This paper is the first large scale, quantitative study of the impact of corporate carbon management practices on corporate greenhouse gas (GHG) emissions. Using data for 2009 and 2010 from the Carbon Disclosure Project survey, we find little compelling evidence that commonly adopted management practices are reducing emissions. This finding is unexpected and we propose three possible explanations for it. First, it may be because corporate carbon data and management practice information have not been reported in a standardized way. Second, there may be a delay between the application of corporate carbon management practices and their impact on emissions performance. Third, carbon management practices are not sufficiently impact-oriented, meaning there is no relationship to observe. Our findings are important for policymakers designing corporate GHG reporting standards, for the multiple stakeholders trying to understand the drivers of corporate carbon performance, and for the corporate managers responsible for measuring, reporting and mitigating emissions.

CO 2 emissions and GDP move together over the business cycle. Most climate change researchers would agree with this statement despite the absence of a study that formally analyzes the relationship between emissions and GDP at business cycle frequencies. The paper provides a rigorous empirical analysis of this relationship in a comprehensive crosscountry panel by decomposing the emissions and GDP series into their growth and cyclical components using the HP filter. Focusing on the cyclical components, four robust facts emerge: 1) Emissions are procyclical; 2) Procyclicality of emissions is positively correlated with GDP per capita; 3) Emissions are cyclically more volatile than GDP; and 4) Cyclical volatility of emissions is negatively correlated with GDP per capita. These facts are potentially important for the calibration of theoretical models used to evaluate climate change mitigation policies.

We propose a theory of the economic advantage (EA) of regulating carbon emissions by linking two emissions trading systems versus operating them under autarky. Linking implies that permits issued in one system can be traded internationally for use in the other. We show how the nature of uncertainty, market sizes, and sunk costs of linking determine EA. Even when sunk costs are small so EA>0, autarky can be preferable to one partner, depending on jurisdiction characteristics. Moreover, one partner's permit price volatility under linking may increase without making linking the less preferred option. An empirical application calibrates jurisdiction characteristics to demonstrate the economic significance of our results which can make linking partner match crucial for the effectiveness and success of the Paris Agreement.

The economic case for limiting warming to 1.5°C is unclear, due to manifold uncertainties. However, it cannot be ruled out that the 1.5°C target passes a cost-benefit test. Costs are almost certainly high: The median global carbon price in 1.5°C scenarios implemented by various energy models is more than US$100 per metric ton of CO2in 2020, for example. Benefits estimates range from much lower than this to much higher. Some of these uncertainties may reduce in the future, raising the question of how to hedge in the near term. Maintaining an option on limiting warming to 1.5°C means targeting it now. Setting off with higher emissions will make 1.5°C unattainable quickly without recourse to expensive large-scale carbon dioxide removal (CDR), or solar radiation management (SRM), which can be cheap but poses ambiguous risks society seems unwilling to take. Carbon pricing could reduce mitigation costs substantially compared with ramping up the current patchwork of regulatory instruments. Nonetheless, a mix of policies is justified and technology-specific approaches may be required. It is particularly important to step up mitigation finance to developing countries, where emissions abatement is relatively cheap.

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