Probit with Spatial Correlation by Field Plot: Potato Leafroll Virus Net Necrosis in Potatoes

Abstract

A probit model with spatial correlation is applied to data from a field experiment, which characterizes the impact of management variables on potato leafroll virus net necrosis in potato tubers. In the estimation, each field plot is assigned distinct spatial autoregressive coefficients for the dependent variable and the residual to be estimated simultaneously with coefficients of the management variables. Statistical findings demonstrate that spatial correlation exists and varies across field plots. We also find that ignoring spatial correlation by plot results in inconsistent parameter estimates and leads to management strategies promoting overuse of insecticides. In contrast, incorporating spatial correlation by plot into the probit model yields empirical estimates that are consistent with past research and promotes more efficient insecticide use from both an individual and environmental perspective.