ERADICATING POVERTY IN FRAGILE STATES: PROSPECTS OF REACHING THE “HIGH-HANGING” FRUIT BY 2030

# _IFS BASE CASE_

The IFs Base Case is not a “business-as-usual” forecast, but rather the model's representation of the dynamic and often non-linear path that countries follow. The IFs model exhibits a few general behaviors in the Base Case that have important implications for the poverty forecasts that follow. First, inequality between states and globally decreases over time but, on average, inequality within developing countries increases (1.5 points between 2010 and 2030 on the 100-point Gini index and a further 1.5 points by 2050). This is an important trend, particularly salient to poverty forecasts over the next 30 years. Second, economic growth per capita among developing countries is fairly stable over the next 40 years. Other socio-economic patterns include decreasing population growth rates in the developed world, decreasing incidence of death attributed to AIDs worldwide, and increasing total aid to developing countries but decreasing aid as a percentage of developing countries’ GDP.

Household consumption is derived from the forecasted value for GDP and the forecasted propensity for a population to consume. Population is forecasted based on historical patterns of birthrates, death rates, and flow of net migrants. The forecast of distribution, represented by the Gini coefficient in this case, is based on the forecasted differences in income generation between two subsections of the population—skilled and unskilled households. The crude nature of the Gini forecasting method is a recognized shortcoming of the model and one that can be addressed by specifying Gini forecasts exogenously. A more detailed description of GDP and Gini forecast calculation within the model can be found in the Technical Appendix.

In terms of global poverty figures, the IFs Base Case is not as optimistic as some other baseline forecasts (Ravallion and Chandy et al.). In the IFs Base Case, poverty rate reduction slows gradually for developing countries in the aggregate and slows more sharply after 2020 in fragile states. There are a variety of explanations for this. One is a simple combination of aggregation and saturation effects. The countries with the highest poverty rates tend to be those with the highest population growth rates (such as the Democratic Republic of the Congo, Madagascar, and Malawi). Thus in a population-weighted representation of the fragile state group, while some countries eliminate poverty and, therefore, stop contributing to poverty reduction, the weight of higher poverty, more populous countries becomes greater and raises it. This would suggest that, rather than the global rate of poverty reduction continuing to accelerate as it has over the last 20 years, we will reach a turning point where the change in the rate actually decreases and global poverty reduction slows.

Other explanations for potentially slowing or stalling poverty rate reduction relate to broader characteristics of fragile states, especially again of those that have some of the highest current poverty rates. For instance, the three states mentioned above and many other fragile states have often run large trade deficits as a portion of GDP. The economic model in IFs does not allow such deficits to continue indefinitely, so, within the model, an increase in interest rates and/or reduction in government transfers will squeeze household consumption and limit poverty reduction. Further, the Base Case of IFs also anticipates that foreign aid from high-income countries will not keep up with economic growth in low-income countries, where aid receipts as a percentage of GDP rose quite steadily to about 8-10 percent over a long period of time but have recently begun to decline. We discuss these phenomena and their implications for poverty reduction in section 5.4.

# _CHANDY ET AL._

In their baseline poverty forecast, Chandy et al. (2013) use consumption growth rate forecasts from the Economic Intelligence Unit and assume unchanged income distribution for the forecast period. The authors’ four alternative forecasts are combinations of optimistic and pessimistic inequality and economic growth. Inequality is varied across the scenarios by altering the consumption shares between richest 10% and poorest 40%; i.e. increasing inequality is represented by a transfer of shares from the poor to the rich, and decreasing inequality in represented by a transfer of shares from the rich to the poor. Consumption shares are transferred either to or from the poor at a rate of 1⁄4 percentage point per year.

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