This essay has been submitted by a student. This is not an example of the work written by professional essay writers.
Entrepreneurship

MICROFINANCE IN DEVELOPING COUNTRIES

Pssst… we can write an original essay just for you.

Any subject. Any type of essay. We’ll even meet a 3-hour deadline.

GET YOUR PRICE

writers online

MICROFINANCE IN DEVELOPING COUNTRIES

Introduction

            According to the World Bank, approximately 1.4 billion people across the world live on less than one dollar a day. These individuals are faced with abject poverty and suffering (World Bank, 2009a). Available literature indicates different effective programs that have been developed to deal with poverty. One of the strategies is microfinance, which is seen as an effective tool in combating paucity. This is because microfinance requires minimal investment and can serve unfortunate people, unlike traditional banks. Microfinance refers to financial services that are mainly offered to low-income households. Microfinance institutions mainly give these services.

In the past few years, many developing countries have established microfinance institutions (MFIs). MFIs are crucial since they are a source of capital for people who are unable to access loans from banks. Loans provided by microfinance institutions help individuals to start small-scale businesses and generate income (Cai, 2016). Income made is crucial in ensuring the reduction of poverty in developing nations. The establishment of microfinance institutions has enabled millions of people across developing countries to have access to loans.

Individuals in developing countries have been unable to access credits from local banks because of their limited income, which makes it difficult for them to repay the loans (Cai, 2016). The majority of people in these countries lack assets which act as collateral for securing bank loans. Apart from offering loans, microfinance institutions provide several amenities ranging from insurance, savings, and remittance transfer services, among others.

Don't use plagiarised sources.Get your custom essay just from $11/page

Financial innovations such as microfinance institutions apprehend that even poor people can become reliable borrowers. Before the establishment of microfinance institutions, access to credit was provided through group lending cooperatives and rural moneylenders (Armendariz, 2000). Innovations in the financial sector led to the development of formal microfinance institutions, which are similar to banks. However, they have particular characteristics that differentiate them from banks (Armendàriz, Beatriz, and Jonathan Morduch. 2000).

Traditional banks have not been effective in providing loans to the poor (Cull, 2014). Banks are faced with the risk of recovering the money they lend to borrowers. Moreover, banks only provide loans to borrowers with positive credit history since they can repay the loans. Therefore, poor individuals without a steady source of income and assets to be used as collateral cannot receive loans from banks. According to the principle of diminishing returns, capital should flow from wealth credits to poor businesspersons. However, this is affected by adverse selection challenges since banks seek to choose safe customers, and risky clients are not considered. Another reason why banks do not offer credit to poor individuals is because of market failure. Small entrepreneurs are unable to cushion themselves from market failures exposing them to risks. In this case, risks that small entrepreneurs face includes political threats, lack of insurance and savings, high transaction costs, lack of collateral, and information asymmetries. Therefore, banks are reluctant to lend money to small entrepreneurs due to these risks. This paper seeks to provide an overview of how microfinance institutions are providing loans to individuals in developing countries.

Literature Review

History of Microfinance

The introduction of microfinance took place in Europe during the 1700s with the implementation of financial systems to assist the poor. During this period, charity organisations in Ireland established interest-free loans. In 1823, a law was passed allowing charity organisations to become financial institutions. The aim of these organisations was to collect interest-bearing deposits and provide the poor with interest-free loans. These intermediary institutions provided high interests on savings, which led to increased competition with banks (McIntosh, 2005). However, in 1950, legislation was passed, which did away with these intermediary institutions.

Microfinance institutions in Germany were established during the 1800s. Schulze-Delitzsch came up with savings and credit cooperatives in urban areas, while Raiffeisen established them in rural regions. These associations were formalised by the 1889 Cooperative Act, the first legislation of its kind in the world. Germany had the highest number of cooperatives, and the model was soon adopted in other countries (Robison, 2001). Modern-day microfinance institutions were established in Indonesia. When the Dutch colonised Indonesia, they introduced People Credit Banks, which grew, and this resulted in the formation of the Bank Rakyat Indonesia (BRI). BRI developed into profitable financial institutions providing credit to people in rural areas. Bank Dagong Bali, a private institution, is the oldest provider of credits that have been offering loans since 1970 (Robinson, 2001). Microfinance in Latin America was introduced by ACCION International, an NGO that provided solidarity loans to small entrepreneurs (Rhyn, 2009; ACCION, 2010). Microfinance institutions looked to provide long-term financial solutions to the needy people. Most governments and donors used grants and subsidies to assist poor people. However, these measures were short-term (Hudon, 2011). John Hatch, through the International Community Assistance, established village banks across Latin America. Awareness on microfinance grew during the formation of the Consultative Group to Assist the Poor (CGAP) in 1995. The group was tasked with the role of increasing resources for microfinance institutions

Theory and Hypothesis        

Financial systems developed in many countries are not capable of benefitting all citizens since not anyone is in a position to access credit services. Therefore, microfinance institutions have been developed to ensure that low-income earners can access financial services (Cai, 2016). In developing nations, MFIs provide loans among other services to poor people who cannot afford to apply to traditional banks. Research suggests that well-developed financial systems negatively impact the operations of MFIs. Studies suggest that the development of microfinance institutions will lead to competition with commercial banks in the future (McIntosh, 2005). The presence of commercial banks may result in borrowers opting to take up their loans. This is because borrowers will enjoy several loan options and can borrow huge amounts of money.

In some cases, loans from banks may have low borrowing costs (Armendàriz, Beatriz, and Jonathan Morduch. 2000). When charges incurred while taking credit facilities from banks reduce, most people apply for more loans to advance their business. This increases the number of loan borrowers, including low-income earners, which enhances their capability to get capital to start their businesses and improves their lifestyles.

The available literature suggests that financial institutions have a positive impact on economic growth (Beck, 2015). The literature states that financial institutions have a unidirectional impact on a country’s economic growth. Therefore, a well-developed financial sector leads to the growth of the economy. Recent research provides the opposing opinions stating that the relationship between financial development and economic growth is an inverted U-relationship (Armendàriz, Beatriz, and Jonathan Morduch. 2000). The affiliation indicates that the financial sector is overfunded and this is likely to have adverse effects on countries’ economic growth in the long run (Beck, 2015). Country’s economic growth has an impact on MFIs. The presence of microfinance institutions allows low-income earners to have access to financial services, thus, enabling them to start businesses. Through businesses, individuals generate income while reducing poverty in developing countries. The majority of people using MFIs to access financial services makes the role of these institutions in the capital markets crucial (Armendàriz, Beatriz, and Jonathan Morduch. 2000).

Theoretical Approaches

The role of MFIs in poverty reduction is based on two approaches. The Minimalist Approach is where MFIs only provide financial services in the form of loans. MFIs do not provide other services due to several reasons, as stated below. High transaction and administrative costs make it difficult for MFIs to provide other services. According to this approach, the main aim of these institutions is profitability and viability. MFIs also use Credit-plus Approach, where these institutions offer clients non-financial services (Karlan, 2009). The services include supplying businesses with inputs, providing marketing assistance, education, and skills training.

According to the theory of economic development, financial institutions are important in economic growth. This is because they provide financial services, and people can also deposit their savings. King and Levine (1993) stated that a country’s financial development is dependent on GDP growth and capital accumulation. Therefore, developing countries need to ensure economic growth since it has a positive impact on financial development. Economic growth results in an increase in the demand for financial services (Hassan et al., 2011).

Impact of Microfinance on Poverty

MFIs are crucial in the reduction of poverty in developing countries. This is because they are providing poor people with loans, which increases their income-generating opportunities (Swain et al., 2008). Though MFIs cannot completely eradicate poverty, they are crucial in the fight against poverty. Loans provided by these financial institutions can transform households both economically and socially. People are poor because of several reasons. However, it is believed that the lack of access to credit is the major reason why people continue to be poor. Funds from MFIs enable poor people to invest in income-generating activities, which reduces poverty. As such, low-income earners can have savings, which they can invest in several activities (Armendàriz, Beatriz, and Jonathan Morduch, 2000).

Microfinance can be effective in fighting poverty, mainly because it is an alternative to traditional finance. MFIs provide funds to the poor to enable them to run their businesses or establish new ones. Studies reveal that the poor have access to funds, then the rate of inequality in a population decreases (Brau, 2004). Microfinance offers several products ranging from simple loans to money transfers, insurance and savings. The products also enable people in developing countries to access healthcare and education. Microfinance is crucial in the promotion of social activities and economic development (Littlefield et al.,. 2003). People in developing countries lack access to financial markets due to market imperfections present in the industry. MFIs address these imperfections by focusing on the poor as vital people that can drive economic growth. Therefore MFIs reduce the level of inequality in developing countries (Crepon, 2015). Several studies on microfinance conclude that MFIs have a positive impact on the creation of income-generating activities and access to credit. The studies stated that MFIs had no impact on women empowerment, health and education.

Measurement of poverty

The UNDP has several measures of poverty as outlined in the table below

MeasureComponents
Human Development IndexLife expectancy at birth, adult literacy,

educational enrolment, GDP per capita

Gender-related development indexAs above, adjusted for gender differences
Gender empowerment measureSeats in parliament held by women,

female administrators and managers,

female professional and technical workers,

women’s share of earned income

Human Poverty Index (developing countries HPI-1)People not expected to survive to 40,

illiteracy, access to safe water, access to

health services, underweight children

Human Poverty Index (developed countries HPI-2)People not expected to survive to 60,

functional illiteracy, population below

mean income, long term unemployment

Source: UNDP Human Development Report 1998

Methodology

 Research Design

            Due to time constraint, this research relied on secondary sources of data. Research data were obtained from the Microfinance Exchange Market (MIX) database. This is because MIX database provides comprehensive information on microfinance institutions. The study involved microfinance institutions from developing countries. Focusing on MFIs in these countries will help the study to establish whether MFIs are significantly contributing to the reduction of poverty in developing countries.

Countries under study were selected using non-probability sampling. It is worth noting that non-probability sampling is classified into three categories, which include quota, convenience, and judgment sampling. Non-probability sampling is effective since it is cheaper, more efficient, and easier to use compared to probability sampling (Ayyagari, 2003). Time constraint did not allow the use of primary data. Therefore, only secondary data were used in this study. Data collection was simple since one was only required to log into the Mix database and obtain the required information. The study also relied on information from existing documents, reports, and surveys.

Validity is referred to as the degree to which it measures what it was supposed to evaluate (Denise et al., 2001). The primary instruments the study was trying to measure was economic growth and poverty reduction among members of microfinance institutions. Reliability refers to a situation where an instrument can produce a similar outcome when used in another study (Ondeng, 2003). To collect information on whether MFIS were effective in poverty reduction, data collected were reliable. The data collected were entered into the Statistical Package of Social Science (SPSS) software. Microsoft spreadsheet was also used to come up with tables and pie charts. Data from MIX database did not contain sensitive information about microfinance institutions.

Data analysis

Descriptive analysis results for the fifty-two countries are outlined in the Table

 

Variable

 

Mean

 

Std. Dev.

 

Min

 

Max

Observations
GINI41.98.524.262.8832
PHC_121.323.50.087.7832
PHC_237.329.80.193.5832
PGAP16.016.00.062.3832
MI-Number1.52.50.024.2832
MI-Loans2.16.40.0101.6832
Arable land16.313.31.664.9832
Agricultural value-added18.611.62.357.7832
Inflation (GDP deflator)10.738.9– 8.51 058.4832
Young population33.59.113.349.4832
Openness index72.535.214.9220.4832
School expenditure3.61.40.69.7832
Health expenditure5.71.81.913.0832
Unemployment7.74.80.635.9832
Polity2-score3.55.6– 7.010.0832
Log-GDP per capita7.21.14.79.5832
Rural population51.221.55.488.6832

 

Table 3 Panel fixed effects (OLS) estimation results (main sample)

VariablesGINIPHC_1PHC_2PGAP
MI-Number– 0.137– 0.586***– 0.292– 0.331**
MI-Loans– 0.056**0.0580.0960.049
Arable land– 0.198*– 0.202*– 0.810***– 0.806***– 0.634**– 0.628**– 0.598***– 0.595***
Agricultural value added– 0.123**– 0.109**0.190*0.1540.0730.0340.1170.092
Inflation– 0.001– 0.001– 0.006– 0.007– 0.009– 0.010– 0.003– 0.004
Young population0.1060.1740.6590.884**0.993**1.090**0.2320.356
Openness index– 0.005– 0.0040.0650.0540.0600.0520.0270.020
School expenditure– 0.081– 0.094– 1.633***– 1.708***– 1.267**– 1.309**– 0.887**– 0.930**
Health expenditure0.0950.113– 0.154– 0.223– 0.061– 0.127– 0.157– 0.204
Polity2-score– 0.011– 0.001– 0.084– 0.0720.0620.0620.0060.011
Log-GDP per capita– 1.654**– 1.729**– 3.046**– 3.489**– 8.305***– 8.553***– 3.610***– 3.867***
Rural population– 0.183– 0.1800.030– 0.034– 0.326– 0.3740.027– 0.013
Number of Observations832832832832832832832832
Number of Countries5252525252525252
F-test2.2683.46213.8018.27214.96310.97913.9818.078
R-squared0.1130.1200.5500.5320.6140.6150.5540.544

Note: Significance level based on robust standard errors are *** (1 %), ** (5 %), * (10 %).

Table 4 Instrumental variables (IV) estimation results

VariablesGINIPHC_1PHC_2PGAP
MI-Number– 0.416***– 1.340***– 0.596*– 0.787***
MI-Loans– 0.098*0.2790.2420.159
Arable land– 0.068– 0.114– 1.041***– 0.976***– 0.701**– 0.628*– 0.796***– 0.750***
Agricultural value added– 0.205**– 0.188**0.1540.0630.1870.0760.0990.037
Inflation0.0240.0080.034– 0.0470.036– 0.0020.037– 0.010
Young population– 0.0990.1590.4631.216**1.120*1.446***0.0870.528
Openness index– 0.016– 0.0230.0730.0330.0590.0360.024– 0.000
School expenditure0.030– 0.029– 1.412**– 1.699***– 1.045– 1.177*– 0.713*– 0.881**
Health expenditure– 0.0170.034– 0.081– 0.3740.128– 0.155– 0.061– 0.250
Polity2-score– 0.038– 0.007– 0.355**– 0.218– 0.076– 0.011– 0.161– 0.081
Log-GDP per capita– 1.853*– 2.105**– 1.789– 3.082*– 7.597***– 8.361***– 2.975***– 3.765***
Rural population– 0.132– 0.1650.097– 0.254– 0.464– 0.677*0.040– 0.165
Number of Observations676676676676676676676676
Number of Countries5252525252525252
F-test4.1723.05213.2638.98317.08912.50014.2839.511
R-squared0.1530.1450.5270.4860.6730.6520.5620.531
Weak identification test (Cragg-Donald Wald F-stat)29.17056.38529.17056.38529.17056.38529.17056.385
Over identification test (Sarganp-value)0.6280.4890.5320.2690.3050.2580.5790.307
Under identification test (Anderson p-value)0.2530.1260.2530.1260.2530.1260.2530.126

Note: Significance level based on robust standard errors are *** (1 %), ** (5 %), * (10 %).

The outcomes introduced in Table 4 show that there is a reasonable negative connection between the number of active borrowers and poverty indicators. The negative and significant coefficient between the number of active borrowers and poverty measures demonstrates that a more extensive inclusion of MFI causes more individuals to move out of poverty. In any case, there is no relationship between per capita loans and poverty. Per capita loans affect the Gini Index. Therefore individual loans affect poverty reduction measures.

For other control factors, we find that increments in school use and per capita GDP lead to a reduction of poverty. Then again, there is no proof of this decline utilising the Gini index. We likewise notice that nations with more youthful population will, in general, perform poorly in fighting poverty. A similar outcome is found for nations with autocratic regimes: extreme poverty (PHC_1) will increase in those nations (– 0.355**). We likewise find that nations that are focused on agricultural practices perform better as far as inequality is concerned. Income inequality is a huge problem in developing countries. Indeed, we find that agricultural practices add value, therefore, lowering the Gini index. In most developing nations, horticulture is generally for subsistence and a source of income for some individuals. The significance of the agricultural sector in developing nations can be affirmed through the negative relationship between arable land and the poverty indicators: when the level of arable land increases, the level of poverty reduces.

Causality analysis with country heterogeneity

To better identify the countries that truly benefit, we use the heterogeneous causality approach of Hurlin and Venet [2001]. This methodology is based on an estimation of the model below and compares the sum of squared residuals (SCR1) with those of three other constrained models. Recall that the study of causality between microfinance intensity (MI_Number or MI_Loans) and Pov (poverty indicators) requires stationary series. As suggested by Pesaran [2003], stationarity tests in panel data have to take into account potential cross-sectional dependence in heterogeneous panels. We therefore first perform Pesaran’s test of cross-sectional independence before choosing the panel unit-root test to use.

Table 5. Pesaran’s test of cross-sectional independence

VariablesGINIPHC_1PHC_2PGAP
(Chi-2 stat)0.2366.732**4.050***5.379***

 

This Table shows the presence of individual reliance on our information and recommends the utilisation of unit-root tests that consider this reliance. We utilise Pesaran’s unit-root test [2007] to think about this reliance. Pesaran’s trials at-test for unit establishes in heterogeneous boards with cross-area reliance. This test depends on the mean of the individual DF (or ADF) t-insights of every unit in the board.

Table 6: Panel Unit-Root Test (Pesaran [2007])

Variablest-barcv10cv5cv1Z[t-bar]P-value
Gini index– 2.068– 2.010– 2.080– 2.200– 2.3890.008
Poverty_hc (1.25 $/day)– 2.661– 2.010– 2.080– 2.200– 6.5810.000
Poverty_hc (2 $/day)– 2.602– 2.010– 2.080– 2.200– 6.1630.000
Poverty_gap (2 $/day)– 2.776– 2.010– 2.080– 2.200– 7.3950.000
MI-Number– 2.406– 2.010– 2.080– 2.200– 4.7800.000
MI-Loans– 2.904– 2.010– 2.080– 2.200– 8.2980.000

 

 

Table 6 indicates that all variables are stationary in level since we always reject the null hypothesis.

Table 7: Heterogeneous causality tests

Variables (X – Y)X not cause YY not cause X
F1-testF2-testF1-testF2-test
MI-Loans PGAP4.735***4.82***2.661***2.608***
MI-Number PGAP3.624***3.042***5.135***4.231***
MI-Loans PHC_25.331***5.428***2.243***2.184***
MI-Number PHC_24.634***3.986***5.296***4.425***
MI-Loans PHC_14.342***4.418***4.547***4.482***
MI-Number PHC14.561***3.78***4.453***3.616***
MI-Loans –   GINI3.628***3.696***3.343***3.29***
MI-Number –                    GINI4.135***3.188***4.349***4.428***

 

Table 7 outlines the two initial steps of the heterogeneous causality investigation and shows a solid validation of heterogeneous and bidirectional causality between levels of microfinance force and the different poverty measures. We can conclude that the two degrees of microfinance power has a relationship with poverty that helps lessen the rate of poverty. Be that as it may, this bidirectional causality does not affect all nations. To comprehend the consequences of the heterogeneous causality examination, we need to remember that microfinance reduces poverty through two principal channels: the number of individuals focused on and the size of the individual loans.

Table 8: Descriptive statistics (on mean values over 1996-2011)

VariablesMeanMinMax
MI-Number1.50.0        (Thailand)8.8     (Bangladesh)
MI-Loans2.10.1          (Mexico)21.5       (Lao PDR)
Per capita GDP2364.8188.4       (Ethiopia)7235.7        (Mexico)
Gini index41.928.9        (Ukraine)58.0          (Bolivia)
Poverty_hc (1.25 $/day)21.30.4          (Albania)81.0   (Madagascar)
Poverty_hc (2 $/day)37.32.5         (Bulgaria)90.6   (Madagascar)
Poverty_gap (2 $/day)16.00.5         (Bulgaria)54.6   (Madagascar)
Number of IMF10.70.3        (Malaysia)40.9    (Philippines)

 

Therefore, the question is whether microfinance institutions have a positive effect on the reduction of poverty in developing countries. The results of Table 13 indicate that the Caribbean and Latin America region has a significant majority of countries that exhibit a relationship between poverty and microfinance institutions. Countries from the region used in the study include Peru, Paraguay, Panama, Nicaragua, Mexico, Guatemala, El Salvador. Ecuador. The Dominican Republic, Costa Rica, Columbia, Brazil, Bolivia and Argentina. The countries exhibited causality and while having a high mean of microfinance institutions compared to the countries used in the sample. For example, Ecuador had twenty-eight microfinance institutions, while Mexico had twenty-five. As far as customers, this area likewise presents measurements frequently over the example normal. For instance, in Paraguay, almost 3 % and in Peru, more than 5 % of the dynamic populace approaches microcredit. In nations where access to microcredit is low, the rate of poverty is high (Argentina). Additionally, the unit value of loans is generally huge (Costa Rica has one of the biggest in the area).

In different areas, nations in which causality is observed have similar characteristics to those recognised in Latin America and the Caribbean. On account of Eastern Europe and Central Asia, we discover 7 out of 11 nations in which microfinance assumes a crucial role. In these nations (Tajikistan, Russian Federation, Armenia, Romania, Kyrgyz Republic, Georgia and Kazakhstan), the loan limits are very high. High amount per loan unit has adverse effects on poverty and inequality.

For the Asian and Pacific area, Cambodia appears to meet the achievement criteria. However, the same cannot be said for Indonesia. Therefore, the Indonesian case is supported by the hypothesis, which stated that higher loan amounts had adverse effects on poverty. MFIs in Indonesia only reach approximately 0.7% of the population. However, Indonesia is one of the nations where microfinance institutions offer the highest loan amounts.

For Africa and Middle East area, this causality is checked uniquely in Madagascar (the country with the highest level of poverty in the sample) and Uganda (one of the African nations with the largest number of microfinance institutions). Madagascar had the highest unit loan ratio in the region. In Madagascar, the level of poverty is affected by the high unit loan ratio as MFIs in the country reached 0.2% of the population. Several countries in the region have microfinance institutions reaching a small population. The unit values offered by microfinance institutions are not enough to enable people to engage in income-generating activities. Therefore, the people in these countries use loans for final consumption.

 

Conclusion

During the 2006 Nobel Peace Prize, microfinance was honoured for its contributions to reducing poverty. People who developed microfinance can be proud of coming up with a strategy of making financial services accessible to the poor. Currently, microfinance institutions have reached the people even in remote areas to provide financial services at a lower price compared to traditional banks. Despite the benefits microfinance intuitions provide, they still face opposition due to several factors. One of the reasons is that they compete with traditional banks to provide financial services. Microfinance does not focus on people who live in urban areas since most of them are employed. MFIs target low-income households, particularly in rural areas.

Development of financial systems has a great impact on the growth of the microfinance sector. The financial sector is dependent on economic growth. Thus, the lack of financial growth hurts MFIs. This is because slow economic growth affects the development of the microfinance sector. Therefore, clients are likely to shift to traditional banks due to the collapse of the microcredit sector. Clients also prefer traditional banks because of low financing costs and provisions of a variety of loans. Economic growth ensures that MFIs receive funding from traditional banks. Financial development ensures efficiency of MFIs through the introduction of banking techniques.

The presence of commercial funding has seen the growth of MFIs, especially in developing countries. The global financial crises affected the fiscal sector, thus making MFIs popular. Microfinance institutions mostly target poor people who are unable to access bank loans. MFIs provide low-income earners with loans to start small businesses from which they can generate earnings, which helps to reduce poverty. However, MFIs only assist a handful of households and do not have a significant impact on economic development, which causes a reduction in poverty. MFIs can reduce poverty if they create employment opportunities and facilitate economic growth.

The primary question is whether microfinance institutions facilitate growth in developing countries. According to Robinson (2001), MFIs facilitate growth by enabling clients to establish small and medium enterprises. Establishment of businesses enables people to escape poverty since trade generates income. However, there are those with a contrary opinion. This is because the majority of start-ups have failed; thus, owners are not in a position to escape poverty. The majority of these enterprises cease to exist three years after they had been established (George, 2005). Failure of these businesses is dangerous as it could make owners lose their remaining assets. Instead of reducing poverty, microfinance institutions may end up making people continue languishing in poverty.

Proponents of microfinance have begun to accept that MFIs institutions might have a negative impact on society. It is crucial to come up with strategies that are aimed at poverty reduction. These strategies should be comprised of poverty reduction models that have been successful. MFIs should provide Conditional Cash Transfers (CCTs) and simple cash grants. These have been proven to reduce poverty. Regulations should be put in place to ensure that financial institutions engage in activities that lead to economic development.

 

 

 

Bibliography

ACCION International, FINCA, Grameen Foundation, Opportunity International, UNITUS, and Women’s World Banking (2010) Measuring the Impact of Microfinance: Our Perspective

Armendàriz, Beatriz and Jonathan Morduch. 2000. “Microfinance Beyond Group Lending.” Economics of Transition8: 401-420

Ayyagari, M., Beck, T., and A. Demirgüç-Kunt (2003). “Small and Medium Enterprises Across the Globe “World Bank Working Paper WPS2127.

Bandiera, Oriana, Robin Burgess, Narayan Das, Selim Gulesci, Imran Rasul, Munshi Sulaiman. 2016. “Labour Markets and Poverty in Village Economies.” London School of Economics, working paper.

Bateman, M. (2010). Why Doesn’t Microfinance Work? The Destructive Rise of Local Neoliberalism. London: Zed Books.

Beck, Thorsten, Asli Demirgüç-Kunt, and Ross Levine. 2007. “Finance, inequality and the poor.” Journal of Economic Growth 12(1): 27-49.

Beck, Thorsten. 2015. “Microfinance—A Critical Literature Survey.” World Bank Independent Evaluation Group, IEG Working Paper 2015/4

Buera, Francisco, Joseph P. Kaboski, and Yongseok Shin. 2016. “Taking Stock of the Evidence on Micro-Financial Interventions.” National Bureau of Economic Research Working Paper 22674.

Cai, Shu, Albert Park, and Sangui Wang. 2016. “Microfinance Can Raise Incomes: Evidence from a Randomized Control Trial in China.” Hong Kong University of Science and Technology, mimeo

BRAU J. C., WOLLER G. M. [2004], Microfinance: A comprehensive review of the existing literature. Journal of Entrepreneurial Finance and Business Ventures 9(1), 1-26

CGAP (2002), Microcredit Interest Rates, occasional paper, November, www.cgap.org.

CRÉPON B., DEVOTO F., DUFLO E., PARIENTÉ W. [2015], and Estimating the Impact of Microcredit on Those Who Take It Up: Evidence from a Randomised Experimenting Morocco, American Economic Journal: Applied Economics, 7(1), 123-150.

Colombage, S.S., 2004. Microfinance as an instrument for small enterprise development: opportunities and constraints. Occasional paper, (52).

Cull, Robert, Asli Demirgüç-Kunt and Jonathan Morduch. 2014. “Banks and Micro banks,” Journal of Financial Services Research, 46(1): 1-53.

Dehejia, Rajeev, Heather Montgomery, and Jonathan Morduch. 2012. “Do interest rates matter? Credit demand in the Dhaka Slums.” Journal of Development Economics 47 (2): 437 -499.

Denise, F. Cheryl, B. & Hunger, B. (eds). (2001). Essentials of Nursing Research Methods, Appraisal and Utilization. New York: Baltimore

González, A. Is Microfinance Growing Too Fast? Microfinance Information Exchange: Washington, DC, USA, 2010

Guérin, Isabelle, Santosh Kumar and Isabelle Agier. 2010. “Microfinance and Women’s Empowerment: Do Relationships between Women Matter? Lessons from rural Southern India.” Centre for Research on Microfinance, Universite Libre de Bruxelles.

Hassan, M., Sanchez, B., & Yu, J. (2011). Financial development and economic growth: New evidence from panel data. The Quarterly Review of Economics and Finance, 51(1), 88-104. https://doi.org/10.1016/j.qref.2010.09.001

Helms, Brigit. 2006. Access for All: Building Inclusive Financial Systems (An Excerpt). Washington DC: CGAP

Hudon, Marek and Daniel Traca (2011). “On the Efficiency of Subsidies in Microfinance: An Empirical Inquiry.” World Development 39(6): 966-973.

Karlan, Dean and Jonathan Zinman. 2016. “Long-Run Price Elasticities of Demand for Credit: Evidence from a Countrywide Field Experiment in Mexico.” Working paper, Yale University and Dartmouth College.

Karlan, Dean and Jonathan Morduch. 2009. “Access to Finance”.In Dani Rodrik and Mark Rosenzweig, eds., Handbook of Development Economics, Volume 5. Amsterdam: Elsevier, pp. 4704 – 4784.

Kabeer, N., (2001) “Conflicts Over Credit: Re-Evaluating the Empowerment Potential of Loans to Women in Rural Bangladesh” World Development Vol.29, No. 1, pp. 63-84.

LITTLEFIELD E., MURDURCH J., HASHEMI S. [2003], Is Microfinance an Effective Strategy to reach the Millennium Development Goals?, CGAP Focus Note, Washington, DC

McKenzie, David. 2015. “Identifying and Spurring High-Growth Entrepreneurship: Experimental Evidence from a Business Plan Competition.” World Bank policy research working paper 7391.

McIntosh, Craig and Bruce Wydick, 2005. “Competition and Microfinance.” Journal of Development Economics, 78(2): 271-298

MIX Market (2017). Global Outreach & Financial Performance Benchmark Report – 2015.Washington, DC: The MIX Market.

RHYNE E., (2009), Microfinance for Bankers and Investors, McGraw Hill, New York.

Robinson, M. (2001) The Microfinance Revolution: Sustainable Finance for the Poor. Washington, DC: World Bank.

Rosenberg, R.; González, A.; Narain, S. The New Moneylenders: Are the Poor Being Exploited by High Microcredit Interest Rates? CGAP: Washington, DC, USA, 2009

Swain, R.B., Sanh, N.V. and Tuan, V.V., 2008. Microfinance and poverty reduction in the Mekong Delta in Vietnam. African and Asian Studies, 7(2-3), pp. 191-215.

Vanroose, A.; D’Espallier, B. Do microfinance institutions accomplish their mission? Evidence from the relationship between traditional financial sector development and microfinance institutions’ outreach and performance. Appl. Econ. 2013, 45, 1965–1982

World Bank, 2009a. “World Development Report 2010: Development and Climate Change”, Washington D.C: the World Bank

  Remember! This is just a sample.

Save time and get your custom paper from our expert writers

 Get started in just 3 minutes
 Sit back relax and leave the writing to us
 Sources and citations are provided
 100% Plagiarism free
error: Content is protected !!
×
Hi, my name is Jenn 👋

In case you can’t find a sample example, our professional writers are ready to help you with writing your own paper. All you need to do is fill out a short form and submit an order

Check Out the Form
Need Help?
Dont be shy to ask