Governing wildfire insurance under mortgage constraints: an availability-affordability-capacity framework with decision-oriented evaluation for California, 2018-2024

When a homeowner takes out a mortgage to buy a house, the bank requires a safety net: property insurance. This is not just a suggestion; it is a rule written into the loan contract. If the house burns down and the owner has no insurance, the bank loses its collateral. In the United States, particularly in places like California where wildfires are becoming more frequent and severe, this requirement creates a difficult squeeze. On one side, insurance companies are pulling back from high-risk areas because the fires are too dangerous and expensive to cover. On the other side, homeowners need that coverage to keep their loans, but the prices are rising so fast that many cannot afford them. This leaves a gap where people are caught between a lender's demand for protection and their own inability to pay, a situation that threatens to leave homes exposed to disaster and banks holding empty promises.

Researchers have long known that insurance markets can fail when risks are too high or too unpredictable. They also know that government programs exist to step in when private companies leave, offering a last-resort safety net. However, a new study by Lu Chao, XiaoXi Ma, and Sun ShuiMiao from Tianjin Tianshi College suggests that previous ways of measuring this crisis have been missing a crucial piece of the puzzle. The team focused on the specific years between 2018 and 2024 in California, a period marked by intense fire seasons and a dramatic shift in interest rates. They wanted to understand exactly how many homeowners were actually failing to get the insurance coverage their mortgages required, and whether the standard way of calculating this risk was telling the whole truth.

The core of the problem lies in how researchers usually calculate the cost of a mortgage. For decades, models assumed that every homeowner was paying the current market interest rate for their loan. This made sense when rates changed slowly, but it broke down after 2021, when interest rates jumped sharply. In reality, millions of Americans hold fixed-rate mortgages that were locked in years ago at much lower rates. A homeowner who bought a house in 2020 with a low rate is not paying the same monthly amount as someone buying a house today, even if they live in the same neighborhood. By treating everyone as if they were paying the new, high rates, older models were overestimating the financial strain on these families. The researchers realized that this error was making the insurance crisis look much worse than it actually was for many people.

To fix this, the team built a new way of looking at the data. Instead of guessing what every homeowner was paying, they used a massive, publicly available database of actual mortgages to see the real distribution of interest rates. They grouped homeowners by the rate they were actually locked into, ranging from very low rates under 3 percent to higher rates above 6 percent. They then ran their simulation again, asking a simple question: given the actual monthly payments these families are making, how many can still afford the insurance premiums required by their lenders? They also refined how they counted the "last-resort" insurance, which is a state-run program designed to cover those who cannot find private coverage. They made sure to count these policies against the total number of homes in the state, rather than just against the number of policies the model predicted, ensuring their numbers matched real-world records.

The results of this recalibration were significant. Under the old method, which assumed everyone was paying high current rates, the model suggested that in 2023, nearly 43 percent of mortgaged homeowners in California were facing a situation where they could not afford the insurance required by their loans. This implied a massive wave of people who would either lose their homes or be forced into a dangerous state of being uninsured. However, when the researchers used the real interest rates that people were actually paying, the picture changed. The number of families in this precarious position dropped to about 26.5 percent. While this is still a serious problem affecting millions of people, it means that the crisis is not as all-encompassing as the old models suggested. The difference is substantial: the new calculation shows that nearly 62 percent of the "failure" predicted by the old models was actually an artifact of using the wrong interest rate data.

The study also broke down the remaining problem into three distinct categories to show exactly where the gaps are. The first group, making up about 70 percent of the population, successfully found private insurance that they could afford. The second group, about 3.6 percent, could not find private insurance but was able to secure coverage through the state's last-resort program. The final group, the 26.5 percent who remain, are those who cannot afford either private or state insurance. The researchers are careful to note that this last group does not mean these people are currently uninsured in reality. Instead, it represents a theoretical exposure: these are the households that, according to the model, would eventually trigger a lender to step in and force a policy onto the home. This "force-placed" insurance is often much more expensive and offers less protection than a standard policy, and it is a last resort that banks use only when a borrower fails to provide proof of coverage.

The researchers did not stop at California. They looked at how similar systems work in other states to see if their findings held up. They examined Florida, where a state-run insurer called Citizens Property Insurance Corporation has seen its numbers swell and then shrink dramatically as it tries to move people back to private markets. They also looked at Texas, where a different organization handles windstorm risks with a complex system of funding layers. These comparisons showed that while the specific rules and numbers vary, the underlying tension between private market limits and the need for universal coverage is a shared challenge. The study confirmed that when the "last-resort" market is full, simply adding more money or lowering prices does not always help if the system is physically unable to take on more customers.

One of the most important takeaways from this work is that solving the wildfire insurance crisis requires looking at the whole picture, not just one part. The study shows that you cannot fix the problem by only looking at insurance prices or only looking at mortgage rates; you have to see how they interact. If interest rates stay high, the pressure on homeowners increases, but if many homeowners are locked into low rates, they have more breathing room. Similarly, if the state's last-resort program runs out of capacity, the system breaks down no matter how affordable the private market might be. The researchers found that in a scenario where the last-resort program is full, simply lowering prices for that program does not help the overall situation; the only solution is to increase the capacity of the program itself.

This research does not claim to have solved the wildfire insurance problem, nor does it suggest that the situation is safe. The 26.5 percent of homeowners who are still struggling represent a massive number of families and a significant risk to the housing market. However, by correcting the way interest rates are counted, the study provides a clearer, more accurate map of the danger zone. It tells policymakers and lenders exactly where the pressure points are, distinguishing between those who are truly priced out and those who are still managing to stay covered. The study concludes that future solutions must be precise. They need to target the specific groups that are failing to get coverage, rather than assuming a blanket crisis. By understanding the real financial situation of homeowners, from their locked-in mortgage rates to their ability to pay for insurance, society can design better rules to keep homes safe and loans secure in an era of increasing fire risk.