In this blog, three and a half years ago we revisited our prediction of the rate of unemployment in Italy, which had been made in our
2008 paper. Five years after
this publication, we found that the accuracy of prediction was excellent. We
decided that our model works well. Since the model has a natural 11-year horizon, in this post we check our original (2008!)
prediction for 2013 and 2016 (preliminary) using new estimates. According to the OECD, the unemployment rate
in 2015 is 12.0%. For 2016, the rate is 11.6%. There is no doubt; these values again fully validate
our model of unemployment as a function of the change in labour force. Moreover,
our model has predicted two pivot points in the unemployment rate – in 2008 and
2014. There was a peak observed in 2014 and currently the rate of unemployment
is falling.

We introduced the model of unemployment in Italy in 2008
with data available only for 2006. The rate of unemployment was near its bottom
at the level of 6%. The model predicted a long-term growth in the rate
unemployment to the level of 11% in 2013-2014.

The overall agreement between the measured and predicted
unemployment estimates in Italy validates our concept, which states that there
exists a long-term equilibrium link between unemployment,

*u*, and the rate of change of labour force,_{t}*l*. Italy is a unique economy to validate this link because the time lag of unemployment behind_{t}=dLF/LFdt*l*is eleven (!) years._{t}
The
estimation method is standard – we seek for the best overall fit between
observed and predicted curves by the LSQR method. All in all, the best-fit equation
is as follows:

*u*5.0

_{t}=*l*0.07 (1)

_{t-11}+
As mentioned above, the
lead of

*l*is eleven years. This defines the rate of unemployment many years ahead of the current change in labour force._{t}
Figure 1 presents the observed
unemployment curve and that predicted using the rate of labour force change 11
years ago and equation (1). Since the estimates of labour force in Italy are
very noisy we have smoothed the annual predicted curve with MA(5). All in all,
the predictive power of the model is excellent and timely fits major peaks and
troughs after 1988. The period between 2006 and 2016 was predicted almost
exactly. (If anybody knows a better prediction in 2008 of the 2016 unemployment
rate, please give us the link.)

The fit between predictions
and observations is the best validation of any quantitative model. No other
macroeconomic model is capable to describe such dramatic turns many years ahead.
The evolution of the rate of unemployment in Italy is completely defined ten
year ahead. Since the linear coefficient
in (1) is positive one needs to reduce the growth in labour force in order to
reduce unemployment in the second half of the 2020s. For the 2010s everything
is predefined already and the rate of unemployment will be high, i.e. above 9%.

Figure 1. Observed and
predicted rate of unemployment in Italy.

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