Low and volatile agricultural incomes, poor connectivity, low population density and limited information are just a few reasons that have kept commercial banks away of rural areas in developing countries, where nonbank financial institutions (such as MFIs, cooperatives, or credit unions) have played an important role.
However, these rural institutions tend to be small and often suffer from bad risk management, poor governance, and weak technical and managerial capacity. These constraints are in turn passed on to the borrowers in the form of higher interest rates and credit rationing. The lack of human and organizational capital among lenders is a type of market failure where public interventions may be both effective and market friendly (Besley, 1994).
In a new working paper, we study the effects of a support program launched in 2004 that provided technical assistance to rural financial institutions. The program was led by FND, a development finance institution in Mexico that provides financing to rural firms and second-tier financing to financial intermediaries in rural areas.1 The support program consisted of providing grants for capacity building to financial intermediaries with the objective of helping them to responsibly reach more rural borrowers, by increasing their productivity and strengthening their management.
Although grants can be used to purchase equipment or boost the capital of financial institutions, most grants were used for technical assistance, provided through a network of accredited specialists. Examples of technical assistance include credit risk management, capacity building for management and staff and IT systems selection. The average size of these grants was USD$4,000.
One first challenge that we faced when studying the impact of the support program was the lack of data: only some rural financial institutions keep financial statements, and those that do rarely publish them. We thus decided to focus on credit unions, which make up 20 percent of the grant recipients. Since credit unions are supervised, the National Banking and Securities Commission (CNBV) houses a repository of their financial data.
From CNBV, we then obtained financial statements for all credit unions operating in Mexico from September 2002 to December 2012. We merged this information with an FND-provided list of credit unions that obtained a grant through the support program. The final data consists of 124 credit unions, of which 65 received a grant in different years from 2005 to 2008. With this data, we follow all credit unions three years before -and eight years after- the program started.
To estimate the effects of FND grants, we use a staggered difference-in-difference strategy that compares the outcomes of never treated credit unions with credit unions that were treated at different years. To check the robustness of our results and guarantee that treatment and control groups have identical pre-program trends, we also use four propensity score matching techniques.
The hypothesis we test in the data is as follows. Through technical assistance, financial intermediaries can learn how to reduce inefficiencies and become more productive, which would allow them to lower their operating costs. Financial intermediaries can also learn better risk management practices (i.e., improved screening and monitoring of loans) that would reduce their credit risk. Intermediaries can also benefit from the grants by learning how to keep their books and financial statements in order, which would help them raise funding at a lower interest rate. Thus, technical assistance may help rural financial intermediaries to lower their lending interest rates and increase outreach.
However, these spillovers to the final borrowers would depend on the market conditions: in a tight competitive market, credit unions would pass these cost savings on to their clients in the form of better credit terms, whereas in a market in which credit unions have high monopoly power, the gains from technical assistance would then increase their profitability without any spillovers to the final consumers.
To trace out these channels, we first study the effects of the support program on lending interest rates and on four key drivers of lending rates, which are: (i) operating costs, (ii) credit risk, measured by the non-performing loan (NPL) ratio, (iii) the funding interest rate, and (iv) profits, measured by returns-on-assets (ROA). We then examine whether the program allowed financial institutions to expand by looking at the effect on their loan portfolio.
Overall, we find that while the program increased profitability of credit unions, final borrowers also benefited: the grants helped credit unions expand the value of their loan portfolio by about 50 percent (figure 1) and drop their lending interest rates by up to 2.6 percentage points, from a pre-program average of 17.8 percent (figure 2).
Figure 1: Total loan portfolio for credit unions in the treatment and control group
Figure 2: Lending interest rates for credit unions in the treatment and control group
Financial markets in rural areas face many challenges that impede their expansion. One of such challenges is the lack of capacity building of financial intermediaries, which limits their size and operations. This constraint has important consequences for the market, as it increases the cost of credit and reduces the volume lent. We find that through technical assistance, financial intermediaries can learn how to raise their productivity and reduce their NPL ratios, with important spillovers to the final consumers, in the form of lower cost of credit and increased supply of loans.
1FND stands for Financiera Nacional de Desarrollo Agropecuario, Rural, Forestal y Pesquero.
Source : blogs.worldbank.org