Tuesday, January 31, 2023

Climate policy creates winners and losers, and governments need to choose the best models to weigh the results

As the global climate discussion builds on COP26, governments at all levels need to understand how climate and energy policies will affect their greenhouse gas emissions and economies. To do this, they rely on “energy-economy models,” computer simulations that analysts use to assess how energy is produced and used within an economy.

But not all these models are the same. One model may produce very different results from another. Or similar results can be interpreted in different ways. This can make climate policy decisions challenging.

So how can governments match their climate policy questions to an appropriate model? As climate policy experts, my group and I recently conducted a study that helps answer this question. We have identified the best practices that policy-makers should consider when evaluating climate policies to ensure that the best choices are made for the health of the planet and their citizens.

real world decision making

Some models combine similar technologies together, but the models that separate them make it possible to include technology-specific data, such as a vehicle’s fuel economy, in the calculations. It can also help governments better assess the impacts of technology-specific policies, such as Canada’s fuel economy regulations, on energy and greenhouse gas emissions.

The detailed level of technical representation lets us project how technology can change, or be changed, over time. This is especially important for near-commercial technologies because their characteristics are usually not well captured by historical data.

Models also make assumptions about how and why we invest in energy-related technologies. Many energy-economy models do not represent individual people and their actions, but incorporate their overall behavior. This usually works well, but there are two important, often overlooked, dynamics.

Non-financial factors can influence investment decisions, such as the decision not to buy an electric vehicle because there are not enough charging stations nearby.
Canadian Press/Frank Gunn

First, not everyone makes the same investment decisions given the same circumstances. If governments do not account for this dynamic, they may neglect alternative greenhouse gas mitigation routes and technologies. For example, if a model tells us that everyone will soon buy electric vehicles, governments cannot encourage the sale of electric vehicles, thinking that a huge sale will automatically happen.

Second, a variety of non-financial factors can influence investment decisions. For example, some people are less likely to buy an electric vehicle because they see charging an electric vehicle as a nuisance, while others are not as concerned. Models that ignore non-financial factors and include only financial costs can produce results that do not align with real-world decision-making, leading to inaccurate policy decisions.

Cop26: The World'S Largest Climate Talks

This story is part of coverage of The Conversation at COP26, the Glasgow Climate Conference, by experts from around the world.

Amid a rising tide of climate news and stories, The Conversation is here to clear the air and make sure you get information you can trust. more.

understand the connection

COP26 Climate congestion will create both economic benefits and costs for phasing out coal, reducing methane emissions and halting deforestation, and it is important that governments understand the nature and distribution of these impacts for various households and industries . These include changes in employment, economic growth, energy prices and levels of economic activity.

Read more: COP26 Deforestation is the key to slowing climate change, but Canada must tackle carbon accounting and industry issues

An energy-economy model should be able to assess the macroeconomic impacts of climate policies, that is, policies that will have an impact on a large segment of the population. For this the model needs to know how the different sectors of the economy are linked together.

A Field Of Corn In Front Of An Industrial Plant.
Ethanol refineries, like this one in South Dakota, process corn into fuel, but fermentation can release carbon dioxide into the atmosphere.
(AP photo/Stephen Groves)

For example, if governments want to mix more ethanol into our gasoline to cut greenhouse gas emissions, they must understand where ethanol will be produced and how an increase in ethanol production will affect the price of raw materials. Models that can provide information on key economic indicators such as changes in output from inter-sector sectors, trade dynamics and structural changes (such as fewer people working in the oil and gas industry) are particularly useful.

Read more: How Canada can leave 83 percent of its oil in the ground and build stronger new economies

Finally, energy-economy models should be able to accurately represent different types of policies, and should do so in a way that captures unintended policy interactions. For example, a model may be good at guiding decisions about carbon pricing, but may be bad for planning for renewable electricity generation. More importantly, governments must recognize that no one model will be the “best” one to answer all of their climate policy questions. Choosing the right model will depend on which policy question is being asked.

Global leaders should aim to build consensus on climate policy solutions at COP26. Long-standing disagreements, even among climate-related politicians, over the past three decades have led the fossil fuel industry to alarmingly warming the planet. Finding consensus begins with choosing the right model with honest climate leaders.

Aaron Hoyle, a former master’s student in resource and environmental management at Simon Fraser University, co-authored this article.

This article is republished from – The Conversation – Read the – original article.

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