A new rating industry is emerging to help homebuyers assess climate risks
As climate change fuels large-scale natural disasters, the real estate mantra ‘location, location, location’ takes on new meaning. In 2021, homeowners faced threats such as crippling cold on the Great Plains, wildfire evacuations in the west, and flooding from the south to New York and New England.
Buying a home is tough enough in a market that has become overcrowded in many American cities. Emerging risks associated with climate change will further complicate these decisions. Investors will be less likely to regret their decisions if they do their due diligence in researching local climate risks. Mortgage lenders will face less risk of borrower default and insurers will incur fewer losses if they factor climate risks into loan and policy decisions.
I study environmental economics, and in my recent book, “Adapting to Climate Change: Markets and the Management of an Uncertain Future”, I explore how the rise of Big Data will help people, businesses and local governments to make better decisions about climate risks. I see the emergence of a climate risk analysis industry for real estate as a promising development, but I think the federal government should set standards to ensure it provides reliable and accurate information.
Prices send climatic signals, but not everyone is listening
Home prices reflect implicit judgments about whether properties are good investments – including the home and the area around it. For example, the current median of a house in California is almost US $ 720,000, more than double the national median. This difference reflects a judgment that California offers a desirable climate, lifestyle and employment opportunities.
People who buy property in California are betting that the state will continue to be a great place to live in the future. If climate change ravages much of it, buyers might regret their investment.
Recent research on real estate in the United States shows that the risks of flooding and fire are reflected in current house prices. Properties perceived to be riskier sell for a lower price, but it is not clear whether these climatic price discounts fully compensate buyers for the risks to which they are exposed.
Concerns about emerging climate risks vary, in part due to partisan divide. It’s fair to assume that some buyers will be eager to buy homes in places others consider too risky. When people disagree on the likelihood of a bad outcome, the more optimistic bidder is more likely to buy the asset.
Climate change is making extreme weather events, such as tropical storms and flooding, more frequent and intense in many places. Will people’s perceptions of risk change with these changes? Studies show that many people underestimate the climate risks to housing.
As Nobel laureate in economics George Akerlof has shown, asymmetry in market information – when sellers know more about a product than buyers – can hamper trade. Buyers are rightly worried about getting stuck with a âlemonâ, whether it’s a used car or a house that gets flooded with every big storm.
In the automotive market, rating systems like Carfax help level the playing field; in the real estate sector, climate concerns create an opportunity for a nascent industry of climate risk screener modellers offering a similar service to homebuyers.
Like Standard & Poor’s but for climate risk
Just as Moody’s and Standard & Poor’s assess the creditworthiness of private companies to help inform investor decisions, a growing number of companies are looking to assess spatially refined climate risks, ranging from floods to extreme heat and fire risk. forest. These companies include Climate Check, First Street Foundation, Jupiter Intelligence, Moody’s ESG Solutions Group, and RMS.
Climate risk assessors use recent natural disasters to compare the geography of recent flooding to what their model predicts. Typically, they combine peer-reviewed research in climatology and hydrology with a climate change model to generate risk maps. The First Street Foundation has released a step-by-step overview of its modeling approach.
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Like any emerging industry, spatially refined climate forecasts have experienced uneven growth. Some models are scientifically sound and very accurate, while others are inferior. In a normal market, consumers would select the winning products through market competition – but for climate risk predictions, it can take years to assess which offers are the most reliable.
I believe the federal government should play a role in screening the next generation of products against climate risks. Regulators could work with the National Science Foundation to create a jury of experts to assess new products.
One way to check the quality of these offerings would be to foster a competition in which teams publish predictions of likely disaster locations in 2022 and then are ranked in early 2023 based on their ability to predict actual outcomes. This type of annual review could encourage participants to upgrade their models regularly. One potential example is algorithmic trading competitions in financial markets, in which competitors develop new models to accurately predict how the stock market will react to large trades.
Save lives and protect assets
Climate risk assessment companies could help make the US real estate industry more resilient by helping homebuyers become more sophisticated and realistic real estate buyers. Credit patterns will change as banks offer borrowers less generous terms for riskier properties. This incentive should cause people to bid more for relatively safer properties and seek to live in less risky areas.
Such changes could in turn push changes in local land use and zoning laws up the area – allowing higher value-added or denser uses – into relatively safer areas. Building more housing in less risky areas would make climate adaptation more affordable.
Climate change confronts people with fundamental uncertainty. I consider the development of skills and infrastructure to better predict local climate risks as a useful strategy for adapting to climate risks. If forecasters can develop reliable predictive models, people will face fewer future regrets about their real estate investments and less risk in their daily lives.