A triple hurdle model of US commercial bank use of guaranteed operating loans and interest assistance

Author:

Ahrendsen Bruce L.,Dixon Bruce L.,Settlage Latisha A.,Koenig Steven R.,Dodson Charles B.

Abstract

PurposeThe purpose of this paper is to estimate a three‐equation model of US commercial bank usage of the Farm Service Agency's (FSA) guaranteed operating loan and interest assistance programs. Also, to identify the key farm and banking variables that affect the decision to use loan guarantees and the volume of loans with interest assistance.Design/methodology/approachA triple hurdle, three‐equation system is estimated to model three decisions: to participate in the FSA operating loan program; whether to use interest assistance given the decision to participate in the operating loan program; and then the degree of participation in the interest assistance program. Statistical selection is modeled. Data on almost all commercial banks in the USA from 1995 to 2003 are used in the estimation sample.FindingsStatistical selection is statistically significant so selection must be included in the models. Variables reflecting state‐level characteristics such as farm debt servicing ratio, individual bank loan‐to‐asset ratio, bank size and the general guaranteed loan and interest assistance environment are significant in all three equations. Intensity of interest assistance use varies markedly across states.Originality/valueThe interest assistance program has high subsidy costs and is an important source of support for financially marginal farmers. Scant prior research has investigated this program. The present study also shows that modeling interest assistance usage must be embedded in a larger model to give a complete specification.

Publisher

Emerald

Subject

Agricultural and Biological Sciences (miscellaneous),Economics, Econometrics and Finance (miscellaneous)

Reference15 articles.

1. Ahrendsen, B.L., Koenig, S.R., Dixon, B.L., Dodson, C.B. and Settlage, L.A. (2004), “Analysis of borrower and lender use of interest assistance on FSA guaranteed farm loans”, Staff Paper 02, Department of Agricultural Economics and Agribusiness, University of Arkansas, Fayetteville, July, available at: purl.umn.edu/15778 (accessed 12 September 2010).

2. Bard, S.K., Barry, P.J. and Ellinger, P.N. (2000), “Effects of commercial bank structure and other characteristics on agricultural lending”, Agricultural Finance Review, Vol. 60, pp. 17‐31.

3. Barry, P.J. and Pepper, W.H. (1985), “Effects of holding company affiliation on loan/deposit relationships in agricultural banking”, North Central Journal of Agricultural Economics, Vol. 7 No. 2, pp. 65‐73.

4. Boyes, W.J., Hoffman, D.L. and Low, S.A. (1989), “An econometric analysis of the bank credit scoring problem”, Journal of Econometrics, Vol. 40 No. 1, pp. 3‐14.

5. Dodson, C.B. and Koenig, S.R. (2003), “Explaining county‐level variability in Farm Service Agency farm loan programs”, Agricultural Finance Review, Vol. 63 No. 2, pp. 193‐212.

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