Charles Steindel

State labor markets were somewhat improved in August. Four states reported a statistically significant increase in jobs—California gained 39,400 and New Mexico  Eight states saw statistically significant drops in their unemployment rate, though none was larger than .2 percentage points. The highest unemployment rates were in  DC (5.7%), Connecticut (5.1%), Oregon (5.1%), California (5.1%), and Michigan (5.0%). Nebraska, New Hampshire, Hawaii, Vermont, North Dakota, and South Dakota had unemployment rates under 3.0%, while  South Dakota’s 2.0% was the lowest in the nation.

Puerto Rico’s unemployment rate increased to 6.1%, reflecting a .7% increase in the island’s labor force (July saw a .8% rise), while the island’s job count was up 1,000.

State Labor Markets in August 2026

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Mickey D. Levy

10-year Treasury yields averaged 4.2% in the 12 months ending February 2026. They now hover near 5%, a significant increase. Besides higher oil prices, several explanations are plausible. Real rates have risen associated with the sustained healthy economic growth and higher expected rates of return on investment, particularly reflecting the booming AI buildout that is involving more debt financing. Inflationary expectations have remained generally well-anchored, but market-based measures have risen a few tenths of a percent. And the persistence of budget deficits and projections of ever-rising government debt-to-GDP may be exerting pressure on yields.

This note focuses on oil prices and yields.  As a temporary negative supply shock to the economy, the higher oil prices are supposed to hurt economic activity which may be associated with lower real rates and are not supposed to impact intermediate and longer-run inflationary expectations.  But Chart 1 shows convincingly that short-run movements in WTI oil spot prices (measured in 21-day changes in dollar-per barrel) and 10-year Treasuries (21-day percentage point changes) have been very closely correlated since end of February 2026 when the bombing in Iran commenced. Chart 2 shows that the levels of the Treasury yields and oil prices.

WTI rose dramatically from $65/barrel end-of February to the high-$90s end-of-March, bounced around and rose to $108 in May and plummeted to $70 in early July during the temporary ceasefire and then ratcheted up during the summer to its current above $102. Treasury bond yields rose and fell and rose again with these fluctuations.

260916ML1.jpg

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This note is not to understate my serious concerns about the mounting budget government debt, its plausible impact on interest rates that raises debt service costs, and how the persistent deficit spending is allocating national and financial resources and adversely affecting economic activity. Rather it highlights the sizable impacts the higher oil prices associated with the war in Iran have on treasury yields. A resolution of the Iran war that brings down oil prices would materially lower Treasury yields.

U.S. Treasury Yields and Oil Prices

Paul L. Kasriel

At the recent Jackson Hole annual Kansas City barbecue, Fed Chairman Warsh mentioned that if the Fed had paid more attention to the surge in the M2 money supply in 2021, it might have raised the federal funds rate sooner, which, in turn, might have moderated the sharp increase in consumer price inflation that ensued. Wow! The ghost of Milton Friedman, may his memory be a blessing, must have been talking to Warsh while he was at Stanford’s Hoover Institution. The Fed could do worse than paying more attention to the behavior of the M2 money supply. It could do better, though, by paying more attention to behavior of the sum of the monetary base (reserves of depository institutions held at the Fed plus currency) plus securities and loans on the books of depository institutions (broad thin-air credit). But where Fed Chairman does not quite get it is his continued emphasis on using the federal funds interest rate as the Fed’s operating instrument. If the ghosts of Milton Friedman and Robert Laurent (also, may his memory be a blessing) would have had more séance time with Warsh, they might have been able to convince him to abandon using the federal funds interest rate as the Fed’s policy instrument and instead directly set the level of depository institution reserves such that a constant rate of growth in a monetary quantity, be it M2 or thin-air credit, could be achieved. This would require some institutional changes such as the elimination of interest payments on reserves and the re-introduction of reserve requirements. (See, my August 25, 2026 commentary “[A Modest Monetary Policy Proposal for Fed Chairman Warsh to Consider](https://www.haver.com/articles/a-modest-monetary-policy-proposal-for-fed-chairman-warsh-to-consider)” for a discussion of these necessary institutional changes.)

Let’s compare the relationship between percentage changes in the M2 money supply and thin-air credit with goods/services price inflation. Plotted in Chart 1 are the percent changes in the annual averages of the M2 money supply (the blue bars) vs. the percent changes in the annual averages of the Gross Domestic Purchases chain-price index (the red line) starting in 1960. The highest positive correlation between the two series occurs when percent changes in M2 are advanced (lead) by two years. The correlation coefficient is 0.48. Although a correlation coefficient of 0.48 is a long way from the maximum possible value of 1.00, it’s not bad for government work.

260914PK1.jpg

Now, let’s compare the relationship between percentage changes in “broad” thin-air credit (the sum of the monetary base plus the securities and loans on the books of depository institutions) and goods/services price inflation. Plotted in Chart 2 are the percent changes in the annual averages of thin-air credit (the blue bars) vs. the percent changes in the annual averages of the of the Gross Domestic Purchases chain-price index (the red line), again, starting in 1960. The highest positive correlation between these two series occurs when percent changes in thin-air credit are advanced (lead) by two years. The correlation coefficient is 0.61, better than M2’s 0.48.

260914PK2.jpg

So, whether its today’s percentage changes in the M2 money supply or thin-air credit, history indicates that the largest effect on goods/services price inflation occurs two years later. Chairman Warsh, you could do worse by using today’s behavior of M2 as an indicator of the behavior of inflation two years from now. But you could do better by observing the behavior of today’s thin-air credit. If you really want to go down in the annals of outstanding Fed chairpersons, Chairman Warsh, you will abandon federal funds rate targeting and adopt direct reserves targeting to achieve a constant rate of growth in thin-air credit. If you do this, I predict that periods of excessive goods/services price inflation or deflation will be avoided. I also predict that asset-price bubbles will be avoided. So, assign one of your “task forces” to investigate my recommendations and determine the optimal constant rate of growth in thin-air credit.

Note: I am as tired of writing about thin-air credit as you are reading about it. I believe that the Federal Reserve could do a lot worse in conducting monetary than making the necessary institutional changes that would enable it to achieve a steady rate of growth in thin-air credit. But, to quote my son: “No one listens to me!” So, I will attempt to find other issues to rant about in the coming months.

Chairman Warsh and M2 – He Almost Gets It

Sharmila Whelan

There is little to get excited about in the ASEAN-4 cyclical picture. Westbourne Research is underweight Indonesia across asset classes and has become distinctly more pessimistic about its cyclical and structural growth prospects. It is also underweight Malaysian equities and remains ambivalent about the Philippine and Thai stock markets. On sovereign bonds and currencies, positioning is either neutral or underweight.

Figure 1 shows the business-cycle assessment for the big four. As expected, economic activity slowed modestly in Indonesia and the Philippines in the second quarter. More concerning is Indonesia, where the corporate profit cycle has deteriorated sharply, moving from upswing to downturn, while both investment and credit remain in downswing. The positives are recovering broad-money growth and a falling real cost of capital, despite Bank Indonesia raising policy rates by 100bp since January 2026. In the Philippines, the only material change is the inflation signal, which has turned positive.

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Source: Westbourne Research & Haver Analytics

But weak cycles do not mean an absence of investment opportunities. Valuations matter, as do structural trends and diversification. And one ASEAN structural story deserves considerably more attention.

**700m consumers go digital**

With close to 700m people and combined GDP of around US$3.9trn, ASEAN is the world’s third-largest consumer market by population after China and India. That compares with roughly 450m people in the EU and 350m in the US.

Average per-capita income of around US$5,900 is less than half China’s but more than double India’s—and the average disguises considerable purchasing power. Singapore’s per-capita income exceeds that of the US; Malaysia’s is close to China’s; and Thailand’s is above the ASEAN average. Even Indonesia, Vietnam and the Philippines are substantially wealthier per head than India. Estimates of ASEAN’s middle class range from 160m to 190m people.

Digitalisation is making this enormous consumer market increasingly accessible. Seven of the world’s ten fastest-growing e-commerce economies are in Asia, while the region accounts for two-thirds of global e-commerce sales. Digitally delivered services now account for more than half of global services trade and digital exports have quadrupled since 2005, according to the ADB.

ASEAN itself is one of the world’s fastest-growing e-commerce markets, with online sales reaching around US$185bn in 2025. Three in five consumers already shop online and more than 60% of payments are digital. E-commerce, digital payments, logistics platforms and increasingly AI-enabled supply chains are lowering transaction costs and widening market access.

Investment is following. FDI in ASEAN’s digital economy has tripled since 2020, while the digital economy itself is projected to triple by 2030. UNESCAP estimates that every 1% increase in digital growth is associated with a 0.8% rise in GDP per capita.

The ADB Digitalization Index puts the transformation into context (Figure 2). Singapore leads Asia, while Malaysia and Thailand are digitalising rapidly. The Philippines and Indonesia were still classified as emerging digital markets in 2024, highlighting how much further they have to go. The opportunity is therefore not simply ASEAN’s consumer market today, but technology’s ability to make it progressively more connected, accessible and commercially valuable.

260911SW2.jpg

**ASEAN’s tech revolution is hiding in plain sight**

ASEAN has yet to produce many Alibabas, Tencents, TSMCs or Samsungs. But look beneath the surface and a home-grown technology ecosystem is emerging.

Singapore’s Garena developed Free Fire, which within two years of its 2017 launch was reportedly being played by around 2% of humanity. Shopee has become ASEAN’s leading online marketplace, SeaMoney a major digital-financial-services business and Grab the region’s home-grown ride-hailing champion.

AI is the next frontier. ASEAN-6 companies in AI and robotics had raised a cumulative US$291bn as of January 2026, according to the ASEAN AI Intelligence Hub. In 2025 alone there were 461 new funding deals, with AI start-ups accounting for 42% of funds raised.

The ASEAN-6 now has more than 680 AI start-ups. AI attracted 34% of regional venture-capital investment in 2025, making it the largest sector, while the AI market is projected to grow by almost 28% annually, from US$4.1bn in 2024 to US$30bn by 2030. Since 2024, 127 ASEAN AI and robotics companies have raised capital, led by Singapore.

The physical infrastructure is following. Thailand’s True Internet Data Center broke ground in June on a US$182m AI hyperscale facility in northern Bangkok. More than 2,000 data centres are already operating across Southeast Asia, with many more under construction.

Global capital is piling in. Chinese companies were early movers and four of Southeast Asia’s five most popular smartphone brands are Chinese. The top three e-commerce marketplaces across the six largest ASEAN economies and six of the region’s eight highest-valued technology companies are either wholly Chinese-owned or partly owned through joint ventures. Alibaba Cloud added two Johor data centres in June, taking its Malaysian footprint to five.

China is far from alone. Temasek and Samsung have invested in Vietnam; Nvidia, Apple and Microsoft in Thailand and Vietnam; and Hyundai, LG, BYD, Volkswagen and CATL in Indonesia. More than 350 multinationals operate in Penang, including semiconductor giants Intel, Broadcom and Micron. Japan’s Datasection also began phased operations at its Bangkok-area AI data centre in July–August, deploying 4,696 Nvidia B200 GPUs.

ASEAN may lack North Asia’s household-name technology champions, but it increasingly combines home-grown digital businesses, hundreds of AI start-ups, rapidly expanding data-centre capacity and a growing influx of global technology capital.

**Governments are getting behind it**

Technology investment needs more than private capital. Digital infrastructure, interoperable payments and efficient logistics also require trade facilitation, regulatory harmonisation, data protection and coherent AI policies.

On Oxford Insights’ Government AI Readiness Index, ASEAN performs surprisingly well. Among 195 countries, Singapore ranks seventh, Thailand 34th, Malaysia 38th, the Philippines 43rd, Vietnam 45th and Indonesia 46th. Whatever the precision of individual rankings, the broader message is clear: the major ASEAN governments compare favourably with most emerging markets in AI preparedness (Figure 3).

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Source: Oxford Insights & Westbourne Research

Policy is moving quickly. The ASEAN Digital Masterplan 2030 aims to create an integrated digital economy spanning AI, data, digital infrastructure, cybersecurity, cross-border data flows, start-ups, Industry 4.0 and digital skills. Crucially, it explicitly links digital transformation with maintaining ASEAN’s position as a global manufacturing and logistics hub.

National strategies differ. Singapore is pursuing the most comprehensive approach, committing more than S$1bn to AI R&D between 2025 and 2030 and up to S$150m to its Enterprise Compute Initiative. Its National AI Impact Programme aims to help 10,000 companies deepen their use of AI over three years.

Malaysia is combining industrial policy with foreign capital. AWS, Microsoft, Google and Oracle have committed around US$16.9bn through 2038, largely in cloud and digital infrastructure.

Thailand is relying more heavily on tax incentives and regulatory reform. Advanced data centres can receive corporate-income-tax holidays of up to eight years, alongside incentives for AI, automation, big data, software and cloud infrastructure. Digital-sector investment applications reached around US$33bn in the first half of 2026 alone.

Indonesia and the Philippines remain further behind. Indonesia is developing its policy architecture through tax incentives, an AI roadmap and proposals for a sovereign AI fund, while the Philippines remains focused on the more fundamental challenge of connectivity and digital infrastructure.

**The investment opportunity**

For investors, the most important point is that ASEAN’s AI revolution is likely to appear in the investment cycle well before it appears in productivity data.

AI adoption requires enormous capital expenditure on data centres, semiconductors and electronics, cloud infrastructure, fibre, power generation, electricity grids and cooling. The beneficiaries therefore extend far beyond technology companies into utilities, industrials, infrastructure and advanced manufacturing.

The ASEAN macro cycle may offer little reason for enthusiasm today. Its digital investment cycle is a different story.

Asia

ASEAN: The Tech Revolution Hiding in Plain Sight

Andrew Cates

The latest round of inflation releases will help determine what central banks do next. A larger question lies behind the monthly numbers. Has inflation once again become more responsive to economic pressure? For much of the decade after the global financial crisis, falling unemployment generated surprisingly little inflation. That apparent flattening of the Phillips curve, the relationship between economic slack and inflation, encouraged policymakers to believe that economies could run hot at relatively little cost. Evidence since 2020 suggests that assumption is now less secure.

This argument complements, rather than overturns, the analysis in [The age of abundance is over](https://www.haver.com/articles/the-age-of-abundance-is-over-and-neither-policy-nor-markets-have-caught-up). That article argued that today’s inflation overshoot largely reflects scarcer labour, energy and productive capacity, none of which higher interest rates can directly replace. The evidence considered here makes a separate point. Even if supply constraints explain much of the current level of inflation, additional demand may now pass into prices more readily than it did in the 2010s. The source of inflation and its sensitivity to demand are related questions, but they are not the same question.

**The evidence from the United States**
The US provides the clearest example. Comparing a real-time measure of economic tightness with inflation one year later reveals a marked break after 2020. Before then, a one-standard-deviation rise in the tightness measure was associated with an increase of about 0.4 percentage points in subsequent inflation. Since 2020, the estimated response has been roughly four times as large, at about 1.7 percentage points (Figure 1). Put simply, inflation now appears to react more strongly when demand presses against the economy’s capacity.

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Figure 1. US economic tightness and inflation one year later, before and since 2020. Source: ISM and BLS via Haver Analytics.

This may have contributed to the decline in US CPI inflation from 9.1 per cent in June 2022 to around 3 per cent by mid-2023 without the recession many forecasters had expected. The easing of supply disruption was also crucial. A steeper relationship means that the demand-driven part of inflation can fall materially when economic pressure eases only modestly. It does not mean that supply-driven inflation can be eliminated without significant economic cost.

The relationship has also changed over time. It was comparatively firm during the expansion of the mid-2000s, flattened as spare capacity opened after the financial crisis, and steepened sharply after 2020 (Figure 2). This pattern suggests that the Phillips curve may itself depend on the state of the economy. Inflation responds weakly when capacity is abundant, but more strongly when labour, energy and supply chains are constrained. A sufficiently large downturn could therefore flatten it again.

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Figure 2. Rolling seven-year estimate of the US response of inflation to economic tightness. Source: ISM and BLS via Haver Analytics.

**Evidence beyond America**
Two objections arise. The first is that the result is peculiar to the US. The second is that it merely captures the pandemic supply shock. Neither explanation is sufficient on its own. Labour-market pressure can be measured using vacancies relative to unemployment, while supply-chain pressure and energy inflation can be controlled for directly. On that basis, inflation has become more responsive to labour-market tightness since 2020 in the US, UK, Japan and Canada (Figure 3). The controls explain a substantial part of the change, confirming the importance of supply disruption, but they do not eliminate it.

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Figure 3. Estimated response of inflation to labour-market tightness, controlling for supply-chain pressure and energy prices. Source: BLS, ONS, Japan MHLW, StatCan, New York Fed and OECD via Haver Analytics.

The estimates should be treated with care. The post-2020 samples are short, and the euro area cannot be included because it lacks a comparable vacancy series. Even so, a similar shift across four different labour markets is harder to dismiss than an isolated US result. It suggests that the forces which kept inflation unusually insensitive to domestic pressure in the 2010s have weakened across much of the advanced world.

**Why the relationship changed**
Scarcity offers a plausible explanation. The global labour supply is no longer expanding as readily, energy has become more expensive and less dependable, and fragmented trade and production networks provide less capacity to absorb an increase in demand. In this environment, extra spending is more likely to encounter a physical constraint and raise prices. Artificial intelligence could eventually expand productive capacity and flatten the relationship again. For now, however, its data centres, electricity requirements and financing needs are adding to demand for scarce resources before the full productivity benefit has appeared.

**Implications for monetary policy**
A steeper Phillips curve restores some potency to demand management, but only against the inflation generated or amplified by excess demand. Higher interest rates cannot produce energy, repair supply chains or expand the workforce. They can prevent supply shocks from being reinforced by excessive spending, wage pressure and rising inflation expectations. This distinction matters when central banks decide how forcefully to respond to an inflation overshoot.

The policy lesson is therefore more demanding than a simple case for tighter money. Central banks have less room than they did in the 2010s to assume that strong employment will have little effect on prices. Yet forcing supply-driven inflation down through weaker demand alone could impose a substantial cost in output and jobs. Policymakers must judge both where an inflation shock originated and whether domestic pressure is propagating it.

The financial-market consequences follow from the same uncertainty, although they are secondary to the policy issue. If inflation responds more strongly to economic pressure, interest-rate expectations are likely to move more sharply with incoming data, and government bonds may provide less reliable protection during inflation shocks. The central conclusion, however, concerns the economy itself. The decline in inflation after 2022 was unusually benign, but it should not be treated as proof that future episodes will be equally painless. In an age of scarcer supply, demand management matters more, while the limits of what it can achieve have become more apparent.

_Methodology: US estimates relate CPI inflation one year ahead to a real-time slack measure based on ISM supplier deliveries, order backlogs and unemployment. Cross-country estimates relate CPI inflation to vacancies divided by unemployment, controlling for the New York Fed global supply-chain pressure index and energy inflation. Post-2020 samples are short. Data via Haver Analytics._

State Labor Markets in August 2026

Charles Steindel

More Viewpoints

U.S. Treasury Yields and Oil Prices

Chairman Warsh and M2 – He Almost Gets It

ASEAN: The Tech Revolution Hiding in Plain Sight

The End of Painless Disinflation