The demands for funds by agricultural households : evidence from rural India

World Bank Reprint Series: Number 341 Farrukh Iqbal The Demands for Funds by Agricultural Households: Evidence from Rural India Reprinted with permission from Tlhe Journal of Development Studies, vol. 20, no. 1, October 1983, published by Frank Cass and Company, Ltd., London, U.K.  The Demands for Funds by Agricultural Households: Evidence from Rural India by Farrukh Iqbal* This study presents estimates of borrowing functions based on rural household data from India. It improves upon existing work in three key areas. First, it is shown that existing studies have used an itnappropriate definition of the demand for funds, which when recti- fied produces quite different results. Second, the interaction between agricultural technical change and the rural finance market is examined and it is shown that farmers in a position to benefit from technical change tend both to borrow more and to face lower interest rates. Third, it is shown that farm-specific interest rates, when intro- duced endogenously, are quite sensitive to personal and locational characteristics and are significant determinants of borrowing. I. INTRODUCTION Existing studies of the determinants of the borrowing behaviour of farm- households tend to suffer from two biases: a truncation bias, hitherto unrecognised in the relevant literature [e.g. Hesser and Schuh, 1962; Pani, 1966; Long, 1968; Lins, 1972; Ghatak, 1976], arising from the definition of the dependent variable; and a simultaneity bias (recognised but rarely corrected for) arising from the endogeneity of the interest rate used to denote the cost of borrowing. The principal contribution of this study is the estimation of borrowing functions free from these biases. The truncation bias is formally similar to that arising in the case of female market labour supply where non-market wages and hours are unobserved. In the borrowing case, because the conventional empirical definition of borrowing does not take into account borrowing from internal sources (e.g. savings accounts) and/or lending, the dependent variable is effectively trun- cated at zero and neither 'internal' borrowing nor interest rates faced by those who do not borrow in the market are observed in the sample. A number of approaches have been devised to obtain consistent estimates for *The author, currently a staff member of the World Bank, is grateful to Surjit Bhalla, Kenneth Wolpin, Robert Evenson, Dennis DeTray, Daniel Kohler and an anonymous referee for their very useful comments at different stages in the preparation of this paper. In its present form it is a considerably revised version of a note prepared with support from Girant No. AID/OTR-G- 1822 from the Agency for International Development extended when the author was a post-doctoral research fellow at the Rand Corporation. Views and errors to be found in this paper are to be attributed to the author alone.  DENMAND FOR FtNDS BY AGRICULTURAL hlOUSEHOILDS 69 labour supply functions under such conditions [Smith, 1980]. Our task is made simpler by the fact that the censoring of the dependent variable can be corrected by simply redefining it to include adjustments in both the asset and the liability positions of the household. The unobserved interest rates are imputed in accordance with a procedure suggested in Heckman [1979]. An additional advantage of the imputation procedure is tlat it allows us to account for the possibility of the simultaneous determination of the interest rate and the amount borrowed and therebv to correct for the simultaneity bias. Our results suggest that much is gained from such an exercise. While the above considerations are of general relevance, the study is of particular importance to agricultural finance issues in less-developed coun- tries (LDCs) where 'official' credit programmes have become important components of development expenditure. It is reported that rural credit of over $30 billion is now disbursed annually by LDC governments and that over $5 billion has been spent by international agencies over the last several decades [Adams atnd Gralam, 1981]. The empirical basis of such lending programmes, however, is surprisingly weak, as can easily be gauged from a recent survey of the relevant literature [David antd Mver, 1979]. Among others, two important relationships have received inadequate or inappropri- ate treatment. One is the relationship of borrowing to interest rates and the other is the link between the demand/supply of credit and the rate or possibility of agricultural technical change. Both these issues are important to LDC agriculture since concessional interest rates are the centre-piece of official credit policv and agricultural innovation fi Iai Green Revolution is widely believed to be the most important means of development in such countries. Some of the major shortcomings of earlier work are examined in Section 1, and a mixed life-cycle'-permanent-income model of borrowing is pro- posed as a suitable theoretical foundation for the present analysis. Section III 'presents an empirical analysis of the demand and supplv of funds. The data are obtained from a comprehensive national (panel) survev of approxi- mately 3,000 farm households in India for the years 1968-71, conducted bv the National Council of Applied Economic Research (NCAER). The empirical analysis is guided both by theory and by special characteristics of the data at hand. Pertinent details regarding the data and sample-size determination are provided in the appendix. Section IV summarises the important findings of the study. II. So.M1E' PRFEL.lSIINAR' C('()N'SII)ER,R'I'I()NS Perhaps the most serious drawback of conmentionail studies is that they define the demand for credit to be simplv the amount borro\'.ed from external sources. Ihis restricts the dependent variable to non-negative values. a feature which renders standard OI1S c-stiniation subject to bias. Such truncation hias is avtoided in the present analysis by taking a tlow-of- funds approach to the measurement of the dcniriiid for credit. According to this approach. the net demand for funds, B, can be expressed as the identity:  70 THE JOURNAL OF DEVELOPMENT STUDIES B = EB-EL-FA-CD + TI (1) where EB, EL refer to external borrowing and lending and therefore (EB- EL) refers to the change in liabilities; FA refers to the change in financial assets, CD to the change in the household's stock of consumer durables, and TI to the net transfer of income in the form of remittance and gifts. Previous studies have used EB, rather than B, as the measure of the demand for funds. The difference between the two measures is substantial as can be seen from Table 1 where the mean level of EB is shown to be over three times the mean level of B. The characterisation of the role of technical change in influencing the demand for funds by LDC farmers can also be improved upon. One wav to approach this matter is to consider the effects of technical change on farm incomes and productivity. The experience of South Asia in the late 1960s suggests that technical change involving new seeds and fertilizers (the major components of the Green Revolution) tends to raise farm incomes and productivity. Now, the greater the value of expected future income the greater will be the tendency to borrow in anticipation of it. Similarly, the higher the rate of return on capital. the greater will be the tendency to borrow and thereby employ more capital in production. Both of these effects can be captured by the use of a measure of investment opportunity, a term defined by Fisher [19301 as the opportunity to shift from one 'option' or possible income-stream to another. In the case of farm households, an improvement in investment opportunities can be thought of as an outward shift of the production-possibility frontier. Thus if we can distinguish empiri- cally between farmers who face different investment opportunities we should be able to evaluate the effect of technical change on the demand for funds. The empirical implementation of this notion is discussed in a later section. Most existing studies assume the interest of cost of borrowing to be an exogenous variable. However, since loan size could affect both the riskiness of the loan and its administrative cost [Bottomley, 1975], it may be more reasonable to assume that the interest charge is endogenouslv determined. The usefulness of either assumption can only be determined empiricallv; the two-stage estimation approach taken in this paper allows us to do this. The specification of any behavioural function depends on the underlving theoretical framework. We have adopted a mixed version of the life-cvcle/ permanent-income model as a guide to empirical specification. This approach is popular in the savings literature but has received surprisingly little attention in the LDC borrowing literature. Its advantages for our study lie in its ability to integrate consumption and production decisions as well as to allow for time-dependent behaviour. It yields the following determinants of the demand for borrowing (or saving, consumption and investment for that matter): age, initial endowment, current and expected input and output prices, the marginal cost of funds, and shifts in investment opportunities (denoting expected future income). Readers interested in a formal model along the above lines may turn to Iqbal [1981a].  DEMAND FOR FUNDS BY AGRICULTURAL HOUSEHOLDS 71 III. EMPIRICAL ANALYSIS The Strlucture of the Empirical Model The empirical model consists of two equations, one representing the demand for funds and the other in the form of a function relating the interest rate to its determinants, the supply of funds. Consider the latter function first. In a competitive market, three basic costs enter the nominal interest rate (Rn): the opportunity cost of providing a loan, the administrative cost of handling a loan, and the risk premium to be assigned to different borrowers. Thus the nominal interest-rate function can be written as: Rn = r1Z + r,B + r3X (2) where the vectors Z and X contain variables that affect the opportunity and risk costs of lending respectively, and the variable B denotes levels of borrowing and proxies for the administrative (as well as risk) cost of lending [Bottomnlev, 1975; Lonig, 1968]. In the empirical analysis below, the opportunity cost of funds is assumed to vary across villages in accordance with (a) source of loan and (b) prox- imity of the villages to market/urban centres. The rationale for the source- of-loan variable is that farmers who get loans from official lending agencies (e.g. rural banks or co-operative credit societies) get a subsidv, because such agencies are constrained to charge interest rates much lower than the market rate. The operations of these agencies are regulated by the government and subsidised loans are offered for 'development' purposes. Even if a person does not borrow from such agencies, their mere presence in the village should reduce average interest rates (because of reduction in moneylenders' monopoly power. for example) and residents of such villages will benefit. This effect is captured through the inclusion of an additional dummy vari- able which registers the presence or absence of official lending agencies in the village. Distance from market areas is a variable designed to capture lending costs incurred by village moneylenders (the source of 50 per cent of the loans in our sample) who may have to obtain their own funds from larger town moneylenders. Furthermore, distance is also likelv to affect the probability of having idle funds. A moneylender situated close to a town or with easy access to one is more likelv to have his stock of loanable funds placed on loan throughout the year, while those. in remote locations may have idle funds in the post-harvest season [Lonig, 1968]. The administrative cost of funds is perhaps best captured through the size of loan negotiated; i.e. the larger the loan, the smaller the unit cost of administering it. However, the size of loan could also carrv a risk cost, so that the risk would increase with the size of the loan. This possibilitv renders the expected sign ambiguous. Village population is used as an additional proxv for both administrative and opportunitv costs of lending. The larger a village, the greater the demand for funds and the easier it is to spread overhead costs and reduce  72 TIHIE JOUtRNAL. OF DEVELOPMNIENT STUI)IES per-unit expenses of lending. As far as opportunity costs are coicerned, the same arguments that make such costs a positive function of village remote- ness make them a negative function of village size. The risk cost of lending is proxied by all those variables that are likelv to affect repayment probability. From the lender's point of view such charac- teristics as quantity and quality of land owned, other assets owned, wage rate faced, age, family size and investment opportunities are likely to be good indicators of the income-earning ability and, by implication, loan repayment ability, of farmers. These personal and locational risk characteristics also affect the amount demanded. These characteristics will be discussed in the context of the borrowing function, which nmav be written as B = blY + b2Rn + b3TY (3) where Y is a vector of all those factors that theoretical considerations suggest ought to be determinants of the demand for funds, Rn is the nominal interest rate faced, and TY is a measure of transitory income. Among the elements of Y might be included such variables as age of farmers, initial endownment, current and expected wage, current and expected output prices and inea- sures of investment opportunity. From this list only current and expected prices are removed from consideration, on the assumption that thev are invariant in the cross-section given a competitive output market. It may appear that the same argument could be applied to input prices such as wages and interest rates. There is considcrable evidence, however, that factor markets in India are geographicallv imperfect and reveal considerable variations in factor returns. In the case of labour markets geographical immobility seems to give rise to waage variations [Rosenzweig, 1978]. while in the case of capital markaets interest rate variations arise in response to differences in transaction, administrative and risk costs as shown below. Our data do not contain individual wage information. TI'herefore, we have used the district-level average daily male agricultural wage (fronm Agli- c(ultaral Wages in India, 1970-71) as our measure of the opportunitv cost of household time. Of course, one c(Ould have gone in for greater refinement along the lines of sex-specific, skill-specific, and time-specific wages. Data constraints aside, such refinement was considered unnecessary to this par- ticulcar study since we have not elaborated a theoretical mnodel at a similar level of detail. The variable that has received most attention in previous studies is what we have called 'initial C*ndo\\ M1nt'. The proxy used here is a n.icail Ur, of the total area owned by the farm household (in hectares). Although a measure of gross or net cropped area, both owned and leased, miiglt contain more information about the household's wealth. such a measure cannot be used here because the act of leasing involves a capital accumulation decision that is, in the context of our model, made jointly with the borrowing decision. It could be argued that land ownership itself is subject to v,ariation and that current ownership may not reflect original endowvment. Hlowever, the land- ownership market in rural India (as oppomcd to the land-lease market) is quite thin. Because of the status and securitv conferred by land, very few  DEMAND FOR FUNDS BY AGRICULTURAL HIOUSEHIOLDS 73 farmers are willing to part with it; hence very few transactions are generally observed in this market. In our sample, only 112 of 2,939 households reported sales or purchases of land in the reference period. Given this infrequency of change of ownership, current land owned appears to bk e reasonable measure of initial endowment.' Another variable used here, the district proportion of irrigated land, could provide additional and exogenous information regarding the quality of a household's land endowment. Family size may also be considered a measure of initial endowment in addition to land. The idea is to get some assessment of labour power at the disposal of the head of household. A simultaneity prob': mn arises here also in that family size decisions may be made jointlv with phvsical asset accumulation and borrowing decisions over the life cycle. We have, however, not pursued this point, thinking it better to refrain from burdening the empirical task further. The family-size variable can also be interpreted as a measure of life-cycle stage: in this case, however, a measure of the dependencv ratio would be more pertinent. For the present we have assumed that a large family size indicates a high ratio of dependents to earners, a reasonable assumption in the case of rural LDC families. Our proxy for those variables that reflect investment opportunity differ- ences across regions and over time - or, to put it another way, differences in expected future income - is derived from the annual expenditure by each state and by the federal government on major crop research. This expendi- ture is divided by the number of community development blocks in each state. These blocks contain roughly equal numbers of farms, and they form the basic extension village development units in rural India; thus a measure of comparative research intensity is obtained which can be used as an index of investment opportunity. The underlying assumption is that research expenditures in {i rtegion produce enhanced investment opportunities there within a few years and also signify a long-term commitment by the govern- ment to continue technical improvements in agriculture.' Other measures, such as proportion of irrigated land or land under high-ylielding varieties of seeds, might also provide information of a similar nature. Their effect, however, might be difficult to interpret for two reasons: (a) measures pertaining to the quality of one's land could be reasonably thought of as being proxies for one's initial endowment, a factor whose relationship to borrowing is theoreticallv ambiguous, and (b) how is one to interpret a high score along such indices'? A score of 90 per cent along the index which measures proportion of land irrigated or land sown to new seeds could reflect the exhaustion of the growth potential on that farm and thereby a levelling off of income growth expectations. Finallv, we have included a measure of transitorv income in our analysis so as to account for v ariation in the demand for funds that arise simply because of transient and unpredictable variations in income This variable is calcu- lated as the differenice bel\%ecn current income and permanent income, where the latter is calculated as a weighted average of the incomes of the past three years. The technique used to derive the weights is explained and used by Bhalla [1980] in his a.nalysis of the savings behaviour of Indian farmers, using the same data base as ours. Putting the demand and supply equations  74 THE JOURNAL OF DEVEIOPMENT STUDIES together we obtain the structural model defined by (4) and (5). The variables in the vector Y are identical to those in X, since those factors that affect a household's demand for funds (except Rn and TY) are also likely to affect its credit-worthiness and hence will enter the lenders' supply function. Con- stants and error terms have been added to the empirical model. B=b,, + b,X + blRn + b3TY + Ub (4) Rn = r11 + r1Z + r,B + r3X + Ur (5) The model is identified by the presence of transitory income in the demand function and the 'opportunity cost' variables, distance to market, source of loan, and presence of bank, in the supply function. The 'orrowing function can be estimated consistently from our structural system in stan- dard two-stage fashion: an estimate of Rn is formed by regressing it on all the exogenous variables in the system (X, Z. and TY) and this estimate can then be used in Equation (4) to obtain the parameters of the borrowing function. TABLE I *H I ((11-1) SANII'1 I NIl:ANS ANI) SIANI)ARI) I %IA1I10NS Lair,e .Smnall External V ariables and llnits All ilihouholds landholdersv landholders hrmtivse only .IV o--lt Amount borrosNed per year. 4211 453 318 1265 rupees per household (2207) (2467) (1M(50) (2073) Wage rate. 3.23 3.21 3.26 3.09 rupees per dIay (1.25) (1.31) (1.08) (1.1) () Land owned 1125 14.33 1.73 10.59 hectares per houselhold 112.5) (13.52) ((1.87) (11.87) Proportion irrigaited land. 33.15. 33.32 32.63 its