Scientific Research and Essays

  • Abbreviation: Sci. Res. Essays
  • Language: English
  • ISSN: 1992-2248
  • DOI: 10.5897/SRE
  • Start Year: 2006
  • Published Articles: 2768

Full Length Research Paper

Analysing social attributes of loan default among small Indian dairy farms: A discriminant approach

Mukesh Kumar Sinha*
  • Mukesh Kumar Sinha*
  • Directorate of Water Management, Bhubaneswar-751023, Odisha, India.
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J. P. Dhaka
  • J. P. Dhaka
  • National Dairy Research Institute, Karnal-132001, Haryana, India.
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Biswajit Mondal
  • Biswajit Mondal
  • Central Rice Research Institute, Cuttack-753006, Odisha, India.
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  •  Accepted: 20 January 2014
  •  Published: 30 January 2014


The study examines the socio-economic factors discriminating defaulters and non-defaulters of credit repayment. Multi-stage sampling design was adopted for selection of farm respondents. The data were collected through structured questionnaire by personal interview method. A linear discriminant function considered to examine the relative importance of different factors in discriminating between non-defaulters and defaulters. The result revealed that per capita income from crop and milk production, expenditure to total income, earning adults and off-farm income explained major share in discriminating the non-defaulters from defaulters. The mean discriminant score for the non-defaulters (Z1) and defaulter (Z2) were found to be 0.316 and -1.322, respectively. The critical mean discriminant score (Z) for the two groups was found to be -0.503. The high value of Z corresponds to non-defaulter and low value to defaulter. Later the derived classification analysis was observed that 50 out of 83 defaulters and 32 out of 37 non-defaulters were rightly classified in Z function. Thus, grouped cases classified correctly as 68.33% as factors of default. Hence, the model is found to be valid to predict whether an unknown borrower is likely to be defaulter or non-defaulter more precisely.

Key words: Discriminant function, credit, defaulter, dairy farmers.