I. Overview and Methodological Context
The Ministry of Finance’s February 2026 Occasional Paper — the first such update since August 2015 — represents a significant expansion in Singapore’s official statistical toolkit. The paper reviews trends in income growth, inequality, and social mobility in Singapore, and incorporates new data on household market income and wealth to provide a more complete picture of household income and wealth. Ministry of Finance This methodological expansion is itself analytically significant: the 2015 paper relied exclusively on employment income among employed households, a measure that systematically excluded retirees, the self-employed drawing primarily from assets, and households dependent on non-employment income. By broadening the coverage, the paper opens itself to findings that are simultaneously more accurate and, in certain dimensions, more uncomfortable.
A key change from previous reports is that the measure of household income has been expanded to that of “market income,” which includes both employment and non-employment income — such as investments, rental, contributions from other households, and pensions. The coverage of resident households has also been broadened to include both non-employed and employed households. Mothership.SG This matters enormously for interpretation: including non-employed retiree households mechanically raises the measured Gini coefficient even if there is no actual change in distributional dynamics. The paper navigates this by presenting both the old and new metrics in parallel, but readers must remain attentive to which denominator is being used at each point in the argument.
II. The Income Growth Findings: Genuinely Encouraging, with Important Caveats
Broad-Based Real Growth
The headline finding is unambiguously positive. The annualised growth in average real household market income per member between 2015 and 2025 was 4.8 per cent for those in the bottom decile, 3 per cent at the fifth decile, and 0.4 per cent for the top decile. Asia News Network This inverted gradient — where growth rates are higher at the bottom of the distribution — is precisely what economists mean by “pro-poor growth,” and it is genuinely uncommon among advanced economies over the same period, many of which saw median real wage stagnation.
Singapore’s strong 2025 economic performance, buoyed by AI-driven manufacturing demand, masked growing structural strains in its labour market, including skills mismatches, modest retraining uptake, and uneven unemployment across age groups. East Asia Forum This tension between the aggregate headline and the structural underbelly is the defining analytical problem of the paper. The pro-poor income growth story is real, but it coexists with labour market vulnerabilities that may not yet be fully legible in the cross-sectional data.
The Progressive Wage Model’s Contribution
The paper points to targeted labour market interventions as key drivers. The Progressive Wage Model (PWM) — which mandates wage increases tied explicitly to skills upgrading and productivity improvements in specific sectors — is credited alongside the Workfare Income Supplement (WIS) as the primary institutional mechanisms for compressing the bottom of the income distribution. The Workfare Income Supplement and Workfare Skills Support schemes complement the PWM by topping up the income and CPF savings of lower-wage workers and supporting their skills upgrading. BY
This is a meaningfully different architecture from a statutory minimum wage. Rather than a wage floor, it creates a sectoral wage ladder, with the expectation that productivity investments will validate the higher wage costs. The conceptual elegance is real, but so is the empirical challenge: productivity improvements in sectors like cleaning, security, and landscape services are notoriously difficult to measure and verify, raising questions about whether the PWM is generating genuine value creation or redistributing rents in a way that may not prove durable when fiscal co-funding (through the Progressive Wage Credit Scheme) is withdrawn.
A Methodological Warning About Cross-Sectional Comparisons
The paper is admirably transparent that charts on income growth are based on cross-sectional comparisons over the time period, and not longitudinal comparison. BY This is a critical caveat that deserves more prominence in public discussion. A cross-sectional comparison comparing the bottom decile in 2015 to the bottom decile in 2025 does not track the same households: the individuals in the bottom decile may have changed entirely through mobility, migration, or demographic composition effects. True longitudinal analysis — tracking the same households or cohorts over time — is the appropriate tool for assessing whether households at the bottom have actually experienced upward trajectories. The intergenerational mobility data (discussed below) provides some longitudinal grounding, but the income growth claims remain vulnerable to compositional artifacts.
III. Income Inequality: The Gini Decomposition and Its Limits
The Headline Numbers
The Gini coefficient, after tax and transfers and based on household employment income, has improved from 0.409 in 2015 to 0.359 in 2025. The Gini coefficient after tax and transfers and based on household market income has also improved from 0.437 in 2015 to 0.379 in 2025. Ministry of Finance These are substantial declines by any measure, and PM Lawrence Wong is justified in describing the current income Gini as the lowest on record. In real terms, households in the lowest decile saw a 10.5 per cent increase over the last five years compared to 1.4 per cent for the highest decile. BusinessToday
The Role of Transfers: Redistribution or Substitution?
What the headline Gini figures do not adequately foreground is how much of this compression is attributable to market income trends versus fiscal transfers. In 2025, each household member received an average of $7,300 in government transfers, though this was lower than the $7,725 in 2024 due to the end of one-off schemes introduced in 2024. The Star The year-on-year volatility in transfer magnitudes — driven by Budget-cycle decisions rather than structural policy — means that the post-transfers Gini is partly a function of electoral and fiscal timing rather than durable institutional change. Resident households in one and two-room HDB flats received an average of $16,519 per household member, more than double the average amount received by all resident households. Mothership.SG
A more penetrating question is whether Singapore’s transfer architecture, designed around targeted, means-tested support, is appropriate for the distributional challenges ahead. The paper notes that Singapore has taken a different approach from Nordic economies, maintaining a relatively low overall tax burden for the majority while providing targeted support to those who need it most. BY This is defensible as fiscal policy, but it does involve trade-offs: the targeting model is administratively intensive, can stigmatize recipients, and may leave significant gaps for households that are marginally above assistance thresholds but still economically precarious — the phenomenon of the “missing middle.”
The Absolute Income Gap: The Gini’s Blind Spot
The difference in average income between the top and bottom decile was $11,538 in 2014, but was $14,857 in 2024 — the highest figure during this period. Smart Wealth This is the distributional reality that the Gini coefficient, as a summary statistic, obscures. The Gini can fall — as it has — while the absolute income gap simultaneously widens, because proportionate gains at the bottom are compatible with larger absolute gains at the top. For households making consumption and investment decisions in a high-cost city-state where housing, education, and healthcare prices are tied to absolute rather than relative wealth, this widening absolute gap is the economically and socially relevant fact.
IV. The Wealth Gini: Singapore’s New Uncomfortable Truth
The First Official Estimate
The wealthiest 20 per cent of resident households held an average net wealth of S$5.3 million in 2023, with property assets averaging S$3.4 million per household in the top quintile. The Online Citizen This is a striking figure, and its disclosure for the first time in official statistics marks a significant shift in Singapore’s political economy of data transparency.
The key metric, the Gini coefficient for wealth, is estimated at 0.55, significantly higher than the Gini coefficient for income, which stands at 0.38 after government taxes and transfers. Malay Mail The paper compares this favorably to the UK, Japan, and Germany (0.6 to 0.7), but this comparison demands careful scrutiny. As the paper itself concedes in Annex B, CPF balances constitute approximately 22 per cent of household wealth in Singapore and are directly attributable to individuals as defined-contribution savings. In contrast, state-funded defined benefit pension systems in Germany, for example, are typically excluded from household wealth estimates because they operate on a pay-as-you-go basis. A simulation exercise by the Bundesbank suggests that if statutory pensions were capitalised and included as wealth, Germany’s household wealth Gini would fall from 0.72 to 0.58 BY — a reduction that would bring it broadly in line with Singapore’s 0.55. The cross-country comparison, in other words, is structurally inflated for CPF-system countries relative to defined-benefit countries.
Under-Reporting and the Upward Bias Risk
MOF cautioned that wealth data may be affected by under-reporting: some respondents may have chosen not to disclose sensitive financial information or had difficulty recalling details. If under-reporting is more prevalent among wealthier households, wealth at the top of the distribution is likely underestimated. The Online Citizen This is not a minor qualification. The academic literature on wealth inequality measurement (Alvaredo, Piketty, Saez, Zucman) has consistently found that survey-based wealth data substantially undercounts top-end wealth compared to administrative tax records, financial account data, or the Forbes-style billionaire lists used as upper-bound validators. Singapore’s financial confidentiality framework — its status as a premier wealth management and private banking hub — creates structural incentives for non-disclosure precisely among the population whose wealth most affects the Gini.
Housing Wealth: Asset or Equity Trap?
The dual role of housing in Singapore’s wealth picture deserves particular attention. HDB home ownership functions simultaneously as a vehicle for mass wealth accumulation and as a potential mechanism for wealth stratification between cohorts. Households that purchased HDB flats in the 1980s and 1990s at controlled prices have seen significant capital appreciation; younger households entering the market post-2010, when resale prices have been substantially higher, have a much weaker appreciation potential relative to their acquisition cost. This intra-cohort divergence in housing wealth accumulation is not visible in the cross-sectional Gini estimate, but it represents a potentially significant source of intergenerational wealth stratification that will compound over time.
V. Social Mobility: The Most Uncomfortable Finding
The Moderation of Relative Mobility
This is where the paper’s “broadly reassuring” framing is most strained. The data shows a deceleration in relative social mobility. MOF analysed different birth cohorts and found a rising proportion of children from the poorest households remaining in the lowest income bracket as adults. For children born between 1985-1989, 25.3 per cent stayed in the same low-income station as their fathers, up from 24.2 per cent for those born in 1978-1982. Malay Mail
This is a modest but directionally significant finding. The income rank correlation coefficient — the standard measure of intergenerational persistence — has risen across successive birth cohorts, meaning that parental income is becoming increasingly predictive of children’s income outcomes. Dr. Mathew Mathews of the Institute of Policy Studies observed that as the economy matures, family background becomes “more influential over time,” highlighting the risk that wealth and income gaps compound across generations. Malay Mail
Absolute vs. Relative Mobility: A Critical Distinction
The paper is careful to distinguish between absolute and relative mobility, and the distinction matters enormously. Absolute mobility — whether children earn more than their parents in real terms — remains high because Singapore’s overall economic growth has lifted most boats. Relative mobility — whether children’s income rank relative to peers is determined by their parents’ income rank — is declining. For a small, mature, high-income city-state, the absolute mobility path naturally flattens as diminishing returns set in; what replaces it as the politically salient metric is relative mobility, and that is precisely what is showing deterioration.
Education: The Escalator That Is Slowing
An increasing proportion of each cohort has attained higher levels of education and skills, matched by a rising share of Professionals, Managers, Executives, and Technicians in the resident workforce — from 54.4 per cent in 2015 to 64.2 per cent in 2025. BY This credential expansion has historically been Singapore’s primary social mobility engine: the first post-independence generation was able to use education as a genuine escalator because the baseline was low and the economic structure was expanding rapidly into higher-skill sectors.
As credentials become near-universal at the tertiary level, their signalling value differentiates by quality of institution and field rather than mere attainment. In a relentlessly competitive school system, there are concerns that heavy reliance on private tuition — involving 70 per cent of students — contributes to unequal educational outcomes and diminished social mobility by giving an advantage to those whose families can afford the extra expenditure. Atlantic Council The shadow education system — the tuition industry — transforms parental wealth directly into academic performance, partially hollowing out the meritocratic architecture that underpins Singapore’s social contract.
The Structural Limit of Productivity-Led Mobility
Translating education into broad-based opportunity is uneven since the economic structure does not generate enough high-productivity, middle-income jobs for residents outside elite tracks. Without stronger productivity growth at the firm level — driven by job redesign, automation, and diffusion of best practice — credentials do not guarantee commensurate wages. Atlantic Council This structural mismatch between credential supply and job quality demand is the medium-term threat that no amount of tuition subsidy can resolve. It requires a more fundamental transformation of the productive structure of the economy.
VI. Forward-Looking Risks and Policy Adequacy
Technological Disruption and Asymmetric Exposure
The paper acknowledges that technological and global economic shifts could produce more frequent employment disruptions. What it does not adequately quantify is the asymmetric distributional impact of automation: routine cognitive and manual tasks — concentrated in the middle and lower segments of the income distribution — face higher displacement risk than high-skill non-routine cognitive work. If the PWM’s productivity-wage linkage is disrupted by automation of the sectors it covers, the mechanism through which lower-wage income gains have been sustained could weaken precisely when other drivers of mobility are already moderating.
Demographic Pressures on the CPF Model
The CPF system’s adequacy for retirement income is under increasing strain from longevity risk. With residents living well past traditional retirement ages, CPF LIFE annuity payouts — the primary non-employment income for the bottom decile — face actuarial pressure that eventually requires either higher contribution rates, lower replacement ratios, or fiscal top-ups. This has direct implications for both income inequality measurement and for the material living standards of lower-wealth retirees.
The Inequality-Immigration Nexus
There is a continued reluctance to diverge from prevailing policy orthodoxies. Households continue to disproportionately bear macroeconomic, longevity and inflation risks. East Asia Forum The calibration of foreign manpower policy — particularly the Employment Pass and S Pass thresholds — directly affects the distributional outcomes for resident workers at different skill levels. The paper treats this largely as a technical labour market management question, but the political economy of the foreign-local wage differential is a material driver of both perceived and actual inequality, particularly for mid-skill residents who compete most directly with foreign professionals.
The Fiscal Architecture’s Sustainability Question
Singapore has been trying to navigate a tricky balance, striving to keep inequality low without excessively taxing the rich, including high net worth foreigners. PM Wong’s government has raised taxes on high-end property and cars and warned that Singapore risks losing out to other hubs seeking to woo wealthy foreigners if it is too heavy-handed. Free Malaysia Today This tension is structurally unresolvable at the extremes: the revenue base for redistribution ultimately depends on taxation of wealth and high income, but Singapore’s competitive position as a global wealth hub depends on maintaining a comparatively attractive tax environment for mobile capital. The marginal cost of this trade-off has increased as the distributional pressures the paper documents have intensified.
VII. Synthesis: What the Paper Tells Us, and What It Doesn’t
The MOF Occasional Paper is a commendably transparent document by the standards of official statistics in developed Asia. Its disclosure of the wealth Gini for the first time, its acknowledgment of declining relative social mobility, and its candid treatment of measurement limitations reflect a governing administration willing to confront uncomfortable data publicly. The broad conclusion — that Singapore is in a stronger position than most comparators, but faces real structural pressures — is analytically defensible.
What the paper does not provide is a theory of political economy capable of addressing the tensions it identifies. The “whole-of-society effort” framing in its final section displaces structural policy choices onto voluntarism and philanthropic goodwill. The education investment commitments, while worthwhile, address symptoms rather than the structural mismatch between credential supply and job quality. And the fundamental fiscal constraint — that deep redistribution requires either higher taxes on wealth and high income or reduced competitiveness as a wealth hub — remains unaddressed rather than resolved.
The paper’s most important intellectual contribution may ultimately be its implicit reframing of the policy horizon: Singapore can no longer rely on absolute economic growth as the primary vehicle for social inclusion. As the economy matures and absolute mobility naturally slows, maintaining the social contract will require more active distributional intervention — not merely faster growth distributed less unequally than peers, but a deliberate architectural redesign of how wealth, opportunity, and risk are allocated across generations. Whether the political will exists to make that transition, given the constraints the paper itself describes, is a question that belongs to Singapore’s citizens as much as to its technocrats.