Poverty profiles are a useful way of summarizing information on the levels of poverty and the characteristics of the poor in a society. They also provide us with important clues to the underlying determinants of poverty. However, important as they are, poverty profiles are limited by the bivariate nature of their informational content.
The bivariate associations typical in a poverty profile can sometimes be misleading; they beg the obvious question of the effect of a particular variable conditional on the other potential determinants. While there may be certain contexts where unconditional poverty profiles are relevant to a policy decision (see Ravallion 1996), often one would be interested in the “conditional” poverty effects of proposed policy interventions. It is not surprising therefore that empirical poverty assessments in recent years have seen a number of attempts at going beyond the poverty profile tabulations to engage in a multivariate analysis of living standards and poverty. This study for Egypt has a similar motivation.
For Egypt, while there has been some work on a descriptive analysis of the characteristics of the poor, to our knowledge, there is no precursor to an empirical modeling of the determinants of poverty using nationally representative data. To a large extent, this has been due to the nonavailability of unit-record data from the Household Income, Expenditure and Consumption Survey (HIECS), the primary source of data on living standards in Egypt. However, this constraint has been recently alleviated with the 1997 Egypt Integrated Household Survey (EIHS). Using the EIHS data, it is now possible to conduct a household-level multivariate analysis of living standards. The EIHS, being an integrated, multimodule survey, also offers the potential of a richer analysis of this issue than may have been possible from other data sources.
In this paper, we have sought to extend the descriptive analysis of the Egypt poverty profile presented in Datt, Jolliffe, and Sharma (1998) by modeling the determinants of poverty, using data from the 1997 Egypt Integrated Household Survey. Our approach to modeling the determinants of poverty is to model the determinants of the individual welfare indicator, namely, consumption per person, used to define poverty measures. Model predictions for the individual welfare indicator have direct implications for predicted levels of poverty.
We estimate separate governorate-level fixed effect models for the urban and rural sectors. In our preferred model for the urban sector, we include interaction effects between schooling characteristics, measures of unemployment, and landownership. In our preferred rural model, we include interaction effects between schooling characteristics, measures of unemployment, landownership, and community characteristics including irrigation, distance to railroad, and indices of social and
economic capital. We use both the urban and rural regression models to predict changes in consumption levels and hence poverty from simulated policy changes.
A key conclusion of our study has to do with the important instrumental role of education in alleviating poverty in Egypt. Increasing average years of schooling, as well as improving the level of parents education, is indicated to have large impacts on average living standards and poverty levels. Our simulation results suggest that a two-year increase in household average school attainment would result in an 18 percent decline in the number of individuals living in poverty. A two-year increase in school attainment would also result in a reduction in the depth of poverty (as measured by the poverty gap index) and the severity of poverty (as measured by the squared poverty gap index) of 22 and 25 percent, respectively. We find that the estimated beneficial effect of improved school attainment is robust whether we consider the rural or urban sector, Upper or Lower Egypt, and regardless of which poverty index we examine.
While the beneficial effects of improvements in school attainment are significantly larger than the predicted effects from any other policy changes, we do find fairly large and positive effects from improvements to irrigation and reducing the number of unemployed individuals. Improved irrigation is estimated to reduce the national incidence of poverty by 6 percent, while reducing unemployment levels is estimated to reduce the incidence of poverty by 2 to 3 percent.
It is in the nature of these poverty simulations that the results have a reduced form character. The observed effects are nevertheless important, even if the particular pathways are difficult to identify. In interpreting the importance of these results for poverty reduction, one should also not assume these effects to be instantaneous, even though they are estimated from static models. Educational investments, for instance, have inherently long gestation; what our results indicate is that they can be powerful instruments for long-term poverty reduction.