Published on Let's Talk Development

Understanding the Sources of Spatial Disparity and Convergence: Evidence from Bangladesh

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The economic liberalization during the last couple of decades led to impressive economic growth and poverty reduction in many developing countries. This period has also witnessed worsening of income inequality and widening of spatial disparity (World Development Report (2009); Kanbur and Venables (2005); Kim (2008)). There is considerable worry among policy makers about the extent to which this rise in spatial inequality is due to increasing disparity in opportunities in terms of provision of basic infrastructure and services. The recent growth and poverty reduction experience places Bangladesh as an exception to this trend of increasing spatial inequality.  Bangladesh made significant strides in poverty reduction between 2000 and 2010 with incidence of poverty falling from 48.9 percent to 31.5 percent. During the same period, the incidence of poverty declined more than proportionately in traditionally poorer regions, reducing welfare gaps across regions. There is also no evidence of significant change in overall inequality over the same period. What made spatial disparity in Bangladesh to decline while its economic growth accelerated substantially? What were the sources of decline in spatial disparity in welfare?

To answer these questions, we construct a simple measure of spatial disparity in welfare. This measure, termed as "spatial disparity index", estimates the proportion of total variations in welfare that can be attributed to common area characteristics faced by households living an area/community. In a spatial equilibrium model, households of similar attributes and hence similar welfare status tend to live in the same community, resulting in a positive correlation in income and welfare among households. At the one extreme of complete segregation or perfect sorting, all households living in a community will look similar, producing a spatial disparity index estimate of unity. In this case, all of the inequality in welfare is due to inter-community differences. In contrast, if there is no sorting, then a randomly selected sample of households from a community will be indistinguishable from a random sample of households from any other community. The difference in welfare in this case is entirely due to within community differences (spatial disparity=0). The spatial disparity index constructed here has at least two advantages. First, it can be estimated from different representative household surveys to ascertain the evolution of spatial disparity over time. The magnitudes of estimated spatial disparity indices for different years can then be compared to check out for spatial convergence or divergence in welfare. Second, it can be decomposed to determine the community attributes that are important in explaining spatial differences in welfare.

Empirical evidence based on nationally representative household surveys in this paper indicates a significant decline in spatial disparity in Bangladesh between 2000 and 2010. More than a third of the total variance of log of per capita expenditure in 2000 can be explained by spatial factors alone compared with 26 percent in 2010. Spatial disparity declined significantly in urban areas as well (from 0.38 to.30). The extent of spatial disparity is much smaller in rural areas and it declined only marginally (from 0.22 to 0.20) between these years. The sustained urban-rural difference in spatial disparity is consistent with lower labor mobility due to higher skill requirements in urban jobs. The decomposition analysis shows that much of the spatial variations in welfare (log per capita expenditure) in the pooled and urban samples in both survey years can be explained by three community level variables: average years of education, percentage of households with electricity connection, and with phone ownership. In the rural sample, agro-climatic conditions also explain a large share of inter-community variations in welfare.

Electricity and phone coverage improved substantially in both urban and rural areas between 2000 and 2010. Such improvements appear to have conflicting influence on the magnitudes of spatial disparity in urban and rural areas. What explains such difference? In new economic geography models, availability of electricity leads to higher firm productivity which – through agglomeration economies – could result in increasing spatial inequality in the short to medium term. In contrast, basic infrastructure such as electricity has also amenity value to households as it reduces time and costs of household activities (chores, reading). In a willingness to pay framework, households are thus willing to accept lower wages and higher housing prices to avail the benefit of electricity. This in turn reduces spatial disparity in the short to medium term. In urban areas, expansion of electricity and phone network brought newer households under coverage whereas firms already had these connections. As a result, amenity effects predominated over productivity effects and led to spatial convergence. In contrast, spatial disparity in the rural areas remained nearly unchanged suggesting that amenity and productivity effects perhaps offset each other.

Empirical results from Bangladesh thus suggest a way to deal with rising regional inequality during the post-liberalization period. To keep regional inequality in check, investments in infrastructure and services benefitting firms/farms should be balanced by investments benefitting households. For basic infrastructure such as electricity, this means providing it not only to firms/farms for productive use but also to households for its amenity value.


Forhad Shilpi

Senior Economist, Development Research Group

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