Files
Abstract
Technological change in plant research rarely shifts the entire yield distribution upwards as
assumed in the agricultural economics literature. Rather, technologies have been targeted
at a specific subpopulation of the yield distribution--for example, drought resistant seeds
or so-called racehorse seeds--therefore, it is unlikely technological advancements are equal
across subpopulations. In this manuscript we introduce a mixture model of crop yields
with an embedded trend function in the component means, which allows different rates of
technological change in each mixture or subpopulation. By doing so, we can test some interesting hypotheses that have been previously untestable. While previous literature assumes
an equivalent rate of technological change across subpopulations we reject the null in 84.0%,
82.3%, and 64.0% of the counties for corn, soybean, and wheat respectively. Conversely, with
respect to stable subpopulations through time (i.e. climate change) we reject in only 12.0%,
5.4%, and 4.6% of the counties for corn, soybean, and wheat respectively. These results
have implications for modelling yields, directing funds regarding plant science research, and
explaining the prevalence of heteroscedasticity in yield data.