Disaster Assistance Winners and Losers

Abstract

Problem, research strategy, and findings

Disaster assistance in the United States has faced criticism for widening the unequal impacts of disasters, but little is known about whether and how this phenomenon applies to businesses. Small businesses make up most businesses in the United States, but they are particularly vulnerable to hazards given their relative lack of capital. Because recovery assistance to businesses is primarily loan based, this lack of capital can create conflicts in how aid is perceived and allocated. Assistance providers must balance aiding the most severely damaged businesses and lending to those that will be able to repay; for small business, the threat of additional debt can make even low-interest loans seem risky. With this research I attempted to better understand how these competing factors play out in recovery through regression analyses of approved loan amounts and loan utilization decisions in Galveston (TX) after Hurricane Ike. I found that businesses with higher repayment ability such as larger businesses, older businesses, and corporations were approved for high loan amounts. Smaller businesses, businesses with higher damage, and businesses with longer loan terms were less likely to use the loans in their recovery, despite being approved. These findings suggest that businesses with the resources to recover were more likely to be the ones benefiting from additional disaster assistance.

Takeaway for practice

These findings suggest that planners may need to create their own recovery programs specifically targeting subgroups of businesses that are important to their communities. Although important to many economic development initiatives, very small businesses, entrepreneurs, and sole proprietors may not benefit from federal assistance, particularly if they were severely damaged.

Keywords:

• community resilience
• disaster assistance
• disaster planning
• small business

ACKNOWLEDGMENTS

I am grateful to Dr. Ann Forsyth and the three anonymous reviewers for their valuable comments on this article.

RESEARCH SUPPORT

This work was supported by the Center for Risk-Based Community Resilience Planning, a NIST-funded Center of Excellence. The Center is funded through a cooperative agreement between the U.S. National Institute of Standards and Technology and Colorado State University (Grant Number 70NANB15H044). The views expressed are those of the author, and may not represent the official position of the National Institute of Standards and Technology or the U.S. Department of Commerce.

Supplemental Material

Supplemental data for this article can be found on the publisher’s website.

Notes

1 The definition of small business can change based on country, organization, and industrial sector (Hait, 2021). The SBA Office of Advocacy generally defines small businesses as having fewer than 500 employees (Kobe & Schwinn, 2018), but there can be a lot of economic variation within this larger category (Highfill et al., 2020). Many organizations define small businesses as having fewer than 100, 50, or even 20 employees (Highfill et al., 2020). Therefore, although the businesses in this study are considered small by SBA because they have fewer than 500 employees, the research questions posed in this study are aimed at the variation within this definition of small business and whether relatively smaller businesses benefit from disaster assistance.

2 Business size, measured by number of employees, is often used as an indicator of the amount of capital and resources a business has (Webb et al., 2000; Zhang et al., 2009). However, cash flow, profitability, and available cash reserves are all important factors when determining repayment ability. I did not include these in this study due to limitations in the available data.

3 The flood depth maps did not report exact depths but rather 2-ft ranges of inundation (specifically 0 ft, <2 ft, 2–4 ft, 4–6 ft, 6–8 ft, 8–10 ft, and >10 ft), so flood depth was coded at the midpoints and 0, 1, and 1 for the 0 ft, <2 ft, and >10 ft categories, respectively.

Additional information

Notes on contributors

Maria Watson

MARIA WATSON ([email protected]) is an assistant professor in the M. E. Rinker, Sr. School of Construction Management at the University of Florida. She conducted this research while at the Department of Landscape Architecture and Urban Planning at Texas A&M University.