## fmc1 ## Source details **Canonical URL:** [fmc1](https://www.imf.org/-/media/files/publications/fiscal-monitor/2017/october/pdf/fmc1.pdf) ## Other formats - [Markdown version](/-/media/files/publications/fiscal-monitor/2017/october/pdf/fmc1.pdf.md) - [Structured JSON version](/-/media/files/publications/fiscal-monitor/2017/october/pdf/fmc1.pdf.json) --- ### Overview and Key Questions - Global inequality declined substantially over the past three decades; within‑country inequality trends are mixed. - Focus: how fiscal policy can address high inequality while minimizing efficiency‑equity trade‑offs; primary focus on income inequality (disposable income or consumption, Gini coefficient). - Key policy questions: - Evolution and scope to increase income tax progressivity without hurting growth; role of wealth taxes. - Case for universal basic income (UBI) versus strengthening means‑tested transfers; financing options. - Policies to expand access to quality education and health to close opportunity gaps. ### Data, Methods, and Analytical Framework - Evidence sources: theoretical and empirical literature, IMF work, country experiences, static microsimulations on household survey data, dynamic general equilibrium simulations calibrated to country‑specific data. - Main inequality measure: Gini coefficient for disposable income (unless specified otherwise). - Welfare decomposition: Atkinson’s monetary measure (equally distributed equivalent income, EDEI) used to decompose social welfare changes into growth and inequality contributions. ### Inequality Trends and Drivers — Key Findings - Global and between‑country: - Global inequality in 2015 ranged from 0.63 to 0.69. - Differences in per capita income between countries accounted for about 65 percent of global inequality in 2013. - Between‑country inequality declined sharply over the past three decades driven by emerging market economies (notably China and India). - Within‑country: - Over the past three decades, 53 percent of countries saw increased income inequality; some increases exceeded two Gini points. - Most advanced economies experienced sizable increases driven primarily by top 1 percent income gains. - Regional patterns: - Eastern Europe and Central Asia: increase during postcommunist transition, decline afterward. - Latin America and the Caribbean: increase in 1980s–1990s then sharp decline; remain among the most unequal. - Sub‑Saharan Africa: average decline in inequality with diverse country experiences. - Identified drivers: - Global factors: technological progress, globalization, commodity price cycles (skill premium, job polarization). - Country factors: economic developments, domestic policies, recessions (example: EU Great Recession: bottom decile income loss of 17 percent relative to precrisis level). - Wealth implications: top income upswing plus high saving rates increased wealth inequality. ### Growth, Inequality, and Social Welfare — Findings - Many advanced economies saw rising inequality amid low growth over 1985–2015. - Emerging markets: growth often benefited all deciles even when inequality rose. - Regional poverty reduction: - East and South Asia and the Pacific: large poverty reductions 1985–2015 due to high growth. - Sub‑Saharan Africa and Latin America: sustained declines in absolute poverty with strong growth. - Empirical claim: promoting growth and reducing inequality can coexist; cross‑country regressions do not clearly identify specific policies that both raise growth and reduce inequality. ### Fiscal Redistribution: Mechanisms and Evidence - Mechanisms: - Progressive direct taxes and transfers lower disposable income inequality relative to market income. - Consumption taxes affect “real” disposable income inequality. - In‑kind transfers (education, health) reduce “full income” inequality and affect market income over time via human capital. - Advanced economies: - 2015 average Gini (disposable income) = 0.31; market income Gini = 0.49. - Direct taxes and transfers reduce inequality by about one‑third on average. - About three‑quarters of redistribution from transfers; public pensions ~ half of transfer effect. - In‑kind transfers lowered Gini by 5.8 points in five European economies (health 3.6 points; education 2.2 points). - Emerging market and developing economies: - Much lower magnitude of taxes and transfers → much lower redistribution. - Income taxes and transfers reduced Gini by 0.17 in advanced economies versus 0.03 in Latin America (sample). - Coverage of poorest 40 percent receiving any public transfer is very low except in emerging Europe and Latin America and the Caribbean. - ASPIRE evidence: median Gini reduction from transfers ~ two points in Latin America and the Caribbean and Middle East and North Africa; < one point in other regions. - Policy emphasis: design taxes and transfers jointly to minimize efficiency costs. ### Tax Progressivity and Capital Taxation — Evidence and Interpretation - Decline in PIT progressivity: - OECD average top statutory personal income tax rate fell from 62 percent in 1981 to 35 percent in 2015. - Median progressivity measures fell steeply in 1980s–1990s; broadly stable since. - Optimal tax considerations and empirical findings: - No evidence of rising income tax elasticity for top earners over time; Pareto index for top 5 percent shows downward trend (greater top shares). - Illustration parameters: average income tax elasticity = 0.4; Pareto index = 2.2; optimal marginal income tax rate (with welfare weight zero for very rich) = 44 percent. - Example social welfare marginal weight for top earners cited: 0.38. - Conclusion: scope exists for increasing PIT progressivity without significant growth costs; political constraints remain. - Capital income taxation: - Capital income is more unequally distributed and has risen; capital gains can be a large share of top incomes (example: US top 400 in 2014 received 60 percent from capital gains). - Theoretical and empirical arguments justify lower capital taxation but also imply lower optimal capital tax when elasticity is high. - Optimal capital tax formula: t_K* = (1 − g_K) / (1 − g_K + e_K); revenue‑maximizing t_K^R = 1 / (1 + e_K) if marginal welfare weight = 0. - Corporate tax role: tax reinvested earnings and mitigate income‑shifting; downward trend in corporate tax rates due to competition. ### Fiscal Transfers: Universality vs Means‑Testing; UBI Assessment - Tradeoffs: - Means testing: more targeted, lower fiscal cost, requires administrative capacity, risks work disincentives from steep benefit phase‑outs. - Universal transfers (UBI): broader coverage, leakage to nonpoor, high fiscal cost, potential labor supply disincentives. - UBI partial equilibrium calibration examples (Annex 1.6 and simulations): - UBI calibrated at 25 percent of median per capita income (additional to existing programs; no behavioral responses): - Average reduction in inequality: 5.3 Gini points (selected emerging market and developing economies). - Average reduction in relative poverty: about 10.4 percentage points. - Gross fiscal cost examples: - Selected advanced economies: about 6½ percent of GDP. - Selected emerging market and developing economies: about 3¾ percent of GDP. - Annex 1.6 country sample (UBI = 25 percent of net median market income; full coverage, variant (1)) — selected results: - Brazil (2013): Gross Fiscal Cost = 4.6; Reduction in Gini = 0.05; Initial Poverty Rate = 19.0; Reduction in Poverty Rate = 4.1; Annual UBI per person = R$1,286. - Egypt (2012): Gross Fiscal Cost = 3.5; Reduction in Gini = 0.06; Initial Poverty Rate = 18.55; Reduction in Poverty Rate = 10.4; Annual UBI = LE 725. - France (2010): Gross Fiscal Cost = 6.8; Reduction in Gini = 0.04; Initial Poverty Rate = 9.49; Reduction in Poverty Rate = 6.3; Annual UBI = €2,122. - Mexico (2012): Gross Fiscal Cost = 3.7; Reduction in Gini = 0.06; Initial Poverty Rate = 19.68; Reduction in Poverty Rate = 12.0; Annual UBI = Mex$4,994. - Poland (2013): Gross Fiscal Cost = 4.9; Reduction in Gini = 0.04; Initial Poverty Rate = 10.70; Reduction in Poverty Rate = 6.9; Annual UBI = Zl 2,111. - South Africa (2012): Gross Fiscal Cost = 2.3; Reduction in Gini = 0.05; Initial Poverty Rate = 23.65; Reduction in Poverty Rate = 10.8; Annual UBI = R1,584. - United Kingdom (2013): Gross Fiscal Cost = 6.7; Reduction in Gini = 0.04; Initial Poverty Rate = 9.28; Reduction in Poverty Rate = 6.0; Annual UBI = £1,839. - United States (2013): Gross Fiscal Cost = 6.4; Reduction in Gini = 0.05; Initial Poverty Rate = 17.42; Reduction in Poverty Rate = 10.1; Annual UBI = US$3,516. - Budget‑neutral variants: replace existing noncontributory transfers or raise direct/indirect taxes; outcomes depend critically on financing modality and administrative capacity. - General equilibrium model findings (US and Bolivia calibrations): - US calibration: higher efficiency cost when financing via progressive PIT vs VAT; as inequality aversion rises, UBI financed with progressive taxation may be preferable to VAT financing; EITC expansion yields higher welfare than UBI with equivalent fiscal cost; for high inequality aversion, EITC dominates. - Bolivia calibration: due to informality and low PIT capacity, UBI costs to efficiency can be offset by gains to groups even at low inequality aversion; nonetheless, UBI may not be optimal without deeper analysis. ### Education and Health — Equalizing Opportunities and Policy Actions - Education: - Gender enrollment gaps largely closed except in low‑income developing countries. - Socioeconomic status remains key determinant of access across early childhood, secondary, tertiary levels; disadvantaged students underperform advantaged peers. - Public education spending is on average pro‑poor in advanced economies; often pro‑rich in emerging market and low‑income countries; tertiary spending tends to be regressive. - Reallocating resources toward disadvantaged students/schools can reduce education inequality and raise overall outcomes without increasing total budgets. - Health: - Socioeconomic gaps in health outcomes persist; life‑expectancy gaps by education in advanced economies: males with tertiary versus lower secondary education range from about 4 years (Italy) to 14 years (Hungary). - Eliminating inequalities in basic health coverage could raise life expectancy by 1.3 years on average in low‑ and middle‑income countries (simulation based on Annex 1.7). - Public health spending is often pro‑rich in benefit incidence; out‑of‑pocket spending remains high in low‑income and emerging market economies. - Policy instruments: - Expand universal basic and secondary education; promote equality of opportunity in tertiary education via income‑contingent loans and targeted subsidies. - Prioritize universal health coverage of essential services; use targeted subsidies and preventive care; improve quality and access in underserved areas. - Tax unhealthy behaviors (tobacco, alcohol, fossil fuels) and reallocate revenues to progressive spending for both efficiency and distributional gains. - Improve efficiency by curbing regressive tax incentives, enhancing governance, and reallocating resources to cost‑effective services. ### Taxation, Administration, and Redistribution Recommendations - Enhance PIT progressivity where administratively feasible; consider raising marginal rates at the top in countries with relatively low top rates. - Strengthen enforcement to reduce avoidance and evasion; cap or eliminate selective deductions that favor the wealthy. - Tax immobile capital (real estate and land) more effectively; consider recurrent property or net wealth taxes, transaction, inheritance and gift taxes where administratively viable. - Use consumption taxes paired with excises on luxury goods and goods with negative externalities to finance progressive spending; combine with targeted measures to offset regressivity. - In lower administrative capacity contexts: - Set a relatively high PIT exemption threshold and expand PIT coverage gradually as capacity improves. - Consider UBI or targeted universal subgroups (children, elderly) where transfers perform poorly and financing can be progressive. ### UBI Scenarios, Fiscal Costs, and Robustness - Baseline UBI projections and partial equilibrium findings: - UBI at 25 percent of net median market income produces average Gini reductions of about 5 Gini points and notable poverty reductions; gross costs average 6½ percent of GDP for selected advanced economies and 3.8 percent for selected emerging markets. - Financing modalities substantially affect efficiency and distribution: - Financing with VAT reduces efficiency and is regressive; financing with more progressive PIT has larger efficiency costs (greater investment decline) but may be preferable for high inequality aversion. - Targeted instruments like EITC produce larger welfare gains and labor supply benefits than equivalent‑cost UBI in US calibration. ### Global Inequality Projections and Scenarios - Baseline projection (within‑country inequality unchanged; UN population and per capita income projections): - Global Gini declines from 0.69 in 2015 to 0.66 in 2035. - Income ratio 90th/10th percentile: 25 in 2035 (compared with 28 in 2015). - Number of people with annual incomes of $2,000–$20,000 increases by 1.78 billion (largest gains in China, India, Latin America and the Caribbean). - Most population growth in sub‑Saharan Africa remains among incomes < $2,000. - Alternative scenarios: - Kuznets‑type within‑country improvements → global Gini reaches 0.63 in 2035. - For global inequality to remain stable, within‑country Gini would need to worsen by 6.6 Gini points in each country. - More pessimistic growth scenario (real GDP growth revised downward by about half a standard deviation) → global Gini = 0.67. - Faster emerging market growth (half a standard deviation faster) → additional 1.1 Gini point decline. - Structural reforms in emerging markets (IMF 2017b) → additional 0.5 Gini point decline. ### Methodological Notes and Key Elasticity/Regression Results - Income tax elasticities estimated for 35 countries, 1981–2016; median difference‑in‑differences elasticity = 0.40 (top 1 percent/top 2–5 percent comparison). - Growth regressions (OECD, 1981–2016) generally find progressivity measures nonsignificant for growth; robustness checks (five‑year intervals, quantile regressions) do not change this general conclusion. - Welfare (EDEI) dominated by mean income; correlation between mean income and EDEI remains very high across inequality‑aversion parameters (e.g., correlation = 0.999 for γ = 0.22; 0.953 for γ = 2.0). *Source: fmc1 - Introduction and CHAPTER 1 “Tackling Inequality,” Fiscal Monitor (International Monetary Fund | October 2017).* ### Introduction ### fmc1 - Introduction ### Overview - Inequality assessed across countries versus within countries produces starkly different pictures. - Global inequality has declined substantially over the past three decades, reflecting income convergence between developing and advanced economies aided by globalization and technological advancement. - Inequality within national boundaries presents a mixed picture: some countries have seen reductions while others, particularly advanced economies, have experienced significant increases. - Rising inequality in advanced economies, together with job insecurity and stagnating real incomes for a segment of the population, has led to growing public backlash against globalization. - Focus of this Fiscal Monitor: how fiscal policy can help governments address high inequality while minimizing potential trade-offs between efficiency and equity, with primary focus on income inequality (data available for a large sample of countries and relatively long periods). Other measures—wealth inequality, inequality of opportunity, and gender inequality—are also discussed and tend to be highly correlated. ### Key policy questions addressed - How has income tax progressivity evolved, and can it be increased without adversely affecting growth? Should marginal income tax rates be increased for high-income individuals given increased mobility of capital and high-income individuals? Is a wealth tax a good alternative? - Is there a case for adoption of a universal basic income (UBI)? Under what circumstances could a UBI be desirable, and how could it be financed? Or should governments focus on strengthening capacity to use means-tested transfers? - Why is expanding access to quality education and health services important for addressing income inequality? What policies can governments adopt for closing health and education gaps? ### Data and methods - Analysis relies on theoretical and empirical literature, IMF work on inequality and fiscal policy, country experiences, and new analytical work including various static microsimulation analyses based on household survey data. - Also uses results of fiscal policy simulations using a dynamic general equilibrium model calibrated to country-specific data and behavioral parameters to illustrate potential impacts of alternative budget-neutral tax and transfer measures on income inequality and economic growth. - Gini coefficient used as the main measure of income inequality; unless specified otherwise, Gini income inequality refers to disposable income or consumption, reflecting redistribution through taxes and transfers. - Other inequality concepts (lifetime inequality, wealth inequality, inequality of opportunity) are related and analyzed in Annex 1.2. ### Inequality trends and drivers Findings: - In 2015, global inequality (distribution of income over entire global population, abstracting from country borders) ranged from 0.63 to 0.69. - Decomposition: differences in per capita income between countries accounted for about 65 percent of global inequality in 2013. - During the nineteenth and most of the twentieth centuries, global inequality increased dramatically as advanced economies pulled ahead; over the past three decades global inequality has declined sharply. - Emerging market economies including China and India have moved up the global income distribution, contributing substantially to income convergence across countries. - While between-country inequality has declined markedly, rising within-country inequality in many countries has slightly offset the decline in between-country inequality. - Over the past three decades, 53 percent of countries have seen an increase in income inequality; some countries recorded an increase in their Gini coefficients exceeding two points. - Most advanced economies have experienced sizable increases in income inequality, driven primarily by the growing income of the top 1 percent. - Regional heterogeneity: - Eastern Europe and Central Asia: increase in inequality during postcommunist transition years and a decline afterward. - Latin America and the Caribbean: inequality increased during the 1980s and 1990s before declining sharply; despite declines, countries in Latin America remain among the most unequal in the world. - Sub-Saharan Africa: inequality has declined on average, though evolution is diverse across countries. Identified drivers: - Global factors: technological progress, globalization, commodity price cycles. - Technological advancement contributed to the skill premium; in Western Europe and the United States it has also led to job polarization (hollowing out of middle-class jobs). - Country-specific factors: economic developments and stability, domestic policies (financial integration, redistributive fiscal policies, liberalization and deregulation of labor and product markets). - In advanced economies, incomes at the bottom and top experience important losses during recessions; example: in the European Union the Great Recession affected all income deciles, with the bottom decile experiencing an income loss of 17 percent relative to its precrisis level. - Changes in income inequality are reflected in other dimensions such as wealth inequality; upswing of top incomes combined with high saving rates has resulted in growing wealth inequality. ### Growth, inequality, and social welfare Findings: - Changes in income distributions should be considered within the economic growth context. - Many advanced economies experienced increases in inequality in a context of low growth over the period 1985–2015. - Some emerging market and developing economies experienced increases in inequality during periods of strong economic growth; in several countries inequality declined due to widespread sharing of growth benefits. - Income growth by percentile: - In emerging market economies, all deciles benefited from economic growth even when inequality increased. - In advanced economies and low-income developing countries, economic growth has accrued mainly to the top. - Economic growth has dominated the evolution of social welfare over the past four decades even with high aversion to inequality. - Regional poverty reduction: - East and South Asia and the Pacific showed remarkable success in reducing poverty between 1985 and 2015 due to high growth. - Strong growth led to sustained declines in absolute poverty rates in sub-Saharan Africa and Latin America and the Caribbean. - Promoting growth and reducing inequality are not necessarily incompatible; empirical evidence suggests they can coexist, though cross-country regressions fail to clearly identify specific policies that both promote growth and reduce inequality. Analytical approach to trade-offs: - Use of a social welfare function (Atkinson’s monetary measure—the equally distributed equivalent income) to decompose variations in social welfare into contributions from growth and inequality and to rank policies by their efficiency-equity effects. ### Fiscal redistribution Mechanisms by which fiscal policy affects inequality: - Progressive direct taxes and transfers reduce disposable income inequality relative to market income inequality. - Consumption taxes affect "real" disposable income inequality. - In-kind transfers (education, health) reduce inequality of "full income" and affect market income inequality over time by changing human capital distribution and promoting social mobility. Determinants of fiscal redistribution: - The extent of redistribution depends on both the magnitude of taxes and transfers and their progressivity. - Advanced economies generally have larger magnitudes of taxes and transfers, implying greater potential for fiscal redistribution. Policy emphasis: - Importance of appropriate design of taxes and transfers to minimize efficiency costs and of simultaneously considering both taxes and transfers when designing redistributive fiscal policies. *Source: fmc1 - Introduction, https://www.imf.org/-/media/files/publications/fiscal-monitor/2017/october/pdf/fmc1.pdf* ### CHAPTER 1 TACkLINg INequALITy ### CHAPTER 1 TACkLINg INequALity ### Advanced Economies: Fiscal Redistribution and Inequality - In 2015, the average Gini coefficient for disposable income in advanced economies was 0.31 compared with 0.49 for market income. - Direct taxes and transfers reduce income inequality, on average, by about one­third in advanced economies. - Approximately three­quarters of fiscal redistribution was achieved on the transfer side of the budget, with public pension benefits accounting for about half of this. - Between 1985 and 1995, rising fiscal redistribution was able to offset about 60 percent of the increase in market income inequality; between 1995 and 2010, average fiscal redistribution hardly changed while market income inequality continued to increase. - In a number of countries (examples given: Denmark, Finland, and Sweden) fiscal redistribution decreased over the more recent period despite rising market income inequality. - Indirect taxes are primarily revenue instruments and can be regressive; in­kind transfers (health and education) decreased the Gini coefficient by 5.8 points in five European economies (Belgium, Germany, Greece, Italy, and the United Kingdom), with health accounting for 3.6 points and education for 2.2 points. ### Emerging Market and Developing Economies: Low Redistribution and Policy Tradeoffs - These countries have substantially lower levels of taxes and transfers than advanced economies, implying significantly lower redistributive impact. - Tax composition: greater reliance on indirect taxes, which tend to be either slightly progressive or slightly regressive and thus have only a small impact on income inequality. - Low levels of direct transfers and a high share of transfers absorbed by in­kind education and health limit immediate fiscal redistribution but support growth and medium­term inequality reduction. - Regional patterns (figures cited in source): - Composition of Tax Revenues and Social Spending shown by region (percent of GDP) in Figures 1.10 and 1.11. - Comparison: Income taxes and transfers reduced the Gini coefficient by 0.17 in the sample of advanced economies, but by only 0.03 in the sample of Latin American economies. - More than three­quarters of the difference in average inequality of disposable income between advanced economies and Latin American countries is explained by differences in the redistributive impact of taxes and transfers (0.14 out of 0.17). - Coverage and incidence of transfers: - Except in emerging Europe and Latin America and the Caribbean, coverage (share of the poorest 40 percent who receive any public transfer) is very low. - Even in Latin America and the Caribbean with high coverage, the share of total transfers going to the poorest 40 percent is often less than 20 percent. - In virtually all emerging market and developing economies, the share of transfers going to the bottom 40 percent is less than 40 percent. - ASPIRE database evidence: transfers decrease the Gini coefficient by a median of about two points in Latin America and the Caribbean and the Middle East and North Africa, and by less than one point in other regions. - Policy tradeoff highlighted: difficult choice between financing redistributive direct transfers to reduce current poverty and increasing spending on education and health to enhance growth and reduce future poverty and inequality. - Evidence on education: - Improved education outcomes (average years of schooling) are associated with a significant decline in inequality of education outcomes, which in turn reduces income inequality (Coady and Dizioli 2017). - The decline in income inequality due to declining inequality of education outcomes between 1990 and 2005 ranged from 4.8 Gini points in the Middle East and North Africa to 2.8 points in Latin America and the Caribbean. - Conditional cash transfer programs (Brazil, Mexico examples) can reduce both human capital inequalities and current income inequalities. ### Progressivity at the Bottom: In­Work Credits and Poverty Reduction - Tax policy can help the poor by ensuring minimal tax burdens and by using in­work tax credits (example: Earned Income Tax Credit in the United States) to stimulate labor force participation and provide income support. - Implementation caveats: - Redistributive tax policies must be used with caution because steep phasing out of benefits increases marginal tax rates and can create adverse labor supply effects. - In­work benefits can increase labor supply while reducing low­skill wages, which may shift some benefit to employers by reducing labor costs. - Implementation of in­work tax credits is most suitable for countries with strong tax administration based on withholding to curb noncompliance and false claims. ### Progressivity at the Top: Trends in Personal Income Tax (PIT) Progressivity - Tax progressivity (degree to which average tax rate rises with income) has been on a declining trend in recent decades. - Median measures show steep decline in the 1980s and 1990s and broad stability since then (see Figure 1.13 in source). - OECD average top statutory personal income tax rate fell from 62 percent in 1981 to 35 percent in 2015. - Many post‑1990s tax reforms combined increased exemption thresholds with lower top PIT rates, shifting tax burden from very low and very high incomes toward the middle. - Practical factors reducing measured progressivity: - Wealthy individuals have greater access to tax reliefs and avoidance opportunities (mortgage interest deductions, tax planning). - Empirical evidence suggests tax evasion is particularly high at the upper end of the income distribution (Alstadsaeter, Johannesen, and Zucman 2017). ### Explanations for Declining PIT Progressivity and Empirical Findings - Optimal tax theory links optimal top income tax rate to income tax elasticity, income distribution (Pareto index), and social welfare weight on high earners. - Fiscal Monitor assessment findings: - No evidence of an increase in income tax elasticity for top earners over time; empirical literature and IMF estimates do not show a rising trend in top‑earner elasticities. - The share of income earned by top percentiles has not declined; it has increased. The Pareto index for the top 5 percent shows a clear downward trend over the past 35 years, indicating a greater share of income in the upper tail. - Changes in social preferences do not seem to support higher welfare weights for the very rich. - Quantitative example from source: - Assuming a welfare weight of zero for the very rich, the optimal marginal income tax rate can be calculated as 44 percent, based on an average income tax elasticity of 0.4 and a Pareto index of 2.2. - The substantial decline in the average top marginal PIT rate to 35 percent would be consistent with a rise in the social welfare weight on high­income earners from zero to about (text truncated in source at this point). *Source: International Monetary Fund | October 2017.* ### 0.38 over the past 35 years, assuming the other ### fmc1 - 0.38 over the past 35 years, assuming the other ### Decline in tax progressivity: findings and interpretation - Empirical finding: tax progressivity has declined and is difficult to rationalize within optimal tax theory. - Social welfare weights: - Example social welfare marginal weight for top earners: 0.38. - Interpretation: a social welfare weight for top earners of 0.38 implies that the government is indifferent between giving $2.63 (1/0.38 = $2.63) to top income earners and giving $1.61 (1/(1−0.38) = $1.61) to the rest. - Pareto distribution and top shares: - Pareto index example: a Pareto index of 2.2 means that the top 5 percent have approximately a 19½ percent share of total income. - Pareto index values shown: 1.95, 2.20, 2.45, 2.70, 2.95. - Optimal tax formula parameters used in illustration: - Average income tax elasticity: 0.4. - Pareto index used: 2.2. - Evidence on preferences and politics: - Integrated Values Survey indicates societal preferences in favor of redistribution have become stronger since the 1980s, which would imply a reduction in the social welfare weight on high‑income earners. - Political economy constraint: better‑off individuals tend to have more political influence; countries with historically more unequal income distributions often have political systems dominated by elites. - Empirical link between progressivity and growth: - Most specifications yield no effect of progressivity on growth (see Annex 1.5 reference in source). - Some earlier studies find small negative effects in specific samples or lags (examples cited include Padovano and Galli 2002; Rhee 2013), but overall there is no clear evidence that progressivity levels seen since 1981 in OECD countries have been demonstrably harmful for growth. - Conclusion drawn in text: - There appears to be scope for increasing the progressivity of income taxation without significantly hurting growth for countries wishing to enhance income redistribution, though political implementation may be difficult. ### Capital income taxation: rationale, effects, and trends - Role of capital income: - Capital income (profits, interest, capital gains) is distributed more unequally than labor income and has risen over past decades. - Capital gains can make up a large share of an individual’s income, especially for the rich (example: in the United States in 2014, the 400 highest‑income taxpayers received 60 percent of their income from capital gains). - Two main justifications for lower taxation of capital income: 1. Theoretical efficiency arguments: - Taxing capital income can discourage saving and investment by taxing future consumption at a higher effective rate than current consumption. - Chamley (1986) and Judd (1985) argue for a zero tax rate on capital income in some settings; Atkinson and Stiglitz (1976) imply abstaining from capital income taxation if nonlinear income taxation is an option. - A policy compromise: tax‑favored vehicles (for example, pension funds) can allow efficient life‑cycle saving while still taxing capital incomes of very wealthy individuals. 2. Empirical elasticity arguments: - Capital income is empirically more responsive (elastic) to taxation than labor income: taxation influences firm location and investment allocation; opportunities exist to recharacterize returns (for example, tax‑favored capital gains versus dividends). - In optimal capital taxation theory, a higher elasticity of capital income implies a lower optimal capital tax. - Optimal capital tax formula (as presented): - t_K* = (1 − g_K) / (1 − g_K + e_K), where g_K is social welfare weight on high capital income earners and e_K is elasticity of capital income with respect to the marginal tax rate. - If marginal welfare weight is zero, formula simplifies to t_K^R = 1 / (1 + e_K) (revenue‑maximizing rate). - Corporate income tax and enforcement: - Corporate income tax plays an important role in taxing reinvested earnings and mitigating income‑shifting/arbitrage between personal and corporate tax bases. - International tax competition and capital mobility have led to a steady downward trend in corporate income tax rates (Figure 1.17 referenced). - The optimal top income tax rate allowing for income shifting (formula cited): - t* = (1 + s ∙ τ ∙ a e) / (1 + a e), where s is share of marginal income shifted, τ is tax rate on alternative base, and other parameters as previously defined (marginal welfare weight set to zero in derivation referenced). ### Fiscal transfers: universality versus means testing; UBI assessment - Tradeoffs between universal and means‑tested transfers: - Choice influenced by administrative capacity to implement means testing, available tax instruments, and labor supply responsiveness across income distribution. - Advanced economies commonly use means‑tested income support combined with universal categorical family benefits or social pensions. - Many developing economies spend substantially less on such transfers and often rely on indirect targeting by “tagging” characteristics (geography, disability, widowhood, public works participation), which often results in coverage gaps among the poor and leakage to the nonpoor. - Administrative and incentive issues: - Means testing requires capacity to verify incomes, process applications, and deliver transfers. - Design must minimize work disincentives where benefits are withdrawn quickly as incomes rise. - Evidence on labor disincentives: Immervoll and others (2007) estimate effective participation taxes vary between 30 and 85 percent in European countries (higher in Nordic countries). - In 2015, the average marginal effective tax rate (METR) in EU27 countries on earned income in the bottom quartile was 28 percent; it has increased since 2011, with large variation across members. - Policy responses include conditioning eligibility on participation in active labor market programs and using in‑work benefits (wage subsidies) to enhance work incentives. - Universal Basic Income (UBI) discussion and empirical illustrations: - Fiscal Monitor defines UBI as a cash transfer of an equal amount to all individuals in a country. - Arguments for UBI: better address poverty and inequality where means testing is limited; address income uncertainty from automation; help build support for structural reforms. - Arguments against UBI: high fiscal cost; large leakage to the nonpoor (including wealthy households); potential to discourage labor supply; severs links between rights and responsibilities of job seekers. - Calibration example analyzed: - UBI calibrated at 25 percent of median per capita income (additional to existing programs and without accounting for financing or behavioral responses). - Estimated distributional impacts for a selection of emerging market and developing economies: - Average reduction in inequality: 5.3 Gini points. - Average reduction in relative poverty: about 10.4 percentage points. - Fiscal cost (gross) example: - Would cost about 6½ percent of GDP for selected advanced economies. - Would cost about 3¾ percent of GDP for selected emerging market and developing economies. - Caveat: actual implementation, financing, and behavioral responses would affect net impact and fiscal affordability. *Source: IMF Fiscal Monitor: Tackling Inequality (content extracted from provided PDF excerpt).* ### Annex 1.6 presents details on the methodology and under­ ### fmc1 - Annex 1.6 presents details on the methodology and under­ ### Methodology and scope - Annex 1.6 provides details on the methodology and underlying assumptions for the partial static equilibrium analysis used throughout the section. - Many empirical assessments of UBI implementation use a similar methodology (example cited: OECD 2017). - Simulations focus on budget­neutral options given limited fiscal space in many countries. - The fiscal envelope in exercises is estimated based on Luxembourg Income Study (LIS) data (note: LIS data may differ from budgetary data). ### Financing and budget‑neutral assumptions - Budget neutrality can be achieved by any combination of cutting spending or increasing direct or indirect taxes. - Other revenue sources could include elimination of energy and other subsidies (example referenced: India, Box 1.6). - Illustrative fiscal-revenue implication: for eight countries in the Annex 1.6 sample, budget neutrality for UBI financing relying solely on revenues would imply average general government revenue of 47 percent of GDP for advanced economies and 32 percent for emerging market economies, taking 2016 as the base year. ### Calibration and UBI design parameters used in simulations - UBI calibrated at 10 and 25 percent of median market income (after direct taxes) per capita and distributed equally to every individual. - Relative poverty threshold defined as 50 percent of per capita equivalent disposable income. - Computations based on most recent LIS microdata available: 2010 (France), 2012 (Egypt, Mexico, South Africa), 2013 (Brazil, Poland, United Kingdom, United States). - Estimates ignore behavioral responses in partial equilibrium exercises. ### Distributional impacts: coverage, progressivity, and generosity - A UBI distributes existing transfers uniformly across the population, potentially improving coverage of lower‑income households but possibly reducing benefit generosity for those already targeted. - Example: South Africa (LIS 2012 microdata) - For the lowest two income deciles, about 65 percent of households in the bottom two deciles are covered under the existing transfer system. - Average drop in benefits for households covered under the existing system in the bottom two deciles is 19 percent of per capita disposable income. - Average gain for the remaining 35 percent of households in the bottom two deciles (currently not covered) is about 150 percent of their per capita disposable income. - South Africa further illustrative statistics (panels in Figure 1.22): - For households in the bottom income decile, UBI represents 130 percent of per capita equivalent disposable income (PCDI), compared with current transfers representing 74 percent of PCDI (panel 1). - If current transfers were replaced by a UBI, losing households in the bottom income decile would lose, on average, 12 percent of their PCDI, and households in the bottom decile not previously receiving transfers would gain, on average, 274 percent (panel 2). ### Financing modality effects - Replacing current transfers with a UBI financed through an increase in indirect taxes (for example, a flat tax on consumption) can produce different net impacts; the net impact could be progressive if income (and consumption) inequality is very high (Figure 1.22, panels 3 and 4). - Trade‑off emphasized: coverage expansion versus loss of progressivity and reduction in benefit size for existing beneficiaries. ### Country typologies and policy implications - Countries with minimal transfer systems: - A UBI could be an option to provide income support if financed through progressive taxation and other fiscal reforms (such as elimination of energy subsidies) without large efficiency costs. - UBI could be used to strengthen safety nets in low‑income developing countries where coverage and capacity to means‑test are low. - Countries whose transfer systems perform well (examples: France, United Kingdom): - Replacing existing systems with a UBI would likely cause a very large reduction in progressivity and losses in benefit size for many poor households and could even increase poverty. - Priority in such cases should be to reform and strengthen existing targeted systems. - Countries whose transfer systems perform poorly: - Replacing poorly performing systems with a UBI would expand coverage but lower progressivity and reduce benefits for the average beneficiary under the current system. - The key trade‑off is between coverage and progressivity, especially when current systems have low coverage but relatively good progressivity (example: Brazil). - Case example noted: India discussed in Box 1.6 (elimination of subsidies as fiscal space). ### General equilibrium and welfare analysis (summary of model findings) - General equilibrium simulations (Annex 1.3) incorporate behavioral responses, financing modalities, and equity‑efficiency trade‑offs. - Welfare‑based framework used to compare policy options and efficiency‑equity outcomes (Box 1.2). - US‑calibrated model findings: - Cost to efficiency (forgone output) is larger when financing is raised from more progressive PIT rates than when raised with higher value‑added taxes. - As aversion to inequality increases, a UBI financed with progressive taxation is preferable, in terms of welfare, to financing with indirect taxes. - Compared to an expansion of the EITC with equivalent fiscal cost, welfare improvements are higher with the EITC than with the UBI, since the EITC is a targeted subsidy. - For relatively high levels of aversion to inequality, EITC dominates regardless of financing modalities. - Bolivia‑calibrated model findings: - Bolivia lacks a formal personal income tax and has a high degree of informality; effective PIT tax rates are very low and labor supply of formal workers is very inelastic. - In Bolivia’s calibration, costs to efficiency associated with the UBI and its financing are offset by gains to groups, even for low values of aversion to inequality, due to the tax structure and informality. - Despite strong poverty‑reduction potential, the model cautions that a UBI may not necessarily be the appropriate redistributive instrument in Bolivia; a more in‑depth analysis is necessary. ### Other objectives and considerations for UBI adoption - UBI can provide insurance against income/employment shocks in environments of increasing job insecurity (example rationale: technological progress, automation). - Insurance benefits must be weighed against potential moral hazard and disincentives for skill adaptation. - A uniform transfer provides greater social insurance to lower‑income groups less able to self‑insure. - UBI could be used politically/economically to support broader structural reforms (example: removal of energy subsidies), since energy subsidies disproportionately benefit higher‑income groups; replacing them with a UBI targeted to protect lower‑income groups could generate fiscal space plus health and environmental benefits. ### Summary judgment on means testing versus universality - If means testing could be perfectly designed and implemented, it would be superior to universality. - In practice, limited administrative capacity and information constraints make the choice less clear. - Universal transfers can fill coverage gaps in administratively constrained environments but create challenges: leakage to higher‑income groups and financing large costs with distortionary taxation. - The optimal choice (means‑tested transfers, UBI, or combination) depends critically on administrative capacity, availability of financing, and potential impacts on labor supply. ### Education and health: equalizing opportunities (key points) - Education and health policies can directly reduce market income inequality and have potential to promote both growth and equity. - Education: - Gender enrollment gaps largely eliminated except in low‑income developing countries (Figure 1.24). - Socioeconomic status remains a key determinant of access to education across regions; gaps exist in early childhood, secondary, and tertiary education (Figure 1.25). - Disadvantaged students perform substantially worse than advantaged peers; resource gaps (educational materials, staff) are a major factor. - Narrowing disparities improves intergenerational earnings mobility (Figure 1.26) and can lower future income inequality; impact diminishes as countries develop but still matters if quality inequality is addressed. - Public education spending is on average pro‑poor in advanced economies (except tertiary spending which tends to be regressive) and often pro‑rich in emerging market and low‑income countries. - Reallocating public education spending toward disadvantaged students and schools could reduce education inequality and raise overall outcomes without increasing total public education budgets (negative relationship shown between school resource gaps and average PISA scores, Figure 1.28). - Health: - Socioeconomic gaps in health outcomes remain sizable and are not narrowing. - In advanced economies, the life‑expectancy gap between males with tertiary education and those with lower secondary education or less ranges from about 4 years in Italy to 14 years in Hungary (Figure 1.29). - The gap is smaller for females. - Reducing learning gaps can also reduce disparities in health outcomes due to a strong positive association between education and health. *International Monetary Fund | October 2017 — Annex 1.6 and related sections as presented in the Fiscal Monitor excerpt.* ### CHAPTER 1 TACkLINg INequALITy ### CHAPTER 1 TACkLINg INequALity ### Inequality in Access to Education and Test Scores - The number of countries covered in each region is 6 in MENA, 4 in EDA, 3 in CIS, 9 in EDE, 35 in AE, and 10 in LAC. AE = advanced economies; CIS = Commonwealth of Independent States; EDA = emerging and developing Asia; EDE = emerging and developing Europe; LAC = Latin America and the Caribbean; MENA = Middle East and North Africa; PISA = Program for International Student Assessment; SSA = sub-Saharan Africa. - Inequality measures presented include: - Ratio of bottom quintile to top quintile for access indicators (early childhood attendance, primary completion, lower-secondary completion, upper-secondary completion, tertiary completion). - Ratio of disadvantaged students' likelihood of low performance to that of nondisadvantaged students (PISA science). - Overperformance of advantaged schools compared to disadvantaged schools (material and staff resources). - Evidence and relationships highlighted: - Inequality in test scores is defined as the ratio of disadvantaged students’ odds of poor performance on the PISA science assessment to those of nondisadvantaged students. - College completion rate is measured as the ratio of bottom to top quintile. - Cross‑country relationships show links between education inequality (college completion rate, test scores) and intergenerational income elasticity. ### Inequality in Health Outcomes and Coverage - Trends and findings: - In emerging market economies and low‑income countries, large disparities in health outcomes within countries remain. - Over the past decade health disparities—measured by the ratio of the infant mortality rate of the top to the bottom quintile in the population according to their socioeconomic status—have increased in about half of emerging market and developing economies, reflecting slower improvements among the disadvantaged rather than deteriorations in health outcomes in about half of the cases. - Although some progress has been made, large gaps in health coverage still exist between the rich and the poor. - Quality of care received by the poor is substantially lower than that received by the rich. - Health outcomes are increasingly determined by factors other than health care, including nutrition, drinking water, sanitation and hygiene, education, and healthy behaviors, particularly in advanced economies. - Financial protection and consumption: - Public health spending can provide financial protection and increase household consumption by limiting out‑of‑pocket spending and reducing financial exposure to adverse health‑related events. - Out‑of‑pocket spending has declined modestly, progress has been slow, and it remains high in low‑income countries and emerging market economies. - The benefit incidence of public health spending is pro‑rich in many countries because the rich typically use more health care services, so identical health coverage packages benefit the rich more than the poor. - Life expectancy and coverage inequality: - There is a strong positive association between lower inequality in health coverage and average life expectancy in a country, and this relationship remains after controlling for other key determinants of health outcomes. - Simulation analysis indicates that eliminating inequalities in basic health coverage could raise life expectancy, on average, by 1.3 years in low‑ and middle‑income countries. - Definitions and notes: - Basic health coverage refers to a weighted score calculated by the World Health Organization reflecting coverage of eight reproductive, maternal, newborn, and child health interventions. - EMEs = emerging market economies; LICs = low‑income countries. ### Policy Implications and Conclusions - Fiscal policy is a powerful tool for governments wishing to tackle high or rising inequality, but the appropriate design of fiscal redistribution depends on country‑specific factors: - Social preferences: Some countries may prioritize sharing the gains from growth more equally across the income distribution, others may focus on reducing poverty and raising incomes for lower‑income groups. Developing countries with low per capita incomes may accept larger increases in income inequality when growth is high and all income groups are benefiting. - Administrative capacity: Countries with lower administrative capacity have more limited redistributive tools. High‑income countries can implement more sophisticated and progressive fiscal policies (means‑tested benefits, more progressive income tax schedules); low‑income countries typically must rely on less sophisticated instruments. Recent technological advances can improve collection, sharing, and cross‑checking of information, expanding available tax and spending instruments. - Fiscal pressures: Redistributive fiscal policies must be consistent with fiscal sustainability. Countries with high debt or fiscal deficits that wish to scale up redistribution would need to generate fiscal space. Many advanced economies already have high tax and spending levels, leaving little room to increase government size without adversely affecting growth. Limited fiscal space highlights the importance of reallocating spending and improving spending efficiency. - Design considerations: - Consider the combined distributional impact of both tax and transfer instruments, since regressive but efficient tax financing can fund progressive spending. - Other fiscal and nonfiscal policy instruments can help achieve redistributive objectives while minimizing efficiency costs. ### Enhancing Progressivity of Taxation - Personal income tax (PIT) and administration: - Progressivity of the PIT has declined over the past three decades in many advanced economies. - Evidence suggests it may be possible to increase progressivity without adversely affecting economic growth, for instance, by raising marginal tax rates at the top in countries with relatively low rates and progressivity. - Emerging market and low‑income developing countries with lower administrative capacity and larger informal sectors should set a relatively high tax‑exempt threshold and then focus on expanding PIT coverage by gradually decreasing the threshold in line with improvements in administrative capacity. - In many of these countries the PIT does not have a threshold; introducing one would ease administrative burden, strengthen tax compliance, and enhance progressivity (IMF 2014). - Reducing avoidance and taxing capital and wealth: - Reduce opportunities for tax avoidance and evasion, especially among high‑income earners, by capping or eliminating deductions (tax‑favored status of fringe benefits, unlimited tax deductibility of medical insurance costs or mortgage interest). - Reduce scope for turning labor income into capital income; ensure adequate taxation of capital income by reducing differences between taxation of different capital income types, which may require higher and uniform taxation of capital gains. - The OECD/G20 Base Erosion and Profit Shifting (BEPS) initiative is a first step; automatic exchange of information could be extended to more countries and types of incomes. - Most countries have room to enhance revenues from taxation of immobile capital. Different types of wealth taxes—recurrent taxes on property or net wealth, transaction taxes, inheritance and gift taxes—can be important sources of progressive taxation. - Taxes on real estate or land are both equitable and efficient and remain underused in many countries. Higher taxes on second homes can have an even stronger equity impact. - Effective implementation of taxation of immovable property may require a sizable investment in administrative capacity. *International Monetary Fund | October 2017* ### CHAPTER 1 TACkLINg INequALITy ### CHAPTER 1 TACkLINg INequALITy ### Consumption Taxes and Excise Policies - Consumption taxes raise revenues to finance progressive spending, especially in emerging market and low­income countries with limited capacity to raise income taxes. - Consumption taxes can be made more progressive by complementing them with excise taxes on luxury goods such as yachts and luxury cars. - Increasing excise taxes on consumption with significant negative externalities (alcohol, tobacco, and fossil fuel energy) and using revenues for progressive spending is desirable on both efficiency and distributional grounds and can generate large revenue and health gains. ### Universal Basic Income (UBI) Versus Means‑Tested Programs - The choice between universal and means‑tested transfers depends on: administrative ability to implement means testing; range of tax instruments available to raise revenue efficiently; responsiveness of labor supply across the income distribution; and the policy challenges being addressed (for example, substituting for or complementing existing safety nets, addressing labor income uncertainty, or generating public support for structural reforms). - Advanced economies: - Where safety nets are already generous and progressive, a UBI is unlikely to be an effective substitute. - Where systems have gaps in coverage or progressivity, priority should be given to addressing these gaps (for example, reforming eligibility rules or promoting benefit take‑up). - Categorical family benefits with universal reach (such as child benefits and social pensions) already exist in many advanced economies. - Means‑tested programs should address disincentives for labor force participation through strengthened administrative capacity, information systems, and reform design (including greater use of well‑designed in‑work benefits). - Emerging market and developing economies: - A UBI could be an attractive alternative where existing systems have large coverage gaps and low progressivity, provided it can be efficiently financed. - More likely where countries rely heavily on inefficient and regressive universal price subsidies (such as those on food or energy) and have large gaps in their consumption tax bases. - Adoption of a UBI must be consistent with other fiscal priorities (generating fiscal space for other spending needs and ensuring fiscal sustainability), require strengthened capacity to distribute cash transfers, and need a strong communications campaign to build support for a broader reform package. - Administrative, political, and fiscal constraints suggest a gradual approach to reform—possibly focusing first on universal coverage of subgroups (such as children and the elderly). - Recent technologies (biometric identification, information digitalization, and electronic finance) have enhanced the attractiveness of a UBI while administrative capacity to better target redistributive spending continues to improve. - When UBI is considered as a response to growing labor income uncertainty, it should be evaluated as part of a broader set of income insurance instruments; progressive income tax and transfer systems provide important income insurance because after‑tax‑and‑transfer income is more stable than before‑tax‑and‑transfer income. ### Reducing Gaps in Education and Health - Objective: improve outcomes of the disadvantaged and enhance redistributive effect of public education and health spending. - Improving access to quality education and health care: - Education: expand basic—primary and secondary—education to eliminate remaining enrollment gaps; in tertiary education, aim for equality of opportunity so admission is based on ability rather than family socioeconomic background. - Private financing and income‑contingent student loans are justified for tertiary education because much of the benefit accrues to graduates. - Health: priority is universal health coverage of a broad package of essential health services. Examples of countries expanding health coverage include Brazil, China, Ethiopia, India, Mexico, Thailand, and Tunisia. - Targeted subsidies (reduced or zero charges for the poor and those with chronic illnesses) and preventive care (such as immunizations) can play important roles. - Public provision or additional incentives for service provision may be required in less developed areas where many low‑income households reside. - Conditional cash transfer programs and information dissemination can stimulate demand among the disadvantaged. - Improving learning and quality of health care: - Develop and enforce regulations and guidelines, allocate more resources to schools and health care facilities serving the disadvantaged. - Additional resources should be spent to provide performance incentives rather than merely increasing wages. - Invest in early childhood education and parenting skills, strengthen nutritional programs, and improve access to clean water and sanitation. - Subsidies targeted to disadvantaged households for early childhood education can boost employment and earnings in these households. - Programs to improve parenting skills have shown positive effects (examples include Bangladesh, Colombia, and Jamaica). - Food subsidy programs and healthy meal programs for students are generally effective for low‑income households. - Improving access to safe water and sanitation could generate substantial health benefits. - Taxing unhealthy behaviors: - Taxes on smoking and alcohol can improve health outcomes while raising revenues. - Raising energy prices to efficient levels could reduce associated pollution deaths by nearly 60 percent (Coady and others 2017). - Although concerns exist that a large share of these taxes might fall on the poor, effects should be pro‑poor if revenues finance progressive spending measures. - Improving efficiency: - Inefficiencies in education and health spending are large. - Reforms to free resources for inequality‑reducing initiatives include curbing tax incentives and deductions for health and education expenses (which tend to benefit the rich), improving governance, and tackling corruption and waste. - In education, realigning the number of teachers to student declines in many high‑need schools can yield fiscal savings with little effect on outcomes in some advanced economies. - In health, shift resources toward cost‑effective services (primary and preventive care), foster competition and choice, improve provider payment systems, adopt health information technology, and improve public financial management. ### Global Inequality: Projections and Scenarios - Baseline projection (assuming within‑country inequality is unchanged and using UN population growth and per capita income growth projections from IMF, World Bank, OECD, and Consensus Forecasts): - Global Gini coefficient declines from 0.69 in 2015 to 0.66 in 2035. - Income of individuals in the 90th percentile would amount to 25 times that of individuals in the 10th percentile (compared with 28 times in 2015). - The number of people with annual incomes of $2,000–$20,000 would increase by 1.78 billion, with the largest gains in China, India, and Latin America and the Caribbean. - Most population growth in sub‑Saharan Africa would be among those with incomes of less than $2,000. - Alternative scenarios and robustness: - If within‑income inequality evolves with economic growth following the Kuznets relationship observed across countries, the global Gini coefficient would fall faster, reaching 0.63 in 2035. - For global inequality to remain stable, the within‑country Gini coefficient would need to worsen in each country by 6.6 Gini points (a remote scenario given such deterioration has been observed only in one or two countries over the past 20 years). - Under a more pessimistic economic growth scenario (real GDP growth for each country revised downward over 2015–35 by about half a standard deviation in the annual historical growth rates over the preceding 10‑year period), the global Gini would decline to 0.67. - Global inequality would decline by an additional 1.1 Gini points if each emerging market and developing economy grew half a standard deviation (calculated over the 10‑year preceding period) faster than in the baseline. - Global inequality would decline by an additional half Gini point if emerging market and developing economies implemented the structural reforms recommended in IMF 2017b. ### Welfare‑Based Measures and Equally Distributed Equivalent Income (EDEI) - Welfare‑based measures can help policymakers assess trade‑offs between equity and efficiency by representing social welfare with assumptions that should be disclosed. - Equally distributed equivalent income (EDEI), introduced by Atkinson (1970), is a monetary measure of welfare: the income level that if equally distributed would yield the same welfare as the existing distribution. - Atkinson measure of inequality I ranges between 0 and 1; e.g., I = 0.3 implies society would need only 70 percent (1 − 0.3) of present national income if incomes were equally distributed to achieve current welfare. - Operational relationships: - EDEI satisfies U(EDEI) ∫ f(y) dy ≡ ∫ U(y) f(y) dy ≡ W, where f is the income distribution, U is individual utility, y is income, and W is average welfare. - Atkinson measure: I = 1 − EDEI / μ, where μ is mean income; W = μ (1 − I). - Change in welfare: ΔW = Δμ + Δ(1 − I), with Δ as percent change operator. - Isoelastic utility specification: - U(y) = (y^(1 − γ) − 1)/(1 − γ), where γ is the degree of aversion to inequality. - Larger γ implies greater aversion to inequality. - Under isoelastic U, I and EDEI take specified functional forms (as detailed in the source). - Empirical finding: Figure 1.2.1 shows that welfare (EDEI) is dominated by mean income; correlation coefficients between mean income and EDEI across γ values are: - Correlation coefficient = 0.999 for γ = 0.22. - Correlation coefficient = 0.997 for γ = 0.53. - Correlation coefficient = 0.953 for γ = 2.0. ### Bolivia Case Study: Growth, Fiscal Policy, and Inequality Reduction - Bolivia experienced strong economic expansion during 2005–12 accompanied by a sizable decrease in inequality and poverty: - Decrease in inequality: 8.7 Gini points. - Decrease in poverty: 20 percentage points. - A dynamic stochastic general equilibrium model calibrated to Bolivia was used to disentangle contributions of domestic and global factors (including commodity prices) to observed changes in growth and inequality. - Growth and policy drivers: - The 2 percent increase in potential growth observed during 2006–14 is explained mostly by the commodity price boom, which raised profitability in energy and agricultural sectors and led to a surge in government revenues. - Higher government revenues allowed more infrastructure investment, improving private sector productivity. - Substantial increase in the fraction of skilled individuals in the urban labor force helped industrial expansion and productivity gains. - Fiscal policies included higher taxes, which, taken in isolation, had a moderate negative impact on growth. - Distributional implications and quantified contributions to decline in inequality: - Increase in average skill level of the workforce (share of workers with education higher than high school rose from 30 percent to 45 percent between 2000 and 2012) led to higher urban incomes; as skilled workers became less scarce, the skills wage premium declined. The increase in average skill level accounts for about one‑third of the observed decline in inequality. - Higher prices for tradable agricultural commodities increased demand for raw agricultural products, raising rural incomes and reducing rural–urban inequality; increased rural incomes also boosted demand for nontradable goods, bidding up wages for the lowest‑skilled workers (including in the informal sector). This channel accounts for another one‑third of the observed decrease in inequality. - Expansion in social programs (including conditional cash transfers) financed by higher government revenues accounts for the remainder of the observed decline in inequality. - Energy prices were not found to have a direct impact on inequality (the gas sector has very low labor intensity) but generated higher government revenues enabling social spending expansion. - Price controls on final user prices attenuated potential negative effects of higher energy prices on economic activity and of higher agricultural prices on the urban poor, with corresponding budgetary implications. *International Monetary Fund | October 2017* ### Box 1.3. Bolivia: Inequality Decline during a Commodity Boom ### Box 1.3. Bolivia: Inequality Decline during a Commodity Boom ### Available content - Title present: "Box 1.3. Bolivia: Inequality Decline during a Commodity Boom". - Appears on page 36 of the Fiscal Monitor: TACkLINg INequALITy (International Monetary Fund | October 2017). - No substantive text or findings for Box 1.3 are included in the supplied content excerpt. *Source: fmc1 - Box 1.3. Bolivia: Inequality Decline during a Commodity Boom (Fiscal Monitor: TACkLINg INequALITy, IMF, October 2017).* ### Annex Figure 1.2.1. Wealth and Income Shares of Top ### Annex Figure 1.2.1. Wealth and Income Shares of Top Percentiles of Households, Selected OECD Countries, 2010 or Latest Available Year ### Evidence on top wealth and income shares - Saez and Zucman (2016) find that the wealth share of the top 0.1 percent grew from 7 percent to 22 percent over the period 1978 to 2012. - Labor income, including entrepreneurial income, and an increase in the share of income accruing to capital, combined with high saving rates at the top, are described as creating a “snowball effect” on wealth distribution. ### Inequality of opportunity and social mobility - Inequality of opportunity is defined as the extent to which circumstances beyond individual control (family socioeconomic status, gender, ethnic background) affect adult economic outcomes. - Proxy measures reported: - Intergenerational income elasticity: predicted percentage change in a child’s earnings attributable to a percentage change in parents’ earnings (reflects degree of intergenerational social mobility). - Inequality of opportunity (relative): proportion of income inequality explained by circumstances beyond individual control. - Empirical patterns: - Inequality of opportunity is higher, on average, in emerging markets (especially Latin America) than in advanced economies. - Among advanced economies, social mobility is much higher in the Nordic countries. - Time-series evidence within countries is limited; a few studies have failed to find a strong relationship between changes in inequality of opportunities and changes in income inequality over time. Public policies (for example, access to education) may limit the impact of changes in inequality on social mobility. ### Gender inequality: scope and macroeconomic implications - Regional patterns in multidimensional gender disparities: Europe most gender-equal; Asia and Pacific and the Western Hemisphere follow; sub-Saharan Africa and the Middle East have the highest gender inequality. - Examples of numeric indicators and prevalence: - In low-income developing countries, only 9 girls are enrolled in secondary education for every 10 boys. - In South Asia, only 37 percent of women have an account at a financial institution versus 54 percent of men. - Women are barred by law from specific professions in 79 countries. - Across OECD countries, the average gender wage gap—calculated as the difference between male and female median wages divided by male median wages—is estimated to be about 15 percent. - Women’s labor force participation ranges from 21 percent in the Middle East and North Africa to more than 63 percent in East Asia and the Pacific and sub-Saharan Africa. - Macro implications: - Gender equality is positively associated with per capita GDP and competitiveness. - Higher economic participation and earnings by women translate into higher expenditure on children’s school enrollment. - Gender gaps in economic participation restrict the talent pool and can cause total factor productivity losses. ### Model simulations: structure and calibration - Model type: dynamic stochastic general equilibrium model with heterogeneous households (types by education), idiosyncratic productivity shocks, three sectors (manufacturing, high-skill services, low-skill services), segmented labor markets, incomplete domestic credit markets, and exogenous external government debt schedule. - Key assumptions: - Household skill level fixed over the short-to-medium term (up to five years). - Low-skill individuals cannot work in the high-skill services sector. - One nonstate contingent bond for household borrowing/saving; exogenous borrowing constraints differing across skill levels. - Markets competitive; international trade prices determined abroad; capital markets closed except for government external debt (sensitivity tested by assuming open capital markets). - Calibration: - Calibrated to the economy of the United States to yield a “benchmark economy.” - The stationary equilibrium matches key macro ratios and distributional statistics of the US economy. - Labor supply elasticity is set to one-third. - Time horizon and interpretation: - Key variables are close to the new stationary equilibrium in about five years; reported macroeconomic numbers divided by five approximate average yearly effects. ### Industrial sector characteristics (Annex Table 1.3.1) - Low-Skill Service: Labor intensity = Very high; Type of labor = Low and middle skill; Tradability = No - High-Skill Service: Labor intensity = High; Type of labor = Middle and high skill; Tradability = No - Manufacturing: Labor intensity = Low; Type of labor = All; Tradability = High ### Policy scenarios simulated: EITC expansion and UBI (budget-neutral, cost calibrated) - General financing and comparison note: - Policy scenarios are fiscally neutral; financing options include reduction in government consumption of tradable goods, a VAT increase, and a more progressive PIT. - The EITC expansion and the UBI are each calibrated to a fiscal cost of 1 percent of GDP. - Expanding the EITC - Fiscal cost: loss of government revenues of 1 percent of GDP (approximately the cost of doubling the current EITC). - Financing option A — Reduction in government consumption of tradable goods: - GDP effect: slightly lower GDP because exchange rate effects penalize the tradable goods sector. - Labor and investment: hours worked of middle-skill workers and investment decline. - Labor supply: subsidizing labor of lower-income individuals increases their labor supply. - Wages: increased labor supply of low-skill workers exerts downward pressure on low-skill wages; medium-skill workers can be substituted for low-skill workers, reducing demand and wages for low-skill workers. - Consumption: higher consumption for the lowest quintile; consumption of quintiles II–IV benefits less; the fifth quintile (top) tends to experience a decline in consumption because the capital-intensive tradables sector contracts (though capital income preservation mitigates some decline). - Financing option B — VAT rate increase (2 percentage point increase in the VAT rate): - GDP effect: negative impact on GDP more pronounced (about 1.2 percent in total) when financed with a higher VAT. - Distribution: VAT is regressive; households in the bottom quintile lose the most relative to other financing options, although they remain substantially better off than before the EITC expansion. - Financing option C — More progressive PIT: - PIT changes: simulated changes in average effective PIT rate shown in Annex Figure 1.3.5 (figure referenced). - GDP effect: substantially more negative impact on GDP because PIT distorts labor and capital choices and is expected to be more distortionary than indirect taxes. - Distribution: upper quintiles experience consumption losses; bottom quintiles benefit more than under VAT financing. - Introducing a Universal Basic Income (UBI) - Fiscal cost: set at 1 percent of GDP (to be comparable to the EITC expansion). - Financing option — Reduction in government consumption of tradable goods: - GDP effect: UBI has a negligible impact on GDP. - Sectoral shifts: cash transfers raise demand for all goods; nontradable prices and wages increase, resulting in a switch from production of tradables to nontradables. - Wages and labor supply: increase in low-skill wages compensates for potential negative direct impacts on labor effort by low-income individuals; hours worked by low-income individuals barely change. - Investment: because nontradables do not use capital, private investment and private capital stock decline moderately. - Distribution: UBI is described as highly progressive; relative to the size of their incomes, households in the bottom quintile see a 5 percent *Italic: Content derived from "Annex Figure 1.2.1. Wealth and Income Shares of Top" (Fiscal Monitor: Tackling Inequality, International Monetary Fund | October 2017).* ### Annex Figure 1.3.5. United States: Changes in Effec- ### Annex Figure 1.3.5. United States: Changes in Effective Average Personal Income Tax Rates from EITC and Financing with Progressive Taxation (Percent) ### Macroeconomic Impact of UBI and Financing Options - Universal basic income (UBI) and Earned Income Tax Credit (EITC) experiments are analyzed with cumulative effects over five years (Annex Figure 1.3.6). - Financing options considered include: - Government expenditure cuts. - VAT rate increase (the VAT would have to increase 2 percentage points to exactly finance the transfer). - More progressive PIT. - Key qualitative effects described: - Expansion in EITC is targeted to lower quintiles and yields larger increases in consumption for those groups relative to a UBI. - VAT financing worsens macroeconomic impact because the VAT penalizes consumption and the returns to labor. - Financing with higher and more progressive PIT leads to a larger fall in investment (investment would fall four times as much, because progressivity penalizes higher-income individuals, who are the savers). - Medium-skill workers: higher demand for services raises their wages and hours; capital declines, benefiting demand for medium-skill workers. Consumption increases among the second through fourth quintiles partly due to cash transfer receipt. ### Distributional Impact (Percent change in consumption by quintile; cumulative effect over five years) - Annex Figure 1.3.7 summarizes distributional outcomes by quintile for each financing option: - Government expenditure cuts: distributional pattern shown in figure (no numeric quintile values provided in text). - VAT increase: primarily beneficial to the bottom quintile of the consumption distribution (mostly because of the cash transfer itself). - PIT increase: financing with higher and more progressive taxes is more progressive by construction. - EITC expansion redistributes to poor working households and, through labor-supply effects, also redistributes to higher-income households that benefit from lower labor costs. - EITC dominates the UBI because it is targeted and disproportionately benefits lower quintiles and has a positive effect on labor supply. ### Welfare Impact (Equally Distributed Equivalent Income, EDEI) - Welfare measured by equally distributed equivalent income (EDEI), dependent on inequality aversion parameter g. - General findings: - Redistributing income is costly (lowers economic efficiency), and more so when financed through increases in distortive taxation. - For low values of g, all policy packages reduce EDEI, with those financed with PIT being more costly to welfare than those financed with VAT. - EDEI associated with all policy packages has a positive slope with respect to g, reflecting society's willingness to trade efficiency for equity as g increases. - The VAT is more efficient than PIT, but is regressive; as aversion to inequality increases, packages financed with increases in PIT (with increased progressivity) improve and may dominate in welfare effect. - Specific diagrammatic comparison shown in Annex Figure 1.3.8 (change in EDEI versus Aversion to inequality (γ)), including lines for: - UBI, PIT - UBI, VAT - EITC, PIT - EITC, VAT - Note: The universal basic income (UBI) and the Earned Income Tax Credit (EITC) expansion are of equivalent size, equal to 1 percent of GDP. ### Annex 1.4 — The Estimation of Elasticities - Income tax elasticities calculated for 35 countries over the period 1981–2016 using World Wealth & Income Database and OECD tax database. - Elasticity definitions (following Brewer, Saez, and Shephard 2010): - e = Δ ln(Y) / Δ ln(1 − t) or e = Δ ln(s) / Δ ln(1 − t) - Difference-in-differences approach: e = [Δ ln(Y1) − Δ ln(Y2−5)] / [Δ ln(1 − t1) − Δ ln(1 − t2−5)]. - When real incomes are missing, incomes are estimated assuming Pareto distribution: - Y5 = a/(a − 1) t5 - Pareto index a estimated as a = ln(0.2) / ln(t5 / t1) = ln(0.2) / ln(s5 / 5s1) when thresholds unavailable. - Elasticities calculated only when there is a change in the personal income tax rate of at least 1 percentage point; no elasticity if average tax rate changes simply because of changes in the income distribution. - Median of estimated elasticities (Annex Table 1.4.1): - Numerator: Income Shares — Top 5 percent: 0.11; Top 1 percent: 0.26; Difference-in-differences: 0.40 - Numerator: Real Incomes — Top 5 percent: 0.22; Top 1 percent: 0.42; Difference-in-differences: 0.40 - Annex Figure 1.4.1 shows income elasticities for top earners estimated using the difference-in-differences approach (top 1 to top 2–5 percent) in 17 OECD member countries; regression reported: y = –0.02164x + 45.23715, R^2 = 0.0097, t = –0.61. ### Annex 1.5 — Growth Regressions (Progressivity and Growth) - Regression specification used to assess effect of progressivity on growth (sample: OECD countries, 1981–2016): - ŷ_it = a + β1 p_i,t−1 + β2 y_i,t−1 + γ′ X_i,t−1 + f_i + g_t + ε_it - p_i,t−1 is initial level of progressivity; X controls; f_i and g_t are country and year fixed effects. - Main result: Progressivity measures are nonsignificant in most specifications, but turn positive and significant in a few; overall suggests no strong relationship between progressivity and growth. - Robustness checks performed, including: - Regressions on samples restricted to 10-year periods. - Five-year interval regressions using average growth rate over five years (generalized method of moments also used). - Quantile regressions and interaction terms for high progressivity values. - Selected regression results (Annex Table 1.5.1 — Annual Regressions): - Columns report various progressivity measures; example coefficients (standard errors in parentheses): - Progressive capacity t–1: −0.408 (6.412) - Average rate progression, 0–400% per capita GDP t–1: 12.08 (7.465) - Δ Average tax rate / 100–167% Average wage t–1: 3.927 (8.561) - Top statutory rate t–1: −0.00180 (0.0312) - Number of observations and countries vary by specification (examples): - Number of observations: 2,019; 350; 350; 2,591; 712 - Number of countries: 135; 33; 33; 314; 634 - Five-year interval regressions (Annex Table 1.5.2) report, among other results: - Average rate progression, 0–400% per capita GDP t–5: 1.877* (0.968) and 1.849* (0.959) in columns (1) and (2). - Number of observations examples: 2,019; 2,591; 712. Number of countries examples: 135; 146; 341. - AR1 p reported as 0.000 or 0.002 in columns; Hansen p reported as 1.000 in some columns. - Conclusion: Range of robustness checks do not change the general conclusion that progressivity measures are mostly nonsignificant. ### Annex 1.6 — Empirical Assessment of a Universal Basic Income (UBI) - Sample of eight countries using LIS microdata: Brazil, Egypt, France, Mexico, Poland, South Africa, the United Kingdom, the United States. - Analysis method: - Partial static equilibrium simulations using standardized LIS microdata for latest year available; households only; no behavioral responses accounted for. - First step: Estimate gross fiscal cost of a UBI calibrated at 25 percent of the country net median market income per capita (earned market income minus direct taxes paid). - Three coverage variants: 1. Full UBI given to all individuals. 2. Full UBI given to all children (17 and younger). 3. Full UBI given to all children (17 and younger) and elderly (65 and older). - Additional simulated UBI levels: 10, 20, 30, 40, 50 percent of net median market income per capita (levels set arbitrarily). - Key aggregate findings (variant (1): all individuals covered), from Annex Table 1.6.1: - Brazil (2013): - Gross Fiscal Cost (percent of GDP): 4.6 - Reduction in Gini Coefficient: 0.05 - Initial Poverty Rate (percent): 19.0 - Reduction in Poverty Rate (percentage points): 4.1 - Annual UBI Amount (per person): R$1,286 - Egypt (2012): - Gross Fiscal Cost: 3.5 - Reduction in Gini Coefficient: 0.06 - Initial Poverty Rate: 18.55 - Reduction in Poverty Rate: 10.4 - Annual UBI Amount: LE 725 - France (2010): - Gross Fiscal Cost: 6.8 - Reduction in Gini Coefficient: 0.04 - Initial Poverty Rate: 9.49 - Reduction in Poverty Rate: 6.3 - Annual UBI Amount: €2,122 - Mexico (2012): - Gross Fiscal Cost: 3.7 - Reduction in Gini Coefficient: 0.06 - Initial Poverty Rate: 19.68 - Reduction in Poverty Rate: 12.0 - Annual UBI Amount: Mex$4,994 - Poland (2013): - Gross Fiscal Cost: 4.9 - Reduction in Gini Coefficient: 0.04 - Initial Poverty Rate: 10.70 - Reduction in Poverty Rate: 6.9 - Annual UBI Amount: Zl 2,111 - South Africa (2012): - Gross Fiscal Cost: 2.3 - Reduction in Gini Coefficient: 0.05 - Initial Poverty Rate: 23.65 - Reduction in Poverty Rate: 10.8 - Annual UBI Amount: R1,584 - United Kingdom (2013): - Gross Fiscal Cost: 6.7 - Reduction in Gini Coefficient: 0.04 - Initial Poverty Rate: 9.28 - Reduction in Poverty Rate: 6.0 - Annual UBI Amount: £1,839 - United States (2013): - Gross Fiscal Cost: 6.4 - Reduction in Gini Coefficient: 0.05 - Initial Poverty Rate: 17.42 - Reduction in Poverty Rate: 10.1 - Annual UBI Amount: US$3,516 - Summary observations from UBI simulations: - Reduction in inequality could be substantial (about 5 Gini points) and relatively similar across countries. - Reduction in poverty higher in emerging markets than in advanced economies in the sample. - Gross fiscal cost averages 6½ percent of GDP in the advanced economies selected and averages 3.8 percent of GDP in the selected emerging markets. - Restricting UBI recipients (children only; children and elderly) scales down gross fiscal cost and reduces impact on inequality and poverty. - In advanced economies, a UBI given to both children and the elderly helps reduce poverty more than when eligibility restricted to children; it also costs 70 percent more, on average. - Second-step simulations: introduce UBI and simulate financing so net fiscal cost is zero. Fiscal envelope calibrated as the sum of existing universal and means-tested noncontributory transfers in each sample country. Three financing options considered: 1. UBI substitutes for existing noncontributory transfers. 2. Direct income taxes are increased, with current progressive shape held constant. 3. A flat tax on disposable income is levied. - Note: In-kind transfers or subsidies and contributory programs are not included in the budget envelope; the budget captures a subset of monetary transfers estimated based on LIS data. Simulations assume existing tax and transfer schedules and eligibility requirements remain unchanged. *Source: IMF staff calculations and estimates using World Wealth & Income Database, OECD tax database, and Luxembourg Income Study microdata.* ### Annex 1.7. Health Outcomes and Inequality in ### Annex 1.7. Health Outcomes and Inequality in Public Health Spending ### Research design and variables - Sample: 72 low- and middle-income countries over the period 1995–2015; independent variables averaged within each five-year nonoverlapping period. - Baseline specification: y_it = α + β1 ln(h_it^Ineq) + γ′ X_it + c_i + τ + ε_it - y_it denotes average life expectancy at birth for country i at the last year of period t. - h_it^Ineq is the measure of inequality in basic health coverage, calculated as the ratio of household health coverage between the bottom (Q1) and the top (Q5) quintiles of a socioeconomic index within each country (so a larger value reflects lower health coverage inequality). - X_it includes public and private health spending (constant 2011 PPP terms), GDP per capita (constant 2011 PPP terms), average years of schooling, income Gini (disposable income), and education Gini. - c_i and τ denote country and period fixed effects. - Data sources and measures: - Health coverage for each wealth quintile from WHO’s health equity monitor database (index reflecting coverage of eight reproductive, maternal, newborn, and child health interventions). - Income and health spending variables from World Bank’s World Development Indicators; income Gini database used throughout this Fiscal Monitor; education variables from World Bank’s Education Statistics database. - Estimation methods: both fixed and random country effects are used; some specifications allow private health spending to respond, others hold it fixed. ### Causal channels by which health-coverage inequality affects aggregate health outcomes (as described) - Channel 1: Marginal health benefit of health spending is larger for the poor; reallocating public health spending from rich to poor raises overall health outcomes. - Channel 2: Distributional changes in public spending induce responses in private health spending; reallocating public spending to the poor can increase overall private health spending because the rich increase their spending, offsetting any small decline in poor households’ private spending. - Channel 3: Feedbacks from health spending and outcomes to income and its distribution, which in turn affect health spending and outcomes; the model controls for income and education and their distributions and does not model this channel explicitly (effect from this channel is likely small). ### Main empirical results (Annex Table 1.7.1) - Sample statistics reported in table: - Number of observations: 179 - Number of countries: 72 - Country effects: Random in columns (1), (2), (5), (6); Fixed in columns (3), (4) - Period fixed effects: No in columns (1)–(4); Yes in columns (5)–(6) - Key coefficient estimates (coefficient estimate with robust standard error in parentheses; significance stars preserved): - ln(WHO Health Coverage Ratio (Q1/Q5)) - (1) 6.862*** (1.990) - (2) 5.522*** (1.932) - (3) 6.558** (3.013) - (4) 4.693* (2.358) - (5) 4.422** (2.010) - (6) 4.092** (1.956) - ln(Public Health Spending) - (1) 2.413* (1.381) - (2) 1.969 (1.289) - (3) 4.193** (1.613) - (4) 3.513** (1.502) - (5) 0.612 (1.492) - (6) 0.638 (1.460) - ln(Private Health Spending) - (1) — - (2) 3.430** (1.503) - (3) — - (4) 4.479** (2.102) - (5) — - (6) 1.845 (1.414) - ln(GDP per capita) - (1) 2.160 (1.400) - (2) −0.254 (1.894) - (3) 0.944 (2.997) - (4) −3.264 (4.543) - (5) 3.594** (1.531) - (6) 1.967 (2.281) - Income Gini Coefficient - (1) −9.114 (7.435) - (2) −9.480 (7.481) - (3) 14.414 (11.872) - (4) 8.791 (12.541) - (5) −2.852 (7.337) - (6) −3.593 (7.711) - ln(Schooling) - (1) 4.697** (1.895) - (2) 3.491* (1.847) - (3) 3.376 (2.282) - (4) 2.335 (1.902) - (5) 1.069 (1.961) - (6) 1.055 (1.854) - Education Gini Coefficient - (1) 0.013 (0.015) - (2) 0.013 (0.013) - (3) 0.011 (0.017) - (4) 0.016 (0.014) - (5) 0.013 (0.013) - (6) 0.012 (0.012) - Interpretation: - Lower inequality in health coverage (higher ln(WHO Health Coverage Ratio (Q1/Q5))) is associated with higher average life expectancy when public health spending and other determinants are held constant (columns (1), (3), and (5)). - Including private health spending (columns (2), (4), and (6)) reduces the coefficients on health-coverage inequality by somewhere between 7.5 and 20 percent (depending on specification), indicating much of the inequality effect operates through channel 1 (marginal benefit to the poor) rather than channel 2 (private spending responses). ### Quantified policy-relevant scenario - Closing the inequality gap in public basic health coverage: - Increasing h_it^Ineq from its most recent level—if it is less than 1—to 1 (i.e., equalizing Q1 and Q5 coverage) would raise life expectancy by 1.3 years, on average, in 83 countries (including 72 countries included in the regression analysis and 11 additional countries for which some other variables were not available), based on the estimate from column (5). ### Robustness - Results are robust to using healthy life expectancy (HALE) at birth as an alternative measure for health outcomes. - Table notes and estimation use robust standard errors; 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