Economic Risks in Global Markets

For the last part of my Energy Resilience series, we have to talk about the worst-case scenario – when the lights actually go out. Earlier this year we saw that happen in Spain and Portugal. A major blackout left millions without power. Trains stopped, shops couldn’t take card payments, hospitals and factories switched to backup. A wake-up call that modern life depends on electricity in ways we often forget until it is gone.   This is what happens when grids are pushed to the edge by fast-moving disturbances or extreme conditions. A couple of years ago, South Australia experienced a state-wide blackout after severe weather took out multiple transmission lines. Investigations showed the system lacked enough inertia to stay stable through the shock. Part of the solution was to install synchronous condensers – giant flywheels that give the grid “weight” and stability. Siemens Energy delivered two of them as part of the response. Not the only measure of course – adapting regulation is also essential – but it showed something important: without resilience in the system, recovery is slow and uncertain. So what do we actually need if we want a fast ramp-up after a major incident? From my perspective, it comes down to three things. 1️⃣ Standardize before the crisis: When parts fail, every minute spent interpreting drawings or debating specifications is a minute the lights stay out. Standard equipment and uniform processes mean teams can move quickly because they are working with tools they already know. Recovery begins long before the fault happens. 2️⃣ Design power plants with failure in mind: A fast restart depends on assets built to recover quickly, not just run efficiently. That means black-start capability, smart redundancy where it matters and systems that can restart without waiting for the wider grid. In the U.S. for example we supported a power plant with a battery system that enables multiple restart attempts within one hour – resilience designed into the plant itself. 3️⃣ No improvisation in the dark: A blackout is the worst moment to negotiate who does what. Good restoration plans spell out which assets come back first, how to stabilize small sections of the grid and when to reconnect them safely. Regular drills with operators, authorities and major customers turn these plans into routine rather than theory. These steps matter because in any major incident skilled people are often the scarcest resource – grid operators, field crews and technical specialists. That is why preparation matters so much. Clear roles, common standards and trusted partnerships mean limited teams can do more in less time. Because when the worst happens what people remember is how long it stayed dark. I hope you have found this mini-series useful. I know social media is often about speed and short takes but sometimes – especially on important topics like this – I find it worthwhile digging into the detail together.✍️ I’d be interested to hear if you agree.

Tariffs and insurance I’ve heard a few people say and have seen posts about how insurance pricing is free from impacts of the new tariffs. Whilst that may be true in an immediate sense, it’s extremely likely second order effects impact insurance costs. Insurance is never on an island. It is always part of the broader economic picture. New tariffs mean any item may have higher replacement cost, manufacturing cost, market value and/or repair cost. These metrics all directly impact premiums. For example: with new tariffs leading to increased cost of vehicles and vehicle repairs - auto insurance rates would be expected to go up. Oversimplifying a bit, but when it costs carriers more to repair vehicles, their loss ratios shift higher, and higher premiums result. Carriers also incorporate geopolitical risk scores and supply chain exposure metrics into their underwriting models. This is especially true for industries that rely heavily on international trade. So - will we see insurance rates go up overnight? Probably not. Net rates may not be impacted significantly at all for many industries. However, when the rating basis [eg replacement cost] goes up, premiums are directly correlated. If you’re concerned about rising premiums and can carry more balance sheet risk, it may be a good time to weigh the benefit of options like higher deductibles to offset some of the premium bump.

🔥 A ₹350 Restaurant Bill. The Farmer Who Grew Your Meal Gets ₹7. Read that again. I sat down for lunch at a Restaurant today. And as an Agriculture Officer, I couldn’t stop doing the math. Here’s where your ₹350 actually goes: → Real Estate & Ambience: 30% → Staff & Service: 25% → Middlemen & Transport: 20% → Restaurant Profit: 20% → Raw Material (Farmer): 5% (₹18) But here’s the painful truth: That ₹18 is NOT the farmer’s profit. After seeds, fertilizer, labour and irrigation, the farmer’s actual take-home is: 👉 ₹7–₹12. That’s 2% of your bill. And here’s the part most people don’t know: There is NO Minimum Support Price (MSP) for vegetables. If paddy or wheat prices drop, the government procures. But if tomatoes crash to ₹2/kg (which happens every year), the farmer absorbs 100% of the loss. The risk is fully on the creator. The margins are with everyone else. --- The brutal comparison: A food delivery rider earns ₹40–50 per order. A waiter in my city earns ₹400–600/day. A farmer earns ₹200–350/day after input costs. We talk about “doubling farmer income.” But if 95% of the value chain is extracted before the money reaches the farmgate, no scheme can fix this. --- So next time you see headlines like: “Farm-to-fork startup raises $10M” “AgriTech platform eliminates middlemen” Ask one simple question: “What % of the consumer’s payment reaches the farmer within 48 hours?” If they can’t answer with data, they’re not fixing the problem — they’re just taking a new cut from the same old 95%. --- The person refilling your water glass has more income security than the person who grew your food. This is the math. This is the reality. And this is why so many farmers left agriculture in India last year. --- What’s YOUR solution to fixing this value chain? 👇 #Agriculture #FarmEconomics #PolicyFailure #ValueChain #IndianFarming #MSP #LinkedInAgriculture

Today's Sebi paper reveals the ugly face of the F&O market. As options near expiry, retail traders come out to play. Volume shoots up in the last 30 mins. The big bet is on options decaying to zero as they expire. Every day, a new weekly option expires and hence a new frenzy in the Satta bazaar. A daily dose of adrenalin. A lottery ticket. Except you lose and the system wins. And so we've built the world's largest F&O market whose notional turnover is 368 times the cash market, from 19.8 times in FY 18. In FY 24, 92.5 lakh people traded F&O. Of these 78.28 lakh made losses. Spent another 23% of their loss amount as costs. Rs 51,689 crore was cumulatively lost in FY 24. Who profited consistently? High frequency algo prop traders and FPIs. This is like a massive wealth drain on the people of India. Brokers and foreigners profit and the people lose money. Govt also makes money in taxes. Let's not forget the finfluencers belting out Youtube videos and so called classes (which Sebi has refused to touch in the name of financial education). Sebi wants to increase contract size, have weekly contracts on just 1 benchmark index and make various other tweaks on margins to reduce speculation. Great. But please also regulate the finfluencers and the false dreams they sell. Without that, the rest will lack impact and the daily gambling will go on. Read Jash Kriplani, CFP® and Aprajita Sharma, CFP®'s story on F&O from last year https://lnkd.in/gGkVcRfE

China developed its economy by defying free trade — not embracing it. Plenty of developing countries have liberalised their economies but have remained in subordinate positions. Why did China succeed where other developing countries failed? China succeeded via gradual and controlled liberalisation. It actively used state intervention to defy, rather than conform to, the deeply asymmetric structures of the capitalist world economy. Although China opened up to trade and private capital, it maintained tight controls over the flow of capital in and out of the country. China’s joint venture requirements forced foreign firms to partner with Chinese state-owned or domestic firms as a condition of market access. And China’s strong state ownership in the economy meant that the state could retain control over important industries and resources, as well as direct investment to strategic sectors at below-market rates. None of these strategies — capital controls, mandated technology transfer, state ownership of strategic sectors — are consistent with neoliberal doctrine. They are, in fact, direct violations of it. And they are precisely why China’s integration into the world economy produced industrial upgrading rather than permanent subordination. https://lnkd.in/ebC8gjNv

Tug of war - Deregulation Vs Regulation: If done correctly, financial deregulation can spur entrepreneurship, boost economic growth, & increase wages. But if mishandled, it risks destabilizing the financial system & triggering a crisis on a scale that could dwarf 2008. To understand the challenge, imagine a tug of war over a bank’s risk-taking. On one side, some executives & board members pull for high-risk, high-return strategies, enticed by large payouts if investments succeed. On the other side, investors with significant exposure to losses pull for prudence. But what happens when those advocating for caution let go of the rope? The result is excessive risk-taking, with dire consequences for financial stability. But why would influential investors with significant exposures stop advocating for caution? The reason stems from a concept economists call “moral hazard.” When decision makers share the upside of risky bets but are shielded from the downside, they have little incentive to act prudently. In a healthy financial system, investors who stand to lose from a bank’s failures constrain excessive risk-taking. However, when these investors believe government bailouts will rescue them when things go wrong, they stop pulling for caution and join the side advocating for more risk. The current regulatory approach attempts to counteract the powerful risk-taking incentives unleashed by government bailouts by constructing a vast regulatory and supervisory apparatus. But this comes with enormous costs. The apparatus burdens financial institutions with significant compliance costs that are ultimately passed to the public, & it impedes the efficient allocation of credit, slowing economic growth. While deregulation seeks to alleviate these adverse effects, it must be approached cautiously. Rolling back regulatory constraints on risk-taking without addressing the root cause of moral hazard - bailout expectations would only exacerbate the problem. It would loosen the grip of regulators pulling for prudence without replacing it with the steady hands of private investors duly incentivized by having their wealth on the line. What’s needed is a credible strategy to ensure that decision makers within financial institutions have genuine “skin in the game.” This means reforming policies that shield influential investors & executives from the consequences of their actions, restoring the natural tension that constrains excessive risk-taking. Credibility is key. Regulators & policymakers can’t simply promise not to bail out uninsured investors. It has to reflect in their actions. Without credibility, the tug of war over risk will remain dangerously imbalanced. Research consistently shows that well executed deregulation can boost entrepreneurship, drive job creation, & improve living standards esp. for the middle class. But sequencing matters, if deregulation is rushed without addressing moral hazard, the consequences could be catastrophic.

WEF's Global Risks Report 2026 is out 👉 (https://lnkd.in/eaMrdW67).. I put the findings in a 20-year perspective. I mapped 20 years of risk rankings. Two patterns stand out. Both troubling. The headline findings in this report: 🔵 geoeconomic confrontation is now the #1 risk in the short term, 🔵 economic risks are spiking, 🔵 50% of experts expect a turbulent or stormy outlook over the next two years. But the deeper signal only appears when you track the rankings over time (what I did, see 👇 ). ⚫ 𝐏𝐚𝐭𝐭𝐞𝐫𝐧 𝟏 – 𝐋𝐨𝐧𝐠-𝐭𝐞𝐫𝐦 𝐫𝐢𝐬𝐤𝐬 𝐦𝐢𝐠𝐫𝐚𝐭𝐞 𝐢𝐧𝐭𝐨 𝐭𝐡𝐞 𝐬𝐡𝐨𝐫𝐭 𝐭𝐞𝐫𝐦 Not overnight. Not mechanically. But persistently. In 2007–2010, short-term risks were concrete and immediate: asset bubbles, oil shocks, chronic diseases. Fast forward to today. The long-term top risks for 2026 are: 🌪️ extreme weather 🌍 biodiversity loss 🧠 misinformation 🤖 adverse AI outcomes What changed is not that economic risks disappeared. It’s that structural risks began to act as crisis amplifiers. Extreme weather didn’t replace financial shocks, it reshaped them. Climate risks first entered the short-term top 5 around 2014. By 2020, climate action failure topped the list. “Tomorrow’s risks” became today’s stress multipliers, and increasingly, direct crisis drivers. The future didn’t wait. ⚫𝐏𝐚𝐭𝐭𝐞𝐫𝐧 𝟐: 𝐍𝐚𝐭𝐮𝐫𝐞 𝐢𝐬 𝐛𝐞𝐢𝐧𝐠 𝐟𝐨𝐫𝐠𝐨𝐭𝐭𝐞𝐧, 𝐚𝐠𝐚𝐢𝐧 This year, environmental risks dropped sharply in the short-term rankings. More worrying: their severity scores also declined in absolute terms. Yet over the 10-year horizon, environmental risks dominate the top 10. Twenty years of WEF risk data tell the same story: we consistently recognise long-term environmental threats, then consistently deprioritise them when short-term pressures mount. It's not that we don't know. It's that our attention economy is structurally biased toward the urgent over the important. The most interconnected risk for the second year running? Inequality (👇). It fuels everything else: polarisation, migration, political instability, resistance to climate policy. Perhaps that's where to start: 𝐢𝐟 𝐰𝐞 𝐰𝐚𝐧𝐭 𝐭𝐨 𝐚𝐝𝐝𝐫𝐞𝐬𝐬 𝐥𝐨𝐧𝐠-𝐭𝐞𝐫𝐦 𝐜𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐞𝐬, 𝐰𝐞 𝐧𝐞𝐞𝐝 𝐭𝐨 𝐫𝐞𝐝𝐮𝐜𝐞 𝐭𝐡𝐞 𝐬𝐡𝐨𝐫𝐭-𝐭𝐞𝐫𝐦 𝐝𝐞𝐬𝐩𝐞𝐫𝐚𝐭𝐢𝐨𝐧 𝐭𝐡𝐚𝐭 𝐤𝐞𝐞𝐩𝐬 𝐮𝐬 𝐭𝐫𝐚𝐩𝐩𝐞𝐝 𝐢𝐧 𝐜𝐫𝐢𝐬𝐢𝐬 𝐦𝐨𝐝𝐞. #GlobalRisks #WEF #ClimateChange #Sustainability #SystemChange

A 1°C rise in temperature is a poverty multiplier. New global evidence based on subnational data from 130 countries shows that each additional degree of warming: ✖️ Increases poverty by 0.63–1.18 percentage points ✖️ Raises inequality by 1.3–1.9% (Gini index) ✖️ Pushes 62–99 million more people into poverty by 2030 compared to a world without climate change The impacts are not evenly distributed. They are strongest in poorer countries, especially where agriculture dominates livelihoods, and are particularly acute across Sub-Saharan Africa. When we look only at national averages, much of the damage disappears. But subnational analysis reveals the real story: large, localized climate shocks interacting with poverty, inequality, and vulnerability. This matters for policy, finance, and development planning. If we underestimate climate risk by relying on national-level data, we: 1️⃣ Misprice climate risk 2️⃣ Misallocate adaptation finance 3️⃣ Miss the communities most exposed Climate change is no longer just about emissions trajectories. It is about distributional impacts, justice, and who pays the price first. This is why granular climate intelligence must sit at the heart of poverty reduction, adaptation, and development strategies. Because climate risk is not abstract. It is local, unequaland already reshaping development outcomes. read the article in Nature here 👇 https://lnkd.in/ehtBmjip

"Our current #market-led approach to mitigating #climate and #nature risks is not delivering. There is an increasing risk of severe #societal disruption (Planetary Insolvency), as our #economic system drives further global warming and nature #degradation." Not, in fact, another alarmist catchcry from climate extremists, rather a statement from that most analytical and methodical of professions, #actuaries. A profession whose work underpins the functioning of the global pension market with $55 trillion of assets, and the global insurance market, collecting $8 trillion of premiums annually. When actuaries warn of a >$50% loss in global #GDP, it's (well past) time to sit up and listen. What's notable in this latest report (no doubt timed to coincide with the World Economic Forum's latest #GlobalRisk review) is that it reiterates a message from the Institute and Faculty of Actuaries' 2023 publication "The Emporer's New Climate Scenarios", that #ClimateChange risk assessment methodologies, and the climate #scenarios that we have been using to underpin our disclosures and #TransitionPlanning, are understating economic impact, as they often "...exclude many of the most severe risks that are expected and do not recognise there is a risk of ruin. They are precisely wrong, rather than being roughly right."