First Symposium on Policy Research


Severe Weather and Bank Performance

B.T. Ewing, Texas Tech University, Lubbock, TX; and S. E. Hein and J. B. Kruse

This study examines bank performance in several tornado-prone areas and hurricane-prone areas. When a hurricane or tornado outbreak occurs, evidence indicates that regional labor markets, insurance markets, as well as housing markets exhibit strong responses to the event (e.g., Ewing and Kruse, 2002; Ewing, Kruse and Thompson, 2003; Ewing and Covarrubias, 2003; Ewing, Hein, and Kruse, 2004; and Ewing, Kruse and Wang, 2004). There are several reasons why we might expect a community bank to be vulnerable to economic shocks caused by a natural disaster. Community banks tend to be less diversified geographically than their larger competitors. According to conventional wisdom, community banks have greater credit risk due to the geographic concentration of their loan portfolio and therefore are more vulnerable to local economic shocks. A second source of vulnerability is the disproportionate number of small business loan customers typical to many community banks. Due to their ability to collect soft information, community banks are considered a significant source of credit for small businesses which are particularly vulnerable to natural disasters. In this study we examine the time series behavior of regional bank performance in response to severe wind storm events. The MSA markets that we study include Nashville, Oklahoma City, and Fort Worth-Arlington, each of which has been hit by one or more major tornadoes; and Corpus Christi, Miami, and Wilmington, NC each of which has been hit by one or more major hurricanes. Our analysis utilizes event study methodology that allows for the possibility that changes in measures of bank performance may be significantly affected by a severe wind storm. Our analysis relies on three bank ratios: nonperforming loans to total loans, net chargeoffs to total loans, and return on assets (ROA) in an attempt to capture the impact on community banks both in the short term and in the longer term after a wind disaster. We also utilize CAMELS ratings as summary measures of bank performance. Notes: CAMELS stands for Capital adequacy, Asset quality, Management, Earnings, Liquidity and Sensitivity to market risk. Bank examiners assign and overall rating from 1 to 5. The safest banks are rated a 1 with a 5 indicating the riskiest banks. An important breakpoint is if the CAMELS rating is worse than a 2. A CAMELS rating of 3 is likely to prompt supervisory action. However the use of CAMELS data depends upon availability.

Session 2, Economics and Weather: Methods and Applications
Thursday, 2 February 2006, 8:30 AM-12:00 PM, A307

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