Heterogeneity of farm loan packaging term decisions: a finite mixture approach

ABSTRACT

This article revisits the minority borrowers’ discrimination issue in farm lending by departing from traditional loan approval-rejection or default rate-based analytical models to focus on loan packaging decisions. This study analyses such decisions using a Finite Mixture Model that optimally separates the borrowers into two sub-classes allowing for a priori unspecified heterogeneity in borrowers’ data, which has not been accounted for in previous loan discrimination analyses. Results show that non-white farm borrowers tend to receive larger loans among those in the lower loan latent class, but receive relatively lower loans in the larger loans borrower category. These farmers are also charged higher interest rates vis-à-vis their peers in both the low and high interest rate latent classes. This study’s results also indicate that male borrowers are accommodated with larger loans and longer maturities in all loan amount and maturity latent classes. This study validates the interplay among significant trends in loan packaging terms for racial and gender minority borrowers that seems logical from the lenders’ credit risk management perspective.

KEYWORDS:

• Loan packaging
• interest rates
• loan amount
• maturity
• racial bias
• gender bias
• heterogeneity
• mixture model

JEL CLASSIFICATION:

• Q14
• J15
• J16
• C21

Data availability statements

The data that support the findings of this study are available on request from the corresponding author, Cesar L. Escalante. The data are not publicly available due to the propriety, sensitive, and confidential nature of business- and borrowing transaction-specific information associated with each individual farm borrower of the Farm Service Agency that could compromise the privacy of each farm borrower observation.

Disclosure statement

No potential conflict of interest was reported by the authors.