Case study: 2004 hurricane season
Historical catastrophe events of the 2004 hurricane season provide empirical evidence of demand surge and demonstrate how reconstruction timelines, labor market disruption, and construction cost inflation influence post-event losses.
The 2004 hurricane season is notable for four named storms making landfall in Florida within a six-week period: Hurricane Charley in August, followed by Hurricanes Frances, Ivan, and Jeanne in September. In Florida, it was estimated that one in five residential structures sustained some level of damage during the season (Guy Carpenter, 2014). The 2004 hurricane season highlights how multiple storms in a single season can contribute to demand surge.
The clustering of events in Florida created increased demand for reconstruction resources, delaying recovery and rebuilding for many. For example, an extensive survey of impacted households conducted by the Bureau of Economic and Business Research at the University of Florida found that repairs had been completed for only 35 percent of damaged homes nine months after the storms. At the time, 44 percent of damaged properties still had repairs underway, 16 percent were planning but had not yet started repairs, and 5 percent were not planning to make repairs at all (Smith & McCarty, 2006). This reconstruction profile, characterized by high demand for repairs, created conditions for significant labor market disruption and prolonged reconstruction and insurance claim settlement timelines.
Modeled demand surge for the 2004 season in Florida is 10.3 percent using long-term assumptions for post-event construction cost inflation and 12.4 percent using cost inflation trends at the time of the event. Modeled results are consistent with the observed demand surge of 17.9 percent in Florida, on average, and localized demand surge ranging between 8.3 and 27.5 percent. Modeled demand surge is within the range of historical observations. These results demonstrate the model's ability to capture demand surge for clustered events that can occur in a hurricane season.
It is also important to consider economic conditions at the time of event. The 2004 hurricane season coincided with a strong housing construction market in Florida with already high levels of construction cost inflation. A previous retrospective of demand surge following the 2004 hurricane season found that construction permits per worker were at elevated levels in Florida prior to the 2004 hurricane season. The high level of construction activity suggests that the construction labor market had limited excess capacity to absorb the sudden surge in repair demand. In response, construction wages rose sharply following the 2004 hurricane season, while construction material prices continued to follow national trends (AIR Worldwide, 2020). This analysis highlights that demand surge can be significantly driven by local construction labor market disruptions at the time of the event.
Case study: Hurricane Katrina (2005)
Hurricane Katrina made landfall in Louisiana on August 29, 2005, producing catastrophic damage in New Orleans and along the Gulf Coast. The combination of widespread damage, infrastructure destruction, and population displacement created a significantly extended recovery. Following nearly a year of initial emergency response and disaster recovery and restoration, reconstruction in New Orleans did pick up until approximately one year after landfall (Reconstruction of New Orleans after Hurricane Katrina: A research perspective, 2006). Following Hurricane Katrina, construction labor shortages were a dominant driver of demand surge, with local labor costs increasing by more than 20 percent at the peak of reconstruction activity. Material cost increases were more modest and largely tracked national trends.1
The modeled demand surge for Hurricane Katrina in Louisiana is 13.0 percent using long-term assumptions for post-event construction cost inflation and 11.3 percent cost inflation trends at the time of the event. Modeled results are consistent with the historical estimate of 6.6 percent in Louisiana, on average, and localized demand surge ranging between 5.8 and 11.4 percent. The extended reconstruction timeline increases the contribution of post-event construction cost inflation to overall demand surge. Hurricane Katrina highlights the importance of modeling reconstruction and claim settlement times as part of demand surge.
Case study: Hurricane Harvey (2017)
Hurricane Harvey made landfall in southeast Texas on August 25, 2017, before stalling and producing unprecedented rainfall across Texas. The storm deposited nearly 44 inches of rain over the course of four days in Houston, causing catastrophic inland flooding across the Houston area. Insured losses from Harvey were concentrated in Houston and the surrounding areas, with high levels of flood damage across residential and commercial properties (Verisk Analytics, 2025).
The modeled demand surge for Hurricane Harvey in Texas is 7.6 percent using long-term assumptions for post-event construction cost inflation and 5.7 percent at the time of the event.2 The historical estimate of 2.7 percent (with localized demand surge ranging between 0.9 and 5.3 percent) reflects the limited observable demand surge after Hurricane Harvey.
A key characteristic of demand surge following Hurricane Harvey was the proximity of the heaviest damage to major construction employment centers. The highest losses were concentrated in Harris County, which is also home to a high density of construction workers in Texas. This geographic alignment meant that the local construction industry could respond relatively quickly to repair demand (AIR Worldwide, 2020). This case study illustrates that event severity alone does not determine demand surge magnitude. To capture the potential impact of demand surge, additional considerations are needed to understand local construction market conditions, including the concentration of local labor forces, in impacted geographies at the time of the event.
Case study: Hurricane Irma (2017)
Hurricane Irma made its initial U.S. landfall at Cudjoe Key in the Florida Keys on September 10, 2017, two weeks after Hurricane Harvey struck Texas. It made a second landfall later the same day near Marco Island, producing widespread wind damage across South Florida, the Florida Keys, and portions of the Florida peninsula. The storm's broad track exposed a large geographic area to insurable damage, including coastal and inland communities across multiple construction labor markets
The distribution of Irma's losses placed the heaviest damage in close proximity to the state's largest construction employment concentrations. This is analogous to the case of Hurricane Harvey and its proximity to Houston and similarly moderated the labor disruption response. In addition, the geographic spread of Irma's damage across multiple counties and the state's tourism and retirement industries (which sustain construction activity year-round) produced a more diffuse but still observable labor cost effect (AIR Worldwide, 2020).
The modeled demand surge for Hurricane Irma in Florida is 9.0 percent historical assumptions for post-event construction cost inflation and 8.9 percent at the time of the event.3 The historical estimate of 4.2 percent (with sub-region ranges between 1.4 to 5.5 percent) reflects the relatively contained labor market response.