Model 1: Impact of Lending Methodologies on LC (Ratio)

As was discussed earlier in the chapter, some research suggests that microfinance should not be able to function according to traditional economic wisdom, due to its high transaction cost and risk associated with collateral-free lending (e.g. De Aghion and Morduch, 2005; Conning and Morduch, 2011). The authors propose that the reason it does so anyhow, is due to its ability to address the problems arising from asymmetrical information, thus lowering the cost and risk associated with microfinancial activity.

MFIs address issues of adverse selection and asymmetrical information by using innovative lending strategies, in which a group or a community is mutually liable for the loans of other members in the group. The strategy enables the MFI to gain access to more detailed information on the lending behaviour of group members, and pushes a large chunk of the time and cost associated with the monitoring of repayments, onto the group or community itself, since it is in their own interest to ensure prompt and adequate repayment from everyone.

In model 1, I estimate a simple ratio of the particular lending strategy to the total loan portfolio (table 4.14). The results are positive and strongly significant for all 4 measurements of liquidity creation, with regard to both total joint lending and group lending alone. Individual lending, however, is either insignificant or negative.

These results support the theoretical suggestion that lending strategy helps increase liquidity creation for the market, by mitigating risk and reducing auditing and transaction cost for the intermediary. Also, in support of this, the insignificant and negative results for individual lending suggests that this strategy does not have the same effect, due to the lack of peer monitoring and social capital.72

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I do not include a variable for village baking on its own, because the dataset does not provide enough observations to estimate any reliable results. The regressions run return positive but insignificant results, with low adjusted r-squared (below 0.10), and no values for P > F.

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Table 5.5: The Impact of Lending Strategy on Liquidity Creation

LC (log) LC/GTA LC/E LC/GPL

Model A Model B Model C Model A Model B Model C Model A Model B Model C Model A Model B Model C Lending strategy:

Joint lending (ratio) 0.204** 0.054*** 0.244* 0.108***

-0.08 -0.02 -0.1 -0.03

Group lending (ratio) 0.244*** 0.061*** 0.363** 0.131***

-0.08 -0.02 -0.17 -0.04

Individual lending (ratio) 0.05 -0.008 -0.12 -0.039*

-0.07 -0.02 -0.14 -0.02 Capital -1.235*** -1.318*** -1.527*** -0.337*** -0.371*** -0.370*** -4.920*** -4.887*** -5.572*** -0.458*** -0.485*** -0.495*** -0.2 -0.21 -0.21 -0.04 -0.04 -0.04 -0.43 -0.44 -0.42 -0.06 -0.06 -0.05 Size (log) 0.934*** 0.941*** 0.969*** -0.013*** -0.017*** -0.005 -0.061* -0.051* 0.029 -0.001 0.006 0.002 -0.02 -0.02 -0.02 0.00 -0.01 0.00 -0.05 -0.04 -0.03 -0.01 -0.01 -0.01 Age 0.003 0.003 0.006*** 0.001* 0.002** -0.001 0.008 0.011 -0.014** 0.002 0.002 0.00 0.00 0.00 0.00 0.00 0.00 0.00 -0.01 -0.01 0.00 0.00 0.00 0.00 Bank risk -0.874** -0.942** -1.231*** 0.024 0.045 -0.092 0.321 0.741 -0.05 0.393* 0.460* 0.001 -0.42 -0.44 -0.37 -0.07 -0.07 -0.06 -0.61 -0.65 -0.43 -0.22 -0.24 -0.1 OSS -0.015 -0.012 -0.038 -0.011 0.006 -0.025* -0.133 -0.039 -0.304* -0.054 -0.033 -0.071* -0.07 -0.05 -0.07 -0.02 -0.01 -0.01 -0.1 -0.1 -0.16 -0.04 -0.03 -0.03 NGO -0.072 -0.067 -0.082 0.016* 0.014* 0.012 0.344** 0.323** 0.402*** 0.035* 0.037* 0.032* -0.07 -0.07 -0.08 -0.02 -0.02 -0.02 -0.15 -0.16 -0.15 -0.02 -0.02 -0.02 Regulation 0.227*** 0.212*** 0.074 0.051*** 0.054*** 0.020* 0.467*** 0.598*** 0.378*** 0.057** 0.067*** 0.019 -0.07 -0.08 -0.06 -0.02 -0.02 -0.01 -0.17 -0.15 -0.12 -0.02 -0.02 -0.01 Constant 0.289 0.277 0.294 0.521*** 0.485*** 0.448*** 4.329*** 3.877*** 3.263*** 0.406*** 0.338** 0.471*** -0.38 -0.38 -0.28 -0.09 -0.09 -0.1 -0.98 -1.03 -0.8 -0.1 -0.14 -0.13 R2 0.86 0.87 0.88 0.22 0.28 0.22 0.44 0.46 0.39 0.23 0.28 0.24 R2 Adjusted 0.86 0.86 0.88 0.2 0.26 0.21 0.42 0.44 0.38 0.21 0.25 0.22 Probability F > 0 0 0 0 0 0 0 0 0 0 0 0 0 Root MSE 0.62 0.62 0.64 0.13 0.12 0.12 1.19 1.15 1.18 0.22 0.21 0.19 dfres 361 331 511 361 331 511 361 331 511 361 331 511 BIC 1599.6 1405.9 2422.4 -865.3 -867.1 -1489.5 2633.9 2283.8 3876 -92.6 -111.5 -503.5 Number of observations 797 705 1195 797 705 1195 797 705 1195 797 705 1195 Stars *, **, and ***indicate statistical significance at 10, 5 and 1%, respectively. Country-level fixed effects estimations with clustering at firm level. Robust standard errors are reported in brackets. LC is pure values of liquidity creation, deflated using the Consumer Price Index (CPI). LC/GTA is LC scaled by total assets. LC/E is LC divided by equity. LC/GLP is LC divided by gross loan portfolio. Joint, Group and Individual lending (ratio) are the ratios of that particular type of lending practice (joint, group, individual) to total loans. Capital is measured as equity ratio, size and age are logs of assets and years since establishment, bank risk the portfolio at risk for 30 days (PAR30). Regulation and NGO are dummies, indicating whether the MFI is formally regulated and is for-profit. Operational self-sufficiency (OSS) is the ratio of financial revenue divided by financial and operating expense, and impairment loss.

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The results of model 1 present a positive relationship between scaled levels of liquidity created for the market, and the use of joint lending practices. This is especially true for the group loan methodology, where my estimations are significant at the 1 or 5% for all 4 measurements of LC. Group loans are believed to help increase repayment rates and address adverse selection issues, by allowing the MFI access to reliable information on the risk-willingness of the group members. Because the members are reliant on the timely repayment of the other group members, it is in their own interest to screen, monitor and enforce the deadlines set forth by the MFI, lest they risk being subject to sanctions themselves, and be barred from future loans (Morduch, 1998; The World Bank, 2006).

Unlike the group loan estimations, the results for joint lending, while positive and significant, are less consistent. Although this may be due to the noise described above, it is likely be increased insignificance from village loans, which are included in the variable for joint lending. Due to the low amount of available observations for village loans however, I am unable to confirm this with village-only estimations.

Theoretically, while some literature suggests that village banking could help reduce agency issues and solve asymmetrical information constraints; other authors differ, and find results supporting the tentative results above. De Aghion and Morduch (2005), for example, argue that village banking should act like other forms of joint lending, due to its ability to reduce credit rationing issues, but the empirical evidence suggests that it may not be that straightforward.73 In their 2007 study, Cassar et al. found that superficial social information was not enough to increase repayment rates amongst group lenders (Cassar et al., 2007).

In the case of village banking, it is possible that the social ties present in the community are not always strong enough to increase repayment rates, and with it, lower the risk for the MFI. If the screening and monitoring abilities of the community are not strong enough, the cost associated with the village loans may not always be enough to cause a significant increase in the amount of liquidity created for the market, by the MFIs. This may be because users of village banking feel less directly responsible to each other than a group lending set- up.

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