Revisiting the size–productivity relationship with imperfect measures of production and plot size

Monitoring smallholder agricultural productivity growth, one of the targets Sustainable Development Goals, rests on accurate measures crop production and land area. Existing methods protocols for measuring plot size are prone to various sources forms mismeasurement. Inaccuracies in area measurement likely distort descriptive predictive inferences. We examine sensitivity empirical assessments relationship between alternative protocols. implement six protocols, show that most these differ systematically their accuracy. find an apparent inverse size–productivity our data is fully explained by error both size. Moreover, we some previously used “gold standard” themselves nonclassical error, hence can generate spurious findings. Our results also slight improvements precision objective significantly reduce inferential bias associated with relationship.