The Role And Impact Of Micro Finance Institutions

INTRODUCTION

The strong economic growth is bound to create employment opportunities and therefore it will reduce unemployment. The evidence provided by the Labor Force Survey 2005 (First two quarters) clearly supports the fact that economic growth has created employment opportunities. Since 2003-04 and until the last half of 2005-06, 5.82 million new jobs have been created as against an average job creation of 1.0-1.2 million per annum. Consequently, unemployment rate which stood at 8.3 percent in 2001-2002 declined to 7.7 percent in 2003-04 and stood at 6.5 percent during July-December 2005.The rising pace of job creation is bound to increase the income levels of the people. Agriculture, housing and construction, IT and telecom sector, and SME are the sectors, which have created relatively more jobs. The estimation of poverty line enables the policy makers to further identify and group the population into various ‘poverty bands’ such as extremely poor, vulnerable and non-poor etc.

The current growth rates however need to be strengthened to arrest the current growth in poverty levels. Macro stabilization, governance reforms and re-profiling of external debt stock have created prospects for growth in future. The government has indicated its willingness to speed up the pace of structural reforms to meet the major challenges of:

Reducing poverty,

Improving governance and administration,

Improving the fiscal and balance of payments positions,

Restoring investor confidence,

Achieving higher growth on a sustainable basis, and

Improving social indicators.

1.1 MICROFINANCE SECTOR

Microfinance in Pakistan is relatively a new concept as compared to other countries in the region. The NGOs and Rural Support Programs has been the major player in the sector since early 1980s covering about 5% of more than 6.5 million poor households in the country. Recognizing microfinance as an important poverty alleviation tool, the Federal Government has adopted a microfinance policy that mainstreams the concept of sustainable microfinance, recognizes the private sector’s role in poverty reduction and encourages its entry into banking with the poor. It has enacted a legal framework, the MFIs (Micro Financing Intermediaries) Ordinance 2001, for establishing Microfinance Banks in private sector and also facilitated establishment of Khushhali Bank, a public private partnership, with twin objective of substantially increasing outreach of microfinance services in the medium term and giving a model institution to the private sector to follow.

The MFIs Ordinance 2001 inter alia stipulates the functions, capital requirements, ownership structure, terms and conditions for establishing Microfinance Banks/Institutions in the country, audit and disclosure requirements and winding up procedures. The provisions of the ordinance are applicable on microfinance institutions mobilizing savings from public to finance their operations. The operations of NGOs and other programs providing micro credit and allied services through sources other than public deposits/savings are not covered under the ordinance. The framework allows establishment of three categories of formal microfinance banks in the country via:

Nation wide MFBs - minimum paid-up capital of Rs.500 million

Province wide MFBs - minimum paid-up capital of Rs.250 million and

District wide MFBs - minimum paid-up capital of Rs.100 million

1.2 EVOLUTION OF MICROFINANCE IN PAKISTAN

The microfinance movement in Pakistan followed a unique evolutionary path over the last decades. The proceeding paragraphs present the three development phases of the sector. Each phase represents entry of new institutional forms and structures in the Pakistani microfinance sector. Some of the highlights of this 30 year old history are as follow:

Phase-1: 1970s, Government directed credit. The use of finance (mostly credit) as a development tool has a history in Pakistan in the form of government directed/subsidized credit schemes particularly in rural areas. In recent years Small Business Finance Corporation (SBFC), Youth Investment Promotion Society (YIPS), Self Employment Scheme (SES) and Yellow Cab Scheme are typical examples. While SBFC and YIPS represent a direct institutional intervention through use of public funds and institutional structures, SES and Yellow Cab schemes represent indirect government pressures on financial institutions, both public and private; to engage in politically motivated directed credit. In the last two initiatives, the government literally forced commercial financial institutions (mostly public sector) to provide concessionary financing especially to unemployed youth and business start-ups. The loan defaults associated with these schemes affecting the financial institutions profitability has been extensively reported in the popular press.

Phase - 2: early 1980’s to mid 1990’s - philanthropy of finance. The emergence of the Pakistani microfinance sector is usually traced to two pioneering development institutions - The Aga Khan Rural Support Program (AKRSP) and the Orangi Pilot Project (OPP).

The early pioneers was established in 1982 by the Aga Khan Foundation (http:// www.akdn.org/), AKRSP was the first Integrated Rural Development Program of its kind, outside the government domain. It has focused its development interventions on the Northern Areas of Pakistan. The later day Rural Support Programs (RSPs), initiated by the government, were inspired by the AKRSP model of rural development. The first large scale practical implementation and conceptualization of development frameworks such as “social mobilization? and “group lending methodology? can be traced to AKRSP’s microfinance model initiated in 1982.

While AKRSP pioneered development service provision in the rural, agrarian frontiers of north Pakistan, OPP took up the challenge of tackling urban poverty in the biggest slum settlement in Pakistan’s port city and commercial capital - Karachi. OPP was established by Akhtar Hameed Khan, considered to be the father of rural development in Pakistan. OPP was established in 1987 and its development services include housing, sanitation and education.

The RSP model, AKRSP formulated and implemented integrated development approach whereby rural population was organized into Village Organizations (VOs) and the needs prioritized by these community organizations were provided for through a broad range of development services such as education, health, sanitation as well as financial services (microfinance). AKRSP endeavored to develop human, social and financial capital of the communities it worked with. This integrated approach was replicated by government initiated development organizations called Rural Support Programs (RSPs). By 2004, RSPs were working with more than 43,000 community organizations comprising of more than 1,000,000 households.

Sarhad Rural Support Program (SRSP) was the first RSP to be established in 1989 as a replication of AKRSP model in the North-West Frontier Province of Pakistan. In the same year a Pak German development project was restructured as an RSP and renamed as Balochistan Rural Support Program (BRSP). Later on Punjab Rural Support Program (PRSP) was also launched by the Government of the Punjab province.

The establishment of National Rural Support Program (NRSP) (www.nrsp.org.pk) in 1992 has a special significance. While SRSP and BRSP had provincial focus, NRSP was meant to be the largest national RSP with development interventions including a very ambitious microfinance program all over Pakistan.

The rural focused microfinance operations of NRSP have expanded into urban areas as well under its Urban Poverty Alleviation Program (UPAP).

With the above mentioned perspective, the microfinance strategy during the early 1990’s has certain common elements; the word “micro credit? was used instead of microfinance symbolizing provision of only loans (and compulsory savings) as a social service equivalent to other development needs such as education, health, sanitation etc. Microfinance best practices as we know them today were still in their formative stages and had not crystallized into a coherent set of principles and frameworks even at the international level.

Phase-3: late 1990’s till the present - entry of the specialist MFI. The later part of 1990’s saw the entry of regulated financial institutions such as commercial banks and leasing companies in the microfinance arena. Mostly urban based microfinance - only programs also came up in major cities of Pakistan. Regulatory structures started taking shape, spawning a new microfinance institutional structure - The Microfinance Bank (MFB).

1.3 VIABILITY OF PROPOSED MICROFINANCING BANK (MFB) IN THE COUNTRY

In the light of the above scenario the establishment of the proposed micro financing bank (MFB) in the country raises many doubts about its effectiveness to reduce poverty, sustainability to survive in the long run, and opportunity cost of resources diverted from other potential projects towards the MFB.

The banking sector in the country has a long history of poor targeting and high default rate in the economy. The past experience of cooperative societies in the country is also that of a disaster. Million of rupees were lost in these schemes on the name of credit. Mainly their borrowers as well as defaulters are from the high-income group and influentials in the society.

An evaluation of the pilot project for micro financing of the National Bank of Pakistan (NBP) for the future establishment of the proposed MFC is also not very encouraging. The bank does not have any mechanism to identify the poor regions and poorest in the country to provide micro credit. There are no poverty profiles that can indicate, which regions are the poorest and which villages or localities are severely impoverished in different provinces of the country. Therefore, the loans are mainly provided on the basis of subjective criteria which increase the chances of poor targeting of the scheme.

Similarly, the bank does not have the experience, culture and environment for providing microcredit to poor in the country. The procedure for credit and collateral requirements of the bank is so complicated that it not only excludes the poorest from the scheme but it also increases the chances of leakage in the scheme. In fact, during a field visit by the author in one of the pilot project areas in Sindh, it was observed that the bank borrowers are paying extra charges/commission for receiving the inputs from the bank recommended dealers.

Ironically, there is neither women staff nor woman borrowers in the pilot project area of NBP, whereas one major objective of the program is “the empowerment of women through micro financing and women should be 33% among the borrowers?.

Other major NGO’s providing micro financing in the country are Agha Khan Rural Support Program (AKRSP), National Rural Support Program (NRSP), Sarhad Rural Support Program (SRSP), Orangi Pilot Project (OPP), SUNGI Development Foundations, Kashf Foundation (Kashf), Sindh Agricultural & Forestry Workers’ Cooperative Organization (SAWFCO), Thardeep Rural Development Program (TRDP). Moreover some international donor agencies like OXFAM and Save the Children Fund (SCF) also provide providing microfinance through intermediary NGO’s in different parts of the country (www.spdc.com.pk)

1.4 PROBLEM STATEMENT

Studies illustrated that poverty exerts a significant impact on education, health status, savings and the real GDP. For example; the evidence on reducing vulnerability however, is somewhat clearer. The provision of micro credit has been found to strengthen crises coping mechanisms, diversify income earning sources, build assets and improve the status of women (Hashemi et al, 1996);

H0 : Micro financing has not reduced the poverty.

H1 : Micro financing has reduced the poverty.

This hypothesis suggests that as micro financing affects poverty in a positive manner, as a result, education, health status, saving and real GDP of the household has a positive relationship with the micro financing.

The existing evidence on the impact of micro credit on poverty is not clear-cut. There is a work that suggests that access to credit has the potential to significantly reduce poverty. (Khandker, 1998); On the other hand, there is also a research which argues that micro credit has minimal impact on poverty reduction, (Morduch, 1998);

Being a finance student the motivation was previous research which was very broad but not specific to the chosen statement. A broader perspective was present but the absence of narrower contexts compelled me to undertake this research. The study has many aims. The main purpose was to address the problem of poverty and apply it to the national scenario. Efforts are directed to utilize and process all available data, avoid bias and error, and generate important results.

1.5 OBJECTIVE OF THE STUDY

The specific objectives for the study are outlined as follow:

1. To assess the role and impact of micro-finance institutions on the livelihood of poor.

2. To assess factors that hinders the rural poor from participating in Micro finance Institutions

3. To draw conclusion and give some policy recommendations for the successful implementation and development of micro financing programs.

Rest of the project is organized as follows. In chapter two we have provided literature review, in chapter three we have defined data and methodology, in chapter four the results have been explained and in chapter five we have concluded the project with some recommendations.

CHAPTER NO.2

LITERATURE REVIEW

In the past few years there is an increase in research in the area of Micro Financing. Micro finance or micro credit, by providing small loans and saving facilities to those who are excluded from commercial financial services has been promoted as a key strategy for reduction or combating poverty. Access to these facilities is seen as away of providing the client that are economically active with opportunities for self reliance through entrepreneurship, cushioning them against economic shocks, and providing a mean of social empowerment for poor women and men in their communities. Yet although microfinance programs are often driven by a moral imperative to alleviate poverty, the extent to which they are able to reach the poor with their services and likely economic and social impacts continue to be issues of debate.

Binswanger and Landell-Mills (1995) states that constraints in relation to suppliers.i.e. Private Banks excludes the poor because small transactions are unprofitable. Providing financial services to the poor and women is not easy. Many borrowers are not credit worthy and don't have profitable projectors. Thus, that the need for micro financing is an undeniable fact.

According to Yanor, Benjamin and Pipren (1997), the issue that should be raised in this context is the importance of the informal sector in LDCs economy and its constraint to develop by lack of credit. On top of that, Salad vine and checkering (1991) confirmed this fact by noting that, “the informal sector? which contributed about 35% to 65% and 20% to 40% to employment and GDP in most LDCs respectively, is constrained by lack of credit.

The provision of micro credit has been found to strengthen crises coping mechanisms, diversify income earning sources, build assets and improve the status of women (Hashemi et al, 1996);

Coleman (1999),in his study of a village-banking program in Thailand, advances the literature by expanding on this concept to control for self-selection biases and introduces both observable village characteristics and village fixed effects to control for program placement bias. Utilizing data on 455 households, including participating and non-participating households in treatment villages where a village bank is already offering micro credit, and selected future participants and non-participants in control villages that have been identified to receive a village bank program but have not yet actually received funds, Coleman uses a difference-in-difference approach that compares the difference between income for participants and non-participants in program villages with the same difference in the control villages, where the programs were introduced later.

Zaman (1999); explored the relationship between micro credit and the reduction of poverty and vulnerability by focusing on BRAC, one of the largest micro credit providers in Bangladesh. He concluded that micro credit contributes to mitigating a number of factors that contribute to vulnerability, whereas the impact on income poverty is a function of borrowing beyond a certain loan threshold and to a certain extent contingent on how poor the household is to start with. His empirical analysis also suggested that micro credit has the greatest on female control over assets and also on her knowledge of social issues controlling for a host of other characteristics.

The Need For Micro-Financing

According to Khandker (1998), the alleviation of poverty requires diverse measures. The most important being those, which expand the income and employment opportunities of the poor, enabling them to enhance their living standards providing the poor with access to financial services is one of the many ways to increase their income and productivity.

Micro financing programs are developed to fill this gap. The rural poor in LDCs are in desperate needs of credits, microfinance programs are supposed to make available this credit needs and keep the poor to increase their living standard. Lack of saving and capital make it difficult for many poor people who want jobs in the formal and informal sectors to become self employed and to undertake productive employment generating activities, providing credit seems to be a way to generate self-employment opportunities for the poor.

In this regard, MFIs in relation to other financial intermediaries has special role and distinguishing features which are given as follows:

The primary objective of MFIs is to address the credit needs of those who are willing and ready to reduce their chronic poverty by engaging in farming and small scale production and service activities (Getahun, 2001).

Besides provisions of credit facilities, MFIs render managerial, marketing technical and administrative advise to borrowers by reaching borrowers at there place of work.(ibid)

MFIs do not require collateral to extend credit in cash or kind to peasant farmers and small entrepreneurs. Instead peer group-leading scheme, character based loans and the promise of subsequent loans is main motivations for repayment (Marguerite, 2001).

Saving requirement is introduced as a compulsory feature of lending activity and this saving requirement seems to serve as a motivator for repayment of loan since borrowers choose to repay the loan than losing the amount they saved (Getahun, 2001)

2.2 Country Experiences on Micro-financing

2.2.1 Experience of Bangladesh

Why it is that micro-finance becomes a great concern for the whole world as an instrument for poverty reduction in rural areas? It seems because it has recorded success in countries where it has been implemented Abiy (2000). A brief look at this success stories is as follows.

One of the most successful countries often mentioned in the development of microfinance is Bangladesh. Micro finance organizations like Grameen Bank, Bangladesh Rural Advancement Committee (BRAC), Proshika (PK), Association for Social Advancement (ASA), largest 20 credit NGOs (not including Grameen Bank), and Bangladesh Rural Development Board (BRDB) are operating in the country mentioned

For instance, the Grameen Bank, which was established in 1983 as a challenge to existing collateral-based financial system, has had a promising result. It operates exclusively for the poor on the promise that rural people, who won too little land, support themselves as farmers, can never the less make productive use of small loans and repays them on time. The bank also promotes social development by making the poor accountable to individually and socially. Such intermediation improves productivity and income of the poor. This, in turn, also improves their loan payment rate and hence contributes to the Grameen Bank’s financial Viability. As the result it is the most successful credit program for poor and this may be seen from the outreach status and loan recovery so that the bank’s loan recovery rate has consistently remained above 90 percent Pit and Khandker (1998).

2.2.2 Experience of some African Countries

Formalized micro finance institutions’ in Africa is a more recent phenomenon. The 1950s and 1960s led to a proliferation of rural leading programs that focused on the provision of subsidized credit by government development banks. After this period in 1980s, the replication of Bangladesh’s Grameen Bank began to be tested using primary donor funds to provide credit to a wide number of solidarity group members (Paxton and Fruman, 1998).

For our purpose, however, we will look only two countries Kenya and Burkina Faso- the former representing relatively densely populated region and the latter is less densely populated.

For example, in Kenya KREB (Kenya Rural Enterprise Bank) is a micro finance institution serving the poor in rural and urban areas of Kenya. It was established as an intermediary NGO to provide financial and technical assistance to NGOs in Kenya that are involved in developing or promoting the development of micro and small enterprises.

Since 1990, KREB has successfully transformed grants from its development partners into loan capital for nearly 30,000 businessmen and women. It has been able to do so at a positive return since 1994. KREB has distributed over Kenyan shilling 300 million each year since 1995 and has never run short of new customers.

The PPPCR (Le project de promotion du petit credit rural) has been particularly innovative in adopting the Grameen style of group lending to the conditions in Burkina Faso. Certainly the sahelian region represents one of the most challenging environment for micro finance due to the combinations of failed prevails efforts low population density, poverty and illiteracy. To overcome some of these obstacles, PPPCR has departed from a pure Grameen replication and has adapted its own financial services and organization.

Like the Grameen Bank, PPPCR has grown quickly, but cannot be compared in member of clients. By the end of 1994, PPPCR had served 10,000 clients, and two years later it had reached about 25,000 clients. Despite all of the careful modifications of the Grameen model to the Burkina Faso context, the provision of micro finance services has proved to be quite costly in the Sahel. The reasons for these high costs are more related to the environment (low population density, poor infrastructure, poverty, illiteracy etc.) than to the methodology of group lending itself. The PPPCR has experienced greater efficiency in the past couple of years as it continues to learn from its early experience & achieves economies of scale.

Generally, the results in this study have shown that none of the institutions have been able to cover the cost of subsidies despite in roads towards financial viability. Most of micro finance institutions limit their ability to achieve high volumes of loan advances and savings. In sum, the most important lesson is that a wide variety of market niches exist in the field of micro finance.

In a more recent study, James et al, (2001) estimated the impact of an urban credit program in Zambia on business performance and on a range of indicators of household well-being. They found that borrowers who obtained a second loan experienced significantly higher average growth in business profits and household income. The Bolivian experience indicates that all the institutions studied had, on balance, positive impacts on income and asset levels. (Mosley 2001);

In Pakistan’s context, Khan (2001); estimated the economic impact of the support program on rural households. He concluded that the economic impact of the support program on rural households is substantially large and probably makes a significant difference to the households close to the poverty line. However, he qualified this conclusion by arguing “this conclusion holds particularly for those rural households that participate on a sustained basis over a long period?. However, international experience strongly suggests that microfinance projects do not reach all segments of poor. Even the minimal or no collateral requirements potentially exclude the poorest from the schemes. In Bangladesh, for example, only one forth of all microfinance clients is among the hard-core poor. The UNDP report (2000) claims that “the hard-core poor having few assets are reluctant to take on the risks of credit, and when they do, it is usually for emergencies and consumption, not for production?. Extending financial services to the poorest requires innovations which go beyond those that have been developed so far.

Morduch (1999); argued, “The promise of micro finance should be kept in context. Even in the best of circumstances, credit from micro finance programs help find self employment activities that most often supplement income for borrowers rather than drive fundamental shifts in employment patterns. It rarely generate new job for others, and success ha been especially limited in regions with highly seasonal income patterns and low population densities. The best evidence to date suggests that making a real dent on poverty rates will require increasing overall levels of economic growth and employment generations.

Micro finance may be able to help some households take advantage of those processes, but nothing so far suggests that it will drive them. The experience of micro finance in Pakistan is not that different from other countries, it is generally recognized that the present micro financing framework is characterized by low coverage (an inability to reach the poor), targeting inefficiency (the poorest are left out, inadequate of support (insufficient loan sizes), a low degree of ease of lack of self financing (dependence on donors).

Rodriguez-Meza (2001); studies strategic defaults in microfinance. More specifically, he evaluates the effect of different contract designs on borrower repayment behavior for both individual and joint liability contracts. Rodriguez-Meza’s model shows that lenders willing to grant loans large enough for borrower to achieve their optimal level of investment may face sustainability problems, as borrowers may find it optimal to default under these circumstances. He finds that clients can default on their loans even when they have the ability to repay due to the absence of perfect collateral. His results have serious implication for the viability of MFOs and their role in economic development.

In addition to these studies, practitioners, donors and academics concerned about the negative effects of client exit on the overall sustainability of MFOs have conducted several descriptive studies on the issue (Hasan and Shahid, 1995); Khan and Chowdary, 1995; ASA, 1996; Kashangaki, 1999; Maxima Bali, 1999; Painter and MKNelly, 1999; Simanowitz, 1999; Wright et al, 1999; Churchill, 2000; Kuwik and Mashaba, 2000; Churchill and Halpern, 2001; Schreiner, 2001;.Overall, they found that most people are pushed out of MFOs, especially in Africa, due to adverse push factors, such as client maturity and competition, also play a role in pulling clients away from MFOs, especially in Latin America and Asia, where the micro finance industry is more developed and competition is more intense.

The government’s goal of poverty reduction is to be realized through a comprehensive approach that takes into account the interaction of economic, social and governance dimensions. The approach is outlined in the interim poverty reduction strategy paper (IPRSP).Expenditure and budgetary allocations for poverty reduction measures have been enhanced. The poverty alleviation program of the government has five elements:

Small infrastructure projects,

Social safety net,

Food support program,

Improving social indicators and

Expanded access to MF and skills development services through grassroots Organization such as NGOs and village organizations.

Greater private sector involvement in poverty reduction is envisaged. The social action program phase two (from January 1997 to June 2002) aims to improve access to basic social services like primary education, primary health care, population welfare services, potable water, sanitation and middle schooling. The government has also responded to growing unemployment, with a series of scheme including the mass self employment program. The incidence of poverty is to be reduced from 33% of population to be target kevel of 15.1% be end 2008.

To enhance outreach of MF, the government has adopted a comprehensive approach to address issues and constraints through a conductive policy framework, appropriate supervisory and regulatory infrastructure, institutional capable of outreach to the poor and finally, investments in social intermediation and basic infrastructure. The government has plans to restructure DFIs.Emphasis will be placed on good governance, sustainability, and public private partnership, community based services delivery through NGOs, Pro-poor focus and gender concerns. This strategy complements the effort of the PPAF and other MF suppliers and provides the basic for a concerted effort to enhanced outreach in a grossly underserved market.

Gender focus will be emphasized in the strategies and underlying activities in various government programs. A permanent commission on the status of women has been formally announced to protect women’s rights. The IPRSP also recognizes the gender dimension of poverty and proposes reform of discriminatory laws and measures to coordinate policies. Within the IPRSP framework, a review and modification of economic and social policies to incorporate gender perspectives is planned. Strengthening of gender focal points in federal and provincial women development departments and identification of targets for the implementation of the National Action Plan (Ministry of Women Department) have been envisaged.

On the basis of the literature reviewed, we have developed the following conceptual framework.

Fig 2.1 DEVELOPMENT OF CONCEPTUAL FRAMEWORK

Poverty

Micro financing in education, health status, savings and real GDP

Dependent variable Independent Variable

P= f (EDU, HS, SAV, RGDP)

Where,

EDU = Education

HS = Health Status

SAV = Savings

RGDP = Real Gross Domestic Product.

CHAPTER NO.3

DATA & METHODOLOGY

This part of the report illustrates the methodology that will be used to conduct this study. The conceptual framework for the study is depicted in Fig 2.1. We want to study the dependence level of the dependent variable and its association with the independent variables. Pool regression analysis is a well recognized methodology to analyze relationships and dependence among different variables.

The research instruments used in this study were ordinary least square multiple regression analysis, Granger causality test. In view of the limited time frame of the study the sample size was restricted to thirty one. This study was descriptive in nature and deals with the most important and alarming issue of Micro financing.

REGRESSION ANALYSIS:

In statistics, regression analysis is a collective name for techniques for the modeling and analysis of numerical data consisting of values of a dependent variable (also called response variable or measurement) and of one or more independent variables (also known as explanatory variables or predictors). The dependent variable in the regression equation is modeled as a function of the independent variables, corresponding parameters ("constants"), and an error term. The error term is treated as a random variable. It represents unexplained variation in the dependent variable. The parameters are estimated so as to give a "best fit" of the data. Most commonly the best fit is evaluated by using the least squares method, but other criteria have also been used.

Regression can be used for prediction (including forecasting of time-series data), inference, and hypothesis testing, and modeling of causal relationships. These uses of regression rely heavily on the underlying assumptions being satisfied. Regression analysis has been criticized as being misused for these purposes in many cases where the appropriate assumptions cannot be verified to hold.

T – TEST

A t-test is any statistical hypothesis test in which the test statistic has a t distribution if the null hypothesis is true. It is applied when the population is assumed to be normally distributed but the sample sizes are small enough that the statistic on which inference is based is not normally distributed because it relies on an uncertain estimate of standard deviation rather than on a precisely known value.

COEFFICIENT OF DETERMINATION

In statistics, the coefficient of determination, R2 is used in the context of statistical models whose main purpose is the prediction of future outcomes on the basis of other related information. It is the proportion of variability in a data set that is accounted for by the statistical model. It provides a measure of how well future outcomes are likely to be predicted by the model.

DURBIN–WATSON STATISTIC

The Durbin–Watson statistic is a test statistic used to detect the presence of autocorrelation in the residuals from a regression analysis. It is named after James Durbin and Watson. If et is the residual associated with the observation at time t, then the test statistic is

Since d is approximately equal to 2(1-r), where r is the sample autocorrelation of the residuals,[1] d = 2 indicates that appears to be no autocorrelation, its value always lies between 0 and 4. If the Durbin–Watson statistic is substantially less than 2, there is evidence of positive serial correlation. As a rough rule of thumb, if Durbin–Watson is less than 1.0, there may be cause for alarm. Small values of d indicate successive error terms are, on average, close in value to one another, or positively correlated. If d > 2 successive error terms are, on average, much different in value to one another, i.e., negatively correlated. In regressions, this can imply an underestimation of the level of statistical significance.

TEST OF SIGNIFICANCE

"A statistically significant difference" simply means there is statistical evidence that there is a difference; it does not mean the difference is necessarily large, important, or significant in the common meaning of the word.

The significance level of a test is a traditional frequents statistical hypothesis testing concept. In simple cases, it is defined as the probabilities of making a decision to reject the null hypothesis when the null hypothesis is actually true (a decision known as a Type I error, or "false positive determination"). The decision is often made using the p-value: if the p-value is less than the significance level, then the null hypothesis is rejected. The smaller the p-value, the more significant the result is said to be.

In more complicated, but practically important cases, the significance level of a test is a probability such that the probability of making a decision to reject the null hypothesis when the null hypothesis is actually true is no more than the stated probability. This allows for those applications where the probability of deciding to reject may be much smaller than the significance level for some sets of assumptions encompassed within the null hypothesis.

The following model is generated after analyzing the theoretical framework.

P= f (EDU, HS, SAV, RGDP)

P= C + B1 EDU + B2 HS + B3 SAV + B RGDP

Where,

P = Poverty

EDU = Education

HS = Health Status

SAV = Savings

RGDP = Real Gross Domestic Product

HYPOTHESIS

After the analysis of the theoretical framework and the model the following hypothesis are generated.

The “impact on poverty? is influenced by the following variables

Education

Health Status

Savings

Real GDP

Poverty = f (Micro financing in Education, Health Status, Savings, and Real GDP)

Hypothesis in statistical form is narrated as

H0 : β = 0

That there is no relationship of the above mentioned variables with the poverty.

Hı: β ≠ 0

That there is a relationship of education, health status, savings and real GDP with micro financing.

Or we can say that

An appropriate financing tool for low-income people leads them to uplift their income and savings.

Increase in income and savings of low-income people enable them to contribute in the development of social status and social structure.

When the income of a household will increase, it will ultimately increase the expenditure on education and health.

CHAPTER NO.4

RESULTS

The results of the study and the vital statistical measures are shown in the tables and then the hypotheses are tested for the accuracy. Firstly, every effect obtained by using the pooled data is discussed. Finally, the hypotheses are tested on the basis of significance test.

Table 4.1 Descriptive Stats

 

POV

EDU

HS

SAV

RGDP

Mean

82.75

98.33556

153.12

604.7967

-1.05556

Median

63.8

98.34

160.07

564.5

0

Maximum

131

111.1

215.5

1206.8

23.1

Minimum

49.6

82.8

98.27

160.57

-33.84

Std. Dev.

32.22468

9.528934

44.42356

427.5875

16.52883

Observations

31

31

31

31

31

Table 4.2 presents the results of descriptive stats across the variables we have selected. The total numbers of observations undertaken during the research are 31.

Table 4.2 Correlation Table

 

POV

EDU

HS

SAV

RGDP

POV

1

0.669025351

0.409382256

0.030883716

-0.53541

EDU

0.669025351

1

0.67371188

0.607326216

-0.16211

HS

0.409382256

0.67371188

1

0.774163

0.261008

SAV

0.030883716

0.607326216

0.774163

1

0.173355

RGDP

-0.535414159

-0.162110489

0.261007506

0.173354666

1

Table 4.2 presents the results of correlation across the variables we have selected. The correlation values among Poverty & Savings, Poverty & RGDP, Education & RGDP and Health status & RGDP are found to be low.

Table 4.3 Causality Test

Two way relationships are explained by causality. So we name this test as Pair wise Granger Causality test.

Pair wise Granger Causality Tests

 

 

Null Hypothesis:

F-Statistic

Probability

 

 

 

POV does not Granger Cause EDU

1.04751

0.35302

EDU does not Granger Cause POV

0.19883

0.67431

POV does not Granger Cause HS

1.83585

0.23344

HS does not Granger Cause POV

0.72722

0.43273

POV does not Granger Cause SAV

3.60483

0.13044

SAV does not Granger Cause POV

1.11491

0.35057

POV does not Granger Cause RGDP

2.07521

0.20926

RGDP does not Granger Cause POV

0.29329

0.61137

EDU does not Granger Cause HS

0.62858

0.46382

HS does not Granger Cause EDU

0.00997

0.92433

EDU does not Granger Cause SAV

1.16036

0.34202

SAV does not Granger Cause EDU

0.57798

0.48945

EDU does not Granger Cause RGDP

2.69949

0.1613

RGDP does not Granger Cause EDU

1.87547

0.22915

HS does not Granger Cause SAV

0.39185

0.56528

SAV does not Granger Cause HS

2.63726

0.17971

HS does not Granger Cause RGDP

0.39708

0.55627

RGDP does not Granger Cause HS

1.71224

0.24761

SAV does not Granger Cause RGDP

0.00048

0.98356

RGDP does not Granger Cause SAV

0.00422

0.95133

Table 4.3 provides the test of causality. Results show that in all the cases we failed to reject the null hypothesis, i.e.; variable i doesn’t affect variable j significantly,

Where

i, j= Poverty, Education, Health status, Savings and RGDP, such that i ≠ j.

Table 4.4 OLS Regression

Dependent Variable: Poverty

Method: Least Squares

Variable

Coefficient

t-Statistic

Prob.

 

 (Slope)

C

133.7116

15.83492

0.0001

EDU

-0.057115

-0.373254

0.7279

HS

0.024077

0.145556

0.8913

SAV

-0.141915

-0.870543

0.4331

RGDP

0.018588

3.430898

0.0265

R-squared

0.208634

Adjusted R-squared

-0.384891

S.E. of regression

7.025312

Durbin-Watson stat

1.743389

Table 4.4 presents the multiple regression result for the following model.

Poverty = f (Micro financing in Education, Health Status, Savings, and Real GDP)

P= f (EDU, HS, SAV, RGDP)

P= C + B1 EDU + B2 HS + B3 SAV + B RGDP

It is found that the coefficient (slope) of education & savings are with correct theoretical signs. The remaining variables are with wrong signs. The coefficient which are statistically significant are also the same i.e. education & savings. The value of R² (coefficient of determination) is found to be low, suggesting no problem of multi-co linearity. Durbin-Watson test shows that there is no problem of auto-correlation.

Table 4.5 OLS Regression Log

Dependent Variable: Log Poverty

Method: Least Squares

Variable

Coefficient

Std. Error

t-Statistic

Prob.

 (Elasticity)

C

-151.13

41.88386

-3.608312

0.0226

LEDU

1.800471

0.526959

3.416721

0.0269

LHS

0.621705

0.136172

4.565588

0.0103

LSAV

-0.065215

0.012087

-5.395264

0.0057

LRGDP

-1.019242

0.228874

-4.453297

0.0112

R-squared

0.960243

 

Adjusted R-squared

0.920485

S.E. of regression

9.086818

Durbin-Watson stat

1.954621

Table 4.5 presents the log regression result for the following model.

Poverty = f (Micro financing in Education, Health Status, Savings, and Real GDP)

P= f (EDU, HS, SAV, RGDP)

P= C + B1 EDU + B2 HS + B3 SAV + B RGDP

It is found that the coefficient (elasticity) of savings & RGDP are with correct theoretical signs. The remaining variables are with wrong signs. The coefficients which are statistically significant are education, health status, savings, and real GDP. The value of R² (coefficient of determination) is found to be high, suggesting problem of multi-co linearity. Durbin-Watson test shows that there is no problem of auto-correlation.

On the basis of results, we have concluded the whole project with some recommendations in the next chapter.

Chapter no.5

CONCLUSION & RECOMMENDATIONS

CONCLUSION

Poverty is a multifaceted phenomenon that includes, but goes beyond lack of adequate income. The overarching objective of development in many countries has been and continuous to be the eradication of all faces of poverty. Rapid as well as distributed growth in income has always been viewed as an instrument for achieving this objective.

Pakistan has in the last three years initiated a bold reform program for accelerating growth as well as a focused third generation microfinance sector development program providing a conducive policy framework and support mechanisms to encourage private instruments in the sector.

The framework allows everyone to contribute for poverty reduction according to their priorities and competency. The framework provides NGOs a long-term resource support for social services as well as micro credit in a transparent manner based on the quality of their outputs.

The state bank of Pakistan provides for a regulatory framework allowing for the establishment of licensed MFIs, which can mobilize resources from local markets. The government has set up mechanisms for sharing social intermediation costs and risks of banking with the poor.The government will continues to play a catalytic role and it is now for the donors, private investors, civil society institutions and development organizations to take advantage of and make their contribution for poverty reduction, in a sustainable manner.

A large amount of research, and practice, should be demonstrated for creating the positive effects on pro poor financial sectors development. The permanent deepening of financial markets should be build by the government in a manner that provides the access to the poor and can achieve the following outcomes:

Economic growth and job creation can be stimulated, as small business development and access to housing finance generates new cycles of accumulation and effective demands. Poverty can be reduced, as productive assets in the hands of the poor enable them to build a stream of income. Access to finance, in the form of savings, credit or insurance can play a vital role in “smoothing? the income of the poor, and so reducing their vulnerability to financial shocks. Financial services can also play a key role in building viable communities by contributing to the sustainable livelihood strategies of poor households.

It is often argued that economic integration or globalization has played an important role in reducing poverty in developing countries though its impact on growth. More open economies, and those who have been successful in accelerating their pace of integration, have recorded the best growth performance, whereas developing countries with inward-oriented policies have suffered from poor growth rates. By stimulating higher growth, integration can have a strong positive impact on poverty reduction.

The findings reveal that most of the recipients of credit are not hard-core poor. According to the Pakistan official poverty line, about 51 and 11 percent of rural and urban borrowers respectively are poor. About 69 percent of rural borrowers have ownership of land and a majority of borrowers own their houses in rural areas.

For further research, it is suggested that greater attention should be on the composition and management of household economic portfolios (agriculture, livestock, trading) analysis of differences in impact should be across different socioeconomic or poverty level of borrowers, and more attention should be given to how program design, performance and context influences affect.

RECOMMENDATIONS

Government should focus its activities towards a few critical areas mainly poverty reduction through employment generation.

Government should not only act as a facilitator and but actively engaged in developing economic and social infrastructure, particularly water, roads, schools, hospitals, training and skill development facilities.

Agriculture Sector should be developed through the timely availability of critical inputs. The government should protect poor farmers from volatility in prices of agricultural procedure. Development of farms to market roads should be given the utmost priority.

The government and NGOs involvement should educate the locals how to make best use of micro-credit facilities.

The government should disseminate information about its poverty reduction initiatives and how the poor can benefit from the government’s policies and programs.

School and hospital staff should be recruited from amongst local residents. The communities should be involved in the selection process.

NGOs AND MFBs (Micro finance Bank’s) should achieve substantial outreach while remaining commercially oriented and focused on achieving financial stability.

Government should encourage organization like NRSPs (National rural support program), RSPs (Rural support program) to extend their outreach.

Micro finance organizations should use well organized and systematic criteria in order to identify poor and non poor households. Usually, the borrowers in their programs are mainly the better off among the poor.

PPAF (Pakistan poverty alleviation fund) should be strongly supported by the government so that loans can be given in an organized way to the poor and needy people.

Most of the NGOs providing Micro finance are either receiving funding from the government or donor agencies. Their main source of income are these sources and, not from their own activities. So, they should try best to improve their operational effectiveness and achieve sustainability.