Masters Degrees (Agricultural Economics)
Permanent URI for this collection
Browse
Browsing Masters Degrees (Agricultural Economics) by Subject "Agriculture -- Finance"
Now showing 1 - 1 of 1
Results Per Page
Sort Options
Item Open Access The evaluation of credit risk in structured finance lending transactions in agriculture(University of the Free State, 2010-11) Lubinda, Mwala; Willemse, B. J.; Potgieter, PieterEnglish: The study focuses on the evaluation of credit risk in Structured Finance lending transactions in agriculture. The secondary motivation of the study is that Structured Finance lending techniques have the potential of increasing access to credit for farmers, especially smallholder farmers, in the agricultural sectors of developing and emerging countries. Recent studies, in agriculture finance, done by the World Bank, Food and Agriculture Organization (FAO) and the United Nations Conference on Trade and Development (UNCTAD), highlights that application of Structured Finance lending techniques such as warehouse receipts, agricultural value chain financing and securitization, inter alia, has the potential of deepening credit services in agricultural sectors, especially in developing countries. Access to credit services, among other things, has the ability to unlock the potential for agriculture in developing and emerging countries. The primary motivation of the study is the observation that most of the studies that have been done so far, with regard to the application of Structured Finance in agriculture, have primarily focused on the principles underlying Structured Finance lending techniques in agriculture and not on the fundamental question that is of importance to a lending institution, in any lending transaction, namely: how to evaluate or measure the credit risk associated with Structured Finance lending transactions in agriculture. Therefore, the study contributes to the body of literature on Structured Finance in agriculture finance by developing a model or tool that can be used to measure credit risk in agricultural based Structured Finance lending transactions. Therefore, the primary objective of the study is to develop a credit risk model for agricultural-based Structured Finance lending transactions. To develop the credit risk model, the study conceptualizes theoretical framework of modelling credit risk as proposed by Merton (1974) as well as the principles underlying Structured Finance lending techniques in agriculture. Time series econometric forecasting techniques and risk simulation techniques are used to achieve the primary objective of the study. The developed model measures credit risk as the Probability of Default (PD). To demonstrate the application of the developed credit risk model, the study uses a conceptualized example, where the production of white and yellow maize in the Free State province of South Africa, during the 2009/2010 production season, is financed by Structured Finance loans. Using the developed model, the study shows that the probability of a farmer in the Free State province, defaulting on a Structured Finance white maize production loan with a face value of R3783/ha (for instance) is 0.0347 or 3.47%. The output of the developed model, which is the probability of default (PD), can be used by agricultural financial institutions (or agricultural lenders in general) to appraise Structured Finance loans; appropriately price Structured Finance loans and determine the amount of capital to hold against credit risk, inter alia. In other words, the developed credit risk model is a tool that can help financial institutions to manage credit risk in agricultural based Structured Finance lending transactions.