Spatial interdependence is often overlooked in research using instrumental variable methods, leading to biased estimates even with randomly assigned instruments. This bias worsens when the instrument is spatially distributed, like rainfall or economic shocks. The study shows that ignoring spatial interdependence can result in inaccurate causal identification. By using a simple estimation strategy, consistent estimates of desired effects can be obtained.