7 roles, much more than 55 percent of poverty reduction will have to come from rural growth if Tanzania is to make substantial progress in bringing down poverty for the nation as a whole.

# **3.3 Growth Incidence Curves**

The impact of growth on poverty can be examined graphically through a growth incidence curve (GIC), which illustrates the distribution of growth. A GIC is a plot of the growth rate for each quantile of the distribution of per adult equivalent consumption. Growth incidence curves for the nation as a whole and the three strata are shown in Figure 1. The curves were constructed based on the two household surveys, and the annual growth rates reflect average changes over the 1993-2001 period. The growth incidence curves were generated by splitting the distributions into 15 quantiles or bins.

Although the vertical scale is the same across the different curves, the horizontal scale plots percentiles within each sector, so points at the same percentile level for different sectors correspond to different levels of consumption. The vertical line in the graph indicates the poverty headcount index in 1992, while the horizontal line denotes the mean overall growth rate.

We consider growth “absolutely pro-poor” if the mean growth rate for the poor is greater than zero and “relatively pro-poor” if, in addition, the mean growth rate for the poor is at least as large as the growth rate in the overall mean. Hence, “absolute pro-poor growth” only requires that the poor be better off on average in absolute terms, while “relative pro-poor growth” requires the distributional shifts to be pro-poor as well.

In terms of Tanzania as a whole, the growth incidence curve lies entirely above zero, implying that consumption increased at every point in the distribution. In other words, growth for the country as a whole was pro-poor in absolute terms. Likewise, growth was absolutely pro-poor in Dar es Salaam and rural areas. Although mean growth rates were modest everywhere except Dar, growth did improve consumption for rich and poor alike. Only in the distribution for the other urban areas stratum were there absolute declines, in the poorest percentiles.

In Dar es Salaam and other urban areas mean growth rates for the poor were below growth in the mean for the stratum as a whole and growth was not relatively pro-poor. In rural areas, however, growth was relatively pro-poor as the modest amount of growth that did take place was concentrated among the poorest. In rural areas the rate of growth among the poor averaged 0.5% per year, versus mean growth of 0.3% for rural areas overall. This mixed picture for rural and urban areas means that for the nation as a whole the mean growth rate for those who were poor in 1991/92 is 0.6%, just below the growth rate in the mean of 0.7%.

Another way to view the curves is to recognize that a GIC that is upward sloping implies that the poor benefit from growth less than the non-poor, leading to an increase in inequality. The curves for Tanzania show that urban areas, which experienced the greatest gains, also saw increases in inequality.

It should be noted that given the size of the confidence intervals on the curves, small differences between growth rates shown on the curve are not statistically significant. Additionally, for rural areas, other urban areas, and the nation as a whole, we cannot reject the hypothesis that the curves are flat, i.e. that the impact of growth is evenly distributed. The greater rate of growth for non-poor households in urban areas, however, is statistically significant.

In summary, the curves show that growth has had widely different distributional impacts by sector. As the large majority of people live in rural areas, the national growth incidence curve resembles the growth incidence curve for rural areas, showing equally distributed, limited, growth with some relative gains for the poorest.