How Microcredit Programs Improve Business Household Well-being in the Local Economy? An Impact Evaluation

: Household welfare can be improved through microfinancial institutions' support by providing microcredit programs. The shock of the COVID-19 pandemic caused the impact on household welfare to decrease by 2.6% in 2020 in Bengkulu. This study aims to evaluate the impact of the People's Business Credit (KUR) program on the welfare of business households in Bengkulu Province through the National Socio-Economic Survey of the Central Bureau of Statistics (SUSENAS) for the 2022 wave using the propensity score matching (PSM) method. The study results show that microcredit influences household welfare in Bengkulu. Households receiving KUR had higher expenditures of 8.89% than groups not receiving the KUR program. In addition, age, number of households, education, savings account, marital status, and agricultural business influence KUR program recipient participation. The KUR program is expected to improve the quality of MSMEs and provide recommendations for enhancing KUR program services to related financial institutions


INTRODUCTION
The COVID-19 phenomenon has attracted great attention which creates global economic shocks so that most economies experience contraction.This resulted in the activities of the entire community stopping due to restrictions on face-to-face activities and interactions between individuals as well as a decrease in income, especially for business actors.Community welfare has decreased drastically due to the impact of the pandemic meanwhile welfare is an important thing 52 in the development of a country.All policies implemented lead to achieving social welfare.Achieving a person's well-being can be realized through a level of happiness, having their needs met, a peaceful soul, feeling that there is justice in life, and being free from the looming poverty (Thu & Goto, 2020).
Microcredit is an instrument that can be used to overcome problems in a country's economic development, one of which is the problem of poverty.Increasing household income and assets is the real impact of microcredit.Microloans or microcredit are also a form of financing service offered by microfinance institutions and are intended for people who meet the requirements to be given microcredit (Tahmasebi & Askaribezayeh, 2021).Microloans can provide opportunities to change household economic conditions and improve the welfare of middle and lower-class households (Nopiah & Islami, 2018;Sarker, 2013).In terms of terms, micro-loans provided by micro-financial institutions will be identical to the amount of small-scale credit loans provided to customers who have low incomes to develop their businesses.Therefore, microcredit plays an important role in community development, especially in achieving the Sustainable Development Goals (Garcia et al., 2020).In Indonesia, Microfinance Institutions are divided into two, namely Formal microfinance institutions (MFIs) (People's Credit Banks and Bank Rakyat Indonesia Units) and Informal MFIs (Cooperatives, Pegadaian, etc.).Micro, Small, and Medium Enterprises (MSMEs) are an important supporting pillar in Indonesia in supporting economic resilience, especially during the recovery period after the COVID-19 pandemic or as an economic buffer in times of crisis.Based on a report from Bank Indonesia, micro-credit distribution in December 2021 grew by 12.3% (year on year), or to 1,147.3 trillion.
One of the provinces that falls into the category of quite high poverty levels is Bengkulu Province.Bengkulu Province is listed as seventh nationally in terms of the percentage of poor people.Since the recovery of economic activity after the impact of COVID-19, it has led to a reduction in poverty levels in Bengkulu Province.In the September 2021 period, the percentage of poor people decreased by 14.4% compared to the previous year in Bengkulu Province.However, the decline in the poor population has not been accompanied by a decline in the poverty line in Bengkulu Province.The published report data from Bank Indonesia (2021), it states that credit distribution has a quite significant portion of the total credit market share to MSMEs in Bengkulu Province.Since the first quarter of 2020, MSMEs credit has experienced an increasing trend.Apart from that, it was recorded that there was a 38.25% increase in credit market share in the fourth quarter of 2021 compared to the previous year of 35.53% of total credit distribution.The increase in MSME credit was due to increased credit distribution to micro-scale MSMEs.Micro-scale MSME credit growth in the fourth quarter of 2021 was 61.59% (yoy) or an increase compared to the previous quarter which contracted by 20.38% (yoy).
The distribution of MSME credit distribution is dominated by the trade business sector and the agricultural sector which reaches 80% of the total MSMEs credit distribution in Bengkulu Province.Furthermore, donations came from the business sectors of the processing industry, services, construction, and others.Providing microcredit positively impacts the development of MSMEs as one of the priorities of sustainable development policies and encourages increased household welfare.However, the magnitude of the impact of microcredit is still not conclusive.This is demonstrated by several empirical study results providing different outputs.Several studies provide positive output that microcredit increases household income and assets (Aktaruzzaman & Farooq, 2017;Hsu, 2014;Ouertani et al., 2018), reduces poverty (Abera, 2019;Hossain, 2012;Nopiah & Islami, 2018;Thu & Goto, 2020;Yergin et al., 2015).However, some studies also show the opposite results that microcredit is not always profitable, does not reduce household poverty levels significantly (van Rooyen et al., 2012), and has no effect on increasing household income and assets (Ahlin & Jiang, 2008;Ali et al., 2017;Montgomery & Weiss, 2011;Thanh et al., 2019).
The influence of financial flows from microcredit was found to have both positive and negative influences (Loubere, 2018;Loubere & Shen, 2018;Weber & Ahmad, 2014).The correlation between microcredit and the income and assets of farming households is positive that access to micro-credit for farming households creates changes in asset values and increased household income (Ouertani et al., 2018).Studies conducted in China, participation in microcredit programs increases income levels when loans are used for activities that generate additional income (income-generating), and microcredit programs become effective when borrowers are fully involved in the program (Hsu, 2014).A study using primary data conducted by Adju et al. (2023) found that providing people's business credit programs significantly affected the income of MSMEs in Gorontalo City for Bank Rakyat Indonesia (BRI) customers.KUR effectively distributes micro-enterprise assistance for developing MSMEs and poverty alleviation (Ulfa & Mulyadi, 2020).In agricultural households, it was found that the microcredit program had a significant positive impact on per capita income (Dao, 2020).The findings from Akotey & Adjasi (2016) show that households that use microcredit accompanied by microinsurance experience a significant increase in welfare.This is because micro insurance can provide benefits to poor people if risks occur in micro credit.Besides, Crépon et al. (2015) found that the microcredit program not only led to increased investment in assets for entrepreneurial activities and increased profits but also reduced the income of freelancers in Morocco.
However, Félix & Belo (2019) also indicated that microcredit reduces poverty as measured by the headcount index, poverty gap, employment, and education.Amanor et al. (2023) found that although the development of microcredit is improving welfare, yet there is a welfare gap in the provision of microcredit based on gender.Men tend to receive larger loan amounts than women, so there is a need to improve portfolio quality and strengthen the benefits of microcredit access.Besides, microcredit programs can alleviate poverty and contribute to the rural economy but also have unintended consequences such as adverse impacts on children's education (Bhuiya et al., 2019).
Poverty alleviation in Bangladesh through microfinance programs is ineffective as a result of high interest rates, insufficient loans, unproductive use of loans, corruption and poor skills of microfinance Institution staff, weekly repayment schedules, and physical and mental abuse of poor women (Ali et al., 2017).In Vietnam, studies at the micro level found that microcredit benefits entrepreneurship more than other household economic activities.Prominent results from macroeconomic analysis reveal that unlike expected, the effect of microcredit on increasing output is not that great (Thanh et al., 2019).
Using the propensity score matching method, in Vietnam it was found that microcredit improved the standard of living of households, especially in rural Vietnam, by increasing household income and consumption.However, for poor rural communities, microcredit only increases consumption without increasing income, so microcredit does not provide benefits for poor households.Other indicators such as age, education level, leadership status of the head of the household, number of household members, dependency ratio, house value, and geographical location influence participation in microcredit programs (Duong & Thanh, 2014;Thanh et al., 2019).Luan et al., (2015) found that subsidized credit was successful in targeting the poor with the number of customers reaching 24.10% and 83% of ethnic minority households in Vietnam.Apart from that, subsidized credit is also influenced by ethnicity, the age of the head of the household, the number of household members, savings ownership, and the magnitude of the impact on economic shocks.Subsidized credit recipients earn 2.61% and 5.93% higher total income in the agricultural sector compared to non-subsidized credit recipient households in Vietnam.
Micro-credit, such as people's business credit, is a potential target for poverty alleviation because it is often seen as a tool to help low-income households improve their economic conditions.However, there is still a gap in the literature regarding the positive and negative impacts of microcredit programs in improving welfare.The study results can help stakeholders and related microfinance institutions in designing more effective and efficient micro-credit programs to improve household welfare.Therefore, this study conducted a study of the impact of people's business credit on the welfare of households in Bengkulu Province.

RESEARCH METHODS
This study uses quantitative descriptive and explanatory study.Therefore, this study will analyze in depth the impact of a program on household-level economic conditions in a particular area.The data source for this study uses secondary data obtained indirectly (third party) published by the Central Statistics Agency (BPS) of Bengkulu Province.The data used is in the form of micro statistical data, namely the national socio-economic survey (SUSENAS) in the form of pooled crosssection data with a survey wave period of 2022.This data includes individual, household and consumption expenditure data at the Bengkulu provincial level.This study aims to analyze the impact of people's business credit on household welfare in Bengkulu Province.This is because people's business credit has an impact on improving household welfare with household expenditure parameters.Based on this, the operational definition of the variables used in the study is included in Table 1.This study uses data analysis tools through the Stata 17.0 program with a quasi-experimental approach.The analytical method used in this study is Propensity Score Matching (PSM).The PSM method is used as an appropriate method for estimating the effect or impact of a program and accommodates the possibility of selection bias (Putra & Pujiyanto, 2020).Propensity Score Matching (PSM) with a cross-section data pattern where PSM tries to form a control group that is as similar as possible to the participant group based on the observed characteristics (Garrido et al., 2014;Jeffrey M. Wooldridge, 2013).In addition, PSM forms a comparison group based on a probability model, namely the probability of an individual participating in the program based on observed characteristics with a large number of observations so that the number of similar observations (match) meets the requirements for estimation.PSM is a semiparametric method, which means there are few limitations in determining the specifications of the program participation model, including the assumption of normality and error term distribution (Christopher F. Baum, 2006;Jeffrey M. Wooldridge, 2013).
Propensity score matching has two steps, namely selecting a model and selecting variables that must be in the model.In selecting the PSM model, it can be binary logit, probit, multinomial logit, and probit.Several steps fulfilled in the PSM method include (Duong & Thanh, 2014;Thanh et al., 2019).The first step is analysis of the determinants of accessibility to the people's business credit program, and then participation is estimated using the probit model regression method.The equation is written as follows: where,   is an indicator of participation in the people's Business credit program; and  represents the determinants of program participation.The estimated probability of participation or matching score for each household can be calculated from equation (1).
In the second step, each household will be paired with one or more non-users of the program.Then, differences in results such as per capita expenditure for each program recipient and nonrecipient are compared.This difference will reflect the impact of the people's business credit program on each household.The average results of all individual differences will be calculated to obtain an average value as a reflection of the impact of the KUR program on the respondents.The average effect of treatment for the treated (ATT) can be written as follows: where,  1 shows the potential unit of the outcome of treatment and  0 shows the potential unit of the outcome of controls.
Apart from that, PSM is the best choice in the analysis technique for evaluating the impact of a program.The variable of interest in this study is access to financial services through the use of people's business credit services and the outcome assessed is household welfare with the parameter of household expenditure per capita.The groups of KUR and non-KUR recipients are carried out by looking at the distribution between groups to find out how much data overlaps.This method carries out matching by weighting groups that receive people's business credit compared to groups that do not receive people's business credit (Garrido et al., 2014;Jeffrey M. Wooldridge, 2013;Thanh et al., 2019).After the probit estimation process, then each observation in the treatment and control groups is matched (matching) which has the same propensity (tendency) score value.(3) where,   ε {0,1} denote a dummy symbol for group treatment (treatment).  denote an outcome indicator, namely household expenditure per capita as a parameter measuring household welfare. 1 is the outcome or expected result when the household (i) is a recipient of people's business credit with a value of 1 (prosperous) and  0 is the expected result as a result of the household (i) not being a recipient of people's business credit, namely the result of control or when Di is equal to zero (0).

RESULTS AND DISCUSSION
People's Business Credit is credit or financing for working capital and/or investment to individual debtors, business entities, or business groups that are productive and viable but do not have additional collateral or the additional collateral is not sufficient.In general, the KUR programs in Bengkulu Province tend to experience a significant increase.Based on the report from the Directorate General of Regional Treasury of Bengkulu Province, it is stated that the value or progress of KUR distribution in the April 2024 period was IDR 1.11 trillion, experiencing growth of 80.93% compared to the previous year in the same period, as well as the number of debtors growing by 81.20%.
This study emphasizes impact evaluation analysis which is analyzed using a propensity score mathematics approach at the household (micro) level.Using national socio-economic survey data (SUSENAS) for Bengkulu province in 2022, a description of the study data is outlined in Table 2 around 42 years old.This study focuses on the KUR program where study data shows that an average of 15.56% of respondents received the KUR program.Apart from that, 2.8% of respondents received micro-business assistance, 48.1% had a bank account, 98.6% had working status, 2.5% had civil servant status, and 29.3% lived in urban areas.The average number of household members a respondent has is 4 people, with a minimum number of household members being 1 person and the highest number of household members being 10 people.The variable length of education that respondents have taken is an average of junior high school or 9 years.Respondents who had the highest education were at the doctoral level (S3) and the respondents with the lowest education were no school.Additionally, male respondents tend to receive more People's Business Credit programs compared to women.Figure 2 shows that there are 62.89 % or 978 male respondents receiving KUR and 37.11% or 577 female respondents receiving KUR out of a total of 1555 respondents.Furthermore, respondents in the study were also divided based on their business field ownership, namely agricultural and non-agricultural business fields.In business fields in the agricultural sector, there were 48.42% or 753 respondents who received the KUR program and 51.58% or 802 respondents received the KUR program in business fields in the non-agricultural sector.This study uses impact evaluation analysis, namely propensity score matching to eliminate endogeneity problems and appropriate analysis to evaluate the impact of a program or policy.Table 3 reports the results of the total sample treated and the results of the significance of the propensitymatching treatment.The results showed that 1555 respondents were treated in the program (receiving KUR) and 8416 respondents who did not receive the KUR program.The results of the propensity matching treatment also show that this data can be carried out in the next stage with a significance value (Prob > X 2 ) of 0.000.Table 4 reports the second approach, the same results as the first approach were obtained.Based on the results of the Average Treatment Effect on the Treated (ATET), it is 0.0889 with a significance level of 0.000 < 0.05 and a positive coefficient relationship.So, from these results, it can be said that households that receive the KUR program will increase their household welfare by 8.89%.From these two results, it can be concluded that the KUR program will have an impact on household welfare in Bengkulu Province in 2022.
Apart from that, the influence of KUR credit also contributes to increasing household welfare in the short term as shown in Table 5.The results of multiple linear regression as an interpretation of short-term analysis show that KUR credit has a positive and significant influence on increasing household welfare in Bengkulu Province.Individuals or households who receive KUR credit have an opportunity to increase their welfare by 8.5% compared to individuals or households who do not receive KUR credit in Bengkulu Province.Apart from that, other control variables such as demographic and other factors also contribute to welfare, including domicile, marital status, age, bank account ownership, micro business assistance, number of household members, years of education, and type of business field being run.However, it is necessary to know the determinants of participation in the KUR program.This is necessary to find out which households participate in the KUR program due to any factors to make it easier for policymakers and financial institutions to make decisions on regulations, market targets, administration, and others.These results are shown in Table 6 estimates show the same relationship and influence results.The results show that the factors of age, number of household members, education level, savings account ownership, marital status, and employment sector (agricultural and non-agricultural) influence households to participate in the People's Business Credit program.The higher the level of education, the lower a person's participation in the KUR program will be.As the number of household members increases, participation in the program also increases.Married status and having a savings account increase the probability that someone will receive the KUR program.Individuals who work in the non-agricultural sector have a higher probability of receiving or participating in the KUR Microcredit, in this case, the people's business credit program, is a capital assistance program for micro business actors who need additional capital to increase the quantity and quality of their business.People's business credit is given to micro, small, and medium enterprises (MSMEs) or business cooperatives with adequate criteria but insufficient collateral to carry out non-KUR credit (Adju et al., 2023).Testing through impact evaluation analysis found that microcredit has an impact on the welfare of business actors' households.A p-value of 0.000 and a coefficient of 0.088 in Table 5 means that every household that receives the People's Business Credit program will increase welfare by 8.8% in households receiving the KUR program compared to non-KUR program recipient households.
This identifies that the KUR provision encourages an increase in household welfare.Providing KUR encourages business actors to increase the quantity and quality of their production and business competency (Adju et al., 2023).Besides that, Studies conducted in China, participation in microcredit programs increases income levels when loans are used for activities that generate additional income (income-generating), and microcredit programs become effective when borrowers are fully involved in the program (Hsu, 2014).KUR is an effective form of distributing Apart from that, empowering household business actors through providing people's business credit programs can also reduce poverty.This is because the KUR program stimulates an increase in sales turnover and business income.Therefore, one way to achieve sustainable economic development is through policies from policymakers that focus on improving the real sector of the economy such as Micro, Small, and Medium Enterprises.The results of this study are in line with studies from Crépon et al.  (2014).However, several studies also show the opposite results, namely that microcredit is not always profitable, does not reduce household poverty levels significantly (van Rooyen et al., 2012;Ali et al., 2017), and does not affect increasing household income and assets (Ali et al., 2017;Thanh et al., 2019).In addition, microcredit programs can alleviate poverty and contribute to the rural economy but also have unintended consequences such as negative impacts on children's education (Bhuiya et al., 2019).

CONCLUSIONS
This study found that the People's Business Credit program has an impact on welfare through increasing per capita household expenditure as a proxy for the welfare of households that receive the program even though the KUR program is not said to have a large impact.Apart from that, the impact of people's business credit on household expenditure in rural areas is not significant.Therefore, rural households need to receive support in the form of training in entrepreneurship, business, how to run production optimally with minimal risk, and promotion/marketing training so that households who receive the KUR program can more effectively improve their welfare.The KUR program can improve household living standards by increasing household expenditure, where the higher the household consumption, the more prosperous it can be.This study also found that age, number of household members, education level, savings account ownership, marital status, and employment status in the agricultural sector influence households to participate in receiving the People's Business Credit program.The People's Business Credit program helps increase household business actors.To maximize the effectiveness and efficiency of the program, pro-poor policies are needed between financial institutions and households, especially poor rural households, in the form of easy loan granting procedures and other related institutions for providing training and business assistance.

Table 1 .
Operational Definition of Variables Sources: data processed by author, 2024 . Based on the data description, this study had a total of 9971 individual respondents with the respondent analysis unit having an age range of 17 -93 years.The average age of respondents is Available at: https://jep.ejournal.unsri.ac.id/index.php/jep/indexDOI: 10.29259/jep.v22i1.2307456

Table 2 .
Data DescriptionFigure1shows the percentage of respondents who received the KUR program in 2022.Based on processed SUSENAS data, it shows that as many as 15.60% or 1555 respondents received the People's Business Credit Program and 84.40% or 8416 respondents did not receive the People's Business Credit Program.Meanwhile, Figure2shows the percentage of respondents who received the People's Business Credit program based on respondent demographics, namely domicile, gender, and business field (agricultural and non-agricultural).The results of the data description illustrate that as many as 29.65% or 461 respondents live in urban areas and 70.35% or 1094 respondents live in rural areas.Percentage of People's Business Credit recipients in 2022 Available at: https://jep.ejournal.unsri.ac.id/index.php/jep/indexDOI: 10.29259/jep.v22i1.2307457

Table 3 .
Propensity matching treatment assignment (Common support)

Ps-match: Treatment assignment Ps-match: Common Support on Support
Sources: Data SUSENAS is processed by author, 2023

Table 4 .
Impact Evaluation of KUR Program toward Welfare by Propensity Score Matching

Table 5 .
Short-term Regression -Effect of KUR Program toward Welfare in 2022

Table 6 .
Determinants that determine whether someone will receive the KUR program in 2022