Finrod Bites Wolves

Feeding India through the oncoming climate catastrophe

NB: (I seem to be writing these every post these days) I’m a climate… intersectionist, at best. If you’re a specialist and I’ve got something wrong, please do tell me. Basically my national security post got me interested in this.

Our food crisis under climate change is not one problem but several interacting ones: unstable monsoons, collapsing groundwater, nutrient-depleted soils, declining crop nutrition, pest expansion, and institutional systems built for a climate that no longer exists. It is possible to produce record harvests and still raise a malnourished generation, and India is getting dangerously close to discovering what that looks like.

The deeper problem is that India’s agricultural system still optimises primarily for calorie tonnage in a climate where nutrient density, ecological resilience, and hydrological sustainability increasingly matter more, because:

Elevated CO₂ and erratic monsoon → plants close their stomata to conserve water, so fewer minerals travel from soil to grain (the transpiration blockade), while depleted soils have less to offer in the first place → record harvests, but falling nutrition: more calories per plate, less zinc, less iron, less protein per gram → a population already short on protein eats food that is becoming shorter on protein with every degree of warming → food-insecure households face stunting and malnutrition → the same people are simultaneously being asked to do more physical work, not less: more pest management, more manual intervention as weather becomes erratic, malnourished women carrying nutrient-deficient pregnancies through harder seasons → faster physical burnout and growing intergenerational nutritional debt → greater humanitarian crises.

Why?

Because India’s agricultural calendar is built around the southwest monsoon (June to September). About half of our net sown area is rain-fed¹ ², and the IPCC’s Sixth Assessment Report³ ⁴ flagged increasing monsoon variability over South Asia⁵ as a high-confidence finding- this does not necessarily mean less total rain, but that the rain that does happen is more erratic in timing and more violent in intensity⁶: longer dry spells mid-season, more intense precipitation events at either end (it was literally hailing in Delhi a couple of days ago??!!⁷).

Secondly, heat stress is already biting into our agricultural yields even before water variability matters. For example, India lost an estimated 4-5%⁸ of its wheat yield, with losses of up to 10–25% in some districts⁹ ¹⁰, to the 2022 heat wave which arrived weeks ahead of historical norms and struck during grain-filling^{(the stage of grain development at which nutrients and carbohydrates are transferred into the developing grain}¹¹⁾ when the grain is most vulnerable¹².¹³ Without adaptation, several Indian crop‑model studies project that rain‑fed rice yields could fall by around 20% by mid‑century and approach halving by 2080 under high‑warming scenarios¹⁴, while even irrigated rice loses a few percentage points as heat stress intensifies. And that is before accounting for the groundwater that irrigates it running out.

Heat and water stress together could push food production in India down by 16.1% by 2050 in the worst-case scenario, against a global range of 6-14%, making India among the most exposed large economies on the planet.¹⁵ ¹⁶

The air
A landmark 2014 study published in Nature found that wheat grown under elevated CO₂ conditions contains 9.3% less zinc and 5.1% less iron than wheat grown under current atmospheric concentrations.¹⁷ Protein concentrations fall too, across C₃ grains and legumes, which is the category that includes wheat, rice, barley, and most pulses.¹⁷ A comprehensive 2025 meta-analysis synthesising data from approximately 59,000 samples across 43 food crops confirmed the pattern: elevated CO₂ produces food that is increasingly caloric and decreasingly nutritious¹⁸, with the most pronounced losses in zinc, iron, and protein. The researchers put it starkly: our food is becoming more calorie-rich, but less nourishing. The nutrient decline under elevated CO₂ is thought to result from multiple interacting mechanisms such as reduced transpiration, carbohydrate dilution (“more starch, same minerals”), altered nitrogen metabolism, reduced photorespiration effects in C₃ plants, and soil nutrient dynamics.¹⁹

For India, where rice and wheat together constitute the dietary backbone of over a billion people, this is not a theoretical concern. One modelling study projects that, by 2050, elevated CO₂ could reduce the effective global availability of protein, iron and zinc by roughly 15-20% compared with a world that had the same yields but today’s CO₂ levels, with South Asia among the hardest‑hit regions.²⁰ ²¹ A 2018 estimate put the human toll at 175 million people tipped into zinc deficiency and 122 million into protein deficiency by 2050, not because they eat less, but because the food they eat is less nutritious.²²

India already has 194 million undernourished people²³, 53.7% maternal anaemia²⁴, and the world’s highest child wasting rate²⁵. The CO₂ nutrition penalty lands on a population that has almost no buffer.

The soil
A February 2026 ICRIER report on soil health estimates that fewer than 5% of Indian soils now test high in available nitrogen and only around a fifth have adequate organic carbon.²⁶ Decades of intensive monocropping, overuse of urea-based fertilisers, and residue burning²⁷ have stripped soil of the microbial richness that makes nutrients bioavailable in the first place.²⁸ The fertiliser efficiency ratio (the kilograms of crop produced per kilogram of fertiliser applied) has collapsed: agronomists estimate that where farmers once got roughly 10 kilograms of grain per kilogram of fertiliser nutrient in the early Green Revolution years, recent ICAR data put the response at barely 9–11 kilograms, despite much higher application rates, with even lower returns in many intensively farmed districts.²⁹

Fertiliser
India’s agricultural soil now has too much nitrogen. This is because India’s subsidy regime makes urea artificially cheap, while phosphatic and potassic fertilisers are sold under a looser, nutrient‑based subsidy.³⁰ ³¹ The result is a skewed application pattern: against a recommended N:P:K ratio of about 4:2:1, India’s actual consumption is closer to 9-11:4:1 nationally, and far more distorted in some states, meaning fields are drenched in nitrogen and starved of other nutrients.³² ³³ Over time, this imbalance has produced “sick soils”: micronutrient deficiencies, rising salinity and alkalinity, and low organic carbon that together reduce fertiliser efficiency and yields.³⁴ ³⁵

The excess nitrogen does not vanish; it washes into groundwater and surface water as nitrate, where studies in Punjab, Bihar and elsewhere now find wells regularly exceeding WHO safety limits, with blue‑baby syndrome and cancer risks for rural families who drink that water, and when the fertiliser pours into river systems, they act like fertiliser for algae.³⁶ ³⁷ ³⁸Over time this creates eutrophication: thick algal blooms, oxygen‑starved stretches of water, mass fish kills, and sometimes toxin‑producing cyanobacteria that make surface water unsafe to drink.³⁹ ⁴⁰ ⁴¹

The water
Underneath that soil, India’s water table is in freefall.⁴² India is the world’s largest consumer of groundwater for agriculture, with groundwater accounting for 60% of all irrigation supplies.⁴³ A study published estimated that groundwater depletion could reduce crop production by up to 20% nationally, and by up to 68% in regions with the lowest projected future groundwater availability.⁴⁴ A 2024 IIT Gandhinagar study found that weakening summer monsoons, itself a consequence of climate change, are accelerating this depletion.⁴⁵ The warming climate is simultaneously drying the monsoon that recharges our aquifers and increasing the evaporative demand that empties it. By 2080, the rate of groundwater depletion could triple if current trends hold.⁴⁶

Dairy and livestock
India’s nutrition system does not run on crops alone. A significant share of protein, fat, and micronutrient intake comes from milk and other animal-sourced foods, produced largely by smallholder households rather than industrial systems.⁴⁷ ⁴⁸ But this too sits under climate stress. Heatwaves reduce milk yield and fertility in cattle and buffalo, while increasing disease susceptibility and mortality risk.⁴⁹ ⁵⁰ At the same time, fodder availability is becoming more erratic as monsoons destabilise and common grazing lands degrade, forcing farmers to rely on more expensive or lower-quality feed.⁴⁷ ⁵¹ The result is a quiet squeeze: rising input costs, falling productivity per animal in extreme years, and a nutrition buffer that becomes less reliable exactly when crop-based nutrition is also deteriorating.⁵²

The Sea
India is the world’s third-largest fish producer, and for hundreds of millions of coastal and riverine families, fish is the primary protein source.⁵³ ⁵⁴ This source of food is also under stress. The Bay of Bengal is warming, and a 2025 study found that both extreme and weak monsoon conditions, both of which climate change makes more likely, reduce surface food availability for marine life by around half in some simulations, thus disrupting the plankton base that the entire food chain runs on.⁵⁵ ⁵⁶ Inland, erratic monsoons dry out ponds and silt up rivers, destroying the small indigenous fish species that rural families harvest.⁵⁴

The biology⁵⁷ ⁵⁸
There is a biological dimension to this that rarely makes it into climate or food security writing: women are born with all the eggs they will ever have. Every oocyte is already present at birth, formed inside the mother’s uterus before the daughter herself is born. The nutritional environment of the womb may influence those developing oocytes at a molecular level.⁵⁹ ⁶⁰ Researchers studying developmental and epigenetic effects increasingly suspect that severe nutritional stress during pregnancy can alter patterns of gene regulation in ways that may extend across generations.⁶¹ So, a malnourished pregnant woman does not only affect her child’s development. Emerging evidence suggests some nutritional stresses may also influence gene regulation across multiple generations through the oocytes already forming in her developing fetus.⁶²

India’s 57% anaemia rate for women of ages 15-49 is not⁶³, therefore, only a present-tense health crisis, but a multi-generational nutritional debt, and children bear the next wave. India’s approximately 37 million⁶⁴ stunted children will be the workforce of 2040–2050 with permanently reduced cognitive and physical capacity from the malnutrition of their first thousand days. The climate disruption is projected to peak in the same window.⁶⁵ These are not separate problems.

Pestilence
As temperatures rise, the geographic ranges of many insect pests are shifting poleward at rates measured in the tens of kilometres per decade⁶⁶ ⁶⁷, with new climate envelopes allowing species to colonise regions where they previously could not overwinter. In practical terms for India, this means crops in the Indo-Gangetic Plain, including wheat, rice, vegetables, are increasingly exposed to pests and pathogens for which they have evolved no resistance.⁶⁸ ⁶⁹

The consequences are already visible on the ground. Farmers across Maharashtra report that pink bollworm, absent for nearly 12 years, has returned, with repeated pesticide applications the only available response.⁷⁰ ⁷¹ Meanwhile warming temperatures in Rajasthan have produced up to ten pest attack events in a single year, up from historical norms.⁷² Roughly speaking, each additional degree of warming allows many insect pests to shift their ranges by hundreds of kilometres polewards and tens of metres uphill.⁶⁷ For crops bred to local pest profiles over centuries, that is a radically destabilised environment.

The response of farmers in a system with weak extension services⁷³^{(systems that bridge the gap between scientific research and farmers, providing training, technical advice, and information}⁷⁴⁾ and limited credit access⁷⁵^{(because without access to easy credit, poorer farmers are unable to fund access to the knowledge and methods of pest control)} is almost always the same: more pesticide. This adds cost, further degrades soil microbial life, and to round everything off, impairs the very biodiversity in soil and water systems that would otherwise offer natural pest suppression.⁷⁶ ⁷⁷ It is also why traditional and heritage varieties of seeds and plants, which carry broader genetic resistance shaped by long regional exposure, become more valuable as pest ranges shift.⁷⁸

Pollinators
A significant share of the plant food Indians need more of, including vegetables, fruits, oilseeds, and pulses, depends on pollinators to set seed.⁷⁹ ⁸⁰ Climate change disrupts this through what ecologists call ‘phenological mismatch’⁸¹: as temperatures rise, plants flower earlier while pollinator life cycles shift at a different rate, so the flowering window and the pollinator activity window stop reliably overlapping. A study published in 2025, drawing on 120 years of specimen records, documented a significant increase in local extinction risk for flowering plants driven precisely by this kind of bee-flower mismatch.⁸² ⁸³

Concrete
A study using satellite data found that from 2001 to 2010⁸⁴, agricultural land lost to urbanisation was concentrated in districts with high agricultural suitability.⁸⁵ Over the two decades from 1991 to 2011, roughly 1.59 million hectares of prime farmland was converted to non-agricultural use.⁸⁶ ⁸⁷

As that peri-urban agricultural belt disappears, food has to travel further, which makes India’s chronically underdeveloped cold chain more critical and more energy-intensive.⁸⁸ ⁸⁹ Agriculture gets pushed onto marginal land such as hillsides, arid zones, or areas with thin soils, which are, almost by definition, the land most vulnerable to the climate shocks described everywhere else in this piece.⁸⁵ ⁹⁰ ⁹¹

Ownership gap⁹² ⁹³ ⁹⁴ ⁹⁵
As farming becomes less viable men migrate to cities for other work. What remains is increasingly managed by women. Around 80% of rural women in India are now engaged in agriculture; they handle roughly 70% of all farm tasks. However, just 11-12% of agricultural landholdings were registered in women’s names. Without a land title, you are not, legally, a farmer in India: which means no PM-KISAN payments⁹⁶, no crop insurance, no institutional credit, no access to most government agricultural schemes.

Cold Chains– I’ll be writing on this soon. Also, India’s future food resilience depends partly on reliable electricity expansion, because refrigeration⁹⁷, irrigation pumping⁹⁸, fertiliser production⁹⁹, and transport¹⁰⁰ are all energy-intensive.

One bright spot
India’s community seed banks now collectively steward at least 887 traditional varieties across 71 crop species, documented across 15 states in a 2025 CSE report.¹⁰¹ ¹⁰² These varieties are locally adapted, which means they have been shaped over centuries by the specific soils, monsoon patterns, and pests of their regions. Many are more drought-tolerant, flood-resilient, and nutritionally dense than their commercial replacements.¹⁰³

India has the world’s largest formal gene repository, the National Bureau of Plant Genetic Resources.¹⁰⁴ ¹⁰⁵ However, formal conservation and living seed systems are not substitutes for each other. The first preserves genetic material. The second keeps knowledge, practice, and biodiversity alive in farming communities.¹⁰⁶

What we can do
The solutions are not mysterious, if even I can suggest them.

Fix the cold chain. India has roughly 8,000 cold storage facilities¹⁰⁷, most of which store potatoes. Decentralised solar cold storage at the Farmer Producer Organisation level would reduce post-harvest losses, currently between 30–40% for perishables¹⁰⁸, and stabilise supply in the face of erratic weather.
MSP reform toward climate-resilient crops.¹⁰⁹ Millets, pulses, and oilseeds are might be more drought-tolerant, more nutritionally diverse, and less susceptible to CO₂-driven nutrient dilution than rice and wheat.¹¹⁰ Moving minimum support prices to signal farmers toward these crops is the only thing that moves production at scale. Promotional campaigns without price signals don’t work.
Fund and legally empower community seed banks. The CSE report’s estimate of 887 traditional varieties across community banks is a fraction of what has already been lost. Seed sovereignty is food sovereignty. Legal recognition, technical support, and sustained funding for community seed banks, including unrestricted rights for farmers to save, exchange, and sell traditional varieties, is one of the highest-return investments India can make in long-run food resilience.
Recognise women as farmers by activity, not land title. Shift the legal definition from landowner to tiller (which is politically highly improbable of course, but well… do something to improve the actual worker’s access to funds and education).
Reform fertiliser subsidies toward soil health. The current subsidy architecture, which gives 80%+ subsidies to urea while leaving phosphorus and potassium significantly less supported, has produced the soil crisis India now has. Rebalancing toward nutrient-balanced fertilizers, funding soil health cards, and incentivising organic matter restoration is not optional. It is the prerequisite for everything else.
Integrate nutrition tracking into agricultural statistics. A rice crop that produces 20% fewer tonnes at 10% lower protein content per grain is a double failure, but it shows up as one number in production statistics. Climate adaptation schemes, crop insurance frameworks, and agricultural research all need to track nutrient density alongside yield.

What makes this moment so consequential is not any single pressure, but their convergence: Soil that is already depleted produces crops that are already less nutritious. Those crops are grown in a system structurally dependent on groundwater that is already running out. The monsoon that was supposed to recharge that groundwater is becoming more violent and less predictable. And rising CO₂ is simultaneously reducing the nutritional content of the crops that do grow. Each layer of stress compounds the others, and into that situation, add: crops that become less nutritious as CO₂ rises, yields that fall under heat and monsoon stress, and a dairy system that loses productivity precisely as temperatures climb.

For India, feeding people must come before reducing agricultural emissions, but ignoring emissions is not cost-free. Every degree of warming tightens the constraint a little further. India’s record food grain production figures and its catastrophic localised harvest failures have begun to coexist in the same season- the 2025 October monsoon that damaged crops across Maharashtra and Karnataka in the same year production statistics showed record outputs.¹¹¹ That coexistence will become more common, and more violent.

India is obsessed with “Record Production” (the headline numbers). But if those tonnes of grain are nutritionally hollow (due to the CO₂ penalty) and the soil is just a medium for urea-driven growth, we are effectively inflating our food stats. We are producing more food but less nourishment.

We cannot grow our way out of this climate crisis. But we can build a food system that is robust enough to feed its people through the disruption ahead. The alternative is to find out, a generation from now, in the health data of children not yet born, what it cost not to have done so.

Sources

(I cannot figure out where the extras are, so here are four more sources than what I can find in my article above)

Signal and Noise in Cricket Performance

You know that feeling when you see the perfect ball? You may not even see who the bowler is from the camera angle, but you see the ball, and it’s… beautiful and lethal and just. Like a song that hits the spot. It’s the physical manifestation of joy.

So when a bowler bowls such a ball, is that because they are in really good form, or is that just how they bowl in general? That has to be different for every bowler, right? And yes this is about bowlers because I just saw Mitch Starc bowl and the bowling. The bowling. Poetry.

This piece asks a rude question: If you took a bowler whose underlying ability wasn’t changing from match to match, and just let randomness do its thing, how often would you see those streaks anyway? Also, what does “form” mean for a fan watching from the outside, and what does it mean for the bowler inside the game?

Why is this about bowlers and not batters?
When a batter scores runs, the runs are directly and unambiguously attributable to them. They chose the shot, they middled it or they didn’t, it went where they hit it or it didn’t. A batter who scores 80 runs scored 80 runs. The metric accumulates continuously across the innings- every ball is a data point, not just the ones that produce wickets. So in a single innings you might have 150-200 data points building toward the final score. That’s a meaningful sample size from one performance.

A bowler’s primary success metric- wickets- is a joint event. It requires the bowler to produce a good delivery AND the batter to fail to handle it. Even a perfect delivery can be survived if the batter gets a thick outside edge that falls short of slip. A rank bad ball can produce a wicket if the batter top-edges a slog. The wicket isn’t just measuring the bowler. It’s measuring the bowler plus the batter plus the fielding plus a slice of luck.

And wickets are rare. A good Test bowler might take one wicket every 40–60 balls on average.¹ ² That means in a full spell you might have one, maybe two wickets to evaluate. That’s almost no data, and like I said above, the noise in a single wicket is enormous relative to the signal because it’s a joint event.

You might think economy rate solves this because it’s not as rare as wickets because it accumulates ball by ball like a batting score. But economy rate is contaminated by things the bowler doesn’t control: fielding (a misfield gives away four runs the bowler didn’t deserve), the batter’s attacking intent (a batter in T20 mode will score off good balls that a Test batter would defend), and conditions (a wet outfield makes everything travel faster to the boundary). A batter’s score is more directly their own than a bowler’s economy rate is their own.

A batter who scores a hundred has, by definition, not gotten out for the entire duration of that hundred. Getting out removes them from the sample. So a large batting score has a built-in quality filter because the batter proved they could handle everything thrown at them for that entire period. A bowler doesn’t have an equivalent filter- we’ve all seen instances of bowlers getting absolutely pounded, but also of bowlers just not bowling even when they are available because the captain doesn’t trust them. Also, batters can get out and end their performance, but a bad spell stays in the data rather than ending it.

Batting produces a continuous, accumulating, directly attributable metric with a survivorship filter. Bowling produces a rare, jointly caused metric with high per-event noise and no survivorship filter. They could have the same amount of underlying skill variation, but batting gives you better and more frequent measurements of it. So the signal-to-noise ratio is structurally worse for bowling than for batting, even before you account for the process/outcome problem with great balls going for four.

So there are two questions tangled up in that one perfect ball. One: how much does a bowler’s true underlying state actually move around over time? Two: given how noisy bowling outcomes are, how much of what we call a purple patch is just random clumps sitting on top of the former?

Streaks, Clumps and Slumps
Remember that time we kept losing coin tosses across formats, tournaments, venues and captains? If not, you can read more about it here and here. It was exasperating, but it is just something that happens naturally with numbers. In any long sequence of random outcomes, you will see streaks. Not because something changed, but because that’s just what randomness looks like. The longer the sequence, the longer the streaks you’d expect just from chance. Cricket careers are long sequences. Impressive-looking purple patches will appear in random data.

A signal is the meaningful, underlying information or pattern within a dataset that conveys useful information about a phenomenon.³ In statistics it is the meaningful information, true pattern, or underlying trend hidden within a data set. It is the “message” you are trying to find, separate from random irregularities, which is called noise, which is random, unwanted, and unpredictable fluctuations or variability in data that obscure the underlying signal or true pattern.⁴ Think of information vs. data, or someone singing under their breath in an otherwise busy room.

Any observed performance is a mixture of signal (the bowler’s actual underlying ability on that day) and noise (luck, conditions, batter quality, fielding, the specific random variation of where each ball lands). The question isn’t whether good performances cluster- they do. The question is whether the clustering is bigger than the noise would produce on its own. This requires knowing how much noise there is in cricket outcomes.

If real form exists, if something genuine changes in a bowler’s body or mind that persists across matches, then knowing how they bowled last match should help you predict how they’ll bowl this match. That’s called autocorrelation⁵ ⁶ ⁷: the extent to which a value in a sequence is correlated with the value before it. If form is real, you’d expect positive autocorrelation in performance sequences. If it’s just randomness, autocorrelation should hover near zero.

Also there is a caveat: even if real form exists as a statistical signal, most cricket careers may not be long enough to detect it reliably. A bowler might play 50 Tests. Each Test gives you a handful of spells at a maximum. Separating signal from noise in 50-100 data points, when each data point contains substantial outcome variance, requires a very strong signal.

Regression to the Mean
Mean⁸ is a statistical word for average (sum all your data points, divide the sum by the number of data points, what we used to do in school). There’s a related concept that’s even more important for understanding how we perceive form, and it’s called regression to the mean^{(statistical phenomenon where extreme, unusual, or outlier measurements tend to be followed by measurements closer to the average}⁹⁾.

Extreme performances, either very good or very bad, are partly skill and partly luck. After an unusually good spell, the most likely next result is something closer to average. Not because form dropped, or because the bowler did anything differently, but because the extreme outcome reflected an unusually lucky combination of skill and chance variation, and that combination is unlikely to repeat in exactly the same manner.

This creates a specific perceptual trap: Imagine a bowler takes wickets in four consecutive matches. Everyone says they’re in form. The next match is average. Everyone says they’ve lost their rhythm. What actually happened is: the four good matches were skill plus good luck, and the average match was skill without particularly good luck. The average is always more representative.

What looks like form peaking and then fading is often just an extreme performances being followed by more typical ones, because that’s how averages work.

Hot Hands
In 1985, three psychologists, Gilovich, Vallone, and Tversky, published a paper about basketball players.¹⁰ They tested whether a player who had made several consecutive shots was actually more likely to make the next one, as coaches, players, and fans universally believed. The answer was no. When they applied proper statistical tests to shooting data, the streaks that looked like “hot hands” were completely consistent with what you’d expect from random sequences. The hot hand was, they concluded, a cognitive illusion- the human brain is extraordinarily good at finding patterns and just terrible at recognising what randomness looks like.

Then, in 2018, two researchers named Miller and Sanjurjo found a problem with it.¹¹ There’s a subtle mathematical bias that appears when you look for streaks within short sequences — the way the original paper sampled the data produced an underestimate of the true streak effect. When they corrected for it, a small but real hot hand effect appeared in the data. Not large, not the dramatic momentum that commentators describe, but statistically detectable.

So: the hot hand probably exists a little, but there is probably a difference between what it means for the bowler themself (internal), the fan (external), and the statistician (mathematical).

Has this been tested in cricket?

A study titled Significant hot hand effect in the game of cricket specifically looked at ODI and Test performances.¹² Unlike the basketball study, which found outcomes were independent, this research used self-exciting point processes (a fancy way of saying “success increases the probability of immediate future success”, I don’t know why researchers talk like this, it’s so annoying) and found:

Predictability exists: In both ODIs and Tests, individual performance sequences showed more clustering than random chance would allow.
The “60% Rule”: The researchers found that models accounting for the hot hand outperformed random-null models^{(a simplified, randomized version of real data used to test if observed patterns are due to chance. It keeps some data structure fixed (like totals) but randomises others to create a “baseline” for comparison)} about 60-62% of the time, which is statistically significant^{(this means that the outcome is unlikely to have occurred by chance alone}¹³⁾.

Real vs. Casual
A famous Yale study¹⁴ on bowling (ten-pin bowling, that is) data found something similar: the hot hand is real but not causal. One strike doesn’t magically cause the next; instead, players go through high‑ and low‑performance states where every ball in that window is a bit more or less likely to work.

So, a player isn’t “hot” because they just took a wicket; they are “hot” because they are currently in a high-performance state where the probability of a wicket is higher for every ball in that window.

What Does “Normal” Look Like for This Bowler?
Here’s the idea: pick a bowler, and choose a stretch of their career where they feel like roughly the same player- same role, same format, similar fitness, no huge technical overhauls, then take the average of all their performance numbers. The result, is what you’d expect from this bowler on a typical day in this phase of their career, which means it is the baseline- the normal level of this bowler in the period you care about.

Why does version control^{(called non-stationarity in statistics}¹⁵⁾ matter? Because different versions of the same person should not be put in the same streak of matches, because an early Mitch Starc and present day Mitch Starc are completely different bowlers. So they produce maybe the same looking ball, but the process and consistency must be completely different (maybe, I think), and in that way that is a different ball altogether.

And also, as with any average, the larger the sample size, the more representative it will be of the next ball that will be bowled.¹⁶ This is why we want a reasonable sample, so please think dozens of matches, not 3-4.

Now we want to know, game by game, whether the bowler was better than their own usual level or not, and because we know this, we can find out for each match how much they deviated from this average. This is straightforward subtraction- if the Average is A, and the new data point (the performance from the current match) is B, then if:

A>B, the bowler didn’t bowl as well as the recent most applicable average,
A<B, the bowler bowled better than the recent most applicable average, and
A=B, the bowler bowled as well as the recent most applicable average.

We can take this as:

A>B as a score of -1,
A<B as a score of +1, and
A=B as a score of 0- that is, they are bowling on average neither better nor worse than the current average.

So,

+1 = better than usual
0 = roughly normal
−1 = worse

Which means that over ten matches one might see: +1,0,−1,+1,+1,0,+1,−1,+1,+1.
That’s a crude form diary for this bowler in this phase of their career.

What randomness actually looks like
Imagine a bowler whose underlying ability is completely fixed- same skill, same fitness, same everything, match after match. No slumps, no golden periods, no form at all. Just a consistent underlying level of performance with some random variation in outcomes from match to match, because cricket is not a controlled experiment and outcomes are noisy.

Now watch that bowler for fifty matches.

You will see streaks. Strings of matches above their average. Strings below. At some point you will see five good matches in a row and think: they’re in form. At some point you will see four mediocre matches and think: they’ve lost it. Neither conclusion would be correct. You’d be reading patterns into randomness.

In statistics, this is called a ‘run’. A statistical run is a streak of similar outcomes¹⁷, so above average, above average, above average is a run of three. The Runs Test¹⁸ asks: given this sequence of above-and-below-average performances, does the pattern of runs look like what you’d expect from pure randomness, or is there more clustering (or more alternating) than chance would produce? You don’t need the formula. The logic is: count the runs, compare to the expected number if the sequence were random, and ask whether the difference is bigger than chance alone would explain.

But to know what is above average, first we need to know what is average for that bowler.

The Poetry is the Signal
So, is a bowler who scores +1,0,−1,+1,+1,0,+1,−1,+1,+1 in good form or average form?

As far as I can see, there are three types of form in cricket bowling:

Type 1: Physical/biomechanical state: The bowler’s body is working or it isn’t. Rhythm, run-up, shoulder position, wrist at release. This is internal and real and the bowler feels it immediately. A niggle, a slight change in action, fatigue, just their mental state, these affect the actual delivery. This is the closest thing to true form.
Type 2: Outcome form: What the scorebook says. Wickets, economy, match figures. This is what fans and selectors see. It’s a noisy, delayed, jointly-caused signal that reflects Type 1 form plus batter quality plus fielding plus luck. It can diverge wildly from Type 1- a bowler can be in beautiful physical form and get hammered because the batters are brilliant that week, or be slightly off and take a five-for because edges keep flying to hand.
Type 3: Perceived form: What fans, commentators, and sometimes selectors believe based on Type 2. Subject to all the cognitive biases described- hot hand illusion, regression to the mean misread as form loss, pattern-finding in noise.

But bowlers are not coin tosses. People are not numbers, so bowlers remember the last ball, they feel their front leg blocking well or not, they sense whether the seam is landing upright, they know if their shoulder is sore. Those things change the underlying probability of a good ball in a way no simple random model can capture.

The hot‑hand studies in other sports end up in a similar place: they find real fluctuations in a player’s underlying performance level over time, but very little of it is the magical one-success-causes-the-next momentum commentators seem to love.

So,

Individual bowlers do have better and worse phases. There is some persistence in performance beyond pure randomness.
But bowling outcomes (wickets, runs) are so noisy and so joint that even a completely flat bowler would eventually generate streaks that look like form.
The “hot hand” we see on TV, such as wickets in clumps, commentators rhapsodising, is mostly our brain misreading random clumps as deep narrative, with a thin layer of real underlying changes.
For the bowler inside the game, “form” probably means something more process‑y: how their body and action feel, whether they can hit the length in their head, whether their corrections are working. The scorecard is a crude, laggy, sometimes unfair reflection of that.

The “Signal” isn’t the wicket. The wicket is the Outcome, and the Outcome is noisy, messy, and shared with ten other people. The “Signal” is that feeling I had watching Starc bowl. It’s the Process– the perfect snap of the wrist, the late tail of the ball, and only then, sometimes, the sound of the stumps.

Sources

Markets

NB: Not an economist. At all.

I found that I was constantly writing about different kinds of markets without explicitly talking about them, so here’s a quick primer on what markets are. Generally on this website, I speak of markets as a general‑purpose system for allocating burdens, risks, and rewards through prices (or price‑like trade‑offs), rather than a narrow place where “goods are sold”, however, let’s look at how economics looks at them.

Scarcity¹ ²
Markets originate from scarcity.

Most resources are scarce, so they attract competition for who can possess or use them. The scarcer a resource, the greater the competition.

This causes a conflict, because many of us want the same scarce things, and so not all of us can have it (scarcity), therefore there needs to be a mechanism which allows us to “distribute” the resources in question.

Economists typically distinguish between natural scarcity (finite deposits of oil, land) and artificial scarcity (patents, exclusive licences, paywalled content), where supply is deliberately restricted rather than inherently limited. Artificial scarcity is a choice someone made, and is often a market feature used to incentivise creation (like patents) but becomes a market failure when it merely protects a monopoly; natural scarcity is a constraint the world imposed.

A market is a decentralised way to coordinate who gets what, when, and on what terms, using prices (or price‑like trade‑offs) instead of a central command.

Markets³ ⁴
In economics, a marketplace need not actually be a place. It is any set up where buys and sellers can meet, whether physically, postally, or digitally, where they can exchange goods and/ or services for a price both parties agree upon. A market must have the following three qualities:

Buyers and sellers can find each other (directly or via intermediaries).
They can propose and respond to prices.
They can actually complete trades under some agreed rules.

The price can be the explicit price, such as rupees per kilo, dollars per share, or an implicit one where there is a trade‑off in time, risk, or access.

Here are some examples:

Buying goods and services: Retail shops, online platforms, and local mandis are all market institutions.
Working for pay: Job boards, recruitment drives, and informal hiring channels are part of labour markets.
Saving and borrowing: Bank deposits, loans, mutual funds, and stock trading are ways of participating in financial markets.
Using shared resources: Paying for mobile data, electricity, or spectrum licences involves markets (sometimes heavily regulated) for underlying rights or capacity.

For markets to exist, these three conditions must exist:

Mutual benefit: Voluntary trade only happens if both sides believe they are better off after the trade than before. I value the thing I’m buying more than the money I give up; you value the money more than the thing you’re selling. If either side does not feel this way, the trade simply doesn’t happen. After a VOLUNTARY trade, at least one party is better off and neither is worse off than before- this is called a Pareto Improvement. Note that the trade must be voluntary. This condition breaks down when markets shade into exploitation instead of exchange, such as when there is coercion, lack of real alternatives, or misinformation.
Property and usage rights: There has to be some notion of “mine” and “yours.” You must be allowed to sell or lease what you hold; I must be allowed to buy it. This can be formal (land titles, contracts) or informal (everyone in the village agrees that this field is yours), but some recognised right to control and transfer is needed.
Trust and enforcement: When I hand over my money, I need to trust that I will actually receive the good or service, and vice versa. That trust might rest on law courts, regulators, reputation, or community norms. Without some enforcement—formal or informal—exchange becomes too risky to sustain.

Price⁴ ⁵
In economics, a price is the amount of something you must give up to get one more unit of something else. Most of the time that “something” is money- for example, rupees per kilo of rice, dollars per share of stock, but it can also be another good in a barter trade, your time, or a change in risk you are willing to accept.

More formally: In a money economy, price is the amount of money required to purchase one unit of a good, service, or right. In barter, it is the rate at which two goods exchange—for example, “three eggs for one roti.”

In relative terms, you can think of the relative price of A in terms of B as “how many units of B does one unit of A cost?” So a price is a rate of exchange. It tells you “one unit of this is worth this much of that, here and now.”

You can immediately separate three related but different ideas:

Price: what is actually paid or quoted in the market at a given moment.
Cost: what it takes the seller to produce and offer the thing (inputs, effort, time).
Value: how much the buyer feels it is worth to them, which may be higher or lower than the price.

In everyday speech, “price” can mean the tag on a product, a number in a contract, or the figure someone mentions in a negotiation.

Economists usually distinguish:

Asking price / list price: What the seller initially posts or demands.
Bid price: What a buyer is currently willing to pay.
Transaction price (or market price): The price at which an actual trade happens.

In a competitive, active market, many transactions happen over time. The market price at a moment is the going rate at which the good or service is trading—what buyers are paying and sellers are accepting in that marketplace. In your posts, when you say “price”, this is usually what you’re pointing to: the number that comes out of the interaction of demand and supply, not just what one side wishes it were.

Another couple of useful adjectives for later:⁶

Nominal price: The price expressed in current money terms—“₹100 today.”
Real price: The price adjusted for the overall price level (inflation) or expressed relative to another good (“how many bus rides a kilo of tomatoes costs compared to last year.”)

For most of this primer, “price” can safely mean the simple, nominal market price. The real/relative distinction becomes important when you compare across time or across goods.

Prices do two jobs:

Carry Information⁷: This is called “Price Signal”. A rising price often signals that, at current quantities, demand is strong relative to supply; a falling price signals the opposite. You do not need to know the full back‑story (crop failure, input cost increase, a viral social‑media trend). The change in price is a compact way the market tells everyone, “this has become relatively scarcer/desirable” or “this has become relatively more abundant/unwanted.”
Provide Incentive: Higher prices encourage producers to supply more (if they can) and discourage some buyers from purchasing; lower prices do the reverse. This is just the law of supply and demand written as a feedback loop.

There is this cool essay called “The Use of Knowledge in Society” by Friedrich A. Hayek which argues that no central planner can ever gather or process the dispersed, local knowledge held by millions of individuals, and yet prices aggregate all of that knowledge into a single number that everyone can act on without needing to know the backstory.⁴

This was demonstrated in 1986 after the Challenger Space Shuttle disaster⁸ ⁹, when on January 28, 1986, the Space Shuttle Challenger tragically broke apart 73 seconds into flight due to a failure of the O-ring seals in the right solid rocket booster. The rocket boosters were manufactured by Morton Thiokol. While the official investigation took months, the stock market reacted within minutes of the explosion with heavy selling. Twenty-one minutes after the explosion, Lockheed’s stock was down 5%, Martin Marietta’s was down 3%, and Rockwell was down 6%. But something unusual was happening with Thiokol. So many investors were trying to sell its shares, and so few were willing to buy, that the New York Stock Exchange halted trading in Morton Thiokol almost immediately, the only one of the four contractors to be suspended. When trading resumed nearly an hour later, the stock was already down 6%. By market close, it had fallen nearly 12%, shedding approximately $200 million in market capitalisation in a single day. The other three contractors, by contrast, recovered through the afternoon and ended the day down only 2-3%.

The market turned out to be correct. When the Rogers Commission released its report in June 1986¹⁰, it concluded that the O-ring seals on the booster rockets manufactured by Thiokol had failed in the cold temperatures of that January morning, allowing hot gases to escape and ignite the main fuel tank. Thiokol was held liable. The other three contractors were exonerated. Finance professors Michael T. Maloney and J. Harold Mulherin, who studied the market’s reaction in detail, found no evidence of insider trading or manipulation — the market had simply aggregated the dispersed, partial knowledge of thousands of investors, each acting on their own reading of publicly available information, and produced a price signal that pointed, with remarkable precision, to the right culprit within half an hour of the disaster. The $200 million wiped from Thiokol’s market cap that afternoon, Maloney and Mulherin concluded, turned out to be almost exactly what the company eventually lost in real cash flows once culpability was formally established.

This is truly one of my favourite anecdotes about markets. Price is not arbitrary. It is the outcome of many pushes and pulls, such as what people are willing to give up, what it costs to provide, how many alternatives there are, and what rules and power structures sit around the transaction.

Choice¹¹
Because resources are scarce, they have prices attached to them, and because people don’t have unlimited barter goods or money, they have to make a choice about how to use their barter goods and money so they can have their most desired resources.

Each individual decides what resources they wish to have, and how much they are willing and able to pay for it given their own resource constraints (limited amount of money or barter goods). This is the demand side of the economy.

At the same time, each producer, or owner of resources, decides how much they wish to sell or barter their resources for. As we saw above, prices carry information and nudge behaviour- when a resource has many potential buyers, its price will naturally rise up as some people will be willing to pay more for it than others, and this will continue until the demand equals the amount of the resource that is available for sale.

The sale side of the market is called the supply side. Markets exist where demand = supply.¹²

However, when buyers pay less than they were willing to pay, the difference is called consumer surplus. When sellers receive more than their minimum acceptable price, the difference is known as producer surplus. These two ideas explain how much voluntary trade benefits both sides, and why markets, when they work well, are not zero-sum games- when both surpluses are added together, economists call it total welfare or social surplus. Basically:

Consumer Surplus¹³: The “I would have paid $10 but it only cost $5” feeling.
Producer Surplus¹⁴: The “It only cost me $2 to make, but I sold it for $5” feeling.
Total Welfare: The sum of both. This is why economists get so upset about taxes or regulations that “shrink the pie” (the permanent loss of total welfare, called deadweight loss).

Opportunity Costs¹⁵ ¹⁶
An interesting and slightly esoteric concept, opportunity cost is the cost of the alternative people don’t choose.

Economists assume people are rational ^{(as we know, this is not always true, and it has been demonstrated by some economists- it’s not that people are “stupid” or “irrational”; it’s that we have limited time, limited information, and “shortcuts” (heuristics) in our brains)}, which means that they are able to rank how much they desire different resources. Because (in a money market), their resources to purchase the different resources are scarce, economists assume that they will buy a higher ranked resource before they purchase a lower ranked resource. But, they did desire the lower ranked resource too, just not as much as the higher ranked one, so their choice of purchase is double edged- when a person chooses to purchase something, because their resources are scarce, they are also choosing to not purchase something. The cost of what they did not purchase is called the opportunity cost.

Why does it matter? Because we are now aware of what we are giving up, we are forced to understand the trade off, and it helps us make the best choices possible for our particular situation (how much money we have and what we need to buy).

The concept of opportunity cost helps make better choices by accounting for scarcity of resources and highlighting what we are giving up when we make a choice to have something else instead of the lower ranked item, and it guides individuals and firms to choose options that yield the highest possible returns.

In economics, it is used in the following ways:

Decision-Making: It forces individuals and businesses to consider what they lose by choosing one option over another. In business, it helps managers determine the best use of limited resources (time, money, labour), such as choosing between two different projects.
Investment Strategy: Investors use it to weigh potential returns of one asset against another, evaluating what they forego by holding a particular investment.
Policy Analysis: Governments use it to assess the true cost of policies, such as the expense of infrastructure versus healthcare.
Valuing Time: Economists convert time spent into monetary values to measure the cost of non-monetary choices.

So, every time you say “Yes” to a purchase or a project, you are implicitly saying “No” to everything else you could have done with the resources you are spending on it- time, money, or any other resource you use as payment. Price is what you pay; Opportunity Cost is what you lose.

What Markets Do⁴ ¹⁷
Markets are where prices meet choices.

Individuals and organisations constantly face choices: buy or not buy, work here or there, save or spend, invest now or later. Price is the visible side of the trade‑off; their time, energy, money, and goals are the invisible side.

At a very high level:

If the price of something is below what it is worth to you, you are tempted to buy.
If the price is above what it is worth to you, you walk away.
If you are a seller, you are more willing to supply when price is high enough to comfortably cover your costs and effort; less willing when it is not.

A market is the environment in which all those individual “yes/no/ how much?” decisions, at given prices, add up to visible quantities traded and visible prices changing over time. This is called Aggregation. Markets bring together millions of individual choices and converge on one data point- price of the resource on sale.

Market Structures¹⁸ ¹⁹ ²⁰
Different resources live in different types of markets. Market structure is the degree of competition among buyers and sellers. The four canonical structures are:

Structure	Sellers	Price Control	Example
Perfect competition	Many	None- the price is determined entirely by the aggregate market. Perfect competition is an analytical ideal that rarely exists in pure form — it functions as a benchmark against which real markets are measured, not a description of reality.	Agricultural commodities come closest, but there is no real market which is perfectly competitive, except in economists’ dreams.
Monopolistic competition.	Many	Slight- to an extent, sellers can decide their price bands.	Restaurants, clothing brands
Oligopoly. The buyer side equivalent is called an Oligopsony (few buys many sellers).	Few	Significant- because there are fewer sellers, buyers are price takers, that is, they have less control as a group on the prices being charged for the resource as there are few alternative sellers available	Telecom, airlines. For oligopsony: the handful of large apparel brands sourcing from thousands of small garment manufacturers.
Monopoly. The buyer-side equivalent is called a Monopsony (one buyer many sellers).	One	High- since there is only one seller, this seller can dictate the price to the market.	Utilities, some pharmaceutical drugs. For monopsony: the government’s procurement of agricultural produce through MSP (Minimum Support Price)

Understanding structure matters because it shapes how and how likely a market is to fail.

Market Failure²¹ ²² ²³
Markets are a powerful mechanism for allocating resources, but they are not infallible. A market failure occurs when the price mechanism produces an outcome that is inefficient or socially suboptimal. This happens when the prices that buyers and sellers agree on fail to reflect the full costs or benefits of a transaction to everyone affected by it. Economists identify four core causes.

The first is externalities²⁴: when a transaction imposes costs or confers benefits on parties outside the trade itself, those effects go unpriced. A factory that dumps waste into a river lowers costs for its shareholders while imposing costs on every downstream community, which are costs the market price of its product never captures. Most externalities (like pollution) happen because property rights are poorly defined—no one ‘owns’ the air, so no one can charge the factory for using it as a trash can.
The second is public goods²⁵: goods that are non-excludable (you cannot stop people from using them) and non-rival (one person’s use doesn’t reduce another’s), such as clean air, national defence, or open-source software — private markets systematically underprovide these because no one can easily charge for them.
The third is information asymmetry²⁶: when one side of a trade knows something the other doesn’t, prices become distorted. A seller of a used car knows its history; the buyer doesn’t. An insurer cannot fully verify how recklessly a policyholder will behave once covered- this specific problem is called moral hazard. A related problem, called adverse selection, happens before the deal is made: the pool of sellers disproportionately contains those with worse goods to offload, because owners of high-quality goods are less likely to sell.
The fourth is market power: when a single firm or a cartel of firms controls enough of the supply to set prices above competitive levels, buyers pay more and less of the good is produced than society would collectively prefer.

These four failures are precisely why the most contested markets such as for carbon, for data, for healthcare, are so politically charged: they are riddled with externalities, public-good characteristics, and deep information asymmetries, which means the price that emerges from voluntary trade systematically underestimates the true social cost, or overestimates the true social benefit, of what is being exchanged.

Markets answer who gets what (whoever has the most purchasing power and willingness to pay), but they do not answer who should get what. Even a perfectly functioning market with no failure can produce outcomes that are efficient but deeply unequal. This is the gap that political economy and policy fill, because market prices can give very misleading signals for long periods, as the 2008 financial crisis demonstrated, and as climate change, the canonical externality failure, continues to demonstrate.

Government Failure²⁷ ²⁸ ²⁹
Government intervention is the standard prescription for market failure- but governments fail too, and in predictable ways. Regulators can be captured by the industries they oversee, producing rules that protect the producers rather than consumers or the public. Governments also face the same knowledge problem that price signals solve in markets: setting the right carbon price, the right drug approval threshold, or the right spectrum fee requires information that is dispersed, contested, and often unavailable to any central authority. Politicians respond to electoral incentives, not social welfare functions, so policies tend to favour the short-term and the visible over the long-term and the diffuse. And interventions in complex systems produce unintended consequences: for example, rent controls create housing shortages, agricultural price supports depress farmers in poorer countries, financial regulations push risk into unregulated corners of the system.

The choice is therefore never “flawed market vs. perfect government.” It is always “this particular market failure vs. this particular government failure”, which is precisely what makes policy so hard, and so interesting.

Non-Market Allocations³⁰ ³¹
To define what a market is, it often helps to briefly mention what it isn’t. If we don’t use markets to allocate scarce resources, we use:

Rationing: A central authority decides.
Queuing: First come, first served.
Lottery: Random chance.
Violence/ Power: Might makes right.
Social Norms and Reciprocity – The economist Elinor Ostrom won the Nobel Prize in 2009 for showing that communities can sustainably manage shared resources, such as fisheries, forests, irrigation systems, without either markets or top-down authority, using informal rules and reputation. ^{(Ostrom’s contribution was specifically about common-pool resources, which are goods that are rival (one person’s use depletes the stock) but non-excludable (cannot prevent anyone from using them), such as fisheries and groundwater. This is distinct from public goods (non-rival, non-excludable), and from private goods. Her insight was that this middle category could be self-governed through community institutions. Her work directly challenged Garrett Hardin’s influential 1968 argument, known as the tragedy of the commons, that shared resources are inevitably destroyed because each individual has an incentive to exploit them before others do.}³²⁾³³

In practice, most real-world allocation systems are hybrids. A hospital’s ICU uses queuing (who arrived first), rationing (clinical triage), and implicit pricing (quality of insurance) simultaneously. Pure market allocation is an analytical ideal, not an empirical description.

Whenever you see me write about markets, I’m not just talking about money. I’m talking about how we, as a society, are currently calculating what is scarce, what is valuable, and who is willing to pay the price to claim it.

Sources
For most of the concepts in this primer, see any introductory microeconomics textbook. I personally love the ones by Ambika Gulati, who taught me economics in XI and XII grades.

The Bill Comes Due

NB: This whole argument takes for granted that the objective is a sustainable, voluntary economic system with enough future workers and taxpayers. If a society’s real goal is simply to extract reproduction by force, then it has already stepped outside the world of incentives and into slavery, and economics can only describe the damage, not justify it.

NB 2: I’ve tried to make this as explanatory as I can, while still trying to not exasperate any passing economist.

Once, back in 2013, during an internship, I fainted at my desk from period pain. Luckily, I was seated, so my head just hit the table.

Nearly everyone who has ever menstruated has at least one horror story. Mine is relatively tame. Other people can tell you about bleeding through clothes, sitting examinations and meetings with cramps that feel like food poisoning, working full shifts in cramped factories without access to toilets, or being scolded for “unprofessionalism” because endometriosis made them miss a meeting. These stories are usually related as private misfortunes or personal failures of resilience. Economically, they are counted as nothing at all.

This is a mistake, and not just a moral one. It is a category error^{(a category error is when you count something in a category in which it does not belong, and therefore assign it characteristics it cannot possibly have)} in how we think about production.

What this essay argues is simple:

Menstruation, pregnancy, childbirth, childrearing, and menopause are not “women’s issues”. They are the long production process through which societies manufacture their future workers and taxpayers.
That production process is economic work. It creates an economic good called “children”, which becomes (economically) tomorrow’s labour supply, consumer base, and tax base.
The current system does two things at once: it underprices this work and then actively charges girls and women for doing it, via health risks, lost earnings, and literal taxes. Economically, that’s a textbook (negative) externality^{(an externality is when someone not part of a transaction receives a gain or bears a cost that results from it- a negative externality is when the cost is borne by the unrelated party)}: private cost, social benefit, underpriced input^{(the input here being women’s fertility)}. When you treat a crucial input as free, rational producers under‑produce it.

If you follow that logic all the way through, fainting at your desk and falling fertility rates turn out to be points on the same curve.

Menarche to menopause
We usually talk about “having a baby” as if fertility were a single event. Economically, that’s like describing “building a car” as the moment a finished vehicle rolls off the assembly line, and ignoring every step before it. Women’s fertility does not begin with pregnancy and it does not end at childbirth. It begins at menarche and runs to menopause, a multi‑decade production line that converts biological capacity into actual future people. Every part of that line has costs attached:

Menarche and menstruation: Once bleeding starts, there are monthly expenditures on pads, cups, tampons, painkillers, clinic visits, iron supplements. There are also missed school days when products or toilets are unavailable,¹ and missed work days when the pain or blood loss is severe.² None of this is optional if the body is going to remain capable of a healthy pregnancy later.
Fertility management³ ⁴ ⁵: Contraception, abortions, miscarriages, and their follow‑up care all consume time, money, and physical resilience. This is the work of deciding when and whether reproduction will happen, which any economist will recognise as intertemporal optimisation^{(which is when you try to balance how you use your resources through time, such as balancing current consumption/investment against future goals}⁶⁾ with a body on the line.
Pregnancy and childbirth⁷ ⁸: Nine months of metabolic and bodily strain, often accompanied by nausea, gestational diabetes, hypertension, and anaemia, followed by a physically risky delivery. Even a “normal” pregnancy can force women out of certain jobs; a complicated one can remove them from the labour force- or life- entirely. There is also the plain fear associated with birth women are often expected to not talk about, and metabolise without complaint.
Postpartum and childrearing⁹: Months or years of sleep deprivation, breastfeeding, carrying, cleaning, managing illness, making appointments, supervising homework, and often postpartum depression¹⁰ ¹¹. This is “reproductive labour”: the daily work that keeps children alive long enough to become workers. The opportunity cost is foregone wages, stalled promotions, career shifts into “flexible” but lower‑paid jobs.
Perimenopause and menopause¹² ¹³: Hot flashes, insomnia, brain fog, joint pain, and mood changes can all interfere with work, but very few workplaces account for this as anything other than an individual performance issue.

There is no such thing as “children” that exist independently of this long chain. Every future worker and taxpayer is embodied evidence that at least one person has paid these costs. That means children are not just sentimental “blessings”. They are an economic good. They are the raw material for what the textbooks call human capital: the future labour that will show up in productivity statistics and fiscal projections. No children, no labour supply. No labour supply, no GDP. It is that blunt.¹⁴ ¹⁵

What makes this category slippery is that children are not only an economic good in the narrow sense. They are also a source of private value: people have children because they want them, love them, and derive meaning, identity, and security from them. In economic terms, children are both consumption goods (privately valued by families) and investment goods (inputs into the future labour force and tax base).¹⁶ ¹⁷ For economically weaker people, children may even be an old-age insurance product.¹⁸ ¹⁹

Once you state this clearly, the next step is unavoidable: the work that produces and maintains this good (periods, pregnancies, childrearing) is economic work. It is as structurally necessary as work on an assembly line or in a software firm. The problem is not that markets ignore the private value- they do not. The problem is that the public value of the work associated with fertility is systematically underpriced²⁰ ²¹, while a large share of the costs remains private²² ²³.

The hidden invoice
In theory, if something is essential to production, we expect to see it priced, paid for, and protected. That is not how reproduction is treated.

Start with menstruation. For years, India taxed sanitary pads at 12% under GST²⁴, treating them closer to a semi‑luxury than to a basic need. Activism eventually pushed the rate to zero, but research from other countries suggests that when “tampon taxes” are removed, manufacturers and retailers often adjust prices so that the full benefit does not reach consumers.²⁵ ²⁶ In other words: even when the formal tax disappears, the underlying reality remains the same- periods are expensive, and the person bleeding pays.²⁷ ²⁸

The same logic runs through pregnancy and childbirth. In systems without universal coverage, antenatal check‑ups, diagnostic tests, delivery, and emergency care often come with substantial out‑of‑pocket bills.²⁹ ³⁰ ³¹ Even where public health care is nominally free, women pay with time spent queuing, with travel costs, with foregone daily wages.³² ³³ Nutrition during adolescence, pregnancy, and breastfeeding is a private line‑item in a household budget, not a public investment in the quality of the next generation.³⁴

Then there is the loss you cannot put on a receipt: days or years lost from school and work. Period pain and heavy bleeding are common reasons girls miss school, and lack of toilets or products turns discomfort into absence (“Period Poverty” is a real phrase that exists in our world). Women in manual or informal jobs such as factory lines, domestic work, agricultural labour, rarely have the option of calling in sick for their uterus.³⁵ ³⁶ They work through the pain, or they don’t work and lose pay, or they exit the labour market entirely.⁵

And then there are miscarriages. An estimated 23 million miscarriages occur every year worldwide, translating to roughly 44 pregnancy losses every minute.³⁷ In low- and middle-income countries like India, the risk is even more acute; longitudinal data from 2026 indicates a total pregnancy loss risk of approximately 103 per 1,000 pregnancies after the 8th week of gestation.³⁸ ³⁹ Economically, this represents a catastrophic failure, whose costs are nearly 100% borne by the mother.⁴⁰ ⁴¹

Also, in any other sector, a manufacturing defect or a workplace injury would be covered by insurance or a social safety net. In the reproductive economy, a miscarriage is treated as a private medical event. The woman or her family pay⁴² ⁴³ for the hospital stay, lost wages, nutritional requirement, product requirements, etc. while also experiencing psychological and physical pain.⁴⁴

All of this is the cost side of reproduction. It is spent in cash, in time, in health, in future earnings.

The benefit side is much more widely distributed. Everyone who relies on the future existence of workers and taxpayers gains: firms, governments, pension systems, future consumers. That is what makes this an externality.

In textbook microeconomics, when one economic agent bears costs that generate benefits for others who do not pay, markets underprice the activity.⁴⁵ That is what is happening here. The private cost of reproduction, like period products, health risks, lost earnings, is mostly borne by women and their families. The social benefit- a stable or growing population that can work, consume, and pay taxes, is captured by a large set of actors who are not paying the full bill.

Put differently, reproduction is a hybrid case. Part of the return accrues directly to the people raising the child. But a substantial share spills outward to employers, states, and future consumers who did not pay for the child’s upbringing. It is this gap, between private return and social return, that creates the distortion (that is, social benefit – private benefit = value of externality). The result is not that reproduction stops, but that it occurs under conditions of strain, inequality, and, increasingly, shortfall relative to what people say they actually want.

The logic is not mysterious; it is familiar. When polluters are allowed to dump waste into a river for free, they will pollute too much. Here, when the cost of producing the next generation is loaded onto one group while the payoff is spread across the entire economy, reproduction is pushed into the territory of “too costly to do safely, too necessary (or too desired) to abandon”.

The career penalty⁴⁶ ⁴⁷ ⁴⁸
Sometimes this is described as a “motherhood penalty”⁴⁹, as though it were an unfortunate bug in the system. It isn’t. It is the mechanism by which the externality is enforced and accounted for monetarily. Men also do unpaid work, and that matters, but this argument is specifically about reproductive labour such as menstruation, pregnancy, birth, breastfeeding-work that by biology cannot be split evenly, and the data on who takes the wage and pension hit from that work are not ambiguous.

Across many countries, women’s wages and employment trajectories look similar to men’s until the first child arrives.⁵⁰ ⁵¹ Then there are career interruptions for pregnancy and childbirth, reduced availability due to childcare, and discrimination, sometimes subtle, sometimes blatant. The outcome is lower annual wages, slower wage growth, and more part‑time or precarious work.

This does not stop at retirement. Smaller pay packets during working life mean smaller contributions to pensions and savings. Analyses from places like the UK repeatedly find that women’s pension pots are significantly smaller than men’s, with gaps widening in later life.⁵² ⁵³ The compounded effect over a lifetime is a pension gap and a wealth gap built directly on the scaffolding of reproductive labour.⁵⁴

Written as a flow: Fertility (menstruation, pregnancy, childbirth, childrearing, menopause)→ monetary costs, lost school and work days, career interruptions, lower hours, discrimination→ lower wages and slower wage growth→ smaller lifetime earnings→ smaller pensions and assets→ higher risk of old‑age poverty for the people who produced the next generation.

A point to make here is to wonder, if reproductive labour is underpriced, shouldn’t competition eventually push wages up to compensate? The answer is structural, not incidental. The primary beneficiaries of reproductive labour, such as future employers, the state, pension systems, future consumers, are not party to any wage negotiation with the woman currently pregnant. There is no contracting party on the other side of the transaction who could, even in theory, offer higher pay in exchange for the output. The wage market operates between a woman and her current employer, who captures only a small fraction of the lifetime value of the child she is raising. The failure cannot be corrected through wages because the people who owe the payment are not in the room.

(There is a similar issue in climate discussions too- the work put into climate change mitigation and adaptation will benefit future generations, and not current ones. It leaves climate workers to negotiate with people who often cannot see any benefit to curbing their lifestyles or doing the work required now to prevent further climate damage.)

Also, reproduction sits awkwardly between a private decision, an externality, and a quasi-public good⁵⁵ ⁵⁶^{(a product or service that everyone can use, cannot be stopped from using, and whose use by one person does not reduce its availability to others, like clean air- and here, the benefits of more children in an economy – because while a specific child or pregnancy is not a public good in that narrow sense, but: the fiscal and social benefits of children—taxes that fund pensions, schools, hospitals do have public‑good‑like characteristics: they are widely shared and hard to exclude people from}.⁵⁷⁾. Not to mention, households are not firms, and fertility decisions are not made with spreadsheets alone.⁵⁸ Preferences, norms, uncertainty, and identity all play a role.

But prices still matter. When the financial, physical, and career costs of having children rise, they interact with those preferences, often suppressing outcomes below stated intentions. This is visible in the persistent gap between desired and actual fertility across many countries: people report wanting more children than they end up having, and cite cost, job insecurity, and unequal care burdens as the reasons.⁵⁹ That is not a cultural mystery; it is a constrained choice.

The “motherhood penalty” is the accounting system writing down, in money, what the externality looks like at the household level.

The state’s revealed preference
There is another piece of this that rarely gets said: the state is not neutral in this arrangement. It has a revealed preference^{(instead of asking people what they like, you watch what they actually choose to have or do}⁶⁰⁾.

Consider what it would cost a government to assume direct responsibility for raising children: full public childcare from infancy, universal meals, clothing, schooling, health care, and the equivalent of parental time in trained staff. Nordic countries get closest to this, with extensive parental leave and heavily subsidised childcare, and even there, the state does not pay for everything.⁶¹ ⁶² ⁶³ Those programmes are expensive, and they work partially by recognising reproduction as a public good that must be financed collectively.⁶⁴

Whether by design or by constraint, the pattern elsewhere is consistent. Building a fully public system of childrearing, including comprehensive childcare, income support, and care infrastructure, would require high taxes and visible redistribution.⁶⁵ Most states stop well short of that point. The gap is not empty; it is filled inside households, largely by women’s unpaid or underpaid labour.⁶⁶ ⁶⁷ The result functions like a policy choice even when it is not explicitly framed as one: reproduction is treated as a privately financed activity with selectively socialised benefits.

The state’s preference for private financing of reproduction is also visible in how legal systems allocate parental responsibility. Across most jurisdictions, the costs of raising a child are quickly and firmly assigned to the household rather than shared with the broader beneficiaries (employers, pension funds, the state itself).⁶⁸ ⁶⁹ ⁷⁰ ⁷¹ Whatever the stated rationale in any individual jurisdiction, the pattern is widespread and its economic consequence is clear: the state acts to avoid becoming the payer of last resort for reproduction.

The state’s revealed preference is clear: enjoy the tax revenue, avoid the childrearing bill.

From tampon tax to hysterectomy⁷² ⁷³ ⁷⁴ ⁷⁵
At one end of this spectrum are policies that make reproduction incrementally more expensive: a tax on period products, the period products themselves being expensive, no sick leave for period pain, no maternity protection in informal work. At the other end are policies and labour regimes that make reproduction incompatible with survival.

In the sugarcane fields of Maharashtra, the externality stops being metaphorical and becomes surgical. Reports from Beed district, one of the poorest in India, document that thousands of women sugarcane cutters have undergone hysterectomies in their 20s and 30s, not because of health requirements, but because their work contracts and poverty made menstruation and pregnancy intolerable risks. Sugarcane cutting is backbreaking seasonal work. Couples are hired together, paid by the ton of cane they deliver. Missing a day for period pain, for heavy bleeding, for pregnancy complications, can mean fines of 500 to 1,000 rupees, often more than the day’s wage. For families already living on the edge, a week of lost income can mean debt or hunger. In that context, hysterectomy can be seen as a “solution”. Government and academic studies have found hysterectomy rates in Beed many times higher than the national average, concentrated among women who cut cane.

The line from a tax on menstrual products to mass hysterectomies is not a single mechanism, and it would be wrong to treat it as one. What links them is not identical policy design but a common direction of pressure: making the biological realities of reproduction economically costly to bear. At one end, that cost is marginal and dispersed^(marginal⁷⁶^{and dispersed}⁷⁷^{– in economics, “marginal” means additional, the cost of menstrual products is a marginal cost attached to each extra individual and each extra period, and dispersed- smaller spread out costs borne by the women or their families)}. At the other, it becomes so acute that removing the capacity to menstruate is treated as a form of labour discipline, and sometimes the only viable option when the other is chronic hunger.

From a cold economic perspective, what is happening in Beed is this: the labour market is sending a price signal^{(a price signal is information carried by prices that tells people how to behave in a market, so, for example, when price goes up, it signals that something is more in demand}⁷⁸⁾ that a menstruating, potentially pregnant body is too expensive. Removing the uterus reduces downtime. It also removes any future pregnancies and imposes long‑term health risks. But those future cost to the woman’s body and to her family’s fertility are not priced into the immediate wage contract. They are written off as collateral damage.

At one end of this spectrum, you are asked to pay a little extra for bleeding. At the other, you are asked to give up the organ that bleeds so you can keep your job.

The other hand
Now flip to another corner of the world. Nordic welfare states are often held up, as good places to be a mother.⁷⁹ The details matter, because they spell out what it looks like when a state tries, to internalise some of the externality. Countries like Sweden, Norway, Denmark, Finland, and Iceland combine relatively high female employment with generous, earnings‑linked parental leave, job protection, and heavily subsidised childcare. Parents can take months of leave without losing their jobs; part of the leave is reserved for fathers to push men into the care side. Places in public daycare are widely available, and fees are capped or heavily subsidised.

Demographic research links these policies with two outcomes.

First, they raise mothers’ labour force participation and reduce the lifetime earnings penalty of having children.⁸⁰
Second, they are associated with higher and more stable fertility than in otherwise similar rich countries with weak family support; parents, especially mothers, are more likely to go on to have a second or third child when they can expect support and re‑entry into the work they want to do.⁸¹ ⁸²

What the Nordics are doing, in economic terms, is straightforward: they are socialising a slice of the cost of reproduction⁸³, and they are forcing men and employers to bear some of it.⁸⁴ Taxes are higher. Public spending is higher. The state writes cheques for a part of the reproductive bill rather than assuming that women will quietly pay it in unpaid hours and lost earnings. The Beed sugarcane worker and the Swedish software engineer inhabit different universes. One is asked to remove her uterus to remain employable. The other is given months of paid leave and a daycare place to remain employable. Between them lies the full spectrum of how an economy can choose to treat an input it depends on.

What the Nordic model does not resolve is also instructive. Even in Sweden and Finland, women still perform more unpaid care work than men⁸⁵ ⁸⁶, the pension gap persists⁸⁷, and fertility has continued to drift downward despite extensive state support⁸⁸. The partial correction produces a partial result.⁸⁹ This is not a failure of the Nordic model, it’s just that the distortion has not been fully priced out; it has been partially offset- and that personal preferences still apply to such decisions. To be noted, while India and the Nordics are not comparable economic systems, the contrasting realities reveal the range of how costs can be distributed.

What would correct pricing look like?
If this is a pricing problem, then the outline of a solution is not mysterious. Internalising the externality would mean shifting a larger share of the cost of reproduction onto the same broad base that captures its benefits. In practice, that implies some mix of publicly financed reproductive healthcare, income support around childbirth, accessible childcare, and labour market structures that do not permanently penalise time spent raising children. The details vary by country, but the principle is simple: when an activity generates wide social returns, its costs cannot be left almost entirely to the individuals performing it without distorting the outcome. This is not about charity for parents; it is about paying for the labour that keeps the system supplied with workers and taxpayers.

Rational collapse
This is where the externality argument completes its arc. We have an input (reproductive labour from menarche to menopause) that is essential to producing an economic good (children, i.e., future labour and taxpayers). We systematically underprice that input by treating most of the work as unpaid and most of the costs as “personal”. We then occasionally add explicit charges (taxes on menstrual products, unpaid maternity leave, fines for missed days) for good measure.

On the other side, we have beneficiaries: firms that rely on a steady supply of labour they did not pay to raise; states that rely on a steady supply of taxpayers and soldiers; pension systems that rely on young workers’ contributions; men whose own employment and pensions ride on someone else staying home with the kids (in fact, fathers often reap economic benefits from becoming fathers, the opposite of what happens to mothers⁹⁰ ⁹¹– even though they have not borne the physical and general career costs of reproduction). They capture the benefit of reproduction without bearing its full cost.

When the cost of producing children is high and rising, and the private return for the producer is lower than the social return, the aggregate result is under‑investment in reproduction (meaning people choose to have fewer kids). The UN and demographers are already documenting that people in many countries say they want more children than they end up having, citing the cost of living, insecure jobs, and unequal domestic labour as reasons. That gap between desired and actual fertility is the shadow of the externality. It’s the quantity response to cost under constraint (that is, the quantity produced is limited because resources are scarce).

A common counterargument holds that falling fertility is simply the consequence of rising female education and autonomy- that women with better options are rationally choosing smaller families, and that this is a success story, not a market failure. Yes. More education and autonomy for women are unambiguously good. In economic terms, though, they also raise the opportunity cost of childbearing: the better a woman’s career prospects, the more she stands to lose from stepping back for pregnancy and childcare. When women have better careers, the cost of interrupting those careers rises.⁹²That makes the pricing problem worse, not better. A higher opportunity cost with the same absent compensation means the gap between what it costs to have children and what you receive for having them grows wider.

Falling fertility rates are often described as a cultural crisis: young people are selfish; women are too educated; nobody wants families anymore. That story is tidy, and wrong. It treats the collapse in output as a moral failure instead of as a predictable response to a price signal.

However, when an essential input is persistently underpriced, economists do not reach for moral explanations. They look for who is paying, who is free‑riding, and how incentives are misaligned. Reproduction is no different. The difficulty is not that the logic is obscure. It is that applying it requires admitting that a large share of the economy has been quietly subsidised by work that is unpaid, underpaid, and treated as natural.

Falling fertility is not a just a ‘lifestyle choice’ (it can be for some people, it is just not that for everyone); it is the market finally reflecting the fact that the producers can no longer afford to subsidize the rest of the world’s ‘free’ labor supply. The fertility bill has come due.

Sources

Risk – IX: Microlives to Micromorts, or why risk makes so little sense

The previous posts in this series examined how risk operates in energy markets, social systems, national security, and military infrastructure. This one asks why do humans fail to act on risks we can measure, price, and see coming?

I was once trying to explain risk as a concept to my students, and to demonstrate it, confidently asked- okay, would you sky dive? Because reader, I would not throw myself out of a plane. I had forgotten there was an army officer in that class, who stuck a pin to my example by casually answering yes. Yes he would indeed jump out of an airplane, no problem Ma’am.

We were both being entirely rational too, and that is the problem with communicating risk to humans. Everyone perceives risk through the sieve of their lives and personalities. We are surrounded by risk data. We have extraordinarily sophisticated tools to measure, price, and manage some types of risk. And yet, individually and collectively, we routinely ignore the risks that will actually kill us, panic about risks that likely won’t, and remain completely unmoved by risks that threaten the existence of life on our beautiful space rock.

Units
Risk resists measurement. Therefore, it naturally repels measurement units.

We tried anyway.

Ronald Howard, a Stanford engineer, created a unit called micromort in 1989: a unit equal to a one-in-a-million chance of death.¹ The prefix is simply the metric micro-, which means one millionth attached to the word mortality. One micromort is a tiny, almost abstract sliver of the possibility of dying. But the power of the unit is in comparison. So, riding a motorcycle for 9 kilometres costs 1 micromort (UK data)¹, running a marathon costs about 7 micromorts, and skydiving once– just one more micromort at 8². Climbing the Everest: somewhere in the region of 37,000 micromorts, which means your odds of dying even on a successful ascent are roughly 1 in 27.³ ⁴ The numbers are drawn from epidemiological ^{(relating to the study of how diseases spread, who gets sick, and why, within a specific population}⁵⁾data, which just means that you take the population who did an activity, count deaths, and divide. They are approximations, not laws, and they vary by country, era, age, and fitness. But it’s something concrete. Certainly I wouldn’t have thought my aversion to falling would be comparable to my aversion to running.

The second was David Spiegelhalter, Cambridge statistician who invented Microlives in 2012.⁶ One microlife is half an hour of life expectancy, derived by dividing a roughly 57-year adult lifespan into one million equal parts. Every microlife you spend is thirty minutes of your future, gone. It measures the relationship between an individual’s habits and their lifespan, so the daily choices they make and how long they are likely to live.⁷ Longitudinal studies (the kind that follow the same person over many years) have found that watching an extra hour of television is akin to burning up half a microlife, but smoking two cigarettes equals two. You can earn two back with twenty minutes of moderate exercise though.⁸

A micromort measures acute risk. The word “acute” comes from the Latin acutus, meaning sharp, or sudden. A discrete^{(the statistical word meaning single, or individual}⁹⁾ event with a clear before and after: you jump out of the plane, or you don’t. A microlife measures chronic risk, from the Greek chronos, meaning time. Slow, accumulating, invisible, with no clean moment of crisis.⁶

Mathematics says that for someone in their late twenties with roughly one million half-hours of adult life ahead of them, one micromort of acute risk is almost exactly equal to one microlife, or thirty minutes of expected life.¹⁰

Actuaries
There is, unsurprisingly, an entire profession built around calculating risk.¹¹ These people are called actuaries, and they calculate the probability of death or loss across different groups, and price it. They usually work for insurance companies.¹²

Actuarial science establishes something important: risk that is chaotic at the individual level becomes orderly at scale.¹³ No actuary can tell you whether you will die this year. But they can tell you, with considerable confidence, what percentage of a million people like you will. This is why, when you try to buy term insurance in India, you are asked about tobacco use, your pin code, your gender, your profession, your income- so that a calculation can be made about how likely someone like you is to die soon.¹⁴

This is called risk pooling.¹⁵ Insurance companies accumulate risk from many people because they know the chances of all insured events occurring simultaneously are vanishingly small. It is why premiums are lower for younger people- not because the young are invincible, but because the numbers say they are less likely to die right now than someone older.¹⁶

However, while the mathematics works, it is meant for populations. You are not a population. You are a person. And people are usually terrible at thinking about risk.

Risk Perception
A few years ago, before my life lost its plot, I went to Goa. I’m afraid of heights, so I decided to go parasailing- because I was so afraid of it, but also because I knew the instructor would be up there with me. I was terrified all the way up and while I was in the air, but while descending, I started to enjoy myself. So I went up a second time, and enjoyed that entire redo much more.

I was reminded of this recently when I came across a podcast where a Para SF veteran described the moment of hesitation at the gate before his first jump- not fear exactly, but his rational mind asking: why am I doing this?

Two people, two completely different risk profiles, the same pause. The same risk perception.

The difference between this person and me wasn’t in the physics of the fall. Gravity is an equaliser. The difference lay in the “internal weighting” we gave to the danger. To the officer, the risk was a managed variable, mitigated by years of training and a parachute he knew how to use. To me, the risk was an existential threat, unmitigated and visceral. We weren’t looking at the same event; we were looking at two different versions of the future, shaped by our pasts.

This gap between risk as it exists mathematically and risk as it lives in the human mind has a name in behavioural economics: cognitive bias. There are several that are particularly relevant to risk, and between them they explain most of the grand collective failures that follow. Here’s a short list:

The first is the affect heuristic¹⁷: we judge risk by how something feels, not by its actual probability.
The second is availability bias¹⁸: we judge how likely something is by how easily we can recall an example.
The third, and the most important for what comes next in this article, is psychic numbing¹⁹: The psychologist Paul Slovic spent decades documenting a deeply uncomfortable finding: human compassion and concern do not scale with numbers. We feel genuine, mobilising distress for one identified person in danger. As the numbers grow from ten people, to a hundred, then a million, emotional engagement does not grow with them. It collapses. “The more who die, the less we care,” is how Slovic summarises it.
And the fourth is temporal discounting²⁰: we systematically undervalue future outcomes relative to present ones. A certain reward today is worth more to us than a larger reward next year.

Between 7.1 – 33 Million Dead²¹
These are the people we lost to the pandemic.

Official confirmed deaths from COVID-19 stand at approximately 7.1 million, as recorded by the WHO. Excess mortality estimates (the gap between how many people died and how many would have died anyway) put the real figure somewhere between 14.9 million and 33 million.²² ²³

COVID-19 was, for a large part of the global population, the first time in living memory that ordinary people walked around consciously calculating their own mortality risk. It did not make us more rational. It made us more anxious.²⁴

Research published during and after the pandemic found that prolonged exposure to mortality risk increased temporal discounting²⁴, the bias that makes us prioritise the present over the future. People under pandemic stress didn’t become careful, long-term thinkers- they became more impulsive, more present-focused, more likely to reach for the immediate reward over the future benefit. One study found that greater temporal discounting directly predicted lower compliance with masks and social distancing, the behaviours that would actually reduce risk.²⁵

Psychic numbing compounded this.²⁶ In the early weeks, when COVID deaths were in the hundreds, there was genuine grief, and that specific terror of the unknown. By the time the death tolls reached hundreds of thousands, then millions, our emotional machinery had largely switched off, because our brains cannot hold a million deaths the way they holds one. The numbers became, in Slovic’s phrase, mere statistics.¹⁹

The pandemic taught us something important and uncomfortable: mass risk awareness does not produce mass rational behaviour. It produces mass emotional behaviour- fear, denial, exhaustion, and the very human tendency to make the anxiety stop by pretending, at some level, that the threat is not quite as real as the numbers say. We had all the data. We had the micromort equivalent of a daily death budget displayed on every news channel in the world. And we still, collectively, could not think clearly about it.

Now consider what happens when the risk is neither immediate, nor personal, and communicated about constantly using statistics and numbers.

Our Beautiful Space Rock
Climate change is risk that has been engineered, almost perfectly, to defeat every cognitive tool we have. It is chronic, not acute- there is no single moment of crisis, just accumulation. It is global in scale and feels distant even when it isn’t.²⁷ It is statistical, not personal, because it kills in aggregates, not with faces.²⁸ Its worst consequences arrive in timelines beyond our natural planning horizon.²⁹ And it requires collective action at precisely the moment when individuals are most inclined to discount, deny, and defer.³⁰

To this, add that people often believe that weather is made by the gods, which means both- that we are unable to interfere with it (so no anthropogenic climate change)³⁰ ³¹ ³², and that anything we do is also going to be useless- because it is god’s wish for it to be so³³. To this worldview, even if climate were changing, the right response would be to accept it, because it cannot be changed by humans.

This is the central tragedy of climate risk communication. Climate communication has, for the most part, been built for spreadsheets, not for minds. It relies on scale, statistics, and long timelines- exactly the conditions under which human intuition fails. We communicate climate risk in parts per million, degrees of warming, and deaths by the million, and then wonder why it does not move behaviour.³⁴

Climate change is not just an environmental problem. It is a risk communication problem- more specifically, a chronic risk problem. It is literally a million and one small events all over the planet cascading into one big final boss problem.

Solutions
Here is how I would tackle this problem:

Localise the risk: People respond to risks they have seen, or can imagine happening to people like them. Climate communication that begins at the global level fails; communication that begins with lived, local experience has a chance. In India at least, many communities have experienced climate-origin loss. Start there. Explain climate change to them through their own frame of reference.
Shorten the time horizon: As long as climate change is framed as a 2050 or 2100 problem, it will be systematically deprioritised. Communication that highlights present-day impacts such as heatwaves, air quality, food prices aligns with how we actually make decisions.
Use social proof, not just data: Behaviour is contagious. If we are able to change what one person does, especially someone influential in the community, the rest of the community are more likely to follow. Community-level interventions, whether it is water management, crop choices, or energy use, scale because they are visible, repeatable, and socially reinforced.
Understand that only agency beats risk: People do not act on risks they feel powerless to change. Effective communication pairs risk with action which is specific, achievable, and immediate.

None of this is sufficient. The scale of the problem dwarfs every communication strategy we have. But the alternative- continuing to recite statistics into the void and wondering why nothing changes- is not working either.

I was able to overcome my fear of heights, however briefly, only because I felt empowered to do it, had the means to do it, had the right guidance in the parasailing instructor, and felt motivated about it.

These are inherently human traits.

Those conditions- agency, means, guidance, motivation, are the same conditions under which people act on any risk. And they are exactly what is missing from most climate communication.

Climate risk is the ultimate jump. It is a “god-sized” problem, yes, but it is one that will be solved in the very human terrain of local communities, social proof, and individual agency. We have to stop treating people like calculators that have failed a maths test and start treating them like the both the army officers in this post: individuals who can face immense risk, provided they have a mission, a team, and a plan.

Sources

Risk – VIII: A Hidden Vulnerability- Civilian Infrastructure in War

In October 2023, Sikkim suffered a Glacial Lake Outburst Flood (GLOF)¹, which means that the Teesta River surged after the South Lhonak glacial lake burst, destroying the Chungthang dam, sweeping away 11 bridges, damaging NH-10² ³, and disrupting mobile coverage across northern Sikkim.⁴ Rescue operations were immediately hampered because road access, communications, and power failed at the same time. The government’s own situation reports noted that teams from multiple ministries had to be deployed simultaneously because all three systems had gone down together.⁵ Twenty-three Army personnel were among the missing.⁶ ⁷

In my previous post, I explored how climate change was affecting India’s national security with a broad brush, but while doing this I realised that civilian infrastructure is also, often, military infrastructure. And as everyone knows, India’s well known for the upkeep of her civilian infrastructure, and mild climate, so this post was born.

Systemic failure cascading through civil infrastructure is a danger to Indians and to India’s national security.

What Is Happening
Climate can damage infrastructure in two ways:

Disaster events, which are sudden unforeseen shocks, or the more mundane,
Daily stress due to newer ambient conditions, that among other impacts also compresses the window between maintenance cycles.

The former is usually visible, localised, and patched up through specially sanctioned money.

The Science

Chemistry
Most infrastructure is built from steel and concrete. Climate change affects both through several chemical processes.

Corrosion is the oxidation of steel, which is the process that produces rust. It is driven by a reaction that speeds up as temperature and humidity increase.⁸ Higher ambient temperatures and higher humidity therefore accelerate the corrosion of exposed steel and of steel reinforcement bars inside concrete.⁹ Studies have found that this reduces structural resistance and threatens the safety of buildings and infrastructure.¹⁰ ¹¹
For India’s coastal infrastructure, corrosion is intensified by chlorides from seawater and sea spray. Chloride ions penetrate concrete and break down the protective chemical layer on the steel reinforcement inside it.¹² Once that protective layer is lost, corrosion accelerates. As sea levels rise and storm surges push saltwater further inland, more structures are exposed to chloride-rich conditions than they were originally designed for.¹³ ¹⁴
Carbonation is another process affecting concrete.¹⁵ Carbon dioxide from the atmosphere reacts with calcium hydroxide in concrete, gradually lowering the concrete’s alkalinity. Concrete normally protects embedded steel because its high alkalinity creates a passive film on the rebar. When carbonation reduces that alkalinity, the steel loses that protection and becomes vulnerable to corrosion. Research suggests that under climate change, carbonation can advance much further than expected over a structure’s lifetime, potentially causing corrosion-related failure 15 to 20 years earlier than expected.

Physics
Climate change also affects infrastructure through physical processes.

Materials such as steel, concrete, and asphalt expand when heated and contract when cooled through a process called thermal expansion. Roads, bridges, and railway lines are designed with this in mind, using expansion joints and stress tolerances based on the historical temperature range of the area.¹⁶ When temperatures exceed those historical ranges more often, the materials expand more than expected. This can cause bridge cracking, road deformation, and rail distortion. India’s National Disaster Management Authority identifies all of these as current extreme heat risks.¹⁷
Thermal cycling fatigue is when repeated expansion and contraction over months and years creates cumulative mechanical stress.¹⁸ Tiny cracks form, widen, and eventually reduce the strength of the structure.¹⁹ This is especially important in regions with large temperature swings, including mountain areas where freeze-thaw and heat-cold cycles can be intense.²⁰
Freeze-thaw damage is a physical mechanism relevant to Himalayan infrastructure. Water enters small cracks in concrete or rock-supported structures.²¹ When it freezes, it expands and exerts pressure on the surrounding material.²² Repeated freeze-thaw cycles gradually widen cracks and weaken the structure. Roads, retaining walls, bridges, and tunnels in mountain zones are especially vulnerable to this.²³
Electrical infrastructure is also affected by basic physics. Transmission lines sag more in high heat because the metal expands.²⁴ ²⁵ Transformers and cables become less efficient as ambient temperature rises and can operate closer to their thermal limits for longer periods.²⁶ This reduces efficiency and can shorten equipment lifespan for equipment rated for a maximum ambient of 40°C, a threshold India’s plains now routinely exceed.²⁷
The troposphere, which is the lowest layer of the atmosphere, is getting wetter and more turbulent as climate change increases evaporation and convective activity.²⁸ ²⁹ Water vapour absorbs and scatters microwave signals. This creates what’s called tropospheric delay so that signals from GPS and navigation satellites arrive slightly later than they should because they’re passing through a more moisture-loaded atmosphere.³⁰ For civilian navigation this is a minor annoyance. For precision-guided systems, artillery corrections, or drone navigation that depend on GPS accuracy, accumulated error matters.³¹
Heavier rainfall also causes direct signal attenuation for satellites operating in the Ku and Ka frequency bands³², which are commonly used for broadband and military communications satellites³³. During intense monsoon rain events, which are becoming more intense, the signal can degrade significantly.³⁴ This is called rain fade.³⁵ Climate change is making extreme rainfall events more frequent, which means rain fade events are also more frequent.³⁶

Biology
Climate change changes biological conditions in ways that matter for infrastructure.

Mold and fungal growth increase when warm temperatures combine with moisture and poor ventilation. More humid conditions, heavier rainfall, and more water intrusion into buildings create better conditions for mold on and inside building materials. Mold does not usually collapse a bridge, but it does damage internal building materials, coatings, insulation, sealants, and indoor air quality, and it increases maintenance burdens in buildings.³⁷ The US Army Corps of Engineers identifies hot, humid conditions and climate-linked flooding as important drivers of mold risk in buildings.³⁸ ³⁹
Termites are another biological stressor. Research has found that termite decomposition activity increases sharply with temperature, with one study reporting an almost sevenfold increase for every 10°C increase in temperature.⁴⁰ Warmer conditions can lengthen termite active seasons and expand their range.⁴¹ In India, where termites are already a major issue in many regions, this can increase damage to wooden structures, fittings, and stored materials.⁴²
However, the most important biological effect may be on people, specifically the people who inspect, repair, and maintain infrastructure. Outdoor workers face direct heat stress. Studies from India show that high heat impairs hydration, reaction time, and cognitive performance, and reduces labour productivity.⁴³ One study found heat stress was associated with impaired cognitive function among outdoor workers in northeast India.⁴⁴ Another found significant productivity losses under high heat conditions in southern India.⁴⁵ Broader modelling suggests work performance in India could decline by 30-40% by the end of the century under high-emissions scenarios because of heat stress.⁴⁶ This matters because infrastructure maintenance is done by human beings. If workers can safely spend fewer hours outdoors, inspections are delayed, repairs take longer, and maintenance backlogs grow.

Why This Matters

Think of a bridge. It’s close to the Western front, but maybe somewhere hot rather than cold. Our troops and civilians use it. When war happens, it risks becoming a chokepoint. This is what climate change is doing to that bridge:

Chemistry

Atmospheric CO₂ rises → carbonation front advances through concrete → alkalinity drops → passive film on rebar breaks down
Simultaneously: Monsoon rainfall carries agricultural fertiliser runoff into the river→ sulfates and chlorides enter river water → they penetrate the concrete of bridge piers standing in the river → chloride ions attack rebar from below while carbonation attacks from above
All of this converges in the same steel. Corrosion begins. The steel expands as it rusts, cracking the concrete around it from the inside. The cracks then let in more water and more chlorides. The process accelerates itself.

Physics

Summer temperatures exceed original design range → expansion joints in the bridge deck are stressed beyond tolerance → micro-cracking at joints
Winter cold → contraction → same joints stressed in the other direction
This thermal cycling repeats every year → cumulative fatigue damage accumulates in the deck and in the connections between the superstructure and the piers
Monsoon floods → river scour around the bridge foundations → soil removed from around pier bases → foundations become more exposed, less supported
The cracks from thermal fatigue now provide entry points for the chloride-rich floodwater. The chemical and physical tracks have merged.

Biology

Heat + humidity + monsoon moisture → mold grows on bearing pads, sealants, and expansion joint filler → these materials degrade faster than designed
Summer wet-bulb temperatures rise → outdoor workers hit safe heat limits earlier in the day → inspection teams spend fewer hours on the bridge → the cracking goes unlogged for longer.
Maintenance is scheduled based on the old assumption of X inspections per year. The bridge now needs X+2. It might get X-1.

The military uses the national grid, national highways, ports, telecom networks, and fuel systems because these already exist at national scale.⁴⁷ Building separate military-only versions of all of them would be costly and, in many cases, impractical.⁴⁸

In forward areas, large fixed installations like wind turbines or solar arrays are visible on satellite imagery and can mark out military positions, a very obvious security liability.

There is also a wider internal security reason for treating civilian infrastructure as a national security issue: power failures, water shortages, and infrastructure breakdowns can contribute to unrest and instability. India has already seen public disorder linked to extended power cuts and water disruptions.⁴⁹ ⁵⁰

This means the military will continue to depend on civilian infrastructure in most cases. As a result, strengthening civilian infrastructure is not separate from strengthening national defence.

Each issue discussed in this post is treated in planning as a separate system with separate vulnerabilities. The problem is that they are not experienced separately.

They fail together.

India has a Ministry of Power, a Ministry of Jal Shakti, a Department of Telecommunications, a Ministry of Petroleum and Natural Gas, a Department of Space, and a Ministry of Road Transport and Highways. Each has its own climate resilience concerns, its own planning horizon, and its own budget. What India does not have is any institution whose job it is to look at all of these physical risks simultaneously and ask what their combined failure would cost during war, or during a 26/11-style attack.⁵¹ ⁵²

The cascade matters because the response to any single infrastructure failure can usually be managed: reroute the convoy, use the satellite phone, run the generator. It is when several failures occur in the same region simultaneously that the workarounds stop working. In a conflict scenario, an adversary that understands India’s infrastructure dependencies does not need to attack each system individually.⁵³ A weather event that the adversary did not cause, hitting infrastructure that climate change has already weakened, can achieve the same effect at no cost.⁵⁴ The Sikkim GLOF was not engineered. But the military vulnerability it exposed- an entire strategically sensitive zone simultaneously cut off by road, by communication, and by power- is exactly the condition a competent adversary would try to manufacture.

Sources

Risk – VII: Climate Change and India’s National Security Emergency

NB: I don’t know anything about national security. I’m a climate person now exploring risk and this seems… obvious. This is the toughest thing I’ve ever written.

Siachen is the world’s highest active battlefield, at approximately 6,300 metres above sea level in the eastern Karakoram range.¹ During a complete ceasefire between 2013 and March 2016, 41 soldiers still died there. This is what the glacier costs India in peacetime.²

Now the glacier is melting.

what is climate change
Over time, the atmosphere of our planet has been composed of different material. How much heat is retained by the planet is determined in part by this. If the atmosphere has more greenhouse gases, it will lead to a hotter planet, which leads to cascading effects.

Example: As temperatures rise, glaciers and polar ice sheets melt causing sea levels to rise and threatening to inundate coastal cities, erode coastlines, and displace millions of people. Concurrently, this warming disturbs weather patterns, resulting in more intense heatwaves, devastating droughts, and stronger, more destructive storms and floods. These physical disruptions destroy ecosystems and agricultural productivity, creating severe food and water shortages, while simultaneously expanding the range of pests and diseases that endanger human health. Ultimately, these interconnected hazards damage critical infrastructure, destabilise economies, and heighten the risk of mass migration, poverty, and conflict over declining natural resources.

What are India’s prevalent national security issues
From what I understand, our main national security issues are external aggression, terrorism, and militancy.

Threat multiplier³ ⁴
Climate change doesn’t create new conflicts. It takes every single problem in the list above, such as water, food, borders, internal stability, regional rivalry, and makes it harder to manage, more frequent, and more explosive through resource stress. For example, it tightens the supply of water and food, which increases competition for both, which drives displacement, which destabilises borders and communities, which creates the conditions in which existing conflicts (ethnic, political, territorial) escalate. A drought isn’t just an agricultural event. It is, potentially, a political one, which can always make it a military one too.

Let’s explore how:

I. Internal Security

1. Water
India is the 13th most water-stressed country in the world⁵, and climate-change-driven precipitation changes are projected to worsen this dramatically, with more rain falls in violent bursts, and the moderate, sustained rainfall that actually recharges groundwater becoming rarer⁶. A 2024 peer-reviewed study in AGU Geophysical Research Letters found that monsoon drying combined with winter warming has already caused massive groundwater loss between 2002 and 2021- and that this trend will worsen as irrigation demand rises and recharge declines.⁷ A 2018 Niti Aayog report found that states performing poorly on the water index are home to about 40% of India’s population and account for 40% of its agricultural output, creating a cascading risk for food and economic security.⁸ By 2050, the water crisis is projected to cost India nearly 6% of its GDP.⁹

Similarly, communal tensions in water-stressed regions are increasingly animated by resource competition.¹⁰ As river flows decline and groundwater depletes, communities that share or contest watersheds become sites of conflict.¹¹ The state-level Cauvery riots are a visible example; but beneath the surface, a growing number of smaller, less-reported water conflicts are simmering across India, and their frequency is directly tied to climate variability.

The Cauvery water dispute between Tamil Nadu and Karnataka is a preview of what’s coming. The 2016 riots¹², triggered in large part by what was the worst drought Tamil Nadu had experienced in 140 years¹³, left people dead, millions of rupees in damages, and required significant law enforcement mobilisation. While water disputes between Indian states date back to the colonial era, climate change is ratcheting up the intensity by making droughts more frequent and more severe. he Water, Peace and Security (WPS) partnership’s conflict early-warning tool, which uses machine learning across 15–20 indicators and claims 86% accuracy, has consistently flagged large parts of India and Pakistan as high-risk zones for water-driven conflict.¹⁴

2. Heat
Famously, at the moment the world’s 95 hottest cities are in India¹⁵, rompting Redditors to calculate that you’d need 4.3 million ten-metre tunnels — stacked eighteen rows high across the entire mountain range, ideally with RGB lighting — to reduce India’s temperature by 5°C ^{(Favourite comment: “Would it not be easier to just raise India? Put it on some tire jacks or something? Pixar’s Up but with India maybe?”}¹⁶⁾.¹⁷ ¹⁸

This has an internal security dimension that rarely gets discussed: heat is an economic catastrophe. India’s agricultural workforce, which still constitutes roughly 46%¹⁹ of total employment, is almost entirely outdoor and informal. When a heat event destroys a harvest, it doesn’t just create hunger. It destroys livelihoods, triggers distress migration into already-strained cities, and adds pressure to communities where other tensions already exist.²⁰

3. Food Security
India feeds 1.4 billion people largely through rain-fed agriculture- and rain-fed agriculture accounts for 60%²¹ ²² of all cultivated land in India. This is the singular vulnerability that makes climate change so existential: a disruption of the monsoon is a disruption of the nation’s food supply. And that disruption is already underway.

Erratic rainfall, increased droughts, and more intense floods are reducing crop yields, pushing up food prices, and deepening malnutrition, particularly among the most marginalised communities. Staple crops are losing nutrients as rising CO₂ speeds up photosynthesis while reducing protein and mineral content.²³ Lower yields lead to food scarcity, which leads to price spikes, which lead to social unrest, which is a feedback loop that historically has destabilised governments and ignited conflicts. The most recent example is the Syrian civil war, which multiple studies have linked to a catastrophic 2007-2010 drought that drove 1.5 million Syrian farmers into cities.²⁴

4. Disease
Climate change expands both the geographic range and the seasonal window of vector-borne diseases such as malaria, dengue, chikungunya, and others, by making previously inhospitable environments hospitable to the mosquitoes that carry them.²⁵ As temperatures rise, these mosquitoes move to higher altitudes and higher latitudes: places that were, until recently, simply too cold for them to survive and reproduce year-round.²⁶

This matters for India’s security because the Indian Army already manages significant morbidity from malaria in its northeastern and jungle deployments.²⁷ ²⁸ The Northeast is already one of the most malaria-endemic regions in the country, and it is also one of the most militarily active, with ongoing counterinsurgency operations across Manipur, Nagaland, and Arunachal Pradesh (during World War II in Manipur and Nagaland, malaria casualties far exceeded those from Japanese aggression)²⁹. Climate change will extend both the altitude and the season of that disease burden, moving it upward into Himalayan deployment zones that were previously disease-free, and lengthening the transmission window in zones that already carry it.³⁰

5. Migration
Between 2015 and 2024, 32.32 million people were internally displaced in India due to natural disasters (mostly floods and storms).³¹ In 2024 alone, the figure was 5.4 million: the highest single-year displacement in over a decade.³² Nearly half of those 5.4 million were in Assam, which experienced its most intense floods in more than a decade.³³ Cyclone Dana, which tore through Odisha and West Bengal in October 2024, added another million on top of that.³⁴ The World Bank projects that South Asia could see up to 40 million internal climate migrants by 2050 in a worst-case scenario.³⁵

So where are our people moving? Cities, it seems. This means that people are fleeing climate-stressed rural areas and moving into climate-stressed cities.³⁶ The downstream effects are predictable: “expanding informal settlements, rising unemployment, worsening public health, increased competition for water and space, and communities under pressure in the exact ways that historically precede unrest.”³⁷ Research on climate-induced displacement in India found that discrimination, violence, and the lack of basic amenities in urban areas meant that migrants who arrived seeking economic survival found themselves in conditions of compounded vulnerability.³⁸

Distress migration does not produce stable, integrated urban populations. It produces large numbers of people with very little to lose.

And the thing to note here is that security issues like insurgency and climate change share a common engine: desperation- witnessed as the regions most vulnerable to rainfall variability often overlapping with areas prone to Left-Wing Extremism (LWE).³⁹ ⁴⁰ As climate change degrades agricultural livelihoods and forces displacement, it provides fertile recruiting ground for insurgent movements that thrive on grievance.⁴¹ The relief web analysis on India and climate security explicitly highlights how climate change’s adverse interaction with insurgencies could “create or exacerbate national security threats” across multiple domains.⁴²

II. External Security

1. Water
China is building what will be the largest hydroelectric dams in human history on the Yarlung Tsangpo (Brahmaputra) river in Tibet, near Arunachal Pradesh.⁴³ This dam, alongside several others upstream, would give China enormous water storage capacity and the ability to control the flow of the Brahmaputra into India’s northeast.⁴⁴ During the 2017 Doklam standoff, China demonstrated its willingness to use water coercively by stopping the sharing of hydrological data with India, impeding India’s ability to predict and manage downstream floods.⁴⁵ In fact, no such data has been shared since 2022.⁴⁶

India itself responded to the Pahalgam attacks by weaponising water. On 23 April 2025, forty-eight hours after the Pahalgam attack killed 26 civilians in Baisaran valley, India formally notified Pakistan that the Indus Waters Treaty (IWT) of 1960 was being “held in abeyance with immediate effect”, until Pakistan “credibly and irrevocably” ends cross-border terrorism.⁴⁷ In early May 2025, India physically cut off water flow through the Baglihar Dam on the Chenab River and announced it was planning identical measures at the Kishanganga Dam on the Jhelum- both rivers that under the IWT belonged to Pakistan’s allocation.⁴⁸ Pakistan’s foreign minister called any withholding of water “an act of war.”⁴⁹

What happens when a desperate, water-starved, nuclear-armed Pakistan faces internal collapse that starts affecting its ruling classes? Does it start bombing us? Because Climate change isn’t just about “resource competition”- it’s about state failure, and Pakistan’s per capita water availability has fallen by 83% since 1951.⁵⁰

Water is already a coercive instrument in our region.

2. Heat
We have a coastline of 11,098.81 kilometers⁵¹, with several economically important and culturally vibrant city-civilisations on them. Rising sea levels and intensifying cyclones are putting all of this at risk.

The surface temperature of the tropical Indian Ocean has already increased by 1°C between 1951 and 2015, higher than the global average sea surface temperature rise.⁵² Higher ocean temperature contributes directly to cyclones.⁵³ During Cyclone Hudhud in 2014, the Indian Navy suffered infrastructure damage worth ₹2,000 crore at Visakhapatnam.⁵⁴ Rising seas threaten dry docks, repair infrastructure, and coastal logistics networks. The frequency of very intense cyclones in the post-monsoon period has increased significantly during 2000–2018.⁵⁵ Each such event doesn’t just damage physical infrastructure — it pulls naval and military assets away from their primary strategic responsibilities and into disaster relief, degrading operational readiness.

Meanwhile, sea level rise in the North Indian Ocean accelerated from 1.06–1.75mm per year during 1874–2004 to 3.3mm per year during 1993–2017.⁵⁶ A 2025 study published in Nature Scientific Reports confirmed that Mumbai, Kolkata, and Chennai face “intensified risks across all emission projections” due to their low elevation and high population concentration.⁵⁷ Mumbai has already witnessed the maximum rise in sea levels of any Indian city (4.44 cm between 1987 and 2021), and that figure is projected to increase sharply by 2100.⁵⁸

3. Migration
India shares a 4,000+ kilometre border with Bangladesh.⁵⁹ That’s a long border. Bangladesh is also the world’s seventh most climate-vulnerable country⁶⁰, and climate change is projected to submerge approximately 17% of its landmass, displacing roughly 13 percent of its population by 2050⁶¹.

When Bangladesh floods, its people move north and west- into India. India has already spent billions⁶² constructing border fencing, but field reports from the West Bengal border describe fencing on the Bangladesh side with crossing as compromised⁶³, and crossings are facilitated by narrow canals that cannot be fully monitored.⁶⁴ Migration pressure is unlikely to be evenly distributed- it concentrates in Bengal and the Northeast, regions already marked by ethnic tension⁶⁵, political volatility, and a complex history with Bangladeshi migration dating back to 1971⁶⁶.⁶⁷

What transforms this from a humanitarian issue into a security one is the documented presence of banned militant organisations like Jamaat-ul-Mujahideen Bangladesh near the border⁶⁸– groups that can exploit mass migration events for infiltration.

Climate Trigger	The “Climate” Impact	The “Security” Result	Why it matters for National Security
Glacial Melt	Retreating snouts; unstable moraine; GLOFs (floods).	Tactical Instability	Traditional borders (like the AGPL in Siachen) physically shift; supply routes disappear.
Monsoon Shift	Extreme rainfall or prolonged drought.	Economic Despair	44% of the workforce loses income; rural “desperation” becomes a recruitment tool for insurgents.
Extreme Heat	45°C+ days in the plains and high-altitude zones.	Operational Decay	Soldiers face physiological limits; equipment (engines/ammo) fails; training routines are halted.
Sea Level Rise	Coastal inundation and salt-water intrusion.	Base Degradation	Strategic naval assets (like Visakhapatnam) face infrastructure damage; dry docks become unusable.
Water Stress	Depleting groundwater and drying river basins.	Inter-state Riots	Water becomes a “zero-sum” game; leads to internal unrest (Cauvery) or external “Water Wars.”
Crop Failure	Reduced yields and nutrient loss in staples.	Food Riots	High food prices historically lead to urban instability and the potential collapse of state legitimacy.
Migration	Millions displaced by floods (Assam) or cyclones.	Border Pressure	“Distress migration” creates dense, vulnerable urban slums and pushes people across sensitive borders.
Vector Shift	Mosquitoes moving to higher altitudes.	Morbidity Burden	High malaria/dengue rates in active zones (Northeast/Himalayas) reduce troop readiness.

Cheat Sheet

Military Readiness
The April 2026 Planetary Security Initiative report produced by the Clingendael Institute in collaboration with India’s Institute of Peace and Conflict Studies offers this analysis of how climate change degrades military readiness across four core pillars: personnel, infrastructure, platforms, and equipment.⁶⁹

Personnel: Extreme heat is degrading recruitment pools and training routines. India is already experiencing record-breaking heat events across the Indo-Gangetic Plain, and soldiers training in 45°C heat in Rajasthan or operating in flooded terrain in Assam face physiological limits that reduce performance and increase casualties.
Infrastructure: Naval bases, Himalayan forward posts, and logistical nodes are threatened by sea-level rise, cyclones, and flash floods. The 2014 Kashmir floods, which damaged over 40 km of three-tier border fencing and flood-lighting LoC fencing⁷⁰, are a preview of a recurring problem.
Platforms: Extreme temperature fluctuations and humidity degrade armour, engines, and vehicles. The US military has already begun designing vehicles for higher heat and cold tolerance- India must follow suit.⁷¹
Equipment: Ordnance and ammunition have defined storage and operational temperature ranges. A changing climate expands the operational environments beyond these ranges.

Climate change is also squeezing the defence budget from two directions. India already spends about 5.6% of its GDP managing climate change impacts- a share expected to grow.⁷² A Stanford University study found that climate change had a negative 31% impact on India’s GDP per capita from 1961 to 2010.⁷³ Defence spending as a share of GDP has declined steadily, falling below 2 percent in 2024–25 for the first time in over a decade.⁷⁴ As climate disasters redirect more public spending toward relief and rehabilitation, the defence budget will face even greater compression, precisely at a time when India faces two active, nuclear-armed rivals on its borders.

Despite all this evidence, India’s strategic doctrine has been slow to formally integrate climate change into its national security framework. The 2008 National Action Plan on Climate Change (NAPCC)⁷⁵ and the Prime Minister’s Council on Climate Change were early institutional steps, but as a 2024 Tandfonline study noted, India has “remained opposed to discussing security implications of climate change in the UNSC.”.⁷⁶ The Indian strategic discourse, as the Planetary Security Initiative’s 2026 report notes, “remains primarily focused on civilian-centric impacts” rather than hard military readiness⁶⁹, and as recently as March 2026, the Ministry of Defence released its ‘Defence Forces Vision 2047’ — a comprehensive modernisation blueprint that makes no explicit mention of climate change as a security variable⁷⁷.

When the UNSC debate “Maintenance of International Peace and Security: Climate and Security” was convened, India’s permanent representative, TS Tirumurti, voted against a draft resolution in December 2021 on the grounds that it “attempted to securitise climate action and undermine the hard-won consensual agreements” reached at Glasgow COP26.⁷⁸ India’s position, restated across multiple UNSC sessions over 15 years, is philosophically coherent: securitising climate change risks bringing militarised solutions to problems that are inherently non-military in nature;⁷⁹ the UNSC, with its five veto-wielding permanent members who are historically the world’s largest emitters, is not a legitimate forum to decide climate governance;⁸⁰ and the right place for climate action is the UNFCCC, the UNGA, and ECOSOC, which are more representative and participatory⁷⁸.

This is not entirely wrong. The securitisation of climate change at the UN level has real risks- it can be used to justify military interventions dressed up as climate responses, and it gives P5 countries disproportionate control over a global problem they caused.⁸¹ ⁸² India’s resistance carries the moral weight of the Global South.

But there is a distinction that India has repeatedly failed to make cleanly. There is a difference between opposing the international securitisation of climate change (arguing that the UNSC shouldn’t police it) and failing to integrate climate risks into your own domestic security planning (refusing to acknowledge it as a threat to your own military).

India’s 2017 Joint Doctrine of the Armed Forces labels climate change a “non-traditional security issue”⁷⁶, a categorisation that is both technically accurate and practically meaningless, since it places glacier melt in the same administrative drawer as piracy and pandemics⁸³. That framing, non-traditional, therefore not urgent, is the problem.

This is a critical gap. Peer militaries, particularly in the US and within NATO, have been conducting disaster war games, climate risk audits of military installations, and equipment redesign programmes for years.⁸⁴ ⁸⁵ India’s CLAWS has called for the Integrated Defence Staff (IDS) to become the nodal body for climate security planning⁸⁶, and for a “risk-risk” orientation in policy one that weighs the cost of climate inaction against the cost of adaptation (A “risk-risk”⁶⁹ a decision-making approach used to analyze the trade-offs between different risks, specifically comparing the risk reduced by a particular action (e.g., regulation, mitigation) against new risks created by that same action).

So what about Siachen?
ISRO and the Wadia Institute of Himalayan Geology have documented a recession of approximately 800 metres from the Siachen Glacier’s snout over the last 20 years.⁸⁷ As glaciers retreat, the terrain they leave behind is not clean, empty ground. It is unstable moraine^{(Moraine is the debris (rock, sediment, dirt) that a glacier picks up and deposits as it retreats. It is loose, unconsolidated, and structurally unreliable. It also tends to form dams across glacial meltwater, creating glacial lakes that can burst suddenly and catastrophically, these are called glacial lake outburst floods, or GLOFs})⁸⁸ prone to collapse, to sudden flooding, to avalanche patterns that have no historical precedent because the ice that shaped them is no longer there. Old military positions may find themselves sitting on terrain that is physically changing beneath them.⁸⁹ Routes that were stable for decades become lethal. Strategic high points, held at enormous human cost, may shift in their tactical value as the topography itself rearranges.

Can troops continue to serve there? Technically, they currently do despite conditions that would be described, in any other context, as incompatible with human habitation. But the question climate change forces is not just whether they can- it’s whether the positions they hold will still make military sense as the glacier retreats and new terrain emerges. The Army will have to continuously reassess which positions are defensible, which supply routes remain viable and, what seems more frightening to me, which points are downstream of newly forming glacial lakes that could burst without warning.

All over our country, the ground is changing, shifting, melting under our feet. To ignore the security dimension of climate change is to believe that a nation can be “secure” even if its cities are underwater and its breadbasket is a dust bowl, and its soldiers don’t know where to stand. True autonomy in the coming century won’t just be measured by the size of our arsenal, but by the resilience of our resources. If national security is preparing for the worst case scenarios, it is time to acknowledge that climate change is also our war theatre.

Sources

Risk VI – How Disasters Amplify Systemic Injustice

The previous pieces in this series looked at how risk is priced, transferred, and hedged. This one looks at who absorbs it when none of those mechanisms work, and why that’s never random.

When devastating floods hit Kerala in 2018, a Dalit family walked three kilometres to the nearest relief centre at a temple, only to be told they were not allowed to enter.¹ A year later, when Cyclone Fani ravaged Odisha, another Dalit family walked to a relief shelter and was also turned away.¹ ²

Both were excluded by caste.

As activist Sangram Mallick put it: “Your caste determines what kind of treatment you will get during a disaster.”¹

These are often described as failures of disaster response. They are not. They are examples of how disaster response works.

Environmental stress (floods, heatwaves, droughts, cyclones, etc.) appears neutral, but its effects are not. Repeatedly, across countries and across hazards, harm clusters along pre-existing social lines: caste, race, gender, income, disability, age. The World Meteorological Organization puts it plainly:³ inequality and disaster vulnerability are “two sides of the same coin.” Climate change, in this sense, is not an external shock landing on a functioning system. It is a multiplier applied to a system that is already unequal.

To understand how that multiplication works, it helps to look at disasters not as singular events, but as a process, one that unfolds in three stages:

Who is exposed before the event.
Who is able to survive during it.
And who is able to recover after it.

I. Pre-Event: Who is placed in harm’s way
Across contexts, marginalised groups are systematically pushed into what are, in effect, sacrifice zones- places that are cheaper precisely because they are more dangerous.

In India, research published in the journal Demography found that marginalised caste groups experience 25–150% higher heat exposure at work than dominant caste groups, even after controlling for income, education, and geography, a pattern the authors described as “thermal injustice.”⁴ Separately, a 19-year study published in the journal Temperature found that India recorded nearly 20,000 heatstroke deaths between 2001 and 2019, a figure researchers say is an undercount given systemic underreporting.⁵

The same structural logic appears elsewhere. In the United States, racially segregated housing patterns have concentrated Black communities in urban heat islands with less tree cover and higher exposure to extreme temperatures.⁶ ⁷ Indigenous communities, displaced from ancestral land through colonial processes, are now disproportionately located in areas more exposed to climate hazards such as drought, wildfire, and extreme heat.⁸

Income reinforces this exposure. A global study of 573 flood events found that higher inequality within a country correlates with higher flood mortality, and that the protective effect of economic growth disappears once inequality is accounted for.⁹ So GDP growth appears protective in simple models but that effect vanishes when inequality is held constant: for the more than 80% of workers in low- and lower-middle-income countries employed in the informal sector, exposure is not just about where they live, but how they work.¹⁰ In Delhi, daily surveys of informal workers during peak summer showed that each 1°C increase in wet-bulb^{(Wet bulb temperature is the lowest temperature air can reach by evaporating water into it. It measures how effectively sweat evaporates to cool bodies, thus accounting for both heat and humidity. Unlike standard temperature, high wet bulb temperatures mean sweat cannot evaporate, making it difficult for the body to cool down, because high humidity means sweat cannot evaporate as easily.)}¹¹ temperature reduced earnings by 19%, with losses reaching 40% during heatwaves.¹² Medical expenses also rose 14% per degree, reaching 25% on heatwave days.¹² For them, heat is not a background condition, it is a direct constraint on survival.

II. During the Event: Who absorbs the shock
When a disaster hits, it does not affect everyone equally. It interacts with existing vulnerabilities, whether physiological, social, and/ or economic, and amplifies them.

For many women, the danger is not only environmental but social. A systematic review across 15 countries found that disasters increase violence against women through three pathways: economic entrapment, unsafe displacement environments, and shifts in household power dynamics.¹³ After Hurricane Katrina, intimate partner violence among displaced women in Mississippi nearly tripled within two years (went from 12.5% to 34.4%).¹³

Displacement itself often creates conditions where harm becomes easier. Camps without lighting, locks, or private sanitation are not just inadequate—they are enabling environments.¹³

For people with disabilities, the barriers are more immediate. In the 2011 Great East Japan Earthquake, persons with disabilities were twice as likely to die.¹⁴ Across disaster types globally, this ratio ranges from two to four times.¹⁵ The reasons are rarely mysterious: evacuation systems that assume mobility, communication systems that assume visibility or hearing, shelters that assume independence.¹⁵

Age compounds vulnerability in different ways. During the 2021 Pacific Northwest heatwave (United States), a majority of those who died were over 65¹⁶: in Oregon alone, approximately two-thirds of the 107 confirmed heat deaths were over that age.¹⁷ Physiological factors, such as reduced thermoregulation, chronic illness, play a role, but so do structural ones: isolation, dependence on caregivers, limited access to timely information.

For informal workers, the choice during a disaster is often binary: stop working and lose income, or continue working and risk physical collapse. A salaried worker may retreat indoors. A day labourer cannot.¹²

The disaster, in other words, does not create vulnerability in the moment. It exposes how unevenly the capacity to withstand shock is distributed.

III. Post-Event: Who is able to recover
If the disaster itself reveals inequality, recovery is where it becomes entrenched.

A 2023 IMF working paper found that income inequality increases after severe disasters across both advanced and developing economies, particularly when shocks are repeated or coincide with downturns.¹⁸ Recovery is not a reset to equality, it is an underlining of pre-existing societal furrows.

This underlining, in the form of aid, often follows the logic of the market. Systems designed to restore property values tend to benefit those who already have property, while offering little to those who do not.¹⁹ The result is that those with assets recover faster and more fully, while those without fall further behind.

At this point it is important to ask what allowed the wealthy asset-owner to build their initial wealth? There are many who truly come from nothing- including no social status, but there are many who do benefit from at least their social background, such as a poor person who nevertheless benefits from a high caste status, or a person who has exactly the same background and qualifications as another, but benefits from their gender or sexual identity.

Migration is one of the clearest outcomes of this gap. Research has shown that marginalised caste groups in India are significantly more likely to be displaced by climate impacts, with many becoming vulnerable to trafficking and forced labour during that process.²⁰ Globally, climate change is expected to displace tens of millions by mid-century, with the most vulnerable populations facing the highest risks during movement and resettlement.²¹

Food security follows a similar pattern. Global assessments show that the majority of the world’s population already lives in countries below the average food security threshold, and warming scenarios are expected to push hundreds of millions more below it.²² Economic growth offers only limited protection, because it raises income (usually along socially-accepted lines⁹) without fundamentally strengthening resilience.²³

Recovery, then, is not simply about rebuilding what was lost. It determines who has the resources to face the next disaster—and who does not.

Isn’t disaster indiscriminate?
It is often said that disasters do not discriminate.

If that were true, their impacts would be randomly distributed.

They are not.

Across countries, across hazards, and across time, the same pattern repeats: those who are already marginalised face greater exposure, suffer greater harm, and recover more slowly. Even major risk models have historically failed to account for these differences, despite extensive evidence that social inequality drives disaster outcomes.²⁴

This consistency is the point. The pattern is not incidental, it is structural. The cycle is Inequality → Disaster → Unequal Recovery → Deeper Inequality → Next Disaster

When that Dalit family in Kerala was turned away from a relief centre, the issue was not access to a building. It was access to protection itself- who is considered entitled to it, and who is not.

Climate change is often framed as a shared crisis. But its impacts are not shared equally, and its costs are not distributed randomly. They follow the structure of the system they move through.

Disasters do not redraw those lines. They deepen them.

Sources

Risk – V: The Strait of Hormuz and The Price of Uncertainty

If you’ve been following this blog’s series on risk, you know by now that risk isn’t just something that happens on a trading screen or inside a bank. Risk lives in the real world — in weather patterns, in election results… and also clearly in the Strait of Hormuz.

Geography
The Strait of Hormuz is a narrow oceanic passage connecting the Persian Gulf to the Gulf of Oman and, from there, to the rest of the world’s oceans. It is bordered on the north by Iran and on the south by the UAE and Oman.¹ At its narrowest, it is just 21 nautical miles wide, with the navigable shipping lanes only about 2 miles wide in each direction.²

Importance
Through this bottleneck flows roughly one-fifth of all global petroleum liquids, which is approximately 21 million barrels per day of crude oil and condensates.³ UNCTAD puts it at around a quarter of all global seaborne oil trade.⁴ The daily value of oil and LNG transiting the Strait is estimated at over $1.3 billion.⁵Annually, trade flows worth approximately $1.2 trillion from five Gulf countries (Iran, the UAE, Qatar, Kuwait, and Bahrain) depend on this waterway remaining open.⁵

So, if this strait is blocked for one single day, between US $2 and $2.3 billion worth of oil trade will be disrupted.⁶

Update, if you live under many rocks
The strait has been blocked since Israel and USA decided to start bombing Iran on 28 February 2026⁷, with the Strait formally closing to most traffic by 4 March⁸ (aside: I feel like March has lasted for 84 years).

Risk
In previous posts on this blog, we’ve talked about risk as the possibility that something unexpected happens, and that the unexpected thing costs you something⁹ ¹⁰ (because when it gifts you something, you’re happy- we only tend to be worried when something bad happens, not when something nice happens by accident/ through uncertainty). That cost could be money, time, safety, or opportunity. But the key insight is always this: risk is not just about bad outcomes. It’s about uncertainty itself.¹¹

Finance has a more precise definition. In financial markets, risk is typically measured as the volatility of returns (how much a price, yield, or value might swing from its expected level).¹² But risk also has a tail dimension¹³ ¹⁴: the small-probability, catastrophic events that are hard to price and even harder to hedge ^{(hedging is a risk management strategy where you take the opposite position from an asset you already own so that if the first asset reduces in value, the opposite hedged position will experience the exact opposite and either maintain value or increase in value, which allows the entity that is using hedging as a strategy to continue to be part of the market rather than sell the first asset which is facing volatility, while also not losing everything if its value falls sharply. It involves the cost of buying the opposite asset, so it is a kind of insurance)}¹⁵. The Strait of Hormuz is the textbook example of this second kind of risk. It sits in the tail, but when the tail wags, it apparently wags the whole dog with it.

Geopolitical Risk Premium (GRP)
Geopolitical risk is the threat, occurrence, or escalation of adverse events, such as wars, terrorism, and international tensions, that disrupt global relations, economies, and supply chains.¹⁶ ¹⁷

Every time tension rises in the Gulf, the price of oil goes up- even before a single barrel is disrupted.¹⁸ This is called the Geopolitical Risk Premium (GRP): the extra cost added to the price of oil simply because the possibility of disruption exists.¹⁹

In early 2026, Oxford Economics estimated this premium at approximately US $9 per barrel.⁵²⁰ That means every barrel of oil being bought and sold globally was US $9 more expensive than it would be in a world without Hormuz tension, and not even because supply had actually been cut, but simply because markets were pricing in the possibility that it might be.

As we know, this is a foundational concept in risk and risk management: people pay for uncertainty (this is how insurance works as a business, for example).²¹ ²² The premium is the market’s way of costing the uncertainty of not knowing what will happen, whether for a term life insurance (which actuarial nerds actually know a lot about) or about Iran closing the Strait of Oil: we don’t know what will happen, and that not-knowing is worth something (priced as the premium).²³ ²⁴

Scenario Analysis
Oxford Economics published a scenario analysis in February 2026 that laid out how it was thinking about Hormuz risk:⁵

20% probability of faster de-escalation, where the risk premium unwinds quickly
45% probability of the Strait stays open, flows remain broadly normal
30% probability of low-level disruption, where repeated interference cuts vessel traffic by 50% for two months, reducing global oil supply by 4 million barrels per day
5% probability of severe disruption, where Iran halts transit for up to a week, pushing oil to $140 per barrel and gas above $40 per MMBtu

So, according to Oxford Economics, the most likely scenario was that nothing would go drastically wrong. Still, that 30% scenario of low-level disruption is not a small number. In finance, a 30% probability event is something you plan for, hedge against, and price into your decisions. And then the 5% tail event happened. In risk-speak, this is called a Grey Rhino²⁴– a highly probable, high-impact threat that is visible and repeatedly warned about but neglected anyway, because acting on it costs money now, and the event is only probable, not certain.

Insurance
One of the most sensitive early-warning signals of financial risk is insurance pricing, because when something becomes riskier, insurers reprice insurance to cover both, the rising uncertainty, and the total risk.²⁵ They’re basically trying to cover all major possibilities that they’ll have to pay you rather than you either swallowing the losses, or you paying them.

Therefore, war risk insurance premiums for ships transiting the Strait have been surging²⁶, which means that freight rates for oil tankers have spiked. Marine fuel costs are rising too, layering cost upon cost.²⁷ Maritime insurance companies have the incentive to be ahead of the news, not behind it.²⁸When they start repricing risk aggressively, or worse, when they start withdrawing cover entirely, ships that are theoretically able to transit the Strait become practically unavailable because they can’t afford or obtain insurance.²⁹³⁰

This is not the first time insurance has been the mechanism that shut down a shipping lane. When Houthi attacks began in the Red Sea in late 2023³¹, the persistent collapse in traffic wasn’t primarily because ships were being sunk- it was because the threat alone made insurers reprice, which made shipowners reroute. War risk premiums for Red Sea voyages rose from effectively zero to between 0.5% and 1.0% of a ship’s hull value, and major carriers including Maersk, MSC, Hapag-Lloyd, and CMA CGM suspended transits entirely, not because their ships couldn’t physically pass, but because the insurance mathematics no longer worked.³² By late 2024, S&P Global reported that Cape of Good Hope reroutes were likely to “persist well into 2025”, and they did.³³ The Hormuz closure is the same mechanism, at a far larger scale.

Cascading Effects
A cascade effect is a sequence of events in which each event produces the circumstances necessary for the initiation of the next event.³⁴ Here are some impacts that we’re all seeing these days:

Higher oil prices are a tax on everything. They raise the cost of transportation, manufacturing, petrochemicals, and heating- essentially every sector of the modern economy.³⁵ ³⁶
Qatar, the world’s largest LNG exporter, ships nearly all its gas through Hormuz. Any disruption to LNG flows hits Europe, Japan, South Korea, and increasingly India. These are countries that have been restructuring their energy systems around gas as a “transition fuel.”³⁷ ³⁸
Fertilisers are made from natural gas and other petrochemical inputs. The Gulf is a major producer. If fertiliser shipments are disrupted, the cost of growing food goes up. Planting decisions change. Crop yields fall, with the most severe consequences falling on developing economies.³⁹
When ships can’t transit the Strait (or won’t, because insurance costs make it uneconomical) they have limited alternatives. The next-best option is to go around the Cape of Good Hope at the southern tip of Africa, which adds roughly 3,500–4,000 nautical miles and about 10–15 days to the journey.⁴⁰ ⁴¹ That means more fuel, higher crew costs, slower delivery times, and, crucially, fewer ships doing more work: Before the crisis, around 150 vessels transited the Strait each day; that figure has since fallen to four or five. The result could be a supply-side squeeze in global shipping capacity.⁴² Freight rates rise not just for oil tankers but for cargo ships, container ships, and bulk carriers.⁴² These higher costs flow through to the price of every manufactured good that depends on components, materials, or energy from the Gulf region.
When oil prices spike, petro-dollar economies gain. Gulf sovereign wealth funds get richer.⁴³ ⁴⁴ The US dollar often strengthens (since oil is priced in dollars).⁴⁵ But for oil-importing nations, the impact is brutal: India, for instance, imports over 85%⁴⁶ of its crude oil, and while it has diversified⁴⁷ supply routes in recent years, roughly 40%⁴⁸ of crude imports and 90%⁴⁸ of LPG imports still transit the Strait. When the Strait closed, the government was forced to issue emergency orders directing refineries to maximise domestic LPG production to stop cooking gas running out in households.⁴⁸ A sustained oil price spike means a widening current account deficit,⁴⁹ a weaker rupee,⁵⁰ imported inflation, and growing pressure on the Reserve Bank of India to raise interest rates^{(to curb inflation and defend the currency because raising interest rates increases borrowing costs for consumers and businesses, reducing demand and slowing down economic activity, which helps bring inflation down)}: even if the domestic economy doesn’t otherwise warrant it.
The cost of jet fuel has more than doubled since the Strait closed.⁵¹ ⁵² The cost to airlines is estimated at $11 billion⁵³ in additional annual fuel costs, which will show up in your flight bills, but also in the cost of any items being transported through air, including, for example organs for transplant⁵⁴ (that’s right, it won’t just impact Amazon deliveries).
UNCTAD⁵⁵⁵⁶⁵⁷ explicitly warned that high debt burdens and rising borrowing costs limit these countries’ ability to absorb new price shocks. When energy bills go up and borrowing costs rise simultaneously, governments face impossible choices: cut subsidies, raise taxes, or default.
- To understand why, you need to know one thing about how developing-country debt works: a significant amount of the $11.4⁵⁸ trillion in external debt owed by developing countries is denominated in US dollars. This means that while these governments collect their taxes and revenues in their own local currencies they must repay their loans in dollars, a currency they don’t control and can’t print.⁵⁹
- When oil prices rise and economic conditions worsen, local currencies tend to weaken against the dollar.⁶⁰ ⁶¹ Think of it this way: if your salary is paid in rupees but your rent is charged in dollars, and the rupee suddenly buys fewer dollars than it did last month, your rent just got more expensive, even though the dollar amount didn’t change. That is exactly the position these governments are in. The debt didn’t grow; their money just became worth less, making the same debt harder to pay.⁵⁶
- The result is a brutal squeeze from three directions at once: energy bills going up, borrowing costs rising, and debt repayments consuming an ever-larger share of government revenue in real terms.⁵⁷ When a government is spending a significant portion of what it earns just to service debt it took on years ago, there is almost nothing left for the things governments are supposed to do: run schools, staff hospitals, maintain roads, and protect its most vulnerable people.⁶² Please note: currently 3.4 billion people live in countries already spending more on debt than on health or education.⁶³ ⁶²
When oil prices spike, the standard central bank response is to raise interest rates to fight inflation, but higher rates, combined with rising energy costs, create the nightmare scenario of stagflation⁶⁴– the sepulchral portmanteau of stagnation + inflation: economies are not growing, are even contracting, and then being hit with inflation.⁶⁵ The 1970s oil shocks produced exactly this scenario, and most Western economies spent nearly a decade fighting it.⁶⁶ ⁶⁷

What happens next?
As of April 12, 2026, US-Iran talks in Islamabad collapsed after 21 hours without a deal⁶⁸, and Trump has announced a naval blockade of the Strait.⁶⁹

According to CNBC’s analysis of oil-shock-induced bear markets, the average duration of a market decline caused by an oil shock is approximately 13 months, with an average drop of around 30%.⁷⁰ But the range is enormous, and duration, more than any other variable, determines how much lasting damage gets done.⁷⁰ Allianz Research has already stated plainly: if the Strait remains blocked for more than three months, the impact on global growth will start to be recessionary.⁷¹ Global GDP growth for 2026 has already been revised down to 2.6%, from 3.1% projected before the conflict.⁷¹

However, the thing to note is that even if the Strait reopens, the effects don’t simply switch off.

Insurance premiums, once repriced upward, tend to stay elevated for years.⁷² ⁷³ This is because the risk hasn’t gone away once the issue has been resolved, it has simply been revealed: that is, now people know, and Iran knows, and people know that Iran knows, that they can do this any time they wish to. Iran has even begun charging transit tolls to ships seeking passage, a development that, if it stands, converts a one-time crisis into a permanent feature of the global shipping cost structure.⁷⁴

Secondly, shipowners who rerouted through the Cape of Good Hope have restructured their logistics, signed new contracts, and reoriented supply chains that won’t simply snap back the moment a ceasefire holds.⁷⁵ ⁷⁶ The IFO Institute forecasts that Germany, which is used as a proxy for industrial Europe, will still see the drag from the war on its GDP growth through 2027, even in the de-escalation scenario.⁷⁷ The inflation spike from Q2-Q3 2026 has already been priced in by Allianz, and that won’t change just because the Strait opens.⁷⁸

There is also the question of what the world does with the lesson. Every oil shock in history has accelerated investment in energy alternatives.⁷⁹ ⁸⁰ The 1973 embargo triggered the first serious wave of Western investment in nuclear power and efficiency standards.⁸¹ The 2026 shock has already prompted urgent conversations about alternative pipelines, renewable acceleration, and LNG infrastructure diversification.⁸² ⁸³ These structural responses will, eventually, reduce the world’s dependence on this chokepoint: but they operate on decade-long timescales, not quarterly ones.⁸⁴

In the shorter term, the most honest answer is: nobody knows⁶⁴, and we’re all paying the cost of not knowing.⁸⁵ The financial markets’ best guess, reflected in options pricing and analyst forecasts, is that there is a meaningful probability of both a relatively contained outcome and a prolonged, recessionary one.⁸⁶⁸⁷The uncertainty itself has a cost, as we’ve now established. And that uncertainty will remain priced into everything. This is the architecture of systemic risk. It doesn’t ask for your involvement. It doesn’t need you to have invested in oil futures or to have taken a position on Iranian politics. It just needs the world to be as interconnected as it is.

Sources

E-Waste – III: Biomining

This is the third in a series on e-waste. Post I established the scale of the problem and the concept of urban mining. Post II examined India’s informal recycling sector and the limits of EPR policy. This post looks at the biotechnology frontier.

Rare Earth Elements, or REES, are not, despite their name, particularly rare in the Earth’s crust.¹ The challenge is that they are seldom found in concentrated deposits², and they almost always occur together, sharing such similar chemical properties that separating one from another is technically demanding and chemically intensive.³ That cost is not merely financial. Conventional REE mining generates radioactive waste, strips landscapes, and produces acid drainage that contaminates groundwater for decades.⁴

Also, China currently supplies nearly 90% of the world’s REE demand⁵, a concentration of geopolitical risk that rattled supply chains as recently as 2019⁶, and the geopolitical situation has escalated dramatically since: on April 4, 2025, China introduced export restrictions on seven rare earth elements in direct retaliation for U.S. tariffs⁷ ⁸. In October 2025, China expanded those controls further, adding five more REEs critical to magnets and defense, including erbium.⁹ China did pause some of these restrictions temporarily in late 2025 following U.S.-China trade negotiations, but analysts universally treat the pause as tactical, not structural.¹⁰¹¹ The leverage remains.

E-waste has become one of the fastest-growing solid waste streams in the world, with approximately 62 million tonnes generated globally in 2022 alone¹², of which less than one quarter was documented as recycled¹³, yet global REE recycling rates remain below 5%¹⁴. Meanwhile, global demand for magnetic REEs alone is projected to surge from 59 kilotonnes in 2022 to 176 kilotonnes by 2035, a tripling in just over a decade. The trajectory is not sustainable.¹⁵

What are REEs?
Here are the 17 elements, actively sounding like Tolkienian characters:¹⁶

The 17 Elements: Lanthanum (La), Cerium (Ce), Praseodymium (Pr), Neodymium (Nd), Promethium (Pm, the only actually rare REE, and named for Prometheus), Samarium (Sm), Europium (Eu), Gadolinium (Gd), Terbium (Tb), Dysprosium (Dy), Holmium (Ho), Erbium (Er), Thulium (Tm), Ytterbium (Yb), Lutetium (Lu), Scandium (Sc), and Yttrium (Y).
Light vs. Heavy REEs: They are classified into Light Rare Earth Elements (LREEs) (atomic numbers 57-63) and Heavy Rare Earth Elements (HREEs) (atomic numbers 64-71), with yttrium grouped with heavies. HREEs are generally rarer and more valuable. HREEs are more valuable: their greater scarcity relative to demand, and the fact that dysprosium and terbium (both the HREEs) are the critical additives that keep NdFeB magnets performing at high temperatures in EV motors, making them essentially irreplaceable in the short term.¹⁷

Currently, global REE recycling rates remain below 5%. Yet the secondary sources are remarkably rich. The permanent magnets in hard disk drives contain neodymium, dysprosium, and praseodymium at concentrations of 2,500–15,000 parts per million, while the phosphors in fluorescent lamps carry yttrium, europium, cerium, terbium, and lanthanum at 1,000–20,000 ppm, concentrations up to 17 times higher than in natural ores.¹⁸ ¹⁹

Biomining
Using biological organisms to aid mining.

The biological mechanisms involved span a sophisticated toolkit:²⁰

Bioleaching: Microorganisms produce organic acids, siderophores, or other metabolites that dissolve metals from solid matrices. The bacterium Gluconobacter oxydans, for instance, produces gluconic and pyruvic acids that leach REEs from nickel-metal hydride battery powder.
Biosorption: Metal ions bind to functional groups on microbial cell walls or to engineered biomolecules, concentrating them from dilute solutions.
Bioprecipitation: Microbes convert dissolved metals into insoluble forms that can be physically separated.
Bioaccumulation: Some microorganisms, particularly microalgae, internalize REEs through metabolic processes, serving as biological concentrators.
Bioweathering and Bioflotation: Additional mechanisms studied for low-grade ores and mine tailings.

What differentiates biological from chemical approaches is the operating philosophy. Conventional hydrometallurgy uses strong inorganic acids (sulfuric, hydrochloric, nitric) at high temperatures, generating large volumes of hazardous waste. Biomining operates largely at ambient conditions, using biodegradable lixiviants (liquid chemical solutions used in hydrometallurgy to selectively extract metals from ore or recycled materials by dissolving them into a liquid phase)²¹, with significantly reduced freshwater consumption and wastewater generation.

Urban Biomining
It is the recovering of critical resources from the waste streams of cities and industrial systems rather than from natural ores.²² ²³ A 2025 review published in ACS Environmental Au by researchers at George Washington University identifies it as one of the most promising frontiers in sustainable REE recovery.²⁴

Laboratory studies have demonstrated impressive bioleaching yields. Acetic acid achieves leaching efficiencies exceeding 90% for neodymium, dysprosium, and praseodymium from NdFeB magnet powder at concentrations of 1.6–10 mol/L and 60°C.²⁵ ²⁶ Citric acid at 1 mol/L can achieve near-complete (100%) REE leaching from hydrogen-decrepitated (a process used to create extremely small grains)²⁷ NdFeB powder within 24 hours.²⁸ Importantly, the spent culture medium of microorganisms (or supernatant, which is the byproduct liquid remaining after microorganisms have grown, containing metabolic waste, secreted proteins, and residual nutrients)²⁹ often outperforms isolated organic acids, because it contains a richer diversity of leaching agents at higher combined concentration.³⁰ ³¹

A two-step bioleaching process using acidophilic bacteria on e-waste shredded dust was found to mobilise up to 99% of cerium, europium, and neodymium, and up to 80% of yttrium and lanthanum within eight days.³² A sequential microbial process pairing bacterial bioleaching with microalgal biosorption has demonstrated the feasibility of recovering multiple REEs (gadolinium, praseodymium, cerium, lanthanum) from e-scraps.³³

Beyond e-waste, biomining offers a pathway into legacy waste. Coal ash, the residue from burning coal, is one of the most REE-rich and economically promising secondary sources.³⁴ A techno-economic analysis cited in a 2024 comprehensive review found that coal ash yields the highest profitability of all mining waste streams when subjected to biomining recovery.³⁵ Old mine tailings, the rock and mineral residues left behind after primary extraction, also retain significant REE concentrations.³⁶ ³⁷ Biomining these sites simultaneously addresses long-term environmental hazards, reducing acid drainage and radioactive residue exposure, while turning environmental liabilities into resource streams.³⁸ ³⁹

Selectivity
Since rare earth elements are chemically near-identical, so finding just one among the 17 is a complex process, and can require hundreds of solvent extraction stages via conventional methods.⁴⁰

This is where molecular biology can help.

In 2018, researchers discovered lanmodulin (LanM)₄₁, a small (~12 kDa- according to Google AI, a teaspoon holds over 200 quintillion particles)⁴² bacterial protein produced by methylotrophic bacteria that is able to select the required REE to a degree no synthetic chemical method can yet do.⁴³ It also remains stable at pH 2.5 and temperatures up to 95°C, making it practically viable in the acidic, hot conditions of industrial leachates (industrial leachates are the highly contaminated, toxic liquids formed when water percolates through industrial waste, landfills, or contaminated sites, dissolving soluble materials)⁴⁴.⁴³

Beyond lanmodulin, the field has expanded to include:

Lanthanide-binding peptides (LBPs)⁴⁵: Short synthetic sequences that selectively adsorb specific REEs with minimal cross-reactivity for neighboring non-REE elements
Functional nucleic acid aptamers⁴⁶: A DNA aptamer (Sc-1) has demonstrated the ability to bind REE ions selectively and discriminate all 17 REEs into three groups.
Pyrroloquinoline quinone (PQQ)⁴⁷: A microbial cofactor that can precipitate REEs from solution and has a natural preference for light REEs over heavy ones
Lanthanide-binding phage (LBPh)⁴⁸: M13 bacteriophage engineered with ~3,300 copies of an LanM-derived peptide, achieving 35 mg/g binding capacity with preferential uptake of heavy REEs and pH-triggered release over five reuse cycles

Don’t look at me, I cannot pronounce these words either. I was researching urban mining and fell into this ~~black~~ rabbit hole.

What biomining-enabled circular REE recovery ultimately points toward is not merely a more efficient way to recycle old phones. It is a fundamentally different relationship between industrial civilisation and the material world, one in which the waste of one cycle becomes the feedstock of the next, in which biology does the discriminating work that chemistry does badly and expensively, and in which the geopolitical concentration of a critical resource is loosened by distributing recovery capacity to wherever waste accumulates.

This vision aligns with what some materials scientists and industrial ecologists call a regenerative materials system⁴⁹: one that does not merely reduce harm but actively restores, cleaning up legacy pollution in mine tailings and coal ash while simultaneously supplying the materials a decarbonizing economy urgently needs. The circular economy of REEs through biomining represents exactly this kind of convergence: biotechnology, sustainability science, and critical materials security not pulling in different directions, but pointing the same way.

The technology is not yet ready for full industrial deployment. But the science has reached the point where the question is no longer whether it is possible, but how fast we choose to make it happen.

Sources

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