Thoughts on the Market

The biggest AI stocks have had a remarkable run – but questions still remain. Our Head of Americas Specialty Sales, Thomas Wigg, speaks with Global Head of Thematic and Sustainability Research Stephen Byrd and Global Head of Public Policy Research Ariana Salvatore about the competition and durability of the investment cycle.
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Thomas Wigg: Welcome to Thoughts on the Market. I'm Tom Wigg, Morgan Stanley's Head of Americas Specialty Sales.
Stephen Byrd: I'm Stephen Byrd, Morgan Stanley's Global Head of Thematic and Sustainability Research.
Ariana Salvatore: And I'm Ariana Salvatore, Morgan Stanley's Head of Public Policy Research.
Thomas Wigg: Today, the rally in AI CapEx beneficiaries has taken a breather in recent weeks on concerns of competition from open-source models, backlash to token-maxxing, and growing political opposition to data center builds.
It's Tuesday, July 7th at 10am in New York.
Let's start with you, Stephen. There's a lot of discussion recently around a backlash at token-maxxing. Essentially, enterprises trying to curtail their high spending on AI tokens from the frontier labs, and, in many cases, shifting to cheaper open-source China models.
Can you first offer some perspective here on the value of tokens for enterprises? I know you have a popular token factory model that walks through the economics of agents.
Stephen Byrd: Yeah, Tom, we do have this model that really walks through token economics, both from the adopter side as well as the hyperscaler side. So, let's do the adopter side.
So, there's a study out that shows a whole range of enterprise use cases of AI, and the average single use case that they identify would save a company about $55 or provide that much benefit. And while we don't know exactly how many tokens it will require, we can make some educated guesses as to a typical token usage to achieve that $55 outcome.
And we know that a typical American model, though this varies a lot, you can think of as the cost per million tokens being in the range of $5 per million. Some will be lower, some will be higher. So, for a few dollars of token cost, an enterprise can generate benefit of $55.
So that doesn't make me overly concerned about token spend and concerns about token-maxxing. I know we're going to get into that, but the foundation here is really good in the sense that enterprise use cases are very much in the money.
Thomas Wigg: How do you think market share ultimately shakes out on tokens? Do the cheaper models overtake the frontier AI labs? Do tokens bifurcate based on the complexity of workloads? How do you think this plays out?
Stephen Byrd: What we continue to see is this relentless pace of innovation and cost reduction. So, the frontier keeps going out – meaning model capabilities continue to increase, and, with that, we see enterprise adoption growing quite a bit.
Long way to say there is a role for both the frontier as well as these open-source models, and we'll continue to see both flourish. What I see is a lot of tokens will be spent on open-source models. A lot of the value will be in the higher end models because that's where enterprises are going to go. Let me give you an example.
I was speaking with one of our programmers about a recent project, and he used a very high-end coding tool, an American coding tool. And for him, that incremental cost of the tokens was very much worth it. And here's a very practical example as to why it makes sense for many enterprises to use the higher end models.
If a coding tool gets one of the thousands of lines of code wrong, the cost to remediate is very, very high. In other words, that incremental cost – in this example I'm thinking of, it's a few dollars incremental cost – is so worth it because if the quality is not there, the cost to any enterprise to go back and remediate is so high.
And that's true in a lot of enterprise use cases, but not in every use case. And what we are seeing is these open-source models that are cheaper will be very good for a variety of more mundane use cases that are still very valuable. That said, what we've seen in data from places like OpenRouter is dollar-weighted, meaning valued by enterprise spend, the vast majority is still the proprietary models.
But even within proprietary models, we could have more expensive and less expensive models. You do not need to go to the frontier. Where I come out on all this is that I'm very confident that the demand for compute is going to exceed the supply. What is difficult to exactly know is who are the winners, what is the exact mix. But the fundamentals of the demand for compute look extremely strong.
Thomas Wigg: So, I think you just gave me the answer, but I do want to bring this all back to AI CapEx. Now, last year, when the market sold off on Deep Seek concerns, the concept of Jevons paradox ultimately prevailed, where the cheaper pricing led to even greater demand and CapEx went higher.
Do you think the same plays out here?
Stephen Byrd: It does look that way very much. And the Jevons paradox dynamic is what we still see today in the sense that as the models get better, what we can do with the models increase, the cost of tokens will keep dropping, the cost of compute will keep dropping.
But let's talk about what might derail that, just to make sure we're thinking about all the risks. If somehow commoditized models could perform at the same level as proprietary models in all situations, then I would feel differently. But I don't see that. What I see is that these newer models really do have capabilities that are fairly breathtaking and that are worth that extra money.
But if somehow, we hit a wall where these models aren't getting better and therefore the sort of the open models are going to catch up, then I'd feel differently about that. This is where Ariana will, will come in in terms of policy and, you know, this comes up a lot when we think about U.S. versus China. How do we think about, you know, access to different models? How do we think about the cost of different models?
What about the risk of appropriation of capabilities by the Chinese firms, for example? That comes up a lot in policy circles. But the base case that I have is this just looks more like Jevons paradox, and there's going to be continued innovation, continued reduction in the cost of producing these services from these models. That looks like more of the same.
Thomas Wigg: Let's shift to Ariana to talk about the political angle here. The cover of Barron's over the weekend was a guy wearing a no data centers T-shirt. And this does seem to be one of the few bipartisan issues of agreement heading into the midterms.
The stat that the article gave was that 75 data center projects worth $130 billion were blocked or delayed in 1Q26, which is equal to the total number for 2025. This is according to Data Center Watch.
Now, most of this is in blue states like New York, Michigan, Illinois, Minnesota considering a statewide moratorium, but you're also seeing Pennsylvania, Arizona, Ohio, parts of Texas restricting tax incentives here.
So as this gets louder into the midterms, how do you think this plays out?
Ariana Salvatore: So, this is definitely one of the big wedge issues, not just for the midterm elections, but for 2028. And to your point, it's expanding into something that's got bipartisan momentum behind it.
Our view is that as long as the Trump administration is in power, something like a federal ban is unlikely to come to fruition. That's because we think the administration is still broadly supportive of the AI data center build-out. And I think even if you were to see a Democrat in office further down the road, that position is the same. And the reason is, it's just too difficult to imagine the U.S. giving up that strategic imperative relative to China.
So, while it is true that voters are against AI, while it is true that you are seeing these sorts of local efforts pick up steam, it's also the case that China is accelerating its own AI build-out – not just domestically, but around the rest of the world too. It's also the case that they are kind of tweaking some export restrictions on inputs for some of these data centers, and those geopolitical realities, I think, are hard to ignore.
So, at the end of the day, there is a broader strategic imperative here that both Democrats and Republicans kind of recognize and get behind. Now, what does that mean in the near term for the build-out? I think it's not that you're going to see a real pushback or moratorium so much as a conditional build-out.
That means you're going to see data centers have to incorporate things like grid modernization in their contracts, agree to longer term investments, for example. Do something that benefits the communities or give it back in some way. And I think that's kind of the policy trajectory in addition to the administration continuing to lean on tech companies to basically, you know, square the circle here and find some way to make this more affordable for, you know, local constituents.
Thomas Wigg: Stephen, let me get your take on this too, because I know you live in the D.C. area, and you have a lot of political conversations like you referenced earlier. How do you think this plays out? Is it a red state versus blue state dynamic?
And if what Ariana says comes to fruition, where it's a conditional build-out in terms of either giving back to the community or ensuring certain prices or certain technologies behind the meter, in front of the meter, does that have implications for certain areas of the market?
Stephen Byrd: Yeah. First, I think Ariana's points were all spot on. I just want to, kind of, build on that and, and dive into it a little more detail.
A few things. The politics are, from my perspective, not being the expert that Ariana is, I find them a little strange – in the sense that at the federal level, we have one dynamic, and at the state and local level, we have a bit of a different dynamic. And what I mean by that is, at the federal level, I think it's becoming increasingly clear just how geopolitically important AI supremacy is.
As these models get more capable, I think it's pretty clear that the Trump administration really sees just how potent these tools are from a geopolitical point of view. So that points in the direction of wanting to support AI and wanting to ensure that the United States has a leading and dominant position in terms of AI capabilities.
Pause there, and then go to your point about, sort of, the local and state level.
Building on what Ariana said, what I see are basically two approaches to data center development. In states where the utility is vertically integrated, meaning they control everything, like Louisiana, I do see a path where – in those kinds of states where the politics are a bit more favorable – you could develop a data center connected to the grid, where the data center developer is paying full freight and then some. Meaning that they are providing back to the community, they're providing sort of net benefits, and there should be plenty of capital to make that work and really support all constituents.
That can work – in a state where the politics work – because utilities are really weather vanes from a political point of view. So, if their state supports data center development, they will more likely support a data center development.
The other approach, though, in many states, whether it's deregulated or it's in a state where the politics are a little less favorable. Which, to your point on the cover of Barron’s, it's a lot of states, what I'm increasingly seeing is that the developers are going to go off grid. And they just don't want to show any impact to the community that could be considered negative.
So, no use of water, no use of power, and hopefully have a, you know, low or zero emissions profile to show no impact at all. Even then, you want to give back to the community. But the view there is, look, we want to sidestep all of these concerns that we might be causing impacts to the grid by just not being connected.
So, I think we're going to see a whole lot of off-grid data center projects. That's mostly natural gas turbines and fuel cells, that general approach. Energy storage will be required in a big way.
That's not easy to do. So, in the context of delays there, the Bitcoin players who do have grid access today are clearly seeing a lot of demand for their products.
So, I would say politics is now a huge issue that's showing up.
The other thing I'd flag is often local communities and states are rejecting projects and using permit requests as a way to do that. So, for example, if your data center needs an air permit because your turbines are going to emit some kind of an, you know, sulfur dioxide, et cetera, into the air, you can run into trouble there. If your data center requires water and you need a water permit, you can run into trouble.
So, that's causing these developers to try to find approaches that really minimize or eliminate the need for those kinds of permits.
Thomas Wigg: Stephen and Ariana, thank you for taking the time. And to our audience, thank you for listening. If you enjoy Thoughts on the Market, please leave us a review wherever you listen to the show and share the podcast with a friend or colleague today.

A changing macro backdrop is creating new opportunities across the equity market. Our CIO and Chief U.S. Equity Strategist Mike Wilson looks at what's driving the shift and where it may lead next.
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Welcome to Thoughts on the Market. I'm Mike Wilson, Morgan Stanley’s CIO and Chief U.S. Equity Strategist.
Today on the podcast I’ll discuss why I think the broadening out in equity markets can continue.
It's Monday, July 6th at 11:30 am in New York.
So, let’s get after it.
Let’s talk about a market dynamic that’s becoming harder to ignore. The broadening trade is back, and it’s gaining momentum partly because one of the most crowded areas of the market – Semiconductors – is finally starting to lose some of its own.
To be clear, this doesn’t mean the AI cycle is over. However, trends don’t move in straight lines, and leadership can ebb and flow; especially if there are fundamental reasons supporting it. In fact, we’ve seen this happen several times already over the past couple of years with the hyperscalers and semiconductors ebbing and flowing. This is based on positioning, the rate of change on expectations for capex and the returns on that capex.
Meanwhile, our broadening call goes back to last November. Back then, we argued the economy had entered a new expansion after the rolling recession ended in the April of 2025. That view was based on a classic early-cycle setup where revenue growth returns to companies that had become cost efficient. That is the definition of operating leverage and that always leads to better than expected earnings growth – the core differentiation to our original outlook this year.
The market started to discount that broadening late last year and into early this year. Then, the Iran war interrupted it. Oil prices surged, and the bond market went from pricing Fed cuts to pricing hikes, and investors crowded back into the obvious AI capex winners – especially Semiconductors.
That made sense for a while. The revisions in Semis were spectacular. But when earnings revisions breadth gets pressed against historical extremes, the question becomes less about whether the story is good and more about whether the rate of change can keep improving. That’s a much higher bar. And over the past few weeks, the market seems to be asking that question with semiconductor stocks fading.
The underperformance in the hyperscalers was probably the first signal. Semis depend on hyperscaler capex, so when the spenders start to lag the beneficiaries, that divergence can’t last forever. It usually ends up reconciling with hyperscalers’ tempering capex guidance or indicating they are more focused on getting a return on that investment. META’s announcement last week that it would begin selling excess capacity to outside customers fits right into that discussion. It doesn’t kill the AI buildout, but it does change the market’s perception of how linear that buildout will be.
What matters for investors is how they should trade it.
First, the market should continue to broaden out. Second, we continue to favor Consumer Discretionary Goods, Transports, Regional Banks, and now Biotech as part of that rotation. Discretionary Goods remains the cleanest expression, in my view, because the wallet-share shift from services back to goods is underway, goods pricing is improving, oil prices have fallen, and earnings revisions are strengthening. Transports are also showing better revisions, and Regional Banks still benefit from the broader recovery, improving loan growth dynamics and our call for a re-steepening of the yield curve.
Biotech deserves more attention here, too. It is also one of the most rate-sensitive areas of the market, and our work shows it has historically done very well in falling-rate regimes. If the market’s policy expectations are too hawkish – and I think they are – then Biotech offers an attractive risk-reward setup, particularly with an M&A cycle that continues to build.
The Fed is part of this story as well. Chair Warsh’s comments last week that inflation risks have come down should matter, especially after the weaker labor data that came out Thursday. The market had become too hawkish on policy. If falling energy prices and contained core inflation allow the Fed to stay on hold rather than hike, that should help lower rate expectations and further support broader leadership in equity markets.
Bottom line, the major averages may stay choppy because Semis are a large part of the index and crowded. But, the message is improving beneath the surface. The broader market performance indicates a broader economic and earnings recovery may just be beginning. The best news is that this view is still out of consensus, which means the opportunity for investors remains significant.
Thanks for tuning in; I hope you found it informative and useful. Let us know what you think by leaving us a review. And if you find Thoughts on the Market worthwhile, tell a friend or colleague to try it out!

As America nears its 250th birthday, our Global Head of Fixed Income Andrew Sheets looks back at the early republic as a volatile frontier market, and what its path from credit risks to durable institutions can teach investors today.
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Andrew Sheets: Welcome to Thoughts on the Market. I'm Andrew Sheets, Global Head of Fixed Income Research at Morgan Stanley.
Today, markets are closed for the observance of 4th of July. But as America approaches its 250th anniversary, we take a look back to look forward at early America as a frontier market.
It's Friday, July 3rd at 9am in Seattle.
If you were a global investor at the end of the 18th century looking for a stable, low-risk home for your capital, it would have been entirely reasonable to avoid the newly minted United States of America. By the standards of modern finance, the young republic was not a developed market in waiting. It was a frontier economy: volatile, debt-burdened, institutionally fragile, resource-rich, politically combustible, and astonishingly unequal.
Its currency had collapsed. Its public finances were suspect. Its citizens resisted taxation, and its growth prospects were extraordinary. In 1810, 70 percent of the country was under the age of 25.
That is one of the revelations of Gordon Wood's Empire of Liberty, which focuses on the early days of the new country from 1789 to 1815.
Wood's America is not the marble republic of statues and myth. It is speculative, messy, and full of motion. The United States succeeded not by escaping the dysfunctions that we associate with emerging or frontier markets, but by turning them into sources of strength.
Start with capital. Early America needed it desperately. Roads, canals, land purchases, and government all required credit, and there was never enough of it. The country was rich in land and poor in liquidity, a classic emerging market mismatch.
What the young country couldn't borrow or invent, it misappropriated, lifting intellectual property from its former masters in Britain. What Alexander Hamilton understood was the importance of confidence given this challenge; that debts would be honored, contracts enforced, and taxes, however unpopular, collected.
His financial program was an attempt to solve the emerging market problem before the phrase existed. How to persuade investors that a new state, born in revolution and nearly bankrupted by war, could be trusted. To Hamilton, public credit was the foundation of independence.
To many Jeffersonians, however, this system looked like an attempt to smuggle a British financial order back into the country that had just fought to expel it.
The early republic's debates over debt, banks, speculation, and taxation sound contemporary because the underlying question is perennial in frontier markets: Can a society embrace credit and foreign capital without being captured by it?
The U.S. was not starting from zero. It inherited legal traditions, habits of self-government, and a culture of contract and property. Those foundations gave confidence that disputes could be adjudicated, debts pursued, and rules would not be arbitrary.
Early America was risky, but it was not lawless. And still, it did not go smoothly. There was no Federal Reserve, FDIC, or even a uniform national currency. Business was conducted with foreign coins, notes issued by private banks, IOUs, and blind optimism.
Bank failures were common. In 1808, the Farmers Exchange Bank of Rhode Island issued over $600,000 of notes against less than $90 of gold in its vaults. You almost have to admire the audacity.
Yet the same instability that made early America risky also made it unusually open. Land was the country's great asset class, a source of migration, ambition, speculation, and opportunity, at least for white settlers. It also produced bubbles, administrative strain, the expansion of slavery, and the violent dispossession of Native peoples.
The Louisiana Purchase in 1803 was a risky, leveraged acquisition of distressed real estate, doubling the scale of the American experiment before anyone had quite figured out how the original version was supposed to work. Wood is especially good on the familiar energy unleashed by this world.
The engine of U.S. growth was not an aristocracy of polished grandees, but the "middling sort." Shopkeepers, artisans, tavern owners, mechanics, farmers, merchants, and speculators – many convinced that in America, birthright mattered less than hustle.
Commentators of the time complained about the degraded press, political polarization, hostility to expertise, and the vulgarity of a society obsessed with getting ahead. None of this sounds especially distant.
What saved America from the usual traps of frontier economies was not immaculate stability. It was adaptability. Its constitution was amended. Political power changed hands despite animosity.
Bankruptcy laws allowed for failure. Competition was ferocious, and economic power was generally too diffuse to be easily monopolized. The early republic's genius lay less in solving its contradictions than in creating ways to fight over them without destroying the whole.
That is a useful lesson for America at 250. We tend to look backwards for reassurance, imagining that the country once possessed a unity, prudence, and institutional solidity that we have since lost. Wood suggests something different, that the United States was turbulent from the start.
Its legacy was contested, its finances distrusted, its politics venomous, its expansion intertwined with slavery and Native dispossession, and its future uncertain. Emerging markets become developed markets not because they stop having crises, but because they build credibility through them. They learn which institutions matter, which bargains endure, which debts must be paid, and which moral liabilities compound when deferred.
America was not born orderly, rich, or secure. It was born in the mud, financed on fragile credit, driven by speculation, and sustained by an almost irrational confidence in the future.
So, enjoy the fireworks – and let them be a reminder that national maturity is not the absence of volatility. It's the capacity to turn that volatility into renewal.
A postscript: Gordon S. Wood died in early June of this year. As a professor, author, and one of the preeminent scholars of the American Revolution, he brought fresh insight and deep humanization to the country's founding. For anyone looking for a better understanding of America as it celebrates a big anniversary, we'd wholeheartedly recommend his work
Thank you, as always, for your time. If you find Thoughts on the Market useful, let us know by leaving a review wherever you listen and also tell a friend or colleague about us today.

Following meetings across Europe and Asia, our Global Head of Cross-Asset Strategy Research, Serena Tang, discusses two of the main themes on investors' minds: uncertainty around U.S. monetary policy and increasing caution toward AI despite its long-term potential.

Serena Tang: Welcome to Thoughts on the Market. I'm Serena Tang, Global Head of Cross-Asset Strategy Research at Morgan Stanley.
And today, I'm bringing you a debrief from my investor meetings across Europe and Asia, and the key debates around AI and the Fed.
It's Thursday, July 2nd at 10am in New York.
The last two weeks, I have been traveling in Europe and Asia to meet with investors to discuss Morgan Stanley's latest views. Two themes dominated nearly every room I walked into.
The first is the Federal Reserve and monetary policy path in the U.S. Many investors had interpreted Chair Kevin Warsh's June FOMC meeting, his first at the helm, as unambiguously hawkish. What market investors at my meetings pointed out is that [the] Fed's Summary of Economic Projections – commonly shortened to SEP, which details policymakers' forecasts for macro metrics like GDP growth, inflation, and the federal funds rate – added a hike in 2026 and pushed out rate cuts, implying more restrictive policy.
Now, Morgan Stanley's economists think that hikes implied by SEP at the June FOMC meeting should be interpreted with caution. The projections appeared conditioned on elevated near-term inflation and may not capture the disinflation from a straight reopening. We actually anticipate a lower path for core inflation given a combination of a reversal in travel-related inflation and tariff payback, which lead to our call that the Fed remains on hold through 2026.
The second recurring theme in meetings with investors across regions is, unsurprisingly, AI. While in every single meeting investors believe firmly in the secular story of ongoing AI CapEx cycle, there was some unease – especially since AI is now also becoming an inflation story on the macro side and a funding story on the micro side.
Chipflation is a new word in town, with markets still debating whether it can be one of the things that derail the AI CapEx cycle. In our economists’ and sector analysts’ views, it's more nuanced. While memory price is up sixfold over the past year, we think chipflation is more likely to reprice and ration AI infrastructure than derail the cycle.
AI demand is scaling across three layers at once, more memory per chip, more chips per system, and more systems per cluster, while hyperscalers remain first in the allocation queue. Now, the key risk is CapEx efficiency. Memory is becoming a larger share of the AI system cost, but the cycle, we think, remains intact.
As for AI funding needs, the debate with investors has been how much more can it accelerate? It's worth noting that the majority of corporate bond issuance quarter-to-date has been related to funding construction of data centers.
Hyperscale’s have been broadening their investor base through non-dollar issuances. They have collectively issued around $25 billion of debt in other currencies like euro, Swiss franc, and the [Japanese yen] in May.
Our credit strategy colleagues forecast nearly another $600 billion of AI-related global issuance in 2026; meaning for U.S. IG corporate bonds alone, we expect one trillion of net issuance, a reason for our view that the asset class can underperform this year. With our equity colleagues estimating hyperscaler cash CapEx to surpass $1 trillion in 2027, we expect issuance to accelerate.
Bringing it all together, investors globally are all grappling with the same uncertainties around the Fed and AI CapEx, which will likely continue to be key debates to come. But Morgan Stanley's base case view of lower inflation driving the Fed to stay on hold and a strong AI CapEx cycle that remains intact means we recommend investors should still stay constructive on risk assets.
Thanks for listening. Let us know what you think by leaving a review. And if you enjoyed the podcast, please share Thoughts on the Market with a friend or colleague today.

With voters focused on prices and the economy, our Head of Public Policy Research Ariana Salvatore and U.S. Thematic Strategist Michelle Weaver discuss the consumer trends that could matter most heading into November’s elections.
Read more insights from Morgan Stanley.

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Ariana Salvatore: Welcome to Thoughts on the Market. I'm Ariana Salvatore, Morgan Stanley's Head of Public Policy Research.
Michelle Weaver: And I'm Michelle Weaver, Morgan Stanley's U.S. Thematic Strategist.
Ariana Salvatore: Today, we'll be talking about the consumer and what recent data could imply for the midterm elections.
It's Wednesday, July 1st at 10am in New York.
Last week, Mike Zezas and I caught up on the consumer while he was down at our Consumer Captains Conference. This week, Michelle, I want to talk to you about what your data are saying and get into the implications of all of this for the midterm elections.
So, maybe we start with the AlphaWise data. What are our surveys picking up when it comes to how the consumer feels about the outlook in the aggregate?
Michelle Weaver: We run a monthly proprietary survey of around 2,000 U.S. consumers, and it's diversified by age, gender, and region, and we ask questions around sentiment, spending plans, and other special topics. Our survey recently showed a continued gradual recovery in consumer confidence in the U.S. economic outlook.
We're not off to the races by any means, but we did see the net outlook score improve to -10 percent, up from -14 percent a month ago and a low of -18 percent two months ago, when concerns around oil prices were at their peak.
Overall, more consumers feel negatively about the economy versus positively, hence that net score is negative. But we are seeing signs of improvement, so things are improving on a rate of change basis.
Ariana Salvatore: That makes sense given the MOU that was signed between Iran and the U.S. Now, looking forward, what does the survey tell us about spending plans?
Michelle Weaver: Broadly, consumer spending plans remain stable. They expect to spend more on essentials categories. This includes things like groceries, gas, and household items, while they're expecting to spend less on discretionary categories. We saw the weakest spending intentions within the consumer electronics category, and consumers are not likely to see much price relief in that category. Many consumer electronics makers are now taking their prices up because of the high price of memory chips that goes into those products.
Ariana Salvatore: One of the most important components of the survey is the question that you ask on top areas of concern. What are you guys seeing there?
Michelle Weaver: Inflation is still the number one concern for consumers, and we actually saw the percent of consumers citing it among their top concerns tick up again last month. So, now that's at 60 percent, up from 59 percent last month, and a low of 53 percent in January. People are also worried about the U.S. political environment. That was cited by 42 percent of consumers, up from about 39 percent last wave. Concern around geopolitical conflicts rounds out the top three, but that level's been pretty stable around 25 percent.
But Ariana, can consumers expect any relief on prices from the policy front? Consumers got a nice boost from tax refunds. Is there anything else in the pipeline?
Ariana Salvatore: So, we've gotten this question a lot into the midterm elections, and our view is basically that there are a number of obstacles in the way of something like another reconciliation package to give direct stimulus to consumers, whether that's procedural, whether it's the political perception.
One of the most important is actually the deficit concerns, right? So, we don't expect something additional for the consumer through the legislative angle, aside from what we've already seen, like the Road to Housing Act. And that's also against a backdrop of what we've been seeing on the economic side and what your data is reflecting, which is that the consumer sentiment metrics are actually ticking up slightly from their lows. And that, of course, maps directly onto what our U.S. econ team has been saying.
Their view is that the consumer story in 2026 has turned more neutral. Real consumption growth is still expected to decelerate to about 1.7 percent. That's below last year, but again, not falling off a cliff. The core dynamic is that the One Big Beautiful Bill Act had this fiscal boost from last year, tax refunds running about 17 percent higher year-over-year, but the oil shock basically mitigated that and essentially neutralized the fiscal impulse.
But that's not hitting everybody equally. Goods spending tends to bear the brunt. Our econ team estimates that the oil shock takes 30 basis points off consumption entirely from goods rather than services. Low- and middle-income households are most exposed since energy makes up over 8 percent of spending for the bottom income quintile versus under 5 percent for the top.
And that broadening out story from just the high-income consumer driving spending is probably going to be a little bit delayed just given the oil shock.
But maybe let's drill in a little bit more on that income bifurcation. How does that manifest in your view across spending intentions?
Michelle Weaver: Mm-hmm. Overall, short-term spending intentions – so spending plans over the next month – are net +20 percent this month. That's still above the historical average of around +16 percent, but it is down somewhat from 23 percent last month. And the divergence is really driven by income. Upper-income consumers remain meaningfully more optimistic, while lower-income households are still under stress.
So, we're still seeing the K economy very much in place. And the economy and inflation are almost always top issues for voters. How are you expecting the dynamics we've been talking about to impact the midterms?
Ariana Salvatore: So, data are showing an uptick, obviously, which should on net benefit Republicans all else equal, albeit off a low base. And that's because there are other data points to consider here. So, things like the generic ballot, things like historical precedent, things like the presidential favorability ratings – all of those things are painting a more constructive backdrop for Democrats heading into November.
But also, to put a finer point on it, we're seeing the AlphaWise data that you're citing reflected across other surveys as well. So, we saw the UMich data from last week show the year ahead inflation outlook drop to 4.6 percent from 4.8 percent. And of course, that's a reflection of the expectation that gas prices are going to moderate into November too.
Now, on that front, it's about rate of change, right? So, not the absolute level. But again, I would just remind our listeners that this is one factor in the context of many.
So, net-net, we definitely still see a slight advantage for Democrats heading into November, especially when we drill into some of the trends that we've been seeing across the primaries.
Michelle Weaver: And what are some of those trends you've been picking up from the primaries?
Ariana Salvatore: So, the first thing I would say is that we're cautious to extrapolate too much from primaries to the general election, but really maybe two key points here. The first is turnout seems to be an early indicator in favor of Democrats. So, enthusiasm is up. We're seeing more participation and more engagement relative to prior elections.
The second point I would make is that the primaries have been showing a mixed bag in terms of candidates for November. So, in some states like New York and Colorado, you saw more progressive candidates win their races. And all else equal, that could translate to more of what we call a fragile instead of a cohesive majority come November.
So, think more political noise around fiscal deadlines, things like appropriations and the debt ceiling. But of course, we still have less than 50 percent of the primaries, so plenty to watch heading into the fall.
Michelle, thanks for taking the time to talk.
Michelle Weaver: Thanks for having me.
Ariana Salvatore: And thanks for listening. If you enjoy the show, please leave us a review wherever you listen and share Thoughts on the Market with a friend or colleague today.