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### Introduction: key findings
- Income inequality has risen across the world over the last two decades; the academic literature attributes the rise mainly to globalization, skill-biased technical change, and the decreasing bargaining power of workers.
- The global crisis and recent social turmoil have heightened awareness of the potential impact of rising inequality on economic and social stability and on the sustainability of growth.
- Main findings from the paper:
  - Poverty has fallen in recent decades in Asia but inequality has increased.
  - The rise in income inequality has dampened the impact of growth on poverty reduction.
  - Relative to other regions and to Asia’s own past, the recent period of growth has been both less inclusive and less pro-poor.
  - There is scope for policy measures to broaden the benefits of growth, notably enhanced spending on health and education, stronger social safety nets, labor market interventions, financial inclusion, and strengthened governance.

### How Asia compares to other regions: empirical highlights
- Asia’s growth over the last two decades has been much faster than its comparators outside the region, enabling significant reductions in poverty.
- Asia remains home to the largest number of the world’s poor, with China and India together accounting for almost half.
- Selected country figures:
  - China: in 1981, 84 percent of the population lived on less than $1.25 a day; by 2008 this proportion had fallen to 13 percent.
  - India: in 1981, 60 percent of the population lived on less than $1.25 a day; by 2010 this share fell to 33 percent.
- Trends in inequality:
  - China: official estimates show Gini increased from 37 percent in the mid 1990s to 49 percent in 2008; it ticked down to 47.4 in 2012.
  - India: Gini rose from 33 percent in 1993 to 37 percent in 2010 (ADB estimate).
- Spatial and rural–urban disparities:
  - In China, spatial disparities are estimated to account for between one-third and two-thirds of overall inequality; the rural-urban income gap increased to a ratio of more than 3:1 (with a slight decline since 2009).
  - For most other Asian economies, the rural–urban ratio falls between 1.3–1.8.
  - In India, the ratio of urban to rural per capita consumption increased from around 1.5 in 1987–8 to nearly two in 2009–10.
  - Regional disparity example in India: the ratio of per capita GDP of Punjab to Bihar rose from 2.9 in 1980 to 4.1 in 2010.

### Box: China and India — drivers of divergent poverty and inequality dynamics
- China
  - Rapid poverty reduction associated with rural economic reforms and low initial inequality.
  - Relatively equal allocation of land via land use rights helped agricultural growth translate into poverty reduction.
  - High access to health and education facilitated poverty-reducing nonfarm growth.
  - Since the mid-1990s: slowed agricultural growth, reduced rural employment and incomes, increased rural–urban income gap, and rise in urban poverty partly due to large-scale migration.
- India
  - Slower poverty reduction compared with China; lower growth elasticity of poverty reduction.
  - Larger initial inequalities in schooling, health and gender may have impeded the poor from contributing to and benefiting from growth.
  - Trend growth concentrated in modern services (largely urban-based and requiring higher human capital), which may have limited the poor’s participation.
- Contributing proximate factors emphasized:
  - Health and education spending: high fiscal decentralization in China with more than half of expenditure at the sub-provincial level; poor villages lack own-revenue sources, public spending per capita in the richest province is almost 50 times that in the poorest; similar patterns in India stressing need for central redistribution to poor regions.
  - Declining labor share of income: in China and India, the share of labor income to manufacturing value added fell from 50 percent in both countries during the early 1990s to around 40 percent (China) and 25 percent (India) by the mid 2000s.
  - Employment elasticity of growth: in China, the employment elasticity fell from 0.44 to 0.28 between 1991 and 2011.

### Inequality trends and proximate drivers
- Labor and wages:
  - Rural surplus labor reduced bargaining power and held down wages relative to productivity.
  - India: between 1990 and 2007, labor productivity rose by nearly 7½ percent annually, while real wages grew by only 2 percent per year.
- Regional disparities:
  - Coastal regions in China and coastal states in India provided more nonagricultural employment and income opportunities.
  - Disparities compounded by preferential policies and persistent gaps in human capital and infrastructure.
- Skill premia and returns to education:
  - China: between 1988 and 2003, wage returns to one additional year of schooling increased from 4 to 11 percent.
  - India: larger schooling inequalities have inhibited pro-poor growth.
- Financial exclusion:
  - Differential financial development and urban biases in lending contributed significantly to China’s urban-rural income disparity since the late 1980s.
  - India: underdevelopment of financial systems hits the poor more than the rich, resulting in higher income inequality.
- Regional pattern: Inequality has increased across Asia, reversing previous three-decade record of fast and equitable growth in Japan, the NIEs, and the ASEAN. The rise in inequality has been larger than in other emerging regions.

### Observed effects during the global crisis
- Poverty generally continued to fall in Asia, but the global crisis exacerbated the rise in inequality in several economies.
- Notable pronounced trend in rural China and Indonesia; observed also for Japan and some NIEs.
- Selected series in regional Figure 2 include changes in $1.25/day poverty headcount and Gini index for: Philippines (2006-09), New Zealand (2004-09), India, rural (2004-09), China, urban (2005-08), Taiwan Province of China (2006-09), Japan (2005-09), Korea (2006-10), India, urban (2004-09), China, rural (2005-08), Indonesia, rural (2007-11), Indonesia, urban (2007-11).

### Definitions: pro-poor and inclusive growth
- Pro-poor growth: growth that reduces poverty (following Ravallion and Chen, 2003).
- Inclusive growth: growth not associated with an increase in inequality (following Rauniyar and Kanbur, 2010); operationally, growth is inclusive when it is not associated with a reduction in the income share of the bottom quintile.

### Pro-poor growth regression results (Table 2)
- Estimated regression (log of poverty headcount below the $2 line): β gives impact of income growth on poverty reduction; δ gives impact of change in Gini coefficient.
- Instrumental variables approach: lags of real per capita income (Penn World Tables) used to instrument household-survey-based average income.
- Key estimates and implications:
  - A 1 percent increase in real per capita income leads to about a 2 percent decline in the poverty headcount (column 1).
  - A 1 percent increase in the Gini coefficient more or less offsets the beneficial impact on poverty reduction of the same increase in income.
  - Income-Gini interaction is significant: higher inequality reduces the impact of income growth on poverty reduction (column 2).
  - Example: an increase in the Gini coefficient of about 25 percent (as observed in urban China from 1995–2005) reduces the impact of a 1 percent increase in income to about a 1½ percent decline in the poverty headcount from 2 percent in the base case.
- Selected regression details:
  - Log of mean household income (y): -2.146***, -8.205***, -2.627***, -3.406***, -10.536*** (across columns).
  - Log of Gini index: 2.258***, -5.838***, 2.277***, 2.003***, -7.799*** (across columns).
  - Income-Gini interaction: 1.723***, 2.035***.
  - Observations: 579; R-squared range: 0.461 to 0.654; Number of clusters: 98; Models: FE and IV.

### Inclusive growth regressions (Dollar-Kraay style) — bottom and top quintiles (Table 3)
- Model: elasticity λ of bottom-quintile income with respect to average income; if λ < 1 then growth is not inclusive.
- Pooled or fixed-effects without instrumentation: incomes of poorest fifth rise proportionately with per capita income (Dollar-Kraay result).
- Instrumented results:
  - Bottom quintile: income rises significantly less than proportionately with average income after instrumentation.
  - Top quintile: income rises significantly more than proportionately with average income after instrumentation.
- Cross-country variation:
  - Bottom quintile elasticity significantly less than one for China, the NIEs, and South Asia (excluding India).
  - Brazil: bottom-quintile elasticity significantly greater than one.
  - Top quintile: elasticity significantly greater than one for China and South Asia (excluding India); significantly less than one for Brazil.
- Selected coefficients:
  - Log of mean household income (y) for bottom quintile: -0.025, -0.142**, -0.097 (cols 1–3).
  - For top quintile: 0.040*, 0.119***, 0.060 (cols 4–6).
  - Regional interactions: NIEs*y -0.430*** (bottom), Brazil*y 0.469*** (bottom), South Asia*y -0.480*** (bottom).
  - Observations: 661 (bottom) / 633 (top).

### Importance of growth for the poor (Table 4)
- Constructed measures of pro-poor and inclusive growth for Brazil, China, India, Indonesia, Russia, and Mexico across decades.
- Highlights and examples:
  - Inequality widened in China, in contrast to Brazil and Mexico; yet China achieved greater poverty reduction given higher average income growth.
  - Indonesia and Russia: in the 2000s relative to the 1990s, poverty reduction was much greater despite inequality worsening, because growth was much higher.
  - Inclusive-growth example: growth has been half as inclusive in China as in Brazil, but income of the poorest fifth increased relatively more in China due to much stronger average income growth.
- Table 4 sample entry for China 1980s:
  - Elasticity of Poverty w.r.t. Income Growth: -3.4
  - Degree of Inclusiveness: 0.78
  - Change in Predicted Bottom Fifth Income: 54
  - Change in Predicted Gini: -17759 (as proxied by 100 times the change in the log over the corresponding period)

### Structural determinants of pro-poor and inclusive growth (Equations 4–5; Tables 5–7)
- Approach: compile structural reform variables (education, healthcare, labor share of income, share employment in manufacturing, openness, credit penetration, financial reform) and estimate interactions with income to explain variation in βs and λs.
- Bivariate and multivariate findings:
  - Factors that significantly increase the impact of income on poverty (make growth more pro-poor): years of schooling, educational spending, credit penetration, trade openness, labor share, and share of employment in industry.
  - Financial openness reduces the impact of income on poverty.
  - In multivariate specifications, the positive impact of share of employment in industry and the negative impact of financial openness survive.
- Inclusive growth determinants:
  - Labor share, education spending, years of schooling, industry employment, and financial reform significantly increase the degree of inclusiveness (increase impact of average income on bottom-quintile income and reduce impact on top-quintile income).
  - In multivariate regressions, financial reform, education spending, and industry employment remain significant.
- Selected reported coefficients:
  - Table 5 (Pro-poor determinants): Log mean household income coefficients range (e.g., -1.876*** to -2.632***); Log of Gini index coefficients generally positive and significant (e.g., 3.214***, 4.096***).
  - Employment in industry*y coefficients negative and significant in many specifications (e.g., -0.066***).
  - Financial openness*y positive and significant in some bivariate specifications (e.g., 0.003***), but financial openness overall tends to reduce pro-poor impact.
  - Table 6 (Bottom quintile inclusiveness): Employment in industry*y positive and significant (e.g., 0.025***); Financial reform index (normalized), 0 to 1*y positive and significant (e.g., 0.525**).
  - Table 7 (Top quintile inclusiveness): Employment in industry*y negative and significant (e.g., -0.009***); Financial reform index (normalized), 0 to 1*y negative and significant (e.g., -0.220**).

### Policy recommendations to foster inclusive growth
- Fiscal policy
  - Increase and reorient public spending toward education and health.
  - Raise tax revenues and improve progressivity by broadening income and consumption tax bases, reducing exemptions, and improving compliance.
  - Increase reliance on targeted social expenditures aimed at vulnerable households (e.g., conditional cash transfers).
    - Examples and fiscal figures:
      - Brazil’s “Bolsa Familia” covers around 25 percent of the population.
      - Mexico’s program associated with a 10 percent reduction in poverty within two years of introduction.
      - Philippines’ “the 4Ps”: introduced in 2008; in 2012 budgeted to reach 60 percent of the poor; by 2013 planned coverage of 3.8 million households; budget cost about 0.4 percent of GDP.
      - Bolsa Familia and 4Ps cost 0.4 percent of GDP.
      - India’s unique identification scheme (UID) holds promise for better targeting of social schemes.
  - Strengthen safety nets in higher-income Asian countries: many emerging Asian economies lack unemployment insurance and have low pension coverage rates (less than 20 percent of working-age population covered in most of emerging Asia vs. average of 60 percent in OECD countries).
  - Fiscal options and cost management:
    - Potential revenue options: introduce/increase GST, reduce poorly targeted fuel subsidies, reallocate existing spending.
    - Some policies may have no fiscal cost (e.g., unemployment insurance with employee/employer contributions to individual accounts); pension expansion can be cost-managed via defined contribution basis and higher contribution rates.
- Labor market reform
  - Strengthen labor market institutions to support incomes of low-earning workers: address labor market duality, consider minimum wages and employment protection measures.
  - Evidence and nuance on minimum wages:
    - Theory and empirical evidence ambiguous on disemployment effects; effect depends on level relative to market wage.
    - Minimum wages work better in combination with employment-contingent benefits to reinforce work incentives and prevent employers from driving down wages.
  - India’s rural employment guarantee scheme may have contributed to slight decline in rural inequality.
- Financial inclusion and financial development
  - Promote broad access to finance: rural finance, micro-credit expansion, credit information sharing, nondiscriminatory regulation, and venture capital market development.
  - Harness new technologies (e.g., UID-enabled cell-phone banking) to reduce transaction costs and broaden access.
  - Strengthen prudential framework, supervision, legal environment, property rights, and contract enforceability to support SME lending and client protection.
  - Avoid policies that channel credit to politically-favored ends.
- Governance and institutional reforms
  - Reduce corruption, improve transparency, and enforce regulations to ensure growth gains are widely shared.
  - Regional examples: Malaysia’s Government Transformation Program (whistleblower protection; objectives for fighting corruption); Philippines’ reforms in public financial management, business regulations, and the judiciary.

### Box 2. Insiders and Outsiders in Japan and Korea — summary
- Nonregular workers account for over one-third of the labor force in both countries; share of nonregular workers increased markedly in recent decades.
- Drivers: demand for labor market flexibility, aftermath of Japan’s bubble burst and Korea’s Asian Crisis, and deregulation increasing temporary worker use.
- Distributional effects: large pay disparities between nonregular and regular workers (regular worker salaries 25–100 percent higher on average for comparator regular workers), weak safety-net coverage for nonregular workers, and episodes of large nonregular job losses (e.g., 270 thousand nonregular workers lost jobs in Japan after the Lehman crisis).
- Policy recommendations:
  - Reduce discrepancies by lowering the cost of regular employment and increasing protection of the vulnerable under social safety nets.
  - Introduce more flexible labor contracts (e.g., phased-in employment protection) and expand social insurance.
  - Guiding principle: “protect the worker, not the job.”

### Box 4. Financial Development, Growth and Inequality — summary
- Channels: financial development fosters growth and can reduce poverty and inequality by relaxing credit constraints and improving capital allocation; theory predicts possible inverted-U relationship with inequality.
- Risks: financial globalization and liberalization can widen disparities or be captured by elites; too rapid liberalization can cause crises that hurt the poor hardest.
- Empirical evidence:
  - Better developed financial systems associated with lower poverty and faster poverty decline; rural financial development contributes to reducing rural inequality in China; rural India shows output increases and poverty declines with greater access to finance.
  - Access gap: nearly 60 percent of the population in East Asia and 80 percent of that in South Asia lack access to the formal financial system.
  - Specific access disparity cited: "30 times more ATMs for every 100,000 adults than low-income ones."
- Selected regional financial inclusion indicators (Table 9 extract):
  - East Asia and Pacific 42876/51 ‒ 75140‒170 / >59
  - South Asia 22612 /51‒75 60-70 / >59
  - Middle East and North Africa 42136 /26‒50 12‒15 / >59
  - Sub-Saharan Africa 12326 /75‒100 26‒30 / >59
  - Latin America and the Caribbean 40250 /51‒75 11‒12 / 40‒59
  - Central Asia and Eastern Europe 50193 /26‒50 5‒7 / 20‒39
  - High-income countries 9260 /0‒25 10‒12 / <20
- Policy recommendations for financial development:
  - Ensure macroeconomic stability and sequence liberalization prudently; strengthen prudential frameworks and supervision.
  - Remove impediments to financial access; promote rural finance, nondiscriminatory regulation, microfinance, credit information sharing, and wider service offerings (credit, savings, payments, insurance).
  - Harness technologies (e-money, retail payments) and bolster legal/market infrastructure.
  - Promote transparency and competition; avoid credit channeling to politically-favored ends.
- Governance: address corruption and strengthen enforcement to ensure poor benefit from growth.

*Source: _wp13152 - References .............................................................................................................*

### References .............................................................................................................

### _wp13152 - References .............................................................................................................

### Introduction: key findings
- Income inequality has risen across the world over the last two decades; the academic literature attributes the rise mainly to globalization, skill-biased technical change, and the decreasing bargaining power of workers.
- The global crisis and recent social turmoil have heightened awareness of the potential impact of rising inequality on economic and social stability and on the sustainability of growth.
- Main findings from the paper:
  - Poverty has fallen in recent decades in Asia but inequality has increased.
  - The rise in income inequality has dampened the impact of growth on poverty reduction.
  - Relative to other regions and to Asia’s own past, the recent period of growth has been both less inclusive and less pro-poor.
  - There is scope for policy measures to broaden the benefits of growth, notably enhanced spending on health and education, stronger social safety nets, labor market interventions, financial inclusion, and strengthened governance.

### How Asia compares to other regions: empirical highlights
- Asia’s growth over the last two decades has been much faster than its comparators outside the region, enabling significant reductions in poverty.
- Asia remains home to the largest number of the world’s poor, with China and India together accounting for almost half (see Table 1).
- Selected country and regional figures preserved from the source:
  - China: in 1981, 84 percent of the population lived on less than $1.25 a day; by 2008 this proportion had fallen to 13 percent.
  - India: in 1981, 60 percent of the population lived on less than $1.25 a day; by 2010 this share fell to 33 percent.
- Trends in inequality:
  - China: official estimates show Gini increased from 37 percent in the mid 1990s to 49 percent in 2008; it ticked down to 47.4 in 2012.
  - India: Gini rose from 33 percent in 1993 to 37 percent in 2010 (ADB estimate).
- Spatial and rural–urban disparities:
  - In China, spatial disparities are estimated to account for between one-third and two-thirds of overall inequality; the rural-urban income gap increased to a ratio of more than 3:1 (with a slight decline since 2009).
  - For most other Asian economies, the rural–urban ratio falls between 1.3–1.8 (Eastwood and Lipton, 2004).
  - In India, the ratio of urban to rural per capita consumption increased from around 1.5 in 1987–8 to nearly two in 2009–10.
  - Regional disparity example in India: the ratio of per capita GDP of Punjab to Bihar rose from 2.9 in 1980 to 4.1 in 2010.

### Box: China and India — drivers of divergent poverty and inequality dynamics
- China
  - Rapid poverty reduction associated with rural economic reforms and low initial inequality.
  - Relatively equal allocation of land via land use rights helped agricultural growth translate into poverty reduction.
  - High access to health and education facilitated poverty-reducing nonfarm growth.
  - Since the mid-1990s: slowed agricultural growth, reduced rural employment and incomes, increased rural–urban income gap, and rise in urban poverty partly due to large-scale migration.
- India
  - Slower poverty reduction compared with China; lower growth elasticity of poverty reduction.
  - Larger initial inequalities in schooling, health and gender may have impeded the poor from contributing to and benefiting from growth.
  - Trend growth concentrated in modern services (largely urban-based and requiring higher human capital), which may have limited the poor’s participation.
- Rising inequality: contributing factors emphasized in the Box
  - Health and education spending: high fiscal decentralization in China with more than half of expenditure at the sub-provincial level; poor villages lack own-revenue sources, public spending per capita in the richest province is almost 50 times that in the poorest; similar patterns in India stressing need for central redistribution to poor regions.
  - Declining labor share of income: in China and India, the share of labor income to manufacturing value added fell from 50 percent in both countries during the early 1990s to around 40 percent (China) and 25 percent (India) by the mid 2000s (Asian Development Bank, 2012). This contributes to inequality because capital income tends to be less evenly distributed than wage labor income.
  - Employment elasticity of growth: in China, the employment elasticity fell from 0.44 to 0.28 between 1991 and 2011.

### Policy implications emphasized in the source
- Potential policy interventions to broaden benefits of growth:
  - Enhanced spending on health and education.
  - Stronger social safety nets.
  - Labor market interventions (including discussion of minimum wage in the paper’s Box 3 and related analysis).
  - Financial inclusion and financial deepening (see Box 4 and Figure 8 references).
  - Strengthened governance and fiscal redistribution toward poorer regions.

*Source: _wp13152 - References .............................................................................................................*

### 0.53 to 0.41 in India. This has been exacerbated in the case of China by an artificially low cost of capital. In both

### _wp13152 - 0.53 to 0.41 in India. This has been exacerbated in the case of China by an artificially low cost of capital. In both

### Inequality trends and proximate drivers
- Rural surplus labor reduced bargaining power and held down wages relative to productivity.
- India: between 1990 and 2007, labor productivity rose by nearly 7½ percent annually, while real wages grew by only 2 percent per year (Kumar and Felipe, 2010).
- Regional disparities:
  - Coastal regions in China and coastal states in India provided more nonagricultural employment and income opportunities.
  - Disparities compounded by preferential policies and persistent gaps in human capital and infrastructure (Fan, Kanbur, and Zhang., 2009).
- Skill premia and returns to education:
  - China: between 1988 and 2003, wage returns to one additional year of schooling increased from 4 to 11 percent (Zhang and others, 2005).
  - India: larger schooling inequalities have inhibited pro-poor growth (Ravallion and Datt, 2002).
- Financial exclusion:
  - Differential financial development and urban biases in lending contributed significantly to China’s urban-rural income disparity since the late 1980s (Zhang and others, 2003).
  - India: underdevelopment of financial systems hits the poor more than the rich, resulting in higher income inequality (Ang, 2008).
- Regional pattern: Inequality has increased across Asia, reversing previous three-decade record of fast and equitable growth in Japan, the NIEs, and the ASEAN. The rise in inequality has been larger than in other emerging regions (IMF, 2006).

### Observed effects during the global crisis
- Poverty generally continued to fall in Asia, but the global crisis exacerbated the rise in inequality in several economies.
- Notable pronounced trend in rural China and Indonesia; observed also for Japan and some NIEs.
- Figure 2 (Selected Asia): changes in $1.25/day poverty headcount and Gini index during the global crisis include entries for: Philippines (2006-09), New Zealand (2004-09), India, rural (2004-09), China, urban (2005-08), Taiwan Province of China (2006-09), Japan (2005-09), Korea (2006-10), India, urban (2004-09), China, rural (2005-08), Indonesia, rural (2007-11), Indonesia, urban (2007-11).

### Definitions: pro-poor and inclusive growth
- Pro-poor growth: growth that reduces poverty (following Ravallion and Chen, 2003).
- Inclusive growth: growth not associated with an increase in inequality (following Rauniyar and Kanbur, 2010); operationally, growth is inclusive when it is not associated with a reduction in the income share of the bottom quintile.

### Pro-poor growth regression results (Table 2)
- Estimated regression (log of poverty headcount below the $2 line): β gives impact of income growth on poverty reduction; δ gives impact of change in Gini coefficient.
- Instrumental variables approach: lags of real per capita income (Penn World Tables) used to instrument household-survey-based average income.
- Key estimates:
  - A 1 percent increase in real per capita income leads to about a 2 percent decline in the poverty headcount (column 1).
  - A 1 percent increase in the Gini coefficient more or less offsets the beneficial impact on poverty reduction of the same increase in income.
  - Income-Gini interaction is significant: higher inequality reduces the impact of income growth on poverty reduction (column 2).
  - Example: an increase in the Gini coefficient of about 25 percent (as observed in urban China from 1995–2005) reduces the impact of a 1 percent increase in income to about a 1½ percent decline in the poverty headcount from 2 percent in the base case.
- Regional variation:
  - Income growth has a significantly lower impact on poverty in East Asia and Latin America than in the Middle East and North Africa, Eastern Europe and Central Asia, and sub-Saharan Africa (baseline).
  - Impact particularly weak in India and Indonesia, where it is significantly less than the impact of an equivalent reduction in the Gini coefficient.
- Table 2 reported coefficients (selected):
  - Log of mean household income (y): -2.146***, -8.205***, -2.627***, -3.406***, -10.536*** (across columns).
  - Log of Gini index: 2.258***, -5.838***, 2.277***, 2.003***, -7.799*** (across columns).
  - Income-Gini interaction: 1.723***, 2.035***.
  - Observations: 579; R-squared range: 0.461 to 0.654; Number of clusters: 98; Models: FE and IV.

### Inclusive growth regressions (Dollar-Kraay style) — bottom and top quintiles (Table 3)
- Model: elasticity λ of bottom-quintile income with respect to average income; if λ < 1 then growth is not inclusive.
- Pooled or fixed-effects without instrumentation: incomes of poorest fifth rise proportionately with per capita income (Dollar-Kraay result) (column 1 for bottom quintile; column 4 for top quintile).
- Instrumented results (columns 2 and 5):
  - Bottom quintile: income rises significantly less than proportionately with average income after instrumentation.
  - Top quintile: income rises significantly more than proportionately with average income after instrumentation.
- Cross-country variation (columns 3 and 6; Figures 4–5):
  - Bottom quintile elasticity significantly less than one for China, the NIEs, and South Asia (excluding India).
  - For Brazil, bottom-quintile elasticity significantly greater than one.
  - Top quintile: elasticity significantly greater than one for China and South Asia (excluding India); significantly less than one for Brazil.
- Table 3 selected coefficients:
  - Log of mean household income (y) for bottom quintile: -0.025, -0.142**, -0.097 (cols 1–3).
  - For top quintile: 0.040*, 0.119***, 0.060 (cols 4–6).
  - Regional interaction coefficients: NIEs*y -0.430*** (bottom), Brazil*y 0.469*** (bottom), South Asia*y -0.480*** (bottom).
  - Observations: 661 (bottom) / 633 (top); Models: FE and IV.

### Importance of growth for the poor (Table 4)
- Table 4 presents constructed measures of pro-poor and inclusive growth for Brazil, China, India, Indonesia, Russia, and Mexico across decades.
- Highlights:
  - Inequality widened in China, in contrast to Brazil and Mexico; yet China achieved greater poverty reduction given higher average income growth.
  - Indonesia and Russia: in the 2000s relative to the 1990s, poverty reduction was much greater despite inequality worsening, because growth was much higher.
  - Inclusive-growth example: growth has been half as inclusive in China as in Brazil, but income of the poorest fifth increased relatively more in China due to much stronger average income growth.
- Table 4 sample entries (proxies and measures):
  - China 1980s: Elasticity of Poverty w.r.t. Income Growth -3.4; Degree of Inclusiveness 0.78; Change in Predicted Bottom Fifth Income 54; Change in Predicted Gini -17759 (as proxied by 100 times the change in the log over the corresponding period).
  - Other decade/country entries follow similarly formatted measures.

### Structural determinants of pro-poor and inclusive growth (Equations 4–5; Tables 5–7)
- Approach: compile structural reform variables (education, healthcare, labor share of income, share employment in manufacturing, openness, credit penetration, financial reform) and estimate interactions with income to explain variation in βs and λs.
- Bivariate and multivariate findings:
  - Factors that significantly increase the impact of income on poverty (i.e., make growth more pro-poor) include: years of schooling, educational spending, credit penetration, trade openness, labor share, and share of employment in industry.
  - Financial openness reduces the impact of income on poverty.
  - In multivariate specifications, the positive impact of share of employment in industry and the negative impact of financial openness survive.
- Inclusive growth (bottom and top quintiles):
  - Labor share, education spending, years of schooling, industry employment, and financial reform significantly increase the degree of inclusiveness (increase impact of average income on bottom-quintile income and reduce impact on top-quintile income).
  - In multivariate regressions, financial reform, education spending, and industry employment remain significant.
- Interpretation notes:
  - Education and industry employment are important for increasing impact of income on poverty and inequality.
  - Financial openness appears to reduce effect of income on poverty, while financial reform increases degree of inclusiveness.
  - Industry employment robustness is consistent with labor shifts from agriculture to industry raising agricultural productivity where most poor are employed.
- Selected reported coefficients and results:
  - Table 5 (Pro-poor determinants): Log mean household income coefficients range across columns (e.g., -1.876*** to -2.632***); Log of Gini index coefficients generally positive and significant (e.g., 3.214***, 4.096***).
  - Employment in industry*y coefficients negative and significant in many specifications (e.g., -0.066***).
  - Financial openness*y positive and significant in some bivariate specifications (e.g., 0.003***), but financial openness overall tends to reduce pro-poor impact (coefficients reported).
  - Table 6 (Bottom quintile inclusiveness): Employment in industry*y positive and significant (e.g., 0.025***); Financial reform index (normalized), 0 to 1*y positive and significant (e.g., 0.525**).
  - Table 7 (Top quintile inclusiveness): Employment in industry*y negative and significant (e.g., -0.009***); Financial reform index (normalized), 0 to 1*y negative and significant (e.g., -0.220**).

### Policy recommendations to foster inclusive growth
- Fiscal policy:
  - Increase and reorient public spending toward education and health: regressions and scatter plots point to association between inclusiveness and education and health spending.
  - Raise tax revenues and improve progressivity: broaden income and consumption tax bases by reducing exemptions and improving compliance.
  - Increase reliance on targeted social expenditures aimed at vulnerable households (e.g., conditional cash transfers).
    - Examples from text:
      - Brazil’s “Bolsa Familia” covers around 25 percent of the population and is considered successful.
      - Mexico’s program associated with a 10 percent reduction in poverty within two years of introduction.
      - Philippines’ “the 4Ps”: introduced in 2008; in 2012 budgeted to reach 60 percent of the poor; by 2013 planned coverage of 3.8 million households; budget cost about 0.4 percent of GDP.
      - India’s unique identification scheme (UID) holds promise for better targeting of social schemes.
  - Strengthen safety nets in higher-income Asian countries: many emerging Asian economies lack unemployment insurance and have low pension coverage rates (less than 20 percent of working-age population covered in most of emerging Asia vs. average of 60 percent in OECD countries).
  - Fiscal cost considerations:
    - Bolsa Familia and 4Ps cost 0.4 percent of GDP.
    - Minimum social safety net argued to be deliverable at low cost in recent IMF studies on China and Korea.
    - Potential revenue options: introduce/increase GST, reduce poorly targeted fuel subsidies, reallocate existing spending.
    - Some policies may have no fiscal cost (e.g., unemployment insurance with employee/employer contributions to individual accounts); pension expansion can be cost-managed via defined contribution basis and higher contribution rates.
- Labor market reform:
  - Strengthen labor market institutions to support incomes of low-earning workers: address labor market duality, consider minimum wages and employment protection measures.
  - Scatter plots show positive association between inclusiveness and employment protection index and minimum wage levels; South Asia and NIEs have particularly low minimum wages.
  - Minimum wages:
    - Theory and empirical evidence ambiguous on disemployment effects; effect depends on level relative to market wage.
    - Minimum wages work better in combination with employment-contingent benefits to reinforce work incentives and prevent employers from driving down wages.
  - India’s rural employment guarantee scheme may have contributed to slight decline in rural inequality.

*Italic: Source: Excerpt from IMF working paper content provided in the input PDF chapter/section.*

### Box 2. Insiders and Outsiders in Japan and Korea

### Box 2. Insiders and Outsiders in Japan and Korea

### Emergence of dual labor markets
- Nonregular workers now account for over one-third of the labor force in both countries.
- The share of nonregular workers has markedly increased in recent decades, resulting in a system with both insiders (regular workers) and outsiders (nonregular workers).
- The rising share of nonregular workers is significantly higher than comparator countries across the OECD.

### Drivers of the shift
- Demand for a more flexible workforce in systems that strongly protect regular workers.
- Japan: the sharp rise followed the bursting of the Japanese bubble.
- Korea: the rise coincided with the Asian Crisis.
- Deregulation has contributed to the increased use of temporary workers in both countries.

### Distributional and social consequences
- Large pay disparities between nonregular and regular workers have likely influenced recent trends in growing inequality.
- In Japan, salaries are from 25–100 percent higher on average for comparator regular workers, with the difference rising with seniority as regular workers’ salaries increase while nonregular workers’ salaries generally stagnate.
- Nonregular workers are less likely to be protected under established social safety nets.
- Following the onset of the Lehman crisis in Japan, 270 thousand nonregular workers lost their jobs, and many former nonregular workers were broadly reported to have become homeless due to incomplete entitlement to full unemployment insurance.

### Policy recommendations
- Reduce discrepancies by both lowering the cost of regular employment and increasing protection of the most vulnerable under the social safety net.
- Introduce a new, more flexible labor contract to increase incentives for hiring regular workers and allow more young and female workers to enter mainstream career paths with established firms.
  - One possible option: modify regular work contracts to include phased-in employment protection that gradually increases dismissal costs to employers over the course of a worker’s tenure.
  - Expected effect: reduce hiring risks given unknown skills of new workers, while maintaining employment protection for tenured employees.
- Accompany increased flexibility with an expansion of social insurance, particularly in Korea where public expenditure remains low by international standards.
- Guiding principle: “protect the worker, not the job.”

*Source: Box 2. Insiders and Outsiders in Japan and Korea (from the provided IMF content).*

### Box 4. Financial Development, Growth and Inequality

### Box 4. Financial Development, Growth and Inequality

### Channels and theoretical evidence
- Financial development spurs growth by enabling larger investments and more productive allocation of capital, and by offering better and cheaper services for saving money and making payments (avoiding barter or cash transaction costs, cutting remittance costs, enabling asset accumulation and consumption smoothing).
- Financial development that broadens access to finance can benefit the poor disproportionately because financial market imperfections (asymmetric information; transaction and contract enforcement costs) hit poor and small-scale entrepreneurs hardest (lack of collateral, credit histories, connections), impeding capital flow to high-return projects among the poor and aggravating inequality.
- Some economic models predict:
  - Direct and indirect reductions in poverty and inequality via relaxed credit constraints on the poor and improved capital allocation and accelerated growth (example: Banerjee and Newman, 1993).
  - An inverted-U relationship with inequality, where in early development stages the rich benefit disproportionately but at higher income levels financial development begins to relax credit constraints for a larger share of families and firms (example: Greenwood and Jovanovic, 1990).

### Risks and limits
- Financial development does not always reduce inequality, especially in the short run:
  - Financial globalization has been associated with widening income disparities (Jaumotte, Lall, and Papageorgiou, 2008).
  - Financial liberalization can be captured by a narrow elite, reducing rather than broadening access (Claessens and Perotti, 2007).
  - Too rapid financial liberalization can result in crises; beyond certain thresholds rapid financial development can cause macroeconomic volatility when regulation and supervision are weak (Easterly, Islam, and Stiglitz, 2001). The poor and vulnerable can be hit hardest when social safety nets are underdeveloped and social spending and aid stagnate after crises.

### Empirical evidence linking financial development and inclusion to distributional outcomes
- Cross-country studies referenced indicate economies with better developed financial systems tend to have:
  - Lower poverty levels and better health and education indicators at the same level of income.
  - Faster poverty decline where financial intermediaries (banks, insurance companies) are more developed.
  - Faster growth of income for the lowest quintile than average income (Clarke, Xu, and Zhou, 2006; Beck, Demirgüç-Kunt, Levine, 2007).
- Regional and country-level findings in Asia:
  - Lack of access to finance is a major impediment in many parts of Asia: nearly 60 percent of the population in East Asia and 80 percent of that in South Asia lack access to the formal financial system (Table 9).
  - Financial access appears to have worsened for many of the region’s economies during the global crisis (CGAP and World Bank, 2010).
  - Empirical cases: output increases and poverty declines with greater access to finance in rural India (Burgess and Pande, 2005); rural financial development (total rural loans to rural GDP) contributes significantly to reducing rural inequality in China (Liang, 2008).
- Specific access disparity cited: "30 times more ATMs for every 100,000 adults than low-income ones."

### Selected regional financial inclusion indicators (as presented)
- The source presents a Table 9 summary labeled "Selected Indicators of Financial Inclusion" and cites "Financial Access 2010 and Access to Finance 2010." Example regional figures and indicators noted in the table extract:
  - East Asia and Pacific 42876/51 ‒ 75140‒170 / >59
  - South Asia 22612 /51‒75 60-70 / >59
  - Middle East and North Africa 42136 /26‒50 12‒15 / >59
  - Sub-Saharan Africa 12326 /75‒100 26‒30 / >59
  - Latin America and the Caribbean 40250 /51‒75 11‒12 / 40‒59
  - Central Asia and Eastern Europe 50193 /26‒50 5‒7 / 20‒39
  - High-income countries 9260 /0‒25 10‒12 / <20
- Source attribution for the table: "Source: Financial Access 2010 and Access to Finance 2010."

### Policy recommendations to promote financial development that supports growth and reduces inequality
- Ensure macroeconomic stability while liberalizing financial systems and tailoring liberalization to each country's circumstances; sequence reforms prudently to enhance interest rate flexibility, credit allocation, risk management, financial and capital markets depth, and intermediation patterns; strengthen prudential framework and supervision.
- Identify and remove impediments to financial access (including those inhibiting competition) without directing particular outcomes; expand credit availability via rural finance, nondiscriminatory regulations (loan classification criteria, capital requirements), micro-credit expansion, credit information sharing, and venture capital market development; promote a wider range of services (credit, savings, payments, insurance) for underserved segments.
  - Examples of promising initiatives in Asia: CARD MRI card in the Philippines (microfinance-oriented rural bank, a thrift bank for SMEs, and a micro-insurance institution); Thailand's Microfinance Master Plan (2008–11).
- Harness new technologies in less developed economies to broaden access (example: India's UID program enabling use of cell phones to bank, reducing transaction costs and facilitating trade); technologies include e-money and efficient retail payments systems.
- Bolster legal environment and financial market infrastructure (property rights, contract enforceability); well-defined collateral processes can encourage SME lending; more developed economies should focus on capital market development; enhance client financial education.
- Regulatory focus: promote transparency and competition among private financial institutions (Levine, 2011); avoid policies that channel credit to politically-favored ends, which decrease service quality, increase cost, and breed corruption in credit allocation (Barth and others, 2009), disproportionately harming lower income households.

### Governance and institutional reforms
- Institutional reforms can help ensure growth gains are widely shared:
  - High and rising corruption increases inequality and poverty by reducing tax progressivity, the level and effectiveness of social spending, and human capital formation (Gupta, Davoodi, and Alonso-Terme, 1998).
  - In resource-rich countries, reduce rent-seeking via transparency initiatives and anti-corruption efforts (Collier, 2007).
  - Better enforcement of existing regulations can address market failures in financial, land, and human capital markets so the poor benefit from growth (Duflo, 2011).
- Regional governance examples in Asia:
  - Malaysia: Government Transformation Program introduced a whistleblower protection act and set objectives for fighting corruption.
  - Philippines: reforms covering public financial management, business regulations, and the judiciary.

### Key conclusions relevant to financial development, inclusiveness, and policy priorities
- Stylized facts: poverty has fallen across the region over the last two decades, but inequality has increased, dampening the impact of growth on poverty reduction; recent growth has been less inclusive and less pro-poor relative to Asia’s past and other regions.
- Regression and empirical findings highlighted:
  - In East Asia and Latin America, income growth has a significantly lower impact on poverty than in China, the Middle East and North Africa, Eastern Europe and Central Asia, and sub-Saharan Africa; the impact is particularly weak in India and Indonesia.
  - Higher inequality tends to reduce the impact of income growth on poverty reduction, implying past rises in inequality in Asia may reduce future poverty-reducing effects of income growth even if inequality stabilizes.
  - Inclusive regression results indicate the income of the bottom quintile rises less fast than average income when instruments are used—unlike the Dollar-Kraay result—and show significant regional differences: growth generally not inclusive in China, the NIEs, and South Asia (excluding India), but strongly inclusive in Brazil.
  - Per capita income growth remains a key driver of poverty reduction; despite widening inequality in China, greater average income growth produced larger poverty reduction than in Brazil and Mexico due to higher average income growth.
- Policy package suggested:
  - Fiscal policy: higher spending on health and education and enhanced social safety nets (increases in pension coverage; conditional cash transfers).
  - Labor market reforms: increase the voice of labor to boost its share in total income (minimum wages; reducing duality in labor contracts).
  - Financial inclusion: build a more inclusive financial system.
  - Governance: improve governance and institutional quality.

*Source: Box 4. Financial Development, Growth and Inequality, IMF working paper content provided in the supplied PDF excerpt.*

### Appendix II

### Appendix II

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*Source: _wp13152 - Appendix II*

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_Source: https://www.imf.org/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/wp/2013/_wp13152.pdf_