## fm1702 ## Source details **Canonical URL:** [fm1702](https://www.imf.org/-/media/files/publications/fiscal-monitor/2017/october/pdf/fm1702.pdf) ## Other formats - [Markdown version](/-/media/files/publications/fiscal-monitor/2017/october/pdf/fm1702.pdf.md) - [Structured JSON version](/-/media/files/publications/fiscal-monitor/2017/october/pdf/fm1702.pdf.json) --- ### Preface: Health Inequality Findings (Annex Table 1.7.1) - Key findings: - Disparities in health outcomes are not narrowing in many countries. - In advanced economies, the gap in life expectancy between males with tertiary education and those with secondary education or less ranges from about 4 to 14 years. - The ratio of the infant mortality rate in the top socioeconomic quintile to that in the bottom quintile has increased in about half of emerging markets and developing countries. - Progress in health coverage has helped, but significant gaps remain in some emerging market economies and many low‑income countries. - Non‑health determinants (nutrition, education, healthy behaviors) increasingly determine health outcomes, especially in advanced economies. - Policy directions: - Better targeting of public spending to disadvantaged groups to improve access to quality education and health care. - Close education and health gaps to: - help reduce income inequality over the medium term, - address persistence of poverty across generations, - enhance social mobility, - promote sustained inclusive growth. - Combine health coverage expansion with policies addressing nutrition, education, and healthy behaviors. - Key metrics: - Life expectancy gap (males, tertiary vs. secondary or less): about 4 to 14 years. - Increase in infant mortality rate ratio occurred in about half of emerging markets and developing countries. ### Introduction: Global and Within‑Country Inequality — Trends, Drivers, Framework - Findings on trends: - Global inequality in 2015 ranged from 0.63 to 0.69 (Gini coefficient). - Differences in per capita income between countries accounted for about 65 percent of global inequality in 2013. - Over the past three decades, 53 percent of countries have seen an increase in income inequality; some recorded increases exceeding two points in their Gini coefficients. - Many advanced economies experienced sizable increases in income inequality driven primarily by growing income of the top 1 percent. - Drivers of inequality: - Global factors: technological progress, globalization, commodity price cycles (skill premium, job polarization). - Country factors: economic developments, financial integration, redistributive fiscal policies, labor/product market liberalization, recessions (example: bottom decile in the EU lost 17 percent relative to precrisis level during the Great Recession). - Wealth concentration: top incomes plus high saving rates → growing wealth inequality; top 1 percent wealth shares rising in many countries. - Welfare framework and policy inference: - Uses Atkinson’s monetary measure and equally distributed equivalent income (EDEI). - Historical welfare changes driven heavily by mean income growth even with high inequality aversion. - Redistributive policies should avoid unduly undermining growth; promoting growth and reducing inequality not necessarily incompatible. ### Fiscal Redistribution: Roles, Magnitudes, and Channels - Roles and comparative magnitudes: - Fiscal policy reduces inequality via progressive direct taxes and transfers, consumption taxes, and in‑kind spending (education, health). - More than three‑quarters of the difference in disposable income inequality between Latin America and advanced economies explained by greater fiscal redistribution in advanced economies. - Advanced economies (2015 averages and composition): - Average Gini disposable income: 0.31. - Average Gini market income: 0.49. - Direct taxes and transfers reduce income inequality, on average, by about one‑third. - Approximately three‑quarters of fiscal redistribution achieved on the transfer side; public pension benefits account for about half of that. - In‑kind transfers decrease the Gini coefficient by 5.8 points in five European economies; health transfers account for 3.6 points and education transfers 2.2 points. - Emerging market and developing economies: - Lower tax and transfer levels imply significantly lower redistributive impact. - Latin America sample: income taxes and transfers reduced Gini by 0.03. - Advanced economies sample: income taxes and transfers reduced Gini by 0.17. - Coverage and incidence: share of transfers going to bottom 40 percent is less than 40 percent in virtually all emerging market and developing economies. - ASPIRE evidence: transfers decrease Gini by median ~two points in Latin America and the Caribbean and in the Middle East and North Africa; by less than one point in other regions. - Policy trade‑offs: - With low revenues, trade‑off between financing redistributive direct transfers now versus investing in education and health to reduce future inequality. - Increased education access is strongly progressive; declines in education‑outcome inequality contributed to declines in income inequality (examples: decline ranged from 4.8 Gini points in Middle East and North Africa to 2.8 points in Latin America and the Caribbean for 1990–2005). ### Tax Progressivity, Capital Taxation, and Top Incomes - Trend in PIT progressivity: - Average top marginal PIT rate for OECD fell from 62 percent in 1981 to 35 percent in 2015. - Reshaping of tax systems since 1990s: higher exemption thresholds and lower top rates, shifting burden toward the middle. - Measured progressivity declined steeply in the 1980s and 1990s and remained broadly stable since. - Empirical and theoretical considerations: - No robust evidence of rising income tax elasticity for top earners; median estimated elasticities (Annex 1.4) show top 5 percent income share elasticity ≈ 0.11–0.22 depending on numerator (income shares or real incomes), top 1 percent higher (0.26–0.42). - Pareto index example: Pareto index of 2.2 → top 5 percent have ~19½ percent share of total income. - Social welfare weight interpretation: a social welfare weight for top earners of 0.38 implies government is indifferent between giving $2.63 to top earners and $1.61 to the rest. - Capital income taxation rationale: - Capital income is more unequally distributed and often taxed at lower rates than labor income. - Optimal capital tax formula: tK* = (1 − gK) / (1 − gK + eK); simplifies to tKR = 1 / (1 + eK) if marginal welfare weight = 0. - Empirical elasticity argument supports lower optimal capital tax if eK is high. - Corporate income tax and income shifting: - Corporate tax reduces arbitrage; international tax competition and capital mobility have pushed down statutory corporate tax rates 1990–2015, exerting downward pressure on PIT progressivity. ### Progressivity at the Bottom and Bottom‑Focused Instruments - At the bottom of the distribution: - Tax policy should ensure poor pay little or no tax and consider in‑work tax credits (example: EITC in the United States) to stimulate labor participation. - Steep phase‑outs create high marginal tax rates and adverse labor supply effects; in‑work benefits require robust administration. - Effective participation tax rates in Europe estimated between 30 and 85 percent (Immervoll and others 2007). - Taxes and deductions: - Recommendation to cap or eliminate deductions that disproportionately benefit the rich (mortgage interest, unlimited medical insurance deductibility) and reduce scope for converting labor to capital income. ### Universal Basic Income (UBI): Definition, Debates, and Simulation Evidence - Definition: uniform cash transfer of equal amount to all individuals. - Central debate: - Proponents: simpler administration, broader coverage, insurance against job uncertainty, potential to build support for structural reforms. - Opponents: high fiscal cost, large leakage to nonpoor, potential labor supply disincentives, severs ties between benefits and responsibilities. - Partial static simulations (baseline UBI = 25 percent of net median market income, additional to existing programs, no behavioral responses): - Selected cross‑country gross fiscal costs and impacts when all individuals covered: - Brazil (2013): Gross Fiscal Cost 4.6 percent of GDP; Reduction in Gini 0.05; Initial Poverty Rate 19.04 percent; Reduction in Poverty 11.6 percentage points; Annual UBI per person R$1,286. - Egypt (2012): 3.5 percent of GDP; Gini −0.06; Poverty 18.55 percent; Poverty −10.4 points; LE 725. - France (2010): 6.8 percent of GDP; Gini −0.04; Poverty 9.49 percent; Poverty −6.3 points; €2,122. - Mexico (2012): 3.7 percent of GDP; Gini −0.06; Poverty 19.68 percent; Poverty −12.0 points; Mex$4,994. - Poland (2013): 4.9 percent of GDP; Gini −0.04; Poverty 10.70 percent; Poverty −6.9 points; Zl 2,111. - South Africa (2012): 2.3 percent of GDP; Gini −0.05; Poverty 23.65 percent; Poverty −10.8 points; R1,584. - United Kingdom (2013): 6.7 percent of GDP; Gini −0.04; Poverty 9.28 percent; Poverty −6.0 points; £1,839. - United States (2013): 6.4 percent of GDP; Gini −0.05; Poverty 17.42 percent; Poverty −10.1 points; US$3,516. - Average gross fiscal cost across selected advanced economies: 6½ percent of GDP. - Average gross fiscal cost across selected emerging markets: 3.8 percent of GDP. - Alternate coverage variants (Children Only; Children and Elderly Only) reduce fiscal cost and scale down impacts; specific country figures reported (Annex Table 1.6.2). - General equilibrium and welfare simulations (calibrated to US and Bolivia): - US calibration: Efficiency cost larger when financing by progressive PIT than by VAT; as inequality aversion increases, UBI financed with progressive taxation can be preferred; EITC expansion yields higher welfare improvements than UBI of equivalent fiscal cost. - Bolivia calibration: UBI can be powerful against poverty given informality and weak PIT base; country specifics matter. - When UBI might be desirable: - Countries with near‑nonexistent transfers and capacity to finance progressively could consider UBI. - In countries with well‑performing transfer systems, replacing them with UBI may reduce progressivity and increase poverty. - Practical constraints and administrative capacity crucial; phased or subgroup universal schemes (children, elderly) possible intermediate options. - Fiscal space benchmarks (Annex 1.6): - For UBI financed solely from revenues, average general government revenue would need to be 47 percent of GDP for advanced economies and 32 percent of GDP for emerging market economies (sample of eight countries, base year 2016). ### Education and Health as Routes to Reducing Inequality of Opportunity - Education: - Gender enrollment gaps largely eliminated except in low‑income developing countries. - Socioeconomic status remains primary determinant of access; gaps in early childhood, secondary, and tertiary education persist. - Improving enrollment and quality for disadvantaged students: - lowers intergenerational persistence of inequality, - increases intergenerational earnings mobility, - improves efficiency by allocating resources based on ability. - Reallocating education spending toward disadvantaged students can raise outcomes without increasing total budgets (negative relationship between resource gaps and PISA scores). - Health: - Disparities in health outcomes by socioeconomic status are sizable and in many countries not narrowing. - In advanced economies, male life expectancy gap by education: about 4 years (Italy) to 14 years (Hungary). - Simulation: eliminating inequalities in basic health coverage could raise life expectancy, on average, by 1.3 years in low‑ and middle‑income countries (estimate based on Annex 1.7, column (5) coefficient). - Benefit incidence of public health spending often pro‑rich; out‑of‑pocket spending remains high in low‑income countries. ### Empirical Evidence: Health Coverage Inequality and Life Expectancy (Annex 1.7) - Regression specification (72 low‑ and middle‑income countries, 1995–2015): - y_it = α + β1 ln(h_it^Ineq) + γ′ X_it + c_i + τ + ε_it, where h_it^Ineq is WHO health coverage ratio (Q1/Q5). - Key coefficient estimates on ln(WHO Health Coverage Ratio (Q1/Q5)): - Column (1): 6.862*** (1.990) - Column (5): 4.422** (2.010) - Column (6): 4.092** (1.956) - Interpretation: - Lower inequality in basic health coverage is associated with higher average life expectancy controlling for spending, income, education, and distributions. - Column (5) estimate implies closing the coverage gap (h_it^Ineq → 1) raises life expectancy by 1.3 years on average across 83 countries (72 in regression + 11 with partial data). ### Model Simulations: EITC vs. UBI and Financing Trade‑offs (Annex) - Two reform packages each sized at 1 percent of GDP: EITC expansion and UBI introduction. - Financing alternatives and main results: - Financing via VAT (2 percentage point increase for certain cases) is regressive and lowers GDP more than financing via reductions in government consumption of tradable goods. - Financing via more progressive PIT is more redistributive but has larger adverse impacts on investment and GDP. - EITC expansion typically dominates UBI in welfare terms because it is targeted and supports labor supply. - UBI financed by cuts in government consumption of tradables has negligible impact on GDP in the US calibration but can reduce investment moderately through sectoral shifts. - Quantitative points: - VAT financing requires an increase of 2 percentage points to exactly finance a 1 percent of GDP transfer in modeled scenarios. - EITC and UBI calibration for welfare comparison: each equal to 1 percent of GDP. ### Data, Methods, and Dataset Construction - Gini dataset covers 152 countries with prioritization of disposable income Ginis where available; balanced five‑year window dataset constructed for 1980–2015 benchmarks. - Elasticities estimation (Annex 1.4) for 35 countries, 1981–2016; use of Pareto approximations when needed. - Growth regressions (Annex 1.5) find progressivity measures nonsignificant in most specifications — no strong relationship between tax progressivity and growth overall, with robustness checks performed. - UBI static simulations (Annex 1.6) use LIS microdata for Brazil, Egypt, France, Mexico, Poland, South Africa, United Kingdom, United States; baseline UBI = 25 percent of net median market income; partial static equilibrium (no behavioral responses) and variants considered. ### Policy Recommendations and Concluding Priorities - Fiscal policy design: - Consider combined distributional impact of taxes and transfers. - Strengthen means‑testing where administrative capacity permits; consider universal approaches where means testing is infeasible. - Reallocate and improve efficiency of spending—especially in education and health—to target disadvantaged groups. - Reduce tax preferences and loopholes that undermine progressivity; enhance taxation of immobile wealth (property, recurrent property taxes, transaction taxes, inheritance/gift taxes where administratively feasible). - Strengthen measures to curb international tax avoidance (BEPS, automatic exchange of information). - UBI considerations: - UBI may be attractive where transfer systems have large coverage gaps and can be financed progressively; in most advanced economies a UBI is unlikely to substitute effectively for existing progressive safety nets. - Evaluate country‑specific administrative capacity, fiscal space, labor supply responses, and distributional trade‑offs before adoption. - Education and health priorities: - Expand access and quality for disadvantaged students and health care recipients (early childhood programs, targeted subsidies, preventive care). - Rebalance spending toward cost‑effective primary and preventive health services; use taxes on unhealthy goods to raise revenue and improve health. - Broader macro policy: - Redistributive reforms should be consistent with fiscal sustainability and avoid unduly harming growth; financing choices matter for both macro outcomes and distributional impacts. _International Monetary Fund. Fiscal Monitor: Tackling Inequality (October 2017), content unit fm1702 (Chapter 1 and Annexes excerpts)._ ### Preface ### Preface ### Location - Preface: viii ### Function (as indicated by source) - Identifies the prefatory material for the Fiscal Monitor: Tackling Inequality publication. *Source: fm1702 - Preface (Fiscal Monitor: Tackling Inequality), International Monetary Fund* ### Annex Table 1.7.1. Life Expectancy at Birth and Basic Health Coverage Inequality ### Annex Table 1.7.1. Life Expectancy at Birth and Basic Health Coverage Inequality ### Key findings on health inequalities - Disparities in health outcomes are not narrowing in many countries. - In advanced economies, the gap in life expectancy between males with tertiary education and those with secondary education or less ranges from about 4 to 14 years. - The ratio of the infant mortality rate in the top socioeconomic quintile to that in the bottom quintile has increased in about half of emerging markets and developing countries, mostly reflecting slower improvements among the disadvantaged. - While progress in health coverage has contributed to improvements in health outcomes, significant gaps remain in some emerging market economies and many low-income countries. - Increasingly, health outcomes are determined by factors other than health care, including nutrition, education, and healthy behaviors, particularly in advanced economies. ### Implications and recommended policy directions - Better targeting of public spending to disadvantaged groups is required to improve access to quality education and health care. - Closing gaps in education and health services can: - help reduce income inequality over the medium term, - address the persistence of poverty across generations, - enhance social mobility, and - promote sustained inclusive growth. - Policies addressing health inequalities should consider non-health determinants of outcomes (nutrition, education, healthy behaviors) alongside health coverage expansion. ### Key statistics and metrics (as reported) - Life expectancy gap (males, tertiary vs. secondary or less): about 4 to 14 years. - Increase in infant mortality rate ratio occurred in about half of emerging markets and developing countries. *International Monetary Fund. Fiscal Monitor: Tackling Inequality (October 2017), Annex Table 1.7.1. Life Expectancy at Birth and Basic Health Coverage Inequality* ### Introduction ### Introduction ### Overview - Income inequality yields starkly different pictures depending on whether it is assessed across countries or within countries. - At the global level (abstracting from national boundaries), inequality has declined substantially over the past three decades, reflecting income convergence between developing and advanced economies aided by globalization and technological advancement. - Within national boundaries, the picture is mixed: some countries have experienced reductions in inequality while others, particularly advanced economies, have seen a significant uptick in inequality. - Rising inequality in advanced economies, together with job insecurity and stagnating real incomes for a segment of the population, has contributed to growing public backlash against globalization. ### Concepts and Measures - The primary focus is on income inequality, with emphasis on measures for which data are available for a large sample of countries and relatively long periods. - Key inequality concepts discussed: - Income inequality (standard metric), typically measured by the Gini coefficient (values between 0 and 1). - Lifetime inequality. - Wealth inequality. - Inequality of opportunity (impact of circumstances such as family socioeconomic status, gender, ethnic background). - Unless specified otherwise, “Gini income inequality” refers to disposable income or consumption (reflecting redistribution through taxes and transfers). - Note on terminology: variations in the Gini coefficient are commonly expressed in “points.” Example: an increase of 0.02 in the Gini coefficient is described as an increase “of two points.” ### Recent Trends and Drivers of Inequality - Global inequality in 2015 ranged from 0.63 to 0.69 (Gini coefficient). - Decomposition: differences in per capita income between countries accounted for about 65 percent of global inequality in 2013. - Historical context: - Global inequality rose dramatically during the nineteenth and much of the twentieth centuries as advanced economies outpaced others. - Over the past three decades, global inequality has declined sharply due in part to gains in several emerging market economies (notably China and India), which moved up along the global income distribution. - Within-country inequality has risen in many countries, partly offsetting between-country declines. - Cross-country heterogeneity: - Over the past three decades, 53 percent of countries have seen an increase in income inequality, with some countries recording increases exceeding two points in their Gini coefficients. - Most advanced economies have experienced sizable increases in income inequality, driven primarily by growing income of the top 1 percent. - Emerging market and developing economies show large disparities in recent inequality trends (for example, Eastern Europe and Central Asia saw increases during postcommunist transition years and declines afterward; Latin America increased in the 1980s and 1990s and then declined sharply). - Key forces influencing inequality: - Global factors: technological progress, globalization, and commodity price cycles. Technological advancement has contributed to the skill premium and job polarization (hollowing out of middle-class jobs). - Country-specific factors: economic developments, economic stability, financial integration, redistributive fiscal policies, and liberalization/deregulation of labor and product markets. Recessions can hit incomes at the bottom and top particularly hard (example: the bottom decile in the European Union experienced an income loss of 17 percent relative to its precrisis level during the Great Recession). - Relationship with wealth inequality: - Upsurge of top incomes combined with high saving rates has resulted in growing wealth inequality. - Many countries, including the United States, have seen an increase in wealth concentration at the top 1 percent. ### Growth, Inequality, and Social Welfare - The economic growth context matters for interpreting changes in income distribution. - 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 some countries, inequality declined due to broad sharing of growth benefits. - Income growth distribution: - In emerging market economies, all deciles benefited from growth even when inequality increased. - In advanced economies and low-income developing countries, economic growth accrued mainly to the top. - Poverty and growth: - High economic growth contributed to remarkable reductions in poverty in East and South Asia and the Pacific between 1985 and 2015. - Strong growth also led to sustained declines in absolute poverty in sub-Saharan Africa and Latin America and the Caribbean. - Welfare framework: - The analysis uses Atkinson’s monetary measure of welfare—the equally distributed equivalent income—to relate mean income, inequality, and social welfare. - Historical changes in social welfare have been heavily influenced by mean income growth, even with high aversion to inequality. - Policy inference: - Given the importance of growth for household welfare, redistributive policies should avoid unduly undermining growth. - Empirical evidence suggests that promoting growth and reducing inequality are not necessarily incompatible, but cross-country regression analysis does not clearly identify specific policies that achieve both simultaneously; country case studies may yield more actionable lessons. ### Fiscal Redistribution: Roles and Channels - Fiscal policy can reduce income inequality through multiple channels: - Progressive direct taxes and transfers reduce disposable income inequality (income after taxes and transfers) relative to market income inequality (income before taxes and transfers). - Consumption taxes affect “real” disposable income inequality. - In-kind transfer spending (education, health) reduces inequality of “full income” (disposable income adjusted for in-kind transfers) and affects market income inequality over time by shifting human capital distribution and promoting intergenerational social mobility. - The extent of fiscal redistribution depends on both the magnitude and progressivity of taxes and transfers. - Comparative evidence: - More than three-quarters of the difference in disposable income inequality between Latin America and the Caribbean (region with the highest average income inequality) and advanced economies (lowest average income inequality) can be explained by the greater extent of fiscal redistribution in advanced economies. ### Key Fiscal Policy Questions Addressed in the Fiscal Monitor - 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, or has increased mobility of capital and high-income individuals undermined the case for such policies? Is a wealth tax a good alternative? - Is there a case for the 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 their 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, Methods, and Analytical Approach - The analysis relies on: - Theoretical and empirical literature. - IMF work on inequality and fiscal policy. - Country experiences. - New analytical work, including static microsimulation analyses based on household survey data. - The report emphasizes the importance of an integrated approach to tax and transfer policy design (considering both taxes and transfers simultaneously). - It also draws on fiscal policy simulations using a dynamic general equilibrium model calibrated to country-specific data and behavioral parameters to illustrate potential impacts of budget-neutral tax and transfer measures on income inequality and economic growth. *Source: IMF Fiscal Monitor: Tackling Inequality, Chapter 1 — Introduction* ### CHAPTER 1 TACkLINg INequALITy ### CHAPTER 1 TACkLINg INequALITy ### Advanced Economies - Direct taxes and transfers reduce income inequality, on average, by about one­third. - In 2015: - Average Gini coefficient for disposable income: 0.31. - Average Gini coefficient for market income: 0.49. - Approximately three­quarters of fiscal redistribution was achieved on the transfer side of the budget, with public pension benefits accounting for about half of this. - Historical changes in fiscal redistribution: - 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, resulting in average disposable income inequality increasing broadly in line with market income inequality. - Observed policy implications: - Stability in average fiscal redistribution despite rising market income inequality suggests net decreases in the progressivity of redistributive instruments in some countries. - In several countries (examples noted: Denmark, Finland, Sweden), fiscal redistribution decreased over the more recent period despite rising market income inequality. - Indirect taxes and in‑kind transfers: - Indirect taxes primarily raise revenue and can be regressive; regressivity is typically much smaller when assessed against lifetime income or consumption. - In‑kind transfers decrease the Gini coefficient by 5.8 points in five European economies (Belgium, Germany, Greece, Italy, United Kingdom); health transfers account for 3.6 points and education transfers for 2.2 points of this impact. ### Emerging Market and Developing Economies - Lower overall tax and transfer levels imply significantly lower redistributive impact than in advanced economies. - 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. - Spending composition: - Low levels of direct transfers limit fiscal redistribution. - A high share of total transfers is absorbed by in‑kind education and health transfers. - Regional comparisons and magnitudes: - Latin America: income taxes and transfers reduced the Gini coefficient by 0.03 in the sample of Latin American economies. - Advanced economies: income taxes and transfers reduced the Gini coefficient by 0.17 in the sample of advanced 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 (that is, 0.14 out of 0.17). - Coverage and incidence of transfers: - Coverage (share of the poorest 40 percent who receive any public transfer) and benefit incidence (share of transfers received by the poorest 40 percent) are low outside emerging Europe and Latin America and the Caribbean. - 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. - Evidence from ASPIRE: - Transfers decrease the Gini coefficient by a median of about two points in countries in Latin America and the Caribbean and in the Middle East and North Africa, and by less than one point in other regions. - Policy trade‑offs: - With low tax revenues, many emerging market and developing economies face a 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 income inequality. - Empirical evidence shows public spending on education and health is in many cases not very progressive, but increases in education and health spending directed at expanding access to education have been strongly progressive. - A recent empirical analysis finds improved education outcomes (average years of schooling) are associated with a significant decline in inequality of education outcomes (inequality in years of schooling), which in turn has put strong downward pressure on income inequality. - 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 linking cash transfers to school enrollment and attendance at nutrition and health clinics can help reduce both human capital inequalities (future income inequalities) and current income inequalities. ### Progressivity at the Top and at the Bottom - Role of tax policy: - At the bottom of the income distribution, tax policy can support poverty reduction by ensuring poor individuals pay little or no tax and by providing in‑work tax credits (for example, Earned Income Tax Credit in the United States) to stimulate labor force participation and provide income support to low‑income groups. - Caution: steep phasing out of benefits creates high marginal tax rates and adverse labor supply effects; in‑work benefits can increase labor supply while reducing low‑skill wages, potentially transferring some benefit to employers. - Implementation of in‑work tax credits is most suitable in countries with strong tax administration based on withholding to curb noncompliance and false claims. - At the top of the distribution, taxation is the principal means of redistribution: - Optimal tax theory supports higher tax rates for upper‑income groups where redistributive gains dominate efficiency costs. - Taxation of different income categories matters: taxing capital income at lower rates than labor income typically reduces overall tax progressivity because capital income is usually distributed more unequally than wages and creates arbitrage opportunities. ### Progressivity of Personal Income Tax (PIT) - Trend: - Tax progressivity—the degree to which the average tax rate rises with income—has been on a declining trend in recent decades. - PIT progressivity declined steeply in the 1980s and 1990s and has remained broadly stable since then. - Empirical measures (median values and indices referenced in text and figures): - Average top marginal personal income tax rates for OECD member countries fell from 62 percent in 1981 to 35 percent in 2015. - Many tax reforms since the 1990s: increase in exemption threshold together with a lower top PIT rate, shifting tax burden from very low and very high incomes toward the middle. - Additional factors reducing measured progressivity: - Wealthy individuals often have more access to tax relief and opportunities to avoid taxes (for example, mortgage interest deductions and tax planning). - Empirical evidence suggests tax evasion is particularly high at the upper end of the income distribution. - Potential explanations evaluated via optimal tax theory: - No evidence of an increase in income tax elasticity for top earners. Existing empirical literature and IMF estimates do not show a rising trend in elasticity. - The share of income earned by top income percentiles has increased; Pareto index for the top 5 percent shows a clear downward trend over the past 35 years, implying a greater share of income in the upper tail. - Changes in social preferences: assuming a welfare weight of zero on 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 in the most recent years). The gap between this optimal rate and the lower actual top marginal PIT rates (average OECD top rate of 35 percent) suggests a rise in the social welfare weight placed on well‑off individuals; 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 high‑income earners from zero to about [value discussed in source text but not fully provided in excerpt]. *International Monetary Fund | October 2017* ### 0.38 over the past 35 years, assuming the other ### fm1702 - 0.38 over the past 35 years, assuming the other ### Decline in tax progressivity and interpretation - Analysis documents a decline in tax progressivity that is difficult to rationalize fully within optimal tax theory. - Possible explanatory factors discussed: - Changing preferences: Integrated Values Survey evidence shows 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: Better‑off individuals tend to have more political influence (lobbying, media access, political engagement). Ardanaz and Scartascini (2011) find countries with historically more unequal income distributions often have political systems dominated by elites. - Conclusion: 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 constraints may impede implementation. ### Empirical evidence on progressivity and growth - Empirical findings summarized: - There is no strong empirical evidence showing that progressivity has been harmful for growth. - Some studies on fiscal redistribution find no (or even positive) effects for nonextreme redistribution (for example, Ostry, Berg, and Tsangarides 2014). - Empirical evidence on the direct link between tax progressivity and growth is mixed; Annex 1.5 most specifications yield no effect of progressivity on growth. - The lack of a detected negative effect does not rule out negative growth impacts from extremely progressive tax systems (for example, near‑100 percent tax rates in Sweden or the United Kingdom in the 1970s). - Footnoted empirical findings: - Padovano and Galli (2002) find a negative relationship between progressivity and growth for 25 advanced economies in 1970–79, 1980–89 and 1990–98. - Rhee (2013) finds a negative relationship between income tax progressivity and economic growth within US states, with the negative effect coming with a three‑year lag. ### Pareto index and income concentration (figure notes) - Pareto model expression: The share of total income accruing to the qth percentile is derived as (q/100)^(Pareto index − 1)/(Pareto index). - Examples and interpretations: - A Pareto index of 2.2 means that the top 5 percent have approximately a 19½ percent share of total income. - Note on Pareto index: Lower values indicate income is more concentrated at the top of the distribution. - Data source for figures: IMF staff calculations, using World Wealth & Income Database. ### Social welfare weights and optimal marginal tax rates - Social welfare marginal weights represent the government’s relative value of an additional dollar of consumption at each income level. - Example numeric 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. - Figure 1.16 calculation notes: - Calculation is based on the optimal tax rate formula, using an average income tax elasticity of 0.4 and a Pareto index of 2.2. - The optimal marginal tax rate calculation accounts for additional social contributions (including any cap, if applicable) and consumption tax. ### Capital income taxation: rationale and implications - Key points: - Capital income (profits, interest, capital gains) is distributed more unequally than labor income and has risen over recent decades. - Capital income is often taxed at a lower rate than labor income, reducing overall tax progressivity. - Principal justifications for lower taxation of capital income: 1. Theoretical efficiency argument: - Taxing capital income can lower efficiency by effectively taxing future consumption at a higher rate than current consumption, discouraging saving, investment, and growth. - A comprehensive income tax that taxes capital income can make lifetime tax burdens unequal across individuals with identical lifetime incomes realized at different times. - Some economists argue that only consumption—or equivalently labor income—should be taxed; pension funds and tax‑favored vehicles can be used to balance efficiency and equity concerns. 2. Empirical elasticity argument: - Capital income appears more responsive (elastic) to taxation than labor income. - Taxation influences firm location and investment allocation; savings can be invested abroad where tax rates are lower. - Differential tax treatment (for example, tax‑favored capital gains versus dividends/interest) creates avoidance opportunities. - In optimal capital taxation theory, a higher elasticity of capital income implies a lower optimal capital tax. - Optimal capital tax formula (as given): - tK* = (1 − gK) / (1 − gK + eK), where gK is the social welfare weight on earners of high capital income and eK is the elasticity of capital income with respect to the marginal tax rate. - Simplifies to tKR = 1 / (1 + eK) if the marginal welfare weight is set to zero. ### Corporate income tax, income shifting, and international trends - Roles of corporate income tax: - Enforces taxation of labor income when distinguishing labor from capital income is difficult and when individuals can choose the form of income declaration. - Mitigates arbitrage that shifts personal income to alternative bases taxed at lower rates. - Taxes on distributed and retained earnings interact with withholding rules and tax treaties; corporate tax is important where withholding is restricted by treaties. - International trend: - International tax competition and capital mobility have led to a steady downward trend in corporate income tax rates, reducing overall tax progressivity and putting downward pressure on PIT rates. - Figure 1.17 shows the average statutory corporate income tax rate for balanced samples of 37 advanced economies, 92 emerging markets, and 59 low‑income developing countries for 1990–2015. - Optimal top income tax with income shifting (formula provided): - t* = (1 + s ∙ τ ∙ ae) / (1 + ae), where s is the share of marginal income shifted from the individual base, τ is the tax rate on the alternative tax base (for example, corporate income or capital income), and other parameters as previously defined. ### Fiscal transfers: universality versus means‑testing - Practical patterns: - Most advanced economies combine means‑tested income support programs (minimum income guarantees) with universal categorical family benefits (universal child benefits, social pensions). - Most developing economies spend substantially less on such transfers and often use indirect targeting (geographic, disability, widowhood, public works) due to administrative constraints, leading to coverage gaps among the poor and leakage to the nonpoor. - Administrative and behavioral considerations: - Means testing requires administrative capacity to verify incomes, process applications, and deliver transfers; where capacity is lacking, cruder targeting leads to undercoverage and leakage. - Means‑tested programs can create labor supply disincentives if benefits are withdrawn quickly as income rises; evidence shows sizable disincentives in many advanced economies. - Immervoll and others (2007) estimate effective participation taxes vary between 30 and 85 percent in European countries (higher values 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; METR has increased since 2011 with large variation across members (see Figure 1.19). - Policy responses to disincentives: - Conditioning eligibility on participation in active labor market programs. - Use of in‑work benefits (wage subsidies) to enhance work incentives for lowest‑income households. ### Universal Basic Income (UBI): features, debates, and simulated impacts - Definition used: UBI defined as a cash transfer of an equal amount to all individuals in a country. - Central debate: - Proponents: UBI can better address poverty and inequality than means‑tested programs (information constraints, administrative costs, limited take‑up); can address income uncertainty from technological change; can build public support for structural reforms (eliminating subsidies, broadening consumption tax). - Opponents: UBI is very costly; leaks massively to the nonpoor (including wealthy households); discourages labor supply; severs links between rights and responsibilities of job seekers. - Simulated/calibrated impacts (for a UBI set at 25 percent of median per capita income, additional to existing programs and without accounting for financing or behavioral responses): - Distributional impacts (selected emerging market and developing economies): - Average reduction in inequality: 5.3 Gini points. - Average reduction in relative poverty: about 10.4 percentage points. - Reduction effects are higher where income is more unequally distributed and the proportion of the population below the poverty line is large. - Fiscal cost estimates: - A UBI set at 25 percent of median per capita net market income would cost about 6½ percent of GDP and 3¾ percent of GDP. *Italicized source attribution: Content from IMF Fiscal Monitor chapter and figures as provided in the supplied PDF excerpt.* ### Annex 1.6 presents details on the methodology and under­ ### fm1702 - Annex 1.6 presents details on the methodology and under­ ### Methodology and assumptions for UBI partial static equilibrium analysis - Annex 1.6 provides methodology and underlying assumptions for the partial static equilibrium analysis used in the UBI exercises. - Many empirical assessments of UBI implementation use a similar methodology (example cited: OECD 2017). - The fiscal envelope for UBI simulations is often set equal to the sum of existing universal and means‑tested noncontributory transfers (see Annex 1.6). ### Fiscal space and financing considerations - Given limited fiscal space in many countries, simulations focus on budget‑neutral options. - Budget‑neutral financing can involve any combination of cutting spending or increasing direct or indirect taxes. - Other revenue sources could include elimination of energy and other subsidies (case example: India in Box 1.6). - Illustrative fiscal‑revenue benchmark (Annex 1.6 sample of eight countries, base year 2016): - average general government revenue would need to be 47 percent of GDP for advanced economies if UBI financing relies solely on revenues. - average general government revenue would need to be 32 percent of GDP for emerging market economies in that case. ### Distributional mechanics of replacing existing transfers with a UBI - A UBI distributes existing transfers uniformly across the population; net redistributive impact depends on how it is financed and on current transfer system coverage and progressivity. - Example: South Africa (LIS 2012 microdata; figures from Figure 1.22): - For the lowest two income deciles, about 65 percent of households in the bottom two deciles are covered under the existing transfer system. - For the lowest two income deciles under substitution of existing transfers by a UBI: - average drop in benefits for households covered under the existing system is 19 percent of per capita disposable income in South Africa (Figure 1.22, panels 1 and 2). - average gain for the remaining 35 percent of households in the bottom two deciles (not previously covered) is about 150 percent of their per capita disposable income. - For the bottom income decile specifically (South Africa, 2012): - UBI represents 130 percent of per capita equivalent disposable income (PCDI). - current transfers represent 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. - households in the bottom decile not previously receiving transfers would gain, on average, 274 percent. - If a UBI is financed through an increase in indirect taxes (for example, a flat tax on consumption), the net impact could be progressive if income (and consumption) inequality is very high. ### When a UBI might be a desirable substitute - The desirability of replacing or complementing existing safety nets with a UBI depends on: - relative generosity, - coverage of lower‑income groups, - progressivity of benefits, - efficiency, - administrative capacity and prospects for technological improvements in targeting/administration. - Country typology and implications: - Countries with almost nonexistent transfer systems: - A UBI could be an option if it can be financed through progressive taxation and fiscal reforms (such as elimination of energy subsidies in oil‑exporting economies) without large efficiency costs. - Low‑income developing countries with low coverage and limited means‑testing capacity could consider UBI to strengthen safety nets. - Countries whose transfer systems perform well (examples: France and the United Kingdom): - Replacing existing systems with a UBI would result in large reductions in progressivity and losses in benefit size for many poor households and could even increase poverty. - Priority should be given to reforming and strengthening the current system to enhance coverage and targeting. - Countries whose transfer systems perform poorly: - Replacing poorly performing systems with a UBI would expand coverage to all households but lower progressivity and reduce benefits for the average beneficiary under the current system. - Trade‑off: increased coverage versus reduced progressivity; most relevant where current system has low coverage but relatively good progressivity. - Case note: Brazil—relatively low existing coverage but relatively high progressivity; replacing with UBI could improve coverage but cause sizable losses for some lower‑income households. - India discussed in Box 1.6 as an additional illustration (Box not reproduced here). ### Welfare and general equilibrium findings - General equilibrium simulations (Annex 1.3 and Box 1.2 welfare framework) consider behavioral responses, financing modalities, and equity‑efficiency trade‑offs jointly. - Model calibrated to the US economy (high‑level findings): - Efficiency cost (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. - Comparing UBI 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. - Model calibrated to Bolivia (developing economy example): - Structural differences (dominant informality; no formal personal income tax; low effective PIT rates) lead to low formal labor supply elasticity and different outcomes. - Costs to efficiency associated with UBI and its financing can be offset by gains to groups in equity metrics even for low aversion to inequality. - A UBI can be powerful for combating poverty and extreme poverty, but that does not imply UBI is necessarily the appropriate redistributive instrument—deeper country‑specific analysis required. ### Additional objectives and trade‑offs - A UBI can provide insurance against increasing job insecurity (for example, due to technological progress), offering stable income and limiting impact of income and employment shocks. - Insurance benefits must be weighed against potential moral hazard and disincentives for skill adaptation. - Uniform transfers provide greater social insurance to lower‑income groups less able to self‑insure. - UBI could be used to build political and economic support for broader structural reforms (for example, removal of energy subsidies) since energy subsidies largely accrue to higher‑income groups; replacing them with a UBI targeted to protect lower‑income groups could generate fiscal space and health and environmental benefits. ### Summary judgment and practical considerations - If means testing could be perfectly designed and implemented, it would be superior to universality; in practice administrative capacity and information constraints often make the choice less obvious. - Universal transfers can fill coverage gaps where administrative constraints prevent effective means testing, but universality also creates leakage to higher‑income groups and requires financing with potentially distortionary taxation. - The choice or combination of instruments depends critically on: - country administrative capacity, - availability of financing, - potential impact on labor supply, - coverage and progressivity trade‑offs, - the specific design and targeting performance of existing safety nets. ### Education and health: alternative routes to reducing inequality of opportunity - Public spending on education and health can directly reduce market income inequality and promote both growth and equity by enhancing human capital and productivity. - Education findings: - Gender enrollment gaps have been largely eliminated except in low‑income developing countries (Figure 1.24). - Socioeconomic status remains a primary determinant of access to education, especially in emerging market and developing economies; sizable gaps remain in early childhood, secondary, and tertiary education (Figure 1.25). - Primary education gaps have mostly narrowed, but children from disadvantaged families still have low access in sub‑Saharan Africa and Middle East and North Africa, and to a lesser extent in emerging and developing Asia and Latin America and the Caribbean. - Disadvantaged students perform substantially worse across regions; one contributor is enrollment in schools with fewer resources (educational materials and staff). - Improving enrollment and quality for disadvantaged students: - lowers persistence of income inequality across generations, - is associated with larger intergenerational earnings mobility (Figure 1.26), - improves economic efficiency by allocating education resources more on ability than family socioeconomic status, - reduces future income inequality as measured by years of schooling. - Public education spending can relax household budget constraints and raise household consumption; benefit incidence varies: - tends to be pro‑poor in advanced economies (except tertiary spending, which tends to be regressive), - 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 education outcomes while keeping total public education budgets unchanged (negative relationship between resource gaps and average PISA scores, Figure 1.28). - Health findings: - Disparities in health outcomes by socioeconomic status are sizable and not narrowing in many countries. - In advanced economies, gap in life expectancy 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). - Narrowing education and learning gaps can also help reduce disparities in health outcomes given strong positive association between education and health. _International Monetary Fund | October 2017 (excerpts from Chapter 1 and Annex 1.6)_ ### CHAPTER 1 TACkLINg INequALITy ### CHAPTER 1 TACkLINg INequALITy ### Inequality in Education - Regional coverage: 6 in MENA, 4 in EDA, 3 in CIS, 9 in EDE, 35 in AE, and 10 in LAC. - Key patterns and measures: - Inequality is evident in access to education across early childhood attendance, primary completion, lower‑secondary completion, upper‑secondary completion, and tertiary completion (figures summarized in the chapter). - Test‑score inequality: disadvantaged students have higher odds of low performance on the Program for International Student Assessment (PISA) science assessment compared with nondisadvantaged students (chapter shows ratios of disadvantaged students’ likelihood of low performance to that of nondisadvantaged students). - Education inequality is correlated with inequality of opportunity: intergenerational income elasticity is used as a comparator and education measures such as college completion rates (ratio of bottom to top quintile) and PISA test‑score inequality are linked to intergenerational income mobility. ### Inequality in Health Outcomes and Coverage - Trends and magnitudes: - 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 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 (Figure 1.30). - Basic health coverage gaps persist in some emerging market economies and many low‑income countries; quality of care received by the poor is substantially lower than that received by the rich. - Out‑of‑pocket spending has declined modestly, progress has been slow, and it remains high in low‑income countries and emerging market economies (Figure 1.32). - The benefit incidence of public health spending is pro‑rich in many countries because the rich typically use more health care services. - Impacts of narrowing health gaps: - Narrowing health outcome gaps improves social welfare directly, raises productivity, employment, and earnings, and improves school attendance and education outcomes, contributing to equality of opportunity and income equality. - 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 (see Annex 1.7 for methods and discussion). ### Policy Implications and Conclusions - Fiscal policy is a powerful tool to tackle high or rising inequality; appropriate design depends on country‑specific factors: - Social preferences: - Countries differ in priorities (sharing gains of growth more equally across the income distribution versus 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 benefit. - Administrative capacity: - Countries with lower administrative capacity have more limited redistribution tools. - High‑income countries can implement more sophisticated progressive fiscal policies (means‑tested benefits, progressive income tax schedules); low‑income countries typically must rely on less sophisticated instruments. - Recent technological advances offer opportunities to improve design and implementation through improved collection, sharing, and cross‑checking of information. - Fiscal pressures: - Redistributive fiscal policies must be consistent with fiscal sustainability. - Countries with high debt or fiscal deficits wishing to scale up redistribution need to generate fiscal space. - Many advanced economies already have high tax and spending levels, limiting room for further increases without adverse growth effects; hence the importance of reallocating spending and improving spending efficiency. - General principles: - Consider combined distributional impact of both tax and transfer instruments. - Regressive but efficient tax financing can fund progressive spending. - Nonfiscal instruments can complement fiscal policies to achieve redistributive objectives while minimizing efficiency costs. ### Enhancing Progressivity of Taxation - Trends and challenges: - Progressivity of the personal income tax (PIT) has declined over the past three decades in many advanced economies. - Reducing opportunities for tax avoidance and evasion—especially among high‑income earners—is important for both efficiency and equity. - Recommended tax policy measures: - Personal income tax (PIT): - In emerging market and low‑income developing countries with lower administrative capacity and larger informal sectors, set a relatively high tax‑exempt threshold and then focus on expanding PIT coverage by gradually decreasing the threshold in line with administrative capacity improvements. - In many of these countries, the PIT does not have a threshold; introducing one would ease administrative burden, strengthen tax compliance, and enhance progressivity. - Deductions and tax preferences: - Cap or eliminate deductions such as the tax‑favored status of fringe benefits and the unlimited tax deductibility of medical insurance costs or mortgage interest, where applicable. - Reduce scope for converting labor income into capital income. - Capital income and gains: - Ensure adequate taxation of capital income by reducing differences between taxation of different capital income types, potentially requiring higher and uniform taxation of capital gains. - The OECD/G20 Base Erosion and Profit Shifting (BEPS) initiative aimed at limiting international tax avoidance is a welcome first step. - Extend automatic exchange of information to more countries and types of incomes where feasible. - Leverage technology for tax administration provided revenue authorities have access to data and adapted laws. - Taxation of immobile capital and wealth: - Most countries have room to enhance revenues from taxation of immobile capital. - Relevant instruments include recurrent taxes on property or net wealth, transaction taxes, inheritance and gift taxes. - Taxes on real estate or land are equitable and efficient and remain underused in many countries; higher taxes on second homes can have a stronger equity impact. - Effective implementation of taxation of immovable property may require a sizable investment in administration. *International Monetary Fund | October 2017* ### CHAPTER 1 TACkLINg INequALITy ### CHAPTER 1 TACkLINg INequALITy ### Consumption Taxes and Excises - 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 (such as 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) and Means‑Tested Programs - The choice between universal or 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; - the policy challenges being addressed (e.g., substitution for or complement to existing safety nets, response to labor income uncertainty, or to build support for structural reforms). - Advanced economies: - Where safety nets are generous and progressive, a UBI is unlikely to be an effective substitute. - Priority should be to address gaps in coverage or progressivity (for example, reforming eligibility rules or promoting benefit take‑up). - Many advanced economies already have categorical family benefits with universal reach (such as child benefits and social pensions). - Countries with means‑tested programs should address disincentives for labor force participation by strengthening administrative capacity and information systems and using well‑designed in‑work benefits. - Emerging market and developing economies: - A UBI could be an attractive alternative where systems have large coverage gaps and low progressivity, provided it can be efficiently financed. - More likely where countries currently 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 must be consistent with other fiscal priorities and fiscal sustainability, and require strengthened capacity to distribute cash transfers and strong communications campaigns. - Administrative, political, and fiscal constraints suggest a gradual approach—possibly focusing first on universal coverage of subgroups (such as children and the elderly). - Recent technological developments—biometric identification, information digitalization, electronic finance—enhance the attractiveness of a UBI while administrative capacity for targeting improves. - When UBI is proposed to strengthen social insurance against growing labor income uncertainty, it should be considered as part of a broader suite 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 - Objectives: focus on improving outcomes for the disadvantaged and improve redistributive effect of public education and health spending. - Improving access to quality education and health care for the disadvantaged: - Education: expand basic—primary and secondary—education to eliminate enrollment gaps; for 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 can be expanded for tertiary education. - Health: priority is universal health coverage of a broad package of essential health services. Examples of countries that expanded 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 an important role. - Public provision or incentives may be required where low‑income households live in less developed areas. - Conditional cash transfer programs and information dissemination can stimulate demand among the disadvantaged. - Improving learning and quality of health care for the disadvantaged: - Develop and enforce appropriate regulations and guidelines and allocate more resources to schools and health care facilities used primarily by 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 could boost employment and earnings; parenting skills programs have shown positive effects (examples: Bangladesh, Colombia, Jamaica). - Food subsidy programs and healthy meal programs for students are effective for nutrition (Frisvold 2015). - Improving access to safe water and sanitation could generate substantial health benefits (WHO and UNICEF 2017). - Taxing unhealthy behaviors: - Taxing smoking and alcohol consumption 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 such taxes might fall on the poor, overall effect 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 teacher numbers to student declines in high‑need schools can yield fiscal savings with little effect on outcomes. - 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 (Box 1.1) - Baseline projection (assuming within‑country inequality unchanged): - 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 assumptions and scenarios: - If within‑country inequality evolves with economic growth based on the Kuznets curve, the global Gini would fall to 0.63 in 2035 (faster decline). - For global inequality to remain stable, the within‑country Gini coefficient would need to worsen in each country by 6.6 Gini points (noted as a remote scenario). - Under a more pessimistic economic growth scenario, the global Gini coefficient 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 faster than 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. - Data and methodology note: projections use population growth from the United Nations and per capita income growth projections from the IMF and World Bank, OECD, and Consensus Forecasts, with household surveys adjusted for underreporting of self‑employment income and undersampling of rich households. ### Welfare‑Based Measures (Box 1.2) - Welfare measures can help policymakers assess trade‑offs between equity and efficiency by reducing income distributions to single numbers under explicit assumptions. - Equally Distributed Equivalent Income (EDEI) and Atkinson measure: - Atkinson inequality I ranges between 0 and 1; I = 1 is complete inequality and I = 0 is complete equality. - Interpretation: a value of 0.3 means that if incomes were equally distributed, society would need only 70 percent (1 − 0.3) of present national income to achieve the same level of welfare. - EDEI definition and relationships as presented: - Operationally, EDEI satisfies U(EDEI) ∫ f(y) dy ≡ ∫ U(y) f(y) dy ≡ W, in which f is the distribution of income, U is the “utility” of the individual with income y, and W is average welfare under the current distribution. - The Atkinson measure is defined as I = 1 − EDEI/μ, in which μ is the mean of the current distribution. It can be shown that W = μ(1 − I). - The change in welfare can be expressed as ΔW = Δμ + Δ(1 − I), in which Δ indicates the percentage operator. - If U is isoelastic, then U(y) = (y^(1 − γ) − 1)/(1 − γ), in which γ is the degree of aversion to inequality. - Then I = 1 − [((W^(1 − γ) + 1)^(1/(1 − γ)))/μ], and EDEI = [((1 − γ) W + 1)]^(1/(1 − γ)). - Figure 1.2.1 (as described) shows social welfare (EDEI) is dominated by mean income across a plausible range of inequality aversion parameters (γ = 0.22, γ = 0.53, γ = 2.0). ### Bolivia Case Study - Bolivia experienced strong economic expansion during 2005–12 accompanied by: - a sizable decrease in inequality of 8.7 Gini points; - a poverty reduction of 20 percentage points. - IMF (2016) and other studies used a dynamic stochastic general equilibrium model calibrated to Bolivia to disentangle contributions of domestic and global factors. - Key quantified findings: - The 2 percent increase in potential growth observed during 2006–14 is explained mostly by the commodity price boom, which led to higher profitability in the energy and agricultural sectors and a surge in government revenues. - Revenues allowed more infrastructure investment, improving private sector productivity. - The fraction of skilled individuals in the urban labor force rose from 30 percent to 45 percent between 2000 and 2012. - The increase in average skill level of the workforce accounts for about one‑third of the observed decline in inequality. - Higher prices for tradable agricultural commodities raised rural incomes and demand for nontradable goods, bidding up wages for the lowest‑skilled workers, accounting for another one‑third of the observed decrease in inequality. - Expansion in social programs, including conditional cash transfers funded 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 allowing social program expansion. - Price controls on final user prices attenuated potential negative effects of higher energy prices on economic activity and attenuated potential income increases for rural households from higher agricultural prices. - Figures referenced: - Figure 1.3.1. Contribution of Individual Factors to GDP Growth (Percent). - Figure 1.3.2. Contribution of Individual Factors to Decline in Gini Coefficient (Gini points), with numerical contributions shown in the figure area (for example, values listed near the figure include −3.3, −2.7, −0.5, −2.2). *International Monetary Fund | October 2017 — CHAPTER 1 TACkLINg INequALITy* ### Box 1.3. Bolivia: Inequality Decline during a Commodity Boom ### Box 1.3. Bolivia: Inequality Decline during a Commodity Boom ### Measuring Tax Progressivity - Common simple measure (Pigou 1928): ratio of the change in the average tax rate to the change in income. - Example illustrated: flat tax of 30 percent with a personal allowance of 50 percent of average income produces substantial changes in progressivity across the income distribution (Figure 1.4.1). - Peter, Buttrick, and Duncan (2010) approach: calculate progressivity as the average tax rate progression over 100 data points ranging from 4 to 400 (also 100 to 300) percent of per capita GDP (slope of regression of average tax rate on income); estimates expand until the end of 2005. - Kakwani (1977) approach: progressivity measured as twice the area between the income Lorenz curve and the tax payment Lorenz curve (gray area in Figure 1.4.2). - Drawbacks: depends on pretax income distribution; a relatively even pretax distribution can make a tax system appear less progressive; changes in pretax income (for example from behavioral responses to higher top tax rates) can alter the measure. - Proposed “progressive tax capacity” measure: - Essentially the Kakwani measure calculated over a fixed range of incomes (0–500 percent of per capita GDP), with each income given equal weight. - Constructed using data on tax systems of OECD countries (tax brackets, rates, allowances, surtaxes, most tax credits) and calculated from 1981 onward. ### Taxes on Wealth Stocks - Wealth distribution is very unequal (Annex 1.2); taxing wealth appears potentially progressive. - Argument: taxing income from wealth rather than taxing wealth itself is more equitable and efficient. - Wealth taxes are equivalent to taxing a fixed return to wealth, leaving excess return untaxed; thus burdensome for investors holding safe assets and beneficial for wealthier investors taking riskier portfolios. - Role for wealth taxes when taxing returns to capital is administratively or politically difficult. - Real estate property taxes: - Common practice to tax estimated value directly. - Advantage: levied on least-mobile asset. ### Taxes on Wealth Transfers (Gifts, Inheritances, Estates) - Can reduce wealth and intergenerational inequality. - Opposing arguments: - Double-taxation concern: bequeathed wealth was taxed when originally earned; inheritance taxes therefore unfair. - Behavioral concern: if assets are accumulated to leave bequests, taxing bequests may affect labor supply and saving. - Counterarguments: - Some incomes were never taxed; taxing transmission offers opportunity for minimum taxation. - With sufficiently large allowances, double taxation affects only very rich individuals and strengthens overall progressivity. - Any reduction in labor supply by extremely wealthy individuals could contribute to more equal income distribution. - Equity preference: - Inheritance taxes preferable to estate taxes because a lower tax applies when a bequest is split among many heirs. - Important to integrate gift and inheritance taxes to address avoidance opportunities. - Practical considerations: - Politically sensitive and administratively costly. - Beneficial equity impact can be lost if loopholes allow avoidance. - Historical revenue: none of the Group of Seven countries collected more than 1 percent of GDP per year from estate, gift, or inheritance taxes over the past four decades (Boadway, Chamberlain, and Emmerson 2010). ### Adopting a Universal Basic Income to Support Subsidy Reform in India (Microsimulation Results) - Context: - Analysis based on India’s 2011–12 National Sample Survey. - Reform simulated: replace food and fuel subsidies with a fiscally neutral UBI. - Fiscal envelope: combined fiscal cost of the PDS and energy subsidies in 2011–12. - UBI amount financed: 2,600 rupees (Rs) per person annually (about US$54) in 2011–12, equivalent to about 20 percent of median per capita consumption in that year. - Fiscal cost of the UBI: approximately 3 percent of GDP. - Energy “tax subsidy” elimination scenario (reflecting environmental externalities) would require large retail price increases: - Gasoline: 67 percent - Diesel: 69 percent - Kerosene: 10 percent - LPG: 94 percent - Coal: 455 percent - Note on timing and reforms since 2011–12: - Analysis does not account for subsidy reforms enacted after 2011–12 (fuel price liberalizations and tax/price changes through 2016/17). - By fiscal year 2016/17, budget-reported subsidies reduced to 0.2 percent of GDP for fuel; food subsidies reduced to about 1.5 percent of GDP. - Improvements in identification (Aadhaar) and Direct Benefit Transfer have potential to improve targeting and reduce fiscal cost. - Microsimulation main findings: a UBI would outperform the PDS and energy subsidies on three dimensions: - Coverage: - PDS exhibits significant undercoverage of lower-income groups (nearly 20 percent undercoverage) despite broad population coverage (Figure 1.6.1). - Progressivity: - Higher-income deciles receive a larger share of PDS spending (the richest 40 percent of households receive 35 percent). - Implicit energy subsidies are highly regressive: top two income quintiles receive 69 percent of implicit subsidies versus 17 percent for the bottom two quintiles (Figure 1.6.1). - Generosity: - Replacing PDS and implicit energy subsidies with a UBI would substantially increase generosity of benefits received by lower-income groups (Figure 1.6.2). - Implementation caveats and success factors: - Introduction of UBI and large subsidy reforms require careful planning to overcome political, social, and administrative challenges. - Lessons from energy subsidy reform that enhance success include: comprehensive energy sector reform plan; transparent and extensive communication; phased price increases; measures to protect the poor; institutional reforms to depoliticize energy pricing (for example, automatic pricing mechanisms). ### Annex: Gini Income Inequality Data Set and Wealth Inequality Dimensions - Gini data set construction: - Covers 152 countries: 35 advanced economies, 65 emerging market economies, 52 low-income developing countries. - Gini estimates chosen from a single source per country, prioritizing disposable income; otherwise consumption or expenditure. - Data sources: Luxembourg Income Study (LIS), Eurostat Income Inequality Statistics (EU-SILC), OECD Income Distribution Database (IDD), SEDLAC for Latin America and the Caribbean, World Bank PovcalNet. - Steps to build balanced five-year window data set (1980–2015): - Expand annual Gini database using alternative sources (e.g., apply absolute changes from EU-SILC or OECD to LIS estimates when LIS not annual). - Create five-year-window database using benchmark years (1980, 1985, 1990, 1995, …). Missing benchmark year values filled by averaging adjacent benchmark years. - Construct balanced sample by linear interpolation at benchmark years and constant extrapolation backward/forward up to two benchmark years. - Resulting balanced sample: - For period 1985 (1995) to 2015 includes 95 (112) countries: 30 (33) advanced, 33 (44) emerging market, 32 (35) low-income developing. - Coverage limited in some regions, notably Middle East and North Africa. - Notes on comparability: - Gini measures differ systematically across regions because advanced economies and Latin America and the Caribbean typically use income-based Ginis, while other regions often use expenditure/consumption-based Ginis (which tend to show more equality). - Wealth inequality evidence (limited sample): - Wealth is more unequally distributed than income. - OECD average: top 10 percent hold 50 percent of net wealth versus top 10 percent holding 24 percent of income (Annex Figure 1.2.1). - United States: top 1 percent holds nearly 40 percent of total net wealth. - Financial assets (currency, equities, fixed income, life insurance, pensions) make up large share of household wealth at the very top (Annex Figure 1.2.2). - Wealth inequality has risen considerably in recent decades; rapid growth of wealth in top decile in China has led to concentration similar to the United States (Annex Figure 1.2.3). *International Monetary Fund | October 2017* ### Annex Figure 1.2.1. Wealth and Income Shares of Top ### Annex Figure 1.2.1. Wealth and Income Shares of Top ### Key empirical findings on wealth and income concentration - 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), an increasing share of income accruing to capital, and high saving rates at the top combine to produce a “snowball effect” on wealth distribution. - Wealth composition and distribution highlights (average among OECD countries, 2010 or latest available year): - Household wealth is partitioned by quintiles and top percentiles into nonfinancial assets, financial assets, liabilities, and net wealth (sources: Murtin and Mira d'Ercole 2015; OECD Wealth Distribution Database). - In 2014, the share of wealth for the bottom 50 percent is close to zero and can be negative as a result of negative equity in homes (source: World Wealth & Income Database; note in figure). ### 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. - Measures and cross‑country patterns: - Intergenerational income elasticity measures the predicted percentage change in a child’s earnings attributable to a percentage change in parents’ earnings (Annex Figure 1.2.5). - Inequality of opportunity (relative) captures the proportion of income inequality explained by circumstances beyond individual control (Annex Figure 1.2.6). - Both measures indicate inequality of opportunity is higher, on average, in emerging markets—especially in Latin America—than in advanced economies; among advanced economies, Nordic countries exhibit much higher social mobility. - Evidence on time‑series within countries is limited; the few studies cited have failed to find a strong relationship between changes in inequality and social mobility over time (Amaral and Perez‑Arce 2015; Perez‑Arce and others 2016). - Public policies—such as access to education—can help limit the impact of changes in inequality on social mobility. ### Gender inequality: scope and macroeconomic implications - Regional patterns in multi‑dimensional gender inequality (education, health, financial access, legal rights, 2015): - Europe appears most gender‑equal; Asia and Pacific and the Western Hemisphere follow; sub‑Saharan Africa and the Middle East have the highest gender inequality (Annex Figure 1.2.7). - Select statistics: - In low‑income developing countries, only 9 girls are enrolled in secondary education for every 10 boys. - In South Asia, 37 percent of women have an account at a financial institution versus 54 percent of men. - In the Middle East and North Africa, men are twice as likely as women to have an account. - Women are barred by law from specific professions in 79 countries; in some countries restrictions impede women’s property rights. - Women’s labor force participation varies from a low of 21 percent in the Middle East and North Africa to more than 63 percent in East Asia and the Pacific and sub‑Saharan Africa. - 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 (IMF 2017c). - Macroeconomic implications: - Gender equality is positively associated with per capita GDP and competitiveness. - Higher female economic participation and earnings translate into higher expenditure on children’s school enrollment. - Gender gaps in economic participation reduce the pool of talent and can result in total factor productivity losses. - In advanced economies, income inequality arises mainly through gender gaps in economic participation; in emerging and low‑income countries, gender gaps in education, political empowerment, and health are key obstacles to more equal income distribution. ### Model simulations: structure and calibration - A dynamic stochastic general equilibrium model is developed to quantify effects of fiscally neutral redistributive reforms on income distribution and the macroeconomy (annex builds on Lizarazo, Peralta‑Alva, and Puy 2017). - Key model features and assumptions: - Households: predetermined types by education level, idiosyncratic productivity shocks, fixed skill level over the short–medium term (up to five years). - Three industrial sectors with differing technologies: Low‑Skill Service (Very high labor intensity; Low and middle skill; Nontradable), High‑Skill Service (High labor intensity; Middle and high skill; Nontradable), Manufacturing (Low labor intensity; All skills; Tradable). (Annex Table 1.3.1) - Labor markets segmented (low‑skill individuals cannot work in high‑skill services). - Domestic credit markets incomplete; one nonstate contingent bond for households; exogenous borrowing constraints varying by skill level. - Capital markets closed except for government external debt with exogenous schedule (a sensitivity test assumes an open financial economy). - Stationary equilibrium calibrated to match key features of the United States economy (the “benchmark economy”). - Personal income tax (PIT) function matches US average and marginal rates including negative and very progressive income tax rates for low incomes (reflecting the EITC); labor supply elasticity set to one‑third. ### Simulated policy scenarios and quantitative outcomes - Two main reform packages analyzed (each sized to cost 1 percent of GDP) and alternative financing options so reforms are budget neutral: - Expansion of the Earned Income Tax Credit (EITC): loss of government revenues of 1 percent of GDP (approximately the cost of doubling the current EITC). - Introduction of a Universal Basic Income (UBI): lump‑sum transfer to all households costing 1 percent of GDP. - EITC expansion: financing alternatives and impacts - Financing option: Reduction in government consumption of tradable goods. - A larger EITC results in a slightly lower GDP because exchange rate effects penalize the tradable goods sector, causing declines in hours worked for middle‑skill workers and in investment. - Subsidizing low‑income labor increases low‑skill labor supply, exerting downward pressure on low‑skill wages; substitution effects reduce demand and wages for medium‑skill workers; consumption gains are concentrated in the lowest quintile. - Financing option: VAT rate increase (2 percentage point increase in the VAT rate). - The negative impact on GDP growth is more pronounced (about 1.2 percent in total) when financed by a higher VAT, which distorts consumption and labor decisions. - VAT financing is regressive; households in the bottom quintile lose relatively more compared with other financing options, though they remain substantially better off than before the EITC expansion. - Financing option: More progressive PIT. - The impact on GDP is substantially more negative, since PIT distorts labor and capital choices and is expected to be more distortionary than indirect taxes. - Because the PIT is more progressive, upper quintiles experience consumption losses; bottom quintiles benefit more than under VAT financing. - Figures and magnitudes reported are cumulative effects over five years; dividing by five gives an approximate average annual effect. - UBI introduction: financing and impacts - Financing option: Reduction in government consumption of tradable goods. - The UBI has a negligible impact on GDP (Annex Figure 1.3.6). - The cash transfer raises demand for all goods, increasing nontradable prices and wages, inducing a switch from tradable to nontradable production. - Increase in low‑skill wages compensates for any negative direct impact of the UBI on labor effort; hours worked for low‑income individuals barely change. - Because nontradables do not use capital, private investment and private capital stock decline moderately. - Distributional effect: - The UBI is highly progressive (Annex Figure 1.3.7). - Relative to the size of their incomes, households in the bottom quintile see a 5 percent ### Policy implications highlighted in the text - Public policies that improve access to education and reduce inequality of opportunity can limit the adverse effects of rising inequality on social mobility. - Choice of financing matters for both macroeconomic and distributional outcomes: - Financing redistributive expansions via cuts to government consumption of tradables has limited short‑run distributional progressivity but affects tradable sector and investment. - Financing via VAT raises GDP costs and is relatively regressive. - Financing via more progressive PIT is more progressive but has larger adverse impacts on GDP through distortions to labor and capital. *Annex Figure 1.2.1. Wealth and Income Shares of Top — Fiscal Monitor: Tackling Inequality, International Monetary Fund | October 2017* ### Annex Figure 1.3.4. United States: Distributional ### Annex Figure 1.3.4. United States: Distributional ### Impact of EITC expansion and alternative financing (key mechanisms and distributional outcomes) - EITC expansion is targeted to lower quintiles and increases consumption most for the bottom quintile relative to alternative transfers. - Financing options considered and salient effects: - Government expenditure cuts: smaller increase in consumption for some quintiles compared with EITC expansion. - VAT rate increase: the VAT would have to increase 2 percentage points to exactly finance the transfer. The VAT penalizes consumption and returns to labor, worsening the macroeconomic impact relative to financing with PIT; the reform is primarily beneficial to the bottom quintile mostly because of the cash transfer itself. - More progressive PIT: financing with higher and more progressive taxes reduces investment substantially (investment would fall four times as much), because progressivity penalizes higher-income individuals, who are the savers; financing with PIT is more progressive by construction. ### Macroeconomic and labor-market channels (summary of mechanisms) - EITC expansion: - Increases demand for services produced by medium-skill workers, raising their wages and hours worked. - Medium-skill workers can substitute for capital; capital declines, further supporting demand for medium-skill labor. - Through increased labor demand and cash transfers, consumption increases among the second through fourth quintiles. - VAT financing: - Penalizes consumption and returns to labor, worsening macro outcomes (see Annex Figure 1.3.6). - PIT financing: - More progressive PIT reduces investment significantly and shifts distribution more toward lower-income households, increasing progressivity but at the cost of efficiency. ### Welfare impact (EDEI results and interpretation) - Welfare is measured by equally distributed equivalent income (EDEI); results depend on aversion to inequality (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 that society is willing to trade efficiency for more equity. - The VAT is more efficient than PIT but regressive; as aversion to inequality increases, packages financed with PIT (which increase progressivity) can improve welfare and may even dominate VAT-financed packages. - Comparison of UBI and EITC: - The EITC dominates the UBI because it is targeted and disproportionately benefits the lower quintiles of the consumption distribution, and it has an important positive effect on labor supply. - Calibration note: - The universal basic income (UBI) and the Earned Income Tax Credit (EITC) expansion are of equivalent size, equal to 1 percent of GDP. ### Key quantitative points from figures cited - VAT financing requires an increase of 2 percentage points to exactly finance the transfer (stated for the UBI/EITC financing comparison). - Reform packages analyzed (UBI, EITC) are calibrated at 1 percent of GDP for the EDEI comparisons. --- ### Annex 1.4 — Estimation of Elasticities (method and summary results) ### Methodology - Income tax elasticities calculated for 35 countries over 1981–2016. - Data sources: income distribution from the World Wealth & Income Database; tax data from the OECD tax database. - Elasticities follow Brewer, Saez, and Shephard 2010, using incomes (Y) or income shares (s) of the top 1 and top 5 percent, independently or in a difference-in-differences approach: - e = Δ ln(Y) / Δ ln(1 − t) or e = Δ ln(s) / Δ ln(1 − t) - Where real income is missing, incomes are estimated assuming Pareto distribution: - Y5 = a/(a − 1) t5 - Pareto index a estimated by a = ln(0.2) / ln(t5 / t1) = ln(0.2) / ln(s5 / 5s1) where thresholds may be unavailable. - Denominator: income-weighted average of tax rates in the relevant tail; often the top income tax rate. - Elasticities calculated only for years with tax rate changes (at least 1 percentage point change in personal income tax rate). ### Descriptive summary of estimated median 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 ### Additional notes - Elasticities estimated only when tax reforms occur; difference-in-differences approach formula shown in footnote. - Figure (Annex Figure 1.4.1) displays difference-in-differences income share elasticities for top earners in 17 OECD countries; regression line given as y = –0.02164x + 45.23715, R^2 = 0.0097, t = –0.61 (as presented). --- ### Annex 1.5 — Growth Regressions (progressivity and growth) ### Regression setup - Annual regression for 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 = initial level of progressivity; y_i,t−1 = initial real per capita GDP; X = control variables; f_i and g_t = country and year fixed effects. - Uses a range of progressivity measures (including top statutory rate, average rate progressions, newly proposed redistributive capacity based on Kakwani 1977). ### Main findings and robustness - Progressivity measures are nonsignificant in most specifications, but turn positive and significant in a few specifications, suggesting no strong relationship between progressivity and growth overall. - Robustness checks performed: - Regressions on samples restricted to 10-year periods. - Five-year interval regressions (average growth over five years) following Ostry, Berg, and Tsangarides 2014. - Quantile regressions and interaction terms for high-progressivity observations. - Generalized method of moments used as additional verification; results broadly consistent. ### Selected regression results (Annex Table 1.5.1 and 1.5.2 highlights) - Annex Table 1.5.1 (annual regressions) reports multiple specifications; constants and sample sizes shown. Example constants: - Column (1) constant: 3.963** (standard error 1.784) - Number of observations and countries vary across columns (e.g., Number of observations: 2,019; Number of countries: 135 in column (1); other columns report 350 observations/33 countries, etc.) - Annex Table 1.5.2 (five-year intervals) reports that Average rate progression, 0–400% per capita GDP has coefficients 1.877* (standard error 0.968) and 1.849* (standard error 0.959) in columns (1) and (2), respectively. - Diagnostic statistics reported where applicable (AR1 p, AR2 p, Hansen p). --- ### Annex 1.6 — Empirical Assessment of a Universal Basic Income (UBI): cross-country static simulations ### Scope and method - Countries analyzed: Brazil, Egypt, France, Mexico, Poland, South Africa, the United Kingdom, and the United States. - Data: standardized LIS microdata for the latest year available for each country. - Partial static equilibrium simulations: households only; no behavioral responses (no changes in labor supply or consumption patterns); existing tax and transfer schedules and eligibility remain unchanged. - Baseline UBI calibration: 25 percent of net median market income per capita (net median market income = earned market income minus direct taxes paid). - Variants considered for population coverage: 1. Full UBI given to all individuals in the country. 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 also considered: 10, 20, 30, 40, and 50 percent of net median market income per capita. ### Main cross-country results (Annex Table 1.6.1: Gross fiscal cost and redistributive impacts when all individuals covered) - Note: Universal basic income is calibrated at 25 percent of net median market income per capita. - Brazil (2013) - Gross Fiscal Cost (percent of GDP): 4.6 - Reduction in Gini Coefficient: 0.05 - Initial Poverty Rate (percent): 19.04 - Reduction in Poverty Rate (percentage points): 11.6 - Annual UBI Amount (per person): R$1,286 - Egypt (2012) - Gross Fiscal Cost (percent of GDP): 3.5 - Reduction in Gini Coefficient: 0.06 - Initial Poverty Rate (percent): 18.55 - Reduction in Poverty Rate (percentage points): 10.4 - Annual UBI Amount (per person): LE 725 - France (2010) - Gross Fiscal Cost (percent of GDP): 6.8 - Reduction in Gini Coefficient: 0.04 - Initial Poverty Rate (percent): 9.49 - Reduction in Poverty Rate (percentage points): 6.3 - Annual UBI Amount (per person): €2,122 - Mexico (2012) - Gross Fiscal Cost (percent of GDP): 3.7 - Reduction in Gini Coefficient: 0.06 - Initial Poverty Rate (percent): 19.68 - Reduction in Poverty Rate (percentage points): 12.0 - Annual UBI Amount (per person): Mex$4,994 - Poland (2013) - Gross Fiscal Cost (percent of GDP): 4.9 - Reduction in Gini Coefficient: 0.04 - Initial Poverty Rate (percent): 10.70 - Reduction in Poverty Rate (percentage points): 6.9 - Annual UBI Amount (per person): Zl 2,111 - South Africa (2012) - Gross Fiscal Cost (percent of GDP): 2.3 - Reduction in Gini Coefficient: 0.05 - Initial Poverty Rate (percent): 23.65 - Reduction in Poverty Rate (percentage points): 10.8 - Annual UBI Amount (per person): R1,584 - United Kingdom (2013) - Gross Fiscal Cost (percent of GDP): 6.7 - Reduction in Gini Coefficient: 0.04 - Initial Poverty Rate (percent): 9.28 - Reduction in Poverty Rate (percentage points): 6.0 - Annual UBI Amount (per person): £1,839 - United States (2013) - Gross Fiscal Cost (percent of GDP): 6.4 - Reduction in Gini Coefficient: 0.05 - Initial Poverty Rate (percent): 17.42 - Reduction in Poverty Rate (percentage points): 10.1 - Annual UBI Amount (per person): US$3,516 ### Interpretation of UBI simulation results - All-individual UBI (25 percent of net median market income per capita) generally yields: - Substantial reduction in inequality (about 5 Gini points, similar across countries in the sample). - Larger reductions in poverty in emerging markets than in advanced economies in this sample, reflecting higher returns to a UBI where inequality levels are greater. - Gross fiscal cost averages: - Advanced economies selected in the experiment: 6½ percent of GDP (average reported across the selected advanced economies). - Selected emerging markets in the experiment: 3.8 percent of GDP (average reported across the selected emerging markets). - Restricting UBI recipients reduces gross fiscal cost and scales down impacts on inequality and poverty. - In advanced economies (older populations), a UBI given to both children and the elderly reduces poverty more than a UBI restricted to children, but costs about 70 percent more on average. - In emerging markets (younger populations), giving UBI only to children has smaller differences in poverty impact compared with including the elderly. --- *Source: IMF staff calculations and estimates as presented in the Fiscal Monitor (October 2017) annex figures and tables.* ### CHAPTER 1 TACkLINg INequALITy ### CHAPTER 1 TACkLINg INequALITy ### Universal Basic Income (UBI) simulations and calibration - The UBI is distributed to all individuals in a country. The fiscal envelope dedicated to the UBI is calibrated as the sum of existing universal and means­tested noncontributory transfers in each sample country (Annex Table 1.6.3).67 - Financing options considered (three scenarios): 1. The UBI substitutes for existing noncontributory transfers. 2. Direct income taxes are increased, with the current progressive shape of direct income taxes held constant. 3. A flat tax on disposable income is levied. - Note: In­kind transfers or subsidies and contributory programs are not included as part of the budget envelope in the analysis presented here. The budget considered captures a subset of monetary transfers and is estimated based on LIS data. Discrepancies between data reported in household surveys and budgetary data are common.67 ### Redistributive impacts and gross fiscal costs (Annex Table 1.6.2) - Annex Table 1.6.2 reports gross fiscal cost (percent of GDP), reduction in Gini coefficient, and reduction in poverty rate (percentage points) for two UBI variants: "Children Only" and "Children and Elderly Only". - Country results as reported: - Brazil (2013) — Children Only: Gross Fiscal Cost (percent of GDP) 1.30, Reduction in Gini Coefficient 0.03, Reduction in Poverty Rate (percentage points) 5.5; Children and Elderly Only: Gross Fiscal Cost (percent of GDP) 1.70, Reduction in Gini Coefficient 0.03, Reduction in Poverty Rate (percentage points) 6.0 - Egypt (2012) — Children Only: Gross Fiscal Cost (percent of GDP) 1.30, Reduction in Gini Coefficient 0.03, Reduction in Poverty Rate (percentage points) 5.6; Children and Elderly Only: Gross Fiscal Cost (percent of GDP) 1.50, Reduction in Gini Coefficient 0.03, Reduction in Poverty Rate (percentage points) 6.1 - France (2010) — Children Only: Gross Fiscal Cost (percent of GDP) 1.50, Reduction in Gini Coefficient 0.01, Reduction in Poverty Rate (percentage points) 2.7; Children and Elderly Only: Gross Fiscal Cost (percent of GDP) 2.60, Reduction in Gini Coefficient 0.02, Reduction in Poverty Rate (percentage points) 3.4 - Mexico (2012) — Children Only: Gross Fiscal Cost (percent of GDP) 1.30, Reduction in Gini Coefficient 0.03, Reduction in Poverty Rate (percentage points) 6.1; Children and Elderly Only: Gross Fiscal Cost (percent of GDP) 1.50, Reduction in Gini Coefficient 0.03, Reduction in Poverty Rate (percentage points) 6.7 - Poland (2013) — Children Only: Gross Fiscal Cost (percent of GDP) 1.10, Reduction in Gini Coefficient 0.01, Reduction in Poverty Rate (percentage points) 2.7; Children and Elderly Only: Gross Fiscal Cost (percent of GDP) 1.70, Reduction in Gini Coefficient 0.02, Reduction in Poverty Rate (percentage points) 3.3 - South Africa (2012) — Children Only: Gross Fiscal Cost (percent of GDP) 0.80, Reduction in Gini Coefficient 0.02, Reduction in Poverty Rate (percentage points) 4.7; Children and Elderly Only: Gross Fiscal Cost (percent of GDP) 0.90, Reduction in Gini Coefficient 0.03, Reduction in Poverty Rate (percentage points) 5.5 - United Kingdom (2013) — Children Only: Gross Fiscal Cost (percent of GDP) 1.40, Reduction in Gini Coefficient 0.01, Reduction in Poverty Rate (percentage points) 2.0; Children and Elderly Only: Gross Fiscal Cost (percent of GDP) 2.50, Reduction in Gini Coefficient 0.02, Reduction in Poverty Rate (percentage points) 3.1 - United States (2013) — Children Only: Gross Fiscal Cost (percent of GDP) 1.50, Reduction in Gini Coefficient 0.02, Reduction in Poverty Rate (percentage points) 4.0; Children and Elderly Only: Gross Fiscal Cost (percent of GDP) 2.50, Reduction in Gini Coefficient 0.03, Reduction in Poverty Rate (percentage points) 5.4 - Source: IMF staff estimates, using Luxembourg Income Study microdata. ### Calibration of UBI to current noncontributory transfers (Annex Table 1.6.3) - Annex Table 1.6.3 reports fiscal envelope (percent of GDP), annual amount (per person), and existing transfers coverage/share of total spending by bottom two deciles and top two deciles for the sample countries. - Reported country lines (as presented): - Brazil (2013) 0.7 R$183555 397 - Egypt (2012) 0.2 LE 51166 2817 - France (2010) 2.3 €7096619 486 - Mexico (2012) 1.0 Mex$1,3786328 2326 - Poland (2013) 0.8 Zl 3684617 418 - South Africa (2012) 3.1 R2,1266513 1611 - United Kingdom (2013) 6.2 £1,4448436 397 - United States (2013) 1.5 US$8226120 389 - Source: IMF staff estimates, using Luxembourg Income Study microdata. ### Health outcomes and inequality in public health spending (Annex 1.7) - Empirical specification for 72 low­ and middle­income countries over 1995–2015: - 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).68 - Health coverage for each wealth quintile is obtained from WHO’s health equity monitor database and is based on an index reflecting coverage of eight reproductive, maternal, newborn, and child health interventions.69 - X_it includes public and private health spending (constant 2011 PPP), GDP per capita (constant 2011 PPP), average years of schooling, income Gini (disposable income), and education Gini. - All independent variables are averaged within each five­year nonoverlapping period. Fixed and random country fixed effects are used; some specifications include period fixed effects. - Mechanisms through which inequality in basic health coverage affects overall health outcomes (with public health spending held unchanged): - Marginal health benefit of health spending is likely larger for the poor; reallocating spending from the rich to the poor raises overall health outcomes. - Redistribution can change the level and distribution of private spending; reallocating to the poor may increase overall private spending because the rich increase their spending while the poor’s decline is small in levels. - Health spending, health outcomes, and income/distribution interactions may feed back into each other; the model controls for income and education and their distributions to limit confounding. - Main regression findings (Annex Table 1.7.1): - Coefficients on ln(WHO Health Coverage Ratio (Q1/Q5)) across columns (1)–(6): - (1) 6.862*** (standard error 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) - Other reported coefficients (selected): - ln(Public Health Spending): 2.413* (1.381) in (1); 1.969 (1.289) in (2); 4.193** (1.613) in (3); 3.513** (1.502) in (4); 0.612 (1.492) in (5); 0.638 (1.460) in (6) - ln(Private Health Spending): 3.430** (1.503) in (1); 4.479** (2.102) in (2); 1.845 (1.414) in (3) - ln(GDP per capita): 2.160 (1.400) in (1); −0.254 (1.894) in (2); 0.944 (2.997) in (3); −3.264 (4.543) in (4); 3.594** (1.531) in (5); 1.967 (2.281) in (6) - ln(Schooling): 4.697** (1.895) in (1); 3.491* (1.847) in (2); 3.376 (2.282) in (3); 2.335 (1.902) in (4); 1.069 (1.961) in (5); 1.055 (1.854) in (6) - Number of observations: 179 in all columns. - Number of countries: 72 in all columns. - Country effects: Random in columns (1), (2), (5), (6); Fixed in columns (3), (4). - Period fixed effects: Yes in columns (5) and (6); No in columns (1)–(4). - Note: Robust standard errors are in parentheses. Q1 = first (top) income quintile; Q5 = fifth (bottom) income quintile; WHO = World Health Organization. Significance levels: ***p < 0.01; **p < 0.05; *p < 0.1. - Interpretation and magnitude: - Results suggest that lower inequality in health coverage is associated with higher average life expectancy when controlling for public health spending, income, education, and their distributions (columns (1), (3), and (5)). - Coefficients decline by between 7.5 and 20 percent—depending on the specification—when private health spending is included (columns (2), (4), and (6)), indicating the impact operates mainly through the first channel (higher marginal benefit for the poor). - Using the estimate from column (5): increasing h_it^Ineq from its most recent level—if it is less than 1—to 1 (closing the inequality gap in health coverage) would raise life expectancy by 1.3 years, on average, in 83 countries (72 included in the regression analysis plus 11 additional countries with some missing variables).71 *Italic: Source: CHAPTER 1 TACkLINg INequALITy — International Monetary Fund | October 2017* ### CHAPTER 1 TACkLINg INequALITy ### CHAPTER 1 TACkLINg INequALITy ### References cited - Dollar, D., T. 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Basel. ### Country abbreviations and coverage - Includes an alphabetical list of country codes (selected examples shown in the source): AFG Afghanistan; AGO Angola; ALB Albania; ARE United Arab Emirates; ARG Argentina; ARM Armenia; AUS Australia; AUT Austria; AZE Azerbaijan; BDI Burundi; BEL Belgium; BEN Benin; BFA Burkina Faso; BGD Bangladesh; BGR Bulgaria; BHR Bahrain; BHS Bahamas, The; BIH Bosnia and Herzegovina; BLR Belarus; BLZ Belize; BOL Bolivia; BRA Brazil; BRB Barbados; BRN Brunei Darussalam; BTN Bhutan; BWA Botswana; CAF Central African Republic; CAN Canada; CHE Switzerland; CHL Chile; CHN China; CIV Côte d’Ivoire; CMR Cameroon; COD Congo, Democratic Republic of the; COG Congo, Republic of; COL Colombia; COM Comoros; CPV Cabo Verde; CRI Costa Rica; CYP Cyprus; CZE Czech Republic; DEU Germany; DJI Djibouti; DMA Dominica; DNK Denmark; DOM Dominican Republic; DZA Algeria; ECU Ecuador; EGY Egypt; ERI Eritrea; ESP Spain; EST Estonia; ETH Ethiopia; FIN Finland; FJI Fiji; FRA France; FSM Micronesia, Federated States of; GAB Gabon; GBR United Kingdom; GEO Georgia; GHA Ghana; GIN Guinea; GMB Gambia, The; GNB Guinea-Bissau; GNQ Equatorial Guinea; GRC Greece; GRD Grenada; GTM Guatemala; GUY Guyana; HKG Hong Kong SAR; HND Honduras; HRV Croatia; HTI Haiti; HUN Hungary; IDN Indonesia; IND India; IRL Ireland; IRN Iran; IRQ Iraq; ISL Iceland; ISR Israel; ITA Italy; JAM Jamaica; JOR Jordan; JPN Japan; KAZ Kazakhstan; KEN Kenya; KGZ Kyrgyz Republic; KHM Cambodia; KIR Kiribati; KNA St. Kitts and Nevis; KOR Korea; KWT Kuwait; LAO Lao P.D.R.; LBN Lebanon; LBR Liberia; LBY Libya; LCA St. Lucia; LKA Sri Lanka; LSO Lesotho; LTU Lithuania; LUX Luxembourg; LVA Latvia; MAR Morocco; MDA Moldova; MDG Madagascar; MDV Maldives; MEX Mexico; MHL Marshall Islands; MKD Macedonia, former Yugoslav Republic of; MLI Mali; MLT Malta; MMR Myanmar; MNE Montenegro; MNG Mongolia; MOZ Mozambique; MRT Mauritania; MUS Mauritius; MWI Malawi; MYS Malaysia; NAM Namibia; NER Niger; NGA Nigeria; NIC Nicaragua; NLD Netherlands; NOR Norway; NPL Nepal; NZL New Zealand; OMN Oman; PAK Pakistan; PAN Panama; PER Peru; PHL Philippines; PLW Palau; PNG Papua New Guinea; POL Poland; PRT Portugal; PRY Paraguay; QAT Qatar; ROU Romania; RUS Russia; RWA Rwanda; SAU Saudi Arabia; SDN Sudan; SEN Senegal; SGP Singapore; SLB Solomon Islands; SLE Sierra Leone; SLV El Salvador; SMR San Marino; SOM Somalia; SRB Serbia; STP São Tomé and Príncipe; SUR Suriname; SVK Slovak Republic; SVN Slovenia; SWE Sweden; SWZ Swaziland; SYC Seychelles; SYR Syria; TCD Chad; TGO Togo; THA Thailand; TJK Tajikistan; TKM Turkmenistan; TLS Timor-Leste; TON Tonga; TTO Trinidad and Tobago; TUN Tunisia; TUR Turkey; TUV Tuvalu; TWN Taiwan Province of China; TZA Tanzania; UGA Uganda; UKR Ukraine; URY Uruguay; USA United States; UZB Uzbekistan; VCT St. Vincent and the Grenadines; VEN Venezuela; VNM Vietnam; VUT Vanuatu; WSM Samoa; YEM Yemen; ZAF South Africa; ZMB Zambia; ZWE Zimbabwe. ### Glossary: key fiscal and inequality concepts (selected definitions) - Average tax rate progression: Percentage point increase in the average tax rate for an increase in income by 1 percentage point of per capita GDP. - Benefit incidence: Share of public benefits received by a particular socioeconomic group. - Budget-neutral policies: Policies that keep a country’s fiscal deficit unchanged. - Categorical targeting: Selecting individuals based on specific easily observable characteristics—such as age, gender, or disability status. - Conditional cash transfer programs: Social assistance programs that transfer cash to households only if they meet certain conditions, for example, enrolling their children in schools. - Cyclically adjusted balance (CAB): Difference between the overall balance and the automatic stabilizers; equivalently, an estimate of the fiscal balance that would apply under current policies if output were equal to potential. - Cyclically adjusted primary balance (CAPB): Cyclically adjusted balance excluding net interest payments (interest expenditure minus interest revenue). - Disposable income: Amount of money that households have available for spending and saving after direct taxes and income-related transfers have been accounted for. - Equally distributed equivalent income: Level of income per person which, if equally shared, would generate the same level of social welfare as the observed income distribution. - Fiscal buffer: Fiscal space created by saving budgetary resources and reducing public debt in good times. - Gini coefficient: Measures the extent to which the distribution of a variable deviates from perfect equality; 0 represents perfect equality, 1 implies perfect inequality. - Gross debt: All liabilities that require future payment of interest and/or principal by the debtor to the creditor; public debt is used synonymously with gross debt of the general government in the Fiscal Monitor unless specified otherwise. - Net debt: Gross debt minus financial assets corresponding to debt instruments (monetary gold and special drawing rights; currency and deposits; debt securities; loans, insurance, pensions, and standardized guarantee programs; and other accounts receivable). - Output gap: Deviation of actual from potential GDP, in percent of potential GDP. - Primary balance: Overall balance excluding net interest payment (interest expenditure minus interest revenue). - Public sector: General government sector plus government-controlled entities (public corporations) whose primary activity is commercial. - Universal basic income: Uniform cash transfer level received by all individuals in a country without conditions attached. - Within-country inequality: Refers to income inequalities within a country. - Infant mortality rate: Number of deaths of young children, typically under one year of age, per thousand live births. - Out-of-pocket health spending: Households’ direct outlays for health care expenses, including gratuities and in-kind payments made to public and private health care providers and to suppliers of pharmaceuticals, therapeutic appliances, and other goods and services. - Revenue-maximizing rate: Tax rate that maximizes revenue, taking into account that raising tax rates discourages labor supply, effort, and compliance. - Pareto distribution and Pareto index: Statistical distribution and parameter used to describe the density of high incomes; the greater the Pareto index, the smaller the proportion of individuals with very high income. ### Methodological and statistical appendix — data sources and conventions - Primary data source: October 2017 World Economic Outlook database for country-specific data and projections for key fiscal variables, unless indicated otherwise. - Data vintage: Data in the Fiscal Monitor tables compiled on the basis of information available through September 5, 2017. - Country classification: - 35 advanced economies; - 40 emerging market and middle-income economies; - 40 low-income developing countries (LIDCs). - LIDC threshold: Per capita income levels below $2,700 in 2016 as measured by the World Bank’s Atlas method contribute to LIDC classification. - G7 subgroup: The seven largest advanced economies by GDP—Canada, France, Germany, Italy, Japan, United Kingdom, United States—form the subgroup of major advanced economies (G7). - Euro area: Members of the euro area are distinguished as a subgroup; composite data for the euro area cover current members for all years, even though membership has increased over time. - Fiscal year exceptions (data refer to fiscal year, not calendar year): Bangladesh; Egypt; Ethiopia; Haiti; Hong Kong Special Administrative Region; India; the Islamic Republic of Iran; Myanmar; Nepal; Pakistan; Singapore; Thailand; Argentina; Australia; Canada; United States (note: some of these are discussed elsewhere for specific adjustments). - Aggregation weights: Composite data for country groups are weighted averages of individual-country data, weighted by annual nominal GDP converted to US dollars at average market exchange rates as a share of the group GDP. - G20 aggregate definition: Refers to the 19 country members and does not include the European Union. ### Fiscal data definitions, adjustments, and country-specific notes (selected) - Accounting manual: In many countries fiscal data follow the IMF’s 2001 Government Finance Statistics Manual (GFSM 2001). Overall fiscal balance refers to net lending (+) and borrowing (–) of the general government; in some cases overall balance refers to total revenue and grants minus total expenditure and net lending. - Debt data caveats: Fiscal gross and net debt data are drawn from official data sources and IMF staff estimates; attempts are made to align with GFSM definitions but data can deviate due to limitations or country circumstances; sectoral and instrument coverage differences can hinder universal comparability. - Data smoothing and estimation: Structural breaks may be adjusted through splicing and other techniques; IMF staff estimates serve as proxies when complete information is unavailable; Fiscal Monitor data can differ from official data and IMF International Financial Statistics. - Country-specific adjustments and notes (selected examples): - Argentina: Total expenditure and the overall balance account for cash interest only. The primary balance excludes profit transfers from the Central Bank of Argentina. Interest expenditure is net of interest income from the social security administration. - Australia and Canada: For cross-country comparability, gross and net debt levels reported by national statistical agencies for countries that have adopted the 2008 SNA (Canada, Hong Kong Special Administrative Region, United States, Australia where relevant) are adjusted to exclude unfunded pension liabilities of government employees’ defined-benefit pension plans. - Brazil: General government data refer to the nonfinancial public sector (federal, state, local governments, and public enterprises excluding Petrobras and Eletrobras) and are consolidated with the sovereign wealth fund. Revenue and expenditures of federal public enterprises are added in full. Transfers and withdrawals from the sovereign wealth fund do not affect the primary balance. Disaggregated data on gross interest payments and interest receipts are available from 2003 only; before 2003 total revenue excludes interest receipts and total expenditure includes net interest payments. Gross public debt includes Treasury bills on the central bank’s balance sheet, including those not used under repurchase agreements. Net public debt consolidates general government and central bank debt. The national definition of nonfinancial public sector gross debt excludes government securities held by the central bank, except the stock of Treasury securities used for monetary policy purposes by the central bank (those pledged as security reverse repurchase agreement operations). According to this national definition, gross debt amounted to 69.9 percent of GDP at the end of 2016. - Chile and Peru: Cyclically adjusted balances include adjustments for commodity price developments. - China: Public debt data include central government debt as reported by the Ministry of Finance, explicit local government debt, and shares—less than 19 percent, according to the National Audit Office estimate—of contingent liabilities the government may incur. IMF staff estimates exclude central government debt issued for the China Railway Corporation. Relative to authorities’ definitions, consolidated general government net borrowing includes (1) transfers to and from stabilization funds, (2) state-administered state-owned enterprise funds and social security contributions and expenses, and (3) off-budget spending by local governments. Deficit numbers do not include some expenditure items, mostly infrastructure investment financed off budget through land sales and local government financing vehicles. - Ireland: General government balances between 2009 and 2012 reflect the impact of banking sector support. Fiscal balance estimates excluding these measures are –11.4 percent of GDP for 2009, –10.9 percent of GDP for 2010, –8.6 percent of GDP for 2011, and –7.9 percent of GDP for 2012. In 2015, if conversion of the government’s remaining preference shares to ordinary shares in one bank were excluded, the fiscal balance would be –1.1 percent of GDP. Cyclically adjusted balances reported in Tables A3 and A4 exclude financial sector support measures. Ireland’s 2015 national accounts were revised as a result of restructuring and relocation of multinational companies, resulting in a level shift of nominal and real GDP. - Japan: Gross debt is equal to total unconsolidated financial liabilities for the general government. Net debt is calculated by subtracting financial assets from financial liabilities for the general government. - Norway: Cyclically adjusted balances correspond to the cyclically adjusted non-oil overall or primary balance, and are expressed in percent of non-oil potential GDP. - Spain: Overall and primary balances include financial sector support measures estimated to be –0.1 percent of GDP for 2010, 0.3 percent of GDP for 2011, 3.7 percent of GDP for 2012, 0.3 percent of GDP for 2013, 0.1 percent of GDP for 2014, 0.0 percent of GDP for 2015, 0.2 percent of GDP for 2016, and 0.1 percent of GDP for 2017. - Switzerland: Data submissions at cantonal and commune level are received with a long and variable lag and are subject to sizable revisions. Cyclically adjusted balances include adjustments for extraordinary operations related to the banking sector. - United States: Cyclically adjusted balances exclude financial sector support estimated at 2.4 percent of potential GDP for 2009, 0.3 percent of potential GDP for 2010, 0.2 percent of potential GDP for 2011, 0.1 percent of potential GDP for 2012, and (note: further years truncated in the source excerpt). ### Statistical appendix scope and updates - The methodological appendix comprises four sections: “Data and Conventions”; “Fiscal Policy Assumptions” (summarizes country-specific assumptions underlying estimates and projections for 2017–18 and the medium-term scenario for 2019–22); “Definition and Coverage of Fiscal Data” (classification of countries and coverage/accounting practices); and statistical tables on key fiscal variables. - Historical data and projections are based on information gathered by IMF country desk officers in the context of missions and ongoing analysis; they are updated continuously as more information becomes available. - Composite and country-group tables, and country notes, document deviations from standard definitions and explain adjustments made for comparability. *Italic line as in source: International Monetary Fund | October 2017* ### 0.0 percent of potential GDP for 2013. For cross- ### fm1702 - 0.0 percent of potential GDP for 2013. For cross- ### Fiscal policy assumptions and projection framework - Historical data and projections of key fiscal aggregates are in line with those of the October 2017 World Economic Outlook, unless noted otherwise. - Short-term fiscal policy assumptions: - Based on officially announced budgets, adjusted for differences between national authorities and IMF staff regarding macroeconomic assumptions and projected fiscal outturns. - Medium-term fiscal projections: - Incorporate policy measures judged likely to be implemented. - When IMF staff has insufficient information to assess authorities’ intentions, an unchanged structural primary balance is assumed, unless indicated otherwise. - United States projections: - Based on the January 2017 Congressional Budget Office baseline adjusted for IMF staff policy and macroeconomic assumptions. - Baseline incorporates key provisions of the Bipartisan Budget Act of 2015 and the Protecting Americans From Tax Hikes Act of 2015. - Projections adjusted for different accounting treatment of financial sector support and of defined-benefit pension plans and converted to a general government basis. - Data are compiled using SNA 2008 and GFSM 2014; most series begin in 2001. ### Cross-country data adjustments and conventions - For cross-country comparability: - Expenditure and fiscal balances of the United States are adjusted to exclude the imputed interest on unfunded pension liabilities and the imputed compensation of employees (counted as expenditure under the 2008 SNA adopted by the United States). - Data for the United States may differ from data published by the U.S. Bureau of Economic Analysis (BEA). - Gross and net debt reported by BEA and national statistical agencies for countries that have adopted the 2008 SNA (Australia, Canada, Hong Kong Special Administrative Region, and the United States) are adjusted to exclude unfunded pension liabilities of government employees’ defined-benefit pension plans for cross-country comparability. - Data and accounting practice notations used in tables: - Coverage: CG = central government; GG = general government; LG = local governments; NFPC = nonfinancial public corporations; SG = state governments; SS = social security funds; TG = territorial governments; BCG = budgetary central government; MPC = monetary public corporations. - Accounting practice: C = cash; NC = noncash. - Valuation of debt: Nominal; Face; Current market. ### Country-specific coverage and notable data notes - Uruguay: - Data are for the consolidated public sector, which includes the nonfinancial public sector (as presented in the authorities’ budget documentation), local governments, Banco Central del Uruguay, and Banco de Seguros del Estado. - Public debt includes the debt of the central bank, increasing recorded public sector gross debt. - Venezuela: - Fiscal accounts for 2010–22 correspond to the budgetary central government and Petróleos de Venezuela S.A. (PDVSA). - Fiscal accounts before 2010 correspond to the budgetary central government, public enterprises (including PDVSA), Instituto Venezolano de los Seguros Sociales (IVSS), and Fondo de Garantía de Depósitos y Protección Bancaria (FOGADE). - Fiscal accounts data for 2016–22 are IMF staff estimates; revenue includes IMF staff’s estimated foreign exchange profits transferred from the central bank to the government and excludes IMF staff’s estimated revenue from PDVSA’s sale of Petrocaribe assets to the central bank. - Libya: - Reliability of Libya’s data, especially medium-term projections, is low due to civil war and weak capacities. - India: - Historical data are based on budgetary execution data; subnational data are incorporated with a lag of up to two years. - IMF and Indian presentations differ regarding divestment and license auction proceeds, net versus gross recording of revenues in certain minor categories, and some public sector lending. - Saudi Arabia: - IMF staff projections of oil revenues are based on WEO baseline oil prices and assumption that Saudi Arabia continues to meet commitments under the OPEC+ agreement. - From 2017, wage bill estimates no longer include the 13th-month wage payment previously awarded every three years in accordance with the lunar calendar. - Thailand: - For the projection period, IMF staff assumes an implementation rate of 50 percent for the planned infrastructure investment programs. - Turkey: - Fiscal projections for 2017 are based on the authorities’ Medium Term Programme 2017–19, with adjustments for additional announced fiscal measures and IMF staff’s higher inflation forecast; medium-term projections assume a more gradual fiscal consolidation than envisaged in the Medium Term Programme. - Venezuela and Yemen: special projection caveats due to data gaps and exchange rate/multi-tier systems (Venezuela) and assumptions on oil price ($55 a barrel used by authorities vs WEO assumptions) for hydrocarbon revenue (Yemen). ### Definitions, groupings, and coverage used in the Fiscal Monitor - Country groupings include Advanced Economies; Emerging Market and Middle-Income Economies; Low-Income Developing Countries; G7; G20; Euro Area; regional groupings (Emerging Market and Middle-Income Asia, Europe, Latin America, Middle East and North Africa and Pakistan, Africa); Low-Income Developing subgroups (Asia, Latin America, Sub-Saharan Africa, Others, Oil Producers). - Tables define specific coverage for Overall Fiscal Balance, Cyclically Adjusted Balance, and Gross Debt across countries with explicit Aggregate and Subsector coverage and Accounting Practice. ### Selected statistical and projection highlights extracted from tables - Aggregate methodological alignment: - Historical and projected fiscal aggregates align with October 2017 World Economic Outlook unless noted. - Representative country-level figures (as presented in tables): - United States General Government Overall Balance, 2008–22: –6.7, –13.1, –10.9, –9.6, –7.9, –4.4, –4.0, –3.5, –4.4, –4.3, –3.7, –4.0, –4.0, –4.2, –4.3 (percent of GDP for 2008–2022 row as shown). - Japan General Government Gross Debt, 2008–22: 191.3, 208.6, 215.9, 230.6, 236.6, 240.5, 242.1, 238.1, 239.3, 240.3, 240.0, 238.5, 237.2, 235.7, 233.9 (percent of GDP). - Advanced Economies average General Government Overall Balance, 2008–22: –3.5, –8.7, –7.6, –6.2, –5.4, –3.6, –3.1, –2.6, –2.8, –2.8, –2.3, –2.1, –2.0, –2.0, –2.0 (percent of GDP). - Advanced Economies average Gross Debt, 2008–22: 79.2, 92.5, 99.3, 103.5, 107.7, 106.2, 105.5, 105.1, 107.4, 106.3, 105.2, 104.2, 102.9, 101.9, 101.0 (percent of GDP). - Gross financing need concept: - Defined as projected overall deficit plus maturing government debt in 2017 (data from Bloomberg and IMF staff projections). - Example selected countries, Gross Financing Need, 2017: - Japan: 29.5 (percent of GDP) - France: 9.5 (percent of GDP) - United States: 15.5 (percent of GDP) - Italy: 9.4 (percent of GDP) - Advanced Economies average gross financing need, 2017: 12.9 (percent of GDP) - Structural fiscal indicators (selected): - Advanced Economies average Pension Spending Change, 2015–30: 0.8 (percent of GDP). - Advanced Economies average Net Present Value of Pension Spending Change, 2015–50: 22.2 (percent of GDP). - Advanced Economies average Health Care Spending Change, 2015–30: 2.5 (percent of GDP). - Advanced Economies average Net Present Value of Health Care Spending Change, 2015–50: 80.8 (percent of GDP). - Advanced Economies average Debt-to-Average Maturity, 2017: 16.4. - Emerging Market and Middle-Income Economies average Pension Spending Change, 2015–30: 1.9 (percent of GDP); Net Present Value of Pension Spending Change, 2015–50: 60.3 (percent of GDP). - Low-Income Developing Countries average Pension Spending Change, 2015–30: 0.4 (percent of GDP); Net Present Value of Pension Spending Change, 2015–50: 16.5 (percent of GDP). ### Methodological notes and caveats highlighted - Some country series are reported on different bases or have undergone methodological changes (examples in tables and country notes): - Data for Canada, Australia, Hong Kong SAR, and the United States adjusted to exclude unfunded pension liabilities when countries adopted the 2008 SNA. - Brazil gross debt refers to the nonfinancial public sector, excluding Eletrobras and Petrobras, and includes sovereign debt held on the balance sheet of the central bank. - Russia projections for 2020–22 are based on an oil price rule to be in effect in 2022, with IMF staff adjustments. - Venezuela fiscal account coverage differs pre- and post-2010 (see country-specific note). - Thailand’s debt series may exclude specialized financial institutions without government guarantee. - Projections incorporate country-specific assumptions where noted (e.g., Chile adjusts for IMF staff projections for GDP and copper prices; Saudi Arabia for OPEC+ compliance; Turkey for higher IMF staff inflation forecast). *Italic: Source — IMF, Methodological and Statistical Appendix, Fiscal Monitor: Tackling Inequality, October 2017.* ### Conclusion and Risk Assessment ### Conclusion and Risk Assessment ### Global outlook and risk assessment - Global activity has strengthened further and is expected to rise steadily into next year. - The pickup is broad based across countries, driven by investment and trade. - The recovery is not complete; medium-term global growth remains modest, especially in advanced economies and fuel exporters. - In most advanced economies, inflation remains subdued amid weak wage growth. - Slow productivity growth and worsening demographic profiles weigh on medium-term prospects. - Several emerging markets and developing economies continue to adjust to a range of factors, including lower commodity revenues. - Directors judged that risks are broadly balanced in the near term but skewed to the downside in the medium term, with rising financial vulnerabilities. - Identified vulnerabilities and risks include: - possibility of a sudden tightening of global financial conditions; - rapid increase in private sector debt in key emerging market economies; - low bank profitability and pockets of still-elevated non-performing loan ratios; - policy uncertainty about financial deregulation; - risks associated with inward-looking policies, rising geopolitical tensions, and weather-related factors. ### Policy recommendations and priorities - Employ a range of policy tools in a comprehensive, consistent, and well-communicated manner to secure the recovery and improve medium-term prospects. - Continued accommodative monetary policy is needed in countries with low core inflation, consistent with central banks’ mandates. - Fiscal policy should: - gear toward long-term sustainability; - avoid procyclicality; - promote inclusive growth; - be as growth friendly as possible, using space, where available, to support productivity and growth-enhancing structural reforms. - In many cases, policymakers should prioritize: - rebuilding buffers; - improving medium-term debt dynamics; - enhancing resilience. - Efforts to raise potential output should be prioritized based on country-specific circumstances, including: - increasing the supply of labor; - upgrading skills and human capital; - investing in infrastructure; - lowering product and labor market distortions. - Social safety nets remain important to protect those adversely affected by technological progress and other structural transformation. - Directors stressed the need to calibrate the path of normalization of monetary policies carefully, implement macro- and microprudential measures as needed, and address remaining legacy problems. ### Multilateral cooperation and shared challenges - A cooperative multilateral framework is vital to amplify mutual benefits of national policies and minimize cross-border spillovers. - Common challenges requiring cooperation include: - maintaining the rules-based, open trading system; - preserving the resilience of the global financial system; - avoiding competitive races to the bottom in taxation and financial regulation; - further strengthening the global financial safety net. - Multilateral cooperation is also essential to tackle noneconomic challenges highlighted by Directors, including refugee flows, cyberthreats, and mitigating and adapting to climate change. - Concerted effort is needed to reduce excess global imbalances through policy recalibration to achieve domestic objectives and strengthen prospects for strong, sustainable, and balanced global growth. - The IMF has a role in continuing to strengthen its multilateral analysis of external imbalances and exchange rates. ### Inequality and fiscal policy choices - Directors noted that income disparities among countries have narrowed, but inequality has increased in some economies. - Well-designed fiscal policies can play a role in achieving redistributive objectives without necessarily undermining growth and incentives to work. - There may be scope for: - strengthening means-testing of transfers in many countries; - increasing the progressivity of taxation in some countries. - Most Directors noted that any consideration of a universal basic income would have to be weighed carefully against country-specific factors—existing social safety schemes, financing modalities, fiscal cost, social preferences, and impact on incentives to work—which raised questions about its attractiveness and practicality. - Improving education and health care is key to reducing inequality and enhancing social mobility over time. ### Emerging market and developing economy priorities - Continued need for emerging market and developing economies to bolster economic and financial resilience to external shocks. - Recommended policies include enhanced macroprudential policy frameworks and exchange rate flexibility. - Common challenge: speed up convergence toward living standards in advanced economies by improving governance, infrastructure, education, and access to health care. - In several countries, policies should facilitate greater labor force participation, reduce barriers to entry into product markets, and enhance the efficiency of credit allocation. ### Financial system conditions and vigilance - Global financial system continues to strengthen and market confidence has improved generally. - Substantial progress has been made in resolving weak banks in many advanced economies; a majority of systemic institutions are adjusting business models and restoring profitability. - A prolonged period of monetary accommodation could lead to further increases in asset valuations and a buildup of leverage in the nonfinancial sector, signaling higher risks to financial stability. - Continued vigilance is needed regarding household debt ratios and investors’ exposure to market and credit risks. ### Low-income developing countries - Directors noted a generally subdued outlook for commodity prices. - Low-income developing countries that are commodity exporters are encouraged to continue improving revenue mobilization and strengthening debt management while safeguarding social outlays and capital expenditures. - Countries with more diversified export bases should further strengthen fiscal positions and foreign exchange buffers. - Across all low-income developing countries, an overarching challenge is to maintain progress toward their Sustainable Development Goals. *The following remarks were made by the Chair at the conclusion of the Executive Board’s discussion of the Fiscal Monitor, Global Financial Stability Report, and World Economic Outlook on September 21, 2017.* --- _Source: https://www.imf.org/-/media/files/publications/fiscal-monitor/2017/october/pdf/fm1702.pdf_