Bank and Money Lender Credit Linkages - A study


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his paper critically reviews proposals for banks and moneylenders to link together in disbursing credit to rural areas of developing

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Bank and Money Lender Credit Linkages - A study

  1. 1. Bank-Moneylender Credit Linkages: Theory and Practice∗ Adel Varghese The Bush School of Government and Public Service,Texas A&M University August 2004 Bush School Working Paper # 415 No part f the Bush School transmission may be copied, downloaded, stored, further transmitted, transferred, distributed, altered, or otherwise used, in an form or by an means, except: (1) one stored copy for personal use, non-commercial use, or (2) prior written consent. No alterations of the transmission or removal of copyright notices is permitted.
  2. 2. Bank-Moneylender Credit Linkages: Theory and Practice∗ Adel Varghese Bush School of Government and Public Service Texas A & M University 4220 TAMU College Station, TX 77843-4220 E-mail: Phone: (979) 458-8015 Fax: (979) 845-4155 August 2004 ∗ I would like to thank Jonathan Conning and especially Mark Schreiner for helpful comments. All errors remain my own.
  3. 3. Bank-Moneylender Credit Linkages: Theory and Practice Abstract — This paper critically reviews proposals for banks and moneylen- ders to link together in disbursing credit to rural areas of developing countries. The linkages suggest that banks should compensate moneylenders according to the moneylenders’ opportunity costs and information contribution. These mech- anisms’ appeal lie in their self-equilibrating and self-sustaining character. With these attractive features, bank-moneylender linkages can emerge as a serious al- ternative to group lending-based microfinance. The paper also provides evidence primarily from Indonesia on incentives similar to those suggested by the theoreti- cal models. It concludes that with the appropriate regulation of informal lenders and with incentives provided to commercial banks, linkages provide an unexplored potential. 2
  4. 4. 1. Introduction In meeting the credit demand of farmers, governments in developing countries have sponsored formal institutions in environments where private banks reluc- tantly enter on their own. These institutions have performed poorly.1 Many of their failures can be traced to the difficulties associated with disbursing and col- lecting credit in risky agricultural environments. Informal private lenders such as moneylenders, friends, relatives, and landlords can overcome some of the lending constraints. By residing close to villagers and free of the bureaucratic layers of formal creditors, these private lenders can meet demand in a quick and flexible manner. Private lenders are still limited by the size of the market. Formal lenders can rely on nationwide funds from savings mobilization and re-financing support from governments. With comparative advantages in different areas, linking the formal and infor- mal sectors can improve the disbursal of credit to farmers. Linkages fall under two categories: explicit or implicit. Under the former, formal lenders actually hire other lenders. Under the latter, formal lenders recognize that borrowers resort to toher lenders as well and incorporate that information in their lending deci- 1 For example see the evidence in Adams, et al. (1984). 3
  5. 5. sions. In creating linkages, formal lenders must structure incentives for informal lenders to cooperate and not collude with borrowers. Thus, lenders face a mech- anism design problem and the recent development of principal-agent models aid in formalizing these incentives. In this respect, the presented models differ from previous literature in that banks act as active profit maximizing participants.2 Linkages would exploit the advantages of each sector. For example, banks could issue large production loans and request moneylenders to monitor and enforce that loan. In monitoring the loan, moneylenders adapt their own flexible practices to the “bank” loan. In this manner, banks access borrowers to whom they would otherwise not lend and borrowers access loans that would otherwise be beyond their reach. Surprisingly, the rural credit markets literature does not systematically address the linkages potential. Morduch addresses this lacuna in a review of alternative mechanisms to microfinance and states that, “Unfortunately, for now policymakers have little to go on beyond a handful of small-scale case studies and ... theoretical 2 Hoff and Stiglitz (1998) provide a model with passive formal lenders. Their model and similar types will not be covered here. They do not address the issue of interaction because they do not explicitly model the formal lender’s behavior but treat it as fixed. By isolating the economic profitability of bank lending, the approach in this paper is also more relevant to financial liberalization efforts (for example in India, see RBI (1998)). Currently, banks in many developing countries face a soft constraint in that they rely on refinancing their deposits from governments but non-profitable banks do not usually obtain continuing funding 4
  6. 6. examples and counter-examples.”3 In all fairness, the literature mentions linkages but in disparate areas and has not discussed its potential rigorously.4 For example, consider the following suggestion: “Better linkages would enable banks to benefit from the outreach and local knowledge of informal lenders, ... improving the overall efficiency of the financial system.”5 This suggestion begs the following questions: how should policymakers con- struct linkages ? Under which circumstances will banks willingly participate in linkages ? What are some constraints that prevent these linkages from being con- structed ? This paper will provide theoretical and empirical support to answer these questions. The search for effective linkages forms part of a wider program in the microeconomics of development. This new line of research recognizes that in- stitutions arise to exploit their relative advantages and respond to the constraints around them. Linkages can help bridge the persistent dualism in many developing countries by providing a step in the development process. Consider a formal lender in rural credit markets. As outlined by others, for- mal lenders face the following problems : at loan disbursal, they face difficulty in 3 Morduch (1999), p. 1575. 4 Mahabel (1954) is an early qualitative discussion of linkages. Linkages are mentioned only in passing in Hulme and Mosley’s (1996ab) two volume study of rural finance for the poor. Linkages do appear in a separate subsection in Ray’s 1998 textbook, Development Economics. 5 Steel, Aryeety, Hettige, and Nissanke (1997), p. 827. 5
  7. 7. differentiating between good and bad borrowers (adverse selection).6 While bor- rowers use the loan, lenders cannot verify borrowers’ dedication to their projects since they may divert the production funds (moral hazard). Ex-post, lenders face difficulties observing and verifying output to a third party (costly state verifica- tion) and extracting repayments (enforcement). A comparative analysis of four proposed linkages in the literature reveals that a well structured incentive system can potentially overcome these four problems. The linkages suggest that formal lenders should compensate informal lenders according to the informal lender’s opportunity costs and information contribution. Linkages provide an alternative to the more popular solution to credit dis- bursal, joint-liability lending or group lending (hereafter JLL). Most microfinance organizations adopt JLL as opposed to individual lending policies. The survey by Ghatak and Guinnane (hereafter G-G) denote this practice as a primary reason for their success. This paper follows a similar structure to G-G but focuses on aspects of lending other than JLL, which has been exhaustively covered in the two major surveys by both G-G and Morduch. As Conning and Fuentes (2000) note, even JLL institutions require a staff member to monitor and oversee the group. This paper then also serves in evaluating contracts where a microfinance 6 For example, see Besley (1994), Ghatak-Guinnane (1999), and Ray (1990). 6
  8. 8. institution hires officers that have greater information and enforcement powers. Thus, this paper both complements previous work and provides an alternative to JLL. Some limits of the scope of the paper follow. As the title indicates, the paper will limit itself to banks and moneylenders. Cooperatives, the other major formal financial institution in many developing countries, are generally poorly run with their economic motives weak. Moneylenders are individuals who lend at an interest either full or part time. This paper will also not focus on linkages through savings such as ROSCAS.7 Furthermore, on the credit side it will discuss the pure lending aspects of trader-lenders and not their inter-linked aspects. It does not include lenders such as friends and relatives who help out in times of need. Friends and relatives may serve as linking agents but since they do not participate as profit maximizing agents, the economic incentives are difficult to discern. This paper first identifies the relative advantages of banks and moneylenders. It then incorporates these advantages in reviewing proposed theoretical models of linkages. The paper then finds several successful cases in Indonesia which incorporate some of the incentives suggested by the theory. In contrast to JLL, it finds that linkages provide additional attractive features. It concludes that for 7 Nagarajan-Meyer (1996) provide an example of this type of linkage. 7
  9. 9. viable linkages, banks need additional “carrots” to enter while informal lenders need “sticks” in regulation. 2. Bank-Moneylender Linkages: Theory In this section, we first outline the models and address how moneylenders can help overcome information and enforcement constraints. We explore the models in a unifying manner through simple equations. Throughout, we will use the following structure: borrower’s output Y has two values: high (Yh ) and low (Yl ) where Yh > Yl = 0. The probability of high (low) output is P (1 − P ). Each borrower requires a loan amount L and needs to repay amounts Rh and Rl for high and low output, respectively. Assume that all projects are socially profitable, i.e. that P Yh +(1−P )Yl = Y > L. Assume that borrowers face limited liability constraints and lenders can extract only what borrowers declare. Then, it follows that Rl = 0. Normalize the borrowers’ alternative from borrowing to zero. Denote the bank’s and moneylender’s cost of funds respectively as γ and ρ, where following the literature, γ ≤ ρ.8 In order to focus on the pure problems of information, assume that banks and 8 Moneylenders must rely on their own funds. Commercial banks,with nationwide branches and re-financing access from governments, face a lower cost of funds. 8
  10. 10. moneylenders are risk-neutral. All the linkages share similar assumptions on infor- mation available to lenders. Banks cannot observe the borrowers’ actions (moral hazard), types (adverse selection), and/or verify incomes (enforcement and costly state verification). In evaluating when banks would link, we first note that banks can lend on their own. We focus on the incentive constraint that banks employ to induce borrowers to “truth tell.” To simplify the technical details, we will assume that these constraints bind which can be formally proven in a more com- plete model. For sustainable linkages, not only moneylenders but also banks must willingly participate. We then add the moneylender as a linkage agent. In con- trast to banks, moneylenders have superior information (or enforcement powers). We then compare the bank’s profits on their own (denoted π B ) to those with the linkage (with moneylenders) (denoted π L ) in evaluating when banks would link. The linkages can be divided into two broad categories: explicit and implicit. In the explicit linkages, banks hire moneylenders. In the implicit linkages, banks alter their own loan contract, aware of the presence of moneylenders. 2.1. Moral Hazard (MH): Moneylenders Monitor Borrowers With moral hazard, the bank cannot explicitly observe how the borrower runs her project because it finds it too costly to observe the borrower’s actions (Conning 9
  11. 11. (1999, 2002)). Borrowers can choose a good or bad action (diligence or non- diligence), where the probability of a high output is greater for a good action than a bad action, i.e. Pg > Pb .9 If the borrower is non-diligent, then she receives a private benefit which is an increasing function of the loan size, B(L). As in standard moral hazard models, an asymmetry rises. In case of non-diligence, borrowers share their lower expected returns with banks but can capture the full value of the private benefit. The borrower will choose to undertake the good action as long as the returns are greater than the bad, Pg (Yh − Rh ) ≥ Pb (Yh − Rh ) + B(L) which, assuming that it binds, simplifies to the following:10 B(L) Rh = Yh − (2.1) 4P where 4P = Pg − Pb . The bank does not extract the full amount in case of high income and leaves a surplus (referred to as the enforcement rent, see Conning 9 We can equivalently model the moral hazard as high and low effort with a disutility in choosing high effort. 10 Following the tie-breaker rule, assume that the borrower will choose the good action. 10
  12. 12. (1999)) which depends upon the amount of the borrower’s private benefit and the sensitivity of 4P . If 4P were large, then diligence probability is high and the bank requires lower repayments. After substituting the binding condition (in which the borrower chooses the good action), the bank profits simplify to the following: B(L) π B = (Pg )(Yh − ) − γL (2.2) 4P From above, in order to obtain positive profits, the bank would set a bound on the loan size, which would in turn limit the private benefit.11 The bank could increase its profits by hiring a moneylender. Assume that the moneylender has access to a linear monitoring technology c which determines whether the borrower chooses a good or bad action. Now monitoring decreases the private benefit the borrower obtains and results in a benefit function B(c, L). The binding incentive compatibility constraint (Equation 2.1) from before now alters to the following: B(c, L) Rh = Yh − 4P 11 Here the bank would want to optimally set L = 0 but that would affect Yh in a fully specified model. 11
  13. 13. Now, in contrast to lending on its own (Equation (2.1)), the bank can extract a higher repayment amount through the increased monitoring and leave a lower enforcement rent. However the bank needs to hire the moneylender and pays wages wh and wl , respectively, for high and low output.12 For the moneylender the participation constraint follows: Pg wh + (1 − Pg )wl − c ≥ Pb wh + (1 − Pb )wl The above, assuming that it binds, simplifies to the following: c 4w = (2.3) 4P where 4w = wh − wl . The left hand side (4w) indicates the compensation differential the bank would pay the moneylender. The compensation differential (4w) directly relates to the monitoring costs and inversely relates to the diligence probabilities (4P ). When the difference (4P ) is large, the bank need not have to compensate the moneylender as much to ensure that the borrower chose dili- gence. This linkage provides a convenient advantage: the bank pays lower wages when moneylenders do not provide a valuable monitoring role and consequently, 12 For now, allow for the possibility of wl 6= 0. 12
  14. 14. banks need not employ moneylenders. It calls for a flexible credit policy across regions depending on moneylenders’ opportunity costs and borrowers’ diligence probabilities. After substituting the repayments and the moneylender’s wages, the bank’s profits then yield (here, WLOG set wl = 0): (B(c, L) + c) πL = (Pg )(Yh − ) − γL (2.4) 4P Comparing π B to πM , banks will hire moneylenders as long as B(L)−B(c, L) > c. In other words, if the incremental lowered diversion through monitoring is greater than the monitoring costs, banks can increase their profits by linking with moneylenders.13 2.2. Enforcement (E): Moneylenders Enforce Repayments In the most commonly observed and suggested linkage, assume that banks on their own cannot enforce repayment and need to hire moneylenders (Fuentes (1996)).14 This linkage shares many features with the (MH) linkage, sometimes denoted as 13 Note that surprisingly this decision does not depend upon 4P , the differential gain between good and bad actions since the moneylender’s wages absorbs the gains 14 In this static case and no collateral, banks will not lend on their own and trivially, πB = 0. With dynamics, as will be seen later, banks can exclude borrowers from future credit access 13
  15. 15. ex-post moral hazard. Similar to the (MH) linkage, the moneylender may choose diligence (eg ) or non-diligence (eb ), where eg > eb represents the moneylender’s effort in recovering a bank loan.15 This linkage differs from (MH) in that the probability (P ) is now of borrower repaying rather than action choice. The above discussion indicates that the wages paid to the moneylender will have a similar structure to Equation (2.3) where now 4e = (eg − eb ) substitutes for the monitoring costs c in the previous equation. The 4P now corresponds to the incremental increased probability the borrower repays if the moneylender puts in high effort. Again focussing on the binding condition, we obtain in a similar fashion: 4e 4w = (2.5) 4P The smaller the differential probabilities (i.e. 4P is small), then a lower re- sponsiveness of moneylender’s high wage to the repayment probabilities. In this case, the moneylender’s value added is small. The bank induces the moneylender to work harder by increasing his wages and may choose not to hire the money- lender. The linkage also reveals a self-equilibrating character: banks will not hire moneylenders when their value is less. In contrast to explicitly hiring money- 15 Usually, these effort levels are referred to as “high” and “low.” But to be consistent with the previous notation, we refer to them as “good” and “bad,” from the bank’s perspective. 14
  16. 16. lenders, banks “free ride” from the information of moneylenders. The following linkages address this option. 2.3. Adverse Selection (AS): Moneylenders Screen Borrowers The bank cannot differentiate between good and bad borrowers (Jain (1999)). Moneylenders, with better information, lend only to the good types at the lenders’ cost of funds ρ. Good borrowers (g) have a higher probability of high output than bad (b): Pg > Pb . Denote as λ (1 − λ) the proportion of good (bad) borrowers. The bank can first offer a pooling contract in which both types obtain the same loan. Here, we allow borrowers the option to borrow from moneylenders. Thus, in order to attract the good borrowers it must provide the same terms as moneylenders, where R denotes the pooling repayments: Pg (Yh − R) ≥ Pg Yh − ρL Simplifying and assuming that the above binds, ρL R= Pg Notice that the banks’ repayments now take into account the presence of money- 15
  17. 17. lenders by tieing their repayments to the moneylender’s cost of funds. The profits under the pooling contract yield: Pb ρL π B = λρL + (1 − λ) − γL (2.6) Pg Banks can extract the moneylender’s information in the following manner. Banks can distinguish between good and bad borrowers by using the additional informa- tion that the good borrowers have access to moneylenders and that all borrowers rely on a critical minimum amount. The bank separates by deliberately under- financing the good, using the implicit knowledge that the good will resort to moneylenders for the rest of the funds.16 The bad will not obtain any funds from the banks but will not mimic the good’s contract since they cannot obtain the remaining funds from moneylenders.17 In other words, the bank offers two con- tracts: one with higher repayments and no financing (the bad will choose), the other with lower repayments and underfinancing (the good will choose). Since the bank cannot observe the riskiness of the borrower, it offers loans 16 Note that this implicit linkage can incorporate the (MH) case as well where now moneylen- ders would only lend to borrowers who choose good projects. The bank, again knowing that moneylenders engage in this type of lending, would then cofinance these borrowers. 17 For certain parameter values, Jain finds that the bad will obtain full financing from the bank as well. In this knife-edge result of either obtaining full or no funding, for the purposes of the paper we will ignore the uninteresting result of full funding. 16
  18. 18. contingent upon what it can observe: repayments.18 The bank must still provide the good with the alternative of borrowing directly from the moneylender so that (where M now represents the partial loan from the moneylender): Pg (Yh − Rg ) − ρM = Pg Yh − ρL Solving for Rg , we obtain: ρ(L − M) Rg = Pg Thus the bank lowers the good’s required repayments by the loan amount it obtains from moneylenders. The bank’s profits now from good types only since the bad now do not have access to bank loans follow: π L = λ(ρ − γ)(L − M) (2.7) Comparing π B to π L , the higher the proportion of bad borrowers (1 − λ), the higher 4P , and the lower the cost difference (ρ − γ), the more likely the bank will link. 18 For the bad borrower, the incentive compatibility constraint yields the following: Pb (Yh − Rb ) ≥ Pb (Yh − Rg ) − ρM . Assuming that the above binds, the constraint simplifies to the following: Pb (Rb − Rg ) = ρM . The differential gain from repaying for a bad borrower is exactly offset by access to moneylenders (ρM ). 17
  19. 19. 2.4. Costly State Verification (CSV): Moneylenders Verify Output The bank now cannot observe if the incomes of borrowers are high or low (Bolton- Scharfstein (1990),Varghese (2004)). Since the bank cannot observe the two states, borrowers would always claim they suffered bad times and the bank will never lend since 0 < L. However, with an additional period, the dynamics of the lending sustain a solution. Banks can separate good (high income) and bad (low income) borrowers again based on what they can observe, i.e. repayments. As in the (AS) linkage, repay- ments are not sufficient but banks can now employ an additional instrument, the threat not to lend anew (denote β i the probability of obtaining a loan conditional on output i = h, l). Only if borrowers repay, they will obtain more loans (thus, we set β h = 1).19 The threat of termination provides good borrowers an incentive to repay. The incentive compatibility constraint for the good borrowers follows: Yh − Rh + P Yh ≥ Yh − Rl + β l (P Yh ) (2.8) Since Rl = 0, then β l = 0 since that would relax the above constraint. Assuming 19 This result can be proven in a full model,see Varghese (2004). 18
  20. 20. that the constraint binds, then the repayments for high income yield: Rh = P Yh The bank thus requests repayments that will cover next period’s expected income. Bad borrowers cannot mimic good borrowers since repayments for good borrowers (Rh ) are too high (P Yh ). In other words, the bank offers two contracts: Rh > Rl but with the additional stipulation that the good will receive loans and the bad will not. The bank’s profits under this separating contract would yield: π B = P (P Yh − γ 2 L) − γL (2.9) The separation comes at a cost since Y = P Yh > L for all borrowers in the next period and the bank does not seize the socially efficient opportunity. Moneylenders recognize this opportunity. Moneylenders with their superior information serve as linking agents by providing loans to excluded borrowers who can then repay banks and enjoy continued access. An advantage of this linkage is that banks need not rely on the threat of termination to separate the good from the bad since the bad can now borrow from moneylenders. In a reversal of the 19
  21. 21. (AS) linkage, the bad and not the good borrowers are active in both markets. Now the bank needs to induce the moneylender to participate, where R refers to the pooling repayments, RM refers to the moneylender’s repayments: P RM −R + ≥0 ρ Assuming that the moneylender will extract the full amount in the good state and competition among moneylenders forces the above constraint to bind, we obtain: P Yh R= (2.10) ρ The bank’s repayments now relate inversely to the moneylender’s cost of capi- tal. As in the previous linkages, this equation reveals a self-equilibrating character. With a higher cost to induce the moneylender to participate, banks require lower repayments from the borrowers. Now the bank profits yield: P Yh πL = − γ 2 L − γL ρ Comparing π B to π L , the bank opts to link when P and ρ are low. One can also show without normalizing Yl = 0, that when the dispersion between incomes 20
  22. 22. (Yh − Yl ) is high, the bank prefers linking with moneylenders. In these situations, banks find it more difficult to differentiate between income types and would rely on the moneylender. 2.5. Summary and Discussion We have reviewed four models of linkages. The theoretical linkages precisely outline the mechanisms of bank-moneylender linkages. The models indicate that banks and moneylenders complement each other, increasing the available lending opportunities.20 While the (AS) and (MH) linkages focus on the ex ante screening aspects, the (E) and (CSV) are concerned with loan recovery. Banks need not always link with moneylenders. A theoretical analysis of the linkages reveals that banks will link when the information value added (∆P ) is high, the monitoring costs or effort of the moneylender (c) are low and the differential cost of funds (ρ − γ) is low. With complete data, an empirical exercise could map these values onto observable variables. The information value added (∆P ) can be captured with proxy variables which measure banks’ knowledge of borrowers. These include trustworthiness, access to collateral, access to credit 20 With overwhelming qualitative evidence,the ADB study essentially comes to the same con- clusion and as eloquently stated by Jain, the interaction between the two sectors creates a “symbiosis.” 21
  23. 23. information, legal recourse, or when idiosyncratic shocks form a major component of the output. The monitoring costs c would be higher when lenders engage in higher marginal activities. Finally, the differential cost of funds (ρ − γ) is related to the costs c above with the larger spread for less well developed and integrated the financial markets. The theory also reveals that wages should be contingent on repayments, which are observable. The linkages are also self-equilibrating in that payments to money- lenders adjust according to their contribution and costs. The above linkages are not purely theoretical, policymakers have implemented these in a number of de- veloping countries. The practical execution of the linkages must overcome some issues which are absent in the theoretical models. 3. Formal-Informal Linkages: Practice Many of the attempted linkages draw from Indonesia, “the world’s laboratory of rural financial markets.”21 Two general surveys on rural credit by Hulme and Mosley (1996ab) and Ghate, (1992, sponsored by the Asian Development Bank, hereafter referred to as ADB) delineate the adopted practices. We will first explore the pay structures of the bank officers in the (MH) and (E) linkages. In 21 Gonzalez-Vega and Chavez, quoted in Hulme and Mosley (1996b), p.32. 22
  24. 24. these linkages, banks explicitly hire officers to monitor repayments and are the most prevalent. The pay structure reflects lenders’ efforts at overcoming incentive problems. In Indonesia, regional development banks established KURKs, village units which disburse loans at weekly mobile bank offices. In order to monitor at this level, the KURKs actually hire ex-moneylenders as commission agents (Hulme and Mosley (1996b)). The lenders receive four percent of collected loan installments. The whole system builds a web of incentives, with other participants such as the village headman (who provides some of the (AS) linkage advantage) screening borrowers and receiving one and a half percent of pre-tax profits. One of the KURKs’ successes was to minimize the guaranteed element in a bank worker’s pay. Another Indonesian bank (BUPB) offers field officers minimum guarantees plus two percent of fully repaid loans seven and a half percent of savings (which thus includes a link through savings) (Fuentes (1996)). The evidence stretches beyond Indonesia to Sri Lanka where banks use informal lenders termed PNNs. These 14,000 PNNs lend bank loans to borrowers with no documentation but have to follow bank regulated interest rates and loan amounts (ADB). In eight other financial intermediaries in Indonesia, village agents (but not 23
  25. 25. necessarily moneylenders) screen and collect loans (Chaves and Gonzalez-Vega (1996)). The agents’ wages depend on observable variables such as collected re- payments, loan installments, and primarily adjusted profits. Profits are adjusted since some events go beyond the control of lenders. This flexible system varies in its implementation across villages in that wages are village specific and incorporate the variables outlined in the theoretical section. The term “on-lending” refers to an implicit version of the above when lenders typically work as traders, i.e. inter-linked credit. In this case, banks aware of the moneylenders’ presence deliberately increase credit so that moneylenders may lend the increased loans without following bank regulations. Moneylenders would then lend on their own. The Philippines has a long history of deliberately increasing credit (Floro-Ray).22 In the NAP Program of 1984, end-users and input suppliers received cheap credit if they extended credit to farmers. In particular, a senior official of one of the largest commercial banks claimed that “some of the informal lenders are, in effect, conduits of bank funds.”23 Credit-layering, an extreme version of on- 22 Conning (2002) provides more direct evidence of the (MH) linkage. He observes that in Chile contract farming firms establish contracts with farmers by signing letters of credit. These notes are technically legally binding, but difficult to enforce. The firm then shows the letters to the bank and requests the bank to cofinance these projects. The bank agrees as long as the firm invests a certain fraction of the money itself. 23 Quoted in Floro-Ray, p.40. 24
  26. 26. lending, is a cascading series of transactions where banks lend to informal lenders who lend to others and so on. On-lending is widespread even when banks do not deliberately increase credit. Frequently, borrowers from banks re-lend at higher interest rates: with examples from Thailand (Coleman (1999)), the Grameen Bank (Rahman (1999)), Malaysia and Pakistan (ADB). The above sources indicate that the percentage of loans that lenders on-lend range from twenty to upwards of eighty percent. With regard to the implementation, linkages (MH) and (E) have strong promise but a number of countries have not fully implemented them. This possibility does not seem to arise from the reluctance of moneylenders. As Karmakar (1999) ex- plains, in informal talks with moneylenders in India, many have offered to act as agents as long as they can lend with an agency commission to meet their operating costs. Policymakers’ attitude towards informal lenders vary in a number of coun- tries. As mentioned in the Philippines, the government has actively intervened to incorporate the informal sector into the overall strategy of agricultural develop- ment (Floro-Ray (1997)). In sharp contrast, in India historically the government has actively excluded the informal sector. In the 1980s though, the Indian gov- ernment as in many other countries has reversed its philosophy. By launching a program where commercial banks participated with informal lenders, linkages 25
  27. 27. have become more viable in India. (reference: RBI) In the (AS) linkage, banks screen borrowers with the complicity of moneylen- ders. Though not the same implicit structure as the (AS) linkage, the aforemen- tioned Indonesian banks engage in explicit screening mechanisms. In particular, within the discussed KURKs, village heads screen borrowers. Robinson (?) re- ports on a similar scheme also in Indonesia (PSP-Kupedes) with traders recom- mending borrowers. Customers with good banking records recommend members from their business networks as borrowers. The head of the network has his name and preferential treatment at stake which explains the low amount of defaults. For now, the (AS) linkage may be a case where theory is ahead of practice. Practically, banks can implement the (AS) linkage in the following manner. Suppose a bank operates in an area with active informal lenders. If banks know the required loan size of the project, they can deliberately underfinance borrowers knowing that low risk borrowers can always resort to moneylenders. The bank’s information requirement is high in this linkage. The bank must not only know the critical minimum amount required by the borrower but also their other financing sources with information such as borrowers’ liquid wealth and access to other lenders. Varghese (2002) provides evidence on the (CSV) linkage, where moneylenders 26
  28. 28. provide loans to borrowers who can then repay banks. Using ICRISAT data from Indian villages, he finds that in general repayments to banks fluctuate with income. However for households that obtain loans from moneylenders, banks’ repayments do not fluctuate with income. Thus, borrowers can use moneylenders to smooth cash flows so as to meet bank obligations better. In another interpretation of this linkage, banks provide production loans and moneylenders provide bridge loans in order to ensure access. In a similar but slightly different set-up in Bangladesh, Sen reports that “recovery agents” help borrowers roll over bank loans for a fee (ADB). Borrowers then obtain a new formal loan and found that even after paying the fee, found the loans worthwhile. Karmakar provides another twist on this linkage from moneylenders in India who provide bridge loans for borrowers who are waiting to receive sanctioned bank loans. In microfinance the above is known as informal “bicycling” which occurs when borrowers who repay a microfinance institution on time obtain immediate access to another larger loan. Informal lenders, aware of this situation, provide bridge loans to borrowers who are short of cash to pay the microfinance lender. A number of studies focus on another aspect uncovered by the (CSV) linkage: the consequences of denying future loan access by formal lenders. For example, as the Masagna- 99 formal credit programs expanded in the Philippines, repayments deteriorated 27
  29. 29. under the formal sector, borrowers were excluded and the lending shifted back to informal lenders. This same phenomenon occurred in rural Thailand when the BAAC attempted to expand credit (ADB). From these case studies, policymakers can follow a more inclusive approach to informal lenders in the launching of new credit programs. Informal lenders can serve an invaluable role in the incipient stages by enabling borrowers to enjoy continuing access to formal sector loans.24 As seen above, the evidence mainly from the largely successful Indonesian experiments serve as lessons for other countries. The question remains on the replicability of the Indonesian experiments. For example, Hulme and Mosley ar- gue that the Indonesian system works because of a clear system of control (the village head) which may not work in all places. Similarly, compensation to money- lenders reflects the opportunities foregone and these vary with respect to Indone- sia. Finally, in some regions moneylenders are not prevalent so that linkages must be attempted with other agents (see Steel, et al. on the continent of Africa and Robinson). These studies and others do not provide evaluation on neither the effectiveness of particular linkages nor whether formal lenders actually hired moneylenders 24 An important caveat is the anecdote told by Coleman inThailand. He found that the village bank recorded a 100 % repayment rate to the NGO but that 67 % of borrowers borrowed from moneylenders to repay the village bank. Later, borrowers repaid the moneylenders with the loan from the village bank, creating a “vicious debt cycle.” 28
  30. 30. as agents. As mentioned before, in not all the cases the hired agents were ex- moneylenders. One would still expect moneylenders with the learned practice of lending to be the most adept at continuing this tradition. Alternatively, banks lend to NGOs, where NGOs guarantee and assist in loan recovery as in Sri Lanka or Bangladesh (ADB and Fuentes). No study provides independent evaluation on the effectiveness of moneylenders with respect to non-moneylenders. Hulme-Mosley state that training costs of staff represent a significant portion of microfinance institutions’ costs. In hiring moneylenders, banks need not expend resources on training since moneylenders have already incurred these costs. Furthermore, the implicit linkages have the added advantage of banks not needing to directly interact with moneylenders. The evidence squares with the theory with its emphasis on bank worker in- centives and its flexibility. Not surprisingly, the Indonesian experiment was built on the work of foreign consultants who were adept at creating incentive based systems. The review of the actual practices also points towards other dimensions not covered in the theory which should be considered for the success of linkages. One research point we can begin to address are the advantages of linkages over other mechanisms such as group lending. 29
  31. 31. 4. Linkages vs Joint Liability Lending In this section, we compare and contrast linkages to joint liability lending. Group lending or JLL circumvents the problems banks face by issuing joint liability contracts: members of a group are liable for one another. Formally, joint liability consists of the following for a two person group: if a borrower will repay her loan but her partner will not repay the loan, then the borrower must repay an additional c to the bank. This incentive constraint replaces the moneylender’s participation constraint in the linkages. Previous literature has not evaluated the advantages of joint liability lending (JLL or group lending) over linkages or any other alternative credit delivery mechanisms. For example, in Ghatak-Guinnane’s (hereafter G-G) survey of JLL, the alternative to group lending is individual bank lending. We will formally only analyze the effects of group lending on the (MH) contract (Conning (1999)). Now we need to account for four possible outcomes (with four corresponding repayments): Yhh , Yhl , Ylh , Yll where the first subscript denotes the borrower’s outcome and the second the partner’s outcome. In the optimal contract, the bank rewards the successful borrower but penalizes the unsuccessful 30
  32. 32. borrower.25 The only relevant constraint is for a successful borrower to truth-tell and monitor the partner in Nash Equilibrium: Pg Pg (Yhh − Rhh ) − c ≥ Pg Pb (Yhh − Rhh ) + B(c, L) − c Thus, one constraint captures the production and monitoring problem. The above, assuming that it binds, simplifies to the following: B(c, L) Rhh = Yhh − Pg 4P Again substituting the above in bank profits yields the following (denote this π G ): B(c, L) π G = (Pg Pg )(Yhh − ) − γL Pg 4P Comparing the above to Equation (2.4), assuming that Yhh = Yh ,note that π G > πB if c > 4P (1 − Pg )Yh . For large monitoring costs and high probability of a good outcome, group lending dominates linkages. The advantage of group lending is that it absorbs the monitoring costs c within the group but requires a 25 See Conning (1999) for a more thorough discussion of a model with collateral. 31
  33. 33. higher likelihood of a good outcome for success. For brevity, for the other problems we will limit ourselves to the G-G informal explanations (please refer to their article for formal derivations). In the (AS) version. the safe will associate with the safe and the risky are left with the risky resulting in positive assortative matching. Banks offer two contracts: one with high interest rates and low joint liability (the risky will choose) and one with low interest and high joint liability (the safe will choose). In the (E) case, if one member will not pay back but the other pays both her own and her partner’s JLL dominates individual liability. Also, if the community imposes social sanctions on a member who does not pay her partner’s then JLL becomes more attractive. For the (CSV) case, now the bank has to induce the borrower to report the truth for high borrower’s returns and low partner’s returns. G-G argue that the partner has an incentive to audit the borrower due to partial liability. So now the bank need only audit when the whole group announces its inability to repay (which occurs with a lower probability). Group lending still introduces further constraints as borrowers are prone to collude with each other. To avoid this possibility, we need to introduce a non-collusion constraint. With this constraint, for large monitoring costs borrowers will not reveal the truth about each other. Due to this limitation, many borrowers would graduate from group loans to linkages or individual lending 32
  34. 34. to reach larger scales. To address greater problems that arise in group lending we limit our analysis to an informal analysis. The lending solution proposed by JLL creates its own problems since the solution relies on interdependence among borrowers. The incentive constraint imposed in JLL is not as innocuous as the participation con- straint imposed in linkages since it introduces interdependence. Practically, in close knit village communities, borrowers reluctantly sanction delinquent borrow- ers (see G-G on Ireland and Burkina Faso). Wydick also finds that with Accion in Guatemala friends do not make reliable group members since members are often softer on friends. Sometimes social ties among possible borrowers are too weak to support feelings of group solidarity as demonstrated in the failed transplant in Arkansas (Ghatak-Guinnane). On a theoretical level, interdependence creates the following: bad borrowers create negative externalities on good ones. The group-lending structure may be less flexible than individual lending for borrowers in growing businesses and those that outstrip the pace of their peers (Morduch). Due to the interdependence, the JLL enjoys more success in areas of high population density and steady and frequent income streams (Conning-Fuentes). Thus, less successful in agricultural environments where the nature of produc- tion requires balloon repayments (Hulme-Mosley). Furthermore, the obsession 33
  35. 35. with the repayments record leads to some undesirable consequences such as vio- lence against women (Rahman (1999) on the Grameen Bank). ADEMI in the Dominican Republic switched to individual lending because it felt that credit ad- visors relied too much on peer pressure for loan repayments and did not develop a significant relationship with clients (Conning-Fuentes). Finally, some finer points include whether group lending leads to excessive monitoring, pressure to undertake “safe” projects, and the costs of weekly meetings and staff training (Morduch). This latter point cannot be overemphasized as Hulme and Mosley indicate that training costs form a large component of JLL programs. For example, with the Grameen bank, salary and personnel costs accounted for half of Grameen’s total costs. Over half of female trainees and a third of male trainees dropped out before taking first positions at Grameen (Morduch). Until recently, the profitability of JLL justified some of the negative conse- quences. Morduch’s re-evaluation (1999) finds that most programs are subsidized with soft loans from donors, with $26-30 m for the Grameen bank. Morduch also reports that some donors believe only five percent of all programs today will be financially sustainable ever. These difficulties of microlending leads one in search of a self-sustaining solution. This search leads one back to the solution proposed here: linkages, a not fully 34
  36. 36. exploited solution with potential. The relative advantages over JLL are many: self-sustainability, no excessive bureaucratic layer, no pressure on neighbors, and the use of the specific capital of moneylenders. Linkages build on villagers who would not engender the suspicion of neighbors. Individuals who traditionally have been lenders, i.e. moneylenders, would continue as lenders. Linkages could potentially achieve Hulme and Mosley’s three main conditions for successful credit programs: intensive loan collection, incentive to repay, and provision for voluntary saving. Linkages would bring the bank worker (moneylender) to the customer, within a self-interested and decentralized decision making process. 5. Conclusion This paper has reviewed potential linkages and provided available evidence of linkages in rural credit markets. Theoretically and empirically, linkages are at an inchoate stage. In exploring why linkages are not prevalent in developing countries, one can uncover some stumbling blocks that remain. An immediate response is that ideas such as mechanism design, institutions, and incentives are relatively new topics. Furthermore, historically policymakers have viewed informal lenders such as moneylenders as exploitative. The ADB study reviews many cases and concludes that these views may be out-dated. enforcement, political economy 35
  37. 37. This paper provides an alternative role for moneylenders. For linkages to be effective, banks are needed alongside moneylenders. In certain cases, banks may not find it worthwhile to enter both on theoretical and practical grounds. The theory is based on knowledge spillovers since one bank would provide another bank with borrower training and management skills gratis. Second, banks may not enter for the same information and enforcement issues raised throughout this paper. Due to these reasons, commercial banks would still need additional “carrots” to enter rural areas. Since the linkages program is at an incipient stage, a myriad of topics remain to be explored. Future research can investigate savings linkages, the advantages of moneylenders over others as linking agents, the relative advantages of one link- age over another, or finally combining linkages, as linkages within linkages. In the future, in light of the new revisionist views of microcredit, policymakers can explore linkages more fully as an alternative credit delivery mechanism. 36
  38. 38. Appendix: Extensions We now extend the discussed linkages to incorporate the following: relax- ing limited liability constraints on borrowers (i.e. allowing for collateral) and moneylenders, introducing risk aversion for moneylenders, and allowing bank- moneylender competition. We will only briefly discuss the extensions. Extension I: Collateral for borrowers First, suppose in the (MH) linkage banks can employ collateralized loans in which monitoring is unnecessary. Borrowers with high levels of collateral will then choose to borrow these cheaper loans from banks For medium levels of collateral, borrowers choose the linkage (Conning (2002)). For the (AS) model, as Besanko- Thakor (1987) and others show, collateral allows banks to screen good and bad borrowers, where the good borrowers now opt for the contract with collateral. The collateral allows banks to overcome the problems in the (CSV) and (E) models if the collateral amount would cover bank profits. In sum, the discussion above indicates that the introduction of collateral allows for less reliance on linkages. However, this assumes away one of the main problems in developing countries where limited wealth and limited legal systems do not allow the use of collateral. In fact, researchers now directly focus on the effects of collateral substitutes (for example, Bond-Rai (2002)). As countries develop into more collateral-based 37
  39. 39. economies, the collateral constraint would lessen. Extension II: Relax limited liability for moneylenders Instead of relaxing the limited liability constraint on borrowers, we can relax the moneylender’s constraint. In the moneylender’s case, a low wage of wl = 0 may not provide enough of an incentive for him to participate. This normalization is harmless for the effects of the contract. Again, in the (MH) and (E) linkages, in the Equation (2.3), set wl = wMin , the minimum accepted wage. Then the equation modifies to the following: c wh = wMin + 4P The above now comprises a guaranteed component (wMin ) and a bonus element c which varies as before ( 4P ).26 For the other linkages, a similar normalization now with respect to the bank’s repayments would yield similar results, with a greater surplus provided to moneylenders and less to banks. Extension III: Risk aversion for moneylenders In introducing risk aversion with moneylenders, banks would need to part with a greater surplus. Risk aversion is more justifiable for moneylenders than banks as 26 Conning and Fuentes (2002) further discuss this extension. 38
  40. 40. they cannot diversify income since they are subject to aggregate shocks within the village economy. Risk-aversion in the (MH) and (E) models introduces concavity in the wage function so that Equation (2.3) would change to the following where U(·) refers to this function: c U(wh ) − U (wl ) = 4P Now since 4U > 4w for small w, an even greater difference in utility is needed to compensate the moneylender for a small 4P .27 Consequently, with risk-aversion we have the well-known trade-off between risk-aversion and incen- tives, i.e. the larger the guaranteed element in wages, the smaller the incentive for the moneylender to follow up on the repayments. Introducing risk-aversion in the other two linkages would also induce banks to lower its repayments so that moneylenders would participate and the linking option would become less attractive. Extension IV: Introducing Competition Jain-Ghasari Instead of providing linkages, competition between banks and moneylenders could potentially transfer surplus from lenders to borrowers. In ad- 27 More precisely, for a concave function, U (wh ) − U (wl ) < U 0 (wl )(wh − wl ), and since U 0 > 0 and U 00 < 0, for small wl , U (wh ) − U (wl ) > (wh − wl ). 39
  41. 41. dition, competition would not entail the inefficient layering required in linkages. Formally, banks face a zero profit condition in addition to the incentive compatibil- ity condition. Moneylenders would not face the incentive compatibility condition but incur a higher cost of funds. In different models, both Mc-Intosh-Wydick (2002) and Hoff-Stiglitz (1998) show that competition in information markets crease some unintended consequences. These problems arise because of the in- creased indebtedness of borrowers and concomitant lack of information sharing among lenders so that all participants may be worse off. Varghese (2002), in a similar model to the (CSV) linkage above, shows that under competition the surplus flows to the good borrowers but poorer borrowers still would not obtain further loans. As the above papers indicate, banks still face constraints with in- formation or collateral and these would be alleviated only with great difficulty. Introducing a guarantee for moneylenders means less incentives and practice might provide directions into the actual mix between guarantee and incentive. 40
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