The Modified Okun's Law For France. Model Validation With Rsq=0.98

As in the previous posts, we minimize the model residuals, i.e. determine the break years together with the regression coefficients. For France, the best fit model between 1962 and 2018 is as follows: 

dup = -0.134dlnG + 0.7501962>t≥1984

dup = -0.255dlnG + 0.620,  1985≥t≥1999     

dup = -0.520dlnG + 0.355,            t≥2000     (1) 

where dup – one-year change in the (OECD) the unemployment rate, G – real GDP per capita (2011 prices). The break years are determined automatically. Figure 2 presents the measured and predicted rate of unemployment (upper panel), the model residual error (middle panel), and the regression of the measured and predicted time series. The overall fit (Rsq.=0.98) is more when excellent with the break years close to those expected from Figure 1. One of the possible reasons is that France has a good set of methods and procedures to measure/estimate economic parameters. This approach does not avoid data incompatibility problems, however, and statistical analysis needs extra efforts to distinguish between actual economic structural breaks and ignorance of basic procedures. The importance of data quality is best illustrated by an example in Figures 3 and 4, where two GDP per capita estimates from the OECD and MPD are compared. One can see that these two agencies provide quite different estimates. The use of the MPD estimates would change the statistical model. We do not know whose estimates are more accurate, but the OECD time series gives excellent results.


Figure 2. Upper panel: The measured rate of unemployment in France between 1960 and 2018, and the rate predicted by model (1) with the real GDP per capita and the unemployment rate published by the OECD. Middle panel: The model residual: stdev=0.50%. Lower panel: Linear regression of the measured and predicted time series. Rsq. = 0.98. 

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