At a recent blogger conference, I was asked to name the most important paper published in my field (macroeconomics) in the last decade. I can’t think of anything.
In some ways, that is a reflection of the fact that the field has moved away from the great 20th century research with which I am most familiar. My ignorance may say more about me than it does about the macro field. In desperation, I suggested that Paul Krugman’s 1998 Brookings paper (Baack said . . . ) the most recent one that I can remember has a big impact on the way we think about macroeconomics. A few years ago, I wrote a paper discussing how the important “Princeton School” of financial economics was heavily influenced by this paper.
Many smart economists continue to do sophisticated research on money/capital. And yet I rarely see new papers that seem interesting to me, at least in the way that many papers from the last half of the 20th century seemed interesting when they were first published. And it’s not just a macro. Casual art fans like myself are familiar with hundreds of famous paintings from 1880 to 1924, but very few famous paintings from 1980 to 2024. Why is that?
Tyler Cowen recently linked to an NBER working paper on Joel P. Flynn and Karthik Sastryx, looking at how optimistic and pessimistic narratives can contribute to the business cycle. On a technical level, the 134-page paper is far beyond anything I’ve ever done, covering hundreds of mathematical calculations, some complex. Here is an excerpt from the conclusion:
If we measure the model to match the data, we find that the effects of the business cycle of the stories are very important: the estimated decrease in the trust account is about 32% of the decrease in the result of the result in the early 2000s and 18. % over the Great Recession. Finally, we show that the interaction of many simultaneous and highly contagious factors, some of which are prone to hysteresis, can nevertheless be subject to stable fluctuations in the resulting prospect and outcome. Taken together, our analysis shows that narratives may be an important cause of the business cycle.
Their work uses a “real business cycle” framework, which I have some doubts about. It’s not that these types of RBC don’t tell us important things about the economy, rather I believe that (at least in the US) real shocks are more important as determining long-term trends, not business cycles. (Since Covid is different.)
I’ve only tested the paper, so I can’t give an opinion on their firm ratings, but this caught my eye:
Our analysis opens up at least two important areas for future study. First, we analyzed how important corporate news is and moved away from studying household news. It seems plausible that similar mechanisms may apply on the domestic economic side, where contagion narratives may influence spending and investment decisions. Furthermore, the changing narratives on both the “supply side” and the “demand side” of the economy may have mutually reinforcing effects. From this perspective, the narrative has the potential to explain even more about the business cycle than our analysis suggests.
I like this observation, as I have long believed that the most important effect of (real) supply shocks is how they interact with (normal) demand shocks. So the real housing/banking shock in 2007 probably depressed the natural rate of interest. The Fed fell behind the curve and cut rates too slowly (especially in 2008.) This led to a decline in nominal GDP (less demand), making the recession worse.
They conclude with an almost obligatory request for further research:
Second, much remains to be learned about what “makes a narrative a narrative”—that is, in the language of our model, what constitutes a collection of stories and their transmission? A rich study of these issues can shed more light on policy issues, including both the interaction of mainstream macroeconomic policies and discourses and the potential implications of “narrative management” directly through communication. In addition, exploring this deep origin of stories can advance the study of narrative constellations beyond our analysis, to discover the full economic, semantic, and psychological connections between stories in a complex world.
Will this next study answer those questions? I doubt it. I worry that the next smart couple of big economists will think to themselves, “Flynn and Sastryx have done that, let’s build a different model.” There is probably enough truth in almost any large plausible model that you can find strong theoretical support (at least if you “crunch” the data set enough.)
It’s possible that my skepticism about modern macro just reflects an old guy who no longer cares about the latest developments. I plead guilty. But in the second half of the 20th century, one did not have to read 100-page research papers to understand that macro was producing many revolutionary ideas. I don’t see interesting new ideas being explained in non-technical papers for the layman.
Here is one way to think about my pessimistic thought. I have done a lot of research almost all my life. Soon, I came to the conclusion that US business cycles were very easy. In most cases (not Covid) it was just a question of monetary policy errors causing NGDP fluctuations, and real GDP being more correlated in the short term due to sticky wages.
If you’re going to explain why paintings from 1880-1924 seem more memorable than paintings from 1980-2024, you might point out that painters in the past found many interesting styles, and that they weren’t. many interesting styles that you can find in the past. Another theory says I’m wrong, and that future generations will experience more art from 1980-2024 than 100 years before. Time will tell.
Thomas Kuhn said that in science we often make progress by building models, then we find that there are “mysteries” that are not explained by these models, and then we develop new and improved models to explain that mystery. Perhaps our best models of the late 20th century do a better job of explaining business cycles (and note that the “Fed error” theory I just offered can explain why description does not mean prediction). Perhaps the remaining mystery is more difficult to explain.
But this does not fully explain my skepticism about modern macro. You could argue that we invented it too many good macro models of the second half of the 20th century. We have Keynesian models, monetary models, real business cycle models, Austrian models, MMT models, and many variations within each category. Flynn and Sastryx use the RBC framework in their paper. Because my opinion is that this framework is not very useful for understanding business cycles, from the outside this whole line of analysis seems to be off target. And that skepticism doesn’t just apply to RBC models, in my opinion anywhere the non-market capital model is somewhat lacking. They all seem to be trying to explain something that has already been explained enough. They are not talking paradoxically in a model where Fed errors drive NGDP and create cycles due to sticky wages; they usually work in a completely different framework.
That’s why for a grouchy old person like me, the macro is no longer visible ongoing. We don’t fill in the blanks; we are always trying to reinvent the wheel.
Again, I’m most likely untouchable. All I can say is that I no longer read papers and think, “I always wondered why certain variables (M,Y, P, i, U, etc.) showed this pattern, now it makes more sense.” I don’t see any progress.
But hey, people in 1890 hadn’t seen Van Gogh’s creativity, so I might be missing something important.
PS. Here is a painting by Kandinsky from 1925. What was left to say?
PPS. Here is one of the 247 mathematical equations in the paper:
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