Nontraditional agricultural equipment lending trends in the Agricultural Resource Management Survey and Uniform Commercial Code data

Master of ScienceDepartment of Agricultural EconomicsJennifer IfftThe U. S. Department of Agriculture’s official farm debt estimates are a vital source of information on the financial characteristics and conditions of farms nationwide and support the economic stability of the farm economy. Farm sector debt estimates are used by government officials and agricultural sector stakeholders to inform policy and financial decisions. Farm debt is categorized by both the debt type (real estate or nonreal estate) as well as the lender. The Agricultural Resource Management Survey (ARMS) serves as the main data source for agricultural lending not subject to public reporting, referred to in official debt estimates as “Individuals and Others.” One lender type that often falls in this category is nontraditional lenders, such as vendor finance divisions and collateral-based finance companies. Recent studies have suggested that nontraditional lending volumes and market share may be increasing, but this increase may not be reflected in official farm sector debt estimates. The unique role of ARMS data in official farm debt estimation motivates analysis of the accuracy of its measurement of nontraditional lending. This study makes use of data from Uniform Commercial Code (UCC) filings, which contain agricultural equipment liens. Given that nearly all loans secured by equipment, or with a lien on farm equipment, have an associated UCC filing, this dataset provides a population measure of agricultural equipment debt levels. This study introduces UCC lien filing data as a corroborative resource for farm debt analysis and statistically analyzes the differences in the measurement of debt sourced from nontraditional lenders between UCC lien filing data and ARMS. The research question is whether ARMS underestimates nontraditional lending volume and market share. The primary finding is that nontraditional debt reported in ARMS is biased downward. This downward bias is large and is consistent across time and region. ARMS data may have limited value in informing the “Individuals and Others” lending category in official U.S. farm debt estimates