measure of probability of the observation being real as opposed to the probability of just being noise. Based on my own experience in the field of social sciences I find it somewhat hard to believe that the differences you observed in the slopes in fig. 2 are statistically really different if tested against the counterfactual hypothesis, i.e. all being statistically "the same". I for one would love to see that assumption challenged and tested by a single-model-approach... Prof. Mitchell - Thanks for the illuminating analysis. Your view is that "employment growth in the US responds to real GDP growth". I don't wish to start a debate on formal cause-&-effect, just to offer an alternative view which may be helpful: Assume employment drives GDP (ie. to contribute, one must be employed); your %change charts will then be transposed. The slopes are then around 2, suggesting that the employees in question are roughly twice as productive as the average, so the economy may be more sensitive to them than appreciated. The offset in your 2007-12 chart similarly indicates a threshold GDP growth-rate (~ +2%/y) below which this employment will continue to decline (also credible). If you can provide some correlation coefficients, we can see how definite these numbers are.