Will the international target of reducing poverty by half over the next 15 years be met? Not unless growth efforts are accompanied by significant improvements in income distribution, according to research conducted at the Overseas Development Institute. Poverty reduction is a twin function of the rate of growth and of changes in income distribution. The research shows better distribution has as much impact on reducing poverty as has increased growth. And given predicted rates of economic growth, it emerges as the factor that will make the main difference between success and failure for new 'pro-poor' growth strategies.

Over the past decade, the amount of poverty reduction resulting from a given rate of economic growth has varied in close step with income distribution. Work by Hanmer and others reveals that, on average, a growth rate of 10 percent reduced the poverty headcount (the percentage of people living on less than $1 a day) by 9 percent in countries where income was fairly equally distributed. However in countries where income was unequally distributed, a growth rate of 10 percent reduced the poverty headcount by only 3 percent.

The World Bank estimates that developing countries will grow at 4 percent per capita per annum until 2015. What are the implications of this growth rate for meeting the DAC (OECD's Development Assisstance Commitee) income-poverty target? If a 4 percent growth rate is accompanied by low income inequality then the DAC target is easily met, and poverty is halved by 2006. If, on the other hand, high income inequality accompanies growth then the DAC target is not achieved. The 4 percent growth rate forecast is optimistic to begin with.

Higher rates of growth help, but only to a limited extent. Shifting from a high inequality to a low inequality growth path has a greater effect on poverty reduction than adding an extra 1 percent to the growth rate. In fact, in the high income inequality scenario it would require an extra 5 percent growth (to make a total rate of 9 percent) per capita per annum to meet the target. This figure would be without historical precedent. Even the Southeast Asian economies only grew 5.5 percent per annum between 1965 and 1997.

High and low income inequality are defined in the calculation respectively as Gini coefficients above and below 0.43 (see Unbottling the Gini). The table shows Gini coefficients for some large developing countries and some developed market economies. Income distribution varies from country to country but there are more high-inequality countries in Latin America and the Caribbean and in sub-Saharan Africa than in Asia, Europe and North America. If income inequality remains unchanged in Latin American and sub-Saharan African the desired poverty target will not be achieved.

So the good news is that the DAC income-poverty target is attainable - provided that significant improvements take place in income distribution. These can be achieved ex-ante, by designing growth strategies that increase disproportionately the incomes of the poorest, or ex-post, by redistributing income through taxation. Many questions arise. What is the recipe for income-redistributing growth? Is there a trade-off between growth and distribution? Are ex-post strategies of redistribution feasible? These questions are far from new. Indeed, to a large degree, they are the very questions on which the development studies profession is founded. Nevertheless, they have been neglected in recent years. Does current research offer new perspectives? Articles in this issue of Insights offer six main conclusions. They are that:

• We need a way to measure 'pro-poor growth'. The concept originates from the 1990 World Development Report of the World Bank and is taken to mean a labour intensive growth path that encompasses the economic activities of the poor. However, such a growth path could be accompanied by increasing, declining or static income inequality. McCulloch and Baulch propose that the 'poverty bias of growth' or PBG (whether pro-poor or not) be defined by comparing actual change in income distribution with the change that would have resulted had all incomes grown at one rate with no change to income inequality. This difference is compared in their report for two states in India. From this comparison it emerges that growth in Bihar state was accompanied by worsening income distribution and has been biased against the poor, whereas in Andhra Pradesh the reverse was true.
• Growth might be expected to be pro-poor if it takes place in areas and sectors where the poor live and work. For the poorest countries this means mostly in rural areas and to a large extent in agriculture. In Asia, Green Revolution technologies were adopted by poor farmers because they were scale-neutral and low-risk. Poor non-farmers also benefited from the extra employment and lower food prices that resulted. In sub-Saharan Africa, the Green Revolution has been slower in coming, but research at Reading by Mosley suggests an African Green Revolution will help. In Uganda, for example, the spread of new technologies in maize and cassava has contributed to sharp falls in poverty, notably in the country's North, where mosaic-resistant cassava has made a conspicuous difference to farmers' yields and incomes in an otherwise poor and undeveloped region.
• Even so, as many will remember well from debates about the Green Revolution in Asia, not everybody benefits from growth. In Ethiopia, researchers from the Universities of Oxford and Addis Ababa found that rural poverty has fallen sharply since the change of government in 1992, driven by market liberalisation and better weather (see Dercon). Yet those who have gained have been those with assets, including land, oxen for ploughing, education and access to public goods such as roads. Those without assets are left behind. Rural inequality has actually risen, implying Ethiopia could reduce poverty faster if policies countered inequality yet maintained current growth rates.
• People without assets might be expected to compensate by migrating or moving out of agriculture. Sometimes this happens, but seeking off-farm opportunities may be easier for the haves than the have-nots. In rural Zimbabwe, for example, Piesse and Thirtle have shown that (in more remote areas at least) those with higher farm incomes are better placed to exploit off-farm opportunities, including the option of working in town.
• In any case, migration to town may not offer much to the unskilled - again, a problem facing those without assets. The evidence here comes from China, in research carried out by the Institute of Economics and Statistics. Wage employment has increased in urban China, but wage inequality has increased sharply, with falling real wages for the unskilled.
• The efficiency (hence the growth) and equity trade-off is far from clear cut. Analysis by Knight of the reasons behind rising wage-income inequality in China has revealed that some of these changes reflect greater labour market efficiency. In other words, more productive, experienced and skilled workers have become better paid.
• Other changes hint at new inefficiencies creeping into China's labour market, such as growing discrimination: females and minority groups find they are disadvantaged in the labour market, whereas members of the Communist Party are more likely to get jobs Other signs are sharper segmentation, with state employees paid more than private sector counterparts and growing differences in wage rates between the provinces, not offset by labour mobility.

The cross-section of findings offered in these pages does not amount to a systematic review of the 'inequality question' in developing countries. Far from it: here is fertile ground for further research. Even so, we are confident that it is time to promote inequality to the fore of the research and policy agenda.

Source(s):
"For richer, for fairer", Insights #31 (Editorial), ID21, Institute of Development Studies, University of Sussex (1999)
Are the DAC Targets Achievable? Poverty and Human Development in the Year 2015 Journal of International Development, Vol. 2: 547-563 By Hanmer, L. et al. (1999)

Funded by: Various

id21 Research Highlight: 7 September 1999

Further Information:
Simon Maxwell and Lucia Hanmer
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Contact the contributor: odi@odi.org.uk

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