Regional income inequality in Egypt: evolution and implications for Sustainable Development Goal 10

ABSTRACT

Research on income inequality in developing economies has scarcely looked at the regional dimension. This is important, as progress in reducing income inequality at national level can only be partially successful if a country consists of very unequal regions alongside relatively equal ones. Using newly assembled Luxembourg Income Study data, we study the evolution of income inequality within Egyptian regions during 1999–2015. The analysis offers three findings. First, income inequality has generally increased. Second, regional differences in income inequality tended to decrease, but less unequal regions are converging to similar levels of inequality of more unequal regions. Third, there has been a decrease in the income share of the bottom 40% and an increase in the proportion of people living below 50% of median income. Hence, geographically diffused progress on the first two targets of SDG 10 depends on reversing these trends.

KEYWORDS:

• Income distribution
• convergence
• regional disparities
• SDG goal 10
• Sustainable Development Goals
• inequality
• decomposition

JEL CLASSIFICATION:

• O15
• D6
• D63
• D3
• D31
• R1

Disclosure statement

No potential conflict of interest was reported by the author(s).

Supplementary material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/13600818.2023.2225429

Notes

1 On the social consequences of income inequality, see Klasen (2008), Wilkinson and Pickett (2009), Dabla-Norris et al. (2015), Easterbrook (2021) and Hirschman and Rothschild (1973). On its relation to human development, see Stewart (2019) and United Nations Development Programme (UNDP) (2019), especially chapter 2. On its economic effects, see Ostry et al. (2014), Easterly (2007), and Thorbecke and Charumilind (2002). This literature has raised the question of whether equity and efficiency are independent objectives, or whether there could be an efficiency gain from greater equality (e.g. see Klasen, 2008). An implication of this body of research is that there may be an optimal level of income inequality, beyond which we see a threat to existing socioeconomic achievements. However, the question of what such an optimal level might be is an open one.

2 See Peters and Jetten (2023) for a survey. Easterbrook (2021) assesses how individuals’ experience of inequality may affect their wellbeing with reference to developing countries contexts.

3 For example, Deaton (2004) and Canning (2012) examined the evolution of health, showing convergence in life expectancy across countries. Prados de la Escosura (2015) looked at convergence in human development in the long run, showing that there has been an overall widening of the human development gap since 1870, and partial convergence among OECD countries and the rest over the period 1913–70. See Asadullah and Savoia (2018) for a brief survey.

4 Regional studies typically look at inequality between regions: territorial differences in average income levels across regions. This study instead looks at inequality within regions (how income is distributed in a given region). The former is important to achieving territorially widespread improvements in living standards across the nation, as the empirical consensus is that higher growth often benefits all parts of the distribution, including the bottom (e.g. Dollar et al., 2016). However, it is also by studying how income is distributed within such territories that we can understand if the gains from economic growth are widely shared.

5 The evolution of wage inequality across sectors and demographic groups in individual MENA countries like Egypt has been thoroughly documented and analysed (e.g. Said, 2015; Said et al., 2019).

6 One way to reconcile this apparent paradox is on technical grounds. There may be substantial discrepancies between the way income inequality is measured and its true extent, because existing inequality statistics underestimate it. One argument is that income inequality estimates are drawn from household surveys fraught with various limitations, especially with respect to the ‘true income’ of top income earners (Achcar, 2020). Hlasny and Verme (2018) addressed this issue. After correcting for problems such as the number of non-respondents in household surveys, the estimated inequality was found to be higher by a minimum of 1.1 to a maximum of 4.1% points. Similarly, Van der Weide et al. (2018) argued that top income shares in Egypt are highly underestimated. Using house prices to re-estimate the top tail of the income distribution, the revised Gini index was found to be 25% higher than the value reported in the World Bank’s statistics.

7 SDG Goal 10 aims to reduce inequality within and among countries. The first two targets are clearly related to aspects of income inequality. In particular, Target 1.1 aims to ‘progressively achieve and sustain income growth of the bottom 40% of the population at a rate higher than the national average’. The idea is to achieve ‘shared prosperity’, i.e. a form of growth with equity, where progress is measured by how gains from economic growth are shared with the poorest members of society over time. Target 1.2 aims to ‘empower and promote the social, economic and political inclusion of all, irrespective of age, sex, disability, race, ethnicity, origin, religion or economic or other status’. The idea here is to address social inclusion, relative poverty and inequality. Refer to https://sustainabledevelopment.un.org/sdg10. See Lang and Lingnau (2015) for a discussion of inequality in the SDGs and an assessment of its measurement.

8 See Luxembourg Income Study (LIS) (2019). On the ERF-LIS dataset, see https://www.lisdatacenter.org/our-data/erf-lis-database/.

9 We bottom-code by setting all values less than zero to zero, and top-code by setting all values greater than ten times the median value to ten times the median value. In Egyptian data, however, using top and bottom coding procedures makes little difference. No significant change occurs when replicating the results after removing top-bottom procedures on income data. The results, not reported here, are available on request.

10 As we are using an equivalised income variable, we apply the household weight multiplied by the number of household members, to weight by person (hpopwgt*nhhmem).

11 Empirically, we show that inequality within regions is relevant. Section A4 in the appendix decomposes income inequality by population subgroups based on their geographical location. The results reveal that within-region inequality explains most of the overall income inequality. For example, according to the Theil index decomposition in 2015, the contribution of the within component (or intra-regional inequality) amounts to 90.8% of the total, whereas the between component (or inter-regional inequality) accounts for the remaining 9.2%. The within component in 1999 was lower, but still very high, at 79.3%.

12 Compare also regional measures with income inequality measures for Egypt at national level. We report them in the appendix, Table A5.1. This highlights that income inequality within regions may be very different from national income inequality. The national level picture suggests that income inequality has been relatively low and stable during 1999–2025, in stark contrast with the large variation in inequality at regional level.

13 Others have emphasised a different statistical notion of convergence (e.g. Quah, 1993): σ-convergence, which looks at whether the cross-sectional dispersion across countries is decreasing, and for which β-convergence is a necessary, but not sufficient, condition. See Sala-I-Martin (1996), for a comparison of the two notions.

14 Shenker (2016) provides an account of how the Arab Spring in Egypt arose also as a reaction to the iniquities of neoliberal policies and how this was misread abroad by some as a cry for more of it.

15 Inequality regressions using including fixed effects suggest that time-invariant regional characteristics, such as historical economic structure, may explain inequality persistence and change. We have produced preliminary evidence, based on conditional convergence estimates, showing this in the appendix. Further systematic econometric analysis is needed to shed light on which region-specific characteristics matter (see Durlauf et al., 2009, on the methodological challenges).

16 Cowell, F. (2000). Measurement of Inequality, in A. Atkinson and F. Bourguignon (eds.), Handbook of Income Distribution, Elsevier Science: Amsterdam. An inequality index can be decomposed only if total inequality is expressed as an aggregate function of each inequality’s subgroup, mean income, and population. Inequality indices additively decomposable by population subgroups belong to the family of Generalized Entropy Indices GE(a), with (a) indicating income difference sensitivity parameter: GE(0) is the mean logarithmic deviation (MLD), GE(1) is the Theil index, and GE(2) is half the square of the coefficient of variation.

17 Verme et al. (2014). Inside inequality in the Arab Republic of Egypt: Facts and perceptions across people, time, and space. The World Bank. https://doi.org/10.1596/978-1-4648–0198–3.