Pre-recession efficiencies and input allocation decisions of agricultural and critically insolvent banks

ABSTRACT

The late 2000s’ economic recession is considered the longest economic downturn since the 1930s Great Depression. Declining real estate values ignited an increase in loan defaults and mortgage foreclosures that led to a surge of bank failures at a rate not experienced by the U.S. banking industry since the 1980s. A total of 509 bank failures were recorded by the FDIC from January 2007–December 2014, with nearly 60% of these failures occurring in 2009 and 2010. In contrast, there were only 24 bank failures in the U.S. during the 7-year period prior to 2007. This study analyzed certain components of operating decisions made by banks that either survived or became critically insolvent during the late 2000s financial crisis using an Input Distance Stochastic Frontier function to estimate the technical efficiency (TE) and allocative efficiency (AE) between agricultural banks and non-agricultural banks. This efficiency analysis was applied to a 7-year pre-recession period and is designed to final out any early warning signals that decrease the efficiency level of banks. Results suggest that survival banks were more technically efficient than critically insolvent banks, and banks’ tendency to utilize cheaper inputs were more likely to stand the economic crisis.

KEYWORDS:

• Bank efficiencies
• agricultural finance
• technical efficiency
• financial crisis

JEL CLASSIFICATION:

• B21
• Q14

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

¹ As an additional measure of risk, a robustness check using Lepetit and Strobel’s (2013) Z-score was used. Results using this measure of risk were consistent with the loan quality index and financial risk index. Results using this additional risk measure is available from the authors upon request.

² Due to the length and number of parameters for the models, the results for the full model as well as the parameter estimates for the agricultural bank model are included in appendix form. The results for these two subsets of specialized banks mirror those obtained for the general model using all bank observations.

³ Marginal cost is calculated as input price divided by marginal product (MP). MP is calculated as the change in output divided by the change in input level (Pindyck and Rubinfeld 2009).