The social and economic success of micro credit:
an analysis of modern empirical literature
Bob Varekamp
Student number: 10342001 Amsterdam, July 2016 Programme code: BSc Eco
2 Statement of Originality
This document is written by Bob Varekamp, who declares to take full responsibility for the contents of this document.
I declare that the text and the work presented in this document is original and that no sources other than those mentioned in the text and its references have been used in creating it.
The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the contents.
Abstract:
The discussion whether micro credit has a positive impact on society is not over yet.
The goal of this paper is to get more insight into the social and economic success of micro credit and explain why there is no consensus. This is achieved by an empirical literature analysis, both subjectively and objectively. The thesis finds that literature primarily focuses on the economic effects of micro credit instead of its social effects and concludes that the approach of micro credit researches does affect their outcomes.
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Content
1. Introduction ... 4
2. Background ... 5
2.1 The start of micro finance ... 5
2.2 The current debate ... 5
3. Methodology ... 7
3.1 Hypotheses ... 7
3.2 Research Method of QTA ... 7
3.2.1 Selection criteria ... 7
3.2.2 Word selection ... 8
4. Data and Findings ... 10
4.1 Word frequency table ... 10
4.2 The 'micro credit impact' table ... 10
4.2.1 Economic effect interpretation of the 'micro credit impact' table ... 10
4.2.2 Social effect interpretation of the 'micro credit impact' table ... 14
5. Conclusion ... 15
5.1 Summary of findings ... 15
5.2 Hypotheses rejected or not? ... 15
5.3 An answer to the research question ... 16
5.4 Discussion ... 16
5.5 Further research ... 16
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1. Introduction
Since a few decades, research on micro credit has been done in different parts of the world. Several methodologies such as questionnaires, surveys, probit estimation models, stochastic variable analysis and many more have been used to capture the impact of micro credit. Mentioning the limitations of their own writings seems very common in the empirical research department of micro credit
worldwide. Therefore, it is hard to find evidence of the effects in many of the empirical results. Personally, I find it most intriguing that there is no universal definition of micro credit. You would expect that in its sense, micro credit is only about repaying small loans. Literature proves that is does not serve a single purpose after all. Where Chowdhury et al. (2005) say: "This movement aims to extend small amounts of capital to poor borrowers throughout the world, typically to facilitate income-generating self-employment activities", a more social welfare oriented view claims it is "a critical anti-poverty tool for the poorest, especially women" (The Micro-credit Summit, 1997).
To get a better grip on the goal of the empirical papers, two types of microfinance scholars and practitioners can be distinguished, namely the institutionalist and welfarist (Olivares-Polanco, 2005). The institutionalists believe that performance is reflected by the extent to which MFI's1 achieve self-sustainability whereas the welfarists say that micro financial institutions, also known as MFI's, should focus on poverty reduction. It is obvious that the first view is much more focused on economic success instead of fulfilling the needs of MFI clients. This last statement is empowered by Olivares-Polanco (2005), who claim that these 'financial broadening' fosterers assess the impact of micro credit by measuring level of production, sales and assets of the MFI's (Bhatt and Tang, 2001). However, Navajas et al. (2000) say sustainability is not an end in itself but rather a means to the end of improved social welfare (Rhyne, 1998). This insinuates that the institutionilist view lies actually very close to the welfarist view but is just too shortsighted.
There must be a reason why there is such a big controversy regarding the focus of micro credit. Are the empirical studies on micro finance done with a social or economic focus in mind? Is it possible that researchers try to solve problems judging from their own perspectives that are not coherent with the views of those who have to cope with the problems? Obtaining food might be far more important to the targeted clients of the MFI’s than obtaining a loan. Researchers could only be looking whether it succeeds on an economic level and not on a social level. This paper tries to emphasize the importance of perspective. It aims to give a better understanding of how research is done in the micro credit department and therefore is it very interesting to know why there is no universal consensus on the goal of micro credit. The research question of this paper is as follows: Does the approach of empirical research on micro credit affect its outcomes?
1MFI: micro financial institution
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This paper consists of several parts. In the following section, background information will be provided to get a better idea on how micro credit entered the world and what modern literature has to offer us about the impact of micro credit. The third part highlights the methodology of an empirical research, both objective and subjective. Section 4 discusses the findings of the empirical research. The last section summarizes the results and gives a proper answer to the research question. Finally, the implications for further research are discussed.
2. Background
2.1 The start of micro finance
While young entrepreneurs fly with their personal planes to their next business meeting, an African kid, struggling to survive, walks over four miles to reach the nearest water well that may or may not even be contagious. Extreme poverty remains a world phenomenon. According to recent estimates, in 2012, 12.7 percent of the world’s population lived at or below $1.90 a day (Worldbank, 2012). Trying to climb up the social ladder and change their lives, poor families set up their own businesses but mostly do not get an opportunity to break through and turn it into a profitable source of income in the long run. This is due to commercial banks charging enormously high interest rates. Banerjee and Duflo claim in their book ‘Poor Economics’ (2011) that MFI’s entered the market by charging a very low interest rate and without the need of collateral so that people can flourish through lending.
2.2 The current debate
Nobel prize winner Muhammad Yunus is generally known as the father of modern micro-finance. He was the founder of the Grameen Bank, an organized microcredit institution in Bangladesh that has been acknowledged as the first in the world, set up in 1983. Initiated as a research project, small loans were given to the impoverished in the form of a group lending-scheme. Nevertheless, this eventually led to an immense success and inspired more than 40 countries over the world to implement similar projects (Khandker et al., 1995). The United Nations even declared 2005 as the Year of Microcredit, assuming that micro finance highly contributed to achieving the Millennium Goals of the United Nations.
However, in 2010, an Indian micro finance crisis erupted because of a massive debt bubble. MFI's had been growing at a rapid pace since the 70's and due to their increasingly large loans, over-indebtedness rose among their clients. A poor population became very much dependent on debt for survival which eventually led to acts of suicide (Mader, 2013).
This sudden turn of events gave rise to the current discussion whether micro credit is indeed a helpful policy. Supporters of microcredit think micro credit can be very helpful in several ways.
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“Besides alleviating poverty, microcredit creates self-employment, promotes gender equality, empowers women and helps achieving universal primary education” (Crépon, Devoto, Duflo & Parienté, 2011).
On the other hand, micro credit can worsen the financial status of individuals through a debt trap. Also, the costs of monitoring loans and forcing the clients to repay can be relative high. This means that even higher returns to capital are required but since the amount of the loan is mostly quite small in micro finance, this is a problem. As MFI’s cannot depend on collateral as well as bearing the risk of default on their loans, micro credit seems unattractive. Some argue that micro credit can actually have negative impacts. Karlan & Zinman (2011) states that disrupting relatively efficient "informal" (community or family-based) mechanisms (Conning et al. 2005), and says "psychological biases may induce some to “overborrow” and do themselves more harm than good" (Zinman, 2010). According to Bateman (2014), the micro credit model of the Grameen Bank did not fulfill its promise of poverty reduction but instead "led on to the establishment of a 'poverty trap' of increasingly historic proportions." He concludes that “micro credit has been one of the most
damaging interventions in recent economic/development policy history”.
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3. Methodology
3.1 Hypotheses
To be able to answer the research question properly, an empirical research is conducted. A quantitative text analysis (QTA) method, an objective measure, as well as a personal interpretation analysis, an objective measure, is used to analyze the content of the empirical literature. There are two tables mentioned in section 4. The word frequency table only covers the objective measure. The 'micro credit impact' table reflects both measures. For a better explanation, a short description beneath each table is provided.
I expect that literature on microfinance focuses more on economic effects than social effects. Examples of economic effects are repaying the micro credit loan and increasing the profits of your own business. Examples of social effects are an increase of status and being happy. I expect this because I think social effects are more difficult to measure than economic effects. To prove whether micro credit even discusses social effects in the first place, the following hypothesis will be tested:
H1: Empirical literature does not reveal (significant) social effects
Assuming that the distinction between the institutionalist and welfarist view is solid, we can divide the literature into two categories: those that are socially oriented and those that are economically oriented. These orientations are represented by the SOC/ECO ratio, which will be explained later in this thesis.
The second hypothesis is more relevant for answering the research question because it can give insight on whether the effects, social and economic, are in line with their orientation. The following hypothesis wil be tested:
H2: Socially oriented articles will reveal social effects to a larger extent than economic effects
3.2 Research Method of QTA
3.2.1 Selection criteria
Research facilities such as the Boston Consultancy Group and the HCSS (The Hague Centre for Strategic Studies) use quantitative text analysis as a research method. For this research to be of probative value, a subtype of quantitative text analysis method namely word counting, is used. By
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means of text analysis software called ANTCUNC2, a list appears with the words and their frequencies mentioned in the text.
Nine articles have been selected. Three selection criteria were used. First, publication. All articles have been published in economic journals such as the Journal of Development Studies, World Development and the Journal of Microfinance. Second, they make use of only economic models and data, thus being highly quantitative. Third, diversity. All have a different setting, different authors and are written in different time periods. Three articles describe the use of micro credit applied in Asia, three describe micro credit applied in Latin America and three about its appliance in Africa. Each continent has an article written between the 1990's and the 2000s, one written between 2000 and 2010 and one currently written between 2010 and 2016. Why is this important? The Grameen Bank in Bangladesh might just only look at the economic success of micro credit whereas the Latin American institutions are only busy trying to make the poor happy. Moreover, due to the
commercialization process of MFI's through the years, current literature might only focus on economic success whereas older literature emphasizes the social relevance of micro credit.
3.2.2 Word selection
The next step consists of a selection of representative words that reflect social and economical value. Determining the word quantity is a matter of choice. A selection of too many words for each value could be incorrectly representative because their meaning could overlap with the other value and the distinction will be blurred. Selecting only two or three words for each value might understate each value. Therefore, a list of at least five words for each value has been chosen.
Selecting the words that reflect social value is based on preliminary research. The social variables that are often tested in empirical literature on micro credit are poverty, education, well-being, social welfare and the empowerment of women. Therefore, these make up the list of social words reflecting social value.
Selecting the words that reflect economic value is based on the particularly high word frequencies in the word lists. Also, online dictionaries and thesaurus generators found similarly related words and synonyms.3 The words that reflect economic value best are: economic, business, finance, loan, borrow, investment, capital, institution, income and pay.
Controlling for word forms is necessary to ensure the word frequencies are not
underreported. The past tense, plural form, noun and verb are all taken into account. For example,
2ANTCUNC software downloaded from: http://www.laurenceanthony.net/software/antconc/ 3 Thesaurus dictionary retrieved from: http://dictionary.cambridge.org/us/topics/finance/economics/
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the frequency fraction of the word ‘borrow’ is a sum of the frequency fractions of ‘borrow’, ‘borrowed’, ‘borrowing’, ‘borrower’ and ‘borrowers’.
Section 4.1 discusses the word frequency table and section 4.2 discusses the subjective interpretation of the economic and social effects mentioned in the 'micro credit impact' table. The SOC/ECO ratio in the second table will be discussed at the end in order to reject or support the hypotheses.
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4. Data and Findings
4.1 Word frequency table
The word frequency table on page 12 shows the percentage frequencies of the social and economic words. Except for the social word ‘poverty’ which come along quite often, the table confirms that economic words show up more often than social words pretty much all of the time. For example, the word ‘LOAN’ fills up almost 2% of Reinke's research about micro credit in Africa in 1998. Social value is less reflected: the word wellbeing does not show up at all in 6 out of 9 empirical articles. The individual percentages are scientifically relevant because the social words represent tested variables and it is quite interesting to see whether these variables are much spoken of in the literature because it tells us something about the scientific orientation.
4.2 The 'micro credit impact' table
Both economic and social effects are interpreted in the next two sections. I will be comparing the social and economic effects and observe whether they are solid on basis of the ´micro credit impact´ on page 13. The less variables needed for targeting an objective of micro credit, the more solid the effect is. I will come back to this statement in section 5.3.
4.2.1 Economic effect interpretation of the 'micro credit impact' table
Several economic effects can be distinguished from the table. Some researchers talk about the effect of micro credit on self-employment through financial success. Karlan & Zinman (2011) conclude that the treatment group of business owners were significantly operating 7% fewer business than the control group, suggesting that micro credit discourages self-employment. In contrast, Crépon et al. (2014) claim that self-employment, on average, has definitely increased over time due to the significant increases of profits, revenues and expenses. However, the randomized experiment done by Crépon et al. (2014) could include a large percentage of borrowers who already owned a business before acquiring the loan, which means they were already self-employed, as in the paper by Karlan & Zinman (2011). So, the effect of micro credit on business profits is definitely positive but the effect on self-employment is not clear.
Other researchers take a look at the repayment or default rate. Both Reinke (1998) and Sharma & Zeller (1997) take a look at which factors determine a high or low level of repayment. They claim that the participation of women significantly increases the repayment rate and insignificantly decreases the default rate respectively. So, it is hard to proof whether MFI's should target women or not in order to achieve a higher repayment rate.
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The third aspect that literature talks about is the size of the loan. Copestake et al. (2001) indicate a first loan does not have an impact on profits at all, but a second loan significantly increases business profits by 19.7%, suggesting that micro credit only succeeds when a certain threshold amount of money is received by the client. Sharma & Zeller (1997) say the bigger the loan size, the higher the default rate. Regrettably, the result is statistically insignificant and so the question remains if small or big loans are better for the economic performance of micro credit.
Some researchers try to say something about the type of MFI. NGO's4 can have different incentives and goals than commercial banks which could influence the performance of each of these MFI types. The stochastic econometric frontier technique analysis by Servin et al. (2012) results into different ownership types using different technologies and having different efficiencies. They state that NGO's and cooperatives have a lower technology level than banks and NBFI’s5 because they focus more on the social goals of micro credit. Also claiming that they have significantly higher inefficiencies, the paper tends to prefer commercial banks and NBFI's when it comes down to economic performance. Olivares-Polanco (2005) also tries to say something about the type of MFI. The article states that the type of MFI does not influence the loan size. This result is hard to interpret and in my opinion, it does not say anything about the economic performance of micro credit.
Micro credit institutions use individual lending as well as group lending alternately. The article by Navajas et al. (2000) lays its focus on the outreach of micro credit in Bolivia and concludes his paper by naming an interesting economic effect. That is, group lenders reach the poorest of the poor better than individual lenders. This insinuates that a group-lending scheme might be preferred above individual lending for those who financially need micro credit the most.
4NGO: non-governmental organization 5NBFI: non-bank financial institution
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The percentages represent a fraction of the total word count for each individual article to correct for article length; e.g. the word 'education', including its related word forms, shows up 0,024% of the time in the article of
Reinke in 1998. The 'SOC' and 'ECO' types in the first column stand for social and economic, referring to the social and economic values the words relate to.
WORD FREQUENCY TABLE
Type Word Reinke 1998 Crépon et al. 2014 Copestake et al. 2001 Karlan & Zinman 2011 Sharma & Zeller 1997 Khandker 2005 Olivares-Polanco 2005 Navajas et al. 2000 Servin et al. 2012
SOC social 0,195% 0,013% 0,033% 0,000% 0,202% 0,020% 0,481% 0,030% 0,215% SOC empowerment 0,012% 0,051% 0,000% 0,012% 0,000% 0,020% 0,000% 0,030% 0,000% SOC welfare 0,024% 0,006% 0,011% 0,000% 0,000% 0,029% 0,129% 0,030% 0,000% SOC poverty 0,073% 0,044% 0,577% 0,085% 0,292% 1,282% 2,426% 0,745% 0,184% SOC education 0,024% 0,063% 0,100% 0,073% 0,034% 0,137% 0,035% 0,015% 0,031% SOC satisfaction 0,000% 0,000% 0,033% 0,061% 0,034% 0,000% 0,012% 0,000% 0,000% SOC wellbeing 0,000% 0,006% 0,022% 0,032% 0,000% 0,000% 0,000% 0,000% 0,000% ECO economic 0,098% 0,069% 0,144% 0,146% 0,123% 0,235% 0,117% 0,030% 0,138% ECO business 0,513% 0,196% 0,622% 0,634% 0,011% 0,020% 0,000% 0,030% 0,015% ECO finance 0,476% 0,038% 0,255% 0,195% 0,415% 0,059% 0,035% 0,532% 0,215% ECO loan 1,906% 0,751% 1,010% 1,195% 1,526% 0,431% 1,840% 1,930% 0,569% ECO borrow 1,136% 0,808% 0,477% 0,476% 0,494% 1,155% 0,715% 0,152% 0,092% ECO investment 0,049% 0,152% 0,022% 0,110% 0,045% 0,029% 0,012% 0,030% 0,031% ECO capital 0,110% 0,044% 0,078% 0,037% 0,034% 0,078% 0,012% 0,000% 0,108% ECO institution 0,073% 0,076% 0,011% 0,037% 0,000% 0,039% 0,035% 0,562% 0,061% ECO income 0,318% 0,354% 0,300% 0,207% 0,146% 0,088% 0,059% 0,456% 0,031% ECO pay 0,269% 0,019% 0,089% 0,049% 0,034% 0,000% 0,023% 0,030% 0,000%
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MICRO CREDIT IMPACT TABLE
Reference SOC/ECO
ratio
Social
effect(s) Explanation of social effect(s)
Economic
effect(s) Explanation of economic effect(s)
Crépon et al. 2014 8% n.a. no statistical evidence of impact on education
and women empowerment +
self-employment increases through revenues, expenditures and profits (sign.)
Reinke 1998 9% n.a. n.a. + higher % women and higher % low educated increase the
repayment rate (sign.)
Karlan & Zinman 2011 10% - MC has a null effect on life satisfaction - MC decreases business growth, 7% less operated business (sign.)
Navajas et al. 2000 25% n.a. n.a. n.a. group lenders attain a deeper outreach than individual
lenders
Sharma & Zeller 1997 26% n.a. n.a. n.a. higher % women and higher loan size decrease the default
rate (insign.)
Copestake et al. 2001 26% + 52% say having better quality of life, 38% feels
worse (sign.) +
MC increases business profits; 19.7% (sign.) due to 2nd loan, 1st no impact
Servin et al. 2012 39% n.a. n.a. n.a. NGO's and cooperatives higher inefficiencies than NBFI's
and banks (sign.)
Khandker 2005 70% -
MC accounts for 40% and over 40% for 'moderate poverty' and 'extreme poverty'
reduction respectively
+ higher % women, per capita consumption rises by 0.09%
Olivares-Polanco 2005 112% n.a. n.a. n.a. type of institution has no effect on loan size (sign.)
The first column refers to the nine articles. The second column is related to the objective, quantitative text analysis method. The sum of the frequencies of the social word list for each article divided by the sum of the frequencies of the economic word list for each article equals the SOC/ECO ratio. The indices are ranked from lowest to highest. The other columns are not related to the word counting method but are based on subjective interpretation of the results of the articles. In the third and fifth column, there will be a ‘+’ sign when a social or economic micro credit effect respectively, is positive and tested in the article and a ‘- ‘sign when the effect is negative. An ‘n.a.’ (not applicable) applies whenever the effect is not directly related to micro credit, not mentioned or remains vague/ambiguous. The fourth and sixth column show the actual effect or causal inference of the variable. Note that the discrepancy between social and economic effects is arbitrarily determined. There are three abbreviations: MC = micro credit. A 'sign.' and 'insign.'
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4.2.2 Social effect interpretation of the 'micro credit impact' table
Let us now take a look at the social effects and interpret them. A few researchers try to measure the social effects of micro credit. Copestake et al. (2001) find a significant outcome for the wellbeing of MFI clients. Qualitative survey data recorded that 52% of the borrowers said the loan improved their quality of life over the year, but 38% felt worse off. Apparently, 10% (100% - 52% - 10%) of the people felt not better nor worse. This indicates that the effect of the loan had a negative impact or no impact at all on about 48% (=38% + 10%) of the people who were questioned which makes the effect of micro credit on well-being not as positive as it seems, as the difference between 52% and 48% is quite small. Using credit scoring, Karlan & Zinman (2011) find a null effect on life satisfaction and state the clients’ wellbeing did not improve. Concluding from these two results, a positive effect of micro credit on wellbeing and life satisfaction seems hard to proof.
Khandker (2005) is the only one that talks about poverty. Stating that poverty reduction is an 'overarching objective', he uses consumption as a proxy variable. Data on consumption and the consumption poverty line lead to the conclusion that micro credit accounts for about 40% of the overall poverty reductions in 'moderate poverty', and even more for 'extreme poverty.' This shows that micro credit definitely plays a big role in reducing poverty in terms of consumption levels. Second, the article also discusses spillover effects of micro finance. Apparently, borrowers as well as nonparticipant households can benefit from microfinance as well. When a village woman increases the borrowing amount by 10% on average, an average household, irrespective of participation or not, spends 0.68% more. Men’s borrowing, however, does not have any significant effect on per capita consumption. The positive spillover effects could tell us that women might be more important for improving welfare in society than men.
The article of Crépon et al. (2014) discusses women empowerment and uses several proxies such as an index of women independence and the percentage of household self-employment activities managed by women to measure it. Unfortunately, these regression results are not
significant to infer a causal relationship between micro credit and women empowerment. The same holds for education. The regression coefficient of kids (aged 6-15) in school of the treatment group is 0.006, which is an insignificantly small number that has little empirical value.
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5. Conclusion
5.1 Summary of findings
This article tries to answer the following research question: Does the approach of empirical research on micro credit affect its outcomes? By using an objective QTA measure combined with a subjective interpretation of the empirical results of micro credit, we found several results. From the word frequency table, we find that researchers focus more on the economic aspect than the social aspect of micro credit. The 'micro credit impact' table, in which the results are very different from each other, shows the same thing. The economic interpretation analysis shows that micro credit increases business profits, but discourages operating that business. Also, despite insignificant results, an increase in female participation increases the repayment rate and thus economic performance of micro credit. Third, whether there small or big loans are better remains unclear and fourth, group lending is better for suiting the poorest of the poor. Despite the fact that social effects were hard to find, the social interpretation analysis shows that a positive effect of micro credit on wellbeing and life satisfaction is difficult. Second, women could be more important for improving welfare in society than men, although they are not necessarily empowered through micro credit.
5.2
Hypotheses rejected or not?
Let us recall the predetermined hypotheses and see whether they are rejected or supported.
H1: Empirical literature does not reveal social effects
H2: Socially oriented articles will reveal social effects to a larger extent than economic effects
The first hypothesis is definitely rejected. On the basis of the empirical literature analysis in section 4, it can be concluded that social effects such as an increase in status or happiness are spoken of. Women empowerment, life satisfaction, well-being, education and social welfare are all variables researchers empirically tested the last few decades.
According to the SOC/ECO ratio, the articles with the highest ‘social orientation’ do not specifically focus on social effects. Except for Khandker (2005), with a SOC/ECO ratio of 70%, being the second highest socially oriented, Sharma & Zeller (1997), Servin et al. (2012) and even Olivares-Polanco (2005), with a SOC/ECO ratio 112%, show only economic effects and no social effects whatsoever. Despite the fact that Olivares-Polanco (2005) thoroughly discusses poverty as shown in the word frequency table; the word 'poverty' makes up more than 2,4% of his research, he does not test it. The high socially oriented papers according to the SOC/ECO ratio are not in fact mainly focused on social effects. It turns out that although some show social effects, as the 'micro credit
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impact' tale immediately shows, all articles include economic effects. So, empirical literature reveals economic effects to a larger extent than social effects. This is exactly the opposite of what the second hypothesis tries to test, thus rejection is unavoidable.
5.3 An answer to the research question
Does the approach of empirical research on micro credit affect its outcomes? The answer is yes. Regardless of writing a socially or economically oriented paper according to the SOC/ECO ratio, the outcome will always include economic effects and might possibly show social effects to a limited extent.
5.4 Discussion
One limitation of this research is that the sample size of the research is very limited, which harms the statistical power of the experiment. However, there is a very strong result visible. Regardless of the time period or the continent of interest, the social values are highly underrepresented in the literature. This is probably due to the low degree of measurability of such values. There are three aspects that can confirm this statement. The act of doing this experiment itself reconfirms the fact that arbitrarily assigning labels to the variables you want to test on, is necessary for increasing the degree of measurability. Second, the article by Khandker (2005) calls poverty an ‘overarching
objective’ and using consumption as a proxy variable, I think that this relates to the fact that poverty is too hard to target directly because it consists of several ‘sub’ objectives. Third, the article by Servin et al. mentions that NGO’s and their cooperatives have social goals but also have lower
techonologies and higher ineffiencies, pointing towards a certain tradeoff. Again, this reconfirms that the social effects are harder to get to. Thus, the economic effects of micro credit seem more solid.
5.5 Further research
Literature on micro credit focuses too much on the economic effects and not on the social effects. The reason for this is probably twofold. First, due to the commercialization process, which I mentioned earlier in my thesis, MFI's are busy trying to gain a high repayment rate instead of improving their customers' lives. Second, the measurability of social effects is extremely difficult. As far as I am concerned, the most common method used is a survey. People might not truthfully fill in the blanks which can lead towards totally different results. Therefore, pretending to be one of the ‘welfarists’, I prefer contributing to a better social welfare above attaining high repayment rates. Therefore, it is important that more research has to be done on methodologies that can help improve testing social effects of micro credit in the future. Micro credit has been brought into the world only a few decades ago and since there is no universal definition, it remains a difficult concept to implement into society.
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