We have estimated a version of Okun’s law for the USA, France and Spain. As beforfe, we have apply a LSQ technique to the integral version of Okun’s law:
u(t) = u(t0) + bln[G/G0] + a(t-t0) (1)
where u(t) is the predicted rate of unemployment at time t, G is the level of real GDP per capita, a and b are empirical coefficients.
For Canada, we have estimated a similar model with a structural break somewhere between 1980 and 1990. The best-fit (dynamic) model minimizing the RMS error of the cumulative model (1) is as follows:
du = -0.28dlnG + 1.16, t<1983
du = -0.28dlnG + 0.30, t>1982 (2)
This model suggests no shift in the slope and a bigger change in the intercept around 1983. Figure 1 depicts the observed and predicted curves of the unemployment rate. The agreement is very good. Figure 2 shows that when the observed time series is regressed against the predicted one, R2=0.87. Here we do not test both time series for stationarity but presume that the rate of unemployment has to be a stationary time series in the long run.
The integral form of the dynamic Okun’s law (1) is characterized by a standard error of 0.68% for the period between 1971 and 2010. The average rate of unemployment for the same period is 8.2% with a standard deviation of the annual increment of 0.94%.
One can suggest that the rate of unemployment has been driven by real economic growth and there is no much room for structural unemployment.
Figure 1. The observed and predicted rate of unemployment in the Canada between 1970 and 2010.
Figure 2. The measured time series is regressed against the predicted one. R2=0.87 with both time series likely to be stationary.