In this paper, we attempt to quantify the shadow price of an additional inch of groundwater resource left in situ for the Southern Ogallala Aquifer. Previous authors have shown the degree to which the optimal resource...In this paper, we attempt to quantify the shadow price of an additional inch of groundwater resource left in situ for the Southern Ogallala Aquifer. Previous authors have shown the degree to which the optimal resource extraction path may diverge from the competitive extraction path based upon varying assumptions. We utilize high-quality data over an unconfined groundwater resource to evaluate the validity of these results. We find that the size of the existing groundwater resource is sufficiently small to result in a divergence between the competitive and socially optimal solutions. We are also able to confirm that the model responds to changes in the parameters in a manner consistent with previous research. Finally, we arrive at a marginal user cost for an additional acre-inch of water which is relatively low, but reasonable given uncertainty about future technological improvements.展开更多
Variable Rate Technology （VRT） takes within-field variability into consideration and aims to match resource application to crop requirement. Even though Texas is the most important cotton producing state in the US, ...Variable Rate Technology （VRT） takes within-field variability into consideration and aims to match resource application to crop requirement. Even though Texas is the most important cotton producing state in the US, the rate of VRT adoption is very low here. Hence, analyzing the factors influencing the adoption and providing a regional estimate of the impact of VRT adoption on cotton yield is very important. This study used the 2009 Southern Cotton Precision Farming Survey to analyze the farm and farmer characteristics affecting the adoption of VRT among Texas cotton farmers and to empirically estimate the impact of adoption of VRT on cotton yield in Texas. A two-stage least square procedure with a logistic regression model in the first stage and a multiple linear regression model in the second stage was used to analyze the data. The study revealed that there are significant regional differences in adoption pattern within the state of Texas; and the farmers from the coastal region, where there is higher within-field variability, were more likely to adopt VRT compared to other regions. Younger farmers, farmers managing larger farms, and farmers who use computers for farming operations were more likely to adopt VRT. The results also showed that, on an average, the adoption of VRT does not lead to significant yield improvements for cotton in Texas. Since the impact of VRT adoption on yield is not significant, the source of economic advantage of VRT adoption in Texas may be the reduction of input cost.展开更多
文摘In this paper, we attempt to quantify the shadow price of an additional inch of groundwater resource left in situ for the Southern Ogallala Aquifer. Previous authors have shown the degree to which the optimal resource extraction path may diverge from the competitive extraction path based upon varying assumptions. We utilize high-quality data over an unconfined groundwater resource to evaluate the validity of these results. We find that the size of the existing groundwater resource is sufficiently small to result in a divergence between the competitive and socially optimal solutions. We are also able to confirm that the model responds to changes in the parameters in a manner consistent with previous research. Finally, we arrive at a marginal user cost for an additional acre-inch of water which is relatively low, but reasonable given uncertainty about future technological improvements.
文摘Variable Rate Technology （VRT） takes within-field variability into consideration and aims to match resource application to crop requirement. Even though Texas is the most important cotton producing state in the US, the rate of VRT adoption is very low here. Hence, analyzing the factors influencing the adoption and providing a regional estimate of the impact of VRT adoption on cotton yield is very important. This study used the 2009 Southern Cotton Precision Farming Survey to analyze the farm and farmer characteristics affecting the adoption of VRT among Texas cotton farmers and to empirically estimate the impact of adoption of VRT on cotton yield in Texas. A two-stage least square procedure with a logistic regression model in the first stage and a multiple linear regression model in the second stage was used to analyze the data. The study revealed that there are significant regional differences in adoption pattern within the state of Texas; and the farmers from the coastal region, where there is higher within-field variability, were more likely to adopt VRT compared to other regions. Younger farmers, farmers managing larger farms, and farmers who use computers for farming operations were more likely to adopt VRT. The results also showed that, on an average, the adoption of VRT does not lead to significant yield improvements for cotton in Texas. Since the impact of VRT adoption on yield is not significant, the source of economic advantage of VRT adoption in Texas may be the reduction of input cost.
