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. If you’re going to talk about economics at all, you need some sense of how magnitudes play off against each other, which is the only way to have a chance of seeing how the pieces fit together.

[M]aybe the thing to say is that higher math isn’t usually essential; arithmetic is.

My own work has become rather less mathematical over the course of my career. When people ask why, I usually say that as I have come to learn more about politics, the “sophisticated” wrinkles have seemed to distract more than they adde

“Seeing how the pieces fit together” requires “some sense of how magnitudes play off against each other.” But, paradoxically, ”higher math” can get in the way of “mathematical intuition” about magnitudes. Formal theory is often couched in purely qualitative terms: under such and such conditions, more X should produce more Y. And quantitative analysis—which ought to focus squarely on magnitudes—is less likely to do so the more it is justified and valued on technical rather than substantive grounds.

I recently spent some time doing an informal meta-analysis of studies of the impact of campaign advertising. At the heart of that literature is a pretty simple question: how much does one more ad contribute to the sponsoring candidate’s vote share? Alas, most of the studies I reviewed provided no intelligible answer to that question; and the correlation between methodological “sophistication” (logarithmic transformations, multinomial logits, fixed effects, distributed lag models) and intelligibility was decidedly negative. The authors of these studies rarely seemed to know or care what their results implied about the magnitude of the effect, as long as those results could be billed as “statistically significant.