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Hurricanes (And Insurance) Are Remaking Florida’s Coast For The Rich
Despite the assumption that increased frequency of tropical storms would depress coastal real estate markets, each new hurricane actually increases home prices as the wealthy take advantage of government subsidized insurance and the poor flee inland after being priced out of the market.
The result is “lasting demographic changes” to coastal Florida, according to a new report published by the National Bureau of Economic Research.
According to the report — which studied Florida’s coast real estate market between 2000 and 2016.
Home prices in exposed areas jump 5% on average three years following a hurricane, with a peak of 10% in the second year.
In addition, average income in those same areas increased by around 4% in the first year after a hurricane, and nearly 7% in the second.
Between 1992 and 2017 a total of fifteen hurricanes moved near Florida, with five reaching wind speeds of a Category 3.
The authors say that how the market responds to hurricanes is creating “uneven and lasting demographic changes in affected communities” despite an often quick recovery in physical capital.
Given that homeownership is often a long-term decision, this pattern may result in a lasting change in the economic profile of affected communities toward higher income, and likely higher wealth. In turn, the influx of higher-income households could trigger further gentrification in these neighborhoods, as the new residents demand (and are able to pay for) new local amenities. In most cases, gentrification eventually produce winners and losers, largely depending on who the incumbent homeowners are, and who rents.
The authors added that there are several factors that contribute to hurricane induced gentrification, but a large portion of the blame can go to government-subsidized property insurance schemes that favor the wealthy.
To the extent that homeowners are counting on public assistance or insurance rates not reflective of actual risks, some of this gentrification may be the result of moral hazard, highlighting the need for program reform as advocated for by many researchers.
What The NOAA Appointments Are Saying About Modeling
The Trump Administration continues remaking of the US government weather community with researchers that doubt current climate model practices. Two weekss ago it was announced that David Legates was appointed as the National Oceanic and Atmospheric Administration’s deputy assistant secretary of commerce for observation and prediction and Ryan Maue was named as the NOAA’s new chief scientist.
Below are some of the public comments both have made regarding current climate modeling practices.
…these models are limited in important ways, including:an incomplete understanding of the climate system,
an imperfect ability to transform our knowledge into accurate mathematical equations,
the limited power of computers,
the models’ inability to reproduce important atmospheric
inaccurate representations of the complex natural interconnections
Models have too much sensitivity to climate change, particular with relation to the greenhouse effect, because there’s just too much water in the atmosphere.
The nascent field of “attribution science” attempts to explain how climate change may affect characteristics of a given hurricane using models in “what if” mode. Such research requires a faithful reproduction of events and predictions of the future constrained by subjective choices within computer models.
The inclusion of aerosol linkages to changes in North Atlantic hurricane activity is speculative at best.
The Cost/Benefit Analysis For Louisiana’s Coast
The US Gulf Coast, coastal Louisiana in particular, has seen a particularly active storm season as Hurricane Sally and Laura battered the state. A paper published earlier this year by Louisiana State University researcher Christopher Siverd argues that without natural wetlands to protect the region, there is little that costly flood defense projects can do to prevent the inevitable. Below is a quick conversation regarding the research.
Risk Market News: Could you detail the thesis of your work?
Christophe Siverd: This paper connects flood defense costs with wetland loss to demonstrate the importance of wetlands in reducing storm surge heights and therefore overall flood defense costs.
Costs are calculated for Lafitte, Louisiana, if Hurricane Isaac were to occur in select years from 1930 to 2110. Between 1930 and 2010 the wetlands between Laffite and the Gulf of Mexico gradually subsided and converted to open water. Therefore, if Isaac made landfall in 1930, the required flood defense costs would have been substantially less than those in 2010. We calculate from 1970 to 2010, for example, flood defense costs increased approximately (in 2010 USD) $19,000 per person per kilometer inland migration of the Gulf of Mexico.
RMN: Are there communities where the risk/benefit of storm surge reduction no longer makes sense?
Siverd: This paper also demonstrates there is strength in numbers.
The New Orleans hurricane storm damage and risk reduction system (HSDRRS) protects a population of 924,000 at a post-Katrina upgrade cost of (2010 USD) $14.6 billion or $15,800 per person indicating benefits outweigh costs.
However, the costs to protect Lafitte in 2010 with a population of 4,734 was $181,633 per person indicating lifting houses was the more economical option than building a flood risk reduction system around Lafitte at the level New Orleans is protected.
RMN: Given the region highlighted in your paper is susceptible to hurricanes, what is your expectation of a Category 4 or 5 event?
Siverd: My greatest fear is the next major hurricane that strikes south Louisiana in future years. Rita surge inundated the entire Louisiana coast and accelerated coastal land loss by increasing the salinity in fresh water marshes, which accelerated their eventual conversion to open water.
RMN: Do you feel current windstorm and storm surge models have enough detail to take these regional issues into account?
Siverd: In general, the greatest challenge with all numerical models is the quality of data input at the beginning of a simulation. The higher the quality of bathymetry data, tide data, wind fields and other boundary and initial conditions, the more accurate the model result will be.