# Introduction a) Poverty overty is a multi-dimensional phenomenon related to the inadequacy or lack of social, economic, cultural, and political entitlements (Momoh 2005). Poverty is a multidimensional phenomenon that has different meaning for different people. Poverty can be viewed as absolute or relative, as a lack of income or failure to attain capabilities. It can be chronic or temporary, is sometimes closely associated with inequality and is often correlated with vulnerabilities, underdevelopment and economic exclusion Poverty is as an inability to afford the minimum standard of living. According to UNDP (2006), a person living under one dollar per day is considered to be living under the poverty line. In economic terms a country, region or household are poor when the per capita income of a country or the income of a household is very low. In political terms a country a region or a group of people are poor which are dependent on more powerful groups or individuals in order to express their own rights or choices. Poverty is hunger. Poverty is lack of shelter. Poverty is being sick and not being able to see a doctor. Poverty is not having access to school and not knowing how to read. Poverty is not having a job, is fear for the future, living one day at a time. Poverty is losing a child to illness brought about by unclean water. Poverty is powerlessness, lack of representation and freedom (World Bank -2000). # b) Microcredit Microcredit programs extend small loans to the very poor people for self employment projects that generate income, allowing them to care for themselves and their families. Microcredit also called "microfinance" and "micro lending" means providing small working capital loans to the self-employed people. Even small amounts of capital can make the difference between absolute poverty and a thriving little business generating enough income to feed the family, send kids to school, and build decent housing. Micro-credit refers to programs that are poverty focused and that provide financial and business services to the very poor people for generation of self-employment and income. Credit is a powerful instrument to fight against poverty. The role of micro-credit in reducing poverty is now well recognized all over the world. Governments, donors, development agencies, banks, universities, consultants, philanthropists and others have increasing interest in it. The universal objective of microfinance is to make it possible for large numbers of low-income people to access institutional financial services, hence the potential benefits of microfinance has accounted for its widespread adoption as an economic development, job creation and poverty reduction strategy. There is an ongoing debate whether credit alone or credit plus is needed for poverty reduction. There are views that credit alone on its own is inadequate to fight against poverty. The need for other services is also important in this respect. Such views, although, do not negate the role of credit; fail to appreciate the role of credit on its own merit. # II. # Objectives of the Study The basic objective of this study is to analyze the impact of microcredit on household savings. For that the specific objectives are: ? To assess the impact of microcredit programs on poverty alleviation. ? To identify the socio-economic and demographic factors that affect household poverty status. ? To evaluate whether the microcredit programs are effective in accumulating savings of the participating households. III. # Research Methodology a) Data Collection and Sampling Techniques The present study is based on primary data that have been collected by the researcher from Jhenaidah district of Bangladesh through questionnaire during January 2019 to June 2019 for the purpose of our analysis. A well-organized questionnaire is prepared for data collection. Our study draws the sample data and information from BRAC. The survey has been conducted with great care which covers different socio-economic information of 400 microcredit borrower. The selection of the respondents has been made using the multistage simple random sampling procedure. At the first stage, two out of six upazilas under Jhenaidah district are selected using simple random sampling method. The upazilas are Sailokupa and Kaligonj. There are 6 and 11unions under Sailokupa and Kaligonj upazilas, i The sample size of the respondents was determined by using the formula (Guilford and Fruchter, 1978): respectively. At the second stage, using random sampling technique, from each upazila two unions are chosen which are Nittanondopur and Abaipur of Sailokupa upazila and Triechandpur and Rakhalgachi of Kaligonj upazila. At the third stage, two villages under each union are selected using random sampling technique. Finally, lists of respondents of the selected villages are collected from the upazila BRAC office. When adjusted for a non-responders rate of 10%, N is 418. Hence, a sample of 418 respondents separately from the above mentioned financial institution was selected. Therefore 418 questionnaires were prepared and distributed randomly to the respondents, of which 400 filled-in questionnaires were returned. # b) Techniques of Data Processing and Analysis The basic objective of this study is to analyze the impact of microcredit on savings of respondents after taking loan from BRAC that I have mentioned in the above points. To analyze this, I have adapted the multiple linear regression models for regression analysis and I have analyzed independent samples test to compare respondent's savings level before and after taking loan. On the other hand, I have also analyzed frequency distribution of the respondents according to age, education, gender, number and earners in the household, occupation, size and residential status was presented in Tables and discussed in the paper. Computer software mainly SPSS version 20 are applied to analyze the data. Corrected standard errors are used to allow for heteroscedasticity. # Model specification: Thus the multiple linear regression models were used and written as follows: ?????????????? (??) = ?? + ?? 1 (????) + ?? 2 (??????) + ?? 3 (??????) + ?? 4 (??????) + ?? 5 (????) + ?? 6 (??????????) + ?? 7 (????) + ?? 8 (????) + ?? 9 (??????) + ?????????. i Where the independent variables are: ? AR = # c) Reliability and Validity Test The reliability value of our surveyed data was 0.835 for variables. If we compare our reliability value with the standard value of 0.6 as recommended by Bagozzi and Yi's (1988), we find that the scale used by us are sufficient reliable for data analysis. IV. # Analysis of Findings a) Sample Characteristics Table-1,2,3,4,5,6,7 summarizes the respondent's socio-economic and demographic characteristics according to their age, gender, and educational background, number of earners and dependents of households, occupation, residential status and family size. A number of researches in the region have found that those factors had significant impact on the respondents borrowing and standard living levels. The respondents' profile is discussed in the following sub sections. Table 2 shows the gender distribution of the respondents. Field survey indicates that most of the microcredit borrowers are female (75.8%) and male borrower is 24.3%. Overwhelming majority of the respondents is married. Table 3 shows that the married respondents are 83.5%. It is assumed the marital status of microcredit borrower is the quite a reflection of our societal and cultural ideology and values. Table 5 shows that most of the respondents are educated and among them 33.0 % are completed secondary school certificate (SSC) where 5.5 % are graduate and 13.8% are capable to sign only. Table 7 shows that most of the households' earners are single which 78.8% are and rests of them are dependents. In indicates a large number of people are not self employed or employed. V. Impact of Conventional Microcredit on Respondent's Savings (After Loan) In this study we have estimated simultaneous equations model to determine the impact of microcredit on respondent's savings level. Total savings of the respondent are estimated as the dependent variables. Age of the respondent (AR), Education of respondent (ER), Gender of the respondent (GR), Number of earners in the household (EAR), Number of dependents in the household (DHR), the amount of loan (AL), expenditure for food and non-food items (per month) after loan, Earners in the Household, Occupation, Gender of Respondent, Size of the household (SH), Interest rate (IR) are estimated as independent variables. The value of the coefficient AR (Age of the Respondent) is negative sign, it implies that savings decreases due to youth unemployment and inexperience. This implies that, with an increase in the age of the respondent the probability being poor will fall as a result the savings of the respondent increases. In the context of our country, there is a joint family system in rural areas, the older of the respondent, the higher of the respondent's earnings and accumulation of resources. Field survey data shows that the incidence of poverty increases with youth unemployment and inexperience and incidence of poverty decreases with age of the respondent. # a) Regression results of savings (s) and independent variables Model The value of the coefficient SH (Size of the Household) is negative sign. This implies that, the household size has a negative impact on the household income. The higher the household size the lower the household income. With a decrease in the household size the probability being poor will fall, as a result the income of the family increases. This conclusion is consistent with the earlier observation that the incidence of poverty increases with the household size. The coefficient of household size is -.004, it means that if other things are remaining the same, the size of household increases by one unit which will reduce the household income by 0.4. Field survey data shows that the incidence of poverty increases with the increases of household size. The coefficient of ER (Education of the Respondent) has a negative effect on poverty and income. This implies that the more educated an individual, the greater the potential to exploit resources and technology and avoid poverty, higher the education higher the savings of the family. The coefficient of household education is 0.026; it means that if other things are remaining the same, one per cent increases in education of household will increase the household savings by 2.6. Field survey data shows that the incidence of savings decreases with the increases in education of household. The coefficient of EAR (Earners in the household) has negative effects on poverty. This implies that the more earners of the household lower the poverty and increase the household welfare. The coefficient of earner of household is .009; it means that if other things are remaining the same, one unit increases in earners of household will increase the household savings by 0.9. Field survey data shows that the incidence of poverty decreases with the increases in earners of household. The coefficient of DHR (Number of dependents in the household) has positive effects on poverty, higher the dependency ratio lowers the income of the family. The coefficient of dependency ratio is -0.010, it means that if other things are remaining the same, one unit increases in dependency ratio of household will decrease the household savings by 1.0. Field survey data shows that the incidence of poverty increases with the increases of dependency ratio. Total income of the respondent (TYR) plays a vital role to accumulate savings that can tend to raise investment for the development of rural Bangladesh. From the field survey, it is evident that the coefficient of TYR (Total Income of the Respondent) has negative impact on poverty, increases of TYR, and increases of savings of the respondent. The coefficient of respondent's savings is .117; it means that if other things are remaining the same, one unit increases in savings of respondent will increase the respondent's asset by 1.7. Field survey data shows that the incidence of poverty decreases with the increases of savings of respondent. There are more occupations create in rural Bangladesh. From the field survey, it is evident that the coefficient of occupation of the respondent (OR) has positive impact on poverty alleviation. The coefficient of respondent's occupation is 0.059; it means that if other things are remaining the same, occupational status does ensure the variation on savings of the respondent. The coefficient of interest rate (IR) has negative effects on income and savings, higher the interest rate lowers the income of the family. The of interest rate is -0.20, it means that if other things are remaining the same, one unit increases in interest rate on the amount of loan will decrease the respondent's income by 2.0. Field survey data shows that the incidence of poverty increases with the increases of interest rate. Total expenditures for food and non-food items of the respondent (TExpR) play a vital role to measure living levels of households. From the field survey, it is evident that the coefficients of expenditure for food and non-food items are -0.963 and -0.807. It means that if other things are remaining the same, one unit decrease in expenditure of respondent will increase the respondent's savings by 6.3 and 0.7. Field survey data shows that the incidence of poverty decreases with the increases of savings of respondent. Table 8 shows comparative savings statistics of respondent (before and after loan). After loan around 271 numbers of respondents say that microcredit can accumulate savings and it is an instrument that can help us to alleviate poverty and self-reliability. # VI. # Major Findings From the estimation it may be concluded that the microcredit programs are effective in generating higher income and savings for borrowers. This is a very important finding as it confirms the claims made by the microcredit providers. We may conclude from this finding that microcredit is providing better quality of life for its borrowers. We know from experience that people's income increases as they grow older. Our estimation results suggest that age of the respondent has a significant and positive impact on income and assets. As someone grows older them income also grows. Our results also suggest that educations of the respondents are an important factor in affecting income and assets positively. Education helps people to be more enlightened. According to this finding, education enhances borrowers' income and assets. We have also found from this analysis that infrastructural facilities in the village facilitates borrowers' income and assets. This study also suggests that as the number of earners increases in a household, amount of borrowing also increases. This could be due to the fact that having more earning members increases the ability to repay loans quickly as well as obtain more loans. Infrastructural facilities facilitate the household outcomes. It is also found that families having more earning members enjoy better household outcomes. # VII. Challenges in Microcredit Programs a) Cycle of loans and liability Microcredit has changed life style of the poor people but they could not come out from the causes of poverty. Sometimes they use microcredit loan from one organization to meet interest obligations from another. It chained the poor people, so they are rolling in the cycle of loans and liability. # b) Highly expensive Microcredit imposes high interest on the borrowers. So, many borrowers fail to repay the loans. As a result they are carrying the burden of high interest which is not at all in favor of eradicating poverty. # c) The human system for collecting installment The way micro credit lenders collect the installment of the loans is really pitiable. Most of the field officers are in a position of power locally and are judged on repayment rates as the primary metric of their success. They sometimes use force and even violent tactics to collect installments on the microcredit loans. Many borrowers bound to sale there their last belongings to pay the installment. Many committed suicide under frustration. # d) Increases dowries A large number of people believe that, microcredit increase the dowries. Poor parents take loan for their daughter to meet the demand of the grooms. Many people put pressure on women to borrow from the micro financer. Micro credit is indirectly responsible for increasing dowries. Ignorance to agriculture sector: Micro credit could not play any significant role in the agriculture sector. But it is simply impossible eradicate poverty from our country without developing this sector. # VIII. Recommendations and Conclusion Microcredit, originated in Bangladesh has blown out all over the globe. Today within the international coverage of microcredit Bangladesh's achievement stands out prominently. The world community has appreciated the contributions of Bangladesh in the field of microcredit, which was evident in the Asia Pacific Region Microcredit Summit (APRMS) Meeting of Councils in Dhaka, Bangladesh from 16-19 th February, 2004 arranged by Palli Karma -Sahayak Foundation (PKSF), in association with the Microcredit Summit Campaign based in Washington D.C. More than 1200 participants from 47 countries from different parts of the globe pledged their firm commitment to take forward the microcredit movement. Bangladesh government has also placed adequate emphasis on microcredit programs. The Interim Poverty Reduction Strategy Paper (IPRSP) of the government of Bangladesh has outlined some important roles for microcredit. The policy makers have recognized the importance of microcredit in Bangladesh and the present government has pledged its support to this program. To become micro credit programs more fruitful we should give emphasis on the followings -? Ensuring close monitoring. ? Using micro credit in high profitable business. ? Fixing reasonable rate of interest. ? Making sufficient laws for the operation of micro credit. ? Ensure suitable behavior of by the officers. ? Give more emphasis on rural economic productive sector, especially in agriculture. ? Ensure more research in micro credit and its effectiveness. If we fulfill these requirements, we could hope that micro credit becomes a tool of eradicating poverty. Only then we can get poverty and hunger free Bangladesh. 1Age in YearsFrequency Percent Valid Percent Cumulative Percent20 thru 3026466.066.066.031 thru 406917.317.383.3Valid41 thru 504411.011.094.351 thru highest235.85.8100.0Total400100.0100.0Source: Author's Field-work (2018) 2GenderFrequency Percent Valid PercentCumulative PercentMale9724.324.324.3ValidFemale30375.875.8100.0Total400100.0100.0Source: Author'sField-work (2018) 3Marital StatusFrequency Percent Valid Percent Cumulative PercentSingle348.58.58.5ValidMarried Divorced334 3283.5 8.083.5 8.092.0 100.0Total400100.0100.0Source: Author's Field-work (2018) 4Residential StatusFrequency Percent Valid Percent Cumulative PercentUrban287.07.07.0ValidSemi Urban Rural200 17250.0 43.050.0 43.057.0 100.0Total400100.0100.0Source: Author's Field-work (2018) 4 5Educational StatusFrequency Percent Valid Percent Cumulative PercentSign Only5513.813.813.8Primary12431.031.044.8ValidSecondary Higher Secondary132 6733.0 16.833.0 16.877.8 94.5Graduate225.55.5100.0Total400100.0100.0Source: Author's Field-work (2018) 6OccupationFrequency PercentValid Percent Cumulative PercentDay Labor6315.815.815.8Farmer7719.319.335.0Small Business9724.324.359.3ValidShopkeeper10125.325.384.5Housewife4812.012.096.5Others143.53.5100.0Total400100.0100.0Source: Author's Field-work (2018) 7Earners in the HouseholdFrequency Percent Valid Percent Cumulative Percent1.0031578.878.878.8Valid2.00 3.0074 1118.5 2.818.5 2.897.3 100.0Total400100.0100.0Source: Author's Field-work (2018) 8Independent Samples TestLevene's Testfor Equality oft-test for Equality of MeansVariancesFSig.tdfSig. 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