ABSTRACT
A number of analysts have used indices based on ownership of consumer durable goods and assets and access to public services as an alternative measure of economic well-being to household consumption.2 Items such as a radio, television, refrigerator, bicycle, motorcycle, and car are normally chosen as the consumer durables, while dwelling characteristics such as building materials, the quality of flooring and roofing, main source of drinking water, type of toilet facilities, etc. are used to measure access to services. The methodology of principal components is a common method for providing the weights used to aggregate these indicators into a single asset index. The rank correlation between per capita expenditures and these types of asset indices is typically greater than 0.5, with the correlation higher for countries outside SSA. For example, Filmer and Scott (2008) find that the correlation for Brazil is 0.64, while the correlation for Ghana and Zambia is about 0.4. The lower correlation among SSA countries is likely related to the fact that a large subset of low-income households do not own the consumer durables used in the index while access to piped water and sanitation is very low, especially in rural areas. Booysen et al. (2008) emphasize that the limited discrimination ability at the lower end of the income scale makes asset indices a poor tool for analyzing the extremely poor. This section aims to enrich our understanding on the inclusiveness of growth in the region using seven case studies – from Cameroon, Ghana, Mozambique, Rwanda, Tanzania, Uganda, and Zambia. The sample choice is driven by data availability and is not fully representative of SSA countries in general – there are no post-conflict or fragile states, no large oil exporters (Cameroon is a marginal net exporter), and only one francophone country is included. With the exception of Cameroon and Zambia, the other four countries all enjoyed average per capita income growth of more than 2.25 percent during 1995-2010 (among the region’s faster growing economies). For the sample of countries, data on access to consumer durables and access to publicly provided services is provided through the Afrobarometer surveys supplemented by the household budget surveys.3 Both types of surveys indicate that ownership of consumer durables has increased extremely rapidly over the past decade in all countries. If we weight ownership of radios, televisions, and cars equally, the annual change in consumer durables varies between no change in Zambia to an increase of 2.2 percent per annum in Ghana. Except for Ghana, the changes are broadly inversely related to initial ownership shares. Cameroon has the highest television and motor vehicle ownership share with a 0.4 percent annual increase in ownership shares while Mozambique had the lowest share in 2002 and the highest annual increase (1.5 percent). Access to publicly provided services has also become much more widespread over time across counties (Figures 1.1 and 1.2).4 Ghana and Cameroon have the highest levels of access to the electricity grid, piped water and sewage system, consistent with their higher levels of GDP per capita. Moreover, Ghana has also demonstrated the fastest increase in coverage over this period with Mozambique
a close second. Zambia has shown a sharp improvement in access to services between 2004 and 2010. The increase in access to publicly-provided goods is buttressed by the proportion of respondents who indicate that they seldom go without food, water, medical care, and cooking fuel. Except for access to cooking fuel in Uganda, all countries show a rising share over time of households that report seldom going without these basis needs, with Ghana remaining above the other countries in terms of levels. Based on the demand for durables, various housing characteristics, children’s health status, and family conditions, Young (2010) has argued that the growth
rate of per capita consumption among SSA countries was about 3.5 percent per annum over the 15 year period through 2005/06, which is three times the average estimate from national income product accounts (NIPA) data. His analysis is based on the relationship between these factors and educational attainment, under the assumption that educational attainment is a good proxy for family income (as supported by the Mincer regressions, below). He shows that the elasticity of education with respect to owning a car is positive and significant, and is much higher than the elasticity with respect to owning a radio. Using these relationships between educational attainment and the identified characteristics, combined with an assumption about the rate of return to education, he derives consumption growth estimates.5 As a counter to Young’s argument, Harttgen et al. (2011) argue that the relationship between asset growth and per capita income growth is very weak especially among non-African countries where concerns about NIPA statistics are less serious. They conclude that inferring income growth from changes in asset indices is not very robust.
