Abstract
ABSTRACT Climate-econometric models postulate that increased CO2 levels cause the earth’s average temperature to increase and that the increases in the average temperature will result in huge costs in GDP. However, this causal relation is at odds with datasets that tell a different story: that the causal relationship is inversed and the variable once thought to be the effect may turn out to be the cause and vice versa. Moreover, when the Earth’s temperature is measured, it appears that changes in the measurement set up can lead to changes in the measurement outcomes thereby skewing the relevant estimates. These results reveal two sources of endogeneity in climate-econometrics: simultaneity whereby X causes Y and Y causes X and also measurement error thus making the relevant causal inferences weak from an epistemological viewpoint. Moreover, since climate-econometric models are used to advice decision-making there are further connotations: first, climate policies can hardly be evaluated through common economic methods and, second, different model-based estimates could lead to different policy-prescriptions dependent on whether endogeneity is taken into account or not. And if different policies are tied to different sets of value judgments, then it can be said that different model-based projections carry different normative implications.
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