Low and volatile farming incomes, poor connectivity, low population density and limited information are only a couple of reasons which have stored commercial banks away of rural areas in developing countries, where nonbank banking institutions (for example MFIs, cooperatives, or lending institutions) have performed a huge role.
However, these rural institutions are usually small , frequently are afflicted by bad risk management, poor governance, and weak technical and managing capacity. These constraints have been in turn forwarded to the borrowers by means of greater rates of interest and credit rationing. The possible lack of human and business capital among lenders is a kind of market failure where public interventions might be both effective and market friendly (Besley, 1994).
Inside a new working paper, we read the results of an assistance program launched in 2004 that provided technical help rural banking institutions. This program was brought by FND, an improvement finance institution in Mexico that gives financing to rural firms and 2nd-tier financing to financial intermediaries in rural areas.1 The support program contained supplying grants for capacity building to financial intermediaries with the aim of helping these to responsibly achieve more rural borrowers, by growing their productivity and strengthening their management.
Although grants may be used to purchase equipment or raise the capital of monetary institutions, most grants were utilised for technical assistance, provided via a network of accredited specialists. Types of technical assistance include credit risk management, capacity building for management and staff also it systems selection. The typical size these grants was USD$4,000.
One first challenge that people faced when staring at the impact from the support program was the possible lack of data: only a few rural banking institutions keep fiscal reports, and individuals which do rarely distribute them. We thus made the decision to pay attention to lending institutions, which will make up 20 % from the grant recipients. Since lending institutions are supervised, the nation’s Banking and Securities Commission (CNBV) houses a repository of the financial data.
From CNBV, then we acquired fiscal reports for those lending institutions operating in Mexico from September 2002 to December 2012. We merged these details by having an FND-provided listing of lending institutions that acquired a grant with the support program. The ultimate data includes 124 lending institutions, which 65 received a grant in various years from 2005 to 2008. With this particular data, we follow all lending institutions 3 years before -and eight years after- this program began.
To estimate the results of FND grants, we make use of a staggered difference-in-difference strategy that blogs about the connection between never treated lending institutions with lending institutions which were treated at different years. To determine the sturdiness in our results and be certain that treatment and control groups have identical pre-program trends, we use four tendency score matching techniques.
The hypothesis we test within the information is the following. Through technical assistance, financial intermediaries can learn to reduce inefficiencies and be more lucrative, which may permit them to lower their operating costs. Financial intermediaries may study better risk management practices (i.e., improved screening and monitoring of loans) that will reduce their credit risk. Intermediaries may also take advantage of the grants by finding out how to maintain their books and fiscal reports so as, which may enable them to raise funding in a lower rate of interest. Thus, technical assistance might help rural financial intermediaries to lessen their lending rates of interest while increasing outreach.
However, these spillovers towards the final borrowers depends available on the market conditions: inside a tight competitive market, lending institutions would pass these financial savings onto their customers by means of better credit terms, whereas inside a market by which lending institutions have high monopoly power, increases from technical assistance would then improve their profitability with no spillovers towards the final consumers.
To follow out these channels, we first read the results of the support program on lending rates of interest as well as on four key motorists of lending rates, that are: (i) operating costs, (ii) credit risk, measured through the non-performing loan (NPL) ratio, (iii) the funding rate of interest, and (iv) profits, measured by returns-on-assets (ROA). Then we examine if the program permitted banking institutions to grow by searching in the impact on your finance portfolio.
Overall, we discover that although this program elevated profitability of lending institutions, final borrowers also benefited: the grants helped lending institutions expand the need for your finance portfolio by about 50 % (figure 1) and drop their lending rates of interest by as much as 2.6 percentage points, from the pre-program average of 17.8 percent (figure 2).
Figure 1: Total loan portfolio for lending institutions within the treatment and control group
Total loan portfolio for lending institutions within the treatment and control group
Figure 2: Lending rates of interest for lending institutions within the treatment and control group
Lending rates of interest for lending institutions within the treatment and control group
Markets in rural areas face many challenges that hamper their expansion. Certainly one of such challenges is the possible lack of capacity building of monetary intermediaries, which limits their size and processes. This constraint has important effects for that market, because it increases the price of credit and cuts down on the volume given. We discover that through technical assistance, financial intermediaries can learn to raise their productivity and lower their NPL ratios, significant spillovers towards the final consumers, by means of less expensive of credit and elevated way to obtain loans.