This article continues with the theme of inclusive growth and structural economic transformation that we have treated in our three previous articles published in the Standard Newspaper, We started with the broader strategic analysis of the possible pathways towards this overarching development goal, first at the African continental level, then at the specific level of the Gambia and finally at the more practical level regarding strategies, policies and programmes that can facilitate the attainment of inclusive growth, development and economic transformation objectives. This particular article constitutes the last in this series and it will focus on how inequalities are measured and how this could be applied for strengthening the planning processes and programmes for addressing inequalities for the attainment of inclusive growth and development.
I would like to acknowledge at the outset that the subject matter under review here might appear overly technical for a light newspaper reading, but we have strived to simply as much as possible the presentation of the various measures of inequalities in order to facilitate full appreciation by the non-technical readers of their significance. In our previous articles, we have reiterated over and over the critical importance of high rates of broad-based economic growth and transformation for all societies and countries in order to ensure their sustainability itself and broadly shared prosperity for the populations. All this guarantees social cohesion, peace and stability in societies. Nelson Mandela succinctly captured this important point as follows: “Poverty and material inequality are enemies of lasting peace and stability”. In the rest of the article, we first start with a brief and graphical presentation on the state of inequalities in Africa before proceeding to the presentation and analysis of the various measures of inequalities and how they can be applied to the strengthening of planning and programming processes for inclusive growth and development in our countries.
Broad picture on inequalities in Africa
In this section we present graphically the state of inequalities in Africa as represented by the Gini Coefficient followed by a brief disaggregated analysis focusing mainly on the continent’s groups of countries and/or sub-regions. The graph in the next page has been extracted from a book co-edited by a former UNDP colleague of mine, Dr. Ayodele Odusola. Our starting point is not on a very rosy note, owing to the fact that currently, Africa is the second most unequal region globally, after the Latin America and the Caribbean region.
As we noted in our previous article, on average the Gini Coefficient for African countries as a whole is 0.55 (remember Gini Coefficient is measured between 0, meaning perfect equality, and 1, meaning very very high inequality). But it is essential to note that the actual income distribution in the continent differs from country to country and from sub-region to sub-region, influenced by both historical factors as well as the postures taken by Governments towards addressing inequalities and the specific policies pursued by them. As is the case with all averages, they mask the disaggregated picture. The Gambia’s Gini Coefficient is currently estimated at 0.36, which is well below the average for Africa.
The graph in the next page shows the sub-regional and country patterns of income inequality in Africa. The map indicates that the majority of the African countries with high and rising inequalities are principally located in Southern and Central Africa, characterized by capital-intensive mining, oil and gas sectors as well as historical settler societies with large-scale agricultural production landholdings, especially in the southern African countries regarding the latter. On the other hand, countries with relatively low- or declining-income inequalities are found mainly in West Africa, with predominantly small-holder agricultural sectors, in which productivity enhancement policies were benefitting the small-scale farmers. However, a few countries like Rwanda, Tanzania, Mauritius, Seychelles, Senegal, Cote D’Ivoire and Botswana have taken deliberate strategic and policy stances vis-à-vis inclusive growth and development, which incorporates strategies for both promoting rapid economic growth, reducing poverty and inequalities. Their experience provides valuable lessons for other African countries.
Measures of inequalities
How are inequalities measured? And what does the battery of statistics assembled on them over the past years for both in-country situations and across countries and regions precisely tell us about how they could be used in planning processes The literature on the various
measurements of inequalities have grown tremendously over the past two decades in particular, with some of the discussions conducted very high technical levels (Alun Thomas, IMF, 2012; Ayodele Odusola et al 2017). For this article, we shall strive to simplify them. In this regard, let me start by noting that measures are divided into two main categories: economic inequality, that uses shares of household income and/or consumption controlled by specific groups on one hand; and on the other, non-economic or broader measures such as access to health, education and nutrition as well as spatial or regional disparities. These two measures could then be used to assess disparities between countries or regions or between social groups or gender groups within countries. Spacial inequalities are used to measure disparities between regions, e.g. rural and urban or within the regions themselves e.g. between different urban areas.
The most commonly used indicator of economic inequality is the Gini Coefficient. As a rule, the Gini-Coefficient ranges from 0 (meaning perfect equality or perfect equitable distribution of income or consumption among all the individuals or social groups) to 1 or 100%(that implies total inequality or one (1) person having total control over all the income or consumption of a country or region). Therefore, the closer the Gini Coefficient is to 1 or 100, the more inequitable is income distribution and vice versa. In the early 2000s, the estimated Gini-Coefficient for Africa as a whole was around .60 or 60%, which implied significant unequal income distribution in a high number of the countries. But with a combination of pro-poor growth policies and inequality reducing measures, some countries have succeeded in reducing their Gini coefficients. For instance, Rwanda’s Gini Co-efficient was reduced from .522 in 2005/2006 to 0.448 in 2013/14 and several hundred thousands of people were pulled out of the poverty category. The study by Ayodele et al indicates that between 1991 and 2011, 17 other African countries had
managed to reduce somewhat their degree of income inequality. On the other hand, persisting inequalities in 7 outlier countries, mainly in Southern and Central Africa have continued to drive the relatively high Gini-Coefficients in the continent.
The other commonly used measure of economic inequality is a more direct one: it uses the share of income or consumption controlled by say the top 10% or top 20% of the population compared to the bottom 40%, for instance. This is referred to as the “Palma ratio”. If the richest 10% in a country earns between them 50% of the national income and the poorest 40% earn 10% of the national income, the Palma ration will be arrived at by dividing 0.5 by 0.1, which is 5. For instance, the highly publicized 2016 Report of OXFARM International on inequalities indicated that the top 10% of the world’s wealthiest population was controlling about 50% of total global income, and suggested that this was also on the increase, as shown in a subsequent report it produced in 2017.
The non-economic measures of inequality are the following: health inequalities, whose indicators are life expectancy, child mortality and nutrition; education inequalities, whose indicators are average years of schooling completed by the population aged 15 years and above, proportion of children attending or completing primary school by income or social group and proportion of population attending secondary school by income or social group; as well as inequalities in access to sanitation and portable water. This normally belongs to the multi-dimensional measures of both poverty, lack of capabilities and inequalities. The UNDP Human Development Index (HDI) normally captures very well the state of inequalities in a country in this regard. The Gambia’s HDI belongs to the lowest rungs of the global UNDP HDI ranking.
The extent of inequalities among the gender groups also constitutes a key determinant of inclusivity of growth in any society. This issue has been the focus of extensive analysis and activism over the past several decades and the push for broader changes in development policies and programmes to address it. The close interrelationship between the promotion of empowerment of women and gender equity on one hand and changes in inequalities in a society on the other, is underscored by the by now popular dictum that no society can expect to realize its full growth and development potential if it constrains over 50% of its population, constituted by females, from participating maximally in its mainstream political, economic and social activities. There is consensus that while measurable progress toward gender equity and empowerment of women across the world has been made, much more still needs to be done. In a bid to extend the coverage and relevance of its Human Development concept, framework and indices, UNDP came up with various Gender Development Indices as well as the notion of Gender disaggregated GDP, budget and employment data. The space available in this article is not enough for a more comprehensive discussion of all these indicators and indices.
In recent years, there has also been a renewed focus on the imperative for narrowing spatial disparities, mainly through addressing rural-urban disparities as key to ensuring inclusive and balanced growth and development. Efforts in this area include promotion of more transformational initiatives in the agricultural sector, agro – processing and agribusiness, stimulation of off-farm activities, rural infrastructure development as well as introduction of green energy initiatives. Some countries like Rwanda have adopted more aggressive stances in this connection through creation of secondary cities, with the objective of dramatically reducing the rural-urban gaps and introduction of green sources of energy, notably small hydro-dams, solar and wind farms Such initiatives also provide important opportunities for greening the entire development and transformative processes in the countries.
Undoubtedly, adequate productive employment creation is one of the most effective avenues for poverty reduction and attaining inclusive growth. This is even so when significant job creation takes place in sectors where women, youth and poor groups are actively participating and benefitting from the activities. Mapping unemployment rates among the different social groups and regions could also provide a sound basis for well targeted interventions for reducing inequalities and promoting inclusive growth and structural economic transformation.
In conclusion, several empirical studies clearly demonstrate that high levels of inequality can seriously impede sustainable growth. This occurs through the impact of inequality on the quality of economic growth and its dampening effect on aggregate demand, that prevents the pace of economic growth from reaching the full potentials of an economy. Un-checked levels of inequality also constrain the attainment of poverty reduction objectives. Economic and non-economic inequalities determine to a large extent the responsiveness of poverty reduction efforts to income growth through the exclusion of poor people from participating in, and benefiting from, the fruits of growth.
Persisting inequalities also impact adversely on social mobility i.e. the ability of one generation to leave better lives than their parents. “The degree of mobility within a country is an indicator of the distribution of access to opportunities for building human capabilities, and of the extent to which people can move ahead based on their abilities and efforts”. Ultimately, persisting high inequalities raise the risks of civil strife, violent extremism and political instability in countries.
Comprehending and precise measurements of the characteristics and incidence of various inequalities could help policy makers and other stakeholders in countries effectively address them. That is what this article is about.