THIS PAPER ADDRESSES THE QUESTION of poverty alleviation in subsistence fishing communities by formulating a method to quantify the impact of recent public sector efforts to provide subsistence fishers with access to the industry for the first time. Since the advent of democracy in 1994, the industry has come under the spotlight and undergone a substantive process of reform. This process has had implications for both the commercial and subsistence sectors, which are very differently managed. The commercial sector now leases rights from the state for a given period at a given cost, while the subsistence sector has been provided with access to resources via zones that the state has demarcated for subsistence use only. The process of redistributing rights in the industry has necessarily affected both the subsistence and commercial sectors. However, in this paper we are not concerned with the motives or the process of restructuring the industry. Rather, we focus exclusively on quantifying the povertyreducing effects of the recently created subsistence zones. Consequently, we treat these effects as an income grant, and therefore base the methodology on the Foster, Greer and Thorbecke (FGT) (1984) index of poverty measures. It should be noted that this technique has already been
successfully employed by Bhorat (1999) and Bhorat and Leibbrandt (1999) to analyse poverty alleviation and public expenditure in South Africa. The paper then extends the method beyond the realm of an income grant per se, and applies it within the context of a resource transfer that can be associated with quantities and values of various fisheries. Once this empirical relationship has been defined, we then extend the analysis to include post-resource transfer effects, specifically with
respect to poverty reduction. The method thus allows us to answer the following question: what is the impact of the transfer on income levels in the target population and who are the likely beneficiaries? The data on subsistence fishing communities is taken from the Census (1996) and October Household Survey (1995) (OHS95). Despite the explanatory power of the methodology, it is important to stress that this is a hypothetical exercise, and the results of the simulations in no way imply causality.