Microeconomic impacts of a statefunded farmer loan program

Glenn D Pederson, Wonho Chung, Roelof Nel

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

The purpose of this paper is to determine if there are positive microeconomic effects from a statefunded loan participation program on farm productivity and investment behavior. The authors take the approach that access to credit solves a liquidity problem. If a credit constraint exists it results in a suboptimal allocation of resources and a reduction in farm output and profitability. A twostage regression model approach is used to analyze farmer survey and loan application data. In the first stage, a probit regression model is used to identify the farmers who are likely to be credit rationed. In the second stage, switching regression models are used to observe the effect of credit rationing on farm productivity and on farm investment behavior. It is found that there are liquidity effects of credit constraints for a significant share of the beginning and lowresource farmers who participated in the statefunded farm loan program. After controlling for various farm and farmer characteristics, the estimated productivity and investment demand equations imply that a 1 percent increase in credit received by credit constrained farmers under the state program increased their gross income by about 0.49 percent, and their investments in depreciable assets by about 0.33 percent. This paper is the first to apply the switching regression model to a statefunded farm loan program for the purpose of evaluating the financial impacts on farmer participants.

Original languageEnglish (US)
Pages (from-to)5-21
Number of pages17
JournalAgricultural Finance Review
Volume72
Issue number1
DOIs
StatePublished - May 4 2012

Keywords

  • Agriculture
  • Credit constraint
  • Farm productivity
  • Farms
  • Government policy
  • Loans
  • Microeconomics
  • Real estate investment
  • Statefunded loans
  • Switching regressions
  • United States of America

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