Date of Graduation

12-2015

Document Type

Thesis

Degree Name

Master of Science in Agricultural Economics (MS)

Degree Level

Graduate

Department

Agricultural Economics and Agribusiness

Advisor

Bruce L. Ahrendsen

Committee Member

Bruce L. Dixon

Second Committee Member

Charles B. Dodson

Keywords

Social sciences; Biological sciences; Agricultural resources management survey; Department of Agriculture; Farm debt; Farm service agency; Loans; Response error

Abstract

Many studies have used the U.S. Department of Agriculture’s (USDA) Agricultural Resource Management Survey (ARMS) to research various aspects involving the agricultural sector in the United States. Since nonresponse and inaccurate reporting may cause significant bias in statistical analysis, research was conducted to determine the magnitude of response error on the farm debt section of the ARMS Phase III. A multinomial logit model identified demographic, structural, and financial characteristics of FSA Farm Loan Program (FLP) borrowers who refused to indicate if they had end of year farm debt, or who accurately or inaccurately classified their farm operations as having end of year farm debt on the ARMS for 2001, 2004, 2006, and 2007. Additionally, estimates of the magnitude of response errors in ARMS for both FSA direct and guaranteed FLPs were estimated. The current study found that 12.9 percent of the direct FLP respondents and 9.9% of the guaranteed FLP respondents indicated “no” on the “Owe Money” question when they should have indicated “yes”. Also, those responding “no” were found to have their ARMS total debt outstanding less than their FSA total debt outstanding. Direct FLP operators were more likely to report “no” and, therefore, under-report end of year debt in the ARMS if they had a lower total FSA debt outstanding balance, had a greater value of crop production relative to total production, or had a lower gross cash farm income. Guaranteed FLP operators were more likely to under-report their debt in the ARMS if they had an operating line of credit loan, had a greater share of production from crops, had a lower gross cash farm income, were in survey year 2004, or were in survey year 2007. They were less likely to under-report their debt if they either had some college education, were Socially disadvantaged eligible, or were beginning farmer eligible. These results allow future researchers using ARMS data to appraise operator debt status to be better informed about potential data limitations.

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