Nel and Rogerson (2016) reviewed Local Economic Development (LED) policy and practice in South Africa. They reported that results have been modest despite the significant support for nearly 20 years put into applied local economic development. They suggested that a potential over-focus on pro-poor local economic development at the expense of simultaneously working with the private sector on pro-market interventions, could be a stumbling block to the potential success of LED.
Mason (2018) stated that poverty is a multifaceted phenomenon and the condition of poverty often entails one or more of these realities: a lack of income (joblessness); a lack of preparedness (education); and a dependency on government services (welfare).
I asked if our research on enterprise dynamics that reported a wide range of regularities in the enterprise structures and dynamics of South African towns and municipalities (some of which have already been discussed here) could help to shed light on a question whether a pro-poor LED stance might be justified.
Two relationships are of particular interest here. Firstly, there is a direct correlation between the number of enterprises and employment opportunities; the more enterprises, the more employment. Secondly, an Enterprise Dependency Index (EDI) was developed and promoted as a wealth/poverty measure of South African towns (e.g. Toerien, 2014). It is defined as the:
EDI of town/municipality = (Population of town/municipality)/(Enterprises in town/municipality)
The EDI reflects how many persons are needed to ‘carry the average enterprise’ in towns. In other words, EDIs reflect the spending power of populations, the first of Mason’s realities mentioned above. Low EDIs indicate the ability to carry more enterprises (i.e. there is more wealth) and high EDIs reflect an inability to carry more enterprises (i.e. there is more poverty).
Rearranging the above equation yields:
Enterprises in town/municipality = (population of town/municipality)/(EDI of town/municipality)
This equation shows clearly that the number of enterprises in towns or municipalities, and hence employment opportunities, is determined by the size of their populations and the spending power (EDIs) of these populations.
But will differences in wealth/poverty be important to the enterprise structures and dynamics of South African towns?
The populations of South African towns range from very small to very large. Their population growth rates range from negative (rare) through two percent per annum (often) to four percent per annum (also rare). Small rural towns can typically have about 6 000 residents, medium rural towns about 20 000 residents and large rural towns about 40 000 residents. Recorded EDIs of South African towns range from about 30 to more than 600.
Based on the above, use is made of: EDIs of 40 and 300; town populations of 6 000, 20 000 and 40 000; population growth rates of 2 and 4 percent per annum; and a five-year time window to construct scenarios of the initial enterprise structures as well as the expected five-year development profiles of South African towns. The scenarios are presented in the following Table.
|Town size (population)||EDI||Initial enterprise number||Growth rate per annum||New enterprises added in five years|
The huge positive/negative impacts of wealth/poverty (or spending power) are readily seen. Rich towns, small or large, have many more enterprises and employment opportunities than poor towns, small or large. These differences are exacerbated over five years.
The consequences are clear. ‘Throwing’ money at the development of enterprises in poverty-stricken areas, e.g. into the development of cooperatives (Wessels, 2016), without consideration of the spending power of the markets these enterprises would be serving, is bound to result in ‘dreams turning into nightmares’. Because a prime purpose of LED is to create more employment in South Africa, having a pro-poor LED focus without consideration of markets and their spending powers, will have limited chances of success. The policy should be reconsidered because it achieves the opposite of what is intended.
Nel, E. and Rogerson, C.M. (2016) The contested trajectory of applied local economic development in South Africa. Local Economy 31(1–2): 109–123.
Mason, E.A. (2018) A.I. and Big Data could power a new war on poverty. New York Times. January 2, 2018.
Toerien, D. F. (2014). ŉ Eeu van orde in sakeondernemings in dorpe van die Oos-Kaapse Karoo. LitNet Akademies 11(1):330-371.
Wessels, J. (2016) Cooperatives: has the dream become a nightmare? Available at: http://www.econ3x3.org