In the USA, the rate of unemployment in December 2013
is 6.7%. It is 0.6% lower than in October. According to our model, this
dramatic fall during the last two months was expected. Actually, two years ago
we predicted the level of unemployment to fall between 6.0% and 6.4% by the end
of 2013 or the beginning of 2014.

So, we have been reporting on the decline in the
rate of unemployment in the US since
the beginning of 2012. We predicted a dramatic period of unemployment falling
down to the level of 6.2% (=-0.4%) 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 predicted and observed in
the rate of unemployment since the beginning of the 1960s. Figure 2 depicts the
observed and predicted rate of unemployment since 2006, including a forecast for the next 12 months. The model
showed that the rate will fall to 6.0 % by December 2013. For 114 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%]. So far, our model was accurate in major changes, with all observed short-term deviations returning to the predicted curve.

Figure 1. Observed and predicted rate of
unemployment in the USA.

Figures 2. The predicted and observed rate of unemployment since 2006. We
expect this rate to fall down to 6.0% (and likely below) in the beginning 2014. The red
and black curves have to intercept
somewhere in 2014.