Microfinance Mission Drift?

Article (PDF Available)inWorld Development 38(1):28-36 · January 2010with 2,220 Reads
DOI: 10.1016/j.worlddev.2009.05.006 · Source: RePEc
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Abstract
Summary Claims have been made that microfinance institutions (MFIs) experience mission drift as they increasingly cater to customers who are better off than their original customers. We investigate mission drift using average loan size as a main proxy and the MFIs lending methodology, main market, and gender bias as further mission drift measures. We employ a large data set of rated, multi-country MFIs spanning 11 years, and perform panel data estimations with instruments. We find that the average loan size has not increased in the industry as a whole, nor is there a tendency toward more individual loans or a higher proportion of lending to urban costumers. Regressions show that an increase in average profit and average cost tends to increase average loan and the other drift measures. More focus should be given to cost efficiency in the MFI.
Mersland, R. and Strøm, R. Ø. (2010),
“Microfinance Mission Drift?”
World Development. Vol. 38(1), pp. 28-36.
http://dx.doi.org/10.1016/j.worlddev.2009.05.006
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Microfinance mission drift?
Roy Mersland
University of Agder, Kristiansand, Norway
R. Øystein Strøm
Østfold University College, 1757 Halden, Norway
Abstract
Claims have been made that microfinance institutions (MFIs) experience mission drift as they
increasingly cater to customers who are better off than their original customers. We investigate
mission drift using average loan size as a main proxy and the MFI’s lending methodology, main
market, and gender bias as further mission drift measures. We employ a large data set of rated,
multi-country MFIs spanning 11 years, and perform panel data estimations with instruments.
We find that the average loan size has not increased in the industry as a whole, nor is there a
tendency towards more individual loans or a higher proportion of lending to urban costumers.
Regressions show that an increase in average profit and average cost tends to increase average
loan and the other drift measures. More focus should be given to cost efficiency in the MFI.
Keywords: Microfinance, Mission drift, Panel data, GMM estimation.
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1 Introduction
The microfinance industry is coming of age, and with its maturation have come claims that the
industry is abandoning its mission to serve the poor (Dichter and Harper, 2007). According to
Nobel Peace Prize winner Muhammad Yunus, clients who are financially better off crowd out
poorer clients in any credit scheme (Christen and Drake, 2002 p. 10). The mission of all
microfinance institutions (MFIs) is to provide banking services to the poor, that is, to lend very
small sums to very poor borrowers. The objectives of this paper are first to determine the extent
of mission drift, and second, to provide explanations for why mission drift does or does not
occur.
Financial viability is a major concern for the industry. A recent survey conducted by the
MicroBanking Bulletin (autumn 2007) based on the THEMIX 2006 benchmark data set of 704
MFIs reveals that 41% are not financially self-sustainable; they rely on donor support to keep
afloat. However, in pursuing financial objectives, there is the risk of losing sight of social
objectives. Ever since PRODEM, a Bolivian non-governmental MFI, was commercialized and
transformed into the shareholder-owned Banco Sol in 1992, addressing the risk of mission drift
has been high on the industry’s agenda (Rhyne, 1998). Recent events, such as the initial public
offering of Banco Compartamos in Mexico that led to a handful of people making a USD 450
million fortune, have added steam to the debate (Rosenberg, 2007).
Thus, some critics fear that MFIs become too focused on making profits at the expense of
outreach to poorer customers. The argument is that higher profits lead to lower outreach.
However, Rhyne (1998) and Christen and Drake (2002) conjecture that a more commercialized
microfinance industry is better able to serve the poorest members of the community, since their
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profit motives lead them to be more efficient and more willing to seek out new markets for their
loan products. The implication is that when we seek explanations for mission drift, we should
focus upon the MFI’s costs as well as its profits. In this paper, we address these issues in the
framework of a bank’s profit function freixasrochet2008, where we also include the MFI’s risk.
Preliminary empirical evidence supports the Rhyne (1998) and Christen and Drake (2002)
position. Hishigsuren (2007) thoroughly analyzes one MFI in Bangladesh using archival,
survey, and interview data from different stakeholders. This important case study concludes
that the MFI shows no statistically significant mission drift when measured by depth, quality,
and scope of outreach to poor clients, at the same time that the MFI is able to achieve greater
cost efficiency. In country studies, Paxton et al. (2000) argue that there is a trade-off between
serving the poorest segments and being financially viable, since transaction costs associated
with smaller loans are high when compared to those associated with larger loans. However, in a
study of commercialized and transformed MFIs in Latin America, Christen (2001) concludes
that mission drift has not taken place. Littlefield et al. (2003) find that programs that target very
poor clients perform better than others in terms of cost per borrower, an efficiency indicator that
neutralizes the effect of smaller loan size. Fernando (2004) analyzes 39 transformed MFIs and
finds that their financial positions improved significantly and they did not lose sight of their
mission. Both case and country studies lack generality. Until now, Cull et al. (2007) is the only
larger cross-country study to address mission drift. Using a sample of 124 MFIs in 49 countries,
they find that MFIs can stay true to their mission even when they aggressively pursue financial
goals. Our study differs from theirs in that the data material is larger, we use instruments in
estimation, and our study is specifically geared towards the mission drift question.
Woller et al. (1999) and Woller (2002) hold that mission drift occurs when an MFI leaves the
poor customer segment. We subscribe to this view, to which there seems to be general
agreement in the microfinance industry. If mission drift occurs, the MFI’s outreach to poor
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customers, its depth dimension of outreach (Schreiner, 2002), is weakened. Depth outreach
concerns the MFI’s provision of financial services to the poorest segments, and is first and
foremost defined as average loan as in Cull et al. (2007), but depth outreach also includes the
extent of lending in rural communities, to women, and lending through group loans (Bhatt and
Tang, 2001). This paper gives characteristics of outreach measures, and provides explanations
for mission drift using panel data regression estimations with the generalized method of
moments (GMM) for average loan and logistic regressions for the other depth measures. The
GMM methodology enables estimations without endogeneity bias, and, since we use a set of
country variables in the instrument set, country effects are neutralized.
Despite the interest that has been expressed in mission drift, few studies have been carried out
to examine the issue, even fewer rigorous empirical studies. Since relatively few rigorous
studies on the impact of microfinance have been completed, ideology tends to dominate’’ the
debate on misson drift, a New Yorker article by Bruck (2006) runs. In this paper we intend to
replace ideology with analysis. The ongoing debate and the lack of cross-country studies
involving a large number of MFIs indicate a need for our study. We address mission drift
explicitly using data from rated MFIs in 74 countries.
We test three main hypotheses for mission drift derived from Freixas and
Rochet (2008): profitability per customer, costs per customer, and customer risk. The first two
hypotheses imply that an MFI will increase the size of its average loan in order to improve
financial results, while risk is uncertain. The MFI may limit risk by making smaller loans, or by
migrating to customers who are better off. The first strategy implies a smaller average loan size,
the second a larger.
The data set used to conduct this study includes observations of 379 MFIs in 74 countries
collected by rating agencies during the years 2001 to 2008. Since the data were collected by
third parties, they are more reliable than self-reported data. We find no evidence of mission
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