Urbanomics

A graphical summary of India's labour market challenge

noreply@blogger.com (Urbanomics) — Mon, 17 Aug 2026 02:40:55 +0000

I have blogged earlier (see here and here), highlighting the importance of broad-based economic growth and the creation of good jobs as essential requirements for India’s sustained high-growth prospects.

This post has been triggered by two articles. First, a recent op-ed in Business Standard by Kavitha Rao of the NIPFP, which analysed the Periodic Labour Force Survey (PLFS) for the composition of jobs in India and found,

The PLFS classifies information on the composition of workforce into regular workers, self-employed and casual workers and the corresponding wages. The share of regular workers in total workforce was 23.6 per cent in 2025, a little more than half being in government or public enterprises. The self-employed account for more than half (56 per cent), with the remaining being casual workers. The average wage for regular worker was reported to be at ₹22,699, which is higher than the monthly earnings of self-employed ₹14,861, and of casual workers at ₹10,000, assuming a worker works for 22 days in a month. Even among the regular workers, there is considerable variation — over 50 per cent have no written job contract and no social security benefits.
To understand the differences in wages across activities, the survey reports a number of occupation divisions — the ratio of the highest to the lowest wages within regular workers is 4:1. Juxtaposing the highest-wage-earning occupation with casual workers, the differential is 7.4 times, assuming that casual workers get to work 22 days in a month. To top this off, there is a public-sector premium, especially in lower-level jobs. On the other hand, the self-employed category includes a number of unpaid family workers, suggesting significant underemployment in the economy and poor returns to effort. Fewer well-paying jobs and a wage premium for public-sector jobs drive a sharp demand for these jobs.

She also points to the increasingly capital-intensive nature of job creation across sectors, and the convergence of labour intensity in manufacturing with that in services.

Second, The Economist had this graphic on the rising number of graduates and their declining monthly salaries.

Research by the Azim Premji University in Bangalore shows that each year between 2004 and 2023 roughly 5m graduates were added to the workforce; but the number in employment rose by only about 2.8m… Of the young people who report themselves unemployed, fewer than 7% of graduates find permanent salaried work within a year…Education-fuelled aspirations have pushed enrolment in tertiary education to 30% of 18- to 23-year-olds, while the number of higher-education institutions has grown from 6,000 to around 70,000 in the span of 30 years, thanks to a boom in private education… around 45% of Indian graduates have degrees in arts or commerce rather than, say, engineering or medicine. A report by a business body in 2024 estimated that only 55% of India’s graduates were employable.

With this backdrop, I used Claude to dig a bit deeper into the economic growth and labour market. As a framework, broad-based economic growth works at the intensive margin of the labour market to raise disposable incomes, and good job creation works at the extensive margin to expand the meaningful consumption base.

Consider the headline numbers. The employment elasticity of GDP growth has fallen from ~0.4 in the 1980s to 0.26 for 2000–2012 and near-zero by 2019 (RBI 2024 estimate: 0.18).

This is also borne out in the widening wedge between aggregate output and employment growth rates.

The economy needs roughly 20 million new non-farm jobs a year to absorb the demographic bulge, whereas formal-sector job creation runs at about 4 million.

It should be a matter of concern that India, one of the world's largest economies, has one of the smallest formal-sector labour-absorption engines relative to size. It does not help, as I blogged here, that manufacturing’s employment share is stuck at 12%, and every export dollar now buys less domestic employment than a decade ago. As mentioned earlier, the State of Working India 2026 report documents that just under 7% of male graduates secure a permanent salaried job within a year of graduation.

In addition to quantity, another dimension of the extensive margin is the quality of jobs created - i.e., those that pay enough, and reliably enough, to enter the consuming class. Seven rounds of PLFS data (2017-18 to 2023-24) reveal a labour market where employment quantities are rising but quality (measured by contract security, social protection, paid leave, and income sufficiency) has stagnated or worsened for most workers. As a headline number, only 23.6% of workers are regular salaried.

Further, only about 11% are regular salaried with a written contract and social security. Everyone else is either self-employed at very low earnings (56%), a casual daily-wage worker (20%), or a regular worker without protection.

Of the 23.6% who are regular salaried, more than half have no written contract and no social security. It is good that the share of those in regular employment with all three protections has been rising gradually.

The problem is compounded by the quality problem not sparing even the well-educated, and even worsening for them. From 2017-18 to 2023-24, among graduates, precarious contracts (no contract or less than a year) rose from 49.3% to 53.9%; among post-graduates it rose from 38.7% to 44.1%; among technical diploma holders (who should command skill premiums) it rose to 65.8%.

The numbers on quality are likely to be even worse if we exclude government jobs. They have high shares in public administration, education and health, financial services, utilities, and transportation.

On salaries, the average monthly earnings across categories are low enough and vary sharply. The ratio of the wages for regular workers in their highest-paid occupation vs lowest-paid occupation is 4:1, and that for the highest regular vs casual worker earnings is 7.4:1.

The table below captures the summary statistics on India’s employment market today. Only about 11% of India's workersare in the genuinely formal employment cell (regular salaried with a written contract and social security). And within regular salaried work, the 4:1 within-category wage ratio (for regular workers) and the 7.4:1 regular-to-casual ratio mean that even the "good" tier splits sharply.

This brings us to the intensive margin, involving wage trends of existing employees. Are incomes rising for those already in work? Nominal wages roughly doubled 2012–2024 but inflation ate almost all of it. In FY24 corporate profits grew 22.3% and reached a 15-year high.

Real salaried wages fell -4% cumulatively 2012–2024. Real wages for salaried workers were -1.7% lower in Q2 2024 than Q2 2019.

Rural real wages grew about 7% annually in the 2010–2015 period and have been near-zero since.

A decade of near-zero real wage growth means that even the workers who are employed are not getting the income-per-hour gains they need to expand consumption. The corporate sector is booking those productivity gains as profit rather than passing them into wages. This is the "consumption slowdown" that FMCG, auto and durables companies have been reporting from mid-2024 onwards, and is likely caused by the intensive-margin failure documented above. This failure at the intensive margin is a binding constraint to broad-basing economic growth and expanding the consumption class in a substantial manner.

Let’s round things off with the labour-intensity point raised in the Rao oped. The India-KLEMS database shows that labour per unit of capital has fallen steadily across all major sectors, and manufacturing and services have converged to a broadly similar labour intensity. In earlier decades, manufacturing was the obvious job-creation engine because it was more labour-intensive than services. That is no longer true and to that extent diminishes manufacturing value in absorbing agricultural surplus labour.

If labour intensities are similar, the sectors that expands the fastest are the natural venue for large-scale job creation. This points to the importance labour-intensive services like construction, trade, hotels, education, health, etc, as articulated by Rao.

This reality demands a policy strategy that targets improving the quality of education and health services, and increasing their labour productivity. The quality of regulation and formalisation are two instruments in this regard.

To summarise, neither margin is currently operating as India is stuck with quantities of the wrong kind of jobs, qualities that are eroding, and flat real incomes.

India is currently producing high GDP growth without producing either broad-based real income growth or broad-based good-job creation. This means that the growth is not translating into a widening consumption base, which in turn is a binding constraint on the private investment cycle that would generate more good jobs.

Breaking that loop requires action on both margins simultaneously: raising real incomes for those already in work (through productivity gains genuinely passed to wages, and formalisation) and expanding the base of good jobs (prioritising the sectors where labour-intensity remains, and through selective labour-intensive manufacturing where the global window has not fully closed).

India has company in China on the issue of good job creation. An FT long read highlights China’s “great job squeeze”, driving people into low-paying jobs like ride-hailing and food-delivery. This contrasts starkly with the productive factory and construction jobs that underpinned the emergence of China’s middle class and the country’s sustained high-growth era.

The property bust, consumer spending slowdown, and prolonged deflation have taken a toll on job creation. In this backdrop comes the backlash against exports, a major contributor to jobs and economic growth. The result of these trends is a labour market where low-paying gig jobs have become the major source of labour absorption. The number of gig workers has risen by 10 million in just two years.

A precarious gig economy of ridesharing drivers and delivery couriers has been soaking up China’s surplus labour. The labour market has long been at the heart of the social contract between China’s government, eager to maintain stability, and a vast population yearning for economic betterment. Today it is under strain as rarely before. While flexible work has served as an economic escape valve, it too now risks becoming overloaded by more people than it can provide jobs for… More than 53mn people as of 2025 work as food delivery or ridesharing drivers in China, up 10mn in two years… Several municipalities have reported an oversupply of ride-hailing drivers and in June, the southern city of Shenzhen declared its ride-hailing market saturated…“I would say the demand for labour is falling faster than the supply of labour is declining,” says HSBC’s Frederic Neumann, citing automation in factories, the property slowdown and the as-yet unquantified impact of AI…
Andrew Batson, China research director at Gavekal, an economic research firm, suggests flexible employment and gig work are “more of a symptom of broad-based labour market weakness in China than a totally independent development”, even if technology has aided the growth of platform workers. “Because aggregate demand is low, the bargaining power of workers is weaker and they have to accept more underemployment and less favourable working conditions,” he says… “The anecdotal evidence suggests that gig worker incomes are trending towards subsistence levels, given the competition among workers in China for jobs,” says Neumann… Gig work is increasingly drawing in graduates, of whom there are more than 12mn entering the labour market this year, as well as offering options for migrant workers.

In this context, John Burn-Murdoch has an excellent article of relevance which highlights the contrasting tales of US and UK labour markets. He makes the point that while the UK has done better than the US in school learning outcomes and adult skill acquisition (30 per cent of US adults have literacy skills typical of a 10-year-old), the latter has done well in labour market outcomes.

And this shows the higher wages received by US workers (it remains to be disaggregated as to how much of this is due to higher productivity, and how much due to labour market distortions).

Similar to Germany, factory workers in the US earn 60 per cent more than in the UK after adjusting for differences in living costs. Plumbers and electricians earn 90 per cent more, and retail workers earn double. The same proportion of US workers who score stunningly low on literacy earn an average of almost $30 per hour, and two-thirds of them are in work. Their British counterparts make the equivalent of $20 and fewer than half are employed.

Like India, Britain has invested heavily in skill development, and Burn-Murdoch makes a very important point, of relevance to India.

But if we really want to deliver better outcomes, we must stop thinking of particular qualifications or forms of education as things that produce particular economic outcomes and deliver respect. Rather, we should view education as creating potential that a strong economy unleashes (and a weak one disappoints).

The main point is that, if you cut through everything, good job creation is all that matters. And India has much to do on this front, especially with all the headwinds from geopolitics, trade, technology, climate change, and antecedent problems.

Weekend reading links

noreply@blogger.com (Urbanomics) — Sat, 15 Aug 2026 01:00:00 +0000

1. The solutions proposed by Andy Haldane to address housing supply in the UK is universally valid.

Public land developed for public purpose but privately operated; co-financing by municipal bonds and private capital; a bespoke planning regime; and a transformative method of new construction — these are the base elements needed to ease the constraints suffocating the UK’s housing market and to tackle the housing crisis in every postcode.

2. Talk about a company mobilising debt for others to buy its products, and look no further than Nvidia.

The world’s largest financial groups are working with Nvidia to assemble a funding package of more than $500bn for AI infrastructure development, in one of Wall Street’s most ambitious lending efforts to date. A consortium of groups including Apollo Global, Blackstone, BlackRock, Brookfield Asset Management, Goldman Sachs and KKR is entering a partnership with Nvidia to invest in the AI build-out... Nvidia said on Monday afternoon that it has signed memorandums of understanding with the six Wall Street firms to “mobilise over $500bn of third-party capital for the build-out of AI infrastructure over time”. Under the deal, which is still subject to final agreement, the firms will create dedicated pools of capital to finance Nvidia’s AI ambitions “at attractive rates for Nvidia customers”... Morgan Stanley projects so-called hyperscalers will spend $3.5tn between 2026 and 2028.

3. India manufacturing output trends.

But services exports have doubled in less than four years.

4. Israel's scorched earth policy in South Lebanon.

Weeks into the latest conflict, defence minister Israel Katz invoked a different approach, one used with devastating consequences after Hamas’s October 7 2023 attack: the “Rafah and Beit Hanoun model”, a reference to Israel’s wholesale levelling of cities in Gaza. “All homes in Lebanese villages near the border will be destroyed,” Katz said. By July, Katz claimed his threat had been carried out. “Twenty-four Lebanese villages, hundreds of years old, we destroyed all the buildings,” he said, boasting that up to 20,000 homes had been demolished. “Not house by house, but entire villages.”...

Israeli evacuation orders forcibly displaced some 1.2mn people in the war’s first 10 days, the vast majority from Hizbollah-dominated southern Lebanon, as Israeli forces advanced. Fighting raged for weeks, but most of the destruction documented by the FT and Lighthouse came after an initial Israel-Lebanon ceasefire on April 17. While the truce did not hold and some clashes have continued even past the latest ceasefire in June, Israeli forces — who had already established control over many emptied villages — continued to lay waste to the south through air strikes, controlled detonations, bulldozers and the use of white phosphorus. Israel’s occupation is now deeply entrenched, the area under its control demarcated by what it calls “the yellow line”. The zone covers about 6 per cent of Lebanese territory and stretches roughly 10km inland from the two countries’ informal border...

Israel has also done extensive damage to historic monuments and Unesco-listed sites, including 16th-century mosques, 19th-century libraries, religious shrines, ancient Roman ruins and Crusader castles. “It is an attempt to make the areas unrecognisable . . . to sever people’s connection to their land and their history,” said Joanne Farchakh Bajjaly of Biladi, an organisation dedicated to preserving Lebanon’s cultural heritage. “How can they rebuild their communities if everything is gone?”... Lebanon’s environment ministry and rights groups have documented Israel’s widespread use of white phosphorus — an incendiary chemical that triggers fires and can leave contamination in soil and water — in both populated and agricultural areas. Israel says it uses white phosphorus lawfully to clear brush and create smokescreens, but use over populated areas can violate international law.

5. Janan Ganesh is on to something.

If a politician could decouple socialism from the set of cultural ideas known as “woke”, he or she would be difficult to stop... The one place that might have produced a culturally conservative or at least culturally neutral socialism is continental Europe, but even the French left has absorbed American woke jargon, perhaps recognising in it the authorial stamp of Michel Foucault. And so capitalism glides on, never quite facing what would be its sternest political test. The question is why the left allows it to happen... Woke has been such a godsend for capitalism — making its enemies look ridiculous — that it can seem almost engineered for that purpose.

6. Purchase commitments of the hyperscalers jumped from a trillion dollars to 1.5 trillion from Q1 to Q2 of 2026. These are debt in another form.

7. Guy Chazan describes elite capture of the political system in the US.

In America’s Gilded Age, millionaire robber barons operated from the shadows, bribing pliant lawmakers to do their bidding. Under President Donald Trump, billionaires have gone one better. Some are in his cabinet... No longer content to lobby from afar, ultra-rich tycoons — especially from Silicon Valley — have infiltrated the capital’s ecosystem, taking on advisory roles in government, cultivating ties on Capitol Hill and weighing in on the most important issues of the day, from AI to industrial policy. They attend glitzy dinners, donate millions to White House fundraising projects and are photographed with Trump promising eye-popping investments in the US. Many have enjoyed regulatory relief, policies that benefit their businesses and, in some cases, lucrative government contracts worth billions of dollars. But unlike the robber barons of the past, who were often charitably minded and gave generously to public institutions, the tech billionaires of the present show a “complete indifference” to any kind of “social contract” and any need to “compensate people for the disruption they have brought into their lives”, says Quinn Slobodian, a historian of capitalism at Boston University...

If there was a trigger for the growing influence of the ultra-rich in America’s political system, it was the Supreme Court’s 2010 Citizens United ruling, which held that independent political spending on elections by business was protected by the First Amendment. The judgment opened the floodgates to big money in politics. America’s rich had spent $31mn in the 2010 elections, according to liberal advocacy group Americans for Tax Fairness (ATF). In the 2024 election cycle, the 100 largest billionaire donor families gave $2.6bn. A huge proportion of that came from just a handful of individuals. Three billionaires — Elon Musk, Miriam Adelson and Timothy Mellon — accounted for more than a third of the roughly $1.5bn spent to elect Trump.

8. C Thi Nguyen has a brilliant essay on the value of doing something for its own sake or as labour of love (play, as he describes it), and doing something as part of a requirement (work, as he describes it). He channels Aristotle (through Bernard Suits' The Grasshopper) to describe it as the core of a meaningful life.

For Suits, play is not just a side dish for the main meal of work. Play is at the core of a meaningful life. Underneath the hood, Suits’ argument is Aristotle to its bones. For Aristotle, a good life — a truly meaningful life — lay not in the creation or accumulation of stuff or the achievement of outcomes, but in the process of doing itself, in the rich exercise of our full human capacities. Suits found the deepest illumination of Aristotle’s point in the simplest human activity: playing games. Suits provides, and defends, his definition. To play a game, he says, is to voluntarily take on unnecessary obstacles to make possible the struggle to overcome them. To play a game, therefore, is to be inefficient on purpose. When you run a marathon, you are trying to get to a particular spot in space, but you avoid the most efficient ways to get there. You do not take a subway or a taxi or a bicycle. You force yourself to run, and you try to run as quickly as possible. Which means, for Suits, that the struggle must be an essential part of the true value. What you care about can’t just be the bare outcome by itself. You can’t just care about being at that spot in space. Otherwise you’d just take the most efficient path. But if you took the subway then it doesn’t count — not for the game of marathon-running, anyway...

To understand games, distinguish between two things: the goal of a game and your purpose for playing it. The goal is what you pursue inside the game; the purpose is why you played it... For some people, the goal and purpose are one. They want to win, period. Call those people achievement players. The Olympic runner wants to win the marathon by running it — but they do truly care about winning it. But for other people, goal and purpose come apart. We try to win because we are interested in the struggle, and it is the struggle itself that we truly care about. Call us striving players. It’s all right if we try and we lose, if the attempt was beautiful. In ordinary, practical life, we take the means for the sake of the ends. In striving play, we take the ends for the sake of the means. What is the point of life? Is it to make stuff? Or is it to take difficult actions, think rich thoughts, weigh subtle decisions? Is it having a pile of stuff — or does the stuff just support our quest for interesting action?... Suits argues... that play itself is the point, and that we work in order to survive so that we might play...

Rephrase Suits’ definition this way: play is wasting resources for fun. But also: the whole point is that, deep down, it’s not a waste. A truly wasted life would be one spent working hard, stockpiling goods like the ant and never using them to support joyous play. And to truly waste humanity would be to push people so hard to work productively, to make more stuff, to the point where nobody had time to play. Let me try my own fusion of these two definitions. “Work” isn’t distinguished from “play” by difficulty, suffering or practicality. You can make pottery, knit scarves or grow a garden as play. The true difference between work and play is the reason you have, and the control you have, over what it is you’re doing and why. Here’s my suggestion: to “work” is to perform activities to create outcomes that are set by something external. When you work, you are making what the world tells you to make. Maybe you’re gathering food, because biology tells you you have to eat. Maybe you’re earning money, because the world says you need money to buy food and shelter and medicine. Maybe you’re making products, because the world wants something specific from you — planks of wood, a ride to the airport. But “play” is different. You still have goals and struggles, but your goals are up to you.

9. Two important graphics on the Chinese economy. One, the great job squeeze resulting in the rise of the gig economy, whose workforce has increased by 10 million in just two years.

Second, the persistence of negative household sentiment for the fifth successive year.

10. Andrew Puzder, the US ambassador to the EU, draws attention to the substantive equivalence between US tariffs (50% tariffs on primary steel) and the EU's CBAM on their respective steel and aluminium imports.

Protesting against US national security measures while erecting protectionist barriers reveals a striking double standard... The US approach is direct and transparent. Primary steel faces a 50 per cent tariff (with some rates recently increased), and aluminium a comparable duty. To stop circumvention through finished goods, the tariffs extend to derivatives... CBAM differs in form but not in substance. Importers of iron, steel, aluminium and related products must report embedded emissions and relinquish a corresponding number of CBAM certificates priced at the EU’s carbon price — currently around €80 per tonne of CO₂... At root, both policies are adjustments to protect domestic producers from unfair competition, whether from lax environmental rules or subsidised excess capacity. US Section 232 tariffs address foreign overcapacity that threatens to hollow out its metals sector; CBAM is designed to combat carbon leakage, when production shifts to jurisdictions with less stringent climate standards... In both cases, the measures raise the cost of imports to safeguard local production. The parallels are unmistakable. A shipment of steel-containing machinery faces extra US duties based on metal content. In the EU, the same goods face fees based on production emissions under CBAM. One is framed as security policy; the other as climate policy. Both increase the price of targeted imports relative to domestic options.

11. The US equity market today in perspective.

A graphical summary of India's manufacturing challenge

noreply@blogger.com (Urbanomics) — Thu, 13 Aug 2026 03:24:37 +0000

As AI threatens to hollow out commoditised IT jobs that have created a generation of Indian middle class, manufacturing appears even more important for good job creation.

However, manufacturing’s share of GDP has been declining, falling from 17.1% in 2010 to 13.4% in 2025.

Between 2017-25, manufacturing's employment share has remained unchanged at 12.1%!

India could not leverage the opportunity presented by the global value chain diversification away from China. Countries such as Vietnam and Bangladesh have capitalised on labour-intensive manufacturing.

As a result, direct export-related employment fell from 9.5% to 6.5% of total employment (2012–2020, World Bank).

It does not help that India's manufacturing labour productivity is abysmally low.

India’s labour market challenge is two-fold. At the extensive margin, it must produce more good-quality jobs, ones that are productive and also pay reasonably well. The subsistence gig-economy jobs cannot create the middle class required to sustain broad-based high economic growth rates. Manufacturing is critical to this good job creation agenda. At the intensive margin, the existing jobs must become more productive and labour wages must increase proportionately. Export competition is central to increasing productivity.

I’ll blog separately on the labour market challenge.

A template of a localisation scheme for smart meters

noreply@blogger.com (Urbanomics) — Wed, 05 Aug 2026 00:00:00 +0000

I have blogged here and here outlining an industrial policy to promote domestic innovation in electronic products. The policy should identify a few (say, 3-5) products and encourage phased localisation over a five-year policy regime using a combination of targeted incentives and mandates.

No product is more appropriate for such a policy than smart meters, on which India has launched a massive scheme (the RDSS) to replace the existing 200-250 million electromechanical and basic digital meters with bidirectional prepaid meters by the end of 2028. This amounts to almost a 10-year Rs 2.4 - 3 lakh Cr contract. Given that almost all meters are procured by government-owned discoms with the central government subsidy under RDSS, it is a perfect opportunity to use incentives and mandates.

The meters are rolled out largely on a TOTEX model, where private Advanced Metering Infrastructure Service Providers (AMISPs) finance, install and operate the meters over 8-10 year contracts, paid per meter per month (of around Rs 60-80). The AMISPs, in turn, procure the meters from OEMs like Secure Meters, HPL, Schneider, Landys+Gyr, and Genus. The major AMISPs are Adani Energy, Intellismart (now purchased by Adani Energy), Genus, GMR, Tata Power, and Techno Electric. This market concentration, on both the AMISPs and the meter manufacturers, while a risk, also makes it easier to implement any phased localisation policy.

The smart meters are currently assembled in India, with all three major components being sourced externally from foreign suppliers. In terms of its technology, a smart meter is a rugged, always-on computer with three core integrated circuits (plus a latching relay, which is an electromechanical switch rather than a chip). They are the metrology IC (the sensor), the microcontroller unit (MCU) (the brain), and the modem (the voice) of the meter, and they differ sharply in complexity, which makes a phased localisation strategy possible.

Fortunately, India has a few chip design startups who have already commercialised the metrology-plus-processing layer, and with credible domestic microcontroller unit design. The narrowband IoT/4G baseband for the modem is a genuinely hard one, though achievable in a phased manner given the commercial incentives that come with a policy.

The table captures the smart meter components and the current market landscape.

I have blogged here highlighting the entry barriers arising from financing challenges and deployment opportunities (given the lack of Indian OEMs) for indigenous chip design firms to break out in the chip design market. In this context, the massive volume of subsidised smart meters procured by discoms is an unmatched deployment breakthrough for the domestic chip design industry.

This opportunity can be harnessed through a general “product-mission industrial policy” built on four levers: aggregate demand, mandate and phase, bridge OEMs to chip firms, de-risk capital. The 200 million meters (≈600 million chips) is the rarest asset in industrial policy: demand that is enormous, captive, and shaped by the state itself. India is already partway there, having commercialised indigenous meter silicon (Azimuth AI’s ARKA GKT1 and MosChip’s Vidyut).

There are two commercial firms in the smartmeter contract - the AMISPs and the meter OEM. The two parties hold complementary assets - the AMISP holds the bankable multi-year volume and the government’s contractual leverage; the meter OEM holds the design capability and intellectual property (IP). The most incentive-compatible contracting arrangement would be to anchor the mandate in the AMISP/TOTEX contract, cascade execution to the OEM, and pay a per-meter incentive that neutralises the early cost gap. An OEM-only mandate fails on volume, and an AMISP-only mandate fails on capability and gets passed through as cost.

An illustrative localisation phasing and incentivisation is indicated, which would amount to a total subsidy of Rs 1000-1200 Cr, or less than 0.5% of the total project cost and about $1.6 billion of total chip cost over 5 years. The per-meter incentive neutralises the early cost gap, and it tapers off as volume rises. This would amount to localisation of 60% of the chip design for smartmeters. The numbers could be tweaked and finalised after consultations involving all stakeholders - OEMs, AMISPs, and chip design startups.

I am assuming only the localisation of the chip design, and not the fabrication (amounting to about 60% of the chip cost), thereby enabling domestic capture of about $1 bn of chip value besides the development of invaluable chip design capabilities at scale. However, the central government could target even the fabrication of the higher-nanometer chips under the Semiconductor Mission. At the least assembly, testing and packaging (ATMP) could be localised in parallel.

This would be a genuinely end-to-end localisation achievement that can be emulated for certain other products like surveillance cameras, Fixed Wireless Access (FWA) and other customer premises equipment, automotive chips, etc.

The details are important. The target is chip design - ownership of the IP and the front-end engineering - not fabrication. An Indian-designed metrology or MCU chip can be fabricated at a foreign foundry (TSMC, UMC) or, increasingly, at an Indian one (Tata-PSMC, and the Micron and Kaynes/CG packaging lines) and still deliver the objectives of domestic IP, design jobs, security assurance and value capture. Fabrication indigenisation is a different decade-long, capital-intensive problem, albeit achievable now in some degree with the Indian Semiconductor Mission (ISM). For a country which originates 30-40% of the world’s chip-design talent, this is the natural place to start.

To prevent gaming and ‘badge engineering’, ‘indigenously designed’ must be defined tightly - the IP is owned by an Indian entity and the RTL design and tape-out are done in India, verified by a third party - and not an imported design with a domestic label.

The biggest challenge would be to support the domestic startups quickly build design and testing capabilities to meet the large volumes they must commit (including the continuous technology and standards updations). This will require the OEMs and AMISPs working closely with the chip design startups. They could offer some form of advance market commitments to the chip design startups that would allow them the runway to raise capital and finance their rapid capabilities development.

The success of this will depend on its ownership by the Ministry of Power, which would need to work closely with the Ministry of Electronics and Information Technology, which currently run the electronic products and components schemes and the semiconductor mission.

As an important requirement, there should be no relaxation of the quality and standards requirement from the domestic chip designers. They should pass the same accuracy and reliability tests required by incumbents. In fact, they (either directly or through the meter makers) should also be nudged with soft targets on exports so as to create the incentives for maintaining global competitiveness. If they are unable to with all the support, then perhaps it might be justifiable for the government to throw up its hands and reconcile itself to the quality of Indian entrepreneurship.

Some thoughts on private equity in infrastructure

noreply@blogger.com (Urbanomics) — Mon, 03 Aug 2026 05:46:19 +0000

I have written about the problems with private equity (PE) investments in infrastructure. The argument has been that infrastructure is a boring asset with low but stable returns, hardly the kind of asset that would excite high-return investors like PE funds. However, over the last 15 years, private capital has flowed in large amounts to infrastructure assets. And it has resulted in some spectacular failures, most famously Thames Water in the UK and water privatisation in general.

This post will offer an important qualification of this view to avoid the impression that private capital, in general, has no place in infrastructure.

Let’s start with the same UK water sector itself. FT recently reported that the PE group EQT snapped up a 42% stake in strained UK water utility Yorkshire Water’s parent company Kelda Holdings at £9.4bn (with 5.7 million customers in northern England) at 90% of the company’s regulated asset base.

Yorkshire Water… is under close watch by regulator Ofwat, which warned last year that it was “lagging behind” on pollution. Ofwat demanded the company repay a £600mn loan amid concern about its finances and EQT agreed to contribute to the loan’s repayment as part of the deal… In the 30 years to 2024, Ofwat data show that listed water companies were valued on average 10 per cent higher than their regulatory capital value — the asset base on which they are allowed to earn a set return through customer bills. Between 2017 and 2024, stakes in UK water companies sold at a 36 per cent premium to their regulatory capital values, according to a court filing in a Thames Water case. But EQT’s deal for a 42 per cent stake in Yorkshire also demonstrates continuing interest in the sector despite big shareholders in Thames Water previously declaring the largest water utility “uninvestable”… A decision to allow some water companies to raise bills by more than half between 2025 and 2030 was a key factor in EQT’s decision to buy into the sector.

Yorkshire Water’s problems are only a microcosm of those faced by Thames Water, which serves 16 million customers in London, and is trying to stave off nationalisation by the incoming Labour government of Andy Burnham. The heavily indebted Thames Water’s lenders have recently offered a “golden share” to the UK government (similar to that held in Royal Mail) as part of a bid to keep it private and avert nationalisation. The creditors have been in control of the utility since its shareholders walked away in 2024 and have been talking to Ofwat to take formal ownership before it runs out of money by October 2026.

The government is expected to announce whether it will temporarily renationalise Thames Water under its special administration regime (SAR) within weeks. That could spark a legal battle, with lenders appointing law firm Pallas Partners and indicating they would continue to bid for the utility once nationalised… The senior creditors previously offered to inject £3.35bn of new equity into the utility and stump up £3.25bn of fresh debt. The group is also asking Ofwat to waive certain penalties until March 2030 in exchange for a one-off £800mn payment to the business… The group of creditors, which represents holders of about £17bn of the utility’s debt, is planning a stock market listing of the business as early as 2030.

In simple terms, the distressed-debt and PE funds now offering a golden share and pledging to reinvest all profits are being forced back into utility-like behaviour by the credible threat of state administration.

However, it is hard to imagine any scenario through which this restructuring can address the underlying insolvency of Thames Water as an asset. This is merely kicking the can down the road. A sustainable resolution would require significant haircuts for creditors, sharp squeezing of costs, significant maintenance and capex investments, and running the utility on thin margins for long enough to reach a sustainable debt pathway. It is hard to achieve all this under PE management. So this appears to be the latest in the series of pass-the-parcel routine that Thames Water has been going through.

To better understand such investments, the table below shows the likely returns from various categories of infrastructure investments.

If an asset’s true economic return is 4–6% because a regulator sets it, and the private fund must clear a 12–20% net IRR to justify its fee load and honour its LP promise, the ~10-point gap cannot come from operations, which are capped by the regulator. It has to come from somewhere, and there are only four options.

The first option of leverage (i.e. excessive) is fatal in a regulated asset base (RAB) framework since debt-service costs enter the allowed tariff, thereby making the customer pay the interest bill. It is about socialising the financing choice. The second option is tax structuring of the kind that Macquarie did when Thames Water paid no UK corporation tax during its ownership tenure. The third option is to skimp on cost and maintenance by deferring capital investments, stretching maintenance schedules, socialising externalities (sewage, leakage). Finally, there is the option of dividend recapitalisations, multiple arbitrage, and ‘pass the parcel’ secondary sales.

The balance sheet on the UK water sector privatisation over the 32 years is instructive in so far as it exhibits the use of all four options by PE investors. The sixteen monopolies paid out roughly £78bn in dividends against about £190bn of capex. At the same time, net debt rose from zero at privatisation to the £60–72bn range, much of it borrowed to fund the payouts and loaded onto customers’ bills. Thames alone now carries over £19bn of debt - the highest of any UK water company - after a £3bn rescue loan at 9.75%, was fined £123m by Ofwat in 2025 (the largest ever, including £18m for unjustified dividends), and has been allowed a 35% bill rise to 2030 despite losing roughly a quarter of its treated water to leaks. On the investors’ side, Water UK claims £236bn has been invested since privatisation.

Water is representative of several low-risk and low-but-stable-return sectors (also here) in which private capital has been deployed, such as health, education, prisons, veterinary care, and public housing. Research (also here) shows that PE ownership of clinics raised short-term mortality by about 10%, implying roughly 21,000 additional deaths over the sample, while increasing spending by 19%, the vast majority billed to taxpayers, via lower nurse staffing, worse patient well-being, and reduced compliance with care standards. Similar concerns are highlighted in the Indian context in education and health sectors in a recent oped which argued that in the absence of an independent statutory regulator with outcome-disclosure powers, the extraction by PE runs through billing intensity and selective access rather than balance-sheet gearing.

There are some generalisable lessons from the history of PE funds in infrastructure and similar sectors. Wherever four features coincide - an essential service, a captive or vulnerable user who cannot judge quality at the point of purchase, a third-party payer (the taxpayer or the ratepayer), and an implicit public backstop - high-powered return incentives invariably create faultlines.

In this context, as a slight digression, I came across a brilliant articulation by Aswath Damodaran of how alternative investment strategies have lost their way in the quest for scale.

His broader point is that hedge funds, private equity, and private credit… began as a genuinely good niche business solving a real problem. Hedge funds 30 years ago produced positive alpha, beating passive investing by 3 to 5 percent annually. Today they look like expensive mutual funds, underperforming passive by roughly 1.5 percent. Private equity started as a focused, disciplined strategy for a small set of operators and has grown into a sprawling category that now struggles to deliver the returns that justified its emergence. Private credit had a legitimate original purpose, which was lending to borrowers that banks structurally could not serve. What killed each of these businesses was the same disease. Overreach. A $200 billion niche business gets sold as a $20 trillion opportunity. When that scaling happens, sloppiness follows, bad actors enter the space, and the average quality of every participant deteriorates. The original alpha disappears not because the strategy stopped working, but because too much money chased too few good deals.

The danger with private credit is far more severe than the parallel problems in private equity and hedge funds. Equity investors take their losses and move on. Lending businesses, when they overreach, take others down with them. Banks. Pensions. Insurance companies. Sovereign wealth funds. The systemic linkages run far deeper than most participants understand, and the social costs of a real default cycle in private credit would extend well beyond the funds themselves… the industry is repeating the exact mistake that produced every previous credit crisis. Take a good idea, scale it past its natural capacity, attract bad actors with the promise of easy returns, and wait for the inevitable cycle that exposes how much of the underwriting was never serious in the first place.

I have blogged earlier here and here about Ludovic Phalippou’s extensive research on PE returns (here and here). Across three large datasets for the period 2006-20, PE funds delivered net Multiple of Money (net-of-fee) of ~1.55–1.63x, or about 11% annually, matching public equity indices in the same period. During that time, roughly $230bn in carry accrued to a small number of managers, with the number of PE multibillionaires rising from 3 in 2005 to 22 by 2020. Much of the apparent outperformance, he shows, came from choice of benchmark rather than from the returns themselves.

Now, back to our examination of PE in infrastructure sectors.

Given all the aforesaid, investing in infrastructure becomes a rational choice for PE funds. Once the alpha is gone but the fee structure and the promised IRRs remain, reaching into stable, socially backstopped, “boring” cashflows is not a puzzle. It is the rational move. Those assets are attractive precisely because they are low-risk and captive: low-risk cashflows can bear more leverage, and an essential service that the state cannot let fail carries a free option on the public balance sheet. The infrastructure fund is not, in economic substance, buying a low-return asset. It is buying a levered claim on a government guarantee.

In short, a return-maximiser in a regulated essential monopoly is not investing in a low-return asset at all, but it is buying a levered claim on the public balance sheet, which is why it is drawn to “boring” cashflows. Its investment is not despite the low returns, but because low-risk, captive, socially-guaranteed cashflows can support an extraction that competitive assets cannot.

Some important qualifications are in order lest it be seen as a sweeping claim that private capital investment, especially private equity, in infrastructure is uniformly bad.

As I have written here, infrastructure is not one asset class. PE investment becomes problematic when three conditions coincide - a regulated natural monopoly with captive demand; an essential service the state cannot allow to fail; and returns set by a regulator so operational upside is capped. Water and sewerage hit all three. But they do not apply to a large and growing share of infrastructure segments like fibre, data centres, batteries, new technologies etc., where higher returns are legitimately earned by bearing real development, technology and demand risk. There, return-seeking capital is not merely tolerable, but given fiscal constraints, it is arguably necessary, because patient capital typically won’t take the associated construction and demand risks.

The question should therefore not be about the asset’s headline return but its structure. “Should return-maximisers be in low-return assets?” is the wrong question. Instead, “should they own regulated essential monopolies whose returns are capped and whose failure is likely to be socialised?” is the right one.

It must also be acknowledged that it is not the specific vehicle of PE that is the problem. Apart from Macquarie, an infrastructure fund manager and not a classic buyout shop, Thames’s later owners have included pension and sovereign funds (OMERS, USS, CPPIB-type investors), some of which geared just as aggressively. The largest infrastructure owners today are pension/SWF/insurer capital, though much of it is deployed through fee-charging, IRR-targeting fund structures (Brookfield, GIP-BlackRock, KKR). The problem is a configuration - high return target plus leverage plus regulatory arbitrage - that any owner, including a public pension, can adopt.

Finally, there are the issues of competition and regulation. Too much return-seeking capital chasing a genuinely competitive asset pushes returns down toward the asset’s true economic return. However, in the absence of competition, as with captive-customer monopolies with a public backstop and a weak regulator, incentive distortions emerge quickly. Here the deficiency of regulatory competence and/or avoidance of regulatory capture assumes significance.

In conclusion, the problem with private capital in infrastructure arises when there is a combination of return-maximising capital, high leverage, regulator-capped returns, captive users, socialised failure moral hazard, and a weak or captured regulator. This is a recipe for systematic transfer of value from the public to investors through a pass-the-parcel game, presented as investment and public-private partnership.

The policy challenge then is to match the ownership and return model to the asset’s structure, and where the asset is a regulated essential monopoly, regulate the balance sheet, not just the tariff. This aligns with the findings of the UK government’s Cunliffe Independent Water Commission (July 2025), which, apart from proposing the scrapping of Ofwat in favour of a single integrated regulator and nine regional water authorities, also proposed a supervisory (rather than arms-length) regulatory approach and mandatory asset-health monitoring. This goes against the conventional wisdom on regulation and is exactly in line with the patient capital under active public oversight approach proposed in the long paper here.

The main takeaway for India is not to import the UK’s RAB-plus-leverage-plus-socialisation architecture, but to reserve genuinely patient capital (NIIF/NABFID-type, pension, insurer, etc.) for revenue-generating infrastructure assets (or Core I/II from the paper here), admit return-seeking capital only where the asset is genuinely commercial or greenfield and bears real risk, and in TOT-style road or water monetisation, get the discount rate and the balance-sheet ring-fence right before the concession, not after the renegotiation.

Most importantly, these assets should be regulated with active supervision, including of financing practices, and close asset-health monitoring. This is especially important since, when stripped to its bare bones, the binding constraint to the successful management of private investment in any kind of regulated asset is regulatory capacity and independence. Unfortunately, both are challenging, even in developed countries.

Weekend reading links

noreply@blogger.com (Urbanomics) — Sat, 01 Aug 2026 07:36:15 +0000

1. US equity markets fact of the week.

In the year to March 2026, the US received well over $600bn in net equity inflows. Not only was this a record sum, it was also double the flow into government and agency bonds. Net equity flows exceeded debt flows by the largest margin in history.

2. US utilities are shifting from net metering to net billing on rooftop and home solar installations.

Many utilities pay homeowners the same rate they charge for electricity, meaning the energy sent to the grid when the sun is out offsets the cost of the energy pulled from the grid at night. That’s called net metering, a system where the energy you send is worth typical U.S. prices of 10 to 30-plus cents per kilowatt-hour. Under newer policies, often called net billing, utilities buy the extra energy back at a lower rate, often 2 to 10 cents.

3. In a country ravaged by deflation (pork prices have hit a 16-year low), egg prices are rising in China.

Egg prices are up by more than 40 percent from a year ago, according to an index that tracks the top producing provinces. They recently hit a 10-year high by another benchmark that tracks prices at a wholesale market in Guantao, in northern China... Two years ago, farmers started expanding after several bumper years, adding more egg-laying hens from 2024 to 2025 than ever before, according to Aspen Li, an analyst who studies the egg market. Suddenly, there were too many eggs and the price plunged. Farmers then found themselves short of money to feed all their chickens. So they culled them, at a rate that experts considered excessive. Eventually, there were not enough egg-laying hens to meet demand, sending prices to levels that Mr. Li said were “even higher than my expectations.”

4. Japan's return to normalcy.

5. President Xi's flagship Belt and Road Initiative (BRI) projects hit a record $20.1 bn in green energy financing in the first half of 2026, topping its total value for the whole of 2025,

Total BRI deals rose to a record high of $126.3bn in the first half of 2026, up from $123.3bn in the same period in 2025. The 2026 figure was composed of $49.8bn in investment and $76.5bn in construction projects.

A distinguishing feature of BRI projects is the increased share of the private sector.

The latest data highlighted how the BRI had become primarily driven by private companies rather than China’s state-owned enterprises. According to the University of Queensland data, the share of engagement from the private sector, as opposed to SOEs, reached 48 per cent in the first half, compared with 13 per cent in 2022.

6. The Great Divergence between labour productivity and wages.

Labour's share of income has fallen sharply.

7. Tata Zudio is following in the footsteps of Zara.

Despite its bargain offerings, Tata said gross margins at Trent, which includes the more upmarket Westside clothing stores, stood at 44 to 45 per cent. “The playbook is you go end-to-end — you go from the source of the product to the customer and you do everything yourself in between,” he said. “That’s why we do our own transporting. We do our own warehousing. We have our own shops. The manufacturing units we use are more or less dedicated to us.”... Zudio eschews online retailing, believing that high return rates clog up the operation and generate too much extra cost.Rapid turnover is key to Zudio’s appeal. New lines are launched every Thursday and a team of social media watchers monitors fashion trends and feeds them to a design team.

8. The IPOs of SpaceX, OpenAI, and Anthropic could generate a massive flush of philanthropic capital.

Nan Ransohoff, the head of public goods at the payment processor Stripe, estimated in a Substack post, between $37 billion and $100 billion could become available to charities annually... And that doesn’t even include OpenAI’s employees. Or the newly rich created by SpaceX, whose I.P.O. spawned an estimated 4,400 millionaires (and some 400 employees now worth more than $100 million). Or the many other IP.O.s on the docket... Giving money away is a common maneuver to avoid taxes: Up to 74 cents of every dollar donated to charity would have been paid as taxes, according to the Institute for Policy Studies. It reported that charitable giving in 2022 alone had resulted in $73 billion in lost tax revenue.

9. Debt service and defence make up two-thirds of Pakistan's budget expenditure.

10. On Europe's pensions problem.

Across the EU, 47 per cent of the bloc’s social protection expenditure is spent on old age and survivors’ benefits, ahead of 36.7 per cent spent on sickness and disability and 8.7 per cent on families and children. Even in the UK, where private provision plays a greater role, the country’s fiscal watchdog has forecast that spending on the state pension — the second-largest item in the government budget after health — will rise from almost 5 per cent of GDP to 7.7 per cent by the early 2070s. Italy has the EU’s highest pension costs at just over 15 per cent of GDP, according to statistics from the European Commission. France and Greece each spend over 14 per cent. In Germany, a third of all federal tax revenue will be spent plugging holes in the state pension system this year, according to an estimate by Munich economic think-tank Ifo...

In France, the audit office estimated last year that the country’s pension deficit, currently around €1.7bn, could grow to €15bn by 2035 and balloon out to €30bn by 2045 if further reforms are not made. European countries have tried to tackle their surging pension costs since the 1990s, and have had some successes, with many lifting the state pension age from 65 to 67 or more. Italy has tied its pension age to life expectancy, while France has pegged annual pension increases to consumer price inflation rather than earnings. In some countries, spending on pensions as a percentage of GDP is set to fall in the long term as a result of such moves...

In most big European countries including Germany, France, Italy and Spain, the state provides the main earnings-related pension, paid for by contributions from current workers, which aims to replace a proportion of pre-retirement income. Such systems were modelled after the one created by Otto von Bismarck, who introduced national state pensions in 1889 to ward off surging socialism and strengthen loyalty to the authoritarian German monarchy... It paid up to 20 per cent of average salary to industrial workers when it became payable. It was designed to prevent destitution rather than facilitate a comfortable retirement. Other countries soon followed. In the UK, Prime Minister David Lloyd George ushered in old age pensions in 1909... A full UK state pension is currently close to a third of median earnings; private provision, usually through workplace schemes, is meant to provide additional security in retirement... Italy has one of Europe’s highest replacement rates, with pensions paying out close to 80 per cent of average earnings... Contribution rates, from workers and their employers, are correspondingly high at 33 per cent of earnings in Italy, 28 per cent in France and 19 per cent in Germany... That compares with an average of over 20 per cent in the UK — paid via national insurance — and just 11 per cent in the US.

11. Ramesh Chand argues for rationalising the PDS and moving to a nutrition security programme.

Between 2013-14 and 2025-26, India’s real per capita income (net national income at 2011-12 prices) increased by 78 per cent, from ₹68,572 to about ₹1.22 lakh... At the time of the NFSA’s enactment, around 22 per cent of the population lived below the poverty line. Both official estimates and independent studies now suggest that poverty had declined to around 5 per cent by 2022-23... In the early years of the NFSA, roughly one-third of the beneficiaries were poor and two-thirds were above the poverty line. By 2025-26, only about 10 per cent of those receiving free food grains were estimated to be below the poverty line while the remaining 90 per cent were non-poor... The latest UN report... estimates that the proportion of Indians unable to afford a healthy diet declined sharply from 59.8 per cent in 2017 to 35.5 per cent in 2025. In absolute terms, the number of such people fell from 759 million to 589 million. This indicates that about 170 million people crossed the affordability threshold for a healthy diet during this period as their purchasing power improved... The prevalence of undernourishment in India declined from 13 per cent in 2013-14 to 9.8 per cent during 2023-25, indicating progress but at a relatively slow pace.

12. The Fed under Kevin Warsh appears to be facing a credibility crisis as it grapples with rising inflation.

As Mr. Warsh spoke, longer dated Treasury yields rose sharply, with the 30-year bond closing in on its May peak of 5.2 percent. That was the highest level since 2007. The rise in the 30-year Treasury yield suggests some worry about Mr. Warsh’s ability to tackle inflation in the long run.

And this.

Long-term government borrowing costs shot higher as Mr. Warsh spoke, with the 30-year bond notching its largest one-day increase in more than a year. Trading around 5.22 percent, it is at the highest level since 2007. The 10-year Treasury yield, which serves as the benchmark for borrowing costs around the world, also rose alongside expectations about inflation over a longer time horizon.

13. FT has a long read describing the story of Situational Awareness, the $20 bn hedge fund of 24-year-old Leopold Aschenbrenner, which had racked up gains over 400 per cent on the back of massive leverage, and has now run into the wrong side of the AI sell-off. The fund sold its portfolio to Ken Griffin's Citadel in an almost distressed sale. Apart from being an alumnus of OpenAI, Aschenbrenner is also the husband of Avital Balwit, who now works as chief of staff to the CEO of Anthropic.

What stands out in the entire article is the reluctance to call out the obvious contributor to Aschenbrenner's success: the strong likelihood of insider trading at a massive scale. It is hard to believe that the smart investors who were betting on Situational Awareness were betting on the expertise or competence of Leopold Aschenbrenner, and not on the insider information he possessed.

14. Fascinating snippet on wealth creation in the equity markets.

Economic analyst Hendrik Bessembinder has shown that half of the net wealth creation in US stock markets over the last century flowed from just 46 public companies, out of a total of almost 30,000. Looking at his list of the greatest wealth creators, the knowledge companies dominate the top spots, and all the winners have high walls around them.

Forward guidance and Kevin Warsh

noreply@blogger.com (Urbanomics) — Fri, 31 Jul 2026 05:23:01 +0000

The market reaction to Kevin Warsh’s second FOMC meeting decision to stay the course on interest rates despite rising inflation has triggered a debate on the Fed’s credibility in fighting inflation.

This is how the $31 trillion US Treasury market reacted.

Long-term government borrowing costs shot higher as Mr. Warsh spoke, with the 30-year bond notching its largest one-day increase in more than a year. Trading around 5.22 percent, it is at the highest level since 2007. The 10-year Treasury yield, which serves as the benchmark for borrowing costs around the world, also rose alongside expectations about inflation over a longer time horizon.

Warsh has made it clear that he does not agree with the policy of forward guidance, and intends to discontinue it. He has argued that forward guidance distorts market incentives and comes in the way of market discipline. This blog is in agreement with it.

The reversal of forward guidance comes abruptly, at a time when market expectations of the Kevin Warsh era are vitiated by the circumstances surrounding his appointment. Markets clearly think that Warsh may buckle down to pressure from the White House or prefer to please it and delay raising interest rates.

In this context, I created the table below that evaluates forward guidance and central bank credibility.

The high credibility and low forward guidance Volcker era is the golden quadrant. The central bank has earned trust through demonstrated willingness to act decisively, but it doesn’t tell you what it’s going to do next. Participants must do their own work to assess fundamentals, price risk properly, and build in uncertainty premia. Volcker’s Fed famously targeted money supply, not interest rates, and didn’t telegraph moves. The result was that markets had to think for themselves, and the discipline that emerged was real. Risk was priced because nobody could assume a backstop.

The Bernanke-Yellen era of high credibility coupled with a high degree of forward guidance ensured that the latter became the market’s mirror. When participants believe the central bank will do what it says, and the central bank tells them exactly what it will do, the rational strategy is to front-run the guidance rather than analyse fundamentals. The “dot plot” era, the “considerable period” language, the “whatever it takes” formulation created a world where the trade was to decode the Fed rather than decode the economy. The moral hazard is structural insofar as investors are rewarded for taking risk they don’t understand because the central bank has told them the floor exists.

The worst combination for policy effectiveness is that of low credibility and high forward guidance. The central bank issues guidance but nobody believes it. Participants pursue their own interests, and policy actions run counter to market expectations. This produces whipsaw where the central bank says one thing, markets price another, and when the policy actually arrives it dislocates rather than stabilises. One could argue the late-stage BOJ falls here (decades of forward guidance that markets progressively stopped believing).

Finally, the Warsh era tries to limit forward guidance but in a period of low central bank credibility, inducing a period of “greatest uncertainty”. Worse still, the transition itself amplifies the shock - moving from a regime of high credibility andhigh forward guidance (the post-2008 consensus) to one where both are removed simultaneously. The question to analyse is whether the Warsh Fed currently sits in the fourth quadrant.

There are four points to be noted.

First, the transition path matters enormously. Moving from the Bernanke-Yellen quadrant (high-high) to the Volcker quadrant (high-low) requires maintaining credibility while withdrawing guidance. This means the central bank must demonstrate through actions (not words) that it will do the right thing even when it doesn’t tell you what the right thing is. The Warsh challenge is that he has withdrawn guidance and may not yet have established credibility through a demonstrated willingness to act decisively against inflation. The risk is that he lands in the bottom-left quadrant (low-low) rather than the top-left (high credibility, low guidance).

Second, while I had blogged here listing forward guidance as an important channel in eroding market discipline, it must be noted that it’s not forward guidance per se that erodes discipline, but forward guidance combined with high credibility. Low-credibility forward guidance is merely useless. And high-credibility forward guidance is actively dangerous because it works too well, by substituting the central bank’s judgment for the market’s own.

Third, there’s a temporal asymmetry in credibility. Credibility is earned slowly (Volcker needed 2-3 years of painful rate hikes) but lost quickly (a single capitulation can destroy it). Warsh’s current position - rates unchanged while prices rise - coupled with the circumstances of his appointment (and the credibility problem it engenders) risks a credibility test analogous to Arthur Burns in 1972-73. If inflation accelerates and the Fed is seen as having waited too long, the move from “low guidance with emerging credibility” to “low guidance with low credibility” could be swift and self-reinforcing.

Fourth, this also highlights the less discussed aspect of policy making that involves shaping expectations. Once collective beliefs are formed and incentives aligned, it is very hard to reshape them. The Bernanke-Yellen response to the market tumult during and after the Global Financial Crisis, guided by the research works of Gauti Eggertsson and Michael Woodford, and Paul Krugman, may well have been required in its immediate aftermath. The mistake was to continue and institutionalise it as part of the regular central bank policy toolkit. Bernanke or Yellen, with their credibility, ought to have exited forward guidance once normalcy was restored. But instead, they chose to please the markets with this new crutch. It is a bit like subsidies - once offered, there’s no sunset.

Some thoughts on metro railway systems in India

noreply@blogger.com (Urbanomics) — Thu, 30 Jul 2026 09:53:25 +0000

This post will analyse metro railway projects in India, highlight their failings and make some suggestions.

There are three reasons why metro projects globally struggle to be sustainable, even on the Opex. One, the original traffic projections were on the higher side, making the revenue forecasts a non-starter. In other words, the metro should never have been built. Second, the ticket prices were kept too high, resulting in less demand. Third, there is limited induced ridership due to the lack of TOD, parking facilities, and modal integration.

The first is a common factor associated with projects globally (optimistic forecasts to justify otherwise unviable projects). The second is a tricky problem insofar as lowering it further risks significantly worsening the financials of the metro. Besides, there is enough evidence that metro ticket prices are reasonable across cities. And the real problem is less the fare level than the generalised cost of the trip, or the fare plus the last-mile penalty (arising from the need to change modes, and the lack of any modal integration).

The last one is especially important since the metro is a large investment that is made to shape the city's growth, specifically by densifying the walkable vicinity of its stations and thereby inducing captive ridership. This is the biggest source of sustainable passenger ridership for the metro. Thin station catchments may well be the binding constraint to the operational viability of India’s metro systems.

India's experience with TOD has been disappointing. None of its 900-odd metro stations is a TOD (densified residential and/or office spaces, which enable walkability from the station to house/workplace). This is unsurprising since the TOD policies generally suffer from poor design. There is also the reality that very few metro projects globally can recover even opex with the farebox collections and rely on real estate and other commercial revenue streams. More on it later.

In addition to the three demand or revenue-side challenges, there is also a cost-side problem. They include the wrong mode selection - choosing an underground full metro when light rail or bus rapid transit system would have sufficed. The low-cost foreign loan is deceptive since a depreciating rupee inflates the cost (though the Yen, the major source of metro debt, has been depreciating or holding steady against the rupee). Further, the linear stunted network topology, as against a connected grid, limits ridership. Most Indian systems are linear stubs, so they sit permanently below the ridership threshold at which farebox economics turn. As an illustration, Chennai’s finances turned around dramatically once Phase 1 closed the loop, with ridership surging from 13% of projection at CAG FY20 to now ~60%.

I asked Claude to generate certain parameters for the leading Indian metros. First, the difference between the DPR ridership projection and the actual realised ridership points to strategic misrepresentation with inflated estimates to secure project approval. As can be seen, apart from Delhi, the shortfall is very high, with the majority not even able to generate a third of the estimated ridership. This points to clear strategic misrepresentation to get the project sanctioned by exaggerating the ridership estimates.

Delhi is now above its old 2019-20 target after Phase-III/IV and post-COVID recovery. This points to the fact that maturation and network completion, and not fare tweaks, are likely to move the needle.

In terms of the percentage of just the opex covered by farebox revenues (or ticketing), it is very low in many metros. However, when combined with the other revenues, five metros are able to cover the opex.

But if we include debt-service, the picture becomes extremely bleak. Most Indian metros are deeply in the red.

This has important fiscal implications. I took six major states, and assumed their current ridership trajectory and fare growth to calculate the gap between their total revenues (farebox and non-farebox) and total opex and debt service. This assumption overlooks that ridership trajectory may improve over time. In any case, this analysis points to an undiscounted 25-year total gap of ₹1,06,569 cr, or NPV of ₹64,423 cr when discounted at 7%. The state share is around 60% or ₹38,582 cr, and the central share is ₹25,840 cr, amounting to a total annual budget requirement of ₹6,900 cr for FY26 to ₹6,256 Cr for FY30.

A global comparison yields interesting results. Apart from Northeast Asia, generally, metro railway systems struggle to cover even Opex through farebox collections.

In all western cities, their governments funded the infrastructure (versement mobilité in Paris, LTA asset ownership in Singapore, TfL/Treasury grant in London, MTA authority-level bonds backed by dedicated taxes in New York). The operator, therefore, never sees the debt service, which has been socialised as a public subsidy up front. Only Hong Kong MTR and Tokyo make the operator carry capital and still clear cost, and they do it through property and ancillary income, not fares.

India is a structural outlier in loading the capital debt onto the SPV's own balance sheet. The Indian farebox is being judged against a burden every comparable peer either socialises to the budget or funds from property. The sustainable systems didn't find a magic farebox - they either kept capital off the operator (the European/American subsidy model) or monetised the land (the Hong Kong/Tokyo model). India did neither.

So what can be done?

A systemic reform requirement is to orient the design and implementation of metro railway systems away from being primarily a railway construction project to an urban planning initiative. This would entail tight integration of the planning of metro rail projects by the municipal authorities.

The TOD influence zone (TIZ) around each station should be seen as a genuine opportunity for redevelopment and densification. The planning regulations applicable to the TIZ should make it significantly more attractive to build insidecompared to outside - 3-4 times higher FAR, remove parking minimum, TDR-driven land assembly, TDRs brought in with higher multiples, etc. Equally important, the regulations should make it attractive to redevelop the built-up areas (and not be like this). Instead of being prescriptive on land use, it should be left to market forces to determine the appropriate shares of different types of uses in each zone. It would also allow the markets to crowd in the right kinds of commercial amenities, such as groceries, retail, restaurants and cafes, and services, into the zone, depending on its broader land-use mix.

An important reason for the failure of TOD is the lack of attention given to its public realm elements, specifically the street configuration for connectivity and walkability, and public amenities. This is a bad omission given that walkability (from/to commute and for amenities) is the primary objective of TOD zones. An area without these elements contradicts TOD. Unfortunately, in built-up areas (which form the major part of TIZ), these elements don’t emerge overnight. They require master plans that are configured to enable walkable street connectivity, higher density, and mixed-use developments. Once the master plan is in place, its implementation should be facilitated proactively through the development control regulations and building bye-laws that allow for TIZ preferences and incentives, and instruments like the Town Planning Schemes. These are 10- to 15-year agendas.

The TIZ preferences should be complemented with feeder buses, multi-modal fare integration, and e-rickshaw access so as to extend the catchment beyond the TIZ. Further, as the Chennai example shows, metro lines should complete the loop or connect the grid, and not remain as linear stubs.

For financial sustainability, the TIZ should deploy appropriate value capture finance instruments. I blogged about it here. They would include betterment levies (brownfield areas) and impact fees (greenfield areas), station-area commercial development, air-rights leasing, and purchaseable FAR. However, care should be taken to ensure that these levies do not detract from the commercial attractiveness of building inside the TIZ. These revenues should be assigned to the SPV balance sheet. This is how HK MTR earned 65% of its 2024 profit from property, not fares.

These urban planning and other policy requirements should be tightly incorporated into the approvals given for these projects. Every new metro DPR must include statutory master plan amendments, FAR densification for station catchments, mixed-use zoning, land assembly strategy, and the land-value-capture financing plan. They should be preconditions, not annexures. The rail alignment should be a subset of the urban plan.

There should be no sanction without station-area FAR increases, TDR-driven consolidation, betterment-levy design, and air-rights leasing, all routed to the SPV. TDR can pre-fund land assembly before construction starts. These should become an approval veto. Further, any ongoing support from the Government of India must be made contingent on compliance in letter and spirit with these requirements to pre-empt backsliding and subversion by the states.

The planning elements discussed above would have to go against the conventional wisdom on urban planning held close to heart by town planners across India and the vested interests of builders and others. It would therefore require strong resolve at the highest political and bureaucratic levels to overrule objections and enforce them.

For new projects, central funding should become conditional on a corridor-density threshold, independently audited ridership models, and ex-post accountability. There should be an end to the practice of a self-certified 14% IRR. Anything below the threshold should qualify only for a MetroLite / MetroNeo / BRT.

In conclusion, the urban metro should be used as an opportunity to redraw the metro as an urban plan by densifying station catchments, capturing the value, and servicing the construction capital.

The demand side constraint of the Indian economy

noreply@blogger.com (Urbanomics) — Sun, 26 Jul 2026 23:30:00 +0000

I blogged here, arguing that Indian businesses face a structural cost constraint similar to that of developed economies that erode their global competitiveness. This cost constraint on the supply side must be seen alongside a constraint of a consumption class that is far smaller and shallower than imagined. In other words, a developed country's cost structure in a low-income country's market size.

This point has been a consistent argument of this blog and was documented in great detail in Can India Grow? in 2016, much before it became more widely recognised.

India’s demand-side problem is twofold. For a start, it already has a low per capita income, the lowest among its emerging market peers. Second, this itself conceals a low base of the consumption class that is also not widening proportionately with economic growth. The nature of economic growth is such that it is not only not broad-based enough but is also widening inequality.

The recently released PRICE - Tata Sons Many Urban Indias report is a confirmation of the demand-side constraint. It finds that the top 100 cities, with just under a fifth of the population, capture almost half of all household surplus, the closest measure to genuine discretionary spending capacity. What sits outside, the other 81% of India, holds only about 53% of surplus combined, and most of that is in the top slices of tier-2/3 towns and the productive rural belt. The surplus-generating layer of the economy is essentially urban and already fully contained. There is no large pool of "middle India" outside urban India waiting to broaden the base.

PRICE's top-100 city-tier framework (Big Six, Boomtowns, Breakout, Frontier) is the empirical proof that "urban India" is not a homogeneous consuming class. The gap in savings between the top and bottom tiers is nearly 3.5×, and one in six Frontier-city households is already financially overstretched. This is what “narrow” looks like at the city level.

The top 15 cities have two-thirds of all top-100 consumption, and the Delhi NCR alone has 15% of all urban consumption. The consuming class is a stratum within the Big Six, not the Big Six themselves. Even within the six megacities, PRICE reports that 24% of households are low-income. The consuming class is not "urban India" (~500M) or even "top-100 city India" (282M), but a stratum of prosperous households scattered across the Big Six and the top of the Boomtown tier.

The Blume Ventures categorisation of India’s consumption class finds three groups, with the first comparable in size to the population of Mexico at 30 million households (the Blume Rule of 30, or 10% of Indian households). A worrying finding is that the consuming class that anchors private demand is small and getting deeper, not significantly wider. A vast base has almost no discretionary spending power at all. This is the inverse of the broad, upwardly mobile middle that sustains private investment.

The PRICE report's optimistic headline (~715M "middle income" people by 2031) conflates a household that shares a scooter with one that services a car EMI. Once you apply a real surplus filter - savings above ₹4 lakh a year, which is roughly what it takes to run a car, insure a family, and take one flight - the number lands where Blume said it did. In simple terms, PRICE's 715M by 2031 measures how many Indians will earn enough not to be poor, a significant achievement. Blume's 140M measures how many can act as a consuming class today - the market a brand can actually sell a car, an AC, a holiday abroad or a health-insurance policy to.

The numbers are further validated by other sources. An income assessment by Rama Bijapurkar points to a more differentiated group, but a similar narrow base of the consumption class. She estimates that 93% of households have annual consumption of less than $5,700.

The data on penetration of discretionary goods and behaviours corroborates the Blume survey data. Almost every independent marker lands near the same Blume Rule of 30. Whether you measure cars, ACs, credit cards, foreign travel, or who actually pays income tax, the consuming class converges on the same narrow apex. If anything, the Blume data itself looks too optimistic.

Whichever marker you pick - cars (8%), ACs (13%), passports (~10%), income-tax payers (1.5–3%), credit cards (4.6%), foreign trips (2%) - the consuming class lands at ~10% of households or fewer. That is also exactly where the bottom-up Blume spending model, income surveys of Bijapurkar, and asset penetration estimates of NFHS/Bain lands.

India's "middle class" has been estimated at 29 million people one way and 600 million another, a multiple spread of 20 that reflects what one is choosing to count.

India has a consuming class of ~140M, an aspirant class of ~300M moving toward it, and a base of ~1bn for whom the "middle class" debate is moot. That picture is consistent with every methodology once you ask which question each one answers - how many can afford a car (~10%), how many are above poverty by global standards (~30%), how many participate in the digital economy (~65%). Conflating them is the single most common error in India market-sizing. This is a very nice summary of why nobody gets the elephant in full.

In this context, it is also useful to draw a nuance on India’s high consumption rate of 61% of GDP, which is far higher than China’s ~38% of GDP. India’s problem is that while it is already a consumption-led economy, the problem is the quality of that demand. It is too thin per person, skewed to the top decile, and increasingly financed by debt as households run down savings. In other words, the demand side constraint is not the consumption share of GDP, but that there are too few middle-income earners to generate broad, income-financed volume. That points policy at jobs, wages and investment, not at “stimulating consumption.”

Fundamentally, all the above is a reflection of two important factors - the low per-capita income and the widening inequality in sharing the benefits of aggregate growth.

India's per-capita output (PPP) trails Vietnam and Indonesia and is under half of China's. Its Mexico-like consuming tier is real, but at best, only ~10% of the country.

India imposes rich-country costs on poor-country incomes in capital, fuel and land - and because those costs are policy-made, they are the actionable half of the problem. The demand blade can only be widened the slow way: through jobs, wages and productivity.

Unfortunately, corporate surpluses are being captured, not recycled into the wages that would create the next tier of consumers. Profits race ahead while sales, jobs and pay lag far behind.

It also does not help that Indian businesses across sectors are averse to spending on R&D and innovation.

R&D is a fixed cost that only pays off over a large, contestable market. A thin domestic market depresses the return to it, which is why the economies that lead on R&D expenditures are either big-and-rich at home (the US) or export-driven (Korea, Germany, Taiwan). India is neither, and sits alone in the low-R&D corner.

This is an instructive comparison of India with China and South Korea.

The main takeaway is that India’s existing consumption class, confined to just 10% of the households, is too narrow to sustain high growth rates for long periods. It requires considerable broadening. But broad basing economic growth requires access to good jobs, a daunting task given that the gig economy is the biggest source of job creation and elsewhere it is mainly contractual jobs. Worsening matters is the reluctance of the private sector to invest or innovate.

Weekend reading links

noreply@blogger.com (Urbanomics) — Sat, 25 Jul 2026 06:23:32 +0000

1. SpaceX IPO is ample proof that the Chinese wall between equity research and investment banking in IB firms is a myth.

You might expect wildly divergent views on a company as speculative as SpaceX. Here the underwriters disagreed only over the scale of the upside. Sceptical voices came from outside the syndicate. Morningstar, for example, valued the shares at $63.

This is now dead

When the dotcom bubble burst, regulators uncovered emails showing that Wall Street analysts were privately disparaging stocks they were publicly touting. A 2003 global settlement between banks and regulators on analyst research imposed sweeping restrictions. It barred investment bankers from influencing analyst compensation, tightly controlled communications between research and banking, and banned analysts from IPO pitches and roadshows. New York Attorney General Elliot Spitzer’s premise was that shielding analysts from bankers would deliver truly independent — and better — research. On one level, the reforms succeeded. Banks have constructed a robust compliance apparatus to wall off research from investment banking. “Chaperones” now police interactions between analysts and corporate finance to prevent even the appearance of pressure. The Spitzer global settlement formally ended last December in favour of more flexible rules overseen by an industry association.

It is hard to see how SpaceX shares can avoid a cratering.

About 30 per cent of the roughly 640mn SpaceX shares available to trade have been borrowed to sell short, up 10 percentage points over the past 10 days, highlighting how traders are becoming increasingly sceptical of the company’s market prospects... About 900mn further SpaceX shares could become available to trade as soon as next month when certain lock-up provisions for pre-IPO investors expire. Traders who doubt there is sufficient demand for the deluge of extra equity are cashing out now as a result, market participants say.

2. After reducing their hiring last year, firms with jobs exposed to AI are planning to increase their entry-level hiring this year, but they come with a "seniorisation".

Candidates for starter roles in the most AI-exposed industries are now expected to show a mastery of the skills traditionally demanded of more seasoned staff, such as data-driven decision-making and people management... Eleanor Lightbody, CEO of Luminance, which develops AI for the legal profession, says these middle layers could be squeezed out altogether, “because we are going to hire more juniors, who are really going to understand how AI works, and more seniors [are] staying in the business because [by using AI], they can be more productive and have more capacity”. The challenge for job seekers is that it is hard to find entry-level jobs that allow them to develop the higher proficiency that seniorised roles now require... Reliance on AI is increasing the demand for distinctively human “soft skills” — or “power skills”, as some are now calling them — such as creativity, empathy, judgment and networking ability. PwC’s jobs report found that new tasks added to job adverts for AI-exposed roles were two and a half times as likely to call for such capabilities.

3. Very good description of how China became so dominant.

It enticed unsuspecting giants such as Apple, Tesla, Motorola, and Lucent with low-cost logic. When sufficient local manpower was trained, subcontractors developed, and stakes became important, China applied the squeeze. China would break contracts, cancel licences, coerce the transfer of technology, control pricing, withdraw incentives, force equity participation, conscript technology and evict them. Huawei, BYD, CATL, and SAIC are some examples of the resulting indigenous giants that emerged. In an act of silent invasion, conscripted technologies have been converted into military capability. It is dominant as a supplier of several raw materials, such as rare earth minerals, gallium, graphite, and lithium; a dominant buyer of soya from Brazil and iron ore and wines from Australia; a financier of BRI projects; and a provider of processing technologies for Chilean copper and lithium in select South American countries. With this web of dependencies, it can choke several factories.

4. Janan Ganesh feels that for Britain to start making real reforms, the incoming PM Andy Burnham must do more welfare and subsidies and discredit the whole .ideology.

What is the precedent for a rich democracy doing pre-emptive economic reform? Which nation ever made controversial structural changes — involving winners and losers — to prevent a crisis, rather than in response to one? Southern Europe needed the Eurozone panic of 2009 onwards to make spending cuts. Hawke, Keating, Margaret Thatcher and Ronald Reagan were reacting to 1970s stagflation. François Mitterrand in 1983 was reacting to a market shock that to some extent he’d created. Reform only happens when it absolutely has to happen. So try again, prime minister. Fail again. Fail worse.

5. Japan embraces a more proactive government-driven economic growth policy.

Sanae Takaichi's cabinet approved a policy blueprint that targets a combined $2.3tn of public and private sector investment between now and 2040 in 17 chosen sectors. Ministries will be able to make budget requests without upper limits; budget construction, according to the document, will be “fundamentally” changed. Much of the blueprint is about economic security, but a refreshingly large amount is about growth... possibly the most meaningful lines in the new strategy place Japan’s future efforts in the global context. “Among advanced countries, there is a big trend of the government and private sectors working together on large-scale, long-term industrial spending,” it read... The government would strive, the document further promised, to meet the challenges of “the era of great global competition between industrial policies”...

On the same day that the blueprint was agreed, the Ministry of Economy, Trade and Industry produced separate guidance for growth investment — an effort to encourage Japan’s 4,000-odd listed companies to shift more of their endeavours towards growth and a witheringly blunt critique of how matters are at the moment. Within Japan’s 350 largest companies (by sales), 65 per cent of invested capital remains locked in what it calls value-destructive segments, according to METI’s research. In the US, the equivalent ratio is 39 per cent. Both Takaichi’s blueprint and the new METI guidelines are attempting a new version of industrial policy that not only seeks to spur growth, but places a huge bet on the government’s ability to encourage companies in a way that market forces have not.

6. Kevin Warsh is trying to scale down forward guidance

“Financial market prices are probably the most important source of information to guide central bankers,” he said at his inaugural press conference last month. “But when all the financial markets are doing is reflecting back what we’ve said, then we’re taking the most important source of information and we’re being blind to it.” Many agree with the Fed chair’s view that central banks’ focus on predictability has led to a world in which markets obsess more over what officials say than what is actually happening in the economy. “Forward guidance has turned markets into a mirror,” says Ajay Rajadhyaksha, global chair of research at Barclays. “The Fed watches markets; markets watch the Fed. And no one’s actually watching the economy.”...

Recent research by the US central bank suggests its decisions also have an outsized impact on equity markets, leading to big changes in how investors price stocks. Advocates of forward guidance say it helps avoid the sort of surprises for the markets that feed overall volatility and eventually raise borrowing costs as investors demand greater compensation to stomach market swings. Warsh and his allies counter that the attempt to pacify markets simply encourages greater risk-taking, damping short-term volatility but storing up bigger shocks for later. The debate is all the more important because of the backdrop: the surge in borrowing over almost two decades. Government debt around the world has risen sharply following the global financial crisis, the Eurozone crisis, the pandemic and the wars of the 2020s...

Some analysts highlight the so-called taper tantrum of 2013 — when markets were unnerved by Fed statements about its plans to shrink its balance sheet as a result of officials’ false sense of certainty. Others link the 2023 collapse of the US’s Silicon Valley Bank to central bankers’ previous pledge to keep interest rates low.

This is a very important factoid about Fed communications.

Between 1990 and 2022, an era in which the status and prominence of central banks steadily grew, US 10-year government bond yields fell by more than 7 percentage points. All of the downward moves throughout that period took place during the three days around Fed meetings, rather than in response to political events or economic data. But the relationship broke down after the Fed appeared flat-footed on inflation in 2022. The Riksbank data shows that the central bank’s meetings had little to do with the subsequent rise in yields.

An important concern for the bond markets is the sharply increased volume of Treasuries held by hedge funds that use leverage to bet on tiny differences in interest rates.

The Fed estimates that large hedge funds’ holdings of US Treasuries doubled between 2023 and 2025, faster than the growth of the market as a whole. Such funds now own more than $2.5tn in Treasuries, according to the US central bank and US Treasury data. Such sums dwarf China’s official holdings — not an exhaustive account of the country’s exposure — which have fallen from $1tn in December 2021 to $659bn in May 2026, according to US Treasury statistics. Moreover, the Bank for International Settlements, the central bankers’ bank, has warned that the hedge funds might have to dial back their stakes in government bond markets even quicker than they arrived — a possibility it describes as one of the most troubling financial stability risks in the world today.

Then there are the other concerns for bond markets.

The Bank of England said this month that AI hyperscalers borrowed more in the first half of 2026 than in the whole of 2025. So far this year they have accumulated as much new debt as the UK government. An interest-rate surprise from the Warsh Fed might not only unsettle Treasury yields but set off a vicious circle of margin calls — when a sudden price movement in assets bought with borrowed money requires an injection of capital — and fire sales by hedge funds that could create a dash for cash.

7. A cautionary tale on the difficulty of private enterprise establishing and managing entire railway systems comes from the example of Brightline Express, which connects Miami and Orlando, and became operational in 2023.

Brightline traces its roots to 2007, when Edens’ Fortress spent $3.5bn to acquire Florida East Coast Railway, then a listed freight transport company. Its tracks spanned from north to south in the Sunshine State, and construction for what would become Brightline began in 2014, with the Orlando service beginning a decade later. In a 2024 bond prospectus, Brightline executives forecast that by 2026 they would have nearly 8mn annual riders, split roughly evenly between the Orlando-Miami route and a more local service in South Florida. That base of customers was expected to generate $700mn in revenue... Even with customer levels up 16 per cent year to date through May this year, ridership will struggle to hit 4mn this year. Operating income has at best reached break-even before debt service costs...

The promoter Wes Edens’ Fortress wrote off its investment long ago, and it is now hedge fund bondholders who are jockeying for control of Brightline. But alongside distressed debt specialists such as Nut Tree Capital Management, Aristeia Capital and Redwood Capital Management, there are a handful of more staid asset managers including Nuveen and First Eagle also at the table. As well as corporate bonds issued by subsidiaries, the group’s debt stack includes more than $2bn of traditional municipal bonds, half of which are guaranteed by a bond insurer.

The cost of doing business in India - land prices

noreply@blogger.com (Urbanomics) — Fri, 24 Jul 2026 04:34:26 +0000

I blogged here, highlighting the high cost structure that Indian businesses face. This post dives deeper and examines land cost.

A comparison with peers shows that urban land is priced like that of a rich country and ends up hoarding the nation's savings, with 77% of the households parking their wealth in real estate. Mumbai ranks among the world's 20 most expensive prime markets. Industrial land across the major Indian cities is prohibitively expensive compared to peers.

An Indian manufacturer pays roughly 5–15 times more for industrial land than a Chinese counterpart in a comparable tier-2 city and 1–4 times a Vietnamese peer.

I used Claude to generate the graphic below on the total land transaction cost across states, combining the stamp duty and registration fees and the change of land use fees for the conversion of agricultural land. While stamp duty has converged to 6-7% of land value, the total cost varies widely across states. Interestingly, the southern states have the highest transaction rates.

Four states can’t be reduced to a clean number - Maharashtra charges a premium of 25–100% of the ready-reckoner differential; Gujarat charges on the agri/non-agri differential; West Bengal rarely grants conversion at all; and Delhi’s urban land is already non-agricultural. For these, the combined figure shown is a floor, not a total (hence the ‘+’). Maharashtra, in particular, would likely top the chart if its premium were expressible as a share of land value.

Andhra Pradesh (deemed conversion since 2018, NALA Act now being scrapped) and Uttarakhand (permission eliminated for specified categories) are the only states that have removed conversion permission as a bureaucratic step. Assam, J&K, Odisha, Puducherry and Tripura have moved to negative lists.

I then asked Claude to generate the typical cost of industrial land in some representative locations across India. The wide variations in the construction levies as a share of land value arise from the variations in the underlying land valuations (the % is higher in places with lower land values). While the state and local taxes make up 10-17% of the land value, all the land and building-related taxes make up a near-uniform ~10% of the industrial project cost (land, construction, taxes).

I did the same for residential land cost at representative locations in a few cities. Ignoring the Gurgaon outlier, the state and local taxes make up 16-26% of the land value, and all the land and building-related taxes make up 18-25% of the price paid by the homebuyer. In other words, the tax burden is a fifth to a quarter of what a homebuyer pays.

In both cases, the lower land valuations in places like Lucknow or Indore or Vizag mean that the share of the nationwide levies (GST and labour cess) is much higher. In other words, these levies bite more in the second-tier and below cities and end up eroding their comparative advantage.

A like-for-like global comparison for industrial land is difficult given the lack of data. The graphic below is a broader international comparison, using the World Bank’s last Doing Business 2020 survey, for the construction of a typical (2 storeys, 1,300 sq m, on a 929 sq m plot, valued at 50× GNI per capita) warehouse (as a % of the warehouse value) in each country’s largest business city. It measures every statutory licence, permit, inspection, utility connection, non-recurring tax and property registration fee, but importantly, excludes VAT, capital gains and the price of the land itself.

India’s statutory fee stack is middling, sitting below Mexico, Indonesia, Bangladesh, and Delhi at 2.8% is not too far from the OECD high-income benchmark of 1.5%. This questions the reasoning that Indian construction-permit fees alone make land prices uncompetitive. However, India’s manufacturing competitors like Vietnam, Thailand, Brazil, and Poland levy less than a fifth of what India does on the same measures.

More importantly, the DB survey data excludes land price, stamp duty, conversion charges, and the GST input credit, precisely the costs that were the basis for the discussion earlier. The state’s tax share at 18-43% of industrial land cost, or 9-11% of total project cost is where the land-related competitiveness gap sits, and not in the counter fees that the WB’s DB Survey tracked.

Lessons from Spain for urban planning

noreply@blogger.com (Urbanomics) — Tue, 21 Jul 2026 04:34:47 +0000

Football is not the only area where we can learn from Spain. Energy transition, infrastructure construction and urban planning are some others. This one is about urban planning.

An essay in Works in Progress examined how traditional apartments have declined across Europe, except in Spain, and the role played by late development and public policy. It also underlines how Spain uniquely got all the basics of urban planning right - land readjustment, infrastructure development, mixed-use, densification, connected street network, walkability, mass transit, and low car usage.

This is a good description of mixed-use density in Spanish cities that promote walkability and mass transit commutes, and limit sprawl and carbon emissions.

Spain’s cities are unusual. They are much denser, tighter, and more deliberate than other European cities, let alone North American ones. They reject picket fence for apartment block and choose balcony over front lawn. Two thirds of Spaniards live in flats, against 41 percent of Poles, 36 percent of the French, and just 10 percent of the Irish. Of the remaining third, most live in terraced rowhouses. In Spain’s cities, over four fifths of people live in an apartment. At the edge of Madrid or Valencia, dense mid-rise blocks stand beside open countryside without sprawl in between, something that has almost never happened in an English-speaking country, and that has been rare in France or Germany for a century… Spain’s settlements have some of Europe’s lowest per capita transport emissions, in part because about 70 percent of trips in Madrid and Barcelona are made on foot, tram, or metro. Almost every neighborhood is mixed use; almost all urban Spaniards live in the ‘fifteen-minute cities’ that seem like remote ideals in most affluent societies.

This is a good comparison with other Southern European cities, and even here, Spain stands out.

Spain is not alone in Europe in having become wealthy only recently: most Southern European countries have a similar economic history. And Portugal, Italy, and Greece do share the distinctive features of Spanish urbanism to some extent, with relatively dense cities and relatively high shares of people living in apartments (46 percent in Portugal, 53 percent in Italy and 59 percent in Greece compared to 65 percent in Spain). In other ways, however, Spain is distinctive in Southern Europe. The cities of Portugal, Greece, and Southern or Central Italy are generally surrounded by ragged fringes of unplanned suburban development: their urban cores are dense in the same way as Spain’s, but their peripheries are a chaotic mixture. The transport situation is also dramatically different. About half of journeys in Lisbon and Athens are by car; in Rome, the figure is two thirds, with another substantial share on mopeds; in Nicosia, it is 85 percent, the highest of any European capital. In Madrid, the modal share of cars is below 30 percent. Cities tend to be dense all over Southern Europe, but they have not all achieved the transport outcomes that urbanists associate with density: in this respect, Spain is the outstanding model.

Public policy has played an important role in making this difference. In Britain and the US, the government develops the main arterial roads and allows development that follows the development control regulations, which results in fragmented urban forms (in terms of plot sizes and types of development). In Spain, the authorities undertake land re-adjustments like the Town Planning Schemes of Gujarat and thereby lay down clear boundaries and forms of development.

This also means a high level of infrastructure development with a high density of roads, based on plans that connect streets and localities to promote pedestrians and cyclists.

This has yielded cities with exceptionally good infrastructure. About 28 percent of Madrid’s surface area is taken up by roads, almost exactly the 30 percent recommended by UN specialists. This compares to 21 percent in Paris, 19 percent in London and 20 percent in New York. Even Los Angeles, a famously road-heavy city, uses only 25 percent for roads. As we have seen, these roads are also more skilfully interconnected, which is indispensable for pedestrians and cyclists.

A large road network has not detracted from policy focus on public transport.

Despite having far superior road infrastructure, Spanish cities also have high public transport use. Around 60 percent of trips in the Madrid metropolitan area and over 70 percent of trips in the Barcelona metropolitan area are made through public or active travel, similar to other major European cities and far higher than American, Canadian, or Australian cities, which typically fall below 30 percent. In other words, Spanish cities have Los Angeles-tier road infrastructure and Paris-tier public transport access. This is paired with some of the continent’s best intercity transport. Spain has significantly more motorways than any other European country: 17,228 kilometers, versus 13,183 in Germany and 11,671 in France. It has the second-longest high-speed rail network in the world, after China.

In fact, public policy played perhaps an even more important role by keeping infrastructure construction costs low and ensuring construction was done within budget and without delays. It was able to utilise something like €200 billion in cohesion funding received from the EU between the late 1980s and 2020.

More importantly, Spain kept costs low… Spain, combined with its non-EU injections, built 4,000 kilometers of high-speed rail, 10,000 kilometers of motorway, and numerous metros, trams, ring roads, and radial arterials, because it kept costs extremely low. It did this by maintaining good practice: flexible environmental rules (although these have since become more problematic), top-tier in-house capacity in engineering and contracting, a commitment to a steady pipeline of projects over decades, and, above all, rapid decision-making, avoiding the costly delays and redesigns common elsewhere. Another part of this was giving small areas the power to decide on and fund infrastructure, like the Madrid Metro, avoiding the ping pong between authorities seen in some high-cost countries.
Together, this has allowed it to build metros more than 20 times cheaper than in New York City. For the price of one mile of the New York’s Second Avenue Subway extension, Spanish builders covered the entire 35-mile 1995–1999 expansion of the Madrid Metro. As a result, Spanish transport infrastructure is both abundant and cheap. Madrid’s metro underwent one of the fastest growth spurts in the worldbetween 1995 and 2007, adding around 203 kilometers of new lines to its already impressive footprint. Barcelona has been continuously expanding its metro network since the Second World War: in a period of astonishing activity between 1990 and 2010 there were 18 separate extensions, and seven more since.
Cities including Valencia, Bilbao, Seville, and Málaga all built metro or light rail systems in the 1990s and 2000s. Madrid and Barcelona have both joined their old suburban rail lines up into Cercanías/Rodalies systems, similar to London’s Crossrail scheme but far more comprehensive (though not always well run). The upshot of this is that, despite having some of the world’s best road infrastructure, Spain still has relatively low levels of car use and ownership: the modal share of driving is low not because driving is a bad option, but because other options are so good.

Since the late 2000s, changes in laws placing a series of restrictions on buildings have adversely impacted Spanish urban planning. For example, before 2007, Spanish land was buildable by default; the same was inverted to allow housing construction only if specifically zoned by the local council. Today, in an emulation of the planning practices followed in the US and Europe, building in Spain has become extremely restrictive.

Planning a major Spanish urban extension now depends on agreement from the municipality, the community (the regional government), the landowners, and, individually, each of the environmental, water, roads, electricity, public transportation, and social housing authorities. The result is that creating new city plans now takes an enormously long time. Creating the plan takes between six to eight years, while designing the streets and plots takes another three to seven… This is leading to high prices. Madrid asking prices are now nearly €6,000 per square meter, and Barcelona over €5,000, above Hamburg, Berlin, Frankfurt, Brussels, Milan, and Rome… But Spanish wages are low… This has left leading Spanish cities with some of the worst house price to income ratios in Europe.

Spain offers important lessons for cities in developing countries like India. Spain’s late development means that its experience has even greater relevance for us.

Spain's cities are unusual not on any single dimension but on the combination - density, mixed use, mid-rise (not high-rise) apartments, walkability, cheap and abundant transit, high car ownership but low car use, infrastructure preceding development, and municipally planned street grids. Spain is unique in getting all the dimensions right.

Indian cities, from metros to the lower-tier ones, are characterised by a far lower share of multi-tenement units, rigid land-use restrictions, high setbacks, poorly maintained or absent footpaths, infrastructure coming well after habitations emerge, and sorely deficient mass transit facilities (especially bus networks).

In India, exclusive land-use zoning is the norm, with mixed-use permitted only beyond generally 15-18 m roads and above, which are present in a very small proportion of the localities. In the older areas, commercial facilities in residential areas have emerged informally over time, whereas in the planned colonies and new developments, mixed use is restricted.

Indian cities have among the lowest share of urban households living in multi-tenement units, with Spanish cities being at the other extreme. Only 31% of urban Indian households live in flats (NSS 2018) compared to about 80% in Spanish cities, with Mumbai being the exception. The India NSS “flat” includes chawls, single-storey shared tenements, and informal walk-ups - so Indian numbers overstate what a Spaniard would recognise as a flat.

Similarly, Indian cities have among the lowest share of road network, not even a third of the UN Habitat norm. Most Indian metros are 6–12%, with only Delhi, the only Indian city with municipally planned extension, getting close.

I can think of at least a few big takeaways. Foremost, there’s no alternative to mixed-use, densified development for both greenfield and brownfield areas.

Given its high share of detached housing, Indian cities have a great opportunity to reinvent themselves. This can be done by increasing FAR, and more importantly, doing it in a manner that allows upzoning adjacent to 9 m and 12 m roads. As I blogged here, the current upzoning deregulation, confined to plots with road width greater than 18 m, is largely superfluous.

This must be coupled with planning norms like allowing for relaxations of setbacks, even dispensing with them and encouraging row housing, multi-tenement units, and mixed-use in terms of encouraging commercial amenities. The latter is about ensuring that people living in a locality should be able to buy their regular groceries and other household items and services from within there. Further, the local government fee and property tax regimes must consider lowering the layout development charges, building permission fees, and property taxes to encourage the realisation of these objectives.

These policies and instruments must be deployed with a long-term perspective (as against expectations of immediate results). The objective should be that they would shape incentives and enable the gradual redevelopment of brownfield areas as densified communities.

Second, we must use urban planning to lay down street network configurations that enable connectivity and walkability. Master plans and their development plans should keep this in mind. Minimising or even eliminating setbacks would be one step to enable such street networks. The prioritisation of walkability requires the infrastructure of footpaths and street connectivity to be able to walk, and the supply in terms of mixed-use amenities to create the demand. And all this must be combined with local campaigns to promote the culture of keeping footpaths free of encroachments.

Third, the current dominant trend across Indian cities of the emergence of gated communities in the suburbs must be examined. These communities, while attractive for their residents and developers, go against all principles of sustainable urban development. These are largely monocultures of upper-middle and higher-income housing (the maids and drivers, and others, commute from distant places), with exclusive residential zoning, limited or no mass transit connectivity, exclusively car-based, and very poor external street connectivity (large gated enclaves with one or two entry/exit points). They impose massive negative externalities on the city and locality, while appropriating all the benefits.

Fourth, mass transit must be at the core of all developments. All greenfield areas, in particular, must be planned around mass transit, in the form of transit-oriented development (TOD). This post discusses some principles for TOD in Indian cities, and this post outlines some of the challenges. This would require going beyond the current norm of merely giving higher FAR and offering significant incentives on fees and taxes to make it more attractive for developers to build inside the TOD zones.

Like in Spain, the challenge is to get the combination more or less right. The good thing is that all of them lie with the states and mostly with the cities themselves. It is only required for 2-3 cities to take the lead and strike out on their own in following these principles and reinventing themselves. They can be the lighthouses that guide urban development in India.

Weekend reading links

noreply@blogger.com (Urbanomics) — Sat, 18 Jul 2026 12:35:13 +0000

1. Are people overreacting to small struggles?

When asked if they would consider someone experiencing typical fluctuations in mood (described as broad happiness but occasional moments of worry, frustration or loss of confidence) as having a mental illness, more than half of young Americans say yes, up from just a fifth 15 years ago.

2. A picture of state finances.

3. The promise of quantum computing.

Quantum computers can transcend the limitations of the traditional binary computer bit, which can exist in two states, denoted by zero and one. By contrast, quantum bits, or “qubits”, can exist in both those states at once. This allows quantum machines to survey multiple potential solutions simultaneously, rather than dealing with them one by one like a conventional computer. One analogy is a maze. Where a quantum computer can examine the whole map to find a way through, a traditional machine will keep exploring dead ends until it finds the route. Quantum computers’ superior processing power should make them better able to generalise from small amounts of data and sift through multiple complex patterns...

But many companies are already experimenting with the technology because of its promised leap in capability, predicting early uses for the machines in areas such as chemistry and materials science. The idea is that because of their own workings and structure the computers will be better able to analyse and predict chemical behaviour determined by atomic and subatomic interactions governed by quantum rules. In a sense, they will be speaking the same language rather than translating an analysis into a string of ones and zeros as a traditional computer does. As a result, a sufficiently powerful quantum machine should in theory be adept at predicting the interactions between drugs and living cells that determine whether a new pharmaceutical will work. Such possibilities have already led tech companies to pair up with industrial groups.

4. India's trade account in a nutshell.

In 2025-26, its exports of services, at $421.3 billion, was close to the export of goods worth $446.1 billion. On the other hand, imports of goods ($783.4 billion) were way above the imports of services ($204.7 billion). Thus, while India recorded a merchandise trade deficit of $337.3 billion, it had a surplus of $216.6 billion on the services account.

5. Brilliant article by Simon Kuper on how football came to be dominated by Western Europe.

Western Europeans didn’t start by asking, “How can we win the World Cup?” Instead, they pursued a different goal: making amateur football cheap and widely available. The intended outputs were happiness, community and public health. Winning World Cups was a byproduct... I began playing football aged six, in 1976, after moving from London to Leiden in the Netherlands. Most Dutch boys I met belonged to a football club... The little Leiden region had dozens of football clubs. Some fielded 20 senior teams, seven teams of under-eights and so on. Many people built their identity and social life on being the right-back or linesman of the 14th team. The Netherlands in the 1970s reached two World Cup finals. Everyone played and understood how to play. Football is geometry — about creating space when you have the ball, and shrinking it when you don’t. That knowledge is all around you in western Europe, unlike in Asia, Africa, the US or Brazil... In 2017, the average Dutch person lived 1.6km from a football field. Neighbouring Germany’s football federation is the world’s largest sports association, with more than 7.7mn members...

As a father, I raised three footballers in Paris, now the game’s deepest talent pool. Almost all Parisian suburbs, or banlieues, have well-kept sports complexes, with artificial fields, used nonstop: at half-time of any amateur game, children storm on to the field for a kickaround. So structured is the system that my son had to earn a coaching diploma to train his little club’s under-eights. His own beloved coach, Mustapha Sangaré, who only joined a football club aged 15, now plays for Bulgaria’s Levski Sofia and Mali. He is far from an anomaly: almost 100 players across all squads in the current World Cup were born in France and just under 70 in the Netherlands.

In another article Tej Parikh looks at why China and India does so badly in football.

This is a striking statistic, pointing how globalised football has become and how the leading European clubs have become the feeding grounds for national teams.

At this World Cup, more than 72 per cent of players appear for a club outside the country of their national team, and almost one in four are foreign born. (More than half of Cape Verde’s squad was born outside the nation and ply their trade in various European leagues.)

6. In what will prove to be a dramatic decision, DP World, which operates the Jebel Ali port that has been paralysed by the closure of the Strait of Hormuz, is reportedly planning to build a new port and a container terminal on the UAE's eastern coastal area of Fujairah.

Shifting some of the port’s capacity outside Dubai marks a seismic change for the emirate, which has established itself as a global trade and finance hub partly off the back of Jebel Ali’s growth... But DP World’s plans align with a broader UAE government initiative to attempt to bulletproof its economy against future hostilities with Iran by reducing its dependence on the strait, where shipping has been disrupted by Iranian drones and missile strikes since the US-Israeli attack. The new project would deepen DP World’s presence on the Gulf of Oman, allowing containers to enter and leave the country without having to pass through the strait, before moving them on trucks overland to Dubai, Abu Dhabi and neighbouring Gulf countries. Since the war began at the end of February, Iran has fired nearly 3,000 drones or missiles at the UAE — more than any other country... DP World’s plans underline how the Iran war has forced governments and companies in the region to reconsider infrastructure and economic corridors developed on the premise that there would be uninterrupted passage through the strait.

7. Rote memorisation in schools is celebrated in China.

The guidelines to the gaokao, an exam for 18-year-olds and the world’s largest standardised test, describe memorisation as “the most basic level of ability”, placing it first among six traits that include comprehension, analysis and synthesis, appreciation and evaluation, expression and application, and inquiry. At the simplest level, the Chinese script itself, which operates at the level of the syllable and involves thousands of individually meaningful characters, requires years of memorisation... It is hard not to draw a contrast with the English-language west, where rote memorisation has taken on a faintly pejorative meaning. More than a century and a half ago, at the height of Britain’s industrial age, Charles Dickens was skewering the “facts alone are wanted in life” approach of fictional educator Gradgrind in the novel Hard Times.

8. Trump's makeover of the US State Department.

Abandoning the precedent of the past 60 years, Trump has brushed aside the foreign service officers who have typically run at least two-thirds of embassies. Of the 101 nominations for ambassadorships in his second term, just nine were career diplomats. All this is against the backdrop of swingeing cuts to the department, whose workforce has shrunk by more than 3,000, over 20 per cent, since Trump resumed office.

9. China's remarkable success in reducing air pollution by 60% since 2013.

10. Interesting that the IT sector explains half the difference in productivity growth between the US and EU.

Strikingly, even though the tech sector was only 9.2 per cent of US GDP, against 5.4 per cent of the EU’s, almost half of the difference in productivity growth between the two economies was explained by differences in the relative size of this one sector. Moreover, productivity growth in the EU’s (relatively small) tech sector was also measured as being lower than in the US one. So, overall, the tech sector alone accounts for well over half of the overall difference in growth of GDP per head.

This is important

Life expectancy for US men was 76.5 in 2024, against an average of 80.5 in comparable high-income countries. For women, it was 81.4 against 84.8. That is despite spending a far higher proportion of its GDP on health. The US homicide rate was 5.9 per 100,000 in 2023, against 1.3 in France and 0.9 in Germany. Its prison population was 542 per 100,000 in 2023, against 130 in France and 69 in Germany. Thus, if one takes a wider view of human welfare, the US is very far from superior.

11. China reports the lowest quarterly growth rate in decades at 4.3% for the second quarter of 2026. Industrial production and exports are propping up growth, even as consumption declines.

Retail sales added just 1 per cent in June from a year earlier, while fixed-asset investment was down 5.7 per cent year on year for the first half of the year, compared to 4.1 per cent in the first five months. Industrial production, one sign of strength, grew 5.3 per cent last month on a year earlier... Separate data on Tuesday showed exports soared 27 per cent year on year in June, adding to signs of reliance on trade to support economic activity... Julian Evans-Pritchard, head of China economics at Capital Economics, noted that the GDP data brought it “closer in line” with the consultancy’s alternative measure, which has been around 3 per cent.

Underlining the importance of exports, there was a surge in China's EV exports in June.

China’s monthly car exports rose to a record 1mn cars in June as part of an overall surge in trade that will heighten tensions with partners such as the EU. Shipments of cars rose 71.2 per cent from a year earlier to 1.06mn, putting the country on track to export more than 10mn cars this year, up from 7.1mn last year and more than double the 4.9mn in 2023. The surge in exports comes as domestic sales slow sharply following the phaseout of EV subsidies and a decline in demand for fuel-powered cars... The wave of Chinese exports has been driven by lower-cost cars boasting superior software, further threatening carmakers from Japan, South Korea, Europe and the US... China’s exports of rare earths in June fell 34 per cent year on year and 6.4 per cent in the first half, following tight export controls on the minerals, which are essential for high-technology products... The NBS’s Wang said China’s exports of green energy-related products such as lithium batteries and wind turbines increased 37.6 per cent and 35.6 per cent, respectively, during the first half.

And this highlights how production and exports have sustained growth.

Industrial production rose by 5.4 percent in the first six months of the year, versus the same period last year. High-tech manufacturing rose by more than 13 percent over that period. But fixed asset investment — which includes infrastructure, property construction and manufacturing — fell by 5.7 percent. Real estate development dropped 18 percent. The value of China’s exports surged by more than 20 percent in the first half. But consumer spending, which a Moody’s Analytics report said “remains the economy’s weakest link,” faltered. Retail sales of consumer goods increased by 1.3 percent over the first half of the year.

12. Ruchir Sharma holds that peak China was reached in 2021, and since then it has been a story of decline, papered over by exports and AI.

Since then, China’s share of global GDP has fallen in nominal terms from 18 to 16.5 per cent, while the US share has risen to 26 per cent. China’s growth rate has dropped below the rest of the world, including the US. In real terms, independent estimates now put China’s growth in real terms closer to zero than to the official target of 4.5 to 5 per cent... China’s population also peaked in 2021. Last year, births hit a record low, and deaths hit a record high. The working-age population is on pace to shrink by 75mn every decade this century... After adding little in the 2010s, net exports now account for about a third of the country’s growth, driven mainly by AI-related goods... And though every country now hopes for an AI-driven productivity miracle, the expected boost in China is about a third of a percentage point by 2030, hardly enough to halt its decline.

13. India agriculture statistics

If one looks at the growth areas in agriculture in the 12 years between 2011-12 and 2023-24, production of paddy and wheat rose by just 27 per cent. Fruit and vegetable production rose by 52 per cent, and milk production by 85 per cent, even though they did not receive any substantial support by way of subsidies or minimum support price procurement by the government. The true growth areas in agriculture are out of direct central government support and depend largely on producer enterprise... In 2023-24, the value of output of cereals (mainly paddy and wheat) was ₹8.5 trillion, while the value of the largely cooperative-controlled milk sector was ₹12.2 trillion.

14. Outbound corporate investments from India on the rise.

Indian companies have announced overseas equity investments worth more than $14bn in the first four months of the fiscal year that began on April 1, compared with $18.7bn in the previous 12 months. The outflows come as foreign investors flee India’s markets at the fastest pace ever this year, pulling out more than $23bn as of the end of June over a lack of AI champions.

15. Simon Kuper on Lionel Messi.

On the field, Messi sees everything. All his career, he ignored the ball for the first five minutes and instead walked around, memorising the position of each opponent and the spaces between them. But now he spends almost the entire game walking and scanning. When he breaks into a run, his teammates know he has seen an opening. They play to serve him. When he moved to the right wing against Egypt, seeing space there, the team remade itself around him. Argentina, two goals down after 78 minutes, won 3-2. Scaloni said afterwards: “We were not the ones who told him to go out to the right.” Messi moved right again against England and again Argentina came back to win.

16. The AI-boom is spilling over to energy sector.

Initial public offerings for energy firms raised $12.6bn in the first half of this year, according to data firm Dealogic. That marks the highest half-year level since the peak of the dotcom bubble in late 1999 and the highest first-half figure on record. It is well above 2025’s full-year total of $4.3bn. The surge in fundraising comes as access to the vast amounts of energy needed to run data centres emerges as a bottleneck in a multi-trillion-dollar AI investment boom... US electricity demand is projected to increase 39 per cent between 2026 and 2035, according to consultancy ICF, in large part due to ballooning demand from data centres...

Companies that have been able to raise money on public markets include those involved in complex, capital-heavy projects such as nuclear and geothermal power plants, while investors have also been willing to back businesses trying to develop new technologies... “This is a moment in which speculative projects are being funded and underwritten,” said Julien Dumoulin-Smith, a Jefferies research analyst covering power, utilities and clean energy. “They’re not just limited to venture capital or private equity.”... Nearly two-thirds of the energy companies that floated this year and last are now trading below their offer price, according to Dealogic. That compares with less than 40 per cent of IPOs across all sectors that are underwater.

And Wall Street Banks are already AI trades.

Four of the five big Wall Street banks reported yesterday: JPMorgan Chase, Bank of America, Citigroup and Goldman Sachs (Morgan Stanley chimes in today). The numbers were outstanding, as one would expect in a quarter when markets whipped around and big deals were done. In aggregate, equity and debt trading revenue at the four hit $38bn, up more than a third from a year ago and 60 per cent higher than two years ago. Investment banking fees, at $10bn on the quarter, have grown almost as much... It is AI that has markets churning and drives capital-raising. The banks are another example of the false “broadening” of the stock market that has also driven up industrial and utility stocks in the past few years. All these sectors have lived, and could die, with AI.

And their profits are not confined to the US, with even Asia becoming a major source.

Equities trading in Asia is helping power a record-breaking run from Wall Street’s banks, with the region on course to surpass Europe as the industry’s second-largest source of revenue behind the US. In the past 12 months, clients of large investment banks have ploughed into companies in Asia that provide critical infrastructure to the AI semiconductor industry, including South Korean SK Hynix, Taiwan’s TSMC and China’s Cambricon Technologies... In the most recent quarter, the largest investment banks collectively reported an unprecedented $25.7bn in earnings from equities trading and called out Asia as a crucial factor in the growth.

17. Even by the low standards of Trump 2.0, this is surely an outrageous example of private profiteering from public office.

Donald Trump’s social media company has discussed charging traders and investors as much as $100,000 a month for faster access to the US president’s posts on his Truth Social platform. Trump Media & Technology Group (TMTG) has quoted the six-figure monthly sum in talks with prospective buyers of the “Truth API” data service, according to people familiar with the matter. Proprietary trading firms and hedge funds pay huge sums for ultrafast data feeds because every millisecond counts when reacting to market-moving news. Trump often makes major announcements on Truth Social that trigger huge fluctuations across global markets... TMTG, which is majority owned by the Trump family, controls Truth Social...

A pitch sheet circulated by TMTG to promote Truth API, seen by the FT, lists 10 “documented market-moving posts” from the president’s Truth Social account. On April 9 2025, for example, the document says Trump’s “THIS IS A GREAT TIME TO BUY!!!” post “restored” $4tn to the market capitalisation of the S&P 500. Trump’s post in early June that the US would hit Iran “very hard tonight” caused a 6 per cent intraday jump in oil prices, the document says. “When @realDonaldTrump Truths, the world reacts,” the document continues. “No comparable signal exists. No official API has ever been offered. Until now.” Trump has also touted specific stocks, complimenting companies such as Nvidia and Apple and fuelling rallies in their share prices. More recently after the outbreak of the war with Iran, Trump posted on March 23 that there had been “very good and productive conversations with Iran”, sending oil prices falling sharply.

The probation problem in India's public sector

noreply@blogger.com (Urbanomics) — Thu, 16 Jul 2026 02:37:14 +0000

Public recruitments come with a one- or (mostly) two-year probation period. The idea is to correct a Type I error (a false positive recruit) in the recruitment process.

Underlining its importance, the DoPT Master Circular on Probation/Confirmation of 2019 has this to say about probation:

‘Probation should not be treated as a mere formality. The existing powers to discharge probationers should be systematically and vigorously used so that the necessity of dispensing with the services of employees at later stages may arise only rarely.’

Unfortunately, while it is part of all recruitment rules, it is widely believed that there are few instances of discharge during probation in any local, state, or central government recruitments.

Before we analyse this, it must be clearly stated that data on this is very patchy in the absence of disclosures by either the DoPT, UPSC, state PSCs, or the central or state government cadre controlling agencies. Empirical evidence, or whatever can be gathered, shows that across every service - All-India Services, central Group A civil, central Group A technical, state civil services, state police officers, state medical services, the great mass of teachers, constables and healthcare workers - the discharge rate on performance grounds is effectively zero.

This is what Claude gathered about central government cadres.

And this about state government cadres.

It must be disclosed that both the data are not validated, but conforms to the widely known anecdotal knowledge.

The rare discharges that do occur are almost invariably for fraud (fake caste, disability, TET or degree certificates) discovered post-selection, or for medical/physical failure during pre-probation training. Fraud detection and physical fitness testing are legitimate filters, but they are not the probation function. This has been confirmed by every major civil-service review (Hota 2004, Yugandhar 2003, Second ARC, Baswan 2016).

There are three examples of probation discharges outside of fraud and medical or physical ineligibility. An estimated 2-5% of the scientists and engineers recruited by the Department of Atomic Energy are discharged for non-completion of the academic curriculum. An estimated 3-15% of the police recruits by state and central government paramilitary forces are discharged for physical and disciplinary reasons (not deficiencies in the acquisition of policing capabilities). Thanks to supervision by the High Courts, an estimated 0.5-1% of every batch of state civil judges and munsiffs are discharged for failure to meet defined output and quality metrics during probation.

The absence of any discharge deterrent increases the stakes associated with the recruitment process itself. This most likely contributes to the fraudulent practices that are pervasive across recruitments at all levels.

This is a comparative assessment of probation discharges globally and from India’s own private sector.

The deterrent effect of even a few discharges can be significant.

So what can be done about this?

The probation instrument has not served its purpose because the framework it operates within provides neither the assessment infrastructure (objective performance criteria linked to a role profile), disclosure requirement (not even DoPT publishes data on probations), nor the political-economy incentive (senior officers who discharge a subordinate invite litigation and administrative-tribunal action). In the circumstances, reforming the probation clause without reforming both the criteria and the incentive structure will change nothing.

A low hanging fruit is to shine light on the problem and make it mandatory for all departments to disclose the status of probation confirmation, extensions of probation, and affirm that all the probationers met the requisite benchmarks for the same.

The first step in any systematic effort would be to define a few objective and easily captured metrics of probation performance that are proximate to their roles. This would usher in transparency and shape expectations among probationers about their roles.

Second, the probation performance evaluation should be made a mandatory exercise, by a committee consisting of the Departmental head (or representative), officer responsible for training within the Department, and the Director of the Training Academy. This would mitigate the political economy deterrent to discharges.

Third, there could be a mid-way evaluation of the probationers by the same committee, which discusses any laggards and inform them about where they are falling behind. The same should be documented. This could shape expectations and ensure that the probationers are forewarned before any discharge.

Fourth, the evaluation reports should be submitted every year by the Departments to DoPT (and its state government equivalents) and the UPSC/SPSC, failing which no recruitments by the Department should be allowed. This would bring departmental accountability to the process of probation confirmation.

The aforesaid measures would constitute a simple and realistic start to addressing one of the most farcical features of the recruitment process.

Higher FARs, but very few plots can avail them

noreply@blogger.com (Urbanomics) — Wed, 15 Jul 2026 02:31:00 +0000

Many state governments in India have issued executive directions increasing the permissible Floor Area Ratios (FARs) in their cities. However, these upzoning reforms are likely to struggle to meet the objective of densification due to restrictive conditions to avail the increased FAR. Specifically, three gate-keeping elements - minimums on road width and plot size, and a maximum on height - leave the upzoning reforms largely stillborn.

To understand why, we need to keep in mind the street layout of the typical Indian city. The colony street widths are typically 9 m (30 ft) or less, and at best 12 m (40 ft). Even the connecting roads are no more than 12 m. In any city, a very small proportion of properties, and an even smaller proportion of residential land use, will have road widths greater than 9 m. Only the arterial roads, which are in any case mostly commercial and higher-valued, are above 12 m.

A comparison of upzoning reforms across the ten biggest states reveals some interesting insights. For a start, the upzoning itself is generally marginal, and even where significant, the higher FARs can be realised only on wider roads. In simple terms, the upzoned FAR apply to a tiny minority of parcels - greenfield layouts and edge plots on arterial roads. Every state except Gujarat, UP (individual) and Haryana (small plot) sets the FAR uplift threshold above 12 m - typically 18 m, 24 m or 30 m. But even for the three, the uplift is marginal and only for a few categories of properties. Also, none of the three touches group housing or vertical redevelopment on narrow-road plots.

Further, plot size and setbacks compound the problem of a minimum road-width gate. Even where a 12 m road technically qualifies, high-rise / group-housing rules require minimum plot sizes of 750–2000 sqm and setbacks of 6–12 m. In existing settlements, individual plots average 60–150 sqm, and assembling five to twenty of them is legally and commercially nearly impossible without a TDR/land-pooling instrument. Even then, practical challenges are daunting.

This also means that even the TOD zones cannot benefit from the upzoning. In existing town cores, which are where TOD catchments actually sit, FAR reform delivers almost nothing until the road-width and plot-size gates are lifted or bypassed.

In other words, the upzoning reforms largely bypass the built-up city and are relevant only to the greenfield areas. In these areas, the uplifts linked to higher road widths end up benefiting only the large developers. They, in turn, build high-rise gated communities of higher-end housing, mostly unconnected to mass transit and with multiple car-users in each household. Ironically, this also ends up expanding the sprawl, flooding the roads with cars, thereby worsening traffic and increasing pollution.

On the other hand, it does nothing for the smaller developers who are likely to develop affordable mid-rises (say, 6-12 floors) inside the existing colonies. Instead, they end up constructing low-rises (up to 4-5 floors). Further, the unit economics given high land prices mean that even these low-rises gravitate towards the suburbs.

It is these mid-rises that are likely to contribute meaningfully to expanding supply and addressing the affordable housing problem. Unless the upzoning covers the 9 m road width and smaller plots (which make up the vast majority of the potential developable properties in any city), there cannot be any significant impact on housing supply and the affordable housing problem.

Further, to realise the full potential of such upzoning, it must be complemented with sharply increased mass transit services, especially buses, that cover these colonies. The quality, frequency, and connectivity of the bus network must be high enough to induce people to shift from car usage.

Workers and startups are helping train AI to replace them

noreply@blogger.com (Urbanomics) — Mon, 13 Jul 2026 02:01:57 +0000

Data annotation work is increasingly moving up the value chain, from tagging and labelling data to replicating the work of semi-skilled (on the factory floor) and skilled (consultants, analysts, lawyers, engineers, and doctors) workers.

Startups sell data to AI labs, which use it to train and refine their AI algorithms and develop software products/solutions that replicate the work of these workers. In other words, the semi-skilled and skilled workers, or at least some among them, are feeding their time and skills into the AI algorithms that seek to replace them and their kind. Both the training startups and those workers offering their services to them are basically helping make themselves redundant.

On this, the FT has a very good film about how Indian startups are paying factory floor workers and gig workers (and even people in their homes doing regular household chores) to use cameras and record their work. Data annotation is becoming the new BPO for India’s IT industry.

The Ken has an article that raises the possibility that for all the attention and hype around robotics, Indian startups might remain stuck at the lowest end of the robotics value chain - data collection.

India was the back office for the IT boom. It became the annotation and reinforcement-learning labour pool for the generative AI boom. It is now emerging as the behavioural data factory for the physical AI boom... Building the robot is only half the problem. Building the intelligence behind it is much harder. That requires data. Vast amounts of it. Unlike large language models, which were trained on the equivalent of hundreds of years of human reading scraped from the internet, robotics companies are working with barely a fraction of that in video... What they need is meticulous, first-person recordings of humans interacting with the physical world, carefully collected, annotated, and painstakingly structured.

So the industry turned to India. Across the country, workers are recording themselves doing everyday chores for data-collection firms, which then sell that footage to companies such as Tesla, Figure AI, and Agility Robotics to train their humanoids. Indian startups see this as a moment to claim a seat in the global AI value chain. The country has over 260 robotics startups, and investors are beginning to pay attention... The footage being recorded by Indian workers becomes proprietary once it leaves the country. The datasets assembled from it are accumulating on foreign servers. The foundation models trained on them are owned by foreign companies.

The NYT has an article about how startups like Handshake, Mercor, and Surge in the US are paying skilled workers to collect data on their work.

Mercor and a handful of similar start-ups are the primary middlemen in a supply chain of “human data” that may power the next generation of A.I. As OpenAI, Anthropic and other major ventures compete to become the industry’s dominant platform, the market for premium data that has been vetted by experts is exploding…They need mathematicians to annotate proofs, lawyers to mark up briefs and professors to grade essays… To use the parlance of the industry, data labeling has moved up the “value chain,” and the start-ups that offer this service have become some of the fastest growing in Silicon Valley… The data-training start-ups see a lucrative opportunity in recreating workplaces in miniature: controlled environments in which their gig workers can evaluate and reproduce emails, memos and slide presentations in context. The information emerging from such a setup, the companies boast, will help shrink the gap between what A.I. models can accomplish and what office workers actually do from one minute to the next, as ideas and instructions flow between meetings, documents and applications…
To keep improving their models — to make them more useful, more sophisticated, less prone to hallucination and mistakes — A.I. companies heavily refine what goes into them. That’s post-training, and it includes buying data from vendors like Handshake and its competitors… Deeptune, a start-up that makes “training environments” with simulations of the software programs, like Slack and Salesforce, that many workers toggle between all day long to get their work done. The idea is to painstakingly create a mirror image of, say, an investment bank so that A.I. can observe every interaction…
It may turn out that once OpenAI, Anthropic and others have taught their models to perform a certain job, their need for more training data in that area could sharply decline. In this way, Mercor, Scale, Handshake and their peers are much like the elite freelancers they employ: making money today, but in danger of being dropped tomorrow… People sign up for data-training gigs for a variety of reasons. The main one is, of course, money… Though the labor is unpredictable and rates vary… the workers who cobble together enough shifts can generate meaningful income. People might sign up because they have been laid off, or because they can’t find enough work in their field. They might do it because they’re eager to get “A.I.” on their résumé, or because they need extra cash in retirement… Many people who contract for these companies understand that this is a short-term opportunity, a brief chance to train the models to automate jobs before they themselves are automated out of the job of training models.

I asked Claude to generate a visualisation of this market landscape, including an assessment of the Indian landscape. The numbers are clearly estimates and must be validated (though at a ballpark they appear alright).

The unit economics of the data chain shown below for a garment worker in India is instructive. She gets roughly ₹400 a day to wear the camera (or $0.60 per hour); the startup pays the factory ₹450–500 per hour; US-based startups like Human Archive price data at $1–10 per hour; and once annotated and packaged, it sells to global robotics labs at $15–50 per hour. That is a 25–85 times markup, and every rung above the worker is owned outside India.

The graphic also shows that the vast majority of AI workers are doing the BPO equivalent, whereas the vast majority of funding is going to those building the data centres. India has 170-odd AI startups that have raised $2.6 billion in total and over 260 robotics startups, but the genuine model/product builders are a tiny set, and the majority have rebranded annotation as an AI line of business (iMerit, Objectways, Awign, Karya, Deccan AI, Human Archive, Egolab, Neo Cambrian, Humyn Labs, RoBoEra, etc.).

It must also be highlighted that in the majority of cases in India, the data goes from the garment worker to an Indian data aggregator to a robot-brain lab in San Francisco, and comes back as a robot/humanoid. The frontier LLM labs are not in that loop. This also means that none of the emerging governance conversations about frontier models - safety frameworks, export controls, model-access negotiations - touches the mainstream data collection work being done in India. India is negotiating hard for access to frontier language models while simultaneously handing over, for ₹400 a day, the training substrate for the physical models that will actually displace its manufacturing workforce. Those are two different conversations, and only one of them is being had.

Further, as the Times article highlights, while these annotation startups are flourishing now, they may not be sustainable ventures. Once experts teach the models to do something, their services are no longer needed in the same way, and the vendors themselves need the models to keep improving to show they add value, while needing them to remain imperfect so clients keep coming back.

I asked Claude for historical precedents and got this:

Frederick Winslow Taylor’s explicit programme, from the 1890s, was for management to “gather in all of the great mass of traditional knowledge which in the past has been in the heads of the workmen.” Skilled machinists were stopwatched; the Gilbreths filmed them with chronocyclegraphs — a literal 1910s head-camera. Workers cooperated because they were paid piece-rate bonuses to do so. The tacit craft was decomposed into instruction cards and handed to cheaper, unskilled labour. Outcome: enormous productivity gains, the collapse of the craft wage premium, a machinists’ revolt, congressional hearings in 1911–12, and Taylorism banned in US government arsenals by 1915. It took roughly fifty years and the postwar labour accord before the gains were broadly shared…
In the 1990s American hospitals routed physician dictations to transcriptionists in Bengaluru and Chennai; it was unglamorous work, but India was good at it. That corpus is precisely what trained speech recognition. The industry peaked and then largely evaporated. Compensation to the transcriptionists: zero… most startups in this space risk meeting the same fate as the transcription companies of the 1990s.

In this context, I am reminded of the claim made by Daron Acemoglu and Simon Johnson in their book Power and Progress that the trajectory of technological progress is a political choice made by society and should not be left to corporations and technocrats. Their central claim is that the direction of technology is a social choice, not a technical destiny, and that redirecting it requires countervailing power rather than better-intentioned technocrats.

The problem, though, is that globally, and especially due to the Trump 2.0 regime, the rule makers have surrendered agenda-setting to Big Tech and AI Labs. Closer home, India has almost no leverage over the direction of frontier AI. Instead, its leverage is confined to the terms on which its labour and data enter the supply chain, and not to bending the technology’s arc.

In the circumstances, what can a country like India do?

Here are some thoughts for consideration. One, a statutory floor rate for training-data contribution and an industry-led collective licensing body for data work are both administratively feasible and could increase value capture (from the worker’s current share of 1-2% of the value created) without banning anything. A comparator is the model of SoundExchange (US) or PRS (UK) in the music industry, which acts as a government-designated clearinghouse that collectively licenses music, collects usage fees, and distributes royalties to creators, effectively removing the burden of individual licensing. This model would also subtly frame the market in terms of treating data as labour, and not as mere raw material.

Second, on the regulatory side, it may be useful to revisit the DPDP Act provision that permits employers to process worker data without explicit consent under “employment purposes”. Instead, there should be purpose limitation, or restrictions on repurposing training data for other activities, and consent requirements of all involved.

Third, public spending on AI innovation and procurement preference could be made conditional on the recipient retaining licensing rights to datasets collected from Indian workers rather than doing work-for-hire. This would frame the collection of data as an input and not a product, and industrial policy could price it appropriately. Fourth, there is the argument about extending statutory instruments like the gig worker welfare boards or the Code on Social Security present in some states (Rajasthan, Karnataka, etc.) to cover data work. It could help build countervailing power.

But pursuing these agendas can be costly. This being a global market, prohibiting or putting too onerous terms on value capture and the entry of data into the supply chain will backfire by moving the work to Vietnam, Ethiopia, or the Philippines. Besides, for the Indian workers, already facing an acute scarcity of jobs, the choice isn’t really on offer, and ₹400 a day is ₹400 a day. There is a collective action problem here which calls for multilateral engagement through a forum like the ILO.

But this should not mean that we sit back helplessly and allow the market dynamics to play out. Instead, before enacting any of them, there must be a public debate on the merits or otherwise of these proposed measures. What are their respective costs, and what can be done to mitigate them? What versions, if any, of these measures should be enacted? Such debates are essential to make informed and collective social and political choices.

The public debate is important since the agenda-setting process here, like with any technology change, pushes certain considerations to the forefront while also marginalising certain others. Almost always, the former represents the interests of the corporations and elite beneficiaries of the change, and the latter represents those of the vulnerable and voiceless. Therefore, such agenda-setting debates are a purely political activity, with profound social implications.

It is also important since there is the distinct likelihood that India could spend the next five years as the world’s back office for the third time, and when the juice has been sucked out and value captured, there could be nothing left standing that India owns.

PS: In this context of collective action problems, it is worth taking inspiration from one very impressive and encouraging breakout (which has not received the level of attention it deserves) from South Korea. It is a tribute to the maturity and wisdom of the country’s corporate and political system and the robustness of its democracy that Samsung and SK Hynix agreed to share 10% of their windfall profits from memory chip sales, with no ceiling on payouts, with their employees for the next ten years. Sample this.

Samsung Electronics... agreed last month for employees to share the chipmaker’s blockbuster profits from an AI-led boom... SK Hynix... handed employees a similar profit-sharing deal last year... Samsung is also going to give Won500mn loans at low rates to employees... Samsung and SK Hynix together control much of the market for the advanced memory chips used in AI servers. Employees at both companies are in line for average annual bonus payouts of Won600mn, which compares with a national average salary of about Won50mn... district of Hwaseong... expected to gain corporate income tax receipts of Won1tn to Won1.3tn from Samsung alone this year, an extraordinary sum for a city authority whose annual budget is about Won3.5tn.

Weekend reading links

noreply@blogger.com (Urbanomics) — Sat, 11 Jul 2026 04:05:56 +0000

1. FT long read on how senator Deborah O'Neill, as chair of the Parliamentary joint committee on corporations and financial services, has single-mindedly exposed and brought the knees the Big Four auditing and consulting firms in Australia.

Deborah O’Neill has led the charge against KPMG in Australia over a client confidentiality scandal that prompted the departure of the firm’s chair, chief executive, chief operating officer, audit leader and a senior partner over the past month... comes on the heels of a similar implosion at PwC. The rival Big Four firm came unstuck when a data leak led to the exit of senior management... An EY employee was charged with accessing the bank details of Prime Minister Anthony Albanese while working on contract at Australia’s biggest bank. Meanwhile, Deloitte partially refunded the Australian government after admitting that it used AI to compile a report...

In 2023, the Labor senator forced the publication of emails that implicated PwC partners in the tax leaks scandal. PwC partners were caught sharing secret government tax plans that one of them had obtained from his work on an advisory board in Canberra, in the hopes of winning business in the US. This year O’Neill used parliamentary privilege to air allegations made by a KPMG whistleblower that had been inadequately investigated by the firm. KPMG has now been exposed as having used confidential information from existing audit clients to try to win new business from rivals — some from PwC as its audit customers looked to switch in the wake of that firm’s woes...

She entered parliament in 2010 having spent her career in education. O’Neill soon discovered that some Big Four consultants acted like some of her former pupils — copying the answers from the back of the book and then marking their own work, as she puts it — and used her role to put the leaders of the firms under pressure.

2. Soumaya Keynes points to a fascinating study by Rebecca Diamond of Harvard University of the use of GLP drugs that appears to show increased confidence and employment rates among women in the US. The study finds, using data gathered between 2021 and 2023, that the poorest third of women in the US suffered an obesity rate 14 percentage points higher than the richest third, whereas the gap was negligible for men.

The study's main findings:

After 18 months, women using GLP-1 drugs who start off without a job enjoy employment rates 27 percentage points higher than otherwise similar non-users. Women who start off with a job see their employment rate fall slightly, and although the data is too noisy to pick out effects on their earnings, it looks like their household income rises by 10 per cent. That second effect is a bit surprising, and possibly explained by parallel developments in these women’s love lives. Diamond estimates that GLP-1 drugs give single women a dramatic 29 percentage point increase in their chances of coupling up. On average, their new partners are richer than them, giving their household income a bump. Which could explain why a few of the women losing weight then feel able to drop out of work.

The study also points to a more disturbing consequence.

So far at least, GLP-1 drugs are disproportionately used by the rich. In Diamond’s study two-fifths of the women paid for the drugs out of pocket, at a median cost of $275 a month. Research based on Voy prescriptions shows how, adjusting for relative obesity rates, uptake is skewed towards more affluent areas. If obesity becomes an even stronger signal of economic disadvantage, the stigma attached could grow.

3. The rise of London's King's Cross area as perhaps Europe's AI capital.

Two decades ago, King’s Cross was central London’s most neglected district. Today, it is home to the main foreign outposts for several of the world’s wealthiest companies, from Big Tech giants Google and Meta to their richly funded AI challengers including OpenAI, Anthropic and Jeff Bezos’ Prometheus. AI researchers and entrepreneurs are packing out the area’s canal-side cafés so densely that venture capitalists prowling for their next deal are struggling to prevent their coffee meetings from being overheard by rivals.

For many, this resurgence can be traced back to one individual: Sir Demis Hassabis, the DeepMind co-founder and Nobel laureate who stayed in London to build his AI lab following its sale to Google in 2014 for £400mn. “Demis keeping DeepMind in London and resisting the gravitational pull of [America’s] West Coast is the most important thing that has ever happened to the London tech ecosystem,” says Tom Hulme, a tech investor at Alphabet’s GV venture capital unit... Just as PayPal helped launch the careers of a generation of Silicon Valley founders and investors including Elon Musk and Peter Thiel, a “DeepMind mafia” in London is pulling in billions of dollars to AI start-ups founded by Hassabis’s former lieutenants, including David Silver’s Ineffable Intelligence and Tim Rocktäschel at Recursive Superintelligence...

It was Hassabis’s pursuit of an “artificial general intelligence” capable of scientific research and a wide range of human tasks that in many ways kick-started the current AI boom. DeepMind’s sale to Google prompted Elon Musk to set up a research lab to counterbalance the internet group’s dominance of AI; that lab was OpenAI. DeepMind went on to make a series of AI breakthroughs including AlphaGo, which in 2016 beat the board game Go’s world champion Lee Sedol, and AlphaFold, which used deep learning to predict protein structures with superhuman speed.

King's Cross has emerged as the Canary Wharf of tech in UK, and this description is apt and underlines the continuing importance of personal interactions and connections.

The density of AI talent in King’s Cross was why the government’s scientific research agency Aria took a “very conscious decision” to base itself there rather than Whitehall, says Pippy James, its deputy chief executive. “We were definitely inspired by Kendall Square in Boston,” she says, referring to the area surrounding MIT where Google, Microsoft and Amazon, as well as biotech companies Moderna and Novartis, have offices. “Value creation comes from those serendipitous collisions.” In recent weeks there has been a steady stream of American AI companies announcing moves into the area. OpenAI and Anthropic have signed leases for tens of thousands of square feet in King’s Cross. Others moving in include Bezos’s “physical AI” company Prometheus, Cursor, the AI coding company that recently agreed a $60bn sale to SpaceX, AI agent group Perplexity and open model developer Reflection. Google, which already has many researchers and engineers in the area, plans to start moving staff into its vast new “Platform 37” office this summer after almost a decade in development.

4. This is a striking factoid about the importance of chips now.

With SpaceX going public, the list of the 10 most valuable US public companies is entirely made up of tech companies for the first time. Of those, three are semiconductor specialists. But with chips a key ingredient in AI, the other seven are also now all designing their own chips.

Some stats about the global chip squeeze.

... Elon Musk’s xAI to rent out spare capacity in its data centres. In recent weeks, Anthropic, Google and start-up Reflection AI have agreed to pay a total of around $2.3bn a month — or $28bn a year. This looks like a big return on Musk’s data centre investments. As of March this year, xAI’s total capital spending over its lifetime totalled $26.5bn... this surge in demand has already prompted a huge increase in supply, both of planned chipmaking capacity and newly minted chip stocks. One sign is the $600bn that memory chipmakers Samsung and SK Hynix said this week they plan to invest in Korea. Another is the $29bn that SK Hynix hopes to raise when its American depositary receipts begin trading in the US next week... TSMC has said it will boost its capital spending by as much as 37 per cent this year, as it did in 2025. But those increases follow two years of retrenchment and would leave 2026 capex only around 50 per cent higher than 2022. Contrast that with the biggest buyers of AI chips. Seven of the largest data centre operators are planning to spend an astounding $848bn this year, at least five times what they spent in 2022, according to a calculation by the newsletter Exponential View.

5. On the new bonds issued by SpaceX.

The bonds enjoyed very robust demand at the point of issuance, but some see that as a problem in itself. Allianz’s chief investment officer has described the market’s willingness to hand money over to Musk as a clear sign that we have moved from “a healthy boom, a stretched boom . . . into bubble territory”. Ominously, the bonds have weakened since they launched.

6. The AI LLMs scorecard.

Where will Sarvam stand?

Also national scorecard.

7. The low-margin business of mobile phone assembly. Amber Industries which makes air conditioners for eight of the top 10 brands and more than a quarter of all ACs made in the country, now proposes to assemble smartphones for Oppo.

Now, the company plans to sub-lease a part of Oppo India’s factory in Noida, set up SMT lines, and start assembling phones there... But smartphone assembly is one of the toughest businesses in electronics manufacturing... The target is to eventually assemble about a fifth of Oppo India’s volumes, scaling from roughly 8 million handsets in the first year to nearly 15 million in the second... Amber expects Ebitda margins of 1.5–2%, excluding benefits from the government’s production-linked incentive (PLI) scheme. That’s well below the 8.8% Ebitda margin generated by its broader electronics business in FY26, and the 7.1% operating margin recorded by its AC-heavy consumer-durables segment... Take Dixon, for instance. The company already accounts for nearly one-fifth of India’s smartphone output. Even at that scale, smartphone assembly, aided by PLI incentives, generates Ebitda margins of only about 3%.

8. AI boom compared with historical episodes.

9. On the rise of non-compete clauses in OECD countries and their adverse impact on productivity.

About 30 per cent of employers surveyed by the OECD said they had increased their use of the clauses in the past five years... It estimates that a 10 percentage-point increase in the prevalence of non-compete clauses in an industry was associated with a 1.9 per cent decline in the level of labour productivity, with workers stuck in sub-optimal jobs and firms less able to gain new skills. In many countries, non-competes have spread into parts of the labour market where the original justification of protecting sensitive information and firm-specific information is “weak or absent”, the research found, pointing to their use among entry-level fast-food staff in the US, manual workers in Italy and childcare workers or yoga instructors in Australia.

10. The market concentration in DRAM chips.

A market in which a monopolist owns 100 per cent gets an HHI of 10,000, a duopoly scores above 5,000, and a perfectly competitive market approaches zero... The US DoJ considers anything between 1,000 and 1,800 points to be “moderately concentrated”. Per Counterpoint Research, as of the first quarter of 2026 the memory market is 38 per cent Samsung (South Korea), 29 per cent SK Hynix (South Korea), 22 per cent Micron (US), 8 per cent CXMT (China), 2 per cent Nanya (Taiwan), and 1 per cent everyone else. This gives us an HHI of 2,838... Both Samsung and SK are two of Korea’s largest conglomerates (the so-called chaebols) which benefit from cosy relations with the state, so viewing them as fierce competitors in the same memory market might be wrong-minded in this case... And if the two companies function as a single economic entity in the global DRAM market, we should probably count them together for HHI purposes. And doing this we get a much higher HHI reading of 5,042. That’s above 5,000 —the HHI of a perfect duopoly.

11. China’s excess capacity in manufacturing requires something similar to what was done by the former Prime Minister Zhu Rongji.

In the late 1990s and early 2000s… under Zhu’s slogan of “zhua da, fang xiao” or “grasp the large, let go of the small”, Beijing retained its grip on key strategic industries while relinquishing control of a vast sea of smaller companies and factories…Thousands of mines, steel mills and other industrial sites were shut for good. An estimated 30mn to 40mn workers lost their jobs. The process was deemed painful but necessary: not only in setting up China’s accession to the World Trade Organization in 2001, but in freeing Beijing from supporting uneconomic industries…
Over the past 15 years, as China’s share of global manufacturing surged to around one-third, the share of lossmaking industrial businesses jumped from about 10 per cent in 2010 to nearly 25 per cent last year, according to the MERICS China Overcapacities Monitor. This dynamic exists across everything from steel and cement to cars, computer chips and robots. Take the automotive sector for example. Domestic car sales last year totalled 23.9mn against estimated production capacity of 45mn to 50mn. Sales are highly concentrated among a clutch of leading companies. According to HSBC, more than 70 per cent of EV sales — including plug-in hybrids — are being soaked up by 10 brands, leaving 47 others jostling for the remainder. In the shrinking market for petrol and diesel cars, 10 brands have about 70 per cent of sales and 73 others compete for the rest.

12. South Korean capitalism and windfall profits sharing - SK Hynix and Samsung edition.

Soaring global demand for high-bandwidth memory chips used in AI systems has propelled SK Hynix and Samsung Electronics to record earnings. This week Samsung announced quarterly operating profit of Won89.4tn ($59.7bn). The windfall is being shared with employees. Last September, SK Hynix agreed to pay workers 10 per cent of annual operating profits for a period of 10 years. Samsung followed with a similar arrangement in May after its union threatened strike action. With both firms expected to earn hundreds of billions of dollars this year, average bonus payouts per memory chip worker could reach about Won600mn ($400,000) at Samsung and even more at SK Hynix. Such amounts are staggering in a country where the average worker earns Won50.6mn per year, according to Korea Enterprises Federation data.

The Bank of Korea has warned of potential inflationary pressure as a result, and towns where many semiconductor workers live are undergoing property price jumps. Competition is intensifying for places at universities offering semiconductor “contract” programmes that guarantee jobs at Samsung Electronics or SK Hynix upon graduation. Admission scores required for some such courses now exceed the average for natural sciences at Seoul National University, the country’s top-ranked university, and are just below those needed for medicine... The boom is also reshaping Korea’s marriage market. Matchmaking agencies, which are known for using meticulously harsh metrics to rank clients, are now giving higher points to chip workers.

13. Data centres are consuming massive amounts of power and water.

Data hubs already devour more electricity globally than all but 10 countries. About 448 terawatt hours last year if you’re interested. The AI boom means that amount is on track to roughly double within four years... By 2030, they could be using enough water to meet the basic needs of all 1.3bn sub-Saharan Africans for a year, UN researchers estimate.

And it is provoking backlashes. Sample this from the US.

An unprecedented 75 US data centre projects worth around $130bn were blocked or delayed in the first three months of this year, nearly as many as in the whole of 2025, says the Data Center Watch research group. It reckons active opposition group numbers have grown from 396 at the end of 2025 to 833 by the end of March.

14. The Strait of Hormuz squeeze was not as bad as earlier episodes.

15. Transformers are at the heart of power transmission, distribution, and use. Thanks to the AI and data centre boom, transformer prices have gone over the roof.

Specialist electrical steel — essential for transformer cores — is produced by only a handful of global suppliers, many of whom are struggling to keep up with the surge in demand. Market growth, price volatility and limited mining capacity have also strained supplies of copper, crucial to the conductivity of windingsaround a device’s core. But one of the most acute bottlenecks is the shortage of skilled workers needed to carry out complex, labour-intensive manufacturing tasks...

With up to 80,000 different designs, most transformers still have to be built largely to order, taking three to six months to make. The most demanding stage is the windings, when copper wire is applied around a transformer’s core — a “beautiful” process, according to Bruno Melles, an engineer now leading Hitachi’s global transformer business. Each winding is unique and is “still a human manual activity that we’re very proud of”, he says. The number and pattern of these windings dictate voltage — fewer turns lead to lower voltage while higher-voltage devices can have multiple windings stretching hundreds of kilometres. Once complete, the assembly is placed in a protective outer metal shell, where oil acts to insulate and cool the device...

The world’s biggest transformer manufacturers have reported tens of billions of dollars in backlogs in the first quarter of 2026... US developers are turning to imports. The EU, Mexico, South Korea and Brazil are the biggest suppliers of power transformers to the US, together accounting for more than three-quarters of imports by value last year.

Into this mix come innovations in the form of modular solid-state transformers that use modern power electronics and respond dynamically to changing power needs, enabling real-time monitoring and control (which legacy transformers with their steel and copper cannot do).

The loss of financial market discipline

noreply@blogger.com (Urbanomics) — Fri, 10 Jul 2026 02:09:09 +0000

This post will provide a framework for thinking about the erosion of financial market discipline.

The FT has an article on an inflating earnings bubble in the financial markets.

Analysts are now forecasting a 25 per cent increase in S&P 500 company earnings for the coming year, according to Bloomberg data… Ben Inker, co-head of asset allocation at GMO, said forecasts for the next two years were “rising at an exceedingly high rate, nothing we have seen outside of a crisis recovery”. Consensus estimates for coming-year profits have risen by almost 20 per cent in six months, the biggest such jump since 2021…
Capital Economics analysts warned this week that “AI-related equity markets may be approaching a point where earnings expectations and capital expenditure assumptions become difficult to sustain” and a correction in these could “trigger a broad equity market pullback”. Michel Lerner, head of UBS’s investment analytics platform HOLT, said “shares in the AI food chain are priced to maintain supernormal profits” and warned of an “earnings bubble” forming in the market. While exceptional profits appear likely to keep being delivered in the immediate future, he said, “the likelihood of sustaining these levels of profitability and growth is incredibly low”.

This earnings bubble supplements an already inflated valuations bubble.

The BIS Annual Report has an excellent graphic that shows that stocks are pricing an earnings bubble, underpricing risk, and household exposure has increased sharply.

The implied long-term earnings growth for the largest corporations sits well above recent historical benchmarks, with US stocks often trading at large premia to peers in other major markets. These implied rates often exceed even the elevated growth that some of the technology firms have delivered in their relatively short lifetimes. As these firms mature and command a larger share of the market, sustaining such high growth could become increasingly challenging… Risk premia on the largest US stocks have compressed markedly since the COVID-19 pandemic, with the distribution shifting clearly to the left. This points to growing investor complacency and reduced compensation for risk-bearing… A major equity market correction could have larger macroeconomic consequences today than in the past. Household equity exposures have grown over the past few decades, both relative to total wealth and income. A large correction in valuations could have more pronounced wealth effects and sharper consumption pullback than in the past. And with US stocks accounting for an outsized share of global equity markets – about 64% of the MSCI Global index – the wealth impact from a US-led repricing could propagate globally.

And, the report says, all this is fuelled by a complex web of private circular transactions involving hyperscalers, chip makers and AI labs.

Chip makers and hyperscalers take equity stakes in AI labs or neocloud providers, who in turn commit to multi-year purchases of chips or computing power. Data centre construction is increasingly outsourced to third parties that lease facilities back to hyperscalers on long-dated contracts with embedded exit clauses. The terms of such deals are typically poorly disclosed, with risks of the same asset being pledged multiple times. Together, such arrangements account for a sizeable share of sector-wide financing and forward revenue. A sharp repricing of equity risk could prompt a reassessment of corporate credit risk and lead to tighter credit conditions more broadly…
Any tightening in credit conditions could expose existing vulnerabilities in the less transparent private credit space, whose reach has expanded among middle market and small firms… A larger shock, whether from a renewed inflation surge or a sharp AI-led repricing, could trigger a more widespread credit crunch… The growing role of private credit also raises concentration risks. Direct lending funds, dominant players in the private credit ecosystem, have quadrupled their lending to the AI and information technology (IT) sectors in the past five years, to about 15% of their portfolios. These loans tend to be larger than those in other sectors, while their terms such as tenor and pricing remain broadly similar, raising questions about lending standards and risk pricing.

In this backdrop, it is useful to ask the question whether financial markets have lost their disciplining powers. What is it about modern financial markets that makes them underprice risk?

For sure, greater access to information has bridged information asymmetries, increased transparency, and reduced uncertainties and risks. And this has, in turn, lowered price discovery frictions and increased market efficiency. However, this has gone alongside trends in the opposite direction. Already, the complexity of financial instruments obscures risks and distorts price discovery. But other market practices have emerged in the last two decades that distort incentives and erode the market discipline. Some of them are consequences of the aggressive expansion of central bank monetary policy toolkits in the aftermath of the Global Financial Crisis.

There is a moral hazard created by the market participants’ internalising the belief that too-big-to-fail institutions or industries will always be bailed out. The institutions themselves come to view this as an insurance against their risk-taking. Well-intentioned actions of central bankers like forward guidance and commitments to backstop against shocks (Greenspan Put and Draghi’s “whatever it takes”) create similar moral hazard across markets. The gradual erosion of gatekeeping standards (ratings inflation, audit failings, index inclusion - e.g., for SpaceX) distorts incentives and leads to underpricing of risks. Excessively bullish market guidance, like with AI stocks now, fuels a cycle of irrational exuberance that amplifies bubbles. Finally, the inherent dynamics of financial markets bake in the fear of missing out among the institutional investors.

The fundamental basis for any efficient market is that information flows facilitate price discovery, and the costs of the actions of market participants are internalised. Based on this, an analytical framework on financial market discipline can be built on three pillars - information quality (participants must get accurate signals); price discovery (prices reflecting the underlying value); and skin in the game (losses must fall on risk takers). All three must hold simultaneously for market discipline.

The three erosions are not independent. Mechanical demand distorts prices; distorted prices reward gatekeepers who validate them; validated prices attract more backstops when they wobble. Each pillar’s erosion masks the erosion of the others. By the time discipline is missed, all three have been hollowed out simultaneously. This is why the current market environment can display record-high valuations (Price Discovery pillar broken), narrow risk premia (Skin in the Game pillar broken), and record-optimistic analyst forecasts (Information Quality pillar broken) - all at the same time, without triggering any traditional warning system. The system that would normally catch such a configuration has been progressively disassembled.

Interestingly, each erosion channel began as a reasonable response to a specific problem. Deposit insurance solved bank runs. Forward guidance solved communication ambiguity. Passive investing solved active-fund underperformance. Rating agencies solved information asymmetry. None of them is wrong in isolation. The problem is what happens when all the individual protections are stacked simultaneously, and all of them are pursued to their extremities. The system loses its balance.

The market’s self-correcting machinery is gradually replaced by a suite of external supports, and the participants who set prices become smaller and smaller relative to the participants who follow rules. At some point, arguably reached, the market is no longer a disciplinary mechanism at all. It is a policy instrument with an ambiguous owner. That is why the current earnings-bubble concern is qualitatively different from previous bubbles in that there is no obvious mechanism left through which the market disciplines its own excess.

So what can be done to restore the disciplining powers of the market?

Quite simply, it should be about restoring accurate price signals, consequences and costs of risk taking, and the trustworthiness of information, and all by going back to first principles.

The restoration of price discovery requires both thickening the market (a high concentration of buyers and sellers) and increasing liquidity (allowing assets to be transacted without significantly impacting the price). The internalisation of the costs of risk-taking demands rolling back moral hazard-inducing backstops and bailouts, or at the least ensuring these interventions are priced appropriately. Finally, restoring the quality and credibility of information requires separating information provision from the transactions side of financial intermediaries, and letting the market guide with information. An agenda is outlined below.

This must be complemented with cross-cutting reforms such as restrictions and greater oversight on revolving-door personnel movements, enhancing the white-collar prosecutorial capabilities of regulators, enhancing the supervision of non-bank financial institutions (NBFI), macroprudential capital surcharges for risk concentration, etc.

The problem, though, is that these are all very difficult reforms even at the best of times, but particularly difficult now. The silver lining is that a big crash can create the conditions for such reforms.

AI for organisational and bureaucratic reforms

noreply@blogger.com (Urbanomics) — Wed, 08 Jul 2026 03:49:00 +0000

The debate rages about the extent of AI’s likely impact on the economy and human lives. So far, there has been an apparent lack of commercial value creation to justify the gigantic and exponentially increasing volume of AI investments.

I blogged here on the distinction between horizontal and vertical use cases of AI, with success on the latter being limited, here cautioning about the likely impact of AI on development and in developing countries, and here on some possible high-impact use cases for AI in lower-income countries.

The most common horizontal use of AI is in personal productivity improvements. Claude, ChatGPT, etc., are already having large effects on personal productivity. But its translation into vertical use products is muted.

On this, John Burn-Murdoch points to the work of Mert Demirer, Leon Musolff and Liyuan Yang to make two important points. The first point is the “disconnect between reported increases in coders’ output and the apparent lack of a corresponding boom in product or value creation,” which creates a very steep funnel between inputs and outputs.

The study by MIT’s Mert Demirer and co-authors tracked software developers’ work before and after they adopted AI tools. Importantly, they measured this at several different levels, from the amount of code written, to the number of discrete files edited, to the number of projects or features worked on, to actual releases of new software. They found an explosive impact at the top of this funnel — coders created or edited almost 300 per cent more files — but that boost was halved to 150 per cent by the time they got to the number of discrete pieces of work submitted for review, and that in turn shrunk fivefold to a roughly 30 per cent uplift in the number of full software releases.

The authors also found little evidence of AI-assisted increases in software development, leading to increased consumption of Apps.

This brings us to the second point made by the authors about AI’s impact - it is likely to be fully realised only when new organisational structures, markets, and business models emerge.

But Demirer and his co-authors feel the more likely explanation is that current organisational structures and marketplaces are not set up to take advantage of real underlying gains. That view is supported by the evidence from past technological revolutions, where the real jumps in productivity and job displacement came from new companies and processes rather than incumbents grafting new technology on to existing workflows. In the case of electricity in the late 19th and early 20th century, productivity gains were modest where factories simply replaced giant steam engines with giant electric motors but left the rest of the machinery and layout unchanged. The boom arrived decades later when engineers fitted individual workstations with their own small motors.

In this backdrop, Jack Dorsey and Roelof Botha have an insightful article on organisational impact. Specifically, they claim that AI’s productivity-enhancing value can address the fundamental coordination problem in large organisations that manifests in the form of a trade-off between span-of-control limitations (which add organisational layers) and speed of information flows. They argue that AI sharply increase people’s span of control, thereby reducing organisational layers and hastening decision-making.

The first organisational models emerged in the military to organise large numbers of soldiers into a coherent and effective fighting unit. It involves a hierarchical chain of command that allows for a span of control and a seamless flow of information and instructions. The model then entered the corporate world through the US railroads in the 1840s and 1850s, which borrowed West Point-trained engineers from the US Army. They trace the evolution of the modern organisational form,

In the mid-1850s, Daniel McCallum of the New York and Erie Railroad created the world’s first organizational chart to manage a system stretching over 500 miles with thousands of workers… McCallum’s chart formalized the same hierarchical logic the Romans had used: layers of authority, defined reporting lines, structured information flow. It became the blueprint for the modern corporation… Frederick Taylor (1856-1915), often called the “Father of Scientific Management,” optimized what happened within that hierarchy. Taylor broke work into specialized tasks, assigned them to trained experts, and managed through measurement rather than intuition. This produced the functional pyramid organization - a structure optimized for efficiency within the information routing system that the military had pioneered and the railroads had commercialized…
In 1959, McKinsey’s Gilbert Clee and Alfred di Scipio published “Creating a World Enterprise” in the Harvard Business Review, providing an intellectual framework for a matrix organization that combined functional specialties with divisional units. Under the leadership of Marvin Bower, McKinsey helped companies like Shell and GE implement these principles, balancing central standards with local agility. This became the “professional” or “modern” corporation that propelled the postwar global economy… The McKinsey 7-S framework, developed in the late 1970s by Tom Peters and Robert Waterman, distinguished the “hard Ss” (Strategy, Structure, Systems) from the “soft Ss” (Shared Values, Skills, Staff, Style). The core idea was that structural elements alone were insufficient. Organizational effectiveness required alignment across cultural traits and the human factors that determine whether a strategy actually succeeds.

They suggest that AI makes it possible to solve the fundamental coordination problem within large organisations that necessitate hierarchical formations.

For the first time, a system can maintain a continuously updated model of an entire business and use it to coordinate work in ways that previously required humans relaying information through layers of management… In a traditional company, a manager’s job is to know what’s happening across their team and relay that context up and down the chain. In a remote-first company where work is already machine-readable, AI can build and maintain that picture continuously. What’s being built, what’s blocked, where resources are allocated, what’s working and what isn’t. That’s the information the hierarchy used to carry. The company world model carries it instead…
In a conventional company, the intelligence is spread throughout the people and the hierarchy routes it. In this model, the intelligence lives in the system. The people are on the edge… The edge is where the intelligence makes contact with reality… the edge doesn’t need layers of management to coordinate it. The world model gives every person at the edge the context they need to act without waiting for information to travel up and down a chain of command… Everything else the old hierarchy did, the system coordinates, and everyone is empowered, with a role that’s much closer to the work and the customer.

They identify three roles - Individual contributors (ICs) who are deep specialists and experts who build and operate system capabilities; Directly Responsible Individuals (DRI) who own specific cross-cutting problems or opportunities and customer outcomes; and player-coaches who replace the traditional manager whose primary job was information routing, who do both building and handling people.

All this makes great sense and points to how corporate organisational models are likely to emerge as the application of AI progresses. There will be frontier firms in a few sectors that will lead the way for others to follow.

AI applications are a promising opportunity to address inefficiencies and coordination failures in public bureaucracies, too, and improve the quality of public administration.

For a start, it has the potential to restore internal capabilities, which have eroded steeply. Over the years, thanks to practices like outsourcing all analytical and documentation work to consulting firms and the hiring of individual consultants (most notably now, the system of Young Professionals, YPs, in governments), there has been a complementary erosion of in-house expertise. The capabilities to articulate proposals for internal deliberations and file circulation have atrophied. Given that bureaucracies run on deliberations and files, this trend is an underappreciated aspect of state capability weakness.

AI provides an opportunity to reverse these trends and develop internal capabilities. The primary reason for the reliance on external expertise is the extent of analytical work and documentation required during the deliberative process (everything from a concept note on the proposal to reports for appraisals, and Cabinet Notes). The bureaucratic leaders who are burdened with a multiplicity of tasks, work under tight timelines, face increased fetters from oversight agencies and courts, and must rely on an increasingly enfeebled internal bureaucracy. In the circumstances, they prefer to outsource the thinking and documentation to outsiders. I have blogged earlier on the perils of this approach.

AI tools like Claude are excellent at analytical work and the generation of these documents in response to clearly articulated prompts. It becomes a simpler proposition if bureaucrats can quickly and easily obtain a draft concept and supporting documents, and then scrutinise, validate, and refine it before circulation for approval. AI tools can then become a force multiplier for bureaucratic leaders, who are now constrained by their limited bandwidth and acute dependencies.

This would also empower bureaucratic leaders, or at least some among them, and could enhance the quality of their engagement with the decision-making process. Besides, by minimising the drudgery of the bureaucratic process, it would also allow bureaucratic leaders to apply their minds and exercise judgment more effectively, thereby improving the quality of decisions and policy design and implementation. It would also lower decision-making delays.

It should therefore become a priority of the National Informatics Centre (NIC) (or an AI division within it) to develop or license AI application that is embedded in the e-office software and enables officials to sift through large documents and generate proposals/presentations, circulation notes and reports using prompts. This has transformative potential for productivity improvements, not only stopping the erosion of internal capabilities but also helping rebuild them.

If this can be done, it opens up opportunities for far-reaching administrative reforms. The current bottom-heavy pyramid can be rationalised to make it fit-for-purpose.

A major inefficiency is the presence of multiple layers within the administrative system. It is a widespread practice across governments to have YPs, and those recruited as data entry operators originate the note file (a task earlier performed by the clerical staff). The note then gets circulated across several layers, often seven or eight till the approver. This can be radically pruned down to no more than three or four, including the approving authority.

Such de-layering is especially relevant for technical ministries and departments whose activities are more amenable to AI-based support. Such ministries should have a separate administrative staffing plan, one that takes into account the role that AI can play in generating documentation and considerably reducing any drudgery associated with analytical work.

As a general illustration, there are perhaps three kinds of activities in any department - shared services (HR, procurement, establishment issues, statutory matters, etc.), administration of departmental programs, and analytical and technical work. There are significant low-hanging likely process-efficiency improvements in all three, and substantive value-addition potential in the third activity.

This would also necessitate a reassessment of public recruitments. The advent of AI applications means that, unlike in earlier times, apart from merely documenting the issues in a note file, the case worker (the ASO or SO) can now be expected to do some analysis and provide comments. This also means that a smaller base can serve the clerical roles (the entire paraphernalia of clerical cadres can be collapsed into just two functional levels - maker and checker), and their educational qualifications and skills must reflect the requirements for the revised scope of work. I’ll blog separately on this.

The increased use of AI applications to analyse and document, and a compact and delayered deliberative process captured in the file circulation can also increase the quality of collective engagement and ownership of the bureaucracy in decision-making. It lets (and nudges or forces) everyone contribute meaningfully to the process instead of being passive pass-throughs of instructions and note files. It presents the opportunity to shed reliance on outsourced expertise and build back state capabilities.

This is deep work and, even in the best case, is likely to be adopted only by a few units in the first phase. The objective should be to create the conditions that encourage the emergence of these lighthouses and channel them to diffuse change more widely.

Some thoughts on the AI trade

noreply@blogger.com (Urbanomics) — Sun, 05 Jul 2026 23:30:00 +0000

The AI trade is clearly blowing into a bubble of utterly spectacular proportions.

FT Alphaville points to the interesting reality that both equity valuations and earnings of the underlying companies are in bubble territory. They quote from the monthly market update by Joachim Klement and Francisca Reis of Panmure Liberum.

In 1929, the cyclically-adjusted P/E-ratio (CAPE) of the S&P 500 reached 32.6x according to Prof. Robert Shiller’s data. This was 1.8 standard deviations above trend at the time. In 2000, the CAPE reached 44.2x, or 3.3 standard deviations above trend – a clear sign of a bubble. However, as our chart below shows, earnings in both instances were within normal range, less than one standard deviation above trend. Today, the CAPE is at 41.0x, or 2.9 standard deviations above trend. Once again, we are clearly in bubble territory for stock market valuations.
However, unlike in previous bubbles, we are having extremely high CAPE at a time when earnings themselves are 1.8 standard deviations above trend. In other words, we are in a valuation bubble at a time when earnings are in a bubble themselves. If we correct for the earnings bubble, the current CAPE would be 67.6x or 4.6 standard deviations above trend, a bubble that surpasses anything ever seen in US history by an extreme margin. If valuations followed a normal distribution (which they don’t, so don’t take this literally), this would happen in 0.00019% of months or once every 43,432 years.

See just the Shiller CAPE ratio.

That being the case, what makes any assessment of the AI trade problematic is its unique nature.

It is the creation of a general-purpose technology that is most certain to transform several aspects of business models, work practices and trends, and life itself (and maybe even more). There are five stakeholders on the supply side of the AI story - semiconductor chips, cloud and data centre infrastructure, LLMs, financing, and support services. They encompass a vast spectrum of businesses - chip designers and makers, equipment makers, cloud infrastructure services, AI LLM developers, data centre developers, utilities, financial institutions, etc. On the demand side are all the different kinds of AI applications users, spanning every imaginable industry.

While the LLMs and the cloud services are software, the rest are all hardware. At the vanguard are the top public limited companies of our times, all with formidable moats and strong balance sheets. Till the recent surge in private credit, the AI investments were being financed from their large cash surpluses. Further, all of them make massive and growing profits, even creating an earnings bubble. Finally, given the network effects generally associated with digital technologies, the AI landscape is more likely to create winner-takes-all markets.

Also, so far, the AI trade has been running on the massive investments pouring into the development of AI LLMs and their applications. This investment binge is being driven by an intensely competitive race to outdo each other in improving the LLM algorithms and building up scale capabilities. The achievements to date on this have been truly spectacular. The applications development, though gathering pace, is lagging. No killer Apps or hardware have emerged on the landscape.

The true reckoning for the AI trade will depend on whether the AI algorithms developed will find commercially valuable use cases. More specifically, whether these use cases, which will emerge in the years ahead, will justify the massive investments already made and being committed.

Even more specifically, if the market smell tests of the AI promise endure, the bubble will continue to inflate. Such persistence of bubble inflation is, to a great extent, the perpetuation of stories. Elon Musk and SpaceX are the totemic illustrations. The two critical metrics of aggregate profits possible from the AI industry are the addressable market and margins. However, both are nearly maxed out in the valuation pricing on the upstream (supply) side. The best that can therefore be expected is that the downstream (demand) AI applications industry starts to create successful products. This would let the AI trade inflate more, at least for the immediate future.

On the contrary, if the market smell test points to the other way, at least in a few vanguard areas like autonomous driving or software development or healthcare and life sciences, then all bets are off and the wheels will start to come off. Another downward pathway is if the upstream supply-side margins start to get squeezed due to competition or disruption or rising costs. Given the asymmetric nature of such turns (bubble inflated gradually upwards, but the pop could be rapid), we could then see a rapid unravelling of the AI trade, with all its disruptive implications. The disruptions could be economy-wide, far deeper and broader than with the dotcom and other bubbles, given the wide sweep of markets that the AI industry has enveloped.

Interestingly, even as the seven largest data centre operators are planning to spend $848 bn this year, five times what they spent in 2022, the stock prices of the applications-side hyperscalers are struggling. Microsoft is down nearly 20% this year, and Meta is down 11%. The AI trade is now running purely on the chipmakers.

The critical place in the market to keep a close eye on may be the downstream side of AI applications and product development.

Weekend reading links

noreply@blogger.com (Urbanomics) — Sat, 04 Jul 2026 07:54:50 +0000

1. Indian universities have come to dominate the global rankings for research paper retractions, following complaints of plagiarism, fake peer reviews, and other misdemeanours. According to the Retraction Watch database, India recorded 887 research paper retractions in 2025, form 21% of all retractions (second to China with 41%) despite contributing just 5% of all publications, and occupying six of the world's top 10 universities for retractions.

2. Stunning statistic about the Algerian demographic dominance of the Les Blues, the French national soccer team.

Only two of France’s 26 players are of non-immigrant ancestry — 22 of them have African roots. Some, such as Mbappé, are deeply connected to their country of origin.

And this dynamic of reverse migration and migrant domination elsewhere.

Of England’s 26 players, eight have Caribbean forebears, 10 African, and 20 who were eligible to represent at least one other country because of their family heritage or birthplace. Belgium has players who trace their lineage to its former colonies — Congo, Burundi and Mali. The Portugal team has those of Cape Verdean, Angolan, and Guinean lineage. Those surplus to their requirements — players of African descent born and raised in Europe — in turn, populate most of the African teams. Ten of the 11 Senegalese players in the starting lineup against France in the opening game were born in France... Six of the players in the US national team are of Afro-Caribbean heritage... There are those from Nigeria, Ghana, and Jamaica. Three are from Hispanic backgrounds — Christian Roldan (Guatemala), Ricardo Pepi (Mexican-American) and Jesús Ferreira (Colombian-American). As many are from Europe, and three others have dual nationalities... For Australia's Socceroos, four players were born in refugee camps. The players represent 15 ethnic backgrounds and include a Malaysian with Sri Lankan roots. Eighteen other players have direct immigrant or refugee heritage. To contextualise, only one Black player (Sam Morris) and another of Caribbean descent (Andrew Symonds) have represented Australia in cricket.

This is a brilliant article by Sandip G about the magnificent quartet in the French team - Kylian Mbappe, Ousmane Dembele, Michael Olise and Desire Doue.

3. The US military learns from Iran.

The US has, similarly, begun to build its production of drones. It used the Lucas, a one-way attack drone reverse-engineered by start-up SpektreWorks from an Iranian Shahed-136, for the first time in combat in February. The Pentagon is looking to begin mass-producing them, and has requested to triple its spending on drones and related technologies to over $74bn next year.

4. Shenzhen, with 400,000 taxi drivers licensed to provide services in 26 platforms, will permit robotaxis from July 1. The new rules will allow the Shenzhen government to promote the “orderly development” of robotaxi tests, demonstrations and commercial pilots either in select zones or citywide.

5. Friedrich Merz's landmark pension reforms

Under proposals agreed by a bipartisan commission, a compulsory initial contribution of 0.5 per cent of employees’ pre-tax income, rising to 2 per cent by 2031, will go into a Swedish-style public pension fund managed centrally and invested in capital markets. Contributions are split 50/50 between employees and employers. The statutory minimum retirement age of 67 is set to rise in line with life expectancy; rights to early retirement for people with 45 years of contributions will be restricted.

Such measures have become vital to reduce the deficits of Germany’s unsustainable pay-as-you-go system. Some 16.5mn baby boomers will retire by 2036 with only 12.5mn new workers joining the workforce, according to some estimates. The government spent about a quarter of the total federal budget on plugging gaps in the system in 2024; economists say that could double to 50 per cent in two decades.

Linking the retirement age to life expectancy is projected to mean only a gradual increase — to 67.5 by 2041 and 70 by 2091. But economists say this is the only sound way to stabilise the system without spiralling payroll taxes or huge federal subsidies. Narrowing early retirement rights will address a drain of experienced workers amid acute skills shortages.

6. Important graphic that highlights the extent of renminbi depreciation since the beginning of 2022 and the surge in surplus.

7. China expands export restrictions on dual-use items against Japanese companies in the latest instance of weaponisation of its manufacturing dominance.

The companies added to the export control list include subsidiaries of Mitsubishi Electric and Mitsubishi Heavy Industries. The restrictions will also apply to several Japanese government research organisations including the National Institute for Defense Studies. Chinese exporters are banned from selling to the entities on the restricted list, and foreign organisations or individuals are also prohibited from selling dual-use items that were built or originated in China. China last expanded the list to 40 companies in February. In parallel with the expanded export control list, China’s commerce ministry on Monday put 20 Japanese companies and organisations on its watchlist, meaning they will get closer scrutiny in any matters relating to potential dual-use technologies. The list includes subsidiaries of Fujitsu, Mitsui E&S, Hitachi, Komatsu and Terra Drone. Beijing’s targeting of Japanese companies is the latest example of China’s weaponisation of trade in recent years. The EU Chamber of Commerce in China in April has found that Beijing has nearly tripled its use of export controls in the past five years. While some instances have been in response to western measures, the researchers noted that Beijing’s controls have also frequently targeted trade chokepoints.

8. GST balance sheet.

Though average GST collections in absolute terms are almost 90 per cent higher than those in the pre-GST period, other parameters tell the real story. The average growth rate in tax collections and the tax-GDP ratio are lower under the GST regime compared to the pre-GST era. Collections were further marred by GST cuts starting September 22, 2025.

9. India's labour market challenge.

With high-skilled IT services under pressure, a financial sector with limited capacity to create low and medium skilled jobs and manufacturing struggling to gain traction, the one area where jobs are being created is low-end services. Delivery riders for Zepto, which has just filed its papers for an IPO, have gone up from 49,278 in 2024 to 2.21 lakh in 2026 — more than a four-fold increase. Zomato and Blinkit have almost doubled to 10 lakh riders in two years. Swiggy now has 6.1 lakh riders, while Uber, at 14 lakh active drivers, outstrips Indian Railways. The gig economy is emerging as an urban employment sink.

10. The Uniqlo-Toray partnership that underpins Fast Retailing's spectacular growth.

In April 2000, Uniqlo founder Yanai paid a visit to the offices of Toray, a Tokyo-based chemicals and materials conglomerate he had read about in a magazine. It marked the start of a strategic collaboration that provided Uniqlo with arguably its most important advantage over rivals: access to high-tech, specialised fabrics. After testing 10,000 prototypes, Toray invented a material combining four types of synthetic yarn that absorbs moisture from the body and converts it to heat. Uniqlo branded it Heattech, and since 2003 has sold 1.5bn garments made from or containing it. Toray also helped develop the fabrics behind AIRism, used as a breathable base layer, and the Ultra Light Down ranges of packable jackets insulated with bird plumage... control over fibre shape and fineness, dubbed nanodesign, has helped to make highly water-repellent and durable $50 lightweight parkas, creating a far cheaper alternative to specialist outdoor brands such as Patagonia. The two sides are entering a fifth phase of collaboration that aims to combine synthetic fabrics with natural ones, such as introducing cashmere into Heattech products to make them softer. Okawa believes few other retailers have such deep relationships with their key suppliers.

11. Good FT long read about the Jamie Dimon succession struggle at JPMorgan. The things that stand out are the following:

One, the appointment of someone to the top position in any organisation, public or private, is bound to be opaque and involve considerable discretion. The only disqualification would be the egregiously ineligible. For any others, there will always be ways to spin it as a fair process. This holds with greater effect as the stakes go up.

Two, in the succession struggle, dominated as they are by a multiplicity of considerations, among those eligible or qualified, it is rare that the most professionally competent will emerge as the successor.

Three strong leaders will always delay succession, and even when they choose to retire, will seek to retain enough levers to influence the decisions of their successors. Most often, it is about decisions involving the promotion of the interests of those in the organisation closest to them, their pet projects or initiatives, broader organisational strategic shifts, etc.

More on the limits to China's growth trajectory

noreply@blogger.com (Urbanomics) — Fri, 03 Jul 2026 02:20:56 +0000

The valuations of the US AI stocks and its public debt binge are not the only bubbles waiting to pop. An equally big bubble that could pop is China’s investment-driven and debt-fuelled growth model. Of the three bubbles, the last could well be the most consequential.

I had blogged here explaining the hard limits to China’s current growth trajectory. This post highlights the unsustainability of the country’s credit-driven growth.

The Economist has a very good read on China’s economic growth strategy, with its latest focus on high-technology sectors.

This puts China’s infrastructure investments in perspective.

The old model of growth took shape on China’s coasts before spreading to the interior. Factories in the wealthy east employed poor migrant labourers from the hinterland. Those migrants in turn, unable to obtain residency in metropolises, often used their earnings to invest in property back home. Towering apartment blocks erected during the two-decade property boom have sprung up in the smallest towns, employing tens of millions of construction workers each year and hoovering up low-end manufactures. High-speed rail has penetrated the poorest counties.

All this investment was fuelled by local-government borrowing. One tally puts these debts at around 60trn yuan ($9trn), or 43% of GDP. The comparable figure in America is 12%. The poorest regions often relied the most on debt-fuelled construction of houses, roads and bridges. This has left some places, such as Guizhou province in the south-west, with dazzling infrastructure (including a bridge 626 metres high, the world’s tallest) along with insurmountable debts. Few of these costly public works have so far come close to generating the revenues needed to pay back creditors.

As the Cold War with the US and the West intensifies, President Xi has set the goal of global leadership in advanced technologies - EV, batteries, semiconductors, AI, robotics, fusion, etc. This has set the stage for a new round of competitive investments by governments across the country, with enabling credit supply measures.

A national semiconductor fund has raised roughly 687bn yuan over the past 12 years. Government-backed fund managers watched their coffers swell to nearly 400bn yuan last year, an increase of 75% from 2024. In December the state launched a 100bn-yuan national venture fund with a mandate to invest in aerospace, semiconductors, brain-linked machines and quantum technology. Many local governments, including in small cities, are creating similar vehicles using tax revenues and capital from local state companies. They are setting up “high-tech zones” and “AI parks” to lure innovative companies with tax breaks and other perks. These new tech businesses are meant to generate tax revenue and help local governments grow out of their debts, says Jean Oi of Stanford University. While officials wait for their homespun DeepSeek, the AI lab that stunned the world last year with its powerful model, the central government relaxes the rules to give them more time to repay their debts.

The massive expansion of investments and intense competition have generated spectacular failures.

In 2021 the city government of Yichun invested 2.3bn yuan to help build an EV factory in a sprawling National High-tech Development Zone. But in contrast to successful EV clusters like those in Shenzhen and Hefei, the facility was isolated from suppliers and expertise required to build cars efficiently. It has since halted production. The rest of the industrial zone looks just as lifeless… A decade ago a fund with local- and central-government money poured around 150bn yuan into Guizhou, a mountainous province in central China, mostly into data storage and cloud-computing. But these ventures could not be integrated with local industry. The companies building the data centres are based on the coasts, the server parts are made elsewhere and local demand for the data capacity is scarce… The north-western industrial city of Lanzhou has invested in commercial space flight and a “drone economy” project even as it struggled to pay its bus drivers for several years (asking them to take out personal bank loans to tide them over)…
Mr Xi’s industrial policy promotes fierce competition in which companies and their host places, sometimes down to city districts, duke it out. This competitive pressure pushes down prices and elevates quality. The best businesses which emerge from this free-for-all, like BYD in carmaking, Huawei in electronics or Xiaomi in both, are formidable and ready to take on the world. They are also rare—and concentrated in established commercial centres, with deeper talent pools and pockets. Profits are even rarer. Investment returns accrue less to individual companies and more to integrated supply chains, which lower costs and speed up product cycles and innovation, says Chi Lo of BNP Paribas, a bank.

The share of industrial firms generating losses has shot to a record high of around 32% in April, up from 10% in 2011 and above the previous peak during the Asian financial crisis in 1998. Corporate debt is also high and rising. Mark Williams of Capital Economics, a consultancy, notes that Chinese firms owe twice as much to domestic banks and bond investors today as they did in 2019. In that period, GDP has expanded by a third. Companies may move away from productive activities and instead chase subsidies that are available for centrally supported sectors, he says… a trio of IMF economists calculated last year, China’s “total factor productivity” (which captures how efficiently both capital and workers are used) was 1.2% lower than it would have been in the absence of industrial policy over the past decade or so. GDP was 2% lower, equivalent to forgoing around $400bn in value added each year. The more companies get caught up in the chase for subsidies and, by slashing their prices, for customers, the harder it will be for them to wring out profits.

China faces a confluence of headwinds - slowing economy; weakening aggregate demand and consumer sentiments (with persistent low domestic consumption); ten quarters of factory deflation (PPI −2.6%) (involution or neijuan); the property market still in crisis and recovery perhaps still a few years away; local governments deeply indebted; large excess capacity across industries; growing backlash among trade partners against surging Chinese exports; intense competition among domestic companies squeeze margins and are leaving companies running losses; and zombie firms kept alive by local and central government subsidies, cheap credit, and debt repayment rescheduling.

Each panel below is a single number with its recent track. Red is contracting or dangerous; amber is stalling; green is the part still running hot, which is exactly where the next overcapacity is building.

In an environment where consumption is weak, any squeeze on investment and reduction of exports (due to rising backlash among trade partners) will only lead to job losses and social discontent. This has increased the reliance on investments to achieve the 4.5-5% GDP growth rates.

And exports are critical to absorb the excess capacity that has been built up.

After infrastructure, real estate, and manufacturing in the first two decades, the current focus of the investment-driven growth model has been advanced technology sectors like EVs, batteries, semiconductors, robotics, AI, etc., where there is also a geopolitical imperative arising from the Cold War with the US. The macroeconomic policy mantra has been to “hold growth at ~5%, protect jobs, and roll the borrowing forward each time.”

All this points to the model of a giant economy-scale Ponzi scheme where investment is shifting from one sector to another in order to sustain a target GDP growth rate and prevent job losses, while also accumulating a growing pile of massive debts.

A debt-funded model works only while each new yuan of credit produces enough output to service it. In China, that link has snapped: credit keeps compounding while nominal growth fades - the classic signature of a system paying old debts with new ones.

The cleanest unsustainability signal isn't the debt level per se but its productivity: total social financing has passed 309% of GDP, and in 2025 credit grew +8.9% while nominal GDP grew just +4.1% — more than twice as much debt as output. When each extra point of growth costs ever more borrowing, new credit is increasingly servicing yesterday's liabilities rather than funding tomorrow's, which is the arithmetic that ends the loop. And this is also reflected in the continuously rising fiscal deficit, especially in the off-balance sheet side.

Worsening matters, these trends coincide with a period in which fiscal revenues have flatlined in nominal terms and declined relative to the economy since 2020.

As the RAND report writes, with the fiscal space disappearing, the government has relied on credit and mandates to keep the wheel spinning.

Beijing can still mobilize large-scale borrowing for industrial policy. The central government and policy banks retain substantial capacity because Beijing can expand bond issuance, and national commercial or policy banks raise trillions of yuan annually in quasi-sovereign debt to finance strategic sectors. By contrast, local governments are squeezed; bond quotas are capped, land sale revenue has fallen, and off–balance sheet LGFV borrowing is under regulatory pressure. The most important immediate trigger was Beijing’s “three red lines” policy introduced in 2020, which sharply curtailed developer borrowing and land sales. Because land sales to developers had long been a major source of revenue for local governments, the resulting property downturn led directly to a collapse in land sale proceeds and fiscal capacity at the local level. A correction was likely inevitable because of the structural exhaustion of a land finance model that relied on perpetually rising property values to fund local growth. Therefore, localities are less able to cofinance subsidies or guidance funds.
Policy is shifting as a result. Centrally directed (or funded) credit and investments remain important. Meanwhile, traditional cash subsidies and local incentives play a reduced role. Government procurement has fallen relative to GDP. Instead, Beijing is leaning on lower-cost directives and mandates (including procurement requirements, regulatory obligations, and selective credit guidance) that require less fiscal outlay but effectively spread the costs of industrial policy across firms and institutions required to comply.

There are hard limits to how far this can go.

Since around 1980, the political bargain between the Communist Party and the Chinese people was simple - rising prosperity in exchange for political acceptance. With consumption weak, any squeeze on investment, or a real loss of export markets to a rising trade backlash, flows straight into jobs. Youth unemployment is already near 18%. The flywheel is kept spinning not only for growth, but to keep that bargain intact. How long can the flywheel keep spinning?

The problems of additionality and technology sector skew in the public funding of startups and innovation

noreply@blogger.com (Urbanomics) — Wed, 01 Jul 2026 01:36:25 +0000

Public risk capital funding of innovation and startups in India is done almost entirely through the VC-driven Fund of Funds (FoF). The RDIF is only the latest effort.

However, as I have blogged earlier, there are two important concerns with public funding of innovation through the FoF approach.

One, would it primarily expand the investable universe of startups (genuine additionality) or primarily subsidise returns on investments that would have happened anyway (returns-amplification for private investors)? Second, would it prioritise scalable digital technology innovations at the cost of manufacturing and industrial innovations?

The evidence on both suggests returns amplification for private investors and the dominance of technology innovators. This should raise concerns about whether scarce public funds are being deployed most effectively. This post points to yet more evidence in this regard.

The Ken has analysed the performance of the Self-Reliant India (SRI) Fund, a Rs 50,000 Cr fund with 20% government contribution (the rest coming from VC and PE) to finance MSMEs, and found both concerns being validated.

The SRI fund model is described here.

SRI Fund is being implemented by NSIC Venture Capital Fund Limited (NVCFL), which is an Alternative Investment Fund (AIF) of Category II registered with SEBI. SRI fund is oriented to provide the funding support through NVCFL to the Daughter Funds for onward provision to MSMEs as growth capital, in the form of equity or quasi- equity, for the following:

Since the start of the fund in 2020, it has backed around 750 companies and catalysed more than Rs 16,000 crore of investment.

Nearly seven out of every 10 companies it has backed are tech-heavy businesses. Only three are in traditional manufacturing… In fact, several of these companies had already been backed by VC firms before the SRI Fund got anywhere near them. Truemeds, for instance, is backed by Accel, Peak XV, and Westbridge, while Chai Point is backed by Eight Roads Ventures and Saama Capital. Understandably, this dims, if not outright flouts, the proposition of the SRI Fund, which was supposed to scope out companies “ignored” by venture capitalists…

“Fund managers get empanelled under SRI with the intention of backing underserved MSMEs,” said Ishaan Ajay, a development-and-sustainable-finance consultant. “But when faced with the choice between a profitable but slow-growing industrial supplier and a software platform capable of scaling rapidly, they tend to gravitate towards the latter. It’s what they understand the best.” Just consider the numbers. Suppose there’s a precision components manufacturer growing 15% annually with, say, 18% Ebitda margins. That may be a great business, but if you invest Rs 10 crore today, you’ll get only 2–3X your money over seven years. Contrast this with a spacetech company, which, if it succeeds, could be worth hundreds of crores.
“Venture funds are built around the second outcome,” said an analyst at a VC firm. This explains why SRI-funded companies tend to be tech-heavy. For every Bellatrix Aerospace in the portfolio, there’s an invisible machine-parts manufacturer outside it that was passed up… startups are generally more innovation- and tech-heavy, whereas MSMEs tend to be traditional, manufacturing-heavy businesses…
The government, for its part, tries its best to redirect funds towards their intended purpose. If it doesn’t agree with a fund’s investment choices, it expresses its objections, according to a VC with knowledge of the matter. But at the end of the day, it’s one LP among many. And when it can’t sway others, it ends up “recusing” itself from investing in that particular portfolio company, added the VC… “There is no prescription that a certain percentage of the fund must necessarily go towards traditional manufacturing or non-tech MSMEs,” a VC said. Which is the one thing that might have prevented all the confusion.

The point about returns amplification for private investors has also been highlighted in a study of IFC’s blended finance deals in the 2000-20 period, which found comparable financial returns to non-blended projects but “no statistically significant excess private mobilisation beyond what IFC’s standard lending would attract.” In other words, blending did not increase the quantum of private investment — it redistributed risk between IFC and private co-investors.

This finding is echoed in a 2023 study of SIDBI’s Fund of Funds for Startups (FFS) 1.0 by the Impact and Policy Research Institute (IMPRI), India’s Startup Engine: A Policy Review of the Fund of Funds Initiative. It finds that most FFS 1.0 capital went to established VC funds that would have raised capital independently. It also found that “crowding-in effect was primarily reputation/signal, not financial additionality”; the government’s involvement functioned more as a validation of fund managers to private investors than as a necessary injection of capital. While FFS 1.0 delivered a 2x mobilisation ratio, it was mostly in already-functioning VC markets.

As I have blogged several times, the startup and innovation sector is going through the same journey that the infrastructure sector has undergone over the last three decades. Multiple policy experiments to catalyse DFIs - IDFC, IIFCL, NIIF, and now NaBFID - have struggled to crowd in private capital into the riskier infrastructure segments like water supply and sewerage, mass transit, solid waste management, street lighting, energy-saving companies, electricity distribution, etc. Instead, these institutions and instruments may have ended up competing and crowding out private capital in the entirely derisked segments of the infrastructure sector.

In this context, it is also useful to ask the question whether the VC model is the right instrument for the funding of non-technology startups and innovations.

Livemint has two long reads that describe the emergence of consumer food brands catering to the niche category of health-conscious people. Sample this

The past few years have seen a spurt in new food brands specializing in regional staples and cooking ingredients. From rural Bengal winter specialty date palm jaggery (nolen gur) to ancient emmer wheat flour (Khapli atta) from Maharashtra, regional staples are finding customers beyond their states of origin. Some brands like Gurugram-based Anveshan and Two Brothers Organic Farms from Pune have crossed a critical mass, with annual sales close to ₹200 crore in 2025-26… Anveshan sources ingredients from key growing regions—like Pollachi in Tamil Nadu known for its high-quality coconuts and aromatic varieties of groundnut from elsewhere in Tamil Nadu and Karnataka—suited to make cold-pressed oils. The ghee, made from the milk of native breeds like the Gir from Gujarat is made using the traditional bilona process where milk is first set to curd and later churned to separate the butter (this has resulted in a new category called ‘cultured ghee’)…
Venture capital funds are betting on these brands: in September last year, Two Brothers raised a $15 million round taking its total fundraise to $25 million (and its post-money valuation to $85 million or ₹781 crore as per data from market intelligence platform Tracxn)… In April this year, KisaanSay, which markets single-origin grocery items like cardamom from Idukki and black raisins from Nashik, raised ₹34 crore ($3.6 million), taking the total funding at the Gurugram-based startup to $5.6 million since it was set up in mid-2022.
In a way, these brands have also helped promote traditional farming practices with more farmers returning to heirloom grain varieties such as the fragrant, short-grain Kala Namak rice grown in eastern Uttar Pradesh and emmer wheat in Maharashtra and Karnataka. These grains have a low glycemic index (a measure of the spike in blood sugar levels from carbohydrate intake) making them suitable for diabetics and often have higher protein and fiber content compared to conventional hybrid varieties… Three distinct factors—growing consumer willingness to pay for clean food driven by a surge in lifestyle diseases, the rise of quick commerce (allowing brands to quickly test consumer response), and influence of social media platforms are reshaping the premium staples market.

All these businesses are distinct from the rapidly scalable technology startups. Take the story of the Two Brothers Organic Farms.

They use organic farming and traditional methods of primary processing to make ghee, jaggery, Khapli flour, and cold-pressed oils. The jaggery is made using native sugarcane with lady finger extract used as a coagulant. “In Khapli, we have created a revolution. We own a seed bank and pay farmers 2.5-times the price of regular wheat. More than 800 farmers grow this wheat for us in 3,000+ acres,” Satyajit said. “It took us ten years to build this brand. At the back-end, our farms are open to everyone (to visit). Consumers trust us and we have a 70% retention rate. But a proliferation of brands (offering traditional, hand-processed staples) also carries the risk of a dilution in quality standards,” he added with a note of caution.

Much the same can be said about most businesses outside of technology - food, textiles, footwear, manufacturing, recycling, etc. Building these businesses requires painstaking efforts for several years, and there are natural limits to their scalability. They are unsuitable for the VC model of funding, as the second Livemint story about the plant-based nutrition startup Oziva shows.

Venture funding, Aarti Gill (co-founder of Oziva) points out, comes with built-in expectations around exits within five to eight years. Unlike venture-backed software companies, consumer health brands compound slowly through trust, habit and repeat behaviour. “If you have investors willing to stay for 10 or 15 years, that changes the equation completely,” she adds. Gill broadly sees three paths for consumer brands: staying profitable and scaling independently over a long period, going public after reaching meaningful scale, or partnering strategically with a larger company. For Oziva, the third route eventually felt like the most practical one. And, that’s where HUL came in… For Oziva, the partnership offered distribution scale, capital and the ability to build beyond a digitally native audience.

Therefore, at a conceptual level and as a framework, it may be a prudent choice for public policy on the funding of startups to distinguish between technology and non-technology sectors. While VCs are appropriate for technology, with their smaller and rapid growth phase, the same may not be appropriate for non-technology startups, which require longer incubation and growth periods. However, in India, most public risk capital funding happens through the VC-driven FoF strategy, which raises concerns of returns amplification and a preference towards technology startups and innovations.

This is also a concern since technology innovations, far from creating jobs, often also tend to destroy jobs, whereas the non-technology innovations, especially in manufacturing, create good jobs. The graphic below captures the problem.

Note: The percentage breakup is probably even more skewed in favour of technology startups.

It also raises the question of effective strategies - instruments and institutions - for funding such non-technology innovations. How are such innovations funded globally? Are there institutional structures in India (state or central governments) that offer promise and can be adopted with tweaks? What are the lessons from the likes of the Maharashtra Aerospace and Defence Fund? What are actionable recommendations on funding of non-technology startups? If it also requires the government to directly fund them, what institutional structures are most practical and realistic? I’ll explore these in another post.

Indian economy's cost competitiveness constraints - a graphical summary

noreply@blogger.com (Urbanomics) — Mon, 29 Jun 2026 01:43:01 +0000

I had blogged here, arguing that the Indian economy faces a cost-competitiveness constraint. I had written that on many inputs, domestic firms face the cost structure of a developed country. This post will examine the empirical evidence in this regard.

This cost structure reflects in the global competitiveness of the country’s manufacturers. India suffers from a persistent and high price disability compared to peers across manufacturing sectors.

What are the contributors to this competitiveness wedge?

Indian factory wages (~$2.1/hour) are the lowest in Asia, about two-thirds of Vietnam's and a third of China's. Its effective corporate tax rate at 17.2% is among the lowest, its GST rates are comparable, and its logistics costs (while contested) are at least not much higher.

So if India loses on net cost, the disability is entirely in non-wage factors: land, capital, power, fuel, scale, tariffs on inputs, and labour productivity.

Start with land, the largest cost wedge. Urban land is priced like that of a rich country, and, most problematically, hoards the nation's savings. Mumbai ranks among the world's 20 most expensive prime markets, and Indians park ~77% of household wealth in real estate. The high land valuations result in capital misallocation and squeeze out the capital that would otherwise have resulted in investment.

In fact, high land valuations, even in the smaller cities, appear to be a big entry barrier for businesses. An Indian manufacturer pays roughly 5–15 times more for industrial land than a Chinese counterpart in a comparable tier-2 city, and 1–4 times a Vietnamese peer. That gap is policy-made. China's local governments subsidise industrial land to attract production, whereas India's restrict supply (FSI, fragmented titles, slow acquisition) and treat land as a fiscal asset to maximise revenues.

Now, come to power tariffs. Indian industrial users pay ~₹7.5–9/kWh ($0.09–0.11), materially above what comparable Asian peers' large industrial users effectively pay. Indian electricity is among the world's most expensive on a PPP basis, with one of the world's widest spreads across consumer types.

The comparisons of electricity prices based on averages are misleading. For example, India and China have similar average electricity tariffs at $0.08/kWh. It conceals that India has one of the world's widest cross-subsidy spreads (farms near zero, industry penalised). The rate that matters for competitiveness is the industrial slab, which is materially higher. Industry overpays to cross-subsidise farms and households, again, another policy choice. To this, we must add another 15–25% for diesel backup against unreliable supply.

The same applies to gasoline prices. Kept outside GST as a revenue mainstay for state governments, petrol and diesel carry stacked central excise plus state VAT. Roughly half the pump price is tax. In raw dollars, India's fuel is dearer than China's, Vietnam's or America's, despite far lower incomes.

The cost of capital adds to the wedge. The credit-to-GDP ratio measures the availability of capital. The other half of the problem is the price. Indian firms pay materially more than peers - across banks, bonds and the SME segment. In fact, after stripping out inflation, the gap stays large, which is the more realistic measure of whether real investment can clear its hurdle rate.

The capital markets are no different. An Indian mid-cap pays roughly 2–3 times the bond yield a Chinese mid-cap pays and ~50% more than a US one, in nominal terms. After inflation, the gap narrows but doesn't vanish. India's real lending rate (~5%) is ~2 percentage points above China's, and the real MSME rate is among the world's highest. Combined with credit availability stuck at 55% of GDP, this means Indian firms, and especially the missing middle, face the worst combination of dear and scarce capital among large economies.

Let’s dig a bit deeper into the capital cost wedge.

Econ 101 informed that the high cost of capital is a reflection of the demand-supply mismatch. On the demand side, as we have seen, the high land valuations are encouraging resource misallocation. What about the supply side?

The country’s reasonable gross domestic savings rate (~30%) conceals a disproportionately high share of illiquid assets. When 77% of wealth sits in physical assets (land and gold), and only ₹40 for every ₹100 of household financial savings reaches the financial system, the banks have less to lend, the bond market stays thin, and the price of credit rises.

In other words, there’s a link between the land and capital problems facing the economy. The causal chain goes something like this - physical-asset preference (land + gold) → low household financial savings (5.3% of GDP) → shallow bank deposits & bond market → low credit-to-GDP (55%) → dear capital (~9% vs ~3.5% in China). The same wealth-allocation pattern that raises land prices also raises the cost of capital. It is one mechanism, not two.

Worsening matters, the net household financial savings fell from ~11.5% of GDP in FY21 to 5.3% in FY24, a 50-year low. The table below breaks down how the cost wedge feeds itself. Households are borrowing more (against assets), and routing more new savings back into physical assets.

The cost constraints impact the economy in two ways. One, it restrains private investment. Second, it weakens global competitiveness and hurts exports.

Take the first. Overall investment slid from a 35.8% peak in 2007-08. Public capex has since surged, but private corporate investment never recovered, flat near 11-12% of GDP. Flush with cash, firms deleveraged and bought financial assets instead of building capacity. I blogged here on this.

The East Asian economies found exports to rich countries as the outlet to overcome thin domestic demand and drive economic growth. Unfortunately, in India’s case, this is exactly the outlet that the cost wedge closes: dear capital, costly logistics, unreliable power and the world's highest tariff walls all erode competitiveness. The result is that India is losing its share of labour-intensive exports to Vietnam and Bangladesh , even as its overall merchandise share stalls near 1.8%.

In fact, the Economic Survey 2016-17 chapter Clothes & Shoes: Can India Reclaim Low-Skill Manufacturing? warned that the space China vacated was being taken by Bangladesh and Vietnam in apparel, and Vietnam and Indonesia in leather and footwear. A decade later, the warning could not have been more prophetic.

In the net, India wins on wages (~$2.1/hour) but loses on net cost. So the disability is entirely from non-wage factors: capital, power, logistics, scale, tariffs on inputs, and productivity. India has a cost structure that is comparable to that of a developed country. That's the central analytical point.

India enters every labour-intensive sector with the world's cheapest workers and exits with a 10–20% cost disability. This is proof that wages aren't the binding constraint. The wedge comes from the rest - scale, input tariffs, capital, power, logistics and productivity, in a market structure that punishes the firms that should be growing. This is why India hasn't replaced China, where Vietnam and Bangladesh have, despite the structural opportunity being identical for all three.

Indian businesses (and especially manufacturers) face a structural cost constraint. It does not have to do with taxation or wages, but with factors like land, power, fuel, cost of capital, input tariffs, labour productivity, and business size/scale. A disproportionate attention and effort go into taxation reforms instead of these more important structural limiting factors.

Weekend reading links

noreply@blogger.com (Urbanomics) — Sat, 27 Jun 2026 02:52:58 +0000

1. New research by Emma Harrington, Natalia Emanuel, and Amanda Pallais shows that remote work is adversely impacting mental health. They paraphrase Robert Putnam to argue that Americans "typing alone" brings serious social consequences.

In 2024, nearly 80 percent of workers said they would be happiest if they could work remotely... Surveys of over half a million Americans from the last decade and a half revealed an uncomfortable truth: Despite its advantages, remote work has significantly deepened Americans’ isolation and distress. Our estimates indicate that remote work explains a third of the deterioration in mental health between 2011 and 2024... Our study compares workers in jobs that could be done remotely, such as finance and software engineering, with workers in jobs that must be done in person. People in remote-capable jobs worked from home three times as often in 2024 as in 2019. As they did, their days became far more solitary. Eighty-four percent of remote workers spend their workday entirely alone. Over half report feeling less connected to their colleagues. Even when communicating online, people working from home receive less feedback from their co-workers and contact fewer people outside their immediate teams.

These workers did not compensate by socializing more outside work. More days passed with no social contact of any kind... In one study, when commuters were instructed to connect with a stranger near them, they reported being happier than those who continued in silence as usual, much to their own surprise. With fewer social encounters, workers in jobs that can be remote saw steeper increases in distress, mental health visits and prescriptions for antidepressants than other workers did... The pain was not evenly shared. People who lived with their spouse and kids saw their mental health hold fairly steady, while those who lived alone experienced a 20 percent decrease in mental well-being. Overall, we found that the rise of remote work increased distress by 7 percent, which accounts for a third of the total increase over the 13-year period we measured.

They argue that face-to-face time with colleagues has no substitute.

2. Katie Martin points to the different ways in which bonds and equities are reacting to Trump policies.

US government bonds, or Treasuries, have never recovered from the drop in price they suffered around the start of the war. Investors in this market, who broadly consider themselves a more cerebral bunch than those in stocks, never bought the hints of a ceasefire with Iran. Bond prices have still not returned to square one, leaving borrowing costs markedly higher. With the prospect of interest rate rises ahead to douse inflation pressures exacerbated by the Iran war, and relentless more borrowing, this is likely to remain the case for some time.

3. As AI threatens to bring down India's tech sector, this is a good article.

On the whole, Indian IT companies spent around 3.7 per cent of their total revenue on R&D in the year that the report covered. This is minuscule compared to around 15 to 25 per cent that Silicon Valley companies spend on R&D. The top IT companies are laggards of first order. For example, in 2022-23, Infosys spent just 0.9 per cent of its total revenue on R&D. The figure for TCS was 1.30 per cent. For Wipro it was 0.5 per cent while for HCL it was 1.60 per cent. The other big companies don’t fare all too well. Reliance, a giant in every way, spent only 0.53 per cent of its total turnover on R&D in 2022-23. Tata Steel is at 0.67 per cent. Maruti Suzuki spent 0.65 per cent on R&D.

4. Indian markets have more to fall before they become competitive.

The FPI outflows have tracked the decline of rupee, feeding a self-fulfilling cycle.

5. The costs of RBI's FCNR (B) deposits and foreign currency borrowing schemes.

If the scheme were to attract $50 billion of FCNR (B) deposits and $20 billion of foreign borrowing by banks and public-sector enterprises, the mark-to-market loss on the RBI’s swap position could approach ₹64,000 crore at current market prices, besides increasing the RBI’s balance-sheet risk. This is not merely an accounting cost. The subsidy is real and will be monetised by participating non-resident Indians (NRIs), banks and borrowers.

Large Indian banks are raising five-year FCNR (B) deposits in dollars at 6 per cent. Their attractiveness is evident from the willingness of overseas banks to lend against the same deposits at around 5 per cent. This, in turn, will allow wealthy NRIs to achieve double-digit leveraged dollar returns against India cross-border risk. Indian banks can further transform the FCNR (B) deposits into clean five-year rupee funding at around 6.4 per cent, below comparable government bond yields.

Will the RBI regret having offered the FCNR (B) deposits to NRIs?

Banks are being permitted to offer leverage to NRIs. The currency risk on such deposits will be borne by the RBI. As reported by this newspaper, State Bank of India is offering leverage of up to nine times on deposits of more than $1 million. Calculations indicate that this could translate into returns of over 14 per cent. Other banks are likely to come up with similar schemes for NRIs.

Banks are competing aggressively for FCNR (B), and are also offering leverage to increase returns.

6. A new large-scale survey experiment of EU companies shows that firms substantially underestimate competitors' current AI investment, and when updated about their competitors' future AI investment plans they increase their own AI investment plans in a statistically significant manner. But this effect, while strong for domestic peers, is weak for information on foreign peers.

We documented large underestimation of competitor AI investment, substantial belief updating in response to information, and a clear asymmetry in how firms react to domestic versus foreign competition... A 1 pp increase in the expected share of domestic peers investing in AI raises a firm's own expected AI investment rate by 0.570 pp. These complementarities are absent across borders: the effect of an increase in the expected share of foreign peers investing in AI on a firm's own expected AI investment rate is statistically insignificant... Firms update both domestic and foreign beliefs when informed, but their own expected AI investment rate responds primarily to domestic posterior beliefs. These findings suggest that strategic complementarities in innovation weaken with distance, broadly understood to include not only geography but also informational, cultural, and market frictions... This asymmetry helps explain why AI diffusion may remain geographically uneven, even within an integrated economic area like Europe. While firms may observe and learn from foreign competitors, their behavioral response to such foreign signals is much weaker compared to domestic competitors.

7. Aswath Damodaran makes a great point about hedge funds, private equity, and private credit - all niche businesses which had a role, but have vastly overextended themselves and set themselves up for failure.

Each one began as a genuinely good niche business solving a real problem. Hedge funds 30 years ago produced positive alpha, beating passive investing by 3 to 5 percent annually. Today they look like expensive mutual funds, underperforming passive by roughly 1.5 percent. Private equity started as a focused, disciplined strategy for a small set of operators and has grown into a sprawling category that now struggles to deliver the returns that justified its emergence. Private credit had a legitimate original purpose, which was lending to borrowers that banks structurally could not serve. What killed each of these businesses was the same disease. Overreach. A $200 billion niche business gets sold as a $20 trillion opportunity. When that scaling happens, sloppiness follows, bad actors enter the space, and the average quality of every participant deteriorates. The original alpha disappears not because the strategy stopped working, but because too much money chased too few good deals. The danger with private credit is far more severe than the parallel problems in private equity and hedge funds. Equity investors take their losses and move on. Lending businesses, when they overreach, take others down with them. Banks. Pensions. Insurance companies. Sovereign wealth funds. The systemic linkages run far deeper than most participants understand, and the social costs of a real default cycle in private credit would extend well beyond the funds themselves.

8. Friedrich Merz initiates measures to address Germany's rising pension burden, which took up 41% of all federal government welfare spending in 2024. The proposals came from a bipartisan committee of MPs who were appointed to examine and make suggestions.

Germany’s pay-as-you-go system is facing widening deficits, with 16.5mn baby boomers retiring by 2036 and only 12.5mn new workers joining the workforce, according to the Cologne Institute for Economic Research. The government in 2024 paid €118bn to plug holes in the system, or about a quarter of the total federal budget. That share could double to 50 per cent within the next two decades, according to economists... Under the proposal, a compulsory individual contribution of 2 per cent of salaries would “be managed centrally and invested in capital markets”... The move would be a novelty for risk-averse and cash-loving Germans, who have been more reluctant than European peers to embrace capital markets to invest their large savings... Other recommendations include linking the statutory retirement age — currently 67 — to the country’s life expectancy and withdrawing early-retirement incentives. For every year gained, people should work eight months longer, the commission proposed. The experts also suggested raising the age — currently 64 — at which people who have made contributions for 45 years are able to go into retirement with their full pensions. Unions are likely to oppose the measure.

9. India has been a laggard in attracting FDI.

10. Ten years on, Brexit has turned to 'Bregret'!

The Brexiteers persuaded a small majority — the vote was 52 percent to 48 percent — that Britain could throw out the austerity that had followed the 2008 global financial crash, reverse the hollowing out of well-paid manufacturing jobs and trade freely and profitably on international markets. Immigrants who had flocked to Britain from Eastern and Central Europe would be sent home. Europe merely held Britain back, and to choose to leave was to believe, as Britons had before, that the nation was meant for more...

It was, of course, a fantasy... The economy has stalled and trade has shrunk. Britain is poorer than it might have been. Its gross domestic product is at least 4 percent — but could be as much as 8 percent — lower, according to independent calculations, while business investment is more than 10 percent lower. It added new frictions to the lives of Britons: new border checks when traveling to E.U. countries, stricter residency rules for living there, fewer opportunities for students to study abroad. Even just using a cellphone while “roaming” often costs more than it used to. There have been other costs, one of them a weakening of the glue between the nations of the United Kingdom itself. The referendum result was more a statement of English than of British nationalism — majorities in Scotland and Northern Ireland voted to remain. Forced to leave, Scottish nationalists claimed stronger cause to promote their case for full independence from England, and the complex political arrangements for Northern Ireland needed to protect the Good Friday peace agreement between Irish nationalists and British unionists in the province have weakened the cause of the unionists.

Rather than a newly independent Britain cutting a swath on the international stage, economic realities forced cuts in spending on foreign aid and diplomacy. The hopes among Brexiteers for a new Anglosphere, adding the English-speaking Commonwealth nations of Canada, Australia and New Zealand to Britain’s “special relationship” with the United States, turned to dust, and Britain’s privileged place in Washington was lost to Mr. Trump’s disdain for traditional alliances.

11. Fascinating graphic that maps the values of AI models.

The models’ answers, in English, on topics ranging from political petitions to God, suggest values that are different from those of most people. In fact, the models are often more extreme than the average respondent in every country included in the polling. On the survey’s “cultural map”, " AI models fall overwhelmingly into the quadrant populated by rich countries. The worldview of GPT models, created by OpenAI, is more secular than any country on earth (see chart 1). Gemini models, made by Google, place more weight on individual freedom (for example, “homosexuality is justifiable”) than people do anywhere. No model reflects the worldviews of most African or Muslim countries.

12. The Economist looks at the issue of popular backlash against AI. This scenario in particular is important.

Scenarios in which some countries give in to popular rage but others forge ahead are also worrying. If America succumbs, it could cede the global ai frontier, and the attendant cyber and military capabilities, to authoritarian China. Europe and Canada are more risk-averse than America. If they choked off ai while the rest of the world kept pushing forward, their losses could be unrecoverable. More than two centuries after the Industrial Revolution, few countries have managed to catch up with the first movers.

13. Rolex SA is a profit-making company with $12-13 bn in revenues and $3-4 bn in profits whose ultimate owner is a spiritual holding company (SHC), a charitable trust called the Hans Wildorf Foundation. Rolex SA has no public shareholders, investors, or owning family, and has been so since 1960. A similar example is Robert Bosch GmbH, the German engineering giant, which has 94% ownership by the Robert Bosch Foundation (SHC) holds 94 per cent and the Bosch family the rest. In both cases, the management and ownership have been clearly separated.