In the post below, I discuss a very strong correlation in the data which surprised me — a high ratio non residential fixed capital investment to GDP is correlated with high nominal interest rates on corporate bonds.

I think the discussion in comments was very interesting and I have promised to pull back 2 comments (I didn't promise to pull them back above the jump).

In a third post on a correlation coefficient, I will get to my current thoughts on what is going on. Here some general thoughts (after the jump)

First it is odd that so striking a correlation is not widely discussed. Partly, I think this is do to the leading role theory has in the academic macroeconomic literature — the correlation is neither implied by a prominent hypothesis nor does it falsify a prominent hypothesis. Partly, I think it is related to the prominent position hypothesis testing has in econometrics. “A atatistic” is read to mean “a test statistics” and statistics whose distribution is not implied by a null hypothesis aren't considered. I'm about to go off on one of my usual tangents noting that, on the other hand, hypothesis testing is allowed no role, since models aren't hypotheses and all models are false. So epirical work must be hypothesis testing and hypothesis testing is irrelelevant, so evidence and data are irrelevant. ùù

Whoah back on topic. the non polemical point is that in the post below, I show graphs and correlation coefficients, but no standard errors, t-statistics or confidence levels. The reason is that the correlation is what is called a spurious regression. It is a regression of one non stationary time series on another. The coefficient of the regression divided by the conventionally calcuated standard error does not have a t – distribution. The conventional test of the hypothesis that it is zero is completely invalid. I think the pulled back comments show that this isn't a point about purely mathematical statistics — there are a large number of possible partial explanations of the pattern, many of which amount to saying it was a coincidence.