China has seen a huge reduction in the incidence of extreme poverty since the economic reforms that started in the late 1970s. Yet, the growth process has been highly uneven across sectors and regions. The paper tests whether the pattern of China´s growth mattered to poverty reduction using a new provincial panel data set constructed for this purpose. The econometric tests support the view that the primary sector (mainly agriculture) has been the main driving force in poverty reduction over the period since 1980. It was the sectoral unevenness in the growth process, rather than its geographic unevenness, that handicapped poverty reduction. Yes, China has had great success in reducing poverty through economic growth, but this happened despite the unevenness in its sectoral pattern of growth. The idea of a trade-off between these sectors in terms of overall progress against poverty in China turns out to be a moot point, given how little evidence there is of any poverty impact of non-primary sector growth, controlling for primary-sector growth. While the non-primary sectors were key drivers of aggregate growth...

Using a large cross-country income distribution dataset spanning close to 800 country-year observations from industrial and developing countries, the authors show that the size distribution of per capita income is well approximated empirically by a lognormal density. The 0 hypothesis that per capita income follows a lognormal distribution cannot be rejected-although the same hypothesis is unambiguously rejected when applied to per capita consumption. The authors show that lognormality of per capita income has important implications for the relative roles of income growth and inequality changes in poverty reduction. When poverty reduction is the overriding policy objective, poorer and relatively equal countries may be willing to tolerate modest increases in income inequality in exchange for faster growth-more so than richer and highly unequal countries.

Poverty reduction has become a fundamental objective of development, and therefore a metric for assessing the effectiveness of various interventions. Economic growth can be a powerful instrument of income poverty reduction. This creates a need for meaningful ways of assessing the poverty impact of growth. This paper follows the elasticity approach to propose a measure of pro-poorness defined as a weighted average of the deviation of a growth pattern from the benchmark case. The measure can help assess pro-poorness both in terms of aggregate poverty measures, which are members of the additively separable class, and at percentiles. It also lends itself to a decomposition procedure, whereby the overall pattern of income growth can be unbundled, and the contributions of income components to overall pro-poorness identified. An application to data for Indonesia in the 1990s reveals that the amount of poverty reduction achieved over that period remains far below what would have been achieved under distributional neutrality. This conclusion is robust to the choice of a poverty measure among members of the additively separable class, and can be tracked back to changes in expenditure components.

The paper examines the ways in which recent economic growth has been uneven in China and India and what this has meant for inequality and poverty. Drawing on analyses based on existing household survey data and aggregate data from official sources, the authors show that growth has indeed been uneven-geographically, sectorally, and at the household level-and that this has meant uneven progress against poverty, less poverty reduction than might have been achieved had growth been more balanced, and an increase in income inequality. The paper then examines why growth was uneven and why this should be of concern. The discussion is structured around the idea that there are both "good" and "bad" inequalities-drivers and dimensions of inequality and uneven growth that are good or bad in terms of what they imply for both equity and long-term growth and development. The authors argue that the development paths of both China and India have been influenced by, and have generated, both types of inequalities and that while good inequalities-most notably those that reflect the role of economic incentives-have been critical to the growth experience thus far, there is a risk that bad inequalities-those that prevent individuals from connecting to markets and limit investment and accumulation of human capital and physical capital-may undermine the sustainability of growth in the coming years. The authors argue that policies are needed that preserve the good inequalities-continued incentives for innovation and investment-but reduce the scope for bad ones...

The authors examine the empirical evidence in support of the poverty trap view of underdevelopment. They calibrate simple aggregate growth models in which poverty traps can arise due to either low saving or low technology at low levels of development. They then use these models to assess the empirical relevance of poverty traps and their consequences for policy. The authors find little evidence of the existence of poverty traps based on these two broad mechanisms. When put to the task of explaining the persistence of low income in African countries, the models require either unreasonable values for key parameters, or else generate counterfactual predictions regarding the relations between key variables. These results call into question the view that a large scaling-up of aid to the poorest countries is a necessary condition for sharp and sustained increases in growth.

The author discusses regional development patterns in China and examines effective ways of using development aid to attain regional balanced growth through optimizing growth spillover effects. Based on provincial panel data from 1978-99 she constructs an indicator "neighborhood performance" to measure the geographic spillover effects of aggregate growth from and to different provinces according to their relative richness and geographic position. Analysis of a Solow-type growth model suggests that positive spillover effects dominate negative shadow effects at the national level as well as the regional level, and some coastal provinces provide growth pull and growth push forces for their neighbors and serve as locomotives. The results show that the rapid takeoff of the coastal provinces has the largest spillover effects on the Chinese economy, but at the expense of a widening regional gap. A policy of encouraging the growth of the non-coastal regional hubs would have strong forward and backward linkages with the inland and western regions and thus reduce the regional development gap without sacrificing much aggregate growth. The author offers support for the policy of developing inland hubs, and argues that directing development aid to Hubei and Sichuan would optimize the growth spillover impacts on inland regions.

This paper investigates the relationship between sectoral growth patterns and employment outcomes. A broad cross-country analysis reveals that in middle-income countries, employment responds more to growth in less productive and more labor-intensive sectors. Employment in middle-income countries is susceptible to a resource curse, and grows rapidly in response to manufacturing and export manufacturing growth. Within Brazil, Indonesia, and Mexico, the effects of different sectoral growth patterns are context dependent, but differences in sectoral growth effects on employment and wages are substantially reduced in states or provinces with higher measured labor mobility. Consistent with this, aggregate employment and wage effects of growth by sector are close to uniform when examined over longer time horizons, after labor has an opportunity to adjust across sectors. The results reinforce the importance of growth in more labor-intensive sectors, and suggest that job mobility may be an important mechanism to diffuse the benefits of capital-intensive growth.

These days it seems that almost everyone in the development community is talking about "pro-poor growth." What exactly is it, and how can we measure it? Is ordinary economic growth always "pro-poor growth" or is that some special kind of growth? And if it is something special, what makes it happen? The author first reviews alternative approaches to defining and measuring "pro-poor growth." He then analyzes evidence on whether growth is pro-poor, what factors make it more pro-poor (including the role played by both initial inequality and changing inequality), and whether the factors that make the distribution of the gains from growth pro-poor come at a cost to growth. The author identifies some priorities for future research.

Incomes in the poorest two quintiles on average increase at the same rate as overall average incomes. This is because, in a global dataset spanning 118 countries over the past four decades, changes in the share of income of the poorest quintiles are generally small and uncorrelated with changes in average income. The variation in changes in quintile shares is also small relative to the variation in growth in average incomes, implying that the latter accounts for most of the variation in income growth in the poorest quintiles. These findings hold across most regions and time periods and when conditioning on a variety of country-level factors that may matter for growth and inequality changes. This evidence confirms the central importance of economic growth for poverty reduction and illustrates the difficulty of identifying specific macroeconomic policies that are significantly associated with the relative growth rates of those in the poorest quintiles.

The paper proposes an approach to understand the relationship between inequality and economic growth obtained by shifting the analysis from the space of final achievements to the space of opportunities. To this end, it introduces a formal framework based on the concept of the Opportunity Growth Incidence Curve. This framework can be used to evaluate the income dynamics of specific groups of the population and to infer the role of growth in the evolution of inequality of opportunity over time. The paper shows the relevance of the introduced framework by providing two empirical analyses, one for Italy and the other for Brazil. These analyses show the distributional impact of the recent growth experienced by Brazil and the recent crisis suffered by Italy from both the income inequality and opportunity inequality perspectives.

It is important to know how aggregate economic growth or contraction was distributed according to initial levels of living. In particular, to what extent can it be said that growth was "pro-poor?" There are problems with past methods of addressing this question, notably that the measures used are inconsistent with the properties that are considered desirable for a measure of the level of poverty. The authors provide some new tools for assessing to what extent the aggregate growth process in an economy is pro-poor. The key measurement tools is the "growth incidence curve," which gives growth rates by quantiles (such as percentiles) ranked by income. Taking the area under this curve up to the headcount index of poverty gives a measure of the rate of pro-poor growth consistent with the Watts index for the level of poverty. The authors give examples using survey data for China during the 1990s. Over 1990-99, the ordinary growth rate of household income per capita in China was 7 percent a year. The growth rate by quantile varied from 3 percent for the poorest percentile to 11 percent for the richest...

The evidence is compelling that the poor in developing countries do typically share in the gains from rising aggregate affluence and in the losses from aggregate contraction. But how much do poor people share in growth? Do they gain more in some settings than others? Do some gain while others lose? Does pro-poor growth mean more or less aggregate growth? Recent theories and evidence suggest some answers, but deeper microeconomic empirical work is needed on growth and distributed change. Only then will we have a firm basis for identifying the specific policies and programs needed to complement and possibly modify growth-oriented policies.

Brazil's slow pace of poverty reduction over the last two decades reflects both low growth and a low growth elasticity of poverty reduction. Using GDP data disaggregated by state and sector for a twenty-year period, this paper finds considerable variation in the poverty-reducing effectiveness of growth-across sectors, across space, and over time. Growth in the services sector was substantially more poverty-reducing than was growth in either agriculture or industry. Growth in industry had very different effects on poverty across different states and its impact varied with initial conditions related to human development and worker empowerment. The determinants of poverty reduction changed around 1994: positive growth rates and a greater (absolute) elasticity with respect to agricultural growth contributed to faster poverty reduction. But because there was so little of it, economic growth played a relatively small role in accounting for Brazil's poverty reduction between 1985 and 2004. The taming of hyperinflation (in 1994) and substantial expansions in social security and social assistance transfers...

The article documents five stylized facts of economic growth: (1) the 'residual' (total factor productivity, tfp) rather than factor accumulation accounts for most of the income and growth differences across countries; (2) income diverges over the long run; (3) factor accumulation is persistent while growth is not, and the growth path of countries exhibits remarkable variation; (4) economic activity is highly concentrated, with all factors of production flowing to the richest areas; and (5) national policies are closely associated with long-run economic growth rates. These facts do not support models with diminishing returns, constant returns to scale, some fixed factor of production, or an emphasis on factor accumulation. However, empirical work does not yet decisively distinguish among the different theoretical conceptions of tfp growth. Economists should devote more effort toward modeling and quantifying tfp.

This paper contributes to explain the cross-country heterogeneity of the poverty response to changes in economic growth. It does so by focusing on the structure of output growth. The paper presents a two-sector theoretical model that clarifies the mechanism through which the sectoral composition of growth and associated labor intensity can affect workers' wages and, thus, poverty alleviation. Then it presents cross-country empirical evidence that analyzes first, the differential poverty-reducing impact of sectoral growth at various levels of disaggregation, and the role of unskilled labor intensity in such differential impact. The paper finds evidence that not only the size of economic growth but also its composition matters for poverty alleviation, with the largest contributions from labor-intensive sectors (such as agriculture, construction, and manufacturing). The results are robust to the influence of outliers, alternative explanations, and various poverty measures.

The extent to which India's poor have benefited from the country s economic growth has long been debated. This paper revisits the issues using a new series of consumption-based poverty measures spanning 50 years, and including a 15-year period after economic reforms began in earnest in the early 1990s. Growth has tended to reduce poverty, including in the post-reform period. There is no robust evidence that the responsiveness of poverty to growth has increased, or decreased, since the reforms began, although there are signs of rising inequality. The impact of growth is higher for poverty measures that reflect distribution below the poverty line, and it is higher using growth rates calculated from household surveys than national accounts. The urban-rural pattern of growth matters to the pace of poverty reduction. However, in marked contrast to the pre-reform period, the post-reform process of urban economic growth has brought significant gains to the rural poor as well as the urban poor.

After Mexico's financial crisis in 1994, the distribution of income, and labor earnings improved. Did inequality increase during the recession, as one would expect, since the rich have more ways to protect their assets than the poor do? After all, labor is poor people's only asset (the labor-hoarding hypothesis). In principle, one could argue that the richest deciles experienced severe capital losses, because of the crisis in 1994-96, and were hurt proportionately more than the poor were. But the facts don't support this hypothesis. As a share of total income, both monetary income (other than wages, and salaries) and financial income, increased during that period, especially in urban areas. Financial income is a growing source of inequality in Mexico. Mexico's economy had a strong performance in 1997. The aggregate growth rate was about 7 percent, real investment grew 24 percent, and exports 17 percent, industrial production increased 9.7 percent, and growth in civil construction (which makes intensive use of less skilled labor) was close to 11 percent. Given those figures, it is not surprising that the distribution of income, and labor earnings improved, but the magnitude, and quickness of the recovery prompted a close inspection of the mechanisms responsible for it. The authors analyze the decline in income inequality after the crisis...

Over the past 20 years, aggregate measures of global inequality have changed little even if significant structural changes have been observed. High growth rates of China and India lifted millions out of poverty, while the stagnation in many African countries caused them to fall behind. Using the World Bank's LINKAGE global general equilibrium model and the newly developed Global Income Distribution Dynamics (GIDD) tool, this paper assesses the distribution and poverty effects of a scenario where these trends continue in the future. Even by anticipating a deceleration, growth in China and India is a key force behind the expected convergence of per-capita incomes at the global level. Millions of Chinese and Indian consumers will enter into a rapidly emerging global middle class-a group of people who can afford, and demand access to, the standards of living previously reserved mainly for the residents of developed countries. Notwithstanding these positive developments, fast growth is often characterized by high urbanization and growing demand for skills...

The author provides sectoral evidence that sheds new light on the current debate regarding the sources of growth of the East Asian miracle. The author tests both the productivity-driven and endowment-driven hypotheses using Hong Kong's sectoral data. The results show that most of the growth in the services sector is driven by the rapidly accumulating capital endowments, and not by productivity growth. In addition, productivity growth in the manufacturing sector is also unimpressive. The manufacturing sector is more labor intensive and its growth is hindered by the reallocation of resources into the services sector as a result of the growth of capital endowments and imports. Overall, sectoral evidence supports the endowment-driven hypothesis for Hong Kong's aggregate growth.

We consider the potential importance of labour market efficiency for aggregate growth. The idea is that efficient labour markets move workers more quickly from low to high productivity sites, thereby raising aggregate productivity growth. We define a measure of labour market efficiency as a structural parameter from a matching function. Using labour market data on 15 OECD countries, we estimate this and show that it has a significant effect on growth. The results are robust to a number of different estimation techniques. The quantitative impact of market efficiency is not trivial.