Abstract:
Cotton used to be a thriving agricultural commodity in South Africa (SA), with dryland production being the backbone of the industry. In the 1980s and early 1990s, the total cotton area covered over 200 thousand hectares but has since decreased dramatically, to less than 10 thousand hectares post-2000. Fluctuating and decreased cotton production has been the South African cotton industry’s biggest challenge. The cotton industry’s demise has been to the detriment of SA’s economy due to the loss of the associated employment and value addition in the production, processing, distribution and trade stages of the value chain. To revive cotton production, sustain livelihoods through job creation, and protect and sustain the domestic cotton industry, several interventions (under the auspice of the Sustainable Cotton Cluster) have been implemented in the sector over the past decade.
The main objective of this study is to determine the relative contributions of international market dynamics and local value chain interventions to variations in cotton area. First Engle-Granger (1987) cointegration procedures were used to analyse price transmission between the local and global cotton markets. Empirical findings confirm a long-run relationship between the two markets; thus, the local lint price is determined by the international cotton price (A-Index). Also, employing the same procedures to estimate domestic producer prices for seed cotton, indicated a cointegration relationship between producer prices, seedcotton supply and the local lint price.
The Autoregressive-Distributed Lag (ARDL) cointegration approach was applied to determine the drivers of cotton area in SA. Prices were analysed as a component of revenue in the empirical analysis. Empirical findings indicate that cotton area is more responsive to domestic procurement volumes, in line with typical contracted production practices, but producer revenue was also an important determinant. Domestic procurement in this context refers to the volume of locally produced lint, which is processed by local spinners. It is important to note that domestic procurement is an imperfect proxy for the cotton cluster, but the best alternative given the lack of available data on annual commitments by the cluster. Also, exports are important and may well have been a driver of additional procurement of seedcotton by ginners as seedcotton is processed into lint either to sell in the local market to spinners or for export. As such, lint processing at the spinning level is used as a measure of local procurement, instead of seedcotton procurement by ginners since we cannot separate between seedcotton processing for the local market and export. Thus, the results of the study should be considered carefully given the limitations indicated above.
The results of the analysis suggest that cotton growers will increase the area planted to cotton in the current season, on basis of increased procurement in the previous season. In the same way, cotton area increases in response to higher cotton revenue. White maize is an important substitute crop in the long-run for irrigation areas while sunflower competes with dryland cotton, suggesting that farmers will consider shifting towards maize or sunflower in the next season if these provided better returns than cotton in previous seasons.
Empirical outcomes show that both industry interventions focused on local beneficiation (between 2014 and 2018) and improvements in revenue resulting from price gains were important drivers of increased cotton area, but local beneficiation was found to have the biggest impact on area. An important takeout from the study is that there is a need for a diversified market approach to utilise opportunities on a local and global scale (i.e when global prices are favourable). Additionally, there is potential for local byproduct value chains to boost the viability of the cotton industry.
