The demand and supply of credit for households

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.

Notes

¹ Desai and Mellor (1993) state that, ‘There are only seven studies that examine this issue quantitatively (Hesser and Schuh, 1962; Pani, 1966; Araujo, 1967; Long, 1968; Nyanin, 1969; Lins, 1972; Paulson, 1984). These studies provide 14 cases–4 in India, 3 in Kenya, 5 in United States, and 1 each in Brazil and Republic of Korea.’

² Marginal farmers own less than 1 hectare while small farmers own between 1 and 2 hectares. This is a standard definition used in government and census reports.

³ Though the formal credit institutions lend primarily for the productive purposes, the informal credit institutions lend for both the consumption and production purposes.

⁴ The interest rate function is subject of the discussion in Section ‘The interest rate function’.

⁵ Reference to author's earlier publication removed for the double anonymous peer review process.

⁶ Loans taken for investment in land, business or house, etc. and for meeting the operating expenses in agriculture are considered productive loans. Consumption loans are loans taken for meeting contingencies, consumption and other needs.

⁷ The RBI report of ‘A Review of the Agricultural Credit System in India’, 1990.

⁸ The current interest rate regulations are: For loans below Rs. 25 000 the rate of interest charged is 12% and for loans between Rs. 25 000 and Rs. 200 000, the interest rate is 13.5%. For loans over Rs. 200 000, the banks are free to fix their own rates. (Information from the RBI.)

⁹ Loan size rationing occurs when the loan amount received by the borrower is smaller than the one they demanded.

¹⁰ This is calculated by using the village specific prices on irrigated and unirrigated land. The information on prices prevailing in the village was collected simultaneously during the survey.

¹¹ Financial assets, which were mainly in the form of savings for the surveyed households, were not included due to underreporting resulting in a lot of missing values.

¹² In the pilot study the respondents were also asked to report on the value of gold and jewellery that they have. This question was later dropped, as the respondents were reluctant to answer it and became suspicious of the surveyors. This was considered necessary in order to preserve the quality of the data and the trust between the surveyor and the respondent. This trade off resulted in an underestimation of the value of assets.

¹³ Paddy is the main crop and a majority of the households engaged in agricultural production produce it.

¹⁴ While conducting the household survey, questionnaires were filled simultaneously for village level variables, for each of the 66 sample villages.

¹⁵ Education is proxied by the ‘number of matriculates’ in the household. Matriculates are individuals who have completed at least 10 years of education but need two or more years to complete their senior school.

¹⁶ The interest rate function shows spikes that are present around 13% rate of interest for loans taken from formal institution.

¹⁷ The proportion of the irrigated land is over the total amount of operational holding [includes the amount of land owned plus (minus) the amount of land leased-in (leased-out)].

¹⁸ Additional information is needed on: whether the household did not borrow because it expected that it would be turned down. In addition, one should also have information on whether the household was loan size rationed. Nevertheless, in this model we progress with the restricted amount of information available in the data.

¹⁹ For instance, refer to UCO Bank (1999), Manager's Handbook, fourth edition.

²⁰ Of the households, 11.26% lease-in half or less than half of their operational holdings, whereas 15.32% of the households lease in more than half or all of their operational holdings from others.

²¹ This definition does not completely capture rationing. Additional information is needed on: whether the household did not borrow because it expected that it would be turned down. In addition, one should also have information on whether the household was loan size rationed. Nevertheless, in this model we progress with the restricted amount of information available in the data.

²² Major components of nonland wealth include farming equipment, houses or buildings, livestock, fruits or coconut trees, brass utensils.

²³ For example, banks and cooperatives have no use for small houses or huts. It is also difficult to sell these houses as the rural areas have close personal bonding and most of the people in the area know each other. People will generally not buy the house because it might be uncomfortable to live there when you know that the acquaintances that you displace might not have any other place to stay.

²⁴ This is not surprising since the interest rates are administered by the commercial and the development banks. In addition, a large number of loans (more than 17% in the sample) are taken from friends and relatives.

²⁵ The diagnostics of the Double Hurdle model does not necessarily reveal better results than the type 3 Tobit model, which is probably a result of the rather strong assumptions of the model.