Empirical Calibration of Climate Policy using Corporate Solvency

The fundamental goal of climate policy is to incentivise emissions reductions and the transition to lower carbon processes and technologies. When firms face new costs related to reducing carbon emissions, they may suffer some loss of financial condition as they restructure their businesses.

However, if the firm becomes bankrupt as a result of such policies, not only will this restructuring not occur – possibly causing high-emitting industries to expand in less constrained jurisdictions (carbon leakage) – but social value can also be permanently destroyed in the form of: the dissolution of organisational capital; deadweight losses paid to liquidators; and the incurrence of costs on unemployed workers. Corporate failures, especially if they are unnecessary, add to the social cost of tackling climate change. Reductions in solvency that are less than bankruptcy can also impact the ability of firms to employ people and finance investment.

At present, policymakers do not have a means to accurately and impartially gauge the impact of climate policies on corporate solvency. If they did, policymakers could optimise climate policy so that it delivered the least loss of corporate solvency for any given level of emissions reduction.

In a new paper published in Climate Policy, we propose that existing measures of corporate solvency be used for this purpose. Such measures could act as an objective tool for policymakers. In particular, solvency metrics could be used to empirically calibrate the optimal stringency of climate policies. They could also be used as a way to determine the generosity of any industrial compensation to address losses to corporate solvency.

Financial statistics are currently used in this way to calibrate many other areas of government policy. For instance, policymakers monitor and regulate certain aspects of corporate solvency in the financial industry (such as capital reserve requirements) in order to reduce the risk of bankruptcy while maintaining profitability. Similarly, central banks also consult economic statistics when determining monetary policy.

An ideal solvency trajectory for firms affected by climate change policy would cause corporate solvency to initially decline – approaching but not exceeding ‘distressed’ levels – and then gradually improve to a new ‘steady state’ once the low-carbon transition had been achieved, at which point the carbon-limiting regulation would continue. If any compensation was provided to industry to help offset reductions in solvency, these would also then be gradually phased-out. This sequence is depicted by the U-shaped solvency trajectory below.

An additional advantage of using financial statistics to calibrate environmental policies generally is the fact that this process would be objective. At present, there is considerable potential for industrial outcry and political lobbying to influence policy resulting in negative social consequences. By contrast, a climate change policy partly based on corporate solvency could be adjusted relatively mechanically at each financial reporting period, and would be automatically sensitive to variations in the business cycle.

The question of where the optimal solvency threshold should lie is crucial for the practical application of climate policy calibration. For instance, depending on the regulator’s particular goals the relevant benchmark could be either; (i) an overall average solvency level, (ii) a minimum solvency level for the most financially distressed firm, (iii) or a maximum solvency loss for the most affected firm.

Moreover, the policy goal may not just be solvency for affected firms but also their competitiveness, in which case, depending on the regulations faced by international competitors, the optimal lower bound for solvency may need to be raised in from financial distress to some other higher level. The availability and timeliness of financial data will also influence the optimal threshold. Since the financial position of firms may deteriorate between financial reports, it may be prudent to adjust thresholds upwards to add a margin of safety against rapid solvency losses.

Of course, it would be equally essential to ensure that firms could not ‘game’ their financial statements in order to present an artificially dire picture to sympathetic regulators. It may also be the case that within a given emissions target, it may not be possible to maintain the solvency of all affected firms. In such cases the emissions target may need to take precedence over solvency concerns, but nevertheless the use of policy calibration via solvency could still be an efficient way to minimise the bankruptcy losses that may be necessary in order to achieve a desired emissions goal. Future research could refine this optimal policy threshold.

Our proposals highlight the potential of existing corporate solvency metrics to help policymakers objectively minimise negative social impacts for a given emission reduction target. Failure to take account of (or simply wish away) the social impacts associated with bankruptcy or reductions in corporate solvency resulting from climate policy would be serious mistake. It will increase opposition that could successfully undermine climate action. It would also allow fossil fuel interests to continue misleading policymakers and broader society about how climate action is negatively impacting their businesses. Transparency and objectivity enabled by financial data is already integrated into other areas of policymaking and regulation. It should also be embraced by policymakers concerned with climate change.

About the Author

 

Ben Caldecott is the founding Director of the Oxford Sustainable Finance Programme, at the University of Oxford Smith School of Enterprise and the Environment.

 

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