It has repeatedly been shown that properly constructed monetary aggregates based on index number theory (such as Divisia money) vastly outperform traditional measures of money (i.e. simple sum money) in empirical models. However, opponents of Divisia frequently claim that Divisia is “too complex” for little gain. And indeed, at first glance it looks as if simple sum and Divisia sum exhibit similar dynamics. In this paper, we want to build deeper understanding of how and when Divisia and simple sum differ empirically using monthly US data from 1990M1 to 2007M12. In particular, we look at how they respond differently to monetary policy shocks, which seems to be the most essential aspect of those differences from the perspective of the policy maker. We use a very rich, fairly agnostic setup that allows us to identify many potential nonlinearities, building on a smoothed local projections approach with automatic selection of the relevant interaction terms. We find, that—while the direction of change is often similar—the precise dynamics differ sharply. In particular in times of economic uncertainty, when the proper assessment of monetary policy is most relevant, those existing differences are drastically augmented.

This paper uses recent advances in financial econometrics to test the Friedman hypothesis that money supply volatility Granger-causes velocity. Comparisons are made among simple-sum and Divisia velocity series at the M1 and M2 levels of monetary aggregation, using quarterly data from 1959:1 to 2004:3. The conclusion is that the Friedman hypothesis cannot be rejected if money supply volatility is modeled explicitly, using models that capture important volatility effects that previous work has ignored.