Beginning farmer and rancher credit usage by socially disadvantaged status

PurposeThe purpose of this paper is to examine credit usage by beginning farmers and ranchers (BFR). BFR credit usage is stratified by location (state) and by socially disadvantaged farmer and rancher (SDFR, also known as historically underserved) status. SDFR groups are defined to include women; individuals with Hispanic, Latino or Spanish Origin; individuals who identify as American Indian or Alaskan Native, Black or African American, Asian, Native Hawaiian or other Pacific Islander. Non-SDFR is defined as individuals who identify as non-Hispanic, White men.Design/methodology/approachThe US Department of Agriculture’s Census of Agriculture, Agricultural Resource Management Survey (ARMS) is linked with Farm Service Agency (FSA) loan program administrative data to estimate shares of BFR operations using FSA credit. Census data provided information on population changes in total farms and BFR operations from 2012 to 2017 which are compared by SDFR status.FindingsResults reveal differences among BFR operations active in agricultural credit markets by SDFR status and state. BFR were more common among SDFR groups as well as in regions where farms tend to be smaller, such as the Northeast, compared to a more highly agricultural upper Midwest. Among BFR, non-SDFR are more likely to utilize credit than SDFR, however, FSA appeared to be crucial in enabling BFR and especially beginning SDFR groups to access loans.Originality/valueThe results are timely and of keen interest to researchers, industry and policymakers and are expected to assist in developing and adjusting policies to effectively promote and improve BFR success in general and for beginning SDFR groups.

Mapping the Location and Extent of 2019 Prevent Planting Acres in South Dakota Using Remote Sensing Techniques

The inability of a farmer to plant an insured crop by the policy’s final planting date can pose financial challenges for the grower and cause reduced production for a widely impacted region. Prevented planting is primarily caused by excess moisture or rainfall such as the catastrophic flooding and widespread conditions that prevented active field work in the midwestern region of United States in 2019. While the Farm Service Agency reports the number of such “prevent plant” acres each year at the county scale, field-scale maps of prevent plant fields—which would enable analyses related to assessing and mitigating the impact of climate on agriculture—are not currently available. The aim of this study is to demonstrate a method for mapping likely prevent plant fields based on flood mapping and historical cropland maps. We focused on a study region in eastern South Dakota and created flood maps using Landsat 8 and Sentinel 1 images from 2018 and 2019. We used automatic threshold-based change detection using NDVI and NDWI to accentuate changes likely caused by flooding. The NDVI change detection map showed vegetation loss in the eastern parts of the study area while NDWI values showed increased water content, both indicating possible flooding events. The VH polarization of Sentinel 1 was also particularly useful in identifying potential flooded areas as the VH values for 2019 were substantially lower than those of 2018, especially in the northern part of the study area, likely indicating standing water or reduced biomass. We combined the flood maps from Landsat 8 and Sentinel 1 to form a complete flood likelihood map over the entire study area. We intersected this flood map with a map of fallow pixels extracted from the Cropland Data Layer to produce a map of predicted prevent plant acres across several counties in South Dakota. The predicted figures were within 10% error of Farm Service Agency reports, with low errors in the most affected counties in the state such as Beadle, Hanson, and Hand.

Developing and Implementing Farm Stress Training to Address Agricultural Producer Mental Health

Farmers and ranchers (agricultural producers) have higher psychological distress and suicide rates than the general population. Poorer mental health status and outcomes among producers are often attributed to the continuously challenging economic, social, and climate-related changes to agriculture as an occupation and industry. This article describes the development of a training program for agribusiness professionals from the U.S. Department of Agriculture Farm Service Agency (N = 500) who work with producers, as they regularly interact with producers and thus are in a position to readily offer helpful mental health resources. The goal of the program was for agribusiness professionals to build skills and confidence to identify and respond to distressed producers. The educational program was offered primarily online and included a 1-day in-person training to practice skills to communicate with distressed producers and refer them to appropriate mental health resources. Evaluation of the program demonstrated participants experienced gains in knowledge and skills related to identifying and helping distressed producers.

Do farm service agency borrowers' double minority labels lead to more unfavorable loan packaging terms?

PurposeThis study adds a new dimension in the study of racial and gender bias in farm lending. Most previous studies analyzed the separate effects of race and gender attributes on loan approval decisions. The analysis focuses on the stipulation of loan terms (loan amount, interest rate and maturity) among approved farm loan applications. The time period analyzed spans from 2004 until 2014 during which the government has undertaken reforms to improve delivery of loan services to its clientele of minority farmers. Thus, this study's findings could help validate the effectivity of such institutional reforms affecting Farm Service Agency (FSA) lending operations.Design/methodology/approachThis study utilizes a national direct loan origination data from the FSA of the U.S. Department of Agriculture (USDA) collected from 2004 to 2014. The analysis begins by identifying significant differences in cross-tabulations of loan terms among different racial and gender classes. Seemingly unrelated regression (SUR) regression techniques are then applied for a system of equations involving the three loan packaging components. The combined effects of the prescribed loan packaging terms are subsequently analyzed under a simulation-optimization framework.FindingsRegression results validate that indeed, relative to White American borrowers, certain minority borrowers are accommodated with lower loan amounts at higher interest rates and with shorter maturities. However, these decisions seem to be prompted by credit risk management considerations. The most compelling findings include the insignificance of all double minority labeling variables, except for the interest rate equation that even produced favorable results for Hispanic American females. Simulation-optimization results further reinforce that even when one or two unfavorable loan terms are included in the packaging, double minority borrowers end up with better profitability and liquidity positions.Practical implicationsThis study provides a different perspective in dealing with the controversial minority bias in lending by presenting evidence gathered from a government farm lending institution. The USDA-FSA has been sued in numerous occasions by minority borrowers. Since then, however, it has deliberately implemented institutional reforms to rectify previous errors. This study provides empirical evidence strengthening FSA's claim of its intention to improve its delivery of loan services, especially for its socially disadvantaged borrowers with double minority classification.Originality/valueThis study pioneers the analysis of the double minority labeling effect on farm lending decisions. Its contributions to literature are further enhanced by its goal to validate the effectiveness of FSA institutional reforms undertaken since the early 2000s in order to improve credit access of and delivery of credit services to minority farm borrowers, especially those that belong to more than one minority classification.

Farm service agency employee intentions to use weather and climate data in professional services

Agricultural service providers often work closely with producers, and are well positioned to include weather and climate change information in the services they provide. By doing so, they can help producers reduce risks due to climate variability and change. A national survey of United States Department of Agriculture Farm Service Agency (FSA) field staff (n = 4621) was conducted in 2016. The survey was designed to assess FSA employees’ use of climate and weather-related data and explore their perspectives on climate change, attitudes toward adaptation and concerns regarding climate- and weather-driven risks. Two structural equation models were developed to explore relationships between these factors, and to predict respondents’ willingness to integrate climate and weather data into their professional services in the future. The two models were compared with assess the relative influence of respondents’ current use of weather and climate information. Findings suggest that respondents’ perceptions of weather-related risk in combination with their personal observations of weather variability help predict whether an individual intends to use weather and climate information in the future. Importantly, climate change belief is not a significant predictor of this intention; however, the belief that producers will have to adapt to climate change in order to remain viable is. Surprisingly, whether or not an individual currently uses weather and climate information is not a good predictor of whether they intend to in the future. This suggests that there are opportunities to increase employee exposure and proficiency with weather and climate information to meet the needs of American farmers by helping them to reduce risk.

Stored Grain Pack Factor Measurements for Soybeans, Grain Sorghum, Oats, Barley, and Wheat

Grain and oilseed crops stored in bins undergo compaction due to overbearing pressure of the grain inside the structure. Thus, volume measurements of grain in bins need to be combined with the amount of packing (usually called pack factor) in addition to the initial density so that the mass in the structure can be calculated. Multiple pack factor prediction methods are in use in the grain industry, but they have only been validated in the literature and compared with field data for corn and hard red winter wheat. Predictions from WPACKING, the program in ASABE Standard EP413.2, and two standard USDA methods, the USDA Risk Management Agency (RMA) and USDA Farm Service Agency-Warehouse Licensing and Examination Division (FSA-W) methods, were compared to field measurements of 92 bins containing soybeans, grain sorghum, oats, barley, or soft white or durum wheat. The WPACKING predictions had the lowest absolute average error of predicted mass for soybeans, grain sorghum, barley, and wheat, while the FSA-W method had the lowest error for oats. The RMA method gave the largest prediction errors for all five crops and struggled especially with the low-density, high-compaction crops oats and barley, giving average percent absolute errors near or above 10% in both cases. Overall, WPACKING, the RMA method, and the FSA-W method had average percent absolute errors of 2.09%, 5.65%, and 3.62%, respectively, for the 92 bins. These results can be used to improve pack factor predictions for the grain industry. Keywords: Barley, Grain, Grain sorghum, Oats, Pack factor, Sorghum, Soybeans, Steel and concrete bins, Stored grain inventory, Test weight, Wheat.

LOOKING BEYOND FARM LOAN APPROVAL DECISIONS: LOAN PRICING AND NONPRICING TERMS FOR SOCIALLY DISADVANTAGED FARM BORROWERS

This study utilizes Farm Service Agency lending data to verify if previous racial and gender bias allegations still persist in more recent lending decisions. Beyond loan approval decisions, this study focuses on trends in direct loan packaging terms for approved single proprietorship farm borrowers. Results indicate that although no significant disparities were noted in loan amounts and maturities prescribed for various racial and gender minority groups, nonwhite male and female borrowers were usually charged higher interest rates than the others. Loan pricing differentials could have been the lenders' strategy for price management of borrowers' credit risks.

FSA farm loan repayment under economic recession and drought conditions

Purpose The purpose of this paper is to analyze the repayment records of Farm Service Agency (FSA) borrowers in two distinct US farming regions that have been experienced serious drought conditions even as the US economy was going through a recession. The analysis will identify factors that significantly influence both the probability of FSA borrowers’ survival (capability to remain in good credit standing) and temporal endurance (or length of period of good standing with creditor). Design/methodology/approach This analysis utilizes a data set of farm borrowers of the Farm Service Agency that regular farm lenders have classified as “marginal” relative to other borrowers. The research goal is addressed by confining this study’s regional focus to the Southeast and Midwest that have both dealt with financial stress arising from abnormal natural and economic conditions prevailing during the same time period. A split population duration model is employed to separately identify determinants of the probability and duration of survival (condition of good credit standing). Findings This study’s results indicate that larger loan balances, declining commodity prices, and the severity of drought conditions have adversely affected both the borrowing farms’ probability of survival and temporal endurance in terms of maintaining non-delinquent borrower standing. Notably, Midwestern farms have been relatively less affected by drought conditions compared to Southeastern farms. This study’s results validate the contention that the farms’ capability to survive and the duration of their survival can be attributed to differences in regional resource endowments, farming activities, and business structures. Originality/value This study’s analytical framework departs from the basic duration model approach by considering temporal endurance, in addition to survival probability analysis. This study’s original contributions are enhanced by its specific focus on the contrasting farm business structures and operating environments in the Midwest and Southeast regions.