Inequality refers to disparities between individuals (vertical inequalities) or groups (horizontal inequalities) in areas such as income, wealth, education, health, nutrition, space, politics and social identity (Rohwerder 2016). Intersecting inequalities occur when people face inequality in multiple, overlapping, spheres of their lives. Inequality is most commonly understood as either inequality of outcomes (differences in what people achieve in life, for example, level of income) or inequality of opportunities (differences in people’s background or circumstances that condition what they are able to achieve).
Measuring inequality can be complex, because of multiple understandings of what inequality is and varying approaches to measuring it. The common approaches focus on measures of financial inequality (consumption, income or wealth) (Rohwerder 2016). Critics argue that monetary measures fail to capture inequalities beyond material standards of living, and suggest that measuring living standards is key. Approaches to this include indicators for the distribution of education and health although these are less developed than income-based measures of inequality (Peterson, 2014).
The body of evidence around inequality in Rwanda is mixed, both in terms of scope and coverage and quality. It is also characterised by competing narratives about whether or not inequality is declining or not (Behuria and Goodfellow 2016: 3). This reflects, in part, the inherently complex nature of inequality, how it is measured, and different approaches to gathering data.
This review identifies and reviews the evidence on inequalities in Rwanda. Undertaken in six days, it draws primarily on national Rwandan datasets and smaller-scale case studies from
academic research. This study focuses primarily on quantitative datasets and sources, supplemented by some qualitative research. A related report by Carter (2018) which examines the relationship between inequality, exclusion and poverty in Rwanda, also provides insights from key qualitative studies.
Key findings include:
- There is a limited body of disaggregated data on inequalities in Rwanda (Dawson 2018). The key quantitative datasets that illuminate inequality in Rwanda have been collected by the National Institute of Statistics of Rwanda (NISR). These are based on large-scale household surveys carried out every few years and contain a basic level of disaggregation. Although NISR data has been described by Ansoms et al (2018) as reliable, cautions are raised over sole reliance on data from large-scale household surveys since macro-level data can obscure the lived experiences of vulnerable groups (including the poorest, women, historically marginalised people and the disabled).
- There is also a significant body of smaller scale, in-depth research carried out in various geographic locations and on a range of development topics. Whilst these are not intended to be nationally representative, they can add important depth of understanding to the national picture of inequality.
- Commonly used standard indicators to measure poverty and inequality don’t always resonate with experiences of poverty and wellbeing of local communities (including women and historically marginalised people), particularly in rural areas (Dawson 2018). It has been proposed that newer measures are needed to capture their lived experiences (Dawson 2018; Abbott and Malunda 2014). There is growing interest in measures that capture subjective dimensions of wellbeing.
- Existing evidence shows that inequality measured by financial indicators (income/consumption) rose in Rwanda between 2000 and 2005/06, but declined from 2005/06 until 2013/14. Despite this, inequality in Rwanda remains the highest in East Africa measured by a range of indicators (Gini coefficient, Palma ratio).
- Inequality measured by access to basic services such as health, education, water, sanitation and electricity shows improvements over the past two decades. Health outcomes and access to health have improved for many groups, although rural and regional disparities remain. Access to healthcare is also determined by wealth.
- Enrolment in primary and secondary education has grown and gender gaps narrowed – in some cases, girls’ enrolment is higher than boys. Urban-rural divides appeared in both attendance and completion rates. Notable disparities were also identified between the lowest and highest quintiles. Enrolment and completion rates for higher education decline across all groups.
- Inequalities in access to the labour market were also identified, with variation across contexts. For example, youth unemployment is an urban phenomenon, whilst gendered inequalities strongly shaped the rural labour market.
- Other factors that affect economic empowerment include distribution of land and financial assets. These are both shaped by gendered inequalities and vary by location (urban/rural) and region as well as wealth quintile.
- There have been improvements in access to utilities over the past two decades. The survey also found that the lowest quintile made particular significant gains in access to both water and sanitation between 2011 and 2013/14, whilst the wealthiest quintile benefitted the most from increased access to electricity.
This study identified some evidence gaps:
- There is a need for more detailed disaggregated data. For example, many of the existing large-scale datasets do not easily illuminate intersecting inequalities.
- There is very limited empirical work attempting to understand the structural causes of inequality in Rwanda, which has resulted in a poor understanding of inequality trends (Finnoff 2015: 209).
- The quantitative data often neglects people with disabilities, migrants/ refugees, the poorest and historically marginalised people. There is also limited data on the social inequalities experienced by different ethnic groups (Hutu, Tutsi, Twa). This is complicated by the challenges in speaking about ethnicity in Rwanda.
- There is a need for research that takes into account the heterogeneity of the Rwandan poor, in order to better understand rural poverty and inequality (Ansoms and McKay 2010).
- Although there exists a body of evidence comparing Rwanda’s progress on inequality with its East African neighbours, the data this draws on is dependent on the quality of national data from each country. SID (2016) suggests this needs to be strengthened