Information about Asia and the Pacific Asia y el Pacífico
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Chapter 5. Achieving Inclusive Growth

Author(s):
Alfred Schipke
Published Date:
April 2015
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Ravi Balakrishnan, Chad Steinberg and Murtaza Syed 

Frontier Asian economies are poised for continued rapid growth.1 Their per capita incomes may be relatively low compared with the rest of Asia at present, but they are clearly on a path to becoming the next generation of emerging market economies, and their populations will provide the next large market of middle-class consumers. Moreover, these countries are becoming increasingly integrated into a vibrant regional trade network that holds great promise. Lessons from within the region attest to the importance of trade openness as a vehicle for rapid development, and frontier Asian economies appear well placed to step into the global and regional production nexus and move up the value chain.

However, these economies can only make this leap in a sustainable manner if they address key policy challenges. One of the challenges is the need to make growth more inclusive so that the fruits of development are shared equitably across the income levels of their populations. Unless frontier Asia can reverse the rising tide of inequality, its potential for economic takeoff could be undermined.

In some ways, of course, inequitable development is a global issue. Income inequality has risen in most parts of the world since 1990. The academic literature attributes the rise mainly to three factors: globalization, skill-biased technological change, and the decreasing bargaining power of workers. But the rise in inequality in frontier Asia has been unprecedented, compared with both other emerging market regions and with Asia’s own historical record of equitable growth between the 1960s and 1980s. The global financial crisis and recent social turmoil in different parts of the world have heightened awareness of the potential impact of rising inequality on economic and social stability and on the sustainability of growth. Such concerns have not bypassed frontier Asia; policymakers throughout the region are looking for ways to arrest rising inequality and make growth more inclusive.

This chapter assesses the links between growth, poverty, and inequality in frontier Asia since the early 1990s. Its main findings are that poverty has fallen significantly in the region, but inequality has increased across most of the group, particularly in frontier south Asia, although that subgroup started from a relatively lower base. The rise in inequality has dampened the impact of growth on poverty reduction. As a result, compared with emerging market regions outside Asia, the recent period of growth has generally been both less inclusive and less pro-poor. In this context, the performance of frontier east Asian economies has so far generally been comparatively better than that in frontier south Asia. To reverse the trends and broaden the benefits of growth in the respective countries, policy measures need to be taken, specifically enhanced public spending on health and education, stronger social safety nets, labor market interventions, financial inclusion, and strengthened governance.

The rest of this chapter is organized as follows: The next section compares recent trends in poverty and inequality in frontier Asia with those in other regions of the world. Then, a regression approach is used to quantify the extent to which growth is pro-poor and inclusive. The section also assesses frontier Asia’s performance relative to its peers on these metrics. The subsequent section proposes potential policy interventions for broadening the benefits of frontier Asia’s growth. The final section offers concluding thoughts.

Stylized Facts: How Does Frontier Asia Compare with Other Emerging Market Regions?

During the past two decades, growth in most frontier Asian economies has been robust and higher, on average, than in other emerging market regions (Figure 5.1).

Figure 5.1The Quality of Frontier Asia’s Growth

This level of growth has enabled a halving of the incidence of extreme poverty, with relatively larger gains in the east Asian subgroup, including Cambodia, Lao P.D.R., and Vietnam. Notwithstanding this remarkable achievement, nearly one-third of the region’s population continues to live in extreme poverty, with generally higher poverty headcounts in south Asia (Table 5.1).

Table 5.1Number of People Living on Less than $1.25/day (at 2005 PPP prices)
Percent of

Population
Number

(millions)
Percent of

World Total
Number

(millions)
Percent of

World Total
1990200819902008
Europe and Central Asia2<19<120
Latin America and the Caribbean126533373
Middle East and North Africa6313191
Sub-Saharan Africa57482901538630
Asia55251,5448185566
China60136833617313
India47334332339531
Frontier and Developing (FD) Asia60301387937
FD east Asia16019523202
FD south Asia26137865736
Rest of Asia58312891519415
Total43221,9091,290
Source: World Bank, PovcalNet database. Note: PPP = purchasing power parity.

Includes Cambodia, Lao P.D.R., Mongolia, and Vietnam.

Includes Bangladesh, Nepal, and Sri Lanka.

Source: World Bank, PovcalNet database. Note: PPP = purchasing power parity.

Includes Cambodia, Lao P.D.R., Mongolia, and Vietnam.

Includes Bangladesh, Nepal, and Sri Lanka.

Moreover, inequality has increased across most of frontier Asia during the same period, with the exception of Cambodia, Nepal, and Vietnam. This rise in inequality is in sharp contrast to the region’s own past record, as well as to the previous three-decade record of fast and equitable growth in Japan, the newly industrialized Asian economies (NIEs), and the members of the Association of Southeast Asian Nations (ASEAN).2 In addition, this rise has been higher in frontier south Asia than in all other emerging market regions. Inequality has also risen in frontier east Asia, but by comparatively less. The rise in both subgroups compares unfavorably with trends in the Middle East and North Africa and Latin America, where inequality has fallen since 1990. With regard to the level of inequality, frontier east Asia stands close to the commonly used Gini warning threshold of 40, with south Asia not far behind. Earlier work (IMF 2006) attributes the rise in inequality in Asia to skill-biased technological change and the transition from agriculture to industry for lower-income economies (consistent with the Kuznets hypothesis).3 Also, as seen earlier, although the level of inequality in frontier Asia is generally lower than in other emerging market regions, incomes in the other regions have tended to become more equitable over time.

Growth, Poverty, and Inequality in Frontier Asia

Going beyond these stylized facts, regression analysis can be used to quantify how pro-poor and inclusive growth has been in frontier Asia relative to other emerging market regions.4 The following sections discuss the two regions of frontier Asian economies listed in the footnote on page one.5

Inclusive and pro-poor growth can be defined in several ways. This analysis follows the approach in Ravallion and Chen (2003) and simply defines growth as pro-poor if it reduces poverty. Inclusive growth, however, is defined as growth that is not associated with an increase in inequality, following Rauniyar and Kanbur (2010). In particular, growth is defined to be inclusive when it is not associated with a reduction in the income share of the bottom quintile of the income distribution.

How Pro-Poor Is Frontier Asia’s Growth?

To examine the relationship between poverty reduction and growth, the following regression is estimated:

in which Pi,t is the poverty headcount below the $2/day line in country i at time t, γi is a country dummy, yi,t is per capita income in country i at time t, GINIi,t is the Gini coefficient in country i at time t, and is ρd a set of decade dummies. Because the equation is in logs, β gives the elasticity of the poverty headcount ratio with respect to income per capita growth (holding the Gini coefficient constant), and δ gives the elasticity of the poverty headcount ratio with respect to the Gini coefficient (holding per capita income constant). β is allowed to vary across country and decade.6

A set of benchmark countries needs to be chosen to estimate the fixed effects. These benchmark countries are defined as all economies in the Middle East and North Africa, eastern Europe and central Asia, and sub-Saharan Africa. Latin America is excluded because it is commonly highlighted as being an important exception to the nearly global trend of increasing inequality since 1990. Therefore, this analysis is interested in explicitly comparing its experience—as well as those of large middle-income economies such as Brazil, China, India, and Indonesia, which are somewhat further along the development path—with that of frontier Asia. An instrumental variables approach is used to take account of endogeneity bias and potential measurement error in the income variable. In particular, lags of real per capita income as measured in the Penn World Tables are used to instrument the household-survey-based average income variable.7

The regression results presented in Table 5.2 suggest that growth is in general pro-poor, leading to significant declines in poverty across all economies and time periods. Specifically, a 1 percent increase in real per capita income is associated with a decline of about 2 percent in the poverty headcount ratio (column 1). However, a 1 percent increase in the Gini coefficient almost directly offsets the beneficial impact on poverty reduction of the same increase in income. Moreover, inequality interacts with income, meaning that a higher level of inequality tends to reduce the impact of income growth on poverty reduction (column 2). An increase in the Gini coefficient of about 25 percent reduces the impact of a 1 percent increase in income to about a 1½ percent decline in the poverty head-count from 2 percent in the base case. The implication of this result is that higher levels of inequality in frontier Asia are likely to reduce the impact of income growth on poverty. In addition, the impact of growth on poverty reduction is found to be somewhat lower during the 1990s, possibly as a result of the changing nature of growth (column 3).

Table 5.2Pro-Poor Growth Regressions
(1)(2)(3)(4)
Variablespppp
Log of mean household income (y)−2.146***−8.205***−2.627***−3.406***
[0.262][1.079][0.300][0.428]
Frontier east Asia*y1.258**
[0.616]
Frontier south Asia*y−0.159
[1.202]
Latin America and Caribbean*y1.294***
[0.502]
China*y1.149
[0.712]
India*y1.889***
[0.675]
Brazil*y1.220***
[0.436]
Indonesia*y1.957***
[0.433]
Log of Gini index2.258***−5.838***2.277***2.003***
[0.463][1.205][0.450][0.499]
Ninety (90s decade dummy)−0.7430.074
[0.536][0.075]
Noughty (2000s decade dummy)0.6940.262**
[0.647][0.112]
Ninety*y0.193*
[0.110]
Noughty*y−0.067
[0.126]
Income-Gini interaction1.723***
[0.267]
Observations579579579579
R-squared0.5580.6540.5580.461
Number of clusters98989898
ModelFE IVFE IVFE IVFE IV
Source: Authors.Note: FE IV = instrumental variables with fixed effects. Dependent variable is log poverty headcount below the $2 line. Robust standard errors in brackets. ***p < 0.01, **p < 0.05, *p < 0.1
Source: Authors.Note: FE IV = instrumental variables with fixed effects. Dependent variable is log poverty headcount below the $2 line. Robust standard errors in brackets. ***p < 0.01, **p < 0.05, *p < 0.1

The relationship, however, varies across regions and economies (column 4 and Figure 5.2). Within frontier Asian economies, South Asia’s growth has been highly pro-poor. Growth is also pro-poor in frontier east Asian economies, but has a somewhat lower impact on poverty. This impact is also lower than that in the benchmark economies (the Middle East and North Africa, eastern Europe and central Asia, sub-Saharan Africa), although it is still larger than the impacts in India and Indonesia.

Figure 5.2Income Elasticity of Poverty Reduction

Sources: Penn World Tables; World Bank, PovcalNet; and IMF staff calculations.

Note: The red bars represent countries for which the estimated income elasticity of poverty reduction is significantly different to that of the baseline countries. Figure shows the impact on poverty head-count, in percent, of a 1 percent increase in income per capita.

How Inclusive Is Frontier Asia’s Growth?

As a second step, the analysis follows Dollar and Kraay (2002) and examines the relationship between per capita income and an income distribution-based definition of “the poor”—now defined as the bottom quintile of the income distribution. If the income of the poor tends to rise equiproportionately with average incomes—that is, income growth is not associated with a decrease in the income share of the bottom quintile—then growth would be considered inclusive. Specifically, the following panel regression model is used:

in which yp1i,t is per capita income of the bottom quintile of the income distribution in country i at time t, θi is a country dummy, yi,t is per capita income in country i at time t, and ρd is a set of decade dummies. The coefficient λ, which is allowed to vary across country and decade, is the elasticity of income growth of the bottom quintile with respect to growth in average income. Equation (5.2) can be rewritten as

in which Q1i,t is the bottom quintile share of the income distribution in country i at time t. As equation (5.3) shows, if λ is less than 1, income growth is associated with a decrease in the income share of the bottom quintile—that is, growth is not inclusive. Equation (5.3) is the model estimated in this analysis. Given that much of the ongoing debate about inclusiveness has not just focused on the poorest fifth of society being left behind, but the richest fifth doing particularly well, a similar relationship for income in the top quintile is also estimated. As with the pro-poor regressions, an instrumental variables approach is used to take account of endo-geneity bias and potential measurement error in the income variable.

The results are shown in Table 5.3. If all observations are simply pooled, or if just country-specific effects are used, the analysis yields the familiar Dollar-Kraay result, that average incomes of the poorest fifth of society rise proportionately with per capita income (column 1), which also holds for the richest fifth at the 5 percent significance level (column 4). However, once the exercise instruments for the income variable (columns 2 and 5), the results change: the income of the bottom quintile rises significantly less than proportionately with average income, and the income of the top quintile rises significantly more than proportionately with average income—an important departure from the Dollar-Kraay stylized fact.8

Table 5.3Inclusive Growth Regression
(1)(2)(3)(4)(5)(6)
VariableslnQ1lnQ1lnQ1lnQ5lnQ5lnQ5
Log of mean household income (y)−0.025−0.142**−0.0970.040*0.119***0.060
[0.043][0.061][0.126][0.023][0.034][0.061]
Frontier East Asia*y0.126

[0.180]
−0.142

[0.101]
Frontier South Asia*y−0.480***

[0.178]
0.390**

[0.185]
NIEs*y−0.430***

[0.126]
0.098

[0.062]
Latin America and Caribbea*y0.133

[0.186]
−0.068

[0.080]
China*y−0.204

[0.128]
0.138**

[0.062]
Brazil*y0.469***

[0.126]
−0.260***

[0.063]
India*y0.320

[0.305]
−0.224

[0.146]
Indonesia*y0.049

[0.133]
−0.030

[0.069]
Observations661633633661633633
R-squared0.001−0.0270.0170.021−0.0190.064
ModelFEFE IVFE IVFEFE IVFE IV
Number of clusters107105105107105105
Source: Authors.Note: NIEs = newly industrialized economies. FE IV = instrumental variables with fixed effects.Dependent variable is log share of the income distribution of the bottom/top quintile share. Robust standard errors in brackets. ***p < 0.01, **p < 0.05, *p < 0.1.
Source: Authors.Note: NIEs = newly industrialized economies. FE IV = instrumental variables with fixed effects.Dependent variable is log share of the income distribution of the bottom/top quintile share. Robust standard errors in brackets. ***p < 0.01, **p < 0.05, *p < 0.1.

Moreover, these elasticities vary significantly across regions and countries (columns 3 and 6). For the bottom quintile in frontier Asia, the elasticity is significantly less than 1 for the South Asia group, as it is in China and the NIEs. By contrast, for frontier east Asia, it is equal to 1 for the benchmark economies and Latin America and the Caribbean, and in Brazil, it is significantly greater than 1 (Figure 5.3).9

Figure 5.3Degree of Inclusiveness of Growth

Sources: Penn World Tables; World Bank, PovcalNet; and IMF staff calculations.

Note: The red bars represent countries for which the estimated degree of inclusiveness is significantly different from one. The figure shows the impact on income of the bottom quintile, in percent, of a 1 percent increase in income per capita.

Turning to the top quintile, the results are generally the mirror image of those for the bottom quintile (Figure 5.4). The elasticity is significantly greater than 1 for frontier south Asia, as well as for China—and not significantly different from 1 for frontier east Asia nor for the benchmark economies—and significantly less than 1 for Brazil.10

Figure 5.4Degree of Inclusiveness of Growth

Sources: Penn World Tables; World Bank, PovcalNet; and IMF staff calculations.

Note: The red bars represent countries for which the estimated degree of inclusiveness is significantly different from one. The figure shows impact on income of the top quintile, in percent, of a 1 percent increase in income per capita.

In sum, the results suggest that growth has generally not been inclusive in the frontier south Asian economies, China, and the NIEs. However, it has been inclusive in frontier east Asia, as well as in the Middle East and North Africa, eastern Europe and central Asia, sub-Saharan Africa, Latin America and the Caribbean, and especially Brazil.11 This greater equity of frontier east Asia’s development—together with faster growth rates, on average, than in south Asia—has translated into bigger gains in poverty reduction and the incomes of the bottom quintile, even though growth has, on average, been relatively less pro-poor.

Fostering Inclusive Growth

This section discusses policies that could reduce inequality and increase inclusiveness in frontier Asia, based on international experience and econometric evidence (see also Case Studies 5.1 and 5.2).12 The list of policies is not exhaustive, however, given that multiple factors behind rising inequality suggest that a set of mutually reinforcing policies will likely be needed and that the necessary mix will vary from country to country.

Fiscal Policy

Simple scatter plots point to an association between the degree of inclusiveness of growth and education and health (Figure 5.5, panels a and b). The relatively low share in GDP of spending on education and health across frontier Asia (especially south Asia) highlights an important potential role for fiscal policy in strengthening inclusiveness (Figure 5.5, panels c and d).

Figure 5.5Fiscal Policy and Inclusiveness

Sources: World Bank, World Development Indicators; and IMF staff calculations.

Note: Red diamonds represent countries for which the estimated degree of inclusiveness is significantly different from one. FD = frontier and developing economies; LAC = Latin America and the Caribbean (excluding Brazil); NIEs = newly industrialized economies.

Adjusting both the level and the structure of taxes and spending may have a part to play. In Organisation for Economic Co-operation and Development (OECD) countries, taxes and transfer policies have been estimated to reduce inequality as measured by the Gini index by about 25 percent (OECD 2012). In sharp contrast, the redistributive impact of fiscal policy in developing economies is severely restricted by lower overall levels of both taxes and transfers—average tax ratios for advanced economies exceed 30 percent of GDP, whereas taxes in Asian emerging market and frontier economies are only 19 percent of GDP as of the latest year for which data are available. This ratio is lower than the 30 percent in Latin America and 37 percent in emerging Europe (IMF 2013; Bastagli, Coady, and Gupta 2012).

Partly as a result, social spending is also substantially lower than the 15 percent of GDP it is in advanced economies. Public health and education spending in frontier Asia is in the 4–8 percent of GDP range, lower than for peers in other emerging market regions and little increased since 2000.

Reliance on less progressive tax and spending instruments compounds the problem. In frontier Asia, income tax yields are lower than in peers and in advanced economies. Meanwhile, participation in social insurance schemes remains limited in many countries (particularly in rural areas), and expenditure on social assistance programs is often low and poorly targeted. According to ADB (2012), only about half the poor population in frontier Asia benefits from social programs.

It appears that raising tax revenue, and spending more efficiently and equitably, could help address income inequality in frontier Asia. On the tax side, efforts could focus on broadening income and consumption tax bases by reducing tax exemptions and improving compliance. On the spending side, measures could aim toward greater reliance on social expenditures, including on health and education, targeted to vulnerable households. In this regard, conditional cash transfer programs are being increasingly used in low-income emerging market economies, including Bangladesh and Cambodia. Brazil and Mexico have two of the largest schemes (in the former, Bolsa Familia covers about 25 percent of the population), with transfers contingent on requirements such as children’s school attendance and vaccination records. Both are considered to have been successful, with the Mexican program associated with a 10 percent reduction in poverty within two years of its introduction. In Asia, the Philippines introduced a conditional cash transfer program in 2008 (the 4Ps) to help redirect resources toward socially desirable programs in a well-targeted way.13 In 2012, the 4Ps was budgeted to reach 60 percent of the poor, and by 2013 it was to cover 3.8 million households, with a cost to the budget of about 0.4 percent of GDP. In India, the recently launched unique identification scheme holds significant promise in ensuring better targeting of social programs and allowing the vulnerable to access the welfare system.

Enhancing other safety nets could also help. In particular, few frontier Asian economies have unemployment insurance schemes, and many have low pension coverage rates—less than 20 percent of the working-age population is covered in most of emerging Asia compared with an average of 60 percent in OECD countries (OECD 2009). Enhancing such safety nets, as well as increasing the inclusiveness of growth, would also reduce precautionary motives to save, thereby increasing consumption and facilitating global rebalancing.

A key question about such policies is their fiscal cost. The Bolsa Familia and 4Ps programs only cost 0.4 percent of GDP, and recent IMF work on China and Korea (Barnett and Brooks 2010; Feyzioglu, Skaarup, and Syed 2008) argues that a minimum social safety net can be provided at low cost, with more comprehensive safety nets funded by broadening the tax base and increasing some taxes, along with reallocating existing spending. For many economies, introducing (or increasing the rate of) a goods and services tax and reducing poorly targeted fuel subsidies would be obvious candidates. Some policies may have no government spending obligations, such as unemployment insurance schemes with employee and employer contributions to individual accounts. In many cases, the challenge with regard to education is to improve quality. Expanding the provision of pensions could entail costs, but not necessarily if benefits are provided on a defined-contribution basis and contribution rates are increased.

Labor Market Reform

Simple scatter plots suggest that inclusiveness is positively associated with the degree of employment protection and minimum wage levels; frontier east Asia has relatively weak employment protection laws, and frontier south Asia has particularly low minimum wages (Figure 5.6).

Figure 5.6Labor Market Institutions and Inclusiveness

Sources: Botero and others (2004); World Bank, Doing Business database; and World Development Indicators database. Note: Red diamonds represent countries for which the estimated degree of inclusiveness is significantly different from one. FD = frontier and developing economies; LAC = Latin America and the Caribbean (excluding Brazil); NIEs = newly industrialized economies.

1Measures the protection of labor and employment laws as the average of: (1) Alternative employment contracts; (2) Cost of increasing hours worked; (3) Cost of firing workers; and (4) Dismissal procedures.

These results are consistent with recent academic work on advanced economies that links rising inequality to weakened bargaining power of workers (for example, Levy and Temin 2007). Although a comprehensive discussion of the impact of labor market institutions (such as collective bargaining structures) on the inclusiveness of growth is beyond the scope of this chapter, addressing labor market duality and use of a minimum wage are increasingly advocated in the region to support incomes of low-wage workers. In addition, India has launched a program to guarantee a certain minimum level of employment in rural areas, which may have contributed to the slight decline in rural inequality observed there after 2005.

Minimum wage measures are one of the most well-studied policies, yet both theory and empirical evidence on their disemployment effects are largely ambiguous (Boeri and Van Ours 2008). Fine-tuning is often necessary: set the rate too low and it has no impact; set it too high and it will have significant disemployment effects. Moreover, minimum wages usually work better in combination with benefits conditional on employment because they reinforce each other. In particular, although employment-conditioned benefits may be a good way of providing targeted assistance and work incentives, if labor has a limited voice, employers could use such benefits to drive down wages, a situation a minimum wage can help prevent (Gregg 2000).

The labor share of income in frontier Asia has fallen as a result of both weak wage growth and the exceptionally low and declining employment intensity of its economic growth, particularly in south Asia. Potential explanations are increasing capital accumulation and high levels of surplus labor in many of these countries (ADB 2012). More income going to capital rather than to labor tends to increase inequality because capital is typically more unequally distributed than labor income. This tendency suggests that policies that lift the incomes of the poor are needed, such as eliminating any bias in the cost of capital and other inputs that favor capital, promoting labor-intensive sectors such as services, improving rural infrastructure to boost productivity in farming and increase job opportunities for the poor, and increasing household financial income by offering more diversifed and better-priced financial products, as discussed in the next subsection.

Financial Inclusion

The regression analysis indicates that financial reform increases the degree of inclusiveness of growth, suggesting the importance of reforms that enhance financial inclusion. The finding is in line with empirical literature that argues that financial development not only promotes economic growth, but can also help apportion it more evenly. According to some estimates, the benefits to the poorest quintile of financial development (see Chapter 6 on Financial Sector Deepening) are split roughly equally between those benefits attributable to faster growth and those attributable to greater income equality (Beck, Demirgüç-Kunt, and Levine 2007).

How does frontier Asia fare with respect to financial development? Disparity across the region is appreciable (Figure 5.7). Financial deepening—a measure of the level of financial services, typically proxied by the broad-money-to-GDP ratio—is positively associated with per capita income, although its rate of growth has generally been higher in frontier Asia, suggesting some catching up is taking place across the region (see Chapter 6).

Figure 5.7Financial Deepening

(Latest year available)

Source: World Bank, World Development Indicators database; and IMF staff calculations.

In addition, deepening itself may not translate into financial services being broadly available across firms and households, making policies to promote access to finance equally important. Across the globe, high-income countries tend, on average, to have almost 12 times as many bank branches and 30 times as many automated teller machines for every 100,000 adults as do low-income countries. Lack of access to finance is a major impediment in many parts of frontier Asia, with nearly 60 percent of the population in east Asia and 80 percent in South Asia lacking access to the formal financial system (Table 5.4).

Table 5.4Selected Indicators of Financial Inclusion
Households with

Access to Bank

(percent)
Adult Population not Using

Formal Financial Services

(millions/percent)
SMEs Lacking Access to Loan

from Financial Institution

(millions/percent)
East Asia and Pacific42876/51–75140-170/>59
South Asia22612/51–7560-70/>59
Middle East and North Africa42136/26–5012-15/>59
Sub-Saharan Africa12326/75–10026-30/>59
Latin America and Caribbean40250/51–7511-12/40–59
Central Asia and Eastern Europe50193/26–505-7/20–39
High-income countries9260/0–2510-12/<20
Sources: Consultative Group to Assist the Poor and World Bank (2010); and International Finance Corporation (2010). Note: SMEs = small and medium-sized enterprises.
Sources: Consultative Group to Assist the Poor and World Bank (2010); and International Finance Corporation (2010). Note: SMEs = small and medium-sized enterprises.

How might governments in frontier Asia promote financial development that both supports growth and reduces inequality? International experience provides some direction:

  • Ensure macroeconomic stability as financial systems are liberalized, and particularly as they are opened up to the rest of the world. There is no one-size-fits-all approach to liberalizing financial systems; the process should be tailored to each country’s circumstances. Across the world, prudently executed and sequenced reforms have resulted in greater flexibility in interest rates, improvements in credit allocation and risk management by commercial banks, deeper financial and capital markets, and significant enhancement in intermediation patterns. In tandem, the framework for monetary and exchange rate policy has typically undergone major changes, introducing market-based instruments to implement policy actions (see Chapter 9 on Monetary Policy Frameworks). The prudential framework and quality of supervision have also been strengthened to help prevent unsafe credit decisions and promote more effective management of market risks (see Chapter 7 on Financial Sector Vulnerabilities).
  • Identify and remove impediments to access to finance—including those that inhibit competition—without directing particular outcomes. Notably, expanding credit availability by promoting rural finance; ensuring that regulations (such as loan classification criteria and capital requirements) do not discriminate against the provision of finance to the rural poor, including to the agricultural sector; strengthening creditor rights; extending microcredit; promoting credit information sharing; and developing venture capital markets should significantly expand credit availability (Beck and Demirgüç-Kunt 2006).
  • In developing economies, harness new technologies to extend financial access to those previously excluded. Successful examples come from Kenya, where mobile phones have helped promote financial inclusion (IMF 2011), and India, whose unique identification program enables the poor to use their cell phones to perform banking functions while reducing transaction costs and facilitating trade. Technological innovation also has the potential to improve access to finance significantly, such as through the use of e-money and the provision of an efficient retail payments system.
  • Bolster the legal environment and financial market infrastructure, including property rights and contract enforceability. For instance, a well-defined process for securing collateral in the event of default can encourage banks to lend more to small and medium-sized enterprises in developing economies.
  • On the regulatory front, promote policies that foster transparency and competition among financial institutions (Levine 2012). Conversely, policies that channel credit to politically favored ends decrease the quality of financial services while increasing their cost and breeding corruption in credit allocation (see Barth and others 2009, for example). These distortions usually exert a disproportionately large impact on the living standards of lower-income households.

Governance

Finally, institutional reforms can also play an important role in helping ensure that the gains from growth are widely shared. Work by Gupta, Davoodi, and Alonso-Terme (1998) suggests that high and rising corruption increases inequality and poverty, including by reducing the progressivity of the tax system, the level and effectiveness of social spending, and the formation of human capital. In resource-rich countries, potential reforms include reducing rent-seeking behavior through transparency initiatives and anticorruption efforts (Collier 2007). In addition, regulation or better enforcement of existing regulation can also help address failures in markets that the poor participate in—poorly functioning financial, land, and human capital markets—so that they also benefit from growth (Duflo 2012).

Case Study 5.1.Bangladesh: On the Road to Inclusive Growth

Bangladesh’s experience illustrates the links between growth, poverty, and inequality in a populous, low-income frontier Asian economy. Despite its propensity for political upheaval and natural disaster, Bangladesh has achieved steady poverty reduction since 1990. From as high as 57 percent at the beginning of the 1990s, the headcount poverty rate declined to 31.5 percent in 2010,1 keeping Bangladesh well on track to reach Millennium Development Goal 1, to halve the proportion of people living below the poverty line by 2015 (Figure 5.1.1). Reinforcing the pro-poor nature of growth, inequality (as measured by the Gini coefficient of consumption) remained broadly stable during 2000–10, a decade during which Bangladesh experienced accelerating growth, after having picked up in the early 1990s. These advances were achieved in conjunction with improvements in a number of social indicators (Table 5.1.1), with Bangladesh standing out on several fronts when compared with the norms in the frontier south Asia region and low-income countries.

Figure 5.1.1Bangladesh: Indicators of Growth, Poverty and Inequality

Source: World Bank.

Note: GNI = gross national income.

Table 5.1.1Bangladesh: Selected socio-development indicators (most recent available estimate, 2005–2011)
BangladeshSouth AsiaLow Income Countries
Gross national income per capita (Atlas method, US$)7801,176528
Population growth rate (%)1.31.42.1
Total fertility rate (births per woman)2.32.74.1
Life expectancy at birth (years)676559
Infant mortality (per 1,000 live births)415270
Child malnutrition (% of children under 5)413323
Adult literacy, male (% of ages 15 and older)617369
Adult literacy, female (% of ages 15 and older)515054
Net primary school enrolment, male (% of age group)838981
Net primary school enrolment, female (% of age group)908478
Access to an improved water source (% of population)809065
Access to an improved sanitation (% of population)563837
Source: World Bank.
Source: World Bank.

Several factors have contributed to Bangladesh’s strong performance on poverty reduction since 1990. First, Bangladesh has seen sustained economic growth during the period, albeit not as rapid as that of the fastest-growing frontier Asian economies. Part of the growth in incomes was supported by rising worker remittances (more than 8 million Bangladeshis work abroad), which, in the latest period account for more than 11 percent of GDP, with attendant poverty-reducing benefits. Economic growth also translated into substantial improvements in rural income per capita. A key mechanism was the Green Revolution, which meant two crops (instead of one) a year could be grown on the same land. Because the highest incidence of poverty and the most extreme poverty tend to be rural (Figure 5.1.2), the Green Revolution helped make growth more pro-poor and inclusive, alongside the impressive poverty reduction in urban areas.2 Gains from rural poverty reduction were particularly evident during 2005–10, driven in part by greater policy attention to agriculture and rural development; the effects from the exogenous commodity food price increase, which raised real wages in the predominantly agricultural western regions; and in-migration from the western to the eastern divisions (thus reducing surplus rural labor supply).

Figure 5.1.2Bangladesh: Rural-Urban Poverty and Extreme Poverty Trends

Sources: Bangladesh Bureau of Statistics, Household Income and Expenditure Survey 1991–92, 2000 and 2010.

Notes: Upper poverty line defined in monetary terms as an income less than will provide for 2,212 calories per day. Lower poverty line similarly defined to provide for 1,800 calories per day (also taken as a threshold for extreme poverty).

Second, the condition of women has improved significantly in Bangladesh throughout this period. Policies such as for microcredit have helped (Grameen Bank, an institution developed in Bangladesh, offers loans targeted mainly at women) as have family-planning programs introduced after Bangladesh’s independence, which reduced fertility rates and raised the status of women within the household by giving them more influence over household size. The rise of the labor-intensive textile and garment industry, which has created almost 4 million jobs for unskilled and low-skilled workers—about 80 percent of them women—has also been a contributing factor.

Third, the government has maintained basic social spending programs, working in coordination with international and domestic development partners, including nongovernmental organizations. Relative to other south Asian countries, social safety net spending as a share of GDP in Bangladesh is comparable to that in India, but higher than in Nepal, Pakistan, and Sri Lanka (IMF 2012).3 These social safety net programs address poverty from a multifaceted perspective, including through education, health, nutrition, employment, and disaster response, and were estimated to have reached almost 40 percent of the poorest quintile based on Bangladesh’s 2010 Household Income and Expenditure Survey. A major proportion of the support provided food assistance through direct feeding programs, followed by cash transfer social protection programs (including the flagship Employment Generation Program for the Poorest, which was set up in response to the 2008 food price crisis). The work of homegrown nongovernment organizations in Bangladesh has been another influential factor in poverty reduction, with a number of them (such as BRAC, now the largest nongovernment organization in the world) able to scale up operations since Bangladesh’s independence in 1971 and work successfully in partnership with the government to support poverty reduction further.

Although favorable economic growth systematically helped reduce poverty, inequality rose until the mid-1990s as the country started to industrialize and urbanize. Since then, overall inequality trends have broadly stabilized, driven by some decline in urban inequality following rapid growth in the services sector in which many of the urban poor were employed (Paci and Sasin 2008). Nevertheless, inequality remains a pressing government concern, given that significant differences between geographic regions underlie the national poverty story, a phenomenon known as the “East-West divide” (World Bank 2008). The Dhaka, Sylhet, and Chittagong divisions in the eastern part of the country experienced rapid poverty reduction between 2000 and 2005 (Figure 5.1.3), but the gains were much smaller for Rajshahi in the west and almost nonexistent for Barisal and Khulna in the southwest. This pattern was partly reversed during 2005–10 when factors favoring rural incomes emerged, as noted previously. Addressing regional disparities remains a key thrust of Bangladesh’s Sixth Five-Year Plan (fiscal years 2011–15) and reinforces the need for greater infrastructure connectivity for the economically isolated southwest divisions (exemplified by the government’s centerpiece project for a bridge across the Padma River, which would connect those divisions with the economic heartland in the east, reducing transportation costs).

Figure 5.1.3Bangladesh: Headcount Poverty of Divisions

Sources: Bangladesh Bureau of Statistics, Household Income and Expenditure Survey 2000, 2005, and 2010.

Notwithstanding its progress, Bangladesh remains a poor country, with almost 45 million people in poverty in 2010. Looking ahead, the challenge will be to further elevate the rate of economic growth to make even deeper reductions in poverty in Bangladesh, while taking care to preserve the characteristics that have supported inclusiveness in the growth process. Related to this, a key challenge is to reach the poor more effectively by improving the targeting of social safety nets, with the World Bank’s work in Bangladesh on developing a poverty database a critical stepping stone toward this goal.

Source: Prepared by Seng Guan Toh.1 The headcount poverty rate based on Bangladesh’s national poverty line (also known as the upper poverty line), defined in monetary terms as an income that provides for sufficient caloric intake based on the 2010 Household Income and Expenditure Survey, was about $1.22 a day. The poverty headcount rate using the World Bank’s $1.25 a day (on a purchasing power parity basis as of 2005) shows a broadly similar declining trend since 1990, from almost 70 percent of the population in the early 1990s to 43.3 percent in 2010.2 Although urbanization has increased since 1990, Bangladesh remains largely rural, with about 72 percent of the population in rural areas in 2010 (as compared with 80 percent in 1990).3 Social safety net expenditures in the south Asian region ranged from about 0.8 percent of GDP in Sri Lanka to about 2 percent of GDP in Bangladesh and India (based on 2010–11 estimates).

Case Study 5.2.Vietnam: Poverty and Inequality

Growth and inclusiveness: Since 1990, relatively robust growth in Vietnam has enabled an impressive halving of the incidence of extreme poverty, quite a substantial reduction when compared with other countries in the region and a key Millennium Development Goal achieved even before the 2015 target year. Moreover, growth has not resulted in increased inequality (Figure 5.2.1). The inclusive outcome also suggests that postreform growth in Vietnam has largely been pro-poor, buttressed by the provision of basic public services, access to land, and infrastructure investments that have reached the poorer segments of the population.

Figure 5.2.1Vietnam’s Poverty and Inequality

Source: World Bank, World Development Indicators database.

Challenges ahead: Despite remarkable progress, challenges remain because poverty reduction has become less responsive to economic growth. Even though rising education levels, diversification into nonfarm activities, and good coverage of local infrastructure and basic services have been powerful poverty-fighting forces during the past decade, the quality of these services is unevenly distributed. A World Bank report, which bases its findings on successive rounds of the Vietnam Household Living Standards Surveys (VHLSS—latest 2010), reveals that inequality in income and opportunity has started to rise, reflecting widening gaps between urban and rural dwellers and across the socioeconomic and ethnic spectrum (World Bank 2012).

Although educational attainment is increasing rapidly, enrollment gaps between poor and better-off households persist, perpetuating the intergenerational transmission of poverty as well as contributing to rising inequality. Based on an empirical model that uses VHLSS data, the recent increase in income inequality in part reflects (1) the altered relative return on education and on physical and financial assets and (2) inequalities in education and access to jobs and geographic disparities. Furthermore, as the birthrate declines and the population starts to age, the demographic dimension of the policy challenge has changed from the child poverty of the past to the rising risk of old-age poverty.

Policy focus: Based on cross-country experience, a number of policies could further the inclusiveness of growth in Vietnam. Vietnam’s government has already focused higher shares of GDP on public health and education spending than have other countries in the region, but there is room for quality improvement and for more focus on youth in poor and ethnic minority areas. Fiscal policies that could sharpen these improvements include enhanced social safety nets—for example, increases in pension coverage and conditional cash transfers. Expanded basic financial services and improved financial system governance could also go a long way toward improving inclusiveness. Finally, policies to lift the incomes of the poor in Vietnam could include improving rural infrastructure to boost farm productivity and job opportunities, as well as eliminating distortions in the cost of, and access to, capital and land, which spur overinvestment and could undermine laborintensive sectors such as services and small and medium-sized enterprises.

Source: Prepared by Ashvin Ahuja.

Conclusion

This chapter assesses the extent to which frontier Asia’s recent growth has been pro-poor and inclusive compared with its own history and compared with other emerging markets and the factors driving these outcomes. Although poverty has fallen across the region since 1990, inequality has increased in most of the economies, dampening the impact of growth on poverty reduction. As a result, relative to other regions and to frontier Asia’s own past, the recent period of growth has generally been both less inclusive and less pro-poor, the latter in the sense that more gains in poverty reduction could have been possible given the region’s economic growth rates. More specifically, some of the key results include the following:

  • In frontier Asia, growth has been highly pro-poor. In frontier south Asia, income growth has had the highest impact on poverty reduction among all emerging market regions.
  • However, past increases in inequality in frontier Asia are likely to reduce the future impact of income growth on poverty, even if policymakers can somehow stem the tide and keep the level of inequality from worsening.
  • Moreover, the relatively sharp increase in inequality means that growth has generally not been inclusive in frontier south Asia, nor for China and the NIEs. However, growth has been inclusive in frontier east Asia, and strongly so in Brazil. It is important to note though that inequality—as measured by the Gini coefficient—remains lower in frontier south Asia than in many other regions.
  • Economic growth is still a key driver of poverty reduction—although growth in recent decades has been more pro-poor in south Asia, overall growth rates have, on average, been higher in frontier east Asia. These higher growth rates, together with relatively lower increases in inequality, have translated into greater poverty reduction and greater increases in the incomes of the bottom quintile.

Based on cross-country experience and other qualitative considerations, a number of policies could help redress the recent period of less inclusive and less pro-poor growth in frontier Asia. Fiscal policies could include higher spending on health and education and enhanced social safety nets (for example, increases in pension coverage and conditional cash transfers). Greater attention must also be paid to labor market reforms that increase the voice of labor (for example, minimum wages and reducing duality in labor contracts), thereby boosting labor’s share in total income. Finally, building a more inclusive financial system and improving governance should also be part of the policy package.

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1See Chapter 1 for a definition of frontier Asia. In this chapter, frontier Asia is divided into two subgroups by region: frontier south Asia, comprising Bangladesh, Bhutan, Nepal, and Sri Lanka; and frontier east Asia, comprising Cambodia, Lao P.D.R., Mongolia, and Vietnam. Maldives, Myanmar, and Timor-Leste are not covered because of data limitations.
2Newly industrialized Asian economies here refer to Hong Kong SAR, Korea, Singapore, and Taiwan Province of China; ASEAN includes Brunei Darussalam, Cambodia, Indonesia, Lao P.D.R., Malaysia, Myanmar, Philippines, Singapore, Thailand, and Vietnam.
3Jaumotte, Lall, and Papageorgiou (2008) also argue that skill-biased technological progress is a key driver of rising inequality.
4For the econometric analysis, the main sources of data are the latest versions of the World Bank’s PovcalNet database (updated in July 2012) and the Penn World Tables Version 7.0. PovcalNet is used because major effort has been made to make its inequality and poverty data comparable across surveys and countries: it draws on 700 household surveys for 120 countries (econ.worldbank.org/povcalnet). Household survey data for the NIEs are added to the PovcalNet data, resulting in an unbalanced panel between 1971 and 2010, with the sample skewed toward the latter part of the period.
5The group also includes Malaysia, Thailand, and the Philippines, which are also part of the east Asia group in our results.
6The regression model follows the literature that argues that although per capita income growth is a key factor, the same rate of growth can bring very different rates of poverty reduction, meaning that other factors matter—in particular, factors that change the income distribution (such as shocks to agricultural incomes, changes in tax regimes, and so forth). Thus, following Ravallion and Chen (1997), this analysis allows poverty to also depend on the Gini coefficient, which proxies for the underlying factors causing a change in the distribution of income. One can think of growth in average income as shifting the income distribution and changes in inequality as modifying the shape of the distribution, both of which can affect the poverty headcount (the cumulative distribution below a line at a particular income level, in this case the $2/day line).
7Specifically, the lagged variables help correct for endogeneity bias by identifying the component of income that is predetermined, and the Penn World Tables measure of income helps correct for measurement error by identifying the component of income, as measured by the household survey, which is also consistent with this secondary measure of income. Because both endogeneity bias and measurement error are relevant, the direction of the bias in the estimates that are not instrumented is uncertain.
8These results also validate concerns that both measurement error and attenuation bias affected the estimates presented in Dollar and Kraay (2002).
9Although the elasticity for China is not significantly different from that of the benchmark baseline economies at the 10 percent level (column 3 of Table 5.3), further χ2 tests show that it is significantly different from 1 at the 1 percent level.
10Similar to the result for China in the bottom quintile regression, although the elasticity for the NIEs is not significantly different from that of the benchmark economies at the 10 percent level (column 6 of Table 5.3), it is significantly different from 1 at the 1 percent level.
11One important caveat is that Brazil entered the 1990s with a relatively higher level of inequality.
12Other cross-country work finds that the labor share of income, public education spending, years of schooling, industry employment, and financial reform significantly increase the degree of inclusiveness (Balakrishnan, Steinberg, and Syed 2013). For Latin America, recent work has identified several factors that may have contributed to declining inequality, including policies aimed at enhancing employment and better distributing human capital through stepped-up provision of health and education services and conditional cash transfers (see ADB 2012, among others).
134Ps stands for Pantawid Pamilyang Pilipino Program.

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