The role-players in the South African (SA) agricultural sector have in recent years been increasingly exposed to international agricultural markets and this can have an important impact on them because (1) they are generally price-takers in world markets and (2) the rate of change in agriculture, and the uncertainty arising from it, appears to be accelerating in the global context (Boehlje, et. al., 2001). Therefore, it is critical that role players in the SA agricultural sector, including agribusinesses, farmers and government, are able to anticipate future directions of world markets (Meyer, 2002). A system of econometric models that could be used for scenario planning and improving business strategy and policy development would facilitate this. A relatively large-scale, multi-sector commodity level econometric simulation model, based on a method of econometric modelling developed and is successfully used by the Food and Agricultural Policy Research Institute (FAPRI) at the University of Missouri, has been developed to describe various agricultural subsectors in South Africa (Meyer, 2006). It is currently housed at the Bureau for Food and Agricultural Policy (BFAP) at the University of Pretoria. The model has a total of 126 equations representing eight crops, five livestock and five dairy commodities, as well as wine, sugar, potatoes and lastly biofuels, which together are referred to as the BFAP Sector Model. The BFAP Sector Model is frequently used for generating baseline projections and conducting a wide range of scenario analysis. The original or Old Broiler Model, which forms part of the BFAP Sector Model, was constructed in 2003 when the first version of the BFAP Sector Model was developed. Over the past view years there have been a number of occasions where the stability of the broiler model seemed to be questionable, especially when more “drastic scenarios”, for example the impact of Avian Influence on the South African broiler industry, were analysed. The original version of the broiler model was not statistically estimated but synthetically constructed, mainly based on sound micro and macro economic principles and theory. The main objective of this dissertation is, therefore, to attempt the construction of an updated broiler model that has improved abilities to generate baseline projections and scenario analysis that capture salient features of the South African broiler market within the BFAP sector modelling framework. The performance of the updated model is compared to the original broiler model to determine whether the new model is performing better. The New Broiler Model is a partial equilibrium model built using new production, consumption, trade and price data as well as a new feed inclusion index. The ordinary least squares (OLS) method was used to estimate the individual equations and their statistical significance was evaluated using typical statistical tests for individual regressions using OLS estimators. These initial tests indicated that the individual equations fit the historical data well, but the per capita consumption and ex abattoir price equations were found to be wanting in terms of their economic significance and especially their ability to generate reliable projections into the future. Consequently the equations were adjusted, thus becoming synthetic equations. The dynamic system structure that resulted from the combination of the individual equations makes it necessary to examine the performance of the overall model when linked to the rest of the BFAP Sector Model. This was done by comparing the results of the Old and New Broiler Models using the baseline projections and performance when dealing with scenario type questions. The elasticities and the results for the scenario analyses indicate that the New Broiler Model is generally less sensitive to changes in exogenous factors than the Old Broiler Model. The change in closure of the model, from making use the price equilibrator approach to an approach where a net import identity is used, is the most significant change that was made to the model and has introduced a lot more stability in the broiler model and also the BFAP Sector Model. Although the enhanced stability is useful within the context of the total BFAP sector model, the sensitivity that is lost in the New Broiler Model could lead to the underestimation of the impacts of exogenous factors on the broiler industry. To summarise, this study was conducted for an industry that is characterised by strong and consistent increasing trends in production and consumption in the presence of a constantly decreasing real broiler price. These strong trends influence any form of statistical estimation procedure that is undertaken. To certain degree one can argue, that the key objective of this study, namely to improve the performance and stability of the broiler model within the BFAP sector model was achieved. However, the advantages over the original broiler model are not as clear as was originally anticipated and there is still substantial work that can be done to improve the model. Most of these potential enhancements do, however, require the buy in of various role-players in the broiler industry together with more detailed data sets than those that are currently available. Copyright / Dissertation (MSc(Agric))--University of Pretoria, 2010. / Agricultural Economics, Extension and Rural Development / unrestricted

Thesis (MSc. (Agricultural Economics)) -- University of Limpopo, 2016 / The broiler industry in South Africa consists of both small-scale and commercial poultry farmers. It provides the cheapest source of protein, absorbs labour and contributes massively to the agricultural sector. Broiler industry absorbs labour from the labour market, both skilled and unskilled; therefore it is a good source of employment. The specific objectives of the study included determining factors influencing productivity among smallholder broiler producers in Mopani District using Stochastic Frontier Production Function and technical efficiency analysis. The profitability of smallholder broiler production in the study area was also estimated using the Gross Margin Analysis. Furthermore, determinants of market participation among smallholder broiler producers in the study area were analysed using the Logit model. The Stochastic Frontier Production Function results revealed a positive relationship between the productivity of the farmers in their broiler production and labour, feeds, stock size and vaccines. The results also showed that feeds was significant at 1% while stock size was significant at 10% level. The technical efficiency results indicated that smallholder broiler farmers in Mopani District could save an average of 23.4 % in production costs and realize a maximum cost saving of 95.8% in production costs. The Gross Margin Analysis revealed that the cost of feeds were the highest incurred, taking up 70.61% of the total costs of production and the second highest being cost of stock comprising of 15.11% of the total production costs. The Logit results on the determinants of market participation showed that household size, income received per month, experience, land size, access to market information, distance to the market, profitability and land ownership are statistically significant in determining participation in the market. Based on the findings from the study, it is recommended that linkages between the formal markets and the smallholder farmers be established for farmers not participating in the market. Farmers who making profit and have more experience in broiler production should be provided with a platform to grow into commercial farming. This could be through subsidies or provision of other incentives that are key to enhancing expansion, such as land and funds.