The Biden Administration significantly raised its Social Cost of Carbon because of revised predictions that increased global crop yield losses under a changing climate. Although previous studies have estimated and predicted the impact of climate on crop yield distributions—highlighting differences in conditional moments or distributions (given climate)—no one has yet explored whether a changing climate has structurally altered marginal crop yield distributions, particularly with regard to tail probabilities, in a statistically significant way. To that end, we apply a new test for the presence of distributional structural change to U.S. county-level crop yields for corn and soybean. We then investigate the extent to which the spatio-temporal variation in the structural change results is explained by the spatio-temporal variation in climate change measures. Interestingly, we find that the climate change measures are jointly statistically significant and explain a notable extent of the variation despite mitigating factors like on-farm adaptation efforts and measurement error. Our results are consistent across different structural change measures, different regions of the marginal yield distribution, various methods to account for technological change in mean yields, and correcting or not for temporal changes in variance. Importantly, our results statistically justify current approaches that consider the effect of climate on the entire distribution rather than those that only consider the trend and variance.