Mexico Is Ageing on an Income It Cannot Retire On, and the Budget Already Shows It

Why a fertility rate of 1.2 and a pension bill above 6% of GDP measure the same problem, and the two indicators that could prove this wrong

AsiaPresswire – Mexico’s fertility rate was 1.9 children per woman in 2019. In 2024 it was 1.2. Replacement is 2.1. In five years the country moved from a fertility profile that roughly holds a population steady to one where each generation is 43% smaller than the one before it, and it did so at a income level where the state has not finished building the systems that older people need.

That is the whole argument, and it can be falsified in two places. Either fertility recovers toward replacement, or the formal labour market expands fast enough to fund the pension promises already written. If neither happens by 2028, the arithmetic below is not a forecast, it is a schedule.

The Number That Turned

The 2025 inter-census survey, reported by INEGI and relayed through Mexican statistical coverage in 2025-26, put the population at 130.4 million with 19.2 million people aged 60 or over. That is 14.7%. The median age is 32. The ageing index, which counts people aged 60 and over per 100 children aged 0 to 14, reached 68.2, against 47.7 in 2020. Life expectancy at birth is 75.5 years.

None of those numbers is unusual for a middle-income country in isolation. What is unusual is the speed and the sequencing. A fertility rate that falls 37% in five years is not a slow demographic drift; it is a behavioural break, and it arrives before the institutions that amortise it.

Table 1: Six demography indicators, and what each one implies

Indicator	Value	Year	What it changes
Total population	130.4 million	2025	Denominator for every per-capita claim
Population aged 60 and over	19.2 million	2025	14.7% of the total
Median age	32 years	2025	Labour supply still growing, briefly
Ageing index	68.2 per 100 children	2025	Was 47.7 in 2020
Fertility rate	1.2 children per woman	2024	Was 1.9 in 2019
Life expectancy at birth	75.5 years	2025	Duration of the payout

Read the median age and the fertility rate together and the trap appears. A median age of 32 means Mexico still has a large working-age cohort, which is why the fiscal problem does not feel urgent in 2026. A fertility rate of 1.2 means that cohort is the last large one. The two facts are consistent, and they point in opposite directions for about fifteen years.

Three Variables, Not One

Most commentary on Mexican ageing collapses into a single variable, usually the dependency ratio, and then argues about projections. The dependency ratio is a consequence. Three variables drive it, and only three matter for the next decade.

Fertility. At 1.2, Mexico is below every OECD member except Korea and Italy, and it got there faster than either. Fertility is the slowest variable to reverse and the fastest to move; it responds to housing costs, female labour participation and contraceptive access, none of which a pension reform touches.

The contributory and non-contributory split. Mexico runs two pension systems that behave in opposite ways. Contributory pensions, financed by worker and employer contributions through IMSS and ISSSTE, are contractually fixed and growing with the number of retirees. Non-contributory transfers, financed from the budget, are discretionary and politically expandable. In 2026 the budget froze the first and expanded the second, and that is the decision that matters.

Coverage. The share of the population covered by public health insurance fell from 77.1% in 2020 to 72.5% in 2025. Coverage is the variable that determines whether an ageing population shows up as fiscal cost or as household cost. When coverage falls while the old population grows, the cost does not disappear. It moves to the family, and then to the private clinic.

What the 2026 Budget Actually Did

The 2026 expenditure budget allocates 2.3 trillion pesos to pensions, an increase of 3.7% overall. That headline number hides the structure.

Contributory pensions, the ones that depend on contributions from workers, employers and the state, rise by 0.05%. The IMSS pension budget falls 2.5%. The ISSSTE budget falls 2.3%. The number of pensioners grows about 3% a year. Meanwhile the non-contributory old-age pension rises 5.2%, the disability pension 20.8%, and the new pension for women aged 60 to 64 rises 266%, expanding to three million beneficiaries.

Table 2: The 2026 pension budget, by line

Line	2026 change	Beneficiaries	Political status
Total pension spending	+3.7%	—	2.3 trillion pesos
Contributory pensions	+0.05%	about 3% more each year	Contractual
IMSS pension budget	-2.5%	largest block of retirees	Contractual
ISSSTE pension budget	-2.3%	public-sector retirees	Contractual
Old-age pension, 65 and over	+5.2%	13.7 million	Discretionary
Disability pension	+20.8%	2.0 million	Discretionary
Pension for women aged 60-64	+266%	2.8 million registered	Discretionary
Total social programme beneficiaries	—	42.8 million	—

Two things follow, and they are not ideological.

First, the contributory system is being asked to deliver a 3% larger caseload on a budget that grows by five hundredths of one percent. That is arithmetically a cut in the real value of each pension, before inflation. Divide 1.0005 by 1.03 and the real value per beneficiary falls 2.9%. Add 4% inflation and the fall is 6.6% in a single year.

Second, the non-contributory system is becoming the larger growth engine. Thirteen point seven million people receive 6,400 pesos every two months, which is 3,200 pesos a month, about US$171 at 18.7 pesos to the dollar. The women’s pension pays 3,100 pesos every two months, 1,550 a month, about US$83. Multiply by beneficiaries and the two transfers cost roughly 578 billion pesos a year, or 25% of the entire pension budget.

That 25% is the number to hold onto. A quarter of Mexico’s pension money now moves through programmes that a future government can change with a budget line, and three quarters moves through contracts that a future government cannot. The fiscal risk is not that pensions are too generous. It is that the rigid part is frozen while the flexible part expands, and the flexible part is the one that reaches the poorest old people.

The Arithmetic of a Frozen Line

Here is where an ageing population becomes a budget problem rather than a demographic one.

The pension bill passed 6% of GDP in the 2026 budget and approaches a quarter of net public spending, according to the Centre for Economic and Budgetary Research. Six percent of GDP is not remarkable against the OECD, whose public pension spending sits in the region of 8%. What is remarkable is the ratio to the old-age share.

Divide 6% by 14.7% and Mexico spends about 0.41 percentage points of GDP for every percentage point of population aged 60 and over. Do the same for an OECD average of roughly 8% of GDP and roughly 24% of population aged 65 and over, and the figure is 0.33. Mexico is spending about a quarter more per old person, relative to its output, than the rich-country average.

The comparison has an obvious flaw and it runs in one direction. Mexico’s 14.7% counts people aged 60 and over, while the OECD’s 24% counts 65 and over. Using the higher threshold for Mexico would shrink the denominator and raise the ratio further, so the flaw makes Mexico look cheaper than it is, not more expensive. The conclusion survives the correction.

Table 3: Pension spending against old-age share

Measure	Mexico, 2026	OECD reference	Ratio
Public pension spending, % of GDP	6.0	about 8.0	0.75
Population above the threshold, %	14.7 (60+)	about 24 (65+)	0.61
Spending per point of old-age share	0.41	0.33	1.23
Share of net public spending	about 25%	—	—

A country that spends like a rich country on pensions while collecting taxes like a middle-income one has three options, and it is worth naming them plainly because every Mexican budget since 2020 has chosen among them implicitly.

• Raise contributions or taxes, which hits the formal sector that is already paying.
• Cut the real value of contributory pensions, which is what a 0.05% increase against 3% more pensioners does by default.
• Expand non-contributory transfers and accept that the fiscal cost grows with the elderly population rather than with the wage bill.

The 2026 budget chose the second and the third at the same time. That is a coherent political strategy and an incoherent fiscal one, because the two choices have different growth rates.

The ratio has a clock on it, and the clock is easy to read. If the number of pensioners grows 3% a year while the number of registered workers grows 1%, the ratio of contributors to retirees falls 1.9% a year, and 17.8% over a decade. That is not a crisis scenario; it is the current trend extended. To hold the ratio flat, registered employment has to grow at the same 3% as the pensioner count, which in a country where informal work still accounts for a majority of employment is a labour-formalisation target rather than a growth target. Framed that way, the pension debate and the informality debate are one debate, and the 2026 budget treated them as two.

Who Is Hit First: Women Aged 60 to 64

The distributional answer is unusually clear, and it comes from the design of the new programme rather than from advocacy.

A woman who turns 60 in Mexico in 2026 and who spent her working life in the informal economy has no contributory pension, because she never had an employer contributing on her behalf. She becomes eligible for the women’s pension at 60, four years before the universal old-age pension at 65, and she receives 1,550 pesos a month, about US$83.

Two point eight million women are registered. The budget for that line rose 266% in one year, which is the largest percentage increase in the entire pension bill and the clearest statement of political priority in the 2026 budget. It is also a recognition of a real gap: Mexican women have lower formal labour participation, more interrupted contribution histories, and a longer life expectancy than men, which means they draw a smaller pension for more years.

The programme is means-tested by age and gender, not by contribution history, so it reaches exactly the group the contributory system never covered. That is its strength. Its weakness is that 1,550 pesos a month is not a pension. It is a transfer that covers part of a household’s food bill, and it will be paid for as long as the budget line exists.

The second cohort is less visible. Workers hired before July 1997 fall under the 1973 pension law, which calculates the benefit from the average salary of the last five years rather than from an individual account. That group had a legal route to raise its own pension by making voluntary contributions at a higher declared salary, known as Modalidad 40.

On 22 October 2026 that route narrowed. New entrants can only contribute on the last salary registered with the institute plus one unit of measurement, with the UMA set at 117.31 pesos a day for 2026. Retroactive payments from before the application date are no longer possible, and self-employed workers registered under Modalidad 10 cannot also take Modalidad 40. For a worker who was planning to spend five years raising his declared salary before retiring, the option closed on a specific date, and the difference between the pension he expected and the one he will receive is not a projection. It is a subtraction.

Two Indicators That Are Actually Independent

Forecasts about ageing are cheap. What is expensive is knowing which number to watch, and the two numbers below are chosen because they move for different reasons.

The first is the ratio of IMSS-registered workers to the population aged 60 and over. This is the contributory base divided by the people it must support, and it is published monthly. If the ratio rises, formal employment is outrunning ageing and the contributory system can hold. If it falls, every promise in the 1973 and 1997 laws becomes a claim on general revenue.

The second is private spending on geriatric care. IMARC put Mexico’s geriatric healthcare market at US$20.58 billion in 2025. This indicator measures the cost that has already been pushed out of the public system into households. It is independent of the first because it responds to coverage, not to employment: when public health coverage falls from 77.1% to 72.5%, the private market grows whether or not more people have formal jobs.

Table 4: The two indicators, and what each one is measuring

Indicator	Source	Frequency	What a move means
IMSS-registered workers per person aged 60+	IMSS	Monthly	Contributory solvency
Private geriatric care spending	IMARC and clinic filings	Annual	Cost shifted to households
Public health coverage share	INEGI	Annual	Whether the shift accelerates
Ageing index	INEGI	Annual	Speed of the demographic turn

Watch the first two together. If registered workers per old person is stable and private geriatric spending is growing at double digits, Mexico is not facing a pension crisis; it is facing a care crisis, and the money is already leaving households to pay for it. If both deteriorate, the pension problem and the care problem arrive in the same fiscal year, which is the scenario that the 2026 budget’s structure makes likely.

What Would Prove This Wrong

Three observations would break the argument, and each is measurable within two years.

• Fertility recovers above 1.6. A rebound of that size would require either a large-scale childcare expansion or a change in housing costs that no current policy implies. If it happens, the 2045 dependency ratio is materially better than the schedule above.
• Formal employment grows faster than the old population for three consecutive years. IMSS registrations have grown in most years since 2010, but rarely faster than 3% net. Three years above 5% would mean the contributory base is winning.
• Remittances to households headed by someone over 65 rise sharply. Mexico received record remittances through the 2020s. If those flows are increasingly directed at elderly households, the household sector is absorbing the coverage gap and the fiscal crisis is deferred, not solved.

Put a number on the second observation. Registered employment growing 5% a year against a pensioner count growing 3% raises the contributor-to-retiree ratio 19.4% over ten years, which is enough to carry the 1973 cohort through its peak drawdown without a real cut. That is the size of the move required, and it is why the formalisation rate rather than the fertility rate is the variable to argue about in the next two budgets.

Two of the three are about the labour market, which is the variable that Mexican pension debates consistently underweight. The demographic schedule is set. What is not set is how many people are paying into the system while the schedule unfolds.

Data Basis, Two Limits, and the Number I Could Not Find

The demographic figures come from INEGI’s 2025 inter-census survey as reported in Mexican statistical coverage, and the ageing index comparison uses the 2020 census as the base.

• Population 130,392,389, aged 60 and over 19,204,670, median age 32, ageing index 68.2, life expectancy 75.5 and public health coverage 72.5% are 2025 INEGI figures, with the 2020 comparators of 47.7 for the ageing index and 77.1% for coverage stated in the same releases.
• Fertility of 1.2 in 2024 against 1.9 in 2019 is INEGI data reported through Mexico News Daily.
• The 2.3 trillion peso pension total, the 3.7% overall increase, the 0.05% contributory increase, the 2.5% and 2.3% cuts to IMSS and ISSSTE, and the 6% of GDP and quarter-of-net-spending ratios are from the Centre for Economic and Budgetary Research’s analysis of the 2026 expenditure budget.
• The 13.7 million old-age beneficiaries at 6,400 pesos bimonthly, the 2.8 million women registered at 3,100 pesos bimonthly, the 266% increase and the 42.8 million total social programme beneficiaries are from the Welfare Ministry’s 2026 briefing.
• The Modalidad 40 changes, the one-UMA limit and the 117.31 peso daily UMA for 2026 are from the IMSS decree of 21 October 2026 as reported by El Pais on 22 October 2026.
• The US$20.58 billion geriatric healthcare market is IMARC Group’s 2025 estimate.

Two limits deserve stating. The first is that INEGI’s 2025 figures come from an inter-census survey rather than a census, so the denominators carry sampling error that the published tables do not fully express; the ageing index in particular is sensitive to the estimate of the 0-14 population, which is the hardest group to count. The second is that the OECD comparator uses a 65-and-over threshold against Mexico’s 60-and-over, which I have flagged rather than corrected, because correcting it properly requires age-specific spending data that neither the OECD nor the Mexican finance ministry publishes at that granularity.

One number I could not find is the one that would settle the care question: the share of Mexican households with at least one member over 65 that report out-of-pocket health spending above 30% of household income. The national health and nutrition survey collects the components but not in a form that is published annually at that threshold. Until it is, the private geriatric market size is the best available proxy, and a market size is a weaker instrument than a household survey.

Sources

• INEGI, population and housing statistics — 2025 inter-census population, ageing index and median age
• INEGI data via Mexico News Daily — fertility rate of 1.2 in 2024 and coverage trends
• INEGI data via Puebla Online — population 130.4 million and 19.2 million aged 60 and over
• Centre for Economic and Budgetary Research, analysis of the 2026 budget — pension spending above 6% of GDP and the IMSS and ISSSTE allocations
• Pension Policy International, pensions, retirement age and gender inequality — PEF 2026 pension share of GDP and of net spending, OECD comparison
• Welfare Ministry briefing via Mohuawang — 13.7 million old-age beneficiaries, 2.8 million women registered, 42.8 million total
• El Pais, changes to IMSS Modalidad 40 — decree of 21 October 2026, one-UMA limit and UMA value
• IMARC Group, Mexico geriatric healthcare market — US$20.58 billion market size for 2025

This article was prepared by the expert team at Global Infinity Labs, drawing on insights and data provided through its MCP data services.

About Global Infinity Labs

Global Infinity Labs is an AI innovation company specializing in MCP data services.

Email: support@globalinfinitylabs.com

source https://newsroom.seaprwire.com/press-releases/finance/mexico-is-ageing-on-an-income-it-cannot-retire-on-and-the-budget-already-shows-it/

Satlyt’s In-Orbit Scheduling Test Worked. Sharing Compute Between Satellites Is Still Unbuilt

SeaPRwire – The experiment Satlyt ran earlier this month used exactly one computer in space. It sat aboard a spacecraft, worked through a simulated network of four computing hosts, four users and eight services, and sent its answers back to Earth. The other three machines in the scenario existed only as numbers on that one.

What the run establishes is narrower than the phrase “space data center” implies, and more useful than a demo. The software produced a scheduling plan on orbit, using the compute that was actually available where the hardware physically was, instead of modelling the problem on a ground machine and calling that a result. Thirteen months of engineering went into reaching that point.

The scheduling model works through declarations rather than approvals. Operators set permissions, priorities and operating limits, and the software assigns tasks inside those bounds. Afullo’s description of it is precise on this point: users “will only need to define permissions, priorities, and operating limits.” Nobody signs off on each assignment. The operator writes the fence, and the system stays inside it.

That design choice carries the main unresolved question for this class of software. A fence wide enough to be useful is also wide enough to permit an assignment the operator would have refused if asked. The test did not probe that boundary, because probing it requires workloads and hardware that the single-computer setup did not have.

The result Afullo reports is a trade-off instead of a win. One of the approaches available to the scheduler performed best and consumed more computing power than the alternatives. On a spacecraft, where power and thermal headroom are the binding constraints and neither can be upgraded after launch, “best” and “affordable” rank differently. A scheduler that ignores the difference produces plans the satellite cannot execute.

The test also turned up a defect of the kind that a ground simulation tends to hide. The software was stamping communication delay by arrival time, the moment data showed up, rather than by elapsed delay, how long it took to get there. The two numbers diverge exactly when a scheduler has to decide between waiting for a link and reassigning the work to another computer. Afullo treats the fix as a correction, not a failure, and the record supports him: development, onboard execution and the return of outputs all completed.

Context for how much of the problem this solves: NASA already operates a network built to move data through space when links are delayed or intermittent. It went into use earlier this year and has been tested on aircraft. That layer answers whether bits arrive. Satlyt’s layer answers who computes what, and its answer has to change as the link changes. The second question is only interesting once the first has a working answer, which is roughly where satellite operators are now.

The wildfire example is the one Afullo reaches for, and it is a fair illustration of the economics rather than a description of a deployed product. A spacecraft that sees a fire can send raw imagery down and wait for a ground team, spending a communication window on pixels, or it can run detection onboard and send a shorter answer. Earth observation operators have been doing onboard processing for years. What Satlyt is selling is not detection; it is the coordination layer that would let one job be split across several spacecraft when no single one has the compute or the connectivity to finish it alone.

Its software is on three satellites in orbit. The research behind the test was NASA-funded and run with the University of Houston, and the agency has not selected Satlyt for a mission or chosen to deploy the technology. That distinction matters for reading the result. This is a company validating its own planning component inside an agency-funded research project, not an operational system whose output anyone depends on yet.

The list of what remains, in Afullo’s own account, is specific: usable communication links, permission from the operators of participating spacecraft, secure transfers between them, resource scheduling across a fleet, and recovery when a node drops out. The first item on that list is not a software problem, and the second is not either. Cross-operator compute sharing asks satellite owners to accept that another company’s scheduler will direct work on their hardware, under limits they wrote but cannot watch in real time.

Multi-spacecraft transfer is the untested part. Every result so far comes from a single physical machine reasoning about machines that were not there. Satlyt says it will test its software under various workloads, hardware and connectivity conditions before attempting that, and it is researching applications beyond low Earth orbit, including 4K video streaming from the Moon through the NASA-funded work.

The company raised $8 million and reached the top five of TechCrunch Disrupt Battlefield this year, which is a reasonable amount for a scheduling layer and a small amount for a constellation. The longer-term ambition Afullo describes is the standard platform argument: developers write applications for orbit without rebuilding infrastructure for each mission. It is also the hardest version of the argument to deliver in a domain where the hardware is fixed at launch and the network topology changes with orbital mechanics.

Hardware heterogeneity is the constraint that has not been priced. A scheduler assigning work across spacecraft has to model what each node can do, and satellites launched in different years carry different processors, different power budgets and different thermal designs. The test avoided this by simulating four hosts that were interchangeable. Operators running a mixed fleet, which is most of them, would be asking the software to plan across machines it has never benchmarked, and the plan is only as good as the assumptions behind it.

The next milestone is a demonstration that spans separate spacecraft. Until one exists, the accurate description of Satlyt’s software is a scheduler that has been shown to generate a plan on one computer in orbit, and has not yet been shown to work as a network.

source https://newsroom.seaprwire.com/press-releases/technologies/satlyts-in-orbit-scheduling-test-worked-sharing-compute-between-satellites-is-still-unbuilt/

What the Ofcom Information-Notice Ruling Actually Decides, and What It Leaves Open

SeaPRwire – Five grounds went into the Divisional Court. Four of them never reached a hearing on their merits. That procedural detail is the part of the 30 October judgment worth understanding first, because it decides how much of the platforms’ argument was actually tested and how much was simply refused at the gate.

Under the Online Safety Act 2023, section 100 lets Ofcom require regulated services to hand over information the regulator needs to carry out its functions. Meta and WhatsApp, X and TikTok each received notices and each brought judicial review. The judgment, from Lord Justice Singh and Mrs Justice Collins Rice, is reported as [2026] EWHC 2779 (Admin), and it is the first judicial examination of that power.

The four grounds that failed at the permission stage were the argument that the notices circumvented the Act’s separate transparency regime, the argument that the information was not genuinely “required,” the argument that Ofcom had skipped an impact assessment under section 7 of the Communications Act 2003, and, for TikTok alone, predetermination. Permission was refused because the court considered those grounds unarguable, which is a lower bar than being wrong: a ground refused permission does not get argued out in open court, and the reasoning behind the refusal is correspondingly thin.

Proportionality survived that filter. The companies framed it under both section 100(4) and the European Convention on Human Rights, the court granted permission, heard it in full, and rejected it. So of five complaints, exactly one was examined on the evidence, and it lost.

The finding inside that single ground is where the judgment will be cited. The platforms said compliance would impose an extraordinary burden. The court found the evidence offered in support lacked “pertinent substance,” meaning it did not show in concrete terms why the demands were excessive. Read that as a statement about the quality of the record rather than about the size of the burden: the court did not conclude the burden was small, it concluded the platforms had not demonstrated it.

For anyone advising a regulated service on how to resist a section 100 notice, that is the operative paragraph. Expense and complexity are not self-proving. A notice running to hundreds of pages may well cost a great deal to answer; a court will want the costed version, itemised against the specific requests, before it weighs that cost against the regulator’s need. The judgment rewards a company that can produce engineering time estimates, headcount allocations and per-request breakdowns, and penalises one that asserts scale.

What the ruling does not establish is more extensive than what it does. It says nothing about whether the information Ofcom sought was the information it should have sought, only that its decision on that question survives a proportionality review on the record before the court. It says nothing about how Ofcom uses the material, or what standard applies when the data becomes the basis of a breach investigation. Those questions remain where they were.

The transparency argument deserves a note, because it is the one with the widest potential reach. The Act gives Ofcom a separate transparency regime with its own procedures for public reporting, and the companies argued that the information notices were an attempt to route around it. The court found that unarguable. If that conclusion holds through any appeal, the practical effect is that Ofcom can gather material for its own purposes without triggering the disclosure obligations attached to the transparency route, and the two channels stay legally distinct.

Two disputes sit outside this judgment. Meta’s separate challenge to the way fees and penalties are calculated by reference to worldwide revenue is still before the courts, and it addresses a different power: not what Ofcom may ask for, but what it may charge. The platforms may also seek permission to appeal the 30 October decision, which would put the proportionality finding in front of the Court of Appeal and test whether the evidential threshold was set correctly.

The wider read-across is a matter of institutional design rather than of this case. Section 100 is a demand power exercised without prior judicial authorisation. A regulator decides what it needs, issues a notice, and the company either complies or litigates after the fact, which is why the permission stage matters so much: the four grounds that never got heard are the four arguments a regulated service would most want to make. Jurisdictions drafting equivalent regimes will look at how little of the challenge survived, and at how narrow the surviving ground turned out to be.

One asymmetry is worth naming. Because four grounds were refused permission, the court’s reasoning on them exists mainly as a refusal rather than as a reasoned judgment, and a refusal is harder to appeal and harder to rely on in the next case. The proportionality finding rests on a full hearing and a developed record, which makes it the part later litigants can actually use. That is an odd result for a first test of a statutory power: the narrowest ground produced the most durable holding.

What to watch is unglamorous. Whether an appeal is filed. Whether the pending fee challenge produces a different result on a power the court has not yet construed. Whether the data collected under these notices shows up in enforcement action, which is the only test of whether the information was worth demanding. And whether the next company served with a section 100 notice answers it, or spends the effort to build the costed record that this judgment says is required to resist one.

The notice power is not self-executing either. What a platform must produce, in what format and by what date are set by the notice itself, and nothing in this judgment constrains how broadly the next one may be drawn. A ruling that upholds one set of demands says little about the scope of the following set.

The ruling tells regulators their information powers will be enforced and tells companies what kind of evidence it takes to push back. It does not tell anyone whether the requests were well judged, and the court was not asked to answer that.

source https://newsroom.seaprwire.com/press-releases/policy-analysis/what-the-ofcom-information-notice-ruling-actually-decides-and-what-it-leaves-open/