We introduce our monthly Forecast Direct series as a podcast/video. Every month, we bring in guest speakers who bring their unique insight on topics affecting the US and California economies.
Forecast Direct No. 36 - Regulation and Risks in the Private Insurance Market
Sayantani of the Anderson Forecast & the UCLA Ziman Center for Real Estate talks to Reid Taulor, research economist at the Dallas Fed. They discuss how regulation and increasing disaster risks can result in the unraveling of the private insurance market. The paper presents a simple model of a disaster market and an insurer of last resort operating in the market that’s not being provided for by private insurers. Using the case of California’s homeowners and insurance market, they further empirically estimate the effects of the California nonrenewal moratorium, a novel policy implemented by the California Department of Insurance to curb the growth of the FAIR plan.
Key Takeaways:
• As profit-maximizing firms, insurers rationally choose not to offer insurance to those who have an expected marginal cost above the regulated price, leading the riskiest consumers to receive coverage from the insurer of last resort (FAIR plan) in the residual market. Subsequently, the insurer of last resort does not solve any market failure but is necessary to guarantee full market coverage under strict price regulation.
• Zip codes impacted by the moratorium experienced a decrease in company-initiated non-renewals during the year the moratorium was active. However, this effect was short lived; insurers increased non-renewals by at least 80% in the year immediately following the expiration of the moratorium.
• They estimate that the moratorium did not slow the retreat of private firms from high-risk areas and may have even accelerated it. The number of policies written by the voluntary market declined by 200 one year after the moratorium, and the number of policies written by the FAIR Plan increased by 100.
• In order for firms to remain in the market in the long run, premiums must be reflective of the underlying risks. This can be achieved by either relaxing regulation, or investing in climate adaptation. Recent policy changes indicate that both strategies are being pursued in California.
21 Oct 2025
Forecast Direct No. 35 - Climate Risk, Insurance Demand and Homeowner Mobility
Sayantani of the Anderson Forecast talks to Xuesong You, former Climate Research Economist at Freddie Mac. They discuss the how the availability of homeowners insurance influences the locational desirability of both existing homeowners and potential home buyers when searching for a new home. The analysis is especially relevant given the risks that consumers are facing when navigating homeownership, while dealing with an increasing number of wildfires and drastic changes in insurance availability over the recent years, across California.
Key takeaways:
* While most of the literature depends on home prices or values to estimate the desirability for a location, the use of granular parcel-level home loan application data allows more accurate assessment of the demand-side story for home-owners, isolated from any supply-based price impacts.
* The analysis delves into how the risk signals from private insurers indicating the lack of insurability at a location could influence household behaviors, adding new insights into the role that insurance markets can play in guiding fire adaptation.
* Existing homeowners of higher-risk properties are found to be more likely to search for homes in areas with lower fire hazards and less vegetation coverage compared to those who own and reside in low-risk properties.
* In terms of response from potential home-buyers searching for homes:
- For high-risk properties in high-risk communities that face the most challenge of obtaining insurance, application volume is found to decrease sharply, with a more pronounced reduction in years when private home insurance is less accessible. In contrast, the applications for low-risk properties in high-risk communities increased during the same period.
- Home buyers interested in high-risk properties are found to be more likely to come from areas that show lower concerns over climate change, with no significant changes in their income.
8 May 2025
Forecast Direct No.34 - Social Media and Finance
In this episode of the Forecast Direct, Thomas Ash of the UCLA Anderson Forecast talks to Professor Tony Cookson of the University of Colorado, Boulder, Leeds School of Business. They discuss the finance social media ecosystem, what it is, how it functions, and some key research findings related to it. This is especially important as social media takes a larger share of attention away from traditional media.
Key takeaways:
* Key social media platforms for finance include StockTwits, Twitter (“FinTwit”), and Seeking Alpha. On these roughly 80% of posts are bullish and coverage even includes many tiny to mid‑cap firms. By contrast, traditional media outlets show more negative‑tilted information and skew toward large firms.
* A useful way to characterize different parts of social media research is where it can act as a lens to view typical human behavior, versus social media's role as a participant, itself driving trading and volatility.
* There is a difference between firm‑Level vs. market‑level signals on social media. Different social media platforms talk about the same things but tend to disagree on the prospects of individual firms. At the firm level, spikes in social‑media sentiment mildly predict positive returns, while attention spikes tend to predict negative returns. At the aggregated market‑level however the opposite is true for both sentiment and attention, pointing to key differences between the firm and market level signals.
* Echo‑chamber dynamics and fake‑news proliferation can degrade both the quality of information impounded into prices and investors’ trust in genuine signals.
Reach and audience
Public platform figures. Ratings count people who left a rating, not total listeners.
Apple Podcasts (US)
5.0 / 5
1 ratings
Spotify
5.0 / 5
1 ratings
Podcast Authority Score: 13 / 100
A composite of feed quality, social presence, YouTube performance and engagement. Read the methodology.
Quality
2
Social presence
0
YouTube
0
Engagement
60
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