Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 4, 146-156 2025 Publisher: Learning Gate DOI: 10.55214/25768484.v9i4.5950 © 2025 by the authors; licensee Learning Gate © 2025 by the authors; licensee Learning Gate History: Received: 27 January 2025; Revised: 6 March 2025; Accepted: 10 March 2025; Published: 3 April 2025 * Correspondence: bashkim.bellaqa@umib.net The role of microfinance institutions in job creation Qazim Tmava1, Bashkim Bellaqa2* 1,2Faculty of Economics, University of Mitrovica “Isa Boletini”, Mitrovica, Republic of Kosovo; qazim.tmava@umib.net (Q.T.) bashkim.bellaqa@umib.net (B.B.) Abstract: The primary objective of this research is to assess the influence of Micro Financial Institutions (MFIs) on job creation in Kosovo by examining the relationships between MFI microcredits, consulting services, government coordination, interest rates, and so on. According to the September 2024 status, Kosovo's microfinance sector consists of 9 MFIs and 23 Non-Banking Financial Institutions (NBFIs). The findings of the linear regression analysis suggest that there is a weak relationship between the volume of microcredits granted by MFIs and the creation of new jobs, with p = 0.042, which is slightly lower than the significance value of 0.05. The MFI consultancies, MFI programs, and high interest rates of MFI microcredits show a substantial negative link with employment creation. The parameter β values are smaller than the values of p. Methodologically speaking, apart from secondary data, a survey connected to the purpose of the research was also conducted. MFIs have a number of challenges in creating jobs, including a lack of entrepreneurial training and financial skills, low institutional capacity, high interest rates, and so on. The study recommends that policy and strategy makers in Kosovo maximize job creation through MFIs by implementing an integrated approach. Keywords: Development finance, Microfinance, Job creation, Public economics and Correlation, Small firms. 1. Introduction Microfinance Institutions (MFIs) in Kosovo began operations following the conclusion of the war to provide financial aid and support for small business ventures. Job creation is still a primary objective in developing countries such as Kosovo. Much research on economic growth and development concentrates on the labor market, as individual incomes are heavily influenced by job prospects [1]. Their assistance was critical in launching the postwar economic resurgence at a time when the banking sector was almost non-existent. MFIs provide loans to low-income clientele, such as micro companies and the self-employed, who have traditionally been denied funding from banks [2]. MFIs and Non- Bank Financial Institutions (NBFIs) have grown rapidly in recent years, but they account for barely 4% of the financial system. As a result, MFIs have helped microcredit borrowers gain confidence in their entrepreneurial talents [3]. This sector of finance specializes in low-cost financial products and services with quick access, short application processes, and straightforward payment mechanisms. Low-income clients want microfinance to cover basic needs, personal emergencies, or to grow a small business [4]. The MFI study has significant implications for policymakers, development practitioners, and academics interested in fostering economic growth through microfinance in low-income countries [5]. The microfinance market in Kosovo has changed dramatically since 1990. Initially, most MFIs were non-governmental and non-profit organizations that provided low-interest loans to individuals and businesses in need. Over time, several of them have evolved into solid, regulated financial institutions. Kosovo's weak investment and financial system performance is attributed to problems with reforms to institutions, corruption, informality, and inadequate macroeconomic management [6]. Today, this https://orcid.org/0000-0002-3738-8649 https://orcid.org/0000-0003-2565-5954 147 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 4: 146-156, 2025 DOI: 10.55214/25768484.v9i4.5950 © 2025 by the authors; licensee Learning Gate sector is a major aspect of the Republic of Kosovo's financial system, contributing to economic growth by helping small and medium-sized businesses, creating jobs, and reducing poverty. However, this sector continues to encounter obstacles, such as strict regulation and limited access to capital among some groups. The Regulation on Credit Risk Management requires MFIs to have a credit risk management system that is appropriate for the size and complexity of their operations. This system should comprise the risk management strategy, rules, processes, and structure, as well as a plan for increasing profits while keeping risk below acceptable bounds [7]. The Kosovo microfinance sector maintained its upward trend throughout October 2023. Active loans totaled 304 million euros, allocated to 108,680 borrowers [8]. According to the Microfinance Association of Kosovo's (MIK) monthly report, these figures reflect the sector's performance through October 31, 2023. The growth of the MFI sector in an economy might result in a large increase in employment. MFIs offer financial services to low-income and underprivileged people, allowing them to get small loans for productive purposes or to build their small businesses [9]. Deposits in the Central Bank of Kosovo (CBK) by sector: Commercial banks are the other depository corporations in Kosovo, while other financial corporations include insurance firms, pension funds, microfinance institutions, money transfer agencies, and exchange offices. The Privatization Agency of Kosovo's deposits are presented within central government deposits by maturities [10]. The International Labour Organization (ILO) considers microfinance to be an important tool for labor market reforms. Access to credit from MFIs improves employment and income, particularly for unemployed or unbanked individuals. MFIs encourage the formation of new firms, promote self-employment, and create jobs at a lesser cost than typical labor market strategies. These occupations boost entrepreneurs' self-esteem as well as their revenue. As a result, microfinance has become an increasingly essential tactic in employment policy [11]. Staff training, professional growth, and the use of current management practices improve the flexibility and adaptability of Kosovar MFIs to environmental changes, resulting in greater success and better financial services for clients. Access to financial services is critical for those in poverty, allowing them to better control their spending, develop business opportunities, and increase their participation in the formal economy [12]. During our research, we attempted to address the following research question: How does MFI activity influence the creation of new jobs? This study question's framework comprised four sub-questions, which are as follows: 1. Is there a link between microloans offered by MFIs and job creation? 2. Is there a relationship between MFIs providing advisory services and increased employment? 3. Does a lack of coordination among government agencies affect the success of MFI programs in job creation? 4. How do high interest rates on microloans supplied by MFIs impact job creation? The paper's structure is as follows: Section 1: Introduction. Section 2: Literature review. Section 3: Research Methodology. Section 4: Data Analysis and Results. Section 5: Discussions and Section 6: Conclusions and Recommendations based on this study. 2. Literature Review Various researchers have used research to determine the existence of links between microloans provided by IMFs and job creation, the provision of consultancy services by IMFs and employment growth, the impact of coordination between government agencies on the success of IMF programs in job creation, and the impact of high interest rates on microloans provided by IMFs on job creation [13- 16]. Similarly, data from many reputable entities were used (Central Bank of Kosovo, World Bank, Association of Microfinance Entities of Kosovo, American Chamber of Commerce of Kosovo, International Monetary Fund, Ministry of Finance, Kosovo Agency of Statistics, and so on). Microfinancing has been targeted as a tool to address poverty through the provision of credit to the poor and marginalized economic functions [17]. Microfinance strives to increase access to deposits and small loans for low-income persons who are excluded from regular banking. Microsavings is a subcategory of microfinance that offers small deposit accounts to low-income families or individuals. 148 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 4: 146-156, 2025 DOI: 10.55214/25768484.v9i4.5950 © 2025 by the authors; licensee Learning Gate These accounts encourage long-term savings and operate similarly to standard savings accounts, but with lower minimum balances. As a result, the typical balance criteria for opening an account are either ignored or extremely low, allowing for small-scale savings without incurring large service fees. This includes offering financial services to low-income people in both urban and rural locations [18]. Microcredit can also be referred to as "microlending" or "microloans." Microcredit is a method of giving individuals small sums of money to establish or expand a small business. Microfinance borrowers are typically low-income individuals, and the concept began in Bangladesh. MFIs play an important role in increasing financial inclusion, particularly in rural areas with limited conventional banking facilities [19]. Most microfinance initiatives are based on the group lending model pioneered by Nobel laureate Muhammad Yunus and his Grameen Bank [20]. Although there is an abundance of research on microfinance in job creation, there is a lack of research on the links between MFI microloans and job creation, MFI advisory services and employment growth, the impact of government agency coordination on the success of MFI programs in job creation, and the impact of high interest rates on MFI microloans on job creation. The literature review was conducted in both theoretical and empirical terms on the relationship between microcredit and job creation, the role of MFI advisory services to clients in terms of job creation, the coordination of MFI programs with agencies, and MFIs' contributions to job creation, which are presented below. Governments, banks, and non-governmental organizations (NGOs) employ microfinance to address poverty, which affects nearly two billion people living on less than US$2 per day [21]. According to Fidler and Robinson [22] microfinance refers to fundamental financial services such as lending and savings provided to persons engaged in agriculture, small companies, and microenterprises, mostly in developing countries' rural and urban areas. According to Mersland and Strøm [23] many of these individuals lack access to conventional financial institutions. Microfinance Institutions (MFIs) expanded significantly during the 1990s, with a large increase in their financial capacity to provide modest loans Fidler and Robinson [22]. Dichter [24] refers to this decade as the "decade of microfinance," citing its evolution from a small project to assist the poor to a full-fledged industry [25]. Traditional banks frequently refuse credit requests from the informal sector, which is prevalent in developing nations and employs the vast majority of the poor. Microfinance institutions, on the other hand, lend to a far broader spectrum of people, regardless of their industry, as long as they can demonstrate their commitment [26]. MFIs are increasingly important in many countries' post-conflict strategies, with the intention being the providing of the necessary financial assistance to help rebuild the economy and recover in conflict-affected areas [27]. Microfinance Institutions (MFIs) began operating in Kosovo immediately after the 1999 war, mostly with the support of international groups seeking to assist local residents in gaining access to financial resources. In November 2021, the average interest rate on new loans given by microfinance organizations was 18.8 percent, compared to 19.7 percent the previous year. This sector's credit portfolio is likewise considered to be of high quality, with a non-performing loan rate of 2.9% [28]. Based on the research topic, "How does the MFI's activity affect job creation?" In addition to four sub-questions within the framework of this research issue, four hypotheses have been developed on which this study is based: H1: There is a link between the number of microloans given by the MFI and employment creation. H2: The counseling offered to the customer by the MFI has no effect on employment creation. H3: The MFI programs have no effect on employment creation since they are not adequately coordinated with government institutions. H4: The high interest rates on MFI microloans have a negative effect on job creation. 3. Research Methodology The creation of jobs by MFIs is at the core of this study, as are the following components: the existence of a link between microcredits provided by MFIs, the link between MFIs' provision of consulting services, the impact of coordination between government agencies with MFI programs, and the effects of MFIs' high interest rates on microcredits provided. The aforementioned components were 149 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 4: 146-156, 2025 DOI: 10.55214/25768484.v9i4.5950 © 2025 by the authors; licensee Learning Gate examined in terms of job creation in Kosovo. Data for this study were collected from both primary and secondary sources. Secondary sources included data from reliable local and international agencies, while primary data was gathered through a survey. In December 2024, 150 microcredit users were questioned using a questionnaire designed for primary data gathering. The sample, which was dispersed among 15 localities in Kosovo, was chosen using the random method. The questionnaire is divided into four sections: introduction, demographics, MFIs' role in job development, and conclusion. The third section is the key element of the study and consists of four questions: Is there a link between microloans supplied by MFIs and employment creation? Is there a relationship between the offering of advisory services by MFIs and employment growth? Does a lack of coordination among government agencies hinder the performance of MFI programs in job development, and the fourth question, how do the high interest rates on microloans given by MFIs impact employment creation? The answers to the questions are presented as (Yes/No). The completed questionnaires were professionally reviewed, and the data was processed and analyzed using the Statistical Package for the Social Sciences (SPSS) application. The study begins by establishing the hypothesis that job creation is dependent on the presence of a significant link between microloans provided by MFIs and job creation, the provision of consulting services by MFIs, the lack of coordination between government agencies and MFI programs, the impact of high interest rates on microloans, and so on. The dependent variable, Job Creation through Micro Finance Institutions Activities (abbreviated JCAMFI), was compared to the independent variables: whether there was a relationship between microloans supplied by microfinance institutions and the creation of jobs (abbreviated EMLMFIJC); whether there was a relationship between employment growth and the consulting services provided by microfinance institutions (abbreviated LCSMFIE); the effect of a lack of coordination among government agencies on the success of microfinance institutions' job creation programs (ICGAMFIPJC); and the effect of high interest rates on microloans provided by microfinance IHRMMFIJC. The direct correlations between our variable of interest Y and the other dependent variables X1, X2, X3, and X4 were initially built and evaluated using a scheme that envisioned a causal relationship. The hypotheses presented in this research are based on the reviewed literature. The database was used to extract empirical studies of correlations, regressions, coefficients, and other variables. The multiple linear regression model provided by Studenmund [29] is employed in this study based on a theoretical analysis of the aforementioned literature as well as empirical evidence. This analysis was performed using the following constant factor regression model: Yij = β0 + βiXi + ε (1) Where: Y - Dependent variable; β0 = Constant; βi - Partial regression coefficients; Xi - Independent variable; ε - Standard error; The influence of the independent variables EMLMFIJC, LCSMFIE, ICGAMFIPJC, and IHRMMFIJC (as defined above) on the dependent variable JCAMFI was investigated in this study. The linear regression model shown below was used: 𝑌 = 𝛽0 + 𝛽1X1 + 𝛽2X2 + 𝛽3X3 + 𝛽4X3 + ε (2) 𝑌 JCAMFI = 𝛽0 + 𝛽1 EMLMFIJC + 𝛽2 LCSMFIE + 𝛽3 ICGAMFIPJC + 𝛽4 IHRMMFIJC + ε (3) These definitions are as follows: X1 is the existence of a significant relationship between job creation and microcredits offered by Micro Finance Institutions (EMLMFIJC); X2 is any relationship between employment growth and the consulting services offered by Micro Finance Institutions (LCSMFIE); X3 is the effect of government agency lack of coordination on the success of Micro Finance Institutions' job creation programs (ICGAMFIPJC); and X4 is the effect of the high interest rate of Micro Finance Institutions' microcredits on job creation (IHRMMFIJC). The independent variables EMLMFIJC, 150 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 4: 146-156, 2025 DOI: 10.55214/25768484.v9i4.5950 © 2025 by the authors; licensee Learning Gate LCSMFIE, ICGAMFIPJC, and IHRMMFIJC were compared to the dependent variable Y, which is Job Creation through Micro Finance Institutions Activities (JCAMFI). 4. Data Analysis and Results 4.1. Analysis of the Microfinance Sector in Kosovo Economic development and job creation in Kosovo are drivers of the country's socio-economic development, so in this regard, MFIs have played an essential role by providing microloans to individuals and small and medium-sized enterprises, helping to create and expand businesses, which has led to the creation of new jobs. Based on the report published by the Statistical Agency of Kosovo (SAK), it appears that financial and insurance activities in Kosovo contribute 416,894,000 euros to the Gross Domestic Product (GDP) by economic activities at current prices, where its value was around 9,680,068,000 euros [30]. Through their dedication and commitment, microfinance institutions in Kosovo continue to be an important engine of economic development and improvement of the well- being of Kosovo citizens. The microfinance sector in Kosovo has continued to grow during September 2024; the amount of active loans reached 381 million euros distributed to 125 thousand clients [31]. Based on the annual report of AMIK members, below we present the main data of the MFIs operating in Kosovo; see Table 1. Table 1. Key IMF Data as of September 2024. Total loan portfolio (active): 381 million Euros Total number of borrowers (active): 125,730 Average loan size (active): 3,631 Value of new loans disbursed: 31 million Euros Total number of employees: 1,219 Total number of branches: 137 Source: The writers processed data from the Association of Microfinance Institutions of Kosovo in 2024. Regarding the structure and activities of MFIs and NBFIs in Kosovo, according to the Monthly Statistical Bulletin published in September 2024 by the CBK, 9 MFIs operate in Kosovo, of which 6 are foreign-owned, while the number of NBFIs operating in Kosovo is 23, of which 8 are foreign-owned. Regarding the financial activities of MFIs and NBFIs, according to the situation in September 2024, the value of assets is 627.9, loans and leasing 535.5, for households 284.5, and for non-financial corporations 251.0. The annual change in loans and leasing is 21.6%, for households 15.9%, and for non-financial corporations 28.9%; the interest rate on loans and leasing is around 18.8% [32]. 4.2. Survey Results The following is a presentation of the survey's findings about the relationships between MFIs' microloans, their consultancy services, the lack of coordination between government agencies and MFI programs, and the effect of the high interest rates of MFI credit on job creation: In summary, the descriptive analyses derived from 150 observations show that the kurtosis is -1.675, the skewness of - 0.589 indicates a minor negative asymmetry, the average is 1.64, and the standard deviation is 0.482. According to the observation by variables, the standard deviation is 0.348, and the average of the relationship between microloans from MFIs and the creation of new jobs is 0.14. Employment growth and MFIs' provision of consulting services have a 3.31 correlation, with a 4.291 standard deviation. The impact of the government agency's lack of cooperation on MFI programs' ability to create new jobs is 3.63 on average, with a standard deviation of 4.063. The standard deviation is approximately 4.326, while the average effect of the high interest rate of microcredits offered by MFIs on job creation is 3.25. Refer to Table 2 for specifics. 151 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 4: 146-156, 2025 DOI: 10.55214/25768484.v9i4.5950 © 2025 by the authors; licensee Learning Gate Table 2. Descriptive statistics of variables. According to the results of the ANOVA analysis, the regression model predicts the dependent variable Job Creation with statistical significance. This information can be displayed as follows: Model: The regression model's analysis of variance (ANOVA) findings are displayed in this table. In addition to the constant term, there are four predictor variables. Total Squares: Regression = 34.546: This figure shows how much of the variance in the dependent variable the regression model can account for. The model explains a significant amount of the data variation, as shown by a high value. Residual = 0.014: This figure shows the amount of variance in the dependent variable that the model (error) cannot account for. The model is reported to fit the data well if the value is low. Total = 34.560: This indicates the overall variance in the dependent variable and is the sum of the regression sums of squares and residuals. Degrees of Freedom, or df: Regression = 4: This is the model's predictor variable count (4 variables plus 1 constant). Residual = 145: This is the number of observations minus the number of model parameters (n - k). Total = 149: This is the sum of all observations minus 1 (n - 1). Mean square: The total of squares divided by the degrees of freedom. The regression's mean square value is 8.637. Residual = 0.000 is the mean square of the residuals. The F statistic, F = 92521.080 (p < .001), is used to test the model's significance by comparing it to the F distribution. A very high F value, combined with a very small p value (.000), implies that the regression model is statistically significant. This indicates that at least one predictor variable has a statistically significant effect on the dependent variable. Significance (p-value) =.000: The p-value is very low, indicating that the results are unlikely to be attributable to chance. This confirms the model's importance. ANOVA reveals that the regression model explains a considerable portion of the variation in the data (Q3), and it is statistically highly significant. The high ratio of the regression sum of squares to the residual sum of squares indicates the model is well fitted to the data. See Table 3 for further details. Table 3. Anova. ANOVAa Model Sum of Squares df Mean Square F Sig. 1 Regression 34.546 4 8.637 92521.080 0.000b Residual 0.014 145 0.000 Total 34.560 149 Note: a. Dependent Variable: Q3. Job creation b. Predictors: (Constant), Q3.4: How do high interest rates on microloans offered by MFIs effect employment creation? Q3.1: Is there a link between micro-loans provided by MFIs and employment creation? Q 3.3: Does the lack of coordination between government agencies hinder the efficacy of MFI initiatives in employment creation? Q 3.2: Is there a link between MFIs providing consultancy services and increased employment? For the normal distribution of variables, the range of variables should not deviate significantly from zero [33]. According to Wright and Herrington [34], distortion values ranging from -1 to +1 should be statistically acceptable. Based on the descriptive analysis results, which showed that the variables' bias values were between +1 and -1, we can conclude that the variables are within statistically accepted Descriptive Statistics N Minimum Maximum Mean Std. Deviation Skewness Kurtosis Statistic Statistic Statistic Statistic Statistic Statistic Std. Error Statistic Std. Error JCAMFI 150 1 2 1.64 .482 -.589 .198 -1.675 0.392 EMLMFIJC 150 0 1 0.14 .348 2.096 .198 2.425 0.392 LCSMFIE 150 0 9 3.31 4.291 .580 .198 -1.675 0.392 ICGAMFIPJC 150 0 9 3.63 4.063 0.559 .198 -1.667 0.392 IHRMMFIJC 150 0 9 3.25 4.326 0.587 .198 -1.675 0.392 Valid N (listwise) 150 152 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 4: 146-156, 2025 DOI: 10.55214/25768484.v9i4.5950 © 2025 by the authors; licensee Learning Gate parameters and their distribution is within normal limits. The standardized coefficients for all variables in the preceding results indicate that the data fit normal parameters and are statistically acceptable. The level of significance of the correlation coefficient (rho) in correlation analysis can be influenced by sample size. After developing hypotheses, we tested them to see if there is a relationship between the dependent variable Y, in this case tourism development, and the independent variables X1, X2, X3, and X4, and the coefficients of correlation between variables were provided in Table 4. Table 4. Regression coefficients of independent variables. Coefficientsa Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) 2.012 0.002 1289.110 0.000 EMLMFIJC 0.004 0.002 0.003 1.882 0.042 LCSMFIE -0.023 0.003 -0.204 -7.883 0.000 ICGAMFIPJC -0.015 0.002 -0.123 -7.741 0.000 IHRMMFIJC -0.075 0.004 -0.673 -21.317 0.000 Note: a. Dependent Variable: JCAMFI. The coefficient table displays the results of a logistic regression model in which the dependent variable (Q3) is binary (0 or 1), indicating whether an individual was employed throughout the year. To determine which hypothesis is accepted or rejected, we apply a Sig value of 0.05 (Constant) = 2.012 (p < .001). This is the intercept term. It denotes the log-odds of being employed when all predictor variables are zero. The very low p-value implies that the term is statistically significant. Hypothesis test: The linear regression result for H1 demonstrates that there is a weak link between the volume of microloans granted by MFIs and job creation; 0.042 is slightly below the usual threshold of significance (t = 1.882, β = 0.003, p = 0.042). This indicates a minor increase in job creation, as a one-unit increase in this variable corresponds to a 0.003-unit increase in employment. The p-value of 0.042 is slightly lower than the expected level but considerably less than the 0.05 level. Based on this, we may conclude that in H1, there is a weak association between the amount of microloans granted by the MFI and the creation of new jobs, and thus this hypothesis is validated or accepted. H2 indicates that MFI counseling had no significant impact on job creation (t = -7.883, β = -.204, p = 0.000). The relatively low p-value indicates that this effect is statistically significant. This demonstrates that one unit of consultancy offered per client by the MFI has no effect on the creation of new jobs; rather, it reduces the creation of new jobs by -0.204, as well as the value of p = 0.000, which from the KJP resulted in a value less than 0.05. This leads us to the conclusion that H2, which is related to the consultancy provided per client by the MFI, has no impact on the creation of new jobs; hence, this hypothesis is confirmed or accepted. The linear regression result for H3 is significant and negative (t = -123, β = -7.741, p = 0.000), indicating that the MFI initiatives lack an adequate level of cooperation with government institutions and, as a result, have no impact on the creation of new jobs. This demonstrates that a unit of MFI programs lacks appropriate coordination with government institutions and thus has no effect on job creation, or we will have a decrease of -7.741, as well as a p-value of 0.000, indicating that this value is less than the significant value of 0.05. Based on these values, we can conclude that H3 MFI programs lack proper coordination with government institutions and have no influence on employment development; hence, this hypothesis is confirmed or accepted. H4 is significant and negative since it demonstrates that high interest rates on microloans from MFIs have a negative effect on the creation of jobs (t = -.673, β = -21.317, p = 0.000). This 153 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 4: 146-156, 2025 DOI: 10.55214/25768484.v9i4.5950 © 2025 by the authors; licensee Learning Gate demonstrates that one unit of high interest rates on MFI microloans has a negative impact on job creation of -21.317, with p = 0.000, resulting in a value less than the significance level of 0.05. Based on this, we may conclude that H4's high interest rates on MFI microloans have a negative impact on employment creation; therefore, H4 is also approved or affirmed. Table 5. Case Processing Summary. Case Processing Summary N % Cases Valid 150 100.0 Excludeda 0 0.0 Total 150 100.0 Note: a. Listwise deletion based on all variables in the procedure. The "Case Processing Summary" reveals that 150 cases were included in the analysis, with no cases excluded. This is positive since the lack of missing or excluded data implies that the data is comprehensive and ready for analysis. "Listwise deletion" indicates that any case with missing data on any variable has been excluded from the study. In the present instance, there are no such cases. Table 6. Reliability Statistics. Reliability Statistics Cronbach's Alpha N of Items 0.881 4 The Cronbach's Alpha test result in Table 6 on the measuring of statistical reliability shows that Cronbach's Alpha = 0.881, indicating a high level of reliability. The four questions on this scale are measured, and the results are acceptable, with a stable construct. 5. Discussion Job creation and policy management for MFIs in Kosovo remain insufficient to improve labor market performance. Economic development demands a strong private sector, which requires a strong financial system that offers steady funding and good business conditions. However, an advanced financial system is equally reliant on profitable enterprises that contribute to its development. The development of a sustainable national plan aimed at deepening financial inclusion at the country level is still insufficient; therefore, the success of financial inclusion is inextricably tied to the stability of the financial system, necessitating an integrated approach. Kosovo's microfinance business has evolved greatly since its beginnings in the 1990s. In their early phases, MFIs were mostly non-governmental and non-profit organizations that focused on social welfare and community development. However, as time passed, many of them evolved into official, regulated, and sustainable financial institutions, adjusting to the needs of a rising market. The microfinance sector currently plays a substantial role in the Kosovo economy. According to data from September 2024, active loans in Kosovo totaled 381 million euros, allocated to 125 thousand consumers. This demonstrates a substantial prevalence of microfinance services in Kosovo. Given that 9 MFIs and 23 NBFIs operate in Kosovo, with a total asset value of 627.9 million euros, it is apparent that this sector is a critical component of the national financial system. The microfinance sector in Kosovo contributes to the generation of jobs, which is especially significant in a nation with a high unemployment rate such as Kosovo. Job creation is also linked to a strong association between MFI development, microcredits provided, consulting services, government coordination, and loan interest rates. Based on the survey results, the majority of respondents stated yes, with just a small percentage saying there was a strong association between MFI microcredits and employment development. Linear regression analyses for H1, H2, H3, and H4 reveal 154 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 4: 146-156, 2025 DOI: 10.55214/25768484.v9i4.5950 © 2025 by the authors; licensee Learning Gate substantial correlations between job creation and the hypotheses raised in this study in Kosovo; hence, based on the values of t, b, and p, we may conclude that the hypotheses raised in this work can be confirmed or accepted. 6. Conclusions and Recommendations Kosovo's job creation is low due to insufficient economic development, ineffective labor market policies, and ineffective country-level financial management. There is a limited association between the number of microloans made by MFIs and the number of employments produced. Microloans resulted in a minimal rise in employment. It is widely acknowledged that job growth is inextricably tied to the expansion of MFIs; nevertheless, this relationship is influenced by a variety of factors, including service quality, interinstitutional cooperation, and market conditions. The high interest rates on microloans can be a barrier to employment growth. The high cost of borrowing can make certain borrowers unable to sustain, limiting employment growth; hence, it is critical to strike a balance between profitability and loan accessibility. MFIs not only provide microcredit but also consultancy, training, and support services to borrowers, which, according to the study's findings, have not had the desired impact, despite the fact that these services are essential to the success of new businesses and the improvement of existing ones, directly contributing to the increase in employment. Based on the correlation regression analyses and the coefficient values between the constant variable and the independent variables, hypotheses 1, 2, 3, and 4 result as accepted. One of the recommendations emerging from this study, based on the previously explained link between MFIs and job creation, is that the government and financial institutions collaborate to create mechanisms that reduce the costs of lending to MFIs, such as guarantee schemes, favorable refinancing, and tax cuts. This will enable MFIs to offer loans at reduced interest rates, making them more accessible to small enterprises and boosting job development. MFIs should broaden their financial product and service offerings, such as insurance, savings, and money transfers. To guarantee that financing reaches the small businesses who need it the most, the loan application process should be improved, with procedures simplified and borrowers given priority, particularly those with the potential for job creation. MFIs should invest in training their employees to provide consulting and support to businesses. This will improve service quality and boost the likelihood of business success. MFIs should form collaborations with other organizations, such as non- governmental organizations and academic institutions, in order to provide a broader range of advisory and training services. The government should establish a coordination platform that brings together relevant government agencies to discuss and coordinate policies that support small businesses. Loan and subsidy application procedures should be standardized to make it easier for people and small enterprises to apply. Government entities should communicate with one another on a frequent basis in order to monitor program implementation and identify challenges. To solve the issue of high interest rates, the government might subsidize interest rates on specific loans, making them more accessible for consumers and small enterprises. In Kosovo, additional effort is needed to enhance competition; consequently, competition in the microfinance industry should be encouraged, allowing new businesses to enter the market. Financial technology can be utilized to minimize transaction costs and increase the efficiency of MFIs, resulting in reduced interest rates. Implementing these recommendations would significantly improve MFIs' efficacy of creating jobs in Kosovo. The success of these ideas is dependent on successful cooperation among the government, the private sector, and international organizations. One of the constraints in the establishment of the present study is a lack of funding for this research in order to enlarge the sample size, considering the fact that the most comprehensive sample in the research will produce the most representative data. We also urge that future studies consider the findings of this study on job creation by doing comparison analyses across years to minimize gaps in the study of key indicators of job creation through MFI efficacy. The study's findings will have a favorable impact on improving the effectiveness of MFIs, particularly in terms of job creation in Kosovo. 155 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 4: 146-156, 2025 DOI: 10.55214/25768484.v9i4.5950 © 2025 by the authors; licensee Learning Gate Transparency: The authors confirm that the manuscript is an honest, accurate, and transparent account of the study; that no vital features of the study have been omitted; and that any discrepancies from the study as planned have been explained. This study followed all ethical practices during writing. 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