in order to illustrate that it is actually leading by 2.5 years.

Figure 2. MA(7) of the predicted and measured inflation. The prediction is made according to the relationship (1). The predicted curve is shifted by 2.5 years ahead.

Figure 3 displays the observed and predicted cumulative inflation curves starting from 1965. The predicted cumulative curve is obtained by a progressive summation of values from 1963 and is also shifted ahead by 2 years. There is an almost complete agreement between the cumulative curves for the whole period. The only small deviation occurred around 1993 and corresponds to a sharp drop of the rate of labour force growth as induced by the baseline working age population correction.

The predicted cumulative curve is very sensitive to free term in (1). Even the initial difference of 0.0001 results in a tangible deviation from the measured curve after 50 years. Therefore, the value of free term in (1) can be estimated with a good accuracy. With cumulative curves, one can obtain the most accurate coefficients solely on the basis of visual fit. Also, since these two cumulative curves have R2>0.999 and actually represent indexes one can replace the secular growth in the overall price as the cumulated growth in labour force two years before. In a sense, these curves are similar to conservation laws or integral equations in physics (Kitov, Kitov, 2010).

Figure 3. Comparison of the cumulative values of the observed and predicted inflation presented in Figure 1. The predicted curve starts from 1963 and is shifted by 2 years ahead. An agreement is observed with a notable change from convexity before 1980 to concavity one after 1980.

Relationship (1) can be used for a prediction at a larger time horizons using labour force projections made by various institutions. For example, the projections made by CBO (2004) and BLS (2005) undoubtedly indicate a decrease in the participation rate and a decaying growth rate of the working age population. According to these projections, staring from 2010, the annual increase in labour force will be less than 1,200,000 – the value separating inflation and deflation. Hence, the year of 2012 is likely to mark the beginning of the deflationary era in the USA (which hopefully is the global disaster the Mayans talked about) because of the two-year lag between the labour force change and inflation. Figure 4 details the prediction based on the CBO’s projection of the labour force. After peaked at 3.2% in 2007, the rate of price inflation has been at a gradual decrease, which will lead to the first red figure in 2012.

Hence, we are waiting an extended deflationary period in the USA since 2012.

Figure 4. Predicted inflation rate for the period between 2006 and 2016 according to the CBO’s (2004) labour force projection. A deflationary period starts in 2012.

 

 

Conclusion

Considering the accuracy of labor force projections  and inflation estimates we have the prediction  closest to the actual rate inflation observed since 2006. Our horizon was ten years. The FRB is not able to change the future rate.

 

References

Bureau of Labor Statistics. (2005a). Labor force projections to 2014: retiring boomers. Monthly Labor Review, November 2005.

Congressional Budget Office. (2004). CBO’s Projections of the labor force. September 2004.

Kitov, I. (2006a). Inflation, unemployment, labor force change in the USA, Working Papers 28, ECINEQ, Society for the Study of Economic Inequality,http://ideas.repec.org/p/inq/inqwps/ecineq2006-28.html

Kitov, I. (2006b). Exact prediction of inflation in the USA, MPRA Paper 2735, University Library of Munich, Germany

Kitov, I., Kitov, O., Dolinskaya, S. (2007). Inflation as a function of labor force change rate: cointegration test for the USA, MPRA Paper 2734, University Library of Munich, Germany

Kitov, I., Kitov, O. (2010). Dynamics of Unemployment and Inflation in Western Europe: Solution by the 1-D Boundary Elements Method, Journal of Applied Economic Sciences, Spiru Haret University, Faculty of Financial Management and Accounting Craiova, vol. V(2(12)_Summer), pp. 94-113.

Global grid of master events for waveform cross correlation: design and testing

Presented at the CTBT Science and Technology 2013 Conference, Hofburg, Vienna, June 17-21.

 

Link to presentation: Dmitry Bobrov, Ivan Kitov, and Mikhail Rozhkov

Abstract

Seismic monitoring of the Comprehensive Nuclear-Test-Ban Treaty requires a uniform coverage of the earth. The global use of waveform cross correlation for monitoring purposes is hindered by the absence of master events outside the zones of seismic activity.  To populate the aseismic areas we have studied two principal approaches.  Around the seismically active areas, we replicate real events best representing seismicity in a given region and distribute them over a regular grid to distances ~1000 km. These replicated events are called “grand masters”.  For remote aseismic areas, we calculate synthetic seismograms for a regular grid of master events and a predefined set of array stations of the International Monitoring System. Both approaches were tested and showed a resolution similar to the use of real events. Considering three types of master events, we have created a regular and uniform grid with approximately 100 km spacing between nodes as obtained from the equilibrium distribution of charged particles over the earth’s surface. We have created three versions of the grid:  v0.1 with only synthetic templates, v0.2 with real masters added where possible, and v0.3 with grand masters added. The performance of v0.1 has been assessed by full processing of a few data days.

Key words: waveform cross correlation, master events, seismic monitoring, array seismology, IDC, CTBT

The DPRK 2013 underground test and Chebarkul meteorite: joint interpretation of seismic, infrasound, acoustoseismic, and seismoacoustic waves

Presented at the  CTBT Science and Technology 2013 Conference, Hofburg, Vienna, June 17-21.

Link to presentation: Mikhail Rozhkov, Ivan Kitov, and Dmitry Bobrov

Abstract

Two events crucial for monitoring of nuclear explosions under the CTBT occurred on February 12 and 15 and attracted attention of the mass media and scientists. Seismic waves from the underground event and infrasound waves from the meteorite are of extreme interest as well as various processes of energy conversion at the free surface. Infrasound station I45(RU) collocated with seismic array USRK recorded the epicentral I-phase generated by the DPRK 2013 event and the seismoacoustic wave emitted beneath the station. The shock wave from the Chebarkul meteorite generated a regular I-phase recorded by many IMS infrasound stations and a series of seismic phases likely associated with impact and acoustoseismic conversion. Due to the altitude of the peak energy release, the air-coupled ground rolls with a group velocity of 3.5 km/s were generated. A similar pattern was observed after the 1984 r.Chulym (Siberia) bolide. We estimate the energy of both sources and discuss possible mechanisms of acoustic/seismic wave generation and conversion.  

Key words: CTBT, data fusion, IMS, meteorite, DPRK 2013

2008: when all dreams went away

In 2008, an important line was crossed by the rate of participation in labor force, LFPR. Figure 1 shows that the LFPR in the youngest group fell below the level in the group between 55 and 64 years of age. In a way, the US became the country of old workers without perspective. Younger people lost their long term perspective for approximately 35 years. The Kondratiev wave rules.
Figures 2 and 3 demonstrate that the reason behind the LFPR fall in the younger group is related to the fall in labor force caused by the fall in civilian noninstitutional population. The younger population drives the Kondratiev wave.

Figure 1. The rate of participation in labor force in the youngest age group 16 to 24 years and in the group between 55 and 64 years of age, i.e. before retirement.

Figure 2. Labor force in the same age groups as in Figure 1.

 

 

Figure 3. Civilian noninstitutional population in the same age groups as in Figure 1.

 

Will labor force participation rate in the U.S. fall to 59% in 2025?

Since 1995, the rate of participation in labor force, LFPR (the portion of people in labor force) for the working age population (16 years of age and over) has been on a long-term decline. What is the bottom line for this fall? A quasi-scientific answer is shown in Figure 1.  We have found that the evolution of LFPR is symmetric since 1995. Considering 1995 as a pivot point, we mirror-reflected  the current curve and obtained a symmetric future repeating the past. For this dismal future, the LFPR falls to 59% in 2025. At least 30 years (since 1992) are really repeated.
The reader may doubt that such a symmetry is possible and thus cannot be used for quantitative projections.  The Russian economist Kondratiev introduced long-period (50 to 60 years) waves in economic evolution (see Figure 2 borrowed from wikipedia). Looks very similar in period and phase.
Do not be so sure that the LFPR is not free falling into the 2020s.

Figure 1. The actual LFPR curve (black) and that mirror-reflected in 1995 (red line). Both curves practically coincide between 1982 and 2012.

 

Figure 2. The Kondratiev wave.

 

 

60- to 65-year-olds have been "stealing" jobs from 16 to 20-year-olds since 1995

Just one  self-explanatory graph . The labor force participation rate in the age group from 60 to 65 years and in two youngest groups as reported by the BLS. Start time and amplitude of the change since 1995 reveal  a tight link between two processes: grand parents take the jobs of grand children. This cannot be the result of later retirement - just a three year change since the early 1990s.