When are you gonna get job?

Following my previous post on the diminishing probability for a younger person to get rich here I would like to show the back side of this process. The rate of unemployment for younger people has a positive trend. See figure below.  No comments needed.


 

When are you gonna become rich?

Overall, the portion of American population having incomes distributed by the Pareto law (~1% to 5%) has not been significantly changing since 1947.  This portion is a working definition of being rich. When a person gets income above the Pareto threshold - s/he is able to reach any other level with a probability falling as a power of income.  

However, the age when a person  can get into the Pareto has been increasing. (see the paper with our model for explanation) For younger, it is getting harder and harder to get rich.  Figure 1 compares several probability density functions (PDF) describing the  age dependence (as expressed by working experience) of the portion of rich people. In 2011, the peak age is approximately 57 years. In 1990, it was 46 years of age.

Another sad news - old people drop out of the rich population exponentially. Much faster than get into it.    

Figure 1. PDF for several years.
 

January-April 2000, the highest rate of partcipation in labor force ever

Four first months of the 21st centure gave the record high rate of participation in labor force. It was 67.3% (seasonally adjusted). Currently, it is at 63.5% or 4% down from the record. Actually, it is back to 1979. And this low level does not look like the end of the story. The trend is definitely strong and negative.

 

The rate of unemployment on its way to 6% in December 2013

We have been reporting on the decline in the rate of unemployment in the US since the beginning of 2012. We predicted an extended unemployment fall period down to the level of 6.2% in the fourth quarter of 2013. This prediction was made after we accurately forecasted (on March 1, 2012) the rate of unemployment in the US to fall down to 7.8% by the end of 2012. Here we update our model and present the evolution of the unemployment rate in the second quarter of 2013. Overall, the measured rate has been following our prediction. We foresee the rate to fall down to 6% [±0.4%] in the fourth quarter of 2013 or in the first quarter of 2014.

In 2006, we developed three individual empirical relationships between the rate of unemployment, u(t), price inflation, p(t), and the change rate of labour force, LF(t), in the United States. We also revealed a general relationship balancing all three variables. Since measurement (including definition) errors in all three variables are independent it may so happen that they cancel each other (destructive interference) and the general relationship might have better statistical properties than the individual ones. For the USA, the best fit model for annual estimates was a follows:

u(t) = p(t-2.5) + 2.5dLF(t-5)/dtLF(t-5) + 0.0585   (1)

where inflation (CPI) leads unemployment by 2.5 years (30 months) and the change in labor force leads by 5 years (60 months). We have already posted on the performance of this model several times.

For the model in this post, we use monthly estimates of the headline CPI, u, and labor force, all reported by the US Bureau of Labor Statistics. The time lags are the same as in (1) but coefficients are different since we use month to month-a-year-ago rates of growth. We have also allowed for changing inflation coefficient. The best fit models for the period after 1978 are as follows:

u(t) = 0.63p(t-2.5) + 2.0dLF(t-5)/dtLF(t-5) + 0.07; between 1978 and 2003

u(t) = 0.90p(t-2.5) + 4.0dLF(t-5)/dtLF(t-5) + 0.30; after 2003

There is a structural break in 2003 which is needed to fit the predictions and observations in Figure 1. Due to strong fluctuations in monthly estimates of labor force and CPI we smoothed the predicted curve with MA(24).

The structural break in 2003 may be associated with the change of sensitivity of the rate of unemployment to the change of inflation and labor force. Alternatively, definitions of all three (or two) variables were revised around 2003, which is the year when new population controls were introduced by the BLS. The Census Bureau also reports major revisions to the Current Population Survey, where the estimates of labor force and unemployment are taken from. Therefore, the reason behind the change in coefficients night be of artificial character - the change in measuring units.

Figure 1 depicts the prediction and the observed fall in the rate of unemployment. Figure 2 shows that the observed and predicted time series are well correlated (R²=0.82). This is a good statistical support to the model.

Figure 3 depicts the predicted rate of unemployment for the next 12 months. The model shows that the rate will fall to 6.0 % by December 2013. For 113 observations since 2003, the modelling error is 0.4% with the precision of unemployment rate measurement of 0.2% (Census Bureau estimates in Technical Paper 66). Hence, one may expect 6.0% [±0.4%]. After a 0.2% fall in July, we expect a dramatic drop in the rate of unemployment in August/September 2013.

Figure 1. Observed and predicted rate of unemployment in the USA as obtained in April 2013.

Figure 2.  Observed vs. predicted rate of unemployment between 1967 and March 2013. The coefficient of determination   Rsq.=0.82. 

Figure 3. The predicted rate of unemployment. We expect the rate to fall down to 6.0% in December 2013.