## _wp1648 ## Source details **Canonical URL:** [_wp1648](https://www.imf.org/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/wp/2016/_wp1648.pdf) ## Other formats - [Markdown version](/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/wp/2016/_wp1648.pdf.md) - [Structured JSON version](/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/wp/2016/_wp1648.pdf.json) --- ### Drivers of inequality: scope and motivation - Focus: evolution and drivers of income inequality and inequality of opportunities in Asia. - Rationale: - Asia accounts for more than half of the world’s population. - Rising inequality in Asia since the early 1990s marks a break from pre-1990 “Miracle” pattern (Hong Kong SAR, Korea, Singapore, Taiwan Province of China). - Objective: document developments in income inequality and opportunity measures over time in Asian economies; analyze drivers and Asia-specific differences; discuss policies for more inclusion. - Data sources referenced: SWIID Version 5.0; IMF staff calculations; PovcalNet; WID; Global Findex; WHO Health Equity Monitor; ILO. ### Stylized facts and high-level trends - Growth and poverty: - From 1990–15, Asia grew at around 6 percent per annum. - Poverty rate fell from 55 percent in 1990 to 21 percent in 2010 (poverty defined as $1.25/person/day in 2005 ppp). - Aggregate inequality: - Average net Gini coefficient in Asia rose from 36 in 1990 to 40 in 2013. - On a population-weighted basis, net Gini in Asia rose from 37 in 1990 to 48 in 2014. - Within-country standard deviation in the sample: 2.5 Gini points. - Country coverage and patterns: - Of 22 Asian economies with sufficient data, net Gini rose in 15 countries from 1990 to 2013. - Sharpest increases in most populous economies: China, India, Indonesia. - Consequences of rising inequality: - Elevated inequality can harm growth pace and sustainability. - High inequality can reduce investment in health and education and weaken support for growth-enhancing reforms. - Increased inequality has dampened the poverty-reducing impact of growth and hindered middle-class build-up. ### Literature and channels linking inequality to growth and stability - Empirical findings: - Early work: positive or non-linear effect of inequality on growth (Forbes, 2000; Banerjee and Duflo, 2003). - Recent work: negative relationship between inequality and growth (Easterly, 2007; Berg and Ostry, 2011; Dabla-Norris and others, 2015a). - Berg and Ostry (2011): a 10-percentile decrease in inequality increases the length of a growth spell by 50 percent. - Dabla-Norris and others (2015a): increases in top-quintile income share reduce medium-term GDP growth; increases in bottom-quintile share associated with higher growth. - Mechanisms identified: - Political economy channel: inequality can lead to obstruction of reforms or distorted redistribution, increasing instability (Persson and Tabellini, 1994; Alesina and Rodrik, 1994; Benabou, 2002). - Credit constraints channel: inequality combined with credit constraints hampers human capital accumulation and entrepreneurship (Galor and Zeira, 1993; Banerjee and Newman, 1993). - Financial-instability channel: top-income concentration linked to larger external deficits and crisis risk (Rajan, 2010; Kumhof and others, 2015). ### Data and measurement considerations - Main data sources: - SWIID Version 5.0: Gini coefficients for 174 countries from 1960 to present; uses LIS standard and model-based imputation; provides standard deviations of imputations. - PovcalNet: national distributions (mean income and decile shares) for 126 countries from 1979 to 2012; specifies whether measure is consumption or income. - Measurement caveats: - National surveys differ: some report income, others consumption; consumption inequality tends to be lower than income inequality (Alvaredo and Gasparini, 2015). - Differences in sampling unit, net/gross definitions, and reference periods complicate comparability. - WID (tax data) and PovcalNet (household surveys) can show striking differences for top incomes. ### Empirical framework and baseline estimation - Data and sample: annual panel for 82 countries during 1990–2013; includes 17 Asian countries. - Outcome measures: Net Gini, Market Gini, income share of bottom 10 percent, income share of top 10 percent, Palma ratio. - Estimation strategy: - Baseline: country fixed-effects (ζ_i) with time fixed effects (θ_t); Driscoll-Kraay standard errors; explanatory variables lagged by one year. - Robustness: Difference GMM in first differences; multiple-imputation Monte Carlo for incomplete Gini data. - Key explanatory variables and expected signs: - Human Capital: expected negative relationship with inequality. - Trade Openness: theoretically ambiguous. - Technology (IT capital share): often associated with higher inequality (skill-biased). - Financial Openness and Financial Deepening: ambiguous; deepening often associated with higher inequality globally. - Government Consumption (proxy for fiscal policy): expected to lower inequality if well targeted. - Inflation: expected to increase inequality. - Democratic Accountability: higher accountability expected to lower inequality, depending on elite capture. - Growth: Kuznets notion (inverted U) discussed; empirical evidence mixed. ### Baseline regression findings (selected) - Main sample baseline (Net Gini as dependent variable; selected coefficients with Driscoll-Kraay t-statistics): - Growth, t-1: 0.023 (1.248). - Human Capital, t-1: -0.042*** (-5.951). - Trade Openness, t-1: -0.006* (-1.786). - Financial Openness, t-1: 0.002* (1.727). - Financial Deepening, t-1: 0.017*** (7.797). - Gov. Consumption, t-1: -0.080* (-1.885). - Inflation, t-1: 0.006** (2.542). - Democratic accountability, t-1: -0.002* (-1.763). - Sample size and estimation: - Observations: 990 (several specifications). - Number of countries: 82 (varies by column). - Time fixed effects: YES. - Robustness: - Palma ratio, bottom 10% and top 10% income shares broadly confirm baseline findings. - Technological progress associated with higher inequality. - Growth appears equalizing in the global sample, but Asian growth post-1990 did not improve income distribution. ### Is Asia different? Interaction and region-specific patterns - Interaction regressions (Asia dummy with key variables) show: - Human Capital*Asia not statistically significant in changing human capital’s equalizing effect. - Financial Deepening*Asia: negative and marginally significant in Asia, implying financial deepening has been equalizing in Asia. - Gov. Consumption*Asia: positive but not significant in interaction; baseline gov. consumption is equalizing, but composition matters. - Asia-specific regression (Net Gini; selected coefficients): - Human Capital, t-1: -0.045*** (-5.983); Human Capital*Asia, t-1: 0.002 (0.078). - Trade Openness, t-1: -0.013** (-2.396). - Financial Deepening, t-1: 0.011*** (4.522); Financial Deepening*Asia, t-1: -0.015* (-1.784). - Gov. Consumption, t-1: -0.199*** (-3.510); Gov. Consumption*Asia, t-1: 0.14 (1.210). - Inflation, t-1: 0.007*** (4.023). - Share of employment in Industry: -0.190*** (-4.828). - Share of employment in Services: 0.109*** (5.017). - Estimation details: Observations: 848; Number of groups: 78; Time fixed effects: YES. ### Financial deepening: Asia versus global sample - Global finding: financial deepening associated with higher inequality. - Asia-specific finding: financial deepening has been equalizing in Asia. - Interpretation: better availability of credit, successful financial inclusion policies, and increased geographical outreach in Asia. - Country examples: - Thailand: commercial bank branches per 1,000 square kilometers increased by 50 percent between 2004 and 2012. - Thailand: ATMs per 1,000 square kilometers quadrupled between 2004 and 2012. - Financial inclusion indicators show stronger Asian performance on bank account use and access to credit for entrepreneurial activities. ### Fiscal policy: composition, coverage, and Asia-specific caveats - Government consumption is a proxy and does not capture distributional composition. - Specific tax and spending instruments associated with lower inequality (selected coefficients, Table 3): - Top Corporate tax rate, t-1: -0.066*** (-3.541). - Top Personal tax rate, t-1: -0.053* (-1.785). - Education Spending, t-1: -0.385** (-2.481). - Social Benefits, t-1: -0.193*** (-5.889). - Capital Spending, t-1: -0.162** (-2.118). - Asia-specific interactions (Table 3) indicate: - Education Spending*Asia, t-1: -0.943* (1.968) — suggests education spending may have contributed to higher income inequality in Asia. - Social Benefits*Asia, t-1: -0.680*** (3.890). - Capital Spending*Asia, t-1: -0.399** (2.642). - Top tax rate interactions not significant. - Coverage and composition concerns in Asia: - Percent of population above legal retirement age receiving a pension in Asia: 22 percent. - Income tax coverage example: in China less than 3 percent of the population subject to income tax in 2008. - Social spending and revenue: social spending relatively low in Asia; tax-to-GDP examples — China: 19 percent in 2013; India: 17 percent in 2013. ### Human capital, skill premium, and education effects - Human capital (education) is equalizing overall: Human Capital, t-1 coefficient -0.042*** (-5.951). - Skill premium: - Associated with higher inequality overall. - Contribution of skill premia to higher inequality is about three times larger in Asia than elsewhere. - Skill Premium, t-1: 0.007* (1.982); Skill Premium*Asia, t-1: 0.022*** (2.998). - Education levels: - Primary schooling associated with lower inequality overall (Primary school completion, t-1: -0.140*** (-4.139)). - Tertiary education associated with greater income inequality consistent with limited supply of highly skilled labor. - Inequality of opportunities documented: - Upper secondary completion rates for 20–29 year olds in 2009: 31 percent rural, 70 percent urban (rural–urban gap: 39 percentage points). - Large gaps in health intervention coverage by wealth quintile, particularly in South Asia. - Financial access: top 60 percent hold far more bank accounts than bottom 40 percent in many Asian economies. ### Labor market duality, informality, and demographics - High-income Asia (Japan, Korea): rise in non-regular workers — share increased from below 20 percent before early 1990s to 35 percent in 2011; 70 percent of non-regular workers are women. - Informality in developing Asia: share of informality in non-agricultural employment up to 70 percent or more in India, Indonesia, and the Philippines. - Union density associated with lower inequality (Union density, t-1: -0.030** (-2.278)). - Age dependency ratio associated with higher inequality (Age dependency ratio, t-1: 0.002*** (7.527)). - Gross replacement ratio associated with lower inequality (Gross replacement rate, t-1: -0.070*** (-4.474)). ### Labor share: patterns and drivers - Labor shares declined during 1990–2010 in Asia on average, consistent with global trends. - Country heterogeneity (1990–2007): - 7 out of 13 selected Asian countries: labor share decreased while Gini increased. - Korea, the Philippines, and Thailand: rising labor shares and declining Gini. - India, Sri Lanka, Hong Kong SAR: labor shares rose while inequality also rose. - Regression drivers of labor share (Table C1; selected coefficients): - Human Capital, t-1: -0.019*** (-3.803). - Financial Openness, t-1: -0.006*** (-5.406). - Financial Deepening, t-1: 0.029*** (5.519). - Technology, t-1: -0.559*** (-3.550). - Gov. Consumption, t-1: 0.262** (2.546). - Inflation, t-1: -0.010*** (-3.524). - Sample: Observations: 673; Number of groups: 60; Time dummies: YES. ### Country highlights and case studies - China: - Net Gini rose from 33 in 1990 to 53 in 2013. - Urban–rural differences large; urban inequality rose more sharply. - Tertiary enrollment increased from 8 percent in 2000 to 30 percent in 2015 after 1999 expansion. - Policy instruments: Minimum Livelihood Guarantee Scheme (Dibao); New Rural Cooperative Medicare; New Rural Pension Scheme; tax-to-GDP ratio: 19 percent in 2013; less than 3 percent of population subject to income tax in 2008. - India: - Net Gini around 45 in 1990 rising to 51 by 2013. - Rising inequality primarily urban; informality large; income tax-to-GDP ratio: 17 percent in 2013; income tax revenues stagnated around 0.5 percent of GDP (text notes stagnation). - Financial inclusion policies: Pradhan Mantri Jan Dhan Yojana, linkage to Aadhaar planned. - Korea: - Gini decreased from 32 in 1990 to 31 in 2013. - Widening top-income shares in tax data vs survey data divergence noted. - Japan: - Gini rose from 27 in 1990 to 31 in 2010. - Non-regular workers share ~ one third of labor force as of 2013. - ASEAN examples where inequality fell: - Thailand: inequality declined; universal health coverage (2001) expanded protection. - Philippines: Pantawid Pamilyang Pilipino Program introduced in 2008; coverage: 3.9 million households at end-2013 (75 percent of all households identified as poor by national targeting); budget outlay below 0.4 percent of GDP by 2013. - Malaysia: infrastructure and public service reforms; account ownership increased from 66.2 percent to 80.7 percent (2011–2014); borrowing from financial institutions rose from 11.2 percent to 19.5 percent (2011–2014). - Financial inclusion examples: - Philippines: microfinance loans rose from P2.6 billion ($85.79 million) in 2002 to P8.7 billion ($196.73 million) in 2013; compound annual growth rate: 11.6 percent. - Thailand: village funds from 2001; agricultural insurance and National Catastrophe Insurance Fund established; highest level of financial usage in South East Asia as of 2011 (ADB, 2013). ### Key magnitudes and illustrative policy impacts - Fiscal change illustration: - Cut in government consumption by 1.4 percentage points of GDP (observed between 1992 and 2011 for advanced economies) associated with increase of about one third of a net Gini point. - Financial deepening illustration: - Growth of domestic credit to private sector by 16 percentage points of GDP associated with increase by about one Gini point in developing countries. ### Concluding findings and policy recommendations - Key findings: - Asia experienced a rise in income inequality in most countries, contrasting with earlier eras of “growth with equity.” - Global factor: skill-biased technological change contributed to rising inequality. - Regional/country factors: spatial disparities (rural–urban) are important in large countries. - Higher inequality reduced the effectiveness of growth in reducing poverty and hampered middle-class formation. - Financial deepening has been equalizing in Asia, unlike global pattern. - Higher social sector spending, education spending, and capital expenditure are associated with higher income inequality in Asia (contrary to the rest of the world) because of weak coverage and benefits skewed to higher-income groups. - Greater tax progressivity reduces income inequality. - Policy priorities (selected): - Address inequality of opportunities: broaden access to education, health, and financial services. - Strengthen fiscal redistribution: - Improve tax progressivity and reduce exemptions and preferential rates. - Broaden tax base and improve tax compliance. - Expand and target social spending; consider conditional cash transfers as administrative capacity improves. - Increase public spending to improve access to health services and higher education. - Promote well-designed financial inclusion: - Expand access while safeguarding financial stability via better supervision and regulation. - Use bank accounts to deliver government transfers and wages. - Tackle labor market duality and informality: - High-income Asian countries: reduce gaps in legal protection between regular and non-regular workers; encourage balanced contracts. - Low- and middle-income countries: improve business environment, simplify registration, reduce red tape, and incentivize formalization. *Italic: Source — _wp1648 (IMF staff analysis including SWIID Version 5.0; World Bank PovcalNet; WID; Global Findex; WHO Health Equity Monitor; ILO; IMF staff calculations). * ### 1. Drivers of Inequality (Baseline) .................................................................................... ### 1. Drivers of Inequality (Baseline) ### Introduction and scope - Focus: evolution and drivers of income inequality and inequality of opportunities in Asia. - Rationale: - Asia accounts for more than half of the world’s population. - Rising inequality in Asia since the early 1990s marks a break from the region’s earlier pattern of equitable growth (pre-1990 “Miracle” countries: Hong Kong SAR, Korea, Singapore, Taiwan Province of China). - Objective: document developments in various measures of income inequality and of opportunity over time in Asian economies; analyze drivers of income inequality and how these differ in Asia; discuss policies to generate more inclusion. - Data sources explicitly referenced for figures: SWIID Version 5.0; and IMF staff calculations. ### Stylized facts and observed trends - Pre-1990: - Asia experienced strong growth with large gains in poverty reduction and relatively equitable income distributions (see Figure 1: Selected Asia: Income Inequality, Pre-1990; Net Gini Index). - Since the early 1990s: - The region has witnessed rising income inequality, with high levels particularly in large Asian emerging markets (see Figure 2: Selected Asia: Income Inequality, 1990-Latest; Net Gini Index). - Consequences of rising inequality highlighted: - Elevated inequality can harm the pace and sustainability of growth. - High income inequality can lead to sub-optimal investment in health and education, weighing on growth. - Widening inequality can weaken support for growth-enhancing reforms, spur populist policies, and increase political instability risk. - Increases in inequality have dampened the impact of growth on poverty reduction, producing less inclusive and less pro-poor growth compared to Asia’s past. - Inequality of opportunities is also a major concern in Asia, alongside income inequality. ### Policy focus and national responses (examples cited) - Inclusive growth has been placed central in several national development plans: - China’s Thirteenth Five-Year Plan (2016–20) emphasizes a more balanced, inclusive, and sustainable growth model. - India’s Twelfth Five Year Plan (2012–17) emphasizes inclusive growth objectives. - Philippine Development Plan (2011–16) emphasizes inclusive growth objectives. - Indonesia and Malaysia similarly include inclusive growth objectives in development plans. ### Organization of the paper (as presented) - Section II: literature survey on the impact of high inequality on the economy. - Section III: data issues. - Section IV: stylized facts on the evolution of inequality in Asia and extent to which growth has been inclusive. - Section V: empirical framework and results. *Source: _wp1648 - 1. Drivers of Inequality (Baseline); SWIID Version 5.0; IMF staff calculations.* ### Section VI explores the development of specific countries and Section VII discusses the ### _wp1648 - Section VI explores the development of specific countries and Section VII discusses the ### Literature review: impact, evolution, and drivers of inequality - Early empirical work found a positive or non-linear effect of inequality on growth (Forbes, 2000; Banerjee and Duflo, 2003) with mechanisms such as incentives (Lazear and Rosen, 1981), increased investment (Kaldor, 1957), and accumulation of assets for entrepreneurship and education (Barro, 2000). - Recent empirical work finds a negative relationship between inequality and growth (Easterly, 2007; Berg and Ostry, 2011; Berg and others, 2012; Ostry and others, 2014; Dabla-Norris and others, 2015a). - Berg and Ostry (2011): a 10-percentile decrease in inequality increases the length of a growth spell by 50 percent. - Dabla-Norris and others (2015a): increases in the income share of the top quintile reduce GDP growth over the medium term; increases in the income share of the bottom quintile are associated with higher growth. - Mechanisms through which inequality can negatively impact growth and stability: - Political economy channel: higher inequality can lead the rich to block growth-enhancing redistributionary policies or the poor to demand distortionary taxation; inequality can increase political instability, lowering investment and growth (Persson and Tabellini, 1994; Alesina and Rodrik, 1994; Bourguignon and Verdier, 2000; Benabou, 2002; Galor and others, 2009; Benhabib and Rustichini, 1996; Perotti, 1996; Rodrik, 1999). - Credit constraints channel: inequality combined with credit constraints hinders investment in human capital and health and entrepreneurial activity, and causes misallocation of talent (Galor and Zeira, 1993; Aghion and others, 1999; Galor and Moav, 2004; Banerjee and Newman, 1993; Owen and Weil, 1998; Maoz and Moav, 1999; Hassler and others, 2007). - Financial-instability channel: inequality has been cited as a potential cause of crises via political pressure for subsidized housing finance, lobby influence, and a savings glut; higher top income shares associated with substantially larger external deficits (Rajan, 2010; Stiglitz, 2012; Kumhof and others, 2015; Kumhof and others, 2012). - Evolution of inequality: - For most rich and middle-income countries, inequality increased in the last three decades (Morelli and others, 2015; OECD, 2015). - Top income shares have driven income inequality trends (Piketty and Saez, 2003; Atkinson and others, 2011). - For developing countries: inequality rose on average in the 1980s and 1990s and declined in the 2000s (Alvaredo and Gasparini, 2015), with regional heterogeneity. - Asia: increases in inequality since 1990 (Balakrishnan and others, 2013; Dabla-Norris and others, 2015a); Zhuang and others (2014) find 12 out of 30 Asian countries experienced increases in the last two decades driven by top income shares. - Types of inequality and implications: - Distinctions in the literature: market vs. structural (Easterly, 2007); opportunities vs. outcomes (World Bank, 2005); good vs. bad (Chaudhuri and Ravallion, 2006). - Important to go beyond monetary inequality to inequalities in opportunities (Son, 2014; Zhang and Kanbur, 2005; Tandon and Zhuang, 2007; Asadullah and Yalonetzky, 2011). - Drivers of inequality (empirical findings and literature): - Cross-country studies confirm multiple drivers (Milanovic, 2005; OECD, 2011; Dabla-Norris and others, 2015a). - Typical associations: greater financial openness and technology usually increase inequality; strengthened labor market institutions, higher government spending, and educational attainment are equalizing. - Ambiguous effects reported for trade openness and financial deepening. - Asia-specific work: - Zhuang and others (2014): technological progress, globalization, and market-oriented reform increased inequality through capital, skill, and spatial biases. - Claus and others (2014): fiscal policies in Asia—social protection and housing effects distinguish Asia from rest of world. - Balakrishnan and others (2013): education, increasing labor share of total income, and financial reform positively affect inclusive growth. - Aoyagi and Ganelli (2015): fiscal redistribution, monetary policy aimed at macro stability, and structural reforms to stimulate trade, reduce unemployment and increase productivity are important for inclusive growth. - Many studies focus on subsets, individual countries, or particular drivers (education, infrastructure, rural-urban differences, trade and outsourcing). ### Data issues and measurement choices - Focus of the paper: inequality in income or consumption using national household surveys. - Cross-country comparison challenges: - Some statistical offices report household income; others report consumption expenditure. Most low- and middle-income countries in Asia report consumption; high-income countries tend to report income inequality measures. - Differences in sampling unit, definition of income (net or gross), and time period of expenditures or earnings complicate comparability. - Main data sources used: - SWIID Version 5.0 (Standardized World Income Inequality Database by Frederik Solt): - Reports Gini coefficients for 174 countries from 1960 to the present. - Uses the Luxembourg Income Study as its standard and generates additional values via model-based imputation using multiple supplementary sources. - Solt provides standard deviations of imputations and a pre-formatted dataset, allowing uncertainty to be accounted for in cross-country regressions. - PovcalNet (World Bank): - Provides detailed national distributions of inequality (mean income and decile shares) from national household surveys. - Covers 126 countries from 1979 to 2012 and is used for official global poverty estimates. - Does not adjust for comparability but specifies whether the measure is consumption or income based. - Note: consumption inequality tends to be lower than income inequality (Alvaredo and Gasparini, 2015). ### Stylized facts: Asia’s growth, poverty reduction, and rising inequality - Growth and poverty reduction: - From 1990–15, Asia grew at around 6 percent per annum. - Poverty rate fell from 55 percent in 1990 to 21 percent in 2010 (poverty defined as $1.25/person/day in 2005 ppp). - Rising inequality in Asia: - Average net Gini coefficient in Asia rose from 36 in 1990 to 40 in 2013. - On a population-weighted basis, net Gini in Asia rose from 37 in 1990 to 48 in 2014. - Within-country standard deviation in the sample is only 2.5 Gini points, indicating persistence of Gini measures over time. - Inequality is higher in emerging market economies than in advanced economies and has been rising faster in emerging markets. - Historical contrast: - Pre-1990: Asian economies combined fast growth with reductions in inequality ("growth with equity miracle"). - Post-1990: the region has experienced rising inequality despite substantial poverty reduction; poverty rates would have been even lower had inequality not risen. - Country coverage and trends: - Of 22 Asian economies analyzed with sufficient data, income inequality (net Gini) rose in 15 countries from 1990 to 2013. - Increases were sharpest in the most populous economies, including China, India, and Indonesia. ### Country highlight: China (selected finding) - China’s net Gini coefficient rose from 33 in 1990 to 53 in 2013. - China moved from being one of the most equitable economies in 1990 to having inequality higher than most other regions. - There is a large urban–rural difference within China, with inequality in urban areas rising more sharply. *Source: _wp1648 - Section VI explores the development of specific countries and Section VII discusses the (PDF).* ### section VI.A). Combating this rising inequality is one of the policy priorities of the ### _wp1648 - section VI.A). Combating this rising inequality is one of the policy priorities of the ### Regional and country-level inequality trends - China: inequality rose sharply; (see section VI A) — urban areas experienced stronger rises in income shares of the top decile. - India: net Gini around 45 in 1990 rising to 51 by 2013; inequality in India was higher than China in 1990 and remained higher by 2013; urban inequality rising more sharply as top-decile urban income shares increased (See section VI A). - Korea: Gini decreased from 32 in 1990 to 31 in 2013. - Japan: Gini rose from 27 in 1990 to 31 in 2010; key drivers include aging, low female labor participation, and increasing labor market duality. Share of non-regular workers increased from below 20 percent before the early 1990s to 35 percent in 2011; 70 percent of non-regular workers are women (Aoyagi and others, 2015). - ASEAN emerging markets: divergent trends — inequality rising in Indonesia and falling in Thailand, Malaysia, and the Philippines; reductions in some countries attributed in part to policy efforts (see section VI.B). - Asian Low-Income Countries (LICs): average net Gini rose from 36 in 1990 to 39 in 2013. ### Income-share dynamics and measures - Palma ratio: focuses on ratio of top 10 percent to bottom 40 percent; for Asia it coincides with Gini developments — Malaysia, the Philippines, and Thailand became more equitable, while remaining countries became more inequitable (Figure 9). - Top decile income shares (regional averages): - Emerging Asia: 32 percent in 2013 versus 30 percent in 1990. - Advanced Asia: around 28 percent in 2013 versus 27 percent in 1990. - Income-share dynamics: in countries with rising inequality, the bottom 70 percent reduced their share while the top decile incurred large gains (Figure 11). - Top 10 percent country-level differences and data-source divergence: WID vs. World Bank PovcalNet show striking differences (example: Korea — WID shows increase to 45 percent using tax data; PovcalNet shows 22 percent in 2014 and stability since 2003). - Top 1 percent: average increase of 2.2 percent (exceptions include Indonesia); Korea saw a 5 percentage point increase; Singapore highest level with top 1 percent share of 14 percent in 2012 (Figure 13). - Data notes: WID uses tax data (less coverage below tax threshold); PovcalNet uses household surveys (may understate top incomes). Chinese data available only until 2003; Indonesian until 2004; Indian until 1999, possibly understating recent increases. ### Inclusiveness of growth, poverty, and middle class formation - Growth incidence (2004–14 vs prior decade): growth higher over 2004–14 for all deciles on average, but bottom decile growth considerably below other deciles (Figure 14). - Poverty reduction ($2 a day, 2011 PPP): substantial reductions across Asia; rural China decreased headcount ratio by 67 percentage points from 1990 to 2012 (Figure 15). - Decomposition of poverty change (Datt and Ravallion, 1992): poverty reduction in Asia can be attributed exclusively to growth in most countries, despite countervailing redistributional effects (Figure 16). - Middle class (defined as US$10–$20 a day, PPP 2011): much less progress in building middle class across Asia (Figure 17). - China: middle class increased by 33 percentage points, primarily in urban areas, not rural. - Thailand: significant progress in building middle class. - Malaysia: already had a sizeable middle class (data caveat: Malaysia uses income measures while other countries use consumption). - India and Indonesia: struggled most to lift population toward US$10–$20 a day. ### Inequality of opportunities: education, health, financial access, and labor market - Education: large gap in attainment between richest and poorest quintiles; percent with less than four years schooling much higher in poorest quintile — especially in South Asia, Lao P.D.R., Cambodia; China shows less of this gap. Upper secondary completion rates show a rural-urban gap of 39 percentage points (upper secondary completion for 20–29 year olds in 2009: 31 percent rural, 70 percent urban) (see section VI.A). - Policy implication: greater public investment in basic education and demand-side incentives (e.g., conditional cash transfers). - Health: large gaps in coverage of reproductive, maternal, newborn, and child health interventions by wealth quintile, particularly in South Asia (Figure 19); unequal health access can worsen productivity and perpetuate income inequality. - Financial services: share of adults with a bank account is much higher in the top 60 percent versus the bottom 40 percent of income distribution across many Asian economies (India, Indonesia, Vietnam, Philippines, LICs) (Figure 20); limited financial access constrains borrowing for investment and education. - Labor market imperfections and duality: - Korea and Japan: duality between regular and non-regular employment is a key driver of inequality; non-regular employment ~ one third of labor force (as of 2013) (Figure 21). Non-regular workers earn less, receive fewer training opportunities, and have lower social insurance coverage. Probability of moving from non-regular to regular job in Japan estimated at 1.7 percent vs. comparators (Kosugi, 2010; Genda, 2010). - Developing countries: informality is the biggest driver; share of informality in non-agricultural employment as high as 70 percent or more in India, Indonesia, and the Philippines (Figure 22). - Female labor force participation gaps persist and can perpetuate income inequality (Gonzalez and others, 2015). ### Empirical framework and drivers of inequality (section V.A.) - Data and sample: annual data for 82 countries during 1990–2013; includes 17 Asian countries. - Estimation strategy: baseline fixed-effects (FE) panel regressions with Driscoll-Kraay standard errors; robustness checks include (i) GMM in first difference (instrumenting explanatory variables, including lagged Gini) and (ii) multiple-imputation approach for incomplete Gini data (Appendix B). All explanatory variables lagged by one year. - Outcome measures: net Gini, market Gini, income share of bottom 10 percent, income share of top 10 percent, and Palma ratio. - Baseline regression structure: country fixed effects (ζ_i) and time fixed effects (θ_t); explanatory vector X_it-1. Error term ε_it. Lagging of explanatory variables reduces reverse causality risk. - Explanatory variables included and expected theoretical effects: - Education (Barro and Lee 2013; Penn World Tables; Inklaar and Timmer, 2013): expected negative relationship with inequality (composition and wage-compression effects noted). - Trade openness (exports + imports over GDP): theoretical ambiguous effects (Stolper-Samuelson, outsourcing, up-skilling, specialization). - Technological progress (share of information technology capital in total capital stock): often associated with higher inequality via skill-biased technological change. - Financial openness (IIP assets + liabilities over GDP): ambiguous effects similar to trade; FDI can be skill-biased and initially increase inequality. International financial liberalization may raise crisis likelihood, hurting the poor. - Financial deepening (domestic credit to private sector / GDP): can reduce or increase inequality depending on extensive vs intensive margin; possible threshold/Kuznets effect for financial development. - Fiscal policy (government consumption / GDP as proxy): expected to lower inequality if well targeted; composition and targeting matter. Progressive direct taxes equalize; indirect taxes can increase inequality. - Inflation (CPI change): tends to hurt the poor and increase inequality via wage lagging and wealth composition channels. - Democratic accountability (ICRG variable): higher responsiveness expected to equalize via redistribution, but democracy alone may not reduce inequality due to elite capture. - Economic growth: discussed in Kuznets framework (inverted U-shape) but empirical evidence inconclusive. - Estimation notes: FE with Driscoll-Kraay standard errors assumes heteroskedasticity and autocorrelation up to two lags; errors may be correlated across countries due to common shocks. Results capture short-run effects due to one-year lagging and thus should be considered lower-bound estimates for long-run influences. *Italic: Source — IMF staff analysis and figures from SWIID Version 5.0; World Bank PovcalNet; WID; World Bank, Global Findex; WHO Health Equity Monitor; OECD; ILO; and IMF staff calculations (content from section VI and V.A. of the provided PDF).* ### references therein). ### _wp1648 - references therein). ### B. Results — Approach and Baseline Findings - Method: three-pronged approach — (1) baseline model relating inequality measures to common determinants; (2) assess whether drivers differ in Asia via interaction terms; (3) zoom in on individual policy areas using more granular data to limit collinearity. - Baseline (net Gini as main measure): - Human capital and trade openness are associated with lower income inequality (Table 1, column 1). - Financial openness and financial sector deepening seem to aggravate inequality; financial deepening result is more robust. - Government consumption is associated with lower income inequality. - Inflation is associated with higher income inequality. - Democratic accountability is associated with lower income inequality. - Robustness and alternative measures: - Palma ratio, income share of bottom 10 percent, and income share of top 10 percent broadly confirm baseline findings. - Growth appears equalizing in the global sample: higher per capita GDP growth accompanied by lower inequality; however, after 1990 growth in Asia was not accompanied by improving income distribution. - Technological progress is associated with higher inequality. - Magnitudes illustrated: - Cut in government consumption by 1.4 percentage points of GDP observed between 1992 and 2011 for advanced economies associated with an increase of about one third of a net Gini point. - Financial deepening captured by growth of domestic credit to the private sector of 16 percentage points of GDP associated with an increase by about one Gini point in developing countries. ### Baseline — Selected coefficients and sample details (Table 1) - Dependent variables included: Net Gini, Market Gini, Palma ratio (top 10% to bottom 40%), Bottom 10% income share, Top 10% income share. - Selected estimated coefficients (with t-statistics): - Growth, t-1: 0.023 (1.248) for Net Gini. - Human Capital, t-1: -0.042*** (-5.951) for Net Gini. - Trade Openness, t-1: -0.006* (-1.786) for Net Gini. - Financial Openness, t-1: 0.002* (1.727) for Net Gini. - Financial Deepening, t-1: 0.017*** (7.797) for Net Gini. - Gov. Consumption, t-1: -0.080* (-1.885) for Net Gini. - Inflation, t-1: 0.006** (2.542) for Net Gini. - Democratic accountability, t-1: -0.002* (-1.763) for Net Gini. - Sample and estimation: - Observations: 990 (for several specifications). - Number of countries: 82, 82, 81 across columns. - Time fixed effects: YES. - Driscoll-Kraay robust t-statistics reported. ### Is Asia Different? — Interaction analysis and region-specific patterns - Specification: baseline regressions augmented with interaction terms between key policy variables and an Asia dummy (Z_it-1 refers to human capital, financial deepening, government consumption). - Interaction results: - Interaction terms with Asian dummies often change the sign of coefficients (Table 2), though many are not statistically significant — suggesting specific aspects of human capital, financial deepening, and fiscal policy in Asia that merit further investigation. - Asia-specific regression (selected coefficients, Table 2; dependent variable: Net Gini): - Growth, t-1: 0.024 (1.045). - Human Capital, t-1: -0.045*** (-5.983); Human Capital*Asia, t-1: 0.002 (0.078). - Trade Openness, t-1: -0.013** (-2.396). - Financial Deepening, t-1: 0.011*** (4.522); Financial Deepening*Asia, t-1: -0.015* (-1.784). - Gov. Consumption, t-1: -0.199*** (-3.510); Gov. Consumption*Asia, t-1: 0.14 (1.210). - Inflation, t-1: 0.007*** (4.023). - Share of employment in Industry: -0.190*** (-4.828). - Share of employment in Services: 0.109*** (5.017). - Sample details: Observations: 848; Number of groups: 78; Time fixed effects: YES. ### Financial Deepening — Asia versus global sample - Global finding: financial deepening associated with higher inequality overall. - Asia-specific finding: financial deepening has been equalizing in Asia (Table 2). - Interpretation: reflects better availability of credit and successful financial inclusion policies reaching lower-income groups and increasing geographical outreach. - Country examples and magnitudes: - Thailand: number of commercial bank branches per 1,000 square kilometers increased by 50 percent between 2004 and 2012. - Thailand: number of automated teller machines (ATMs) per 1,000 square kilometers quadrupled between 2004 and 2012. - Empirical support: financial inclusion indicators (Figures 23 and 24) show stronger Asian performance on bank account use and access to credit for entrepreneurial activities. ### Fiscal Policy — Composition matters; Asia-specific caveats - Government consumption is a proxy for fiscal policy but may not capture distributional composition. - Specific tax and spending instruments associated with lower income inequality (Table 3): - Top Corporate tax rate, t-1: -0.066*** (-3.541). - Top Personal tax rate, t-1: -0.053* (-1.785). - Education Spending, t-1: -0.385** (-2.481). - Social Benefits, t-1: -0.193*** (-5.889). - Capital Spending, t-1: -0.162** (-2.118). - Asia-specific interactions (Table 3): - Education Spending*Asia, t-1: -0.943* (1.968) — suggests education spending may have contributed to higher income inequality in Asia. - Social Benefits*Asia, t-1: -0.680*** (3.890) — significant Asia-specific effect. - Capital Spending*Asia, t-1: -0.399** (2.642). - Top Corporate tax rate*Asia and Top Personal tax rate*Asia not significant. - Explanatory interpretation: - Many tax and spending instruments are equalizing overall, but in Asia low and poorly targeted policies may have prevented equalizing effects. - Lower coverage of government spending in Asia: - At only 22 percent, the percent of the population above the legal retirement age and receiving a pension in Asia is about four times lower than the level in advanced economies or Emerging Europe and much lower than levels in the Middle East or Latin America. - Coverage of unemployment benefits in Asia represents only half of the coverage in other regions. - Social spending composition and levels: social spending is relatively low in Asia (Figure 25 and Figure 26), reflecting lower revenue collection. ### Human Capital — Skill premium and education levels - Skill premium: - Skill premium is associated with higher inequality overall (Appendix A Table A2). - Contribution of skill premia to higher inequality is about three times larger in Asia than elsewhere. - Barro and Lee (2010) confirm that Asian countries have the highest returns to schooling after advanced countries. - Education levels: - Primary schooling is associated with lower inequality overall but does not seem to impact inequality in Asia. - Tertiary education (higher-level education) is associated with greater income inequality, consistent with a skill premium for a limited highly skilled labor force. - Data note: - Skill premium calculated using the Occupational Wages around the World Database (ILO-based): ratio of highest to lowest reported occupational wage used as approximation. ### Demographics and Labor Market Institutions — Robustness and additional drivers - Results robust to controls for demographics (e.g., aging pressures) and labor market institutions. - Additional findings: - Higher union density is associated with lower income inequality (Appendix A Table A2). - A larger share of dependents (below 15 and over 64) over the working age population is associated with higher income inequality. - A higher gross replacement ratio is associated with lower income inequality. ### C. The Role of the Labor Share - Conceptual link: labor share is a measure of functional distribution between capital and labor; higher labor share usually suggests lower income inequality (all else equal). - Empirical patterns: - Labor shares declined during 1990–2010 in Asia on average, in line with global trends (Figure 28). - Country heterogeneity (1990–2007 changes): - For 7 out of 13 selected Asian countries, labor share decreased while Gini increased. - Korea, the Philippines, and Thailand experienced rising labor shares and declining Gini indices. - India, Sri Lanka, and Hong Kong SAR: labor shares rose while inequality went up as well. - Drivers of the labor share (Appendix C Table C1, summary): - Inflation reduces the labor share (benefits capital income). - Technology and financial openness associated with decline in labor share (capital-augmenting technology; capital mobility boosts capital bargaining power). - Higher human capital decreases the labor share (negative impact of higher productivity on labor demand). - Government consumption increases the labor share (enhances bargaining power of workers). - Asia does not differ significantly with regard to key policy variables affecting labor share. ### VI. Case Studies — A. Understanding Rising Inequalities in India and China - Overview: - Both China and India experienced rapid growth and sharp poverty reduction but also rising inequality. - Consumption distribution and trends: - Latest data indicate China is more unequal than India: bottom five deciles have lower shares in total consumption in China; top 10 percent shares are very similar for both countries (Figure 30). - Over time: - China: strong shifts — bottom 70 percent share fell until 2002 as top 20 percent gained; more recently gains shifted to the middle while bottom 20 percent still missing out (Figure 31, Figure 33–34). - India: smaller changes; persistent trend of top 20 percent gaining; intra-urban inequality rose significantly (Figure 32, Figure 35–36). - Drivers explored: - Spatial inequality: - In China, urban-rural differences are a large contributor to increased inequality; hukou restrictions on migration and concentration of FDI in coastal areas contributed to regional disparities. - In India, rising inequality is primarily an urban phenomenon; rural-urban income gap has increased with higher rural inflation identified as a key driver. - Educational inequality: - China: high primary and middle enrollment initially, lag in tertiary; rapid demand for high-skilled labor increased returns to education; tertiary enrollment increased from 8 percent in 2000 to 30 percent in 2015 after 1999 expansion; educational inequalities worsened due to limits on urban-rural migration and decentralized, locally financed education—rich provinces provide better schooling; rising schooling costs and credit constraints leave poor families behind. - India: educational attainment explains a substantial share of rising inequality (e.g., Cain and others (2014) — educational attainment can explain 47 percent of increase in rural inequality and 42 percent in urban sector from 1993 to 2004); state efforts to increase school participation (National Program of Universal Elementary Education in 2001; Mid-Day Meal Scheme in 2004) but major problems in educational quality and provision in rural areas persist. - Fiscal policies: - Both countries have struggled with basic service delivery in education and health; fiscal redistribution is low and tax revenues remain small compared to peers despite improvements. - China doubled its tax-to-GDP ratio since the early 1990s; nevertheless, more than half of revenues stem from indirect taxes and income taxes do not play a significant redistributive role; social security contributions found to be regressive. - India’s tax-to-GDP ratio has only increased slightly by 1.6 percentage points from 1990 to [text truncated in source]. *Italic: Content derived from the provided IMF PDF excerpt (_wp1648 - references therein).* ### 2013. Income tax revenues have also stagnated at around 0.5 percent of GDP due to constant ### _wp1648 - 2013. Income tax revenues have also stagnated at around 0.5 percent of GDP due to constant ### Inclusiveness of Policies - China - Introduced the “Minimum Livelihood Guarantee Scheme” (Dibao) in the 1990s and expanded coverage thereafter. - Coverage is limited and the level of income provided is low (Cevik and Correa-Caro, 2015). - Has not been found to reduce inequality, but helped to alleviate poverty (Li and Yang, 2009). - Other programs: New Rural Cooperative Medicare, New Rural Pension Scheme, Two Exemptions and One Subsidy Program, and Western Development Strategy (Li and others, 2014). - Note: In 2013 China’s tax-to-GDP ratio was at 19 percent. Less than 3 percent of the population was subject to the income tax in 2008. - India - Labor market rigidities in the formal sector lead to a high share of employment in the informal sector (Sharma, 2009), hampering pro-poor growth (Topalova, 2008). - Advances in financial inclusion: financial literacy push, priority sector lending policies. - Launched Pradhan Mantri Jan Dhan Yojana aiming for universal account coverage (Sahay and others, 2015a; Dabla-Norris and others, 2015b). - Linkage planned between accounts and Aadhaar for future cash transfers under social security schemes. - Note: In 2013 India’s tax-to-GDP ratio was at 17 percent. ### What Explains Declining Inequality in Malaysia, Philippines, and Thailand? - Trends in inequality - Thailand: clear downward trend throughout most of the period. - Philippines and Malaysia: uptick first, declines more recently. - Distributional changes by decile: bottom 10 percent in Malaysia and the Philippines lost share despite decreases in overall inequality; in Thailand the bottom 10 percent gained. - Fiscal policy measures and social programs - Philippines - 2002: Kapit-bisig Laban sa Kahiparan provided resources to poor rural municipalities. - Mid-2008: pro-poor spending package after fuel subsidy removal and food/fuel crisis. - 2008: Pantawid Pamilyang Pilipino Program (conditional cash transfers) introduced; set health and education goals. - Coverage: 3.9 million households at end-2013, or 75 percent of all households identified as poor by the national targeting scheme. - Budget outlay: stayed below 0.4 percent of GDP by 2013. - 2011–16 development plan aimed to improve access to basic social services and build stronger safety nets. - Thailand - 2001: Universal Health Coverage Scheme introduced; substantially reduced uninsured share, benefited the poor more and protected from impoverishment (Yiengprugsawan and others, 2010). - Energy subsidies reduced, with means-tested protection for the vulnerable. - Rice-pledging scheme replaced by direct cash transfers to small-scale farmers. - Eleventh National Economic and Social Development Plan (2012–16) aimed to improve access to social services and cover whole population under national welfare system by 2016. - Malaysia - High infrastructure levels stemming from reforms in the 1980s and 1990s (Seneviratne and Sum, 2013; Mourmouras and Sheridan, 2015). - Government Transformation Program (2009) improved public service delivery; new assistance reached more than a quarter of the extreme poor. - 2011–15 development plan aimed at equitable opportunities and social safety nets. - 2013–14: eliminated petroleum subsidies which had benefited higher-income households relatively more. - Education Blueprint 2013–25 aimed to improve quality and expand tertiary access. - Introduced a minimum wage in 2013. ### Financial Inclusion - Philippines - Microfinance loans rose from P2.6 billion ($85.79 million) in 2002 to P8.7 billion ($196.73 million) in 2013, equivalent to an 11.6 percent compound annual growth rate. - From 2008 to 2018, congress mandated at least 8 percent of banks’ loan portfolio be allocated to micro and small enterprises. - Microinsurance: coverage rose to 19.95 million (20.4 percent of the population) in 2013 from 3.1 million (3.4 percent of the population) in 2008. - Thailand - 2001: village funds established nationwide, one million baht seed money per village. - 2011: extended risk coverage to the informal sector; launched Agricultural Insurance scheme. - 2012: created National Catastrophe Insurance Fund. - Established a Bureau of Financial Inclusion Policy and Development in the Ministry of Finance. - As of 2011, achieved the highest level of financial usage compared to other South East Asian countries (ADB, 2013). - Malaysia - Bank Negara Malaysia mandated promotion of financial inclusion since 2009. - Financial Sector Blueprint 2011–20 aimed to enhance inclusion. - Inclusion indicators between 2011 and 2014: - Share of individuals owning an account at a financial institution increased from 66.2 percent to 80.7 percent. - Share of the population borrowing from a financial institution grew from 11.2 percent to 19.5 percent. ### Concluding Remarks and Policy Implications - Key findings - Asia experienced a rise in income inequality in most countries, in contrast to most other regions. - Global factor: skill-biased technological change played a role. - Regional/country-specific factors: spatial disparities, especially rural-urban, important in larger countries. - Higher income inequality reduced the effectiveness of growth in combating poverty and hampered the build-up of a substantial middle-class in many countries. - Financial deepening has been equalizing in Asia (contrary to other regions). - Higher social sector spending, education spending, and capital expenditure are associated with higher income inequality in Asia (contrary to the rest of the world) due to weak coverage and benefits accruing disproportionately to the higher end of the income distribution. - Greater progressivity in taxation ameliorates income inequality in Asia (consistent with rest of world). - Policy priorities - Address inequality of opportunities: broaden access to education, health, and financial services. - Strengthen redistributional effect of fiscal policy: - Improve tax progressivity and reduce exemptions and preferential rates. - Broaden tax base for income and consumption taxes; improve tax compliance. - Expand and broaden coverage of social spending; better target social benefits. - Consider expanding conditional cash transfers as administrative capacity improves (e.g., Bangladesh, Cambodia, India, Indonesia, Nepal, Philippines). - Increase public spending to improve access to health services and higher education. - Promote well-designed financial inclusion: - Expand access while safeguarding financial stability via improved bank supervision and regulation. - Encourage use of bank accounts to receive government transfers and wages. - Tackle labor market duality and informality: - In high-income Asian countries: reduce gaps in legal protection between regular and non-regular workers; encourage balanced contracts for new hiring. - In low- and middle-income countries: improve business environment, simplify registration, reduce red tape, and provide incentives for formalization. ### Selected Regression and Robustness Results (Appendices) - Appendix A: Drivers of Inequality — Advanced vs. Developing Economies (dependent variable: Net Gini) - Financial Deepening, t-1: - Advanced economies: 0.003 (t-statistic 0.824) - Developing economies: 0.054*** (t-statistic 4.289) - Gov. Consumption, t-1: - Advanced economies: -0.240*** (t-statistic -6.330) - Developing economies: -0.054 (t-statistic -1.074) - Observations: 472 (Advanced), 534 (Developing) - Number of countries: 31 (Advanced), 51 (Developing) - Appendix A: Human Capital, Demographics, and Labor Market Institutions (dependent variable: Net Gini) - Skill Premium, t-1: 0.007* (t-statistic 1.982) - Skill Premium*Asia, t-1: 0.022*** (t-statistic 2.998) - Primary school completion, t-1: -0.140*** (t-statistic -4.139) - Gross replacement rate, t-1: -0.070*** (t-statistic -4.474) - Union density, t-1: -0.030** (t-statistic -2.278) - Age dependency ratio, t-1: 0.002*** (t-statistic 7.527) - Observations vary across specifications (e.g., 232, 388, 521, 600, 990) - Appendix B: Robustness checks - Monte Carlo simulation (Net Gini) and Difference GMM (Net Gini) results summary: - Human Capital: -0.042*** (Monte Carlo), -0.017* (Difference GMM) - Financial Deepening: 0.017*** (Monte Carlo), 0.004* (Difference GMM) - Inflation: 0.006** (Monte Carlo), 0.009*** (Difference GMM) - Difference GMM includes Lag of Gini: 0.894*** (t-statistic 28.530) - Observations: 990 (Monte Carlo), 913 (Difference GMM) - Number of countries: 82 (both) - Sargan Test: 0.740; AR(4): 0.936 *Source: _wp1648 - 2013. Income tax revenues have also stagnated at around 0.5 percent of GDP due to constant* ### APPENDIX C: REGRESSION RESULTS FOR LABOR SHARE ### APPENDIX C: REGRESSION RESULTS FOR LABOR SHARE ### Regression findings: Drivers of the Labor Share (Table C1) - Dependent variable: Labor Share - Explanatory variables and estimated coefficients (Driscoll-Kraay robust t-statistics in parentheses): - Growth, t-1: 0.036 (0.829) - Human Capital, t-1: -0.019*** (-3.803) - Human Capital*Asia, t-1: 0.003 (0.072) - Trade Openness, t-1: -0.003 (-0.443) - Financial Openness, t-1: -0.006*** (-5.406) - Financial Deepening, t-1: 0.029*** (5.519) - Financial Deepening*Asia, t-1: -0.008 (-0.947) - Technology, t-1: -0.559*** (-3.550) - Gov. Consumption, t-1: 0.262** (2.546) - Gov. Consumption*Asia, t-1: -0.249 (-1.055) - Inflation, t-1: -0.010*** (-3.524) - Democratic Accountability, t-1: -0.002 (-0.983) - Share of employment in Industry, t-1: 0.192*** (4.095) - Share of employment in Employment, t-1: 0.022 (0.819) - Sample and estimation details: - Observations: 673 - Number of groups: 60 - Time dummies: YES - Driscoll-Kraay robust t-statistics in parentheses. They are robust to very general forms of cross-sectional and temporal dependence. The error structure is assumed to be heteroskedastic, autocorrelated up to two lags, and possibly correlated between the panels (countries). - Significance levels: *** p<0.01, ** p<0.05, * p<0.1 ### Data definitions and sources (Appendix D, Table D1) - Dependent Variables: - Net Gini: Gini index of distribution of income before taxes and transfers — Standardized World Income Inequality Database - Market Gini: Gini index of distribution of income after taxes and transfers — Standardized World Income Inequality Database - Palma Ratio: Share of Top 10% to Bottom 40% — PovcalNet, WIID3.0A - Shares of income: Share of income/consumption accruing to each decile — PovcalNet, WIID3.0A - Labor Share: Compensation of employees divided by GDP — Karabarbounis and Neiman (2014), ILOSTAT - Other key variables (name — description — data source): - Growth: Real GDP growth — IMF, WEO - Human Capital: See Inklaar and Timmer (2013) — Penn World Table - Trade Openness: Total exports and imports (% of GDP) — IMF, WEO - Financial Openness: Total external assets and liabilities outstanding (% of GDP) — IFS - Financial Deepening: Domestic credit to private sector (% of GDP) — World Bank, WDI - Technology: Share of information and communication technology capital in the total capital stock — Jorgenson, Dale and Khuong Vu (2011) - Government Consumption: General government final consumption expenditure (% of GDP) — World Bank, WDI - Inflation: CPI Inflation — IMF, WEO - Democratic Accountability: Democratic Accountability Index — ICRG - Share of Employment in Sectors: Employment in agriculture/industry (% of total employment) — World Bank, WDI - Fiscal Policy Variables: Government revenue/expense/tax, etc. — IMF WEO, etc. - Skill Premium: Ratio of highest to lowest reported occupational wage — Occupational Wages Around the World Database - Schooling Variables: Completion/Enrollment rate, etc. — World Bank, WDI - Minimum Wage to Mean Wage: Ratio of minimum wage to mean wage — Aleksynska and Schindler (2011) - Gross Replacement Rate: Ratio of unemployment insurance benefits a worker receives relative to the worker's last gross earning — Aleksynska and Schindler (2011) - Union Density: Trade union density as % of paid employment — Database on Institutional Characteristics of Trade Unions, Wage Setting, State Intervention and Social Pacts, Trade Union Membership Statistics *Source: APPENDIX C and APPENDIX D (regression table and data description).* ### Chapter 5. ### Chapter 5. ### Literature cited: selected references on inequality, top incomes, and related topics - Atkinson, A., 2015, Top incomes in Malaysia 1947 to the present (with a note on the Straits Settlements 1916 to 1921). - ––––––, and Leigh, Andrew, 2007, The Distribution of Top Incomes in Australia; in Atkinson, A. 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