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The demand and supply of credit for households

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  • Ranjula Bali Swain

Abstract

The demand and supply of credit in the rural credit markets is investigated in this article using household data from India. The aim is to study the effects of household, farm productive characteristics and the policy variables on the demand and supply of credit. A type 3 Tobit model is estimated which corrects for sample selection and endogeniety bias. In addition, a generalized Double Hurdle model is estimated where the information on the household's access to credit is included to estimate the demand and supply of credit. The results suggest that the size of the operational holdings, net-wealth, dependency ratio, educational level of the household and the wages and output prices are important determinants of the demand and supply of credit for farm households. The Double Hurdle model confirms that the 'size of land owned' plays a crucial role in whether the household has access to a loan or not.

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File URL: http://www.tandfonline.com/doi/abs/10.1080/00036840600749516
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Bibliographic Info

Article provided by Taylor & Francis Journals in its journal Applied Economics.

Volume (Year): 39 (2007)
Issue (Month): 21 ()
Pages: 2681-2692

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Handle: RePEc:taf:applec:v:39:y:2007:i:21:p:2681-2692

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Cited by:
  1. Festic, Mejra & Kavkler, Alenka, 2012. "The Roots of the Banking Crisis in the New EU Member States: A Panel Regression Approach," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 20-40, March.
  2. Doan, Tinh & Gibson, John & Holmes, Mark, 2010. "What determines credit participation and credit constraints of the poor in peri-urban areas, Vietnam?," MPRA Paper 27509, University Library of Munich, Germany, revised 17 Dec 2010.
  3. Kangogo, Daniel & Lagat, Job & Ithinji, Gicuru, 2013. "The Influence of Social Capital Dimensions on Household Participation in Micro-Credit Groups and Loan Repayment Performance in Uasin Gishu County, Kenya," MPRA Paper 48624, University Library of Munich, Germany.
  4. Evzen Kocenda & Martin Vojtek, 2011. "Default Predictors in Retail Credit Scoring: Evidence from Czech Banking Data," William Davidson Institute Working Papers Series wp1015, William Davidson Institute at the University of Michigan.

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