Jack Schieffer

The economic and environmental impacts of precision agriculture and interactions with agro-environmental policy

A whole-farm model was used to investigate the interacting effects of precision agriculture technology and agro-environmental policy on the production choices of a representative grain farm. Although some precision agriculture technologies did increase efficiency of resource use, they also decreased the effectiveness of policy, especially policies that rely on economic incentives (e.g., emission taxes). Precision agriculture can lead to higher marginal abatement costs in the form of forgone profits, decreasing producers’ responsiveness to those policies. Policy-makers targeting pollution reductions from agriculture should take into account the increasing use of precision agriculture techniques and their varying effects on agro-environmental policy.

Precision agriculture and agro-environmental policy

A whole-farm model was used to investigate the effects of precision agriculture adoption on production choices under various agro-environmental policy frameworks. Simulation of a typical grain farm in western Kentucky, USA indicated that adoption of precision agriculture does alter responsiveness to policies based on financial incentives for pollution abatement (e.g. emission taxes). Specifically, those farms were less responsive to financial incentives (i.e. abated less pollution), due to higher marginal abatement costs in the form of forgone profits. Policy-makers targeting pollution reductions from agriculture should take into account the increasing use of precision agriculture techniques and their effects on agro-environmental policy.

The carbon footprint and economic impact of precision agriculture technology on a corn and soybean farm

ABSTRACT This study explores the environmental and economic implications of precision agriculture technologies (PATs) to partially fill the void in empirically based estimates in the available published literature. In doing so, the carbon footprint of a Kentucky grain farmer under different production strategies is estimated. A BASE model was optimised without utilising any PATs and compared to models which did incorporate three PATs: sub-meter auto-steer, RTK auto-steer and automatic section control. The four whole farm analysis models were formulated under no-till conditions. These models were used to determine if these PATs (1) increase expected mean net returns and/or (2) enhance the carbon output–input ratio. The results show that all PATs produce improvements in both economic and environmental measures over the BASE model. Specifically, automatic section control gave the greatest economic improvement with a mean net return that was 0.59% over the BASE while RTK provided the greatest environmental enhancement with an improvement of 2.42% over the BASE model. All of the improvements over the BASE scenario can be attributed to the adoption of PAT in the models.

Do Superfund Sites Affect Local Property Values? Evidence from a Spatial Hedonic Approach

The presence of Superfund sites can have substantial impacts on local property values. Previous studies using the traditional hedonic price model typically fail to account for spatial dependence or autocorrelation in residential housing. Jefferson County, Kentucky is home to Louisville, the largest city in the state. Seven different Superfund sites are located within or just outside the county border. This study shows that the usage of traditional hedonic pricing model leads to inefficient estimates compared to a spatial error hedonic model. This study also investigates sites in two different phases of the cleanup process, suggesting that median housing value is lower with proximity to deleted Superfund sites, but is not significantly affected by sites classified as final. Finally, the implications of multiple Superfund sites located with five miles of the block group centroid are investigated. This study finds that housing value is not significantly affected by additional Superfund sites.

An ex post analysis as a followup to stated preferences for management strategies in Nevada's Black Rock Desert

Abstract Nevadas Black Rock Desert in High Rock Canyon (BRD/HRC) provides a variety of recreation services to a multitude of user groups, which makes the development of a management plan for the area a challenge. Stated preference analysis is a widely accepted method for analysing resource management plans; however, resource users with heterogeneous preferences make it difficult to estimate an empirical choice model across all user types. This study introduces an ex post analysis of attribute preferences by introducing a conjoint experiment with a set of follow‐up questions in order to better understand how visitors to the BRD/HRC feel about various management plans. The cost of data collection for the follow‐up questions is low, while their ability to provide explanatory power of choice behavior is significant.