Return to search

Modeling the marginal revenue of water in selected agricultural commodities : a panel data approach

South Africa is a water-stressed country where water availability is an important constraint to economic and social development, and will become even more so in the future if this scarce resource is not managed effectively. In order to manage this scarce supply of water, we need to value it. This study focuses on the value of water in the agricultural sector, in particular the marginal revenue of water for six irrigation commodities namely avocados, bananas, grapefruit, mangoes, oranges and sugarcane. A quadratic production function was fitted with an SUR model specification in a panel data study from 1975 to 2002 to obtain marginal revenue functions for each of the six commodities. We found that mangoes are the most efficient commodity in its water use relative to revenue generated (marginal revenue of water equals R25.43/m³ in 2002) and sugarcane the least efficient (marginal revenue of water equals R1.67/m³ in 2002). The marginal revenue of water is not an indication of the true “market” price. Neither is it an indication what the administered price should be. The marginal revenue of water is rather a guideline for policy makers to determine which industries or commodities within an industry can generate the largest revenue per unit water applied. / Dissertation (MCom (Econometrics))--University of Pretoria, 2006. / Economics / unrestricted

Identiferoai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:up/oai:repository.up.ac.za:2263/27968
Date16 September 2005
CreatorsMoolman, Christina Elizabeth
ContributorsProf R van Eyden, tina.moolman@up.ac.za
Source SetsSouth African National ETD Portal
Detected LanguageEnglish
TypeDissertation
Rights© 2005, University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria.

Page generated in 0.0023 seconds