Browsing by Author "Conradie, B I"

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    A review of mathematical programming models of irrigation water values
    (2004) Conradie, B I; Hoag, D l
    By introducing the user-pays principle into the irrigation water pricing debate, the 1998 National Water Act created a demand for models to measure willingness-to-pay for irrigation water. Water values are traditionally simulated with mathematical programming models. Models differ in their treatment of crops, irrigation options and water constraints, and other firm-level characteristics but they all use shadow prices as an indication of water value. The 17 models reviewed here, report average annual water values of between $0.0042·m-3 and $0.1899·m-3. Crops modelled influence water values, but there is no apparent relationship between objective function specification and average value. Nor does the number of irrigation options seem to influence water value either. The policy implication is that while similar models for the same region produce consistent estimates, each region requires its own model that has to be updated regularly.
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    Open Access
    A review of mathematical programming models of irrigation water values
    (2004) Conradie, B I; Hoag, D L
    By introducing the user-pays principle into the irrigation water pricing debate, the 1998 National Water Act created a demand for models to measure willingness-to-pay for irrigation water. Water values are traditionally simulated with mathematical programming models. Models differ in their treatment of crops, irrigation options and water constraints, and other firm-level characteristics but they all use shadow prices as an indication of water value. The 17 models reviewed here, report average annual water values of between $0.0042·m-3 and $0.1899·m-3. Crops modelled influence water values, but there is no apparent relationship between objective function specification and average value. Nor does the number of irrigation options seem to influence water value either. The policy implication is that while similar models for the same region produce consistent estimates, each region requires its own model that has to be updated regularly.
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    Efficiency and farm size in Western Cape grape production: pooling small datasets
    (2006) Conradie, B I; Cookson, G.; Thirtle, C.
    A stochastic frontier is fitted to two panels of wine grape farms (34 in Robertson and 36 in Worcester) for 2003 and 2004 and a cross section of 37 table grape farms in De Doorns for 2004 only. The panel of wine grape farms is the best model as tests show that De Doorns is different. Output is explained by land, labour and machinery and efficiency is affected by labour quality, age and education of the farmer, location, the percentage of non-bearing vines and expenditures on electricity for irrigation. There is evidence of a small degree of increasing returns to scale.