The ability of farmers to operate redistributed farms in a profitable and sustainable manner is crucial for both successful integration into agricultural value chains and sustainable production systems. The performance of redistributed farms is becoming increasingly important as the number of redistributed farms increases in light of correcting previous anomalies in land ownership in South Africa while ensuring continued food security. Although much has been done to assess the impact of land reform on macro variables, little has been done to unpack factors associated with the success of redistributed farms. Using a sample of 1956 redistributed farms across the nine provinces of South Africa, the current study employs an ordinary least square regression as well as a generalised logistic regression model to identify factors associated with the success (measured by net farm income and probability to operate at commercially viable scale) of the sampled farms. The results show that infrastructure, support (both technical and financial), and type of market used are significantly associated with the performance of redistributed farms. In addition, the results reveal disparities in performance across provinces and across gender categories. The study provides valuable insight to programme managers on the factors that needs to be enhanced in order to increase the odds of success for redistributed farms.
This paper quality adjusts machinery inputs for South African agriculture. It does this by treating different qualities of machinery as separate inputs. Thus, quality adjustment becomes quantity adjustment when there is sufficient disaggregation. This matters because many mechanical and chemical inputs have been transformed by technological progress. If this is not taken into account, the inputs are under-counted and total factor productivity (TFP) calculations are not accurate. Gandidzanwa and Liebenberg (2016) estimated the proportion machinery to implements and used this series to scale up the tractor series, instead of assuming fixed proportions. This study quality adjusts the machinery and implements input series by applying a greater level of disaggregation and by careful monitoring of model turnover. The number of models monitored was increased tenfold. Removing tractor improvements resulted in a price index that grew more slowly than the official index. Thus, the tractor stock value series is deflated less and by 2015 was 53% larger than in the official figures. The service flow entering the TFP calculations will be similarly increased, so there is less residual to be attributed to TFP growth. If all the inputs were equally undercounted, the TFP estimate would be double its true value.
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