Commercializing Microfinance and Deepening Outreach ?

Does commercialization mean mission drift? Christen (2001) argues that commercialization, which is characterized by profitability, competition, and regulation, does not have any effect on large differences in loan size between regulated and nonregulated MFIs. I used data from 28 Latin American MFIs to conduct a multiple regression analysis to test for some of Christen’s conclusions, as well as for other factors that, according to the literature on microfinance, may affect loan size. The results of the regression indicate first that the type of institution, in terms of NGO versus financial institution, regardless of being regulated or not, has no effect on loan size. Second, the age of the institution predicts loan size in a direction contrary to that suggested by Christen. Third, competition turned out to be significant, in contradiction to Christen’s conclusion; it appears that more competition may lead to larger loan sizes and less depth of outreach. Finally, the models confirm an old belief in microfinance: there is a trade-off between depth and sustainability. Journal of Microf inance Volume 7 Number 2 48 out by Christen in 2001, 205 MFIs were identified in Latin America. Seventy-seven MFIs (37.6% of the total) were regulated and accounted for 73.9% of a US$877 million portfolio. In general, this phenomenon has been called the commercialization of microfinance. Commercialization is characterized by profitability, competition, and regulation, but at the same time large differences in loan size are observed between regulated and unregulated institutions (Christen, 2001). While unregulated MFIs recorded an average outstanding loan size of US$322 in 1999, regulated institutions recorded US$803, which is 2.5 times larger. Assessed in terms of relative wealth, the average outstanding loan size for unregulated MFIs represented 24% of GNP per capita in 1999, versus 49% for regulated MFIs. Do these large differences in loan size mean mission drift? Christen concludes that larger loans do not necessarily indicate mission drift, and they could simply be the function of different factors, such as choice of strategy, period of entry into the market, or natural evolution of the target group. Consequently, in the first place this paper discusses the points of view on impact assessment and the use of loan size as a “proxy” measurement for poverty level, and more important, it tests through a multiple regression analysis for commercialization factors, as well as for those factors that may also affect depth of outreach, in terms of loan size. A preliminary sample of 30 Latin American MFIs was chosen and finally 28 were included, based on the availability of operational and financial information.1 Some Points of View on Impact Assesment Microfinance scholars and practitioners are divided into two fields: the welfarist and the institutionalist (Bhatt & Tang, 2001; Woller & Woodworth, 2001). Morduch (2000) refers to these two positions as the microfinance schism. Each position differs in their views on how microfinance services should be delivered (NGO versus Francisco Olivares-Polanco is currently working as a Consultant for CANTV, the largest telecommunication company in Venezuela. Email: folivares@alumni.pitt.edu Commercia l i z ing Microf inance Volume 7 Number 2 49 commercial banks), on the technology they should use (financial services, or “minimalist,” approach versus an “integrated” service approach), and on how their performance should be assessed, among other subjects. On the last mentioned discrepancy, the welfarists believe that MFI performance should be assessed in terms of the impact on the welfare of the poor. In short, the welfarist approach is not only concerned with the question of how poor the clients are, but whether or not they are less poor after they borrow the money (Cheston & Reed, 1999). Hence, their methods are aimed at determining whether the institutions are achieving their poverty reduction objective. On the other hand, the institutionalists believe that performance should be assessed in terms of the institution’s success in achieving self-sustainability and breadth of outreach. Breadth and depth of outreach, although desirable for both institutionalists and welfarists, are perceived as contradictory objectives, thus representing a trade-off for the institutions. For the welfare-oriented practitioners, microfinance should focus on reaching the poorest and help alleviate both material and nonmaterial poverty, even with subsidized operations. On the other hand, the institutionalists foster financial broadening, where microfinance should focus on providing services to a large number of poor people and reaching financial sustainability through more efficient operations, market or higher-than-market interest rates, and economies of scale (Bhatt & Tang, 2001). Methods, Advantages, and Disadvantages of each Approach The methods used by the welfarists assess the impact of the program on their clients by measuring changes in dependent variables, such as the level of income, the level of production, sales, assets, or the general well being of the client (Alfaro, 1999; Bhatt & Tang, 2001). The underlying assumption is the existence of a direct causal relationship between the credit and the observed change in the dependent variable (Rhyne, 1994). The methodology to assess the impact generally consists in collecting data ex-ante and ex-post the program intervention through direct interviews, and sometimes in comparing the results against a control group. Eventually, the advantage of this approach is that it would allow knowing whether the MFI has a positive impact in fighting poverty. However, there are diverse criticisms to this approach. Selection bias, lack of control groups, and inability to gather longitudinal data are common concerns (Bhatt & Tang, 2001). Validity of the data also seems to be problematic, because such studies “rely on the often unreliable memories of clients to determine their status before receiving a loan” (Cheston & Reed, 1999). In addition, conducting these may take time and may be too expensive to be absorbed by MFIs on a regular basis (Alfaro, 1999). Additional fundamental problems still remain with this methodology. First, credit is not an input for the production process, but rather a financial instrument that increases purchasing power. The fungibility of financial instruments implies that establishing a causal relationship between the credit and the dependent variables would require controlling for the rest of the unit of analysis’s sources and uses of funds (Alfaro, 1999) and probably for other factors different from money that may have an effect on the dependent variables under study (i.e., the level of education of the borrower). Second, the credit does not necessarily represent an addition of 100% in purchasing power. In some cases there is financial substitution and deviation (Von Pischke & Adams, 1980; Alfaro, 1999).2 In addition, even though an impact analysis includes control groups, there is the problem of achieving equivalence between the control group and the group actually receiving loans. As an efficient financial system or institution should discriminate between good and risky clients, the control groups would be essentially different (Alfaro, 1999). Finally, looking for equivalent control groups may also lead to other dilemmas.3 Contrary to the welfarist methods, the analysis of the institution’s performance carries lower costs and becomes more feasible to assess continually in the long run. Basically, the institutionalist approach employs two measurements of success: outreach and sustainability. Outreach is measured in two dimensions: depth, or how poor the clients are; and breadth, or how many people the program is reaching. There is no causality chain analysis, and the Journal of Microf inance Volume 7 Number 2 50 Commercia l i z ing Microf inance Volume 7 Number 2 indicators for depth of outreach are various measures of loan size. For international comparisons, a ratio of loan size to per capita GDP is also commonly used (Alfaro, 1999; Schreiner, 2001), and breadth is usually measured as the number of clients or the types of instruments offered (Bhatt & Tang, 2001). The level of sustainability is measured through financial indicators such as the Subsidy Dependency Index (SDI), suggested by Yaron in 1992, or through other similar indicators such as the Explicit Subsidy Dependency Index (ESDI) or the Implicit Subsidy Dependency Index (ISDI). Other more common measures such as the Return over Equity (ROE) or the Return over Assets (ROA) are also employed, but they do not account for subsidies when they are recorded in the Profit and Loss statement. Contrary to the welfarist approach, subsidies adjustments are necessary under this approach, and they have to be reduced to a minimum level when a MFI is looking for sustainability. In addition, Rhyne (1994) recommends the inclusion of one additional measure: the quality of the service provided or quality of outreach. When an institution records high repayment rates and high growth rates in terms of clients, retains a large number of clients, and its clients are willing to pay interest rates that allow for institutional self-sustainability, then the services provided by the institution are considered of “good quality” because they are “appreciated and relevant to its clients” (Christen, Rhyne, Vogel, & McKean, 1995; Alfaro, 1999). Due to the availability of data to carry out an analysis under the institutionalist point of view, the methodology of this study is framed within this approach. The shortcomings of the study will be addressed when explaining each variable. Consequently, the final results of this study are influenced and affected by these limitations.