Scope

It is of great importance to society to use economic theory and empirical models to understand climate change and its consequences. The risks associated with climate change, such as increased CO2 emissions, rising sea levels, and health impacts, require a global interdisciplinary effort incorporating sectors of technology, individual health, energy, and environmental science. The solution to climate change needs to encompass these various aspects, and therefore economic analysis can play a critical role in determining climate change solutions.

The economic analysis enables us to evaluate both tangible and intangible assets in the monetary term, allowing the public to understand and policymakers to pave the way for the changes. Assessing disaster risks (i.e. due to rising sea levels) can be one method. The current disaster management approach assesses direct economic losses/monetary value of damage to physical assets as ‘disaster losses’. Such methods are commonly used as a metric for assessing massive disaster damages. Calculating damages to physical assets provides essential insights for understanding disaster risks and policy guidelines to mitigate the disaster risks. However, one limitation of assessing disaster risks through physical assets is that it can overlook other dimensions of loss which incorporate the impact on humanity's well-being, health, energy usage, and environmental consequences. Implementing economic analysis by creating a model that can incorporate ‘intangible’ loss dimensions, along with the current metrics on disaster loss management, can be a great solution to complement the current analysis.

Another significant benefit of the economic analysis in climate change, is that it allows for counterfactual simulations; therefore, forecasting future climate change. For an empirical example, some economic models, which are represented as choice modelling, can estimate consumers' demands on pro-environmental goods (e.g. fuel-efficient automobiles, electric cars, and renewable energy sources) that can improve the environment. However, as purchasing pro-environmental goods does not always guarantee pro-environmental outcomes, predicting consumer behaviours after purchase through counterfactual simulations is necessary. Consumers may use more energy, resulting in higher levels of emissions, after purchasing fuel-efficient cars due to the lower fuel costs. Exercising counterfactual simulations through economic modelling can predict whether such an outcome is likely to happen.

To this end, I welcome high-quality submissions in the themes below, but not limited to:

•   Climate change economics

•   Energy and transportation economics

•   Climate modelling and projections

•   Climate risk management

•   Climate economics

•   Energy commodity and regulation and taxation

•   Forecasting

•   International trade

•   Economic growth

•   Monetary policy

•   Natural capital and inclusive wealth

For the methodology, I welcome various methods frequently used in economics - including, but not limited to:

•   Surveys

•   Experiments

•   Econometric modelling

•   Simulation models

•   Equilibrium and optimization models

I hope that research published in Climate and Economics section can help people understand the causes, impacts, and solutions for climate change, as well as the overall implications for our entire global society.

Submission

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