Analysis Of The Study On Market Structure And Borrower Welfare In Microfinance
The Objective
De Quidt, Fetzer and Ghatak’s (2018) Economic Journal Article articulates criticism and controversy on the role of commercial lenders within a microfinance environment. In the 1970s Professor Yunus developed microfinance institutions (MFIs) to service low income individuals, helping the poor move out of poverty. Yunus’s inspirational quote “Poverty should be eradicated, not seen as a money-making opportunity, ” motivated many economists to evaluate whether MFI’s are really alleviating poverty or if MFI’s are simply profiting from poorer borrowers. De Quidt et al. (2018) use a simulation model to analyse different market structures to determine if MFIs are commercialised or are in fact alleviating poverty. The model takes into consideration different types of lenders including non-profit lenders, for-profit monopolists and competition. This article suggests that MFIs are becoming commercialised to enjoy market power.
Findings
De Quidt et al (2018) economic model assumed a set of risk neutral borrowers who derives returns independently. In order to identify the consequences of market power for each market structure, social capital is tested through analysing the effect of social sanctions and loan contracts among both individual and joint liabilities.
The results from the model found that a monopolist for-profit lender can exploit borrowers with high social capital by charging them higher interest rates, which extracts higher rental return. This would reduce the borrowers welfare in social capital. The model found that the borrower would be better off to socially sanction to agree on efficient repayment amounts. If the borrower did not socially sanction, then it may be difficult for them to repay the loan. However, given that borrowers are constrained by the credit environment, de Quidt et al (2018) found that they are still better off borrowing in a joint liability rather than not borrowing at all individually. This is because under a joint liability, borrowers commit to a repayment guarantee, where if one borrower cannot repay part of the loan, the other borrower can step in and guarantee it. Also, under a joint liability, it forces lenders to reduce interest rates below individual liability in order to induce borrowers to guarantee one another. Group liabilities have been criticized for putting stress on individuals, however the model found that both the lender and borrower benefit under a joint liability.
On the contrary non-profit and competitive lenders both do not exploit higher social capital among borrowers. Rather, non-profit lenders maximize borrowers welfare subject to a break-even constraints, while with competitive lenders, borrower can go to other lenders if they default at one lender. De Quidt et al (2013) found that competition eliminates exploitation for borrowers because lenders cannot charge monopoly interest rates, as borrowers will simply go to alternative lenders charging better interest rates. This in effect improves borrowers welfare. However, de Quidt et al (2018) found that enforcement externalities can arise affecting a borrowers ability to repay the loan, which can lead to credit rationing. De Quidt et al. (2013) recognised this through analysing Shapiro & Stiglitz (1984) model, whom came to the conclusion that due to the highly competitive nature of the lending environment, “entry continues until lenders are just breaking even and incentive constraints are binding at which point is the competitive equilibrium. ” Based on this conclusion, de Quidt et al. (2018) ran a simulation model and found that despite an enforcement externality can lead to credit rationing, a competitive market does in fact overpower the non-profit market in terms of borrowers welfare. This is because “all borrowers benefit from the ability to re-borrow in the future”, whereas a non-profit firm is constrained. Therefore, the main finding derived from analysing the different market structures is that competitive firms don’t perform worse than a non-profit market, but really improves the borrowers welfare position, especially when the borrower’s have high social capital.
The Hypotheses
The main hypothesis de Quidt et al (2018) is testing is whether lenders from different market structures are exploiting borrowers social capital. From the findings we can expect monopolist lenders, either for-profit or non-profit, to exploit borrowers as there is no competition for them within the market. Monopolists can impose higher interest rates on borrowers, especially those borrowers who are credit constrained. This means monopolists can extract higher returns, which reduces the borrowers social capital, making them worse off. Sources of DataThe main source of data for this paper is MIX Market database, the Microfinance Information Exchange. This Non-Government Organisation (NGO) is a highly reputable and reliable data source, known to many investors and academics as the “largest and most comprehensive source of data on microfinance institutions”. Hence, its data has been and is used in many academic papers surrounding microfinance literature, particularly by those referenced in this paper. For over a decade it has provided accurate and validated data on financial service providers (FSP) and is one of the leading global data resource for inclusive finance in emerging markets. The database collects robust country and regional data from a range of microfinance institutions from over 100 countries on 5 continents. It is an extremely useful source as it allows instant access to data analysis tools, delivering insight into the financial inclusion and microfinance sector.
MIX aims to transform the data into actionable and easily applicable market intelligence for all different groups of users. Considering this, this source is of crucial importance for the estimates and variables for empirical papers such as this one. The authors extracted data from the set of reports and financial statements from each MFI that MIX receives financial performance data from. The dataset was downloaded in March 2011, so several years before the paper was published. The variables were derived from the “MFIs Overall Financial Indicators, the Income Statement, the Balance Sheet and the Products and Clients report”. The authors utilised data from 2009 because it was the year comprising of the largest number of institutions reporting lending methodology, a total of 911 out of 1106 institutions. Yet, some institutions provided incomplete data sets so the sample was reduced to 715 institutions. The main trends in the MIX Market data that were relevant in the study were that the share of for-profit lenders in the industry has increased from 35% to 43% between 1990 and 2009 and during the same time, the average number of MFIs per country has doubled from 9 to 18. The MIX Market database was the only data source used for empirical estimates in this paper. However, in terms of contribution of existing literature which will be covered later, other papers have used the same database and provided empirical evidence that this paper supports and refers to.
Empirical Method
Previous literature on the model has not kept up pace with developments and changes in micro-finace. It has assumed lenders to be non-profits and for the market to operate in perfect competition. The model allows for extensions to be made that examine the effects of commercialisation and market power in the context of microfinance. The model takes consists of multiple parts, firstly studying the behaviour of a monopolist and show the ingenuity (great outcome/unexpected outcome) of leveraging borrowers social capital which allows lending to unbankable individuals. The model shows that looking at both contractual form IL or JL and lender objectsive (profit or not) is important. The model allows for this. Typically adopts a partial equilibrium framework focusing on one MFI and a given set of borrowers. How does this impact our work? What’s the impact of the partial equilibrium? This is saying that the monopolist doesn’t always have the best interests of the borrowers at heart, we’re not at full equilibrium, so we fix that in our model to get us to a proper equilibrium. We study the behaviour of a monopolist lender who may either be a profit-maximiser or a non-proft who maxmises borrowers welfare subject to a break even constraint. These constraints are a big deal to us too. For profit lenders are shown in the model to be adversely impacted by having higher social capital however shows that without access they would be worse off altogether. The model shows us that exploitation is eliminates exploitation of lenders but has an ambiguous effect on overall borrower welfare (question for mary, is it onl this model that has shown us the overall ambiguous effect?) The model shows that competition erodes any incentives to repay their loans and thus leads to credit rationing.
The specialisation of the model enables other extensions such as studying the welfare consequences of unobservable. We show how joint liability can induce repayment guarantees within borrowing groups, with lucky borrowers helping unlucky partners with repayment. THe model allows for social sanctions. The model concludes that a for-profit lender with market power charges higher interest rates, inefficient user uses joint liability and exploits of joint liability borrowers The structure of the paper is such that a model is outlined in the form similar to much of the current literature, that of a non-profit lender who maximises borrower welfare contrasted to contracts offered by a for-profit monopolist. The paper then analyses the effects of introducing competition into the market. The model’s outline of joint-liability contracts includes a social sanction and considers the risk of either party defaulting. The model is then able to place a value of credit for a representative borrower of The model derives two investment constraints, the first referring to single borrowers with the second referring to those under joint liability contracts.
The two incentive constraints differ because there are naturally different conditions placed on those being lent to. The model shows that depending on the cost of the social sanctions which only apply in IC2, either IC2 or IC2 will be larger. This is an important extension of the model comparing different outcomes. Modelling the above with the given extensions importantly gives proposition 1, that under joint liability lending a monopolist for=profit lender exploits the borrower’s social capital and those with higher social capital are affected most drastically.
Proposition 2 shows that despite this exploitation individuals are still better off under joint-liaiblity even with a for-profit monopolist. The model uses individual liability as a benchmark from which to analyse the choice of contract. The second assumption is shown that when the discounted value of the probability of repayment in both states (R, R) multiplied by Repayment is larger than the opportunity cost of capital. A second condition derived is that the non-profit will tend towards a JL contract and subsequent max S^. The third assumption is that monopoly for profit lending is inefficient when S is ( Shat and Stide). Proposition three is that when there are intermediate levels of S – then the monopolist would prefer IL as they maximise profit and Social Welfare. This is a big part and important. Under IL the value of future credit determines the maximum incentive compatible interest rate – this is RIC1. Under JL the borrower can alsobe disciplined through social sancations which leads to IC2. Without social sanctions ric2 is always smaller because under JL there is the added risk of paying for your partner, now when social capital increase this assumption is relaxed. A policy relevant remark is that a cap on interest rates will cause a shift towards JL where there are higher repayments which means borrower welfare is further increased. This means interest rates are a powerful mechanism for determining the strength of a policy.
This model then introduces the prospect of competition into the market. This is an empirical method that was not used by previous works, notably take this from Audrey’s section. The model observes that there must be credit rationing in equilibirum or there would be no dynamic repayment incentives and all borrowers would default. The model posits that rationing allows local lending branches to act as a monopolist. Such is the strength of the model, it allows the comparison of market structures and shows ambiguous results, weighing up the cost of credit rationing against higher interest rates.
The empirical method comes together with the simulation of the model, the appropriateness of such an estimate is to be discussed later. They show that under a monopoly JL is bad by IL is worse. There are various approaches to modelling social capital. How does the model work in the paper? How does the model differ from other things? They create a robust model with more room for variation which builds upon previous literature which didn’t allow for variation. They use the outline of the model to look at the effects of relaxing the assumption of altruistic non-profit.
