Drago Bergholt

Monetary policy conference on March 2 and 3 and you can watch it online 🇳🇴! I am responsible for the first day with Jordi Galí, Ayşegül Şahin, Christopher Erceg, Luiz Pereira da Silva, Sarah Hunter, Alan Taylor, Anna Seim, Frank Smets and Sharon Kozicki. norges-bank.no/en/topics/abou…

Noe av mest usportslige jeg har sett i et OL! Franskmannen klart best før siste skyting - med to bom på siste stående - så dundre bare Ponsilouma rett forbi, vinner å jubler 😡😡 Hadde Jaqcuelin fått fullt hus så hadde jo aldri Sverige tatt det gullet?

@3RenChengHu @MattBruenig (i) conditional on sorting people by income, consumption inequality is lower—exactly as you suggest—but (ii) unconditionally, consumption is more unequally distributed than income. That latter point is surprising and a key result. The paper's discussion of Figure 3 should clarify

@3RenChengHu @MattBruenig Thanks for taking an interest in our paper. @MattBruenig is spot on: percentile averages can hide substantial dispersion within each bin. There’s also a distinction between conditional and unconditional distributions. In Figure 3 we present both. We show that:

Wild paper from Norway using their great admin data. norges-bank.no/contentassets/… 1. Consumption inequality is higher than income inequality (as it is driven by consumption shocks) 2. People mostly save to weather consumption shocks, not income shocks 3. Recessions lower inequality

@MattBruenig Thanks so much, @MattBruenig — really appreciate your interest in and sharing of our work! 🙏 For those curious about more details on the paper, my coauthor @francescofurla8 has put together a helpful thread here: x.com/francescofurla…

@J_Meanwell @francescofurla8 the car breaks down, a leak appears, I may visit the dentist... At longer horizons, however, consumption vol. becomes more aligned with income vol. (as lifetime BCs start to matter). For more details, see Figure 5 and the discussion in the paper.

@J_Meanwell @francescofurla8 Thanks! You’re absolutely right that time aggregation matters. However, our data show that consumption vol. > income vol. even more at shorter horizons. I believe that makes sense ex post: over the next few months I know my income fairly well, but unexpected expenses can pop up:

🥁🥁NEW WORKING PAPER ALERT 🥁🥁 Consumption Inequality, Household Risks, and the Business Cycle with @DBergholt and Lorenzo Mori norges-bank.no/en/news-events… New and surprising results on consumption! #EconTwitter 1/N

Excited to see our new @NorgesBank WP out! Using Norwegian admin data, we show that consumption is (i) more unequally distributed than income across HHs, (ii) more volatile than income within HHs, and (iii) that rich HHs cut more income and consumption than poor in recessions!👇

Let me explain why I believe modern economics is such a powerful tool for understanding the world. I’ll do this by discussing a great paper by Simone Cerreia-Vioglio, @UncertainLars, Fabio Maccheroni, and Massimo Marinacci, “Making Decisions Under Model Misspecification,” published in the Review of Economic Studies a few months ago. Imagine I want to drive from UC San Diego to UCLA, but I’ve never driven that route before. I need to build a “model of the world” to guide me, which we usually call a map. Maps are simplified representations of reality. They can’t include every detail if they’re to be useful. Borges, in his short story On Exactitude in Science, makes this point beautifully. (In practice, I don’t draw the map myself—I use an app—but someone still had to make it.) Because maps simplify, I can’t fully rely on them. Maybe last night’s storm knocked down a tree and closed a street, or there’s construction and the ramp off the highway in LA is shut down. This uncertainty matters. Suppose I’m driving to UCLA for an important talk at 11 a.m. If the ramp is closed, I might need 15 extra minutes. When should I set my alarm to arrive on time, while still getting enough sleep to give a good talk? The problem is that I can’t assign precise probabilities to all these contingencies. How likely is the fallen tree? Or new roadwork? Even the best traffic apps can’t capture every disruption, and some might happen after I’ve already left. In economic terms, my “model of the world” (the map) is misspecified—and no matter how hard I try, I can’t fully fix that. But sitting down and crying about misspecification doesn’t answer my basic question: when do I set the alarm? Too early, and I’m exhausted. Too late, and I’m late. Simone and his co-authors offer a way to think about this. They start from the idea that we often hold several structured models of an economic phenomenon, grounded in theory. For example, a central bank might use a standard New Keynesian model and a search-and-matching model of money. Yet, aware that each model is misspecified by design, the bank adds a protective belt of unstructured models—statistical constructs that help it gauge the consequences of misspecification. The beauty of the paper is that it provides an axiomatic foundation for this protective belt (and even generalizes it to include a Bayesian approach). It shows that if a decision-maker’s preferences meet certain conditions —reflecting both rational and behavioral features— then those preferences can be represented by an augmented utility function that formally accounts for misspecification. Crucially, we don’t assume that augmented utility function; we derive it. We start with general, plausible properties of preferences and prove that they imply such a representation. That’s real progress. Instead of writing endless critiques of expected utility or rational expectations (as many have done for decades, with little to show), we now have a formal way to reason about misspecification—precise definitions, clear boundaries of validity, and awareness of what we still don’t know. Take, for instance, a brilliant Penn graduate student on the market, Alfonso Maselli economics.sas.upenn.edu/people/alfonso… His job-market paper pushes this frontier further. He studies cases where a decision-maker not only faces model misspecification but is also unsure which model best fits the data and can’t assign probabilities to them—what we call model ambiguity. In my example, the central bank is unsure whether the New Keynesian or the search-and-matching model fits better, and it worries that both might be incorrect. If you read Simone et al. or Alfonso’s paper, you’ll see how misguided—and, frankly, cartoonish—many of the recent criticisms of economics on X have been. First: the idea that economists don’t understand math or have “physics envy.” The math in these papers is subtle and advanced—utterly different from what physicists do (neither better nor worse, just distinct). An engineer transitioning into economics would find these tools unfamiliar. Second: claims of ideological bias are unfounded. I have no idea about the political views of the authors, and I’d be surprised if anyone could infer them from the analysis—beyond vague guesses about typical academics. Third: This has almost nothing to do with what one learns as an undergraduate, or even in first-year graduate school. If your knowledge of economics stops at an intro textbook, it’s best not to pontificate on the field’s frontiers. Fourth: Is this science? Debating that word’s boundaries is pointless; every definition of “science” breaks down somewhere. The Germans solved this long ago with the idea of Wissenschaft—the systematic pursuit of knowledge, whether of nature, society, or the humanities. By that measure, modern mainstream economics is clearly a Wissenschaft: a disciplined, cumulative, and highly useful effort to understand how the world works. Simone and his co-authors have demonstrated that beyond any reasonable doubt.

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🧵8/ This has clear relevance for policymakers navigating supply shocks, imported inflation, and volatile exchange rates — especially in small open economies. Read the full CEPR paper here: 📄 cepr.org/publications/d… /End🧵

🧵7/ The big takeaway: ✅ Policy coordination is not one-size-fits-all ✅ Sometimes, policy tension is a feature, not a bug ✅ Stabilizer design matters — especially in open economies with inflation and exchange rate volatility

🚨 New Working Paper Alert 🚨 Should monetary and fiscal policy pull in the same direction? Spoiler: not always! Especially not in open economies exposed to supply side shocks… A short 🧵 on our new CEPR working paper👇 @NorgesBank @HandelshoyskBI @cepr_org @voxeu @nberpubs