FEIRB Are We Overestimating 43844 Demand for Microloans? How much microcredit is needed? Or, more precisely, how much money will it take to meet global or national demand for microloans to poor and low-income people?1 Although numerous attempts have been made to answer this question, it is difficult to come up with a reliable answer. The limited evidence available suggests that current estimates may be too high. This Brief addresses demand for microcredit only, not How do population-based estimates move from the demand for microfinance or other microfinance total number of poor2 people to an estimate of services, such as savings or funds transfers, which may potential borrowers? To begin with, some poor people be greater than the demand for microcredit. For are too young or too old to be able to use and repay instance, the ratio of savers to borrowers is about 10- loans. Others do not have the income from which to to-1 for Bank Rakyat Indonesia, 9-to-1 for Centenary repay a loan. To reflect these facts, some estimates Bank in Uganda, and 4-to-1 for PRODEM in Bolivia divide population by average household size, on the (MIX Market). assumption that there will be one loan per household, more or less (World Bank 2006 and Bruch 2006).3Other Most microcredit demand estimates address the estimates reduce overall poor population by positing a amount of funding required: the expected number of percentage who are "economically active" or active borrowers is multiplied by an assumed average "economically able" or "the working poor," and thus outstanding loan amount. Reasonable estimates of are assumed to be potential borrowers (Ehrbeck 2006). average loan size can be derived from international databases maintained by the MIX Market and Other estimates, especially country-specific ones, Microcredit Summit. But estimating numbers of begin not with the poor population but with the expected borrowers can be a minefield. number of "microentrepreneurs," based on survey or census data (Navajas and Tejerina 2006 and Tejerina Most borrower estimates begin from one of two and Westley 2007). starting places: the number of poor or low-income people or the number of microentrepreneurs. At this stage of the analysis, the estimator has a broad Whichever universe one starts with, the total number set of potential borrowers. But three further reductions must be reduced when estimating demand; otherwise, must take place: one would be making the dubious assumption that every person in the identified population would have · Many people simply don't want microloans. an outstanding microloan all of the time. This Brief · Some people who might want loans are not discusses the kinds of reductions that should be creditworthy--that is, currently available microcredit factored into a demand estimate and looks at some all- delivery systems can't lend to them without incurring too-sketchy empirical evidence about the size of those unsustainable default levels. reductions. Most--but not all--of this evidence raises · People who want and qualify for loans are not a concern that demand may often be overestimated necessarily borrowing all the time.4 by a considerable margin. 1. Almost all microfinance institutions serve some borrowers who are above the poverty line. In Bangladesh, estimates of "nontarget" or "nonpoor" borrowers range from 15 to 50 percent (Zaman 2004; World Bank 2006). The World Bank study estimates that about three-fifths of microfinance clients in South Asia are nonpoor, based on government-defined poverty thresholds, though many of these may be "vulnerable nonpoor" who are prone to transient bouts of poverty (Zaman 2004). 2. In this Brief, "poor" is used as shorthand for poor or poor-plus-other-low-income people. 3. Four persons per household is sometimes used as a divisor, though actual household size in developing countries varies from 4.8 in Latin America to 5.6 in Africa (Bongaarts 2001). 4. For more about these issues, see Reinke (2004). April 2008 2 Some don't want loans. Many poor people don't people who accept the offer of a loan) between 5 and want microloans, even if they qualify for them. They 15 percent in Peru, Mexico, Ghana, Morocco, the may be reluctant to commit to a repayment schedule; Philippines, and India.6 they may prefer to finance their investments through savings, loans from family, or other informal means; or Some cannot qualify for a loan. Whether a client is they simply may have no good use for borrowed funds. "creditworthy" depends on the lending system used. Millions of poor people would not qualify for a normal In 2002, microlending officers from Bank Rakyat bank loan because they do not have acceptable Indonesia (BRI) interviewed 1,438 households chosen collateral, but they may qualify for microloans that use at random from local censuses in 72 villages a lending methodology based on cash flow and past throughout six provinces. The loan officers applied repayment performance. But not all of them can their usual screening methods to determine whether qualify for microloans. There are important differences each household would qualify for a BRI microloan. Of among MFI lending techniques, some of which can the poor households that would have qualified for a qualify more customers than others. But no MFI can loan, less than a quarter had borrowed from any formal lend to everyone and still achieve high enough microlender in the past 3.5 years, despite the fact that repayment to avoid losing its assets. Clearly, people almost all of the households surveyed were located with a bad history of repaying prior loans have to be reasonably close to such a provider (Johnston and excluded. The biggest excluded group consists of Morduch 2007). people who do not have an income large enough or reliable enough to meet a loan's payments.7 For A survey of 17,000 microenterprises in Ecuador found instance, Rassmussen et al. (2005) estimate that 10 that only one in six had requested a loan in the past 12 percent of households in Bangladesh are too poor to months. Of those who had not requested a loan, about be able to use the microcredit products offered. For half did not want credit at all because they either did these people, other services like grants, special not want to be indebted (37 percent) or did not need services, and savings vehicles may be more useful. a loan (14 percent) (Magill and Meyer 2005). In the Indonesia study mentioned earlier, 40 percent Navajas and Tejerina (2006) reviewed surveys of of the poor households were deemed creditworthy. By household businesses in Ecuador, Guatemala, far the predominant reason for a negative Nicaragua, Panama, and the Dominican Republic. Only determination was insufficient or unreliable household 20 percent of them had applied for a loan. Of those income from which to repay the loan. Insufficient who hadn't applied, 42 percent said they did not apply collateral was almost never an issue. These results do because they did not need a loan; this reason was not mean that none of the rejected households could given more than any other.5 have qualified for a loan from another microfinance provider; BRI's lending standards are somewhat Dean Karlan and his associates at the Institute for conservative. The rejection rates were considerably Poverty Action have conducted experiments in which lower for households above the poverty line (Johnston loans are offered to people who are identified by a and Morduch 2007). microfinance institution (MFI) as viable clients and who generally do not have access to other formal credit. Data cited later in this Brief suggest that MFIs in They report take-up rates (that is, the percentage of Bangladesh lend to a much higher percentage of 5 Authors' calculation from table on p. 14 of Navajas and Tejerina (2006), based on simple averages of the countries. 6 Personal communication from Karlan. These take-up rates usually reflect client response to an initial offer in an area where microcredit is new. Take-up rates may rise significantly higher after people in the area become more familiar with the MFI and hear good reports from their neighbors. 7 Many people are under the impression that MFIs expect their loans to be repaid out of the extra income generated by the borrower's investment of the loan proceeds in her microbusiness. This is usually not the case. In most MFIs, the decision-makers (whether loan officers or a client's fellow group members) want to see an existing income source capable of paying the loan even if the investment of the loan proceeds is unsuccessful. As many as half or more of microborrowers use their loans for some non-business purpose. And those who invest the proceeds in their business are subject to the high risk of failure that is inherent in small business generally. 3 households (Rasmussen et al. 2005). But exclusion still But reports of total market penetration in Bangladesh takes place. A MFI may lend to almost any group that paint a different picture. Rasmussen et al. (2005) cite an applies, but group members are often unwilling to analysis by Dewan A. H. Alamgir of actual and potential accept a risky new member, and individuals may self- microcredit users in Bangladesh. The eligible exclude­­they won't risk committing themselves to a population, based on current lending patterns, is the regular loan repayment because their income is 10th through the 65th percentile in the national irregular or insufficient. Whatever the variations among income distribution--about 13.7 million households.9 lending techniques and countries, significant numbers After adjusting for the estimated one-third of of people will not qualify for microloans. borrowers who have loans at more than one MFI, Alamgir estimated outreach at 10.5 million individual Borrowers don't necessarily borrow all the time. borrowers, or about three quarters of the number of This point is relevant when estimating funding eligible households. In areas with very high coverage, requirements. To serve a million people with loans Rasmussen et al. suggest that as many at 80 percent of whose average outstanding balance is $150, one eligible borrowers actually take out loans. The 2006 would need funding of $150 million--if and only if all World Bank study estimated that microcredit reached those borrowers immediately get new loans as soon as 62 percent of poor families in Bangladesh. they repay the old ones. But if borrowers are active only two-thirds of the time on average, the funding The ultimate test of market estimates is actual numbers requirement would be only $100 million. of active borrowers once a national microcredit market approaches saturation. Thus, the Bangladesh data In 2003­2004, MFIs and government microcredit deserve particular weight, assuming they are correct. programs in Bangladesh reported 23.8 million However, it remains to be seen whether many other members, but only two-thirds were active borrowers countries achieve this level of penetration. Fairly as of the respective reporting dates. In the "Big Four" mature microcredit markets in countries like Bolivia and MFIs--Grameen, BRAC, ASA, and Proshika--five out Indonesia fall far below the penetration levels reported of every six members had an active loan. In the other in Bangladesh. nongovernmental organizations, two out of three members had an active loan (Rasmussen et al. 2005).8 Data about microcredit usage in various countries are These numbers suggest that a significant reduction sketchy and not entirely consistent. On balance, our should be made to allow for gaps between loans. suspicion is that most microcredit demand estimates are probably overstated, sometimes by wide margins. A large caveat: market penetration in Bangladesh. Such estimates should be treated with considerable Most current demand estimates assume that half or caution, both by those who prepare them and by those more--sometimes much more--of the target who read them. population would be borrowing at any given time if microcredit were available in their areas. The data cited so far in this Brief consistently suggest that these estimates are probably far too high. 8 These figures do not take into account people who are members of multiple MFIs and who may be borrowing from one when they are not borrowing from another, or borrowing from two or more at the same time. 9 Authors' calculations, based on a 2005 population of 142 million UNFPA (2005) and 5.7 people per household (Britannica online). April 2008 REFERENCES Reinke, Jans. 2006. "Demand Studies and How Not to Do Them: A Story about Pancakes." Unpublished. Bongaarts, John. 2001. "Household Size and http://www.ruralfinance.org/servlet/BinaryDownloader All CGAP publications are available on the Composition in the Developing World in the 1990s." Servlet/10330_Editor_s_note.pdf?filename=10997379 CGAP Web site at Population Studies, 55, No. 3 (November): 263­79. 87726_Pancake_tale.pdf&refID=10330 www.cgap.org. Bruck, Connie. 2006. "Millions for Millions." The New Tejerina, Luis, and Glenn Westley. 2007. "Household CGAP 1818 H Street, NW Yorker (October). Survey Sources and Gaps in Borrowing and Saving." MSN P3-300 Washington, DC: Inter-American Development Bank, Washington, DC Ehrbeck, Tilman. 2006. "Optimizing Capital Supply in May. 20433 USA Support of Microfinance Industry Growth." Working Tel: 202-473-9594 paper. Washington, D.C.: Microfinance Investor UNFPA. State of World Population 2003. New York: Fax: 202-522-3744 Roundtable, October. UNFPA. http://www.unfpa.org/upload/ lib_pub_file/221_filename_swp2003_eng.pdf Email: cgap@worldbank.org Johnston Jr., Don, and Jonathan Morduch. 2007. "The Unbanked: Evidence from Indonesia." New York: World Bank. 2006. "Microfinance in South Asia: Toward © CGAP, 2008 Financial Access Initiative, May. Financial Inclusion for the Poor." Washington, D.C.: World Bank, December. Magill, John H., and Richard L. Meyer. 2005. "Micrenterprise and Microfinance in Ecuador." Zaman, Hassan. 2004. The Scaling-Up of Microfinance Washington, D.C.: USAID, March. in Bangladesh: Determinants, Impact, and Lessons. World Bank Policy Research Working Paper 3398, Microcredit Summit. 2006. State of the Campaign September. Report. Washington, D.C.: Microcredit Summit. www.microcreditsummit.org Suggested citation for this Brief: Anand, Malika, and Richard Rosenberg. 2008. "Are We Navajas, Sergio, and Luis Tejerina. 2006. "Microfinance Overestimating Demand for Microloans." Brief. in Latin American and the Caribbean: How Big Is the Washington, D.C.: CGAP, April. Market?" Washington, D.C.: Inter-American Development Bank, November. Rasmussen, Stephen F., et al. 2005. The Changing Microfinance Sector in Bangladesh. Unpublished draft. AUTHORS Malika Anand and Richard Rosenberg