In a recent paper published in this journal (Ackerman and Munitz, 2012), Ackerman and Munitz (AM) present a sectoral decomposition of the impacts of climate change as represented in FUND, an integrated assessmentmodel, and contrast the resultswith andwithout uncertainty. We welcome outside scrutiny of our work, even if in this case it adds little to what we knew already (Anthoff and Tol, 2011; Anthoff et al., 2011). AM also take issue with the range of uncertainty about the impacts of climate change reported in the peer-reviewed literature, an issue that is outside our control. AM further claim that the equation describing the impacts of climate change on agriculture comes “dangerously close” to dividing by zero and that “the FUND estimate of the [social cost of carbon] is significantly affected” by these runs. This claim is incorrect, based on inconclusive diagnostic tests used by AM. AM report two tests for dividing-by-zero. In both tests, AM change the statistical properties of the Monte Carlo analysis and compare the expectation of the social cost of carbon from their modified version of FUND with estimates from the original model. In the original model, there are 16 composite distributions that are Normal∗Normal/Normal, and 16 that are Normal/Normal. In one test, AM replace these probability density functions with Normal distributions. In the other test, they replace 16 probability density functions with Normal distributions, and 16 others with Normal∗Normal distributions. Although they preserve the modes of the distributions (at least in the first test), AM change the means, all higher moments and all cross-moments.