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Tuesday, October 19, 2010

Analyzing interest caps on MFIs

The Government of Andhra Pradesh's proposed interest rate cap on rates charged by micro-finance institutions (MFIs) will in all likelihood, like similar price control decisions, generate its set of incentive distortions. I can think of three, as illustrated graphically.



1. A lowering of interest rates from the Re to Rc immediately reduces the number of people getting credit from Qe to Qs (this is indicated by the shaded triangle II).

2. However, the numbers willing to access credit at Rc increase from Qe to Qd (this is indicated by the shaded traingle III). In other words, Qd minus Qs is the number of people left without credit supply at Rc.

3. More worryingly, people accessing credit when the rates fall to Rc are most likely to be those with the highest ability to pay (those lying alongside the shaded area I) and also those more likely to have access to other channels of credit. This is because, those MFIs who are willing to provide credit at lower rates are likely to have better due diligence procedures that minimize their transaction (read recovery) costs. This ensures that those in the shaded area I are more likely to end up being given loans. Further, they also have the choice of picking from a large enough pool (demand is from Qd, whereas the supply is only for Qs) and hence are more likley to choose only the most credit-worthy of borrowers.

Prioritizing within the target group of borrowers for the provision of any subsidized credit, those people who are the most credit-worthy are also the least vulnerable and would therefore have to come last in any preference scale. However, assuming all the Qd are needy and willing to borrow at Rc, those lying in the shaded areas II and III are more vulnerable and are more likely to be prized out for all the aforementioned reasons and also not have access to alternative channels of credit. In Econspeak, the more credit-worthy and richer borrowers crowd out the less-credit worthy and poorer borrowers.

If a bank were to be in a position to be able to screen its borrowers and filter out the least credit-worthy and most vulnerable, then it would be operating in a seller's market and consider itself lucky. The MFIs (or atleast some of them) are in a similar market, thanks to the interest rate caps. Instead of helping the poor borrowers in dire need for credit, the interest rate cap ends up benefiting atleast some of the MFIs while helping none of the poor (irrespective of all this, the more credit-worthy ones would have anyway accessed their loans)!

3 comments:

gaddeswarup said...

Will it be pssible to explain a bit about the lines in the diagram and where it is coming from? Thanks.
Swarup

Jayan said...

The MFI came into life because of two reasons. One Govt/PSU banks inability give loans to them. Another reason is MFI joins hands with local community to ensure efficient use of money and expertise.

Instead of fixing the flaw, govt just blocking a nice innovation.

Urbanomics said...

thanks Mr Swarup.
Qe is the number of people who borrow at the eqbm (intersection of S-D curve)
Qd is the number who are willing to borrow if the rate is capped at Rc (intersection of D and interest cap line)
Qs is the number of people who will be able to borrow when the rates are Rc (since lenders are willing to supply to only Qs people) (intersection of S-curve with interest cap line)

The shaded regions represent the numbers of the borrowers and their respective interest rates. Say, Region III represents those willing to borrow only when the rates are between Rc and Re.

the critical thing here is about which Qs borrowers are likely to end up being given loans since Qd borrowers are willing to take the loan when the rate is Rc.

my arguement is that,

1. since the lenders have a large pool of potential borrowers to choose from they will prefer those with the best credit-history and least risk and lend them.

2. further, the lower rate lenders (MFIs lending at lower rates) are also those likely to have higher standards of due-diligence (this in turn reduces their transaction costs and lowers their enforcement costs). this in turn reinforces the earlier point.

hope this clears up your doubts
thanks