Dramatic decline in labor force participation

Michael Mandel at “Economics Unbound” is really interested in labor force participation rate (LFPR). He devoted couple previous posts to related problems in an attempt to explain the evolution of labor force participation rate and productivity by some modern and fancy reasons. It is not worth to repeat his posts here and I just refer to Figure 1 as a general argument against any short-term force driving LFPR. The overall trajectory has a very clear picture of secular oscillations. Between 1965 and 2000, the LFPR was growing with just minor plateaus near 1980m and 1990. After 2000, the LFPR has been declining. This is a robust downward trend which hardly to be compensated by innovations, as Michael suggests.

In 2009, the LFPR has decreased from 66% to 65.4% in Q3 with average over the three quarters of 65.6%. A 0.6% drop in LFPR is a dramatic one. It corresponds to ~2,000,000 people leaving labor force in the US almost at once! (It is worth noting that such a drop may severely affect the rate of unemployment because people without job are more likely to leave labor force). According to our model [1], this the decline in the LFPR was expected in 2010. However, the population estimates, which are used for the prediction, have never been accurate enough for sharp timing. In any case, the model developed in [1-3], which links LFPR and productivity in developed countries to real GDP per capita has proved its consistency. The next two to three years should serve for further validation, as Figure 2 assumes.

Figure 1. The evolution of LFPR between 1960 and 2009.

Figure 2. The observed LFPR and that predicted from real GDP per capita. We expect the LFPR to fall down to 64.5% by 2013.


The observed increase in productivity is directly related to the decrease in the LFPR. As a consequence, it was also well predicted by our model in [2]. We used the projection of the number of 9-year-olds from the number of 1-year-olds for the prediction of real GDP per capita in the 2010s. Since 2010, the productivity has to be growing, as Figure 5 in [2], demonstrates.

a)

b)

Figure 5. Prediction of the number of 9-year-olds by extrapolation of population estimates for younger ages (1- and 6-year-olds).
a) Total population estimates. The time series for younger ages are shifted ahead by 8 and 3 years, respectively.
b) Change rate of the population estimates, which is proportional to the growth rate of real GDP per capita. Notice the difference in the change rate provided by 1-year-olds and 6-year-olds for the period between 2003 and 2010. This discrepancy is related to the age-dependent difference in population revisions.
A downward trend in productivity, as has been observed since 2003, will turn to an upward one in the 2010s. This also means an elevated growth rate of real GDP per capita during the period between 2010 and 2017.


References

[1] Kitov, I., Kitov, O., (2008). The Driving Force of Labor Force Participation in Developed Countries, Journal of Applied Economic Sciences, Spiru Haret University, Faculty of Financial Management and Accounting Craiova, vol. III(3(5)_Fall), pp. 203-222. http://www.jaes.reprograph.ro/articles/3_TheDrivingForceofLaborForceParticipationinDevelopedCountries.pdf

[2] Kitov, I., Kitov, O., (2008). The driving force of labor productivity, MPRA Paper 9069, University Library of Munich, Germany, http://ideas.repec.org/p/pra/mprapa/9069.html
http://mpra.ub.uni-muenchen.de/9069/01/MPRA_paper_9069.pdf

[3] Kitov, I., Kitov, O., (2009). Modelling and predicting labor force productivity, MPRA Paper 15152, University Library of Munich, Germany, http://mpra.ub.uni-muenchen.de/15152/01/MPRA_paper_15152.pdf

Unemployment in Japan: now falling to the long-term level around 5%

In June and August 2009, we posted on the evolution of unemployment in Japan [P1] and [P2], which predicted the rate of 6.0% in August 2009. In the latter post we had to update the prediction and reduce the expected level of unemployment, as dictated by new readings of labor force. Moreover, we found that the level of unemployment in July was likely the peak value and the rate of unemployment in Japan would be decreasing since August 2009 according to the long term forecast (Kitov; 2006, 2007).

On the 2nd of October, the reading for August 2009 was reported by the Statistics Bureau of Japan. The (seasonally adjusted) rate for August was measured at 5.4%, i.e. 0.3% lower than in July. This observed decline is in line with that based on the model linking the rate of unemployment, UE(t), to the rate of change of labor force, dLF(t)/LF(t):

UE(t)= -1.5*dLF(t)/LF(t) +0.045 (1)

Figure 1 updates the observed and predicted curves for 2009. Because the accuracy of short-term estimates provided by labor surveys is not high, the monthly estimates of unemployment and labor force are prone to large measurement errors. The discrepancy between the observed and predicted curves likely manifests the problems with measurements. Figure 2 presents a mid-term view. In 2007 and 2008, the predicted unemployment was lower that the observed one, but in 2009 both variables are essentially the same (see Figure 1). In the long-run, the rate of unemployment in Japan will asymptotically approach 5.2% (Kitov, 2007), as displayed in Figure 3.

From relationship (1), we can conclude that the rate of unemployment in 2009 will likely undergo additional decline. The peak rate of unemployment is left behind, but its further decrease will accompany the decline in the level of labor force.

References

Kitov, I., (2006). The Japanese economy, MPRA Paper 2737, University Library of Munich, Germany, http://ideas.repec.org/p/pra/mprapa/2737.html
Kitov, I., (2007). Exact prediction of inflation and unemployment in Japan, MPRA Paper 5464, University Library of Munich, Germany, http://ideas.repec.org/p/pra/mprapa/5464.html

Figure 1. Observed and predicted rate of unemployment in Japan in 2009.

Figure 2. Observed and predicted rate of unemployment in Japan between 1998 and 2008.

Figure 3. Prediction of the evolution of unemployment rate in Japan between 1990 and 2050 (Kitov, 2007).
Notice excellent prediction between 1998 and 2007 with the peak value in 2001.

Semi-annual report on SP 500: from April to September 2009

This is a semi-annual report on the evolution of S&P 500 index. It compares the actually observed monthly closing levels to those predicted by our model, as originally presented in [1]. The major conclusion is that the prediction of a monotonic growth in S&P level made in March 2009 is correct. There is no indication that the growth will end before May 2010, where we foreseen the turn to a negative slope. Accordingly, the S&P 500 annual return will soon reach positive figures and will be growing at an accelerated rate till May 2010.

The model links S&P 500 annual returns to the number of 9-year-olds and has passed econometric tests for cointegration, with goodness-of-fit reaching 0.9. Since the number of 9-year-olds can be accurately predicted using younger cohorts, one can predict S&P returns at a several-year horizon. (Standard demographic projections may be used to predict over a decade ahead.)

We revealed the link between S&P 500 and the number of 9-year-olds in December 2007 using historical data since 1985. Since the very beginning of 2008, we have been carefully tracking the evolution of S&P 500. The original model actually predicted a sharp fall in 2008 [1]. (As in many scientific studies, the attempt to improve the original model, in order to fit data between 2003 and 2007, had failed, as we reported in this blog at several occasions.) The re-calibrated version of the original model developed in March 2009 is as follows:

Rp(t) = 165dln[N3(t+6)] - 0.17 (1),

In (1), Rp is the 12-month cumulative return; N3 is the number of three-year-olds; t+6 – time shifted by six years ahead to extrapolate the number of 3-year-olds into the number of 9-year-olds; dln is the rate of growth, i.e. the monthly increment in N3 normalized to the contemporary level. The time step is one month or 1/12 of a year.

Figure 1 compares the initial prediction of the S&P 500 evolution, the observed trajectory for the period since February 2009, and a new prediction till 2011. Relationship (1) is used with the number of 9-year-olds extrapolated from the number of 3-year-olds. In March 2009, we used a preliminary calibration of the original model and assumed the monthly increment in S&P 500 would be 80 points. This assumption was too optimistic and the growth was weaker. The original prediction is shown by blue lin with solid circles in Figure 1, and the observed values are shown by red diamonds. The black line represents an updated prediction since September 2009. It reproduces the old prediction but with a 46-point monthly increment since October 2009, as discussed below.

All in all, Figure 1 presents strong evidence in favour of our original model. Six months of almost monotonic growth were not expected by many market players in March 2009. The next nine months should bring additional validation to the model. The most important event will be the turn in May 2010. But the growth before this date is of crucial importance as well.

Figure 1. The evolution of S&P 500. Blue line - the original prediction using (1) with 80 unit per month increment. Red line – observations. Black line – the updated prediction since October 2009 with a 46-point monthly increment.

In any case, the model predicts a sudden drop in 2008 and 2009 to the level of 700, which has been followed by constant growth to the level 1050 in September 20009. Initially, we estimated the peak value in 2010 as 1800. But the last six months demonstrated the necessity to re-calibrate the model using new data. (In physics, even fundamental constants are under permanent re-estimation, and empirical and even fundamental models are constantly recalibrated.) Therefore, we also re-estimated coefficients in (1) to fit the last six S&P 500 (monthly) readings. The new model is as follows:

Rp(t) = 135dln[N3(t+6)] - 0.17 (2),

Actually, we needed to reduce the coefficient of linear term from 165 to 135 with free term unchanged. Figure 2 depicts the updated prediction of the S&P 500 annual returns. The peak S&P 500 value in May 2010 should be 1425 (not 1800) if the future increment will be 46 points per month, as observed between March and September 2009.

Figure 2. Observed and predicted S&P 500 returns. The September level of S&P 500 index is 1057. The past six months are relatively well predicted.

Conclusion
Between 1985 and 2009, the S&P 500 returns can be accurately described by population estimates. The model based on the number of 9-year-olds produces a time series which is cointegrated with the S&P 500 returns, i.e. reveals a weak causality, as proved by the cointegration tests.

The re-calibrated model predicts the continuation of S&P 500 growth into 2010 with the peak level of ~1400 in May. The annual returns will reach positive zone soon and also peak in May 2010 at the level of 50% to 70%.


References
[1] Kitov, I., Kitov, O., (2007). Exact prediction of S&P 500 returns, MPRA Paper 6056, University Library of Munich, Germany, http://ideas.repec.org/p/pra/mprapa/6056.html

Time to buy Treasuries

A deflationary period is coming. As we wrote in 2006, deflation should start in 2012. Some funds (Pimco, for example, as Bloomberg reports) are getting prepared to these poor times. Do not miss the quick start and re-visit our old paper for the prediction of the deflationary period lenght:

Inflation, unemployment, labor force change in the USA
Ivan O. Kitov
Abstract

A model is developed linking the measured inflation (consumer price index or GDP deflator), unemployment and change in labor force. During the last twenty-five years, unemployment in the USA has been a lagged linear function of inflation. In turn, inflation has also been a lagged linear function of relative change in labor force with time. The lag is currently three years. Only a small decrease in labor force participation rate is currently observed in contrast to a strong increase between 1965 and 1990. According to the indicated relationship, the well-known stagflation period clearly resulted from the lag: the sharp increase in inflation coincided in time with the high unemployment induced by the high inflation period two years before. One can predict the unemployment rate in the USA in the following two years within the accuracy of inflation measurements. For example, the end of 2005 is a pivot point from a period of decreasing unemployment to one of moderate growth from 5% in 2005 to 6% in the middle of 2008. Starting in 1960, cumulative values of the observed and the model predicted unemployment are in agreement with the lag between inflation and unemployment. Inflation is defined by a lagged linear function of rate of change in labor force. The observed and predicted inflation almost coincide for the last forty years of annual measurement values, smoothed by a five-year wide moving window curves and as cumulative curves as well. Deviation of the curves before 1960 can be explained by a degraded accuracy of the measurements. A severe decrease in the rate of change of labor force is expected after 2010. This drop can potentially induce a long-term deflationary period. The same effect has been observed for Japan starting in 1990. There are numerous implications of the results for monetary and social policy-makers. The most important is an absence of any means to control inflation and economic growth except though a reasonable labor policy. In addition, some urgent measures are necessary to prevent the start of a deflationary period in 2010-2012.