Quantifying the role of insurance in tornado-impacted community recovery: a survey and simulation-based approach

Abstract

Insurance against disasters plays a critical role in community recovery by providing policyholders with reliable and timely payments for repairing or reconstructing damaged houses. By allowing homeowners to transfer risk, insurance enables homeowners to address house without experiencing significant financial burdens. Although historical events have highlighted the importance of insurance, its quantitative impact on community recovery, particularly in tornado-impacted communities, is understudied. This study focuses on advancing our understanding of whether sufficiently insured houses can have a positive impact on the recovery of tornado-impacted communities (i.e., the main research question). This paper proposes a two-stage simulation framework to quantitatively evaluate the effects of insurance on community recovery. In the first stage of the framework, we developed statistical models to estimate homeowners’ insurance decisions prior to a tornado event. In the second stage, we examined the effects of insurance on various aspects of community recovery. To develop empirical and statistical models regarding insurance decisions and their impacts on housing recovery, we collected data through online surveys targeting residents whose properties were damaged by the tornadoes that occurred in May 2019 in the United States. Finally, the proposed simulation framework was applied to the City of Dayton, Ohio following those May 2019 tornado events to address the main research question. The results of the simulation concluded that sufficiently insured houses can have a positive impact on community recovery and highlighted the need for effective policies and economic incentives to encourage individuals to purchase insurance.

Appendices

Appendix 1: Categories and questions included in the online surveys

Questionnaires	Categories	Questions
Closed-ended	Homeowner characteristics	Location (Zip code)
		Age (years)
		Gender
		Education
		Employment
		Ethnicity
	House condition at the time of the 2019 May tornado	Construction year
		Construction material
		Property type and ownership
		Personal belonging value
		Property value
		Property mortgage status and balance
	Homeowners insurance information at the time of the 2019 May tornado	Homeowners insurance purchase
		Dwelling coverage limit
		Dwelling deductible
		Annual insurance premium
		Additional Living Expenses (ALE) coverage
		Insurance claim application
		Total claim payment
		Percentage of reconstruction cost covered by insurance
		Time to receive an insurance claim payment
	Flood insurance information at the time of the 2019 May tornado	Flood insurance purchase
		Flood insurance type
		Content coverage limit
		Content deductible
		Annual insurance premium
		Insurance claim application
		Total claim payment
		Percentage of reconstruction cost covered by insurance
		Time to receive insurance claim payment
	Reconstruction following the 2019 May tornado	House damaged by windstorm due to the 2019 May tornado
		House damaged by rainwater due to the 2019 May tornado
		Repair actions
		Date of initial recovery
		Date of completed recovery
		Total wealth prior to the 2019 May tornado
		Total wealth following the 2019 May tornado
		Total combined economic losses resulting from the 2019 May tornado
		Financial aid from the federal or local government
		Time to receive government financial aid claim payment
		Financial hardship type due to 2019 May tornado
Open-ended	Insurance-related experience	Reason for purchasing insurance or not
		Insurance claim experience
		Pros and cons of your insurance policy
		Willingness to purchase the insurance in the future
	Financial condition and aid	Other sources of funds to reconstruct property resulting from the 2019 May tornado
		Most helpful sources of funds to reconstruct property resulting from the 2019 May tornado
		Experience during structural (building) damage repair/reconstruction process

Appendix 2: Independent variables for regression models

Variables	Options
Location (Zip code)	Hazard-prone area
	Non-hazard-prone area
Age (years)	18–29
	30–39
	40–49
	50–59
	60–69
Gender	Male
	Female
Education	High school degree
	Some college but no degree
	Associate degree
	Bachelor’s degree
	Master’s degree
	PhD degree
Employment	Employed, working 1–39 h per week
	Employed, working 40 or more hours per week
	Not employed
Ethnicity	Caucasian
	Latino or Hispanic
	Asian
	African-American
	Native American
House constructed year	Before 1970
	1970–1979
	1980–1989
	1990–1999
	2000–2007
	2008–2013
	2014–2019
	Do not know
House construction material	Wood
	Concrete
	Steel
	Other
	Do not know
Property type and ownership	House or condominium rented
	House or condominium owned or being bought by you or someone in your household
	Apartment
	Mobile or manufactured home owned or being bought by you or someone in your household
Personal belonging value	< $1000
	$1000–$4999
	$5000–$9999
	$10,000–$49,999
	$50,000–$99,999
	$100,000–$199,999
	$200,000–$299,999
	$300,000–$399,999
	$400,000–$499,999
	$500,000–$749,999
	$750,000–$999,999
	$1,000,000–$1,499,999
	> $1,500,000
	Do not know
Property (house) value	< $50,000
	$50,000–$99,999
	$100,000–$199,999
	$200,000–$299,999
	$300,000–$399,999
	$400,000–$499,999
	$500,000–$749,999
	$750,000–$999,999
	$1,000,000–$1,499,999
	> $1,500,000
	Do not know
Property (house) mortgage balance	< $10,000
	$10,000–$49,999
	$50,000–$99,999
	$100,000–$199,999
	$200,000–$299,999
	$300,000–$399,999
	$400,000–$499,999
	$500,000–$749,999
	$750,000–$999,999
	$1,000,000–$1,499,999
	> $1,500,000
	Do not know