Solutions Economic and Market Watch

Hello, and welcome to the Economic and Market Watch podcast for the week of May 18, 2026. This is Sam Kem of CFC.

My colleagues and I have had this discussion a lot recently. Why does the macro data keep suggesting resilient consumers while consumer surveys tell a completely different story?

It's come up again and again, the disconnect between what the data says and how people actually feel. And today, I want to walk through a concrete example that helps explain exactly what's going on.

A new study from the New York Fed looked at the recent surge in oil and gasoline prices driven by current disruptions in global supply. And what they found is something we've seen before, but much more pronounced this time, a K-shaped pattern in consumer behavior. Here's what it means in practice. Lower income households cut gasoline consumption sharply, around 7%. Middle income households cut somewhat less, and higher income households barely changed behavior at all.

But here's the key twist. Even though lower income households were using less gas, they were still spending more overall because prices increased so much. So they're worse off in real terms because they're consuming less while still paying more. That's the definition of a regressive shock.

Now at first glance, this might look like a niche observation about gasoline. It's not. It's a window into how the entire economy is functioning right now. Because what the study really shows is that different parts of the population are living in completely different economic realities.

On one side, you have higher income households. They're less sensitive to gas prices. They have benefited from rising asset prices, and they continue spending at a steady pace. They are effectively carrying aggregate demand.

On the other side, you have lower income households, highly exposed to essentials like fuel and food, limited financial buffers, and forced to cut back on real consumption. They are experiencing something much closer to an economic slowdown.

That is what people mean when they say a K-shaped economy. Two paths. One group stay stable or even grows, while another group is under increasing pressure. Now here's where it gets really important. Most of our macroeconomic data, the stuff markets and policymakers watch, is aggregated and dollar weighted.

Think about metrics like retail sales, consumer spending, credit card activity. These are dominated by the people who spend the most money. And guess what? That's the higher income group. If higher income households keep spending, the data says the consumer is strong.

But that's only part of the story. Because at the same time, a large portion of households is cutting back, feeling financial strain, and reporting worse sentiment.

That's why you get the disconnect. Hard data looks resilient and soft data, like consumer sentiment, looks weak. And both are actually correct.

It's just that they're looking at the same population with different weighting. One does so at the aggregate level, while the other gives everyone an equal rate.

Most macro data is expressed in real or nominal dollar, so a small portion of the population can disproportionately drive the outcome. For example, just a handful of high growth households or entities can drive most of GDP growth while the rest are behind.

Consumer surveys, on the other hand, are equally weighted. Every respondent counts the same. No single household, no matter how much they spent, has more influence on the result.

Now why does this matter? Because it means we can misread the economy if we rely only on aggregate data.

Strong spending does not necessarily mean a broadly healthy consumer. It might just mean a narrow group is offsetting widespread weakness.

And that has real consequences, because this kind of structure tends to produce sticky inflation as demand doesn't fully collapse, but also hidden fragility because that demand is concentrated. So the economy can look stable right up until something breaks, which brings us to the final question.

If aggregate data can mislead us, what should we do? Aggregate data is still important, but it must be analyzed with the lens of context. In a K-shaped economy, the best indicators are the ones that capture distributional stress. Here are a few examples.

First, real consumption at the low end -- not just how much people are spending, but what they're actually buying in volume, especially essentials like gas and groceries.

Second, credit stress. Rising credit card balances, higher utilization, and increasing delinquencies, especially among lower income borrowers, are early warning signs.

Third, labor market breadth. Headline job growth might look fine, but you want to watch hours worked, working part time for economic reasons, and lower wage sectors like retail and hospitality.

Fourth, trading-down behavior. When consumers are under pressure, they don't stop spending immediately. They shift from brands to private label, from full service to fast food, from premium to discount. That shift tells you more than total spending, especially in the age of inflation when a bill from McDonald's may look like a meal at a full service restaurant in normal times.

Fifth, and maybe most important: What is funding the spending? Is it coming from income, asset gains, or borrowing? Because spending driven by credit cards at higher interest rates is not sustainable.

So stepping back, the key takeaway is this. We're not looking at a uniformly strong or weak consumer. We're looking at an economy that is compositionally strong but distributionally weak. And if you don't account for that, you risk misunderstanding where we actually are in the cycle.

And that's it for today. But before I let you go, this podcast is available on many podcast apps, including Apple Podcasts and Spotify. If you don't subscribe already, please subscribe, rate us, and leave a review.

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