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Journal ArticleDOI

Repayment behaviour in credit and savings cooperative societies

10 Apr 2009-International Journal of Social Economics (Emerald Group Publishing Limited)-Vol. 36, Iss: 5, pp 608-625
TL;DR: In this paper, the authors examined the factors contributing to credit repayment behavior among the members of savings and credit cooperative societies in rural Rwanda and employed a binary logistic regression empirical model to estimate the contribution of each variable to credit repay rat...
Abstract: Purpose – Like other developing countries, Rwandan rural credit market is repressed, shallow, segmented, inefficient and dual structured where both formal and informal financial systems operate side by side. While the later has been playing a predominant role, cooperative societies have emerged as an apt method of increasing the delivery of formal rural credit and savings facilities on sustainable and non‐exploitative terms albeit of financial imprudence stemming from poor credit repayment records. Thus, the purpose of this paper is to examine the factors contributing to credit repayment behaviour among the members of savings and credit cooperative societies in rural Rwanda.Design/methodology/approach – Both exploratory and descriptive designs are used for primary data collection on variables contributing to the repayment behaviour in savings and cooperative societies. Thereafter, a binary logistic regression empirical model is employed to estimate the contribution of each variable to credit repayment rat...
Citations
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01 Jan 2010
TL;DR: In this paper, the determinants of repayment performances in micro credit programs are reviewed, which can be divided into four factors namely borrower characteristics, firm characteristics, loan characteristics and lender characteristics.
Abstract: The aim of microcredit is to help the poor and lower income group to get funds for their business activities and to improve their lives. Usually, the loans given are very small, in short term period, no collateral needed and required weekly repayment. However, repayment problems become the main obstacle for the microcredit institutions to continue providing microcredit services. This is because most of the microcredit institutions are Non- Governmental Organizations (NGOs), where they received funds from the government and donors and there are not profits oriented organizations. Therefore, this paper tries to review the determinants of repayment performances in microcredit programs which can be divided into four factors namely borrower characteristics, firm characteristics, loan characteristics and lender characteristics.

85 citations


Additional excerpts

  • ...Characteristics Researchers Age Educational level Gender Borrower’s business experience Monthly income Eze & Ibekwe (2007), Papias & Ganesan (2009), Aguilera & GonzalezVega (1998), Reinke (1998), Nannyonga (2000) Bhatt & Tang (2002), Arene (1992), Nikhade et al. (1994), Eze & Ibekwe (2007), Rambabu…...

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  • ...…Reinke (1998), Nannyonga (2000) Bhatt & Tang (2002), Arene (1992), Nikhade et al. (1994), Eze & Ibekwe (2007), Rambabu & Eswaran (1994) Roslan & Mohd Zaini (2009), Papias & Ganesan (2009), Khander et al. (1995); Derban et al (2005); Sharma & Zeller (1997) Arene (1992), Njoku (1997) Nannyonga (2000)...

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Journal ArticleDOI
TL;DR: Although much saving research has been conducted in affluent nations, little is known about consumer saving and well-being at the base of the pyramid, which includes over 3 billion people who live in the developing world as mentioned in this paper.
Abstract: Although much saving research has been conducted in affluent nations, little is known about consumer saving and well-being at the base of the pyramid, which includes over 3 billion people who live ...

77 citations

Journal ArticleDOI
TL;DR: In this paper, a multinomial logit regression model was used to determine the factors affecting repayment performance in micro-finance programs in Malaysia by using a survey on 309 respondents of TEKUN Nasional clients.

69 citations

Journal ArticleDOI
TL;DR: In this paper, the authors analyzed the smallholder farmers' loan repayment capacity using household data from 110 cooperative farmers from selected villages in Ogun State, Nigeria, and examined the socioeconomic and demographic characteristics of respondents, loan repayment rate and factors influencing repayment capacity.
Abstract: Farm credits played vital roles in the socio-economic transformation of the rural economies. However, their acquisition and repayment were characterized by numerous challenges including high levels of default among beneficiaries. This study analyzed the smallholder farmers’ loan repayment capacity using household data from 110 cooperative farmers from selected villages in Ogun State, Nigeria. Specifically, the socio-economic and demographic characteristics of respondents, loan repayment rate and factors influencing repayment capacity were examined. Aside from purposive selection of Yewa North, multistage random sampling technique was used to select the study sample. Data were analyzed using descriptive statistics, correlation and regression techniques. Results revealed that the average age of respondents was 45 years with 36% within 20 to 40 years active working population. Average repayment rate was 69% with 42% repaying above nine-tenths, and 20% less than one-half of potential amounts during the period. Loan size (p<0.01) and farm size (p<0.05) had significant positive influences on loan repayment capacity while household size (p<0.05) had a negative influence. From the elasticity analysis, while a 10% increase in loan and farm sizes resulted to 7 and 2.8% increases respectively, similar 10% increase in household size caused 4.2% decrease in repayment capacity. All significant variables produced a priori signs. The implication is that to enhance loan repayment capacity of smallholder cooperative farmers, policies and programmes capable of increasing sizes of loan and farm holdings, or reducing household size should be promoted. However, higher proportional increases were required for each variable to attain a desired level of increase in loan repayment capacity. Key words: Nigeria, cooperatives, farm size, household size, loan size, repayment capacity, repayment rate, smallholder farmers.

57 citations


Cites background or methods from "Repayment behaviour in credit and s..."

  • ...Others include farm/non-farm expenses (Afolabi, 2010, 2008), family/household size – in some cases adult equivalent household size (Papias and Ganesan, 2009; Oke et al., 2007), number of spouse of respondent (Oke et al., 2007), marital status (Oni et al., 2005) and occupation (Oladeebo and…...

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  • ...Also included were repayment of loan from transfer income, that is whether loan was repaid with transfer income or otherwise (Papias and Ganesan, 2009; Oke et al., 2007), distance between dwelling place and location of the credit institution (Oke et al., 2007), amount of business investment (Oke et…...

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  • ...…profitability level (Oke et al., 2007), degree of loan diversification (number of inputs bought with loan) (Oke et al., 2007), purpose of credit (Papias and Ganesan 2009), business enterprise combination, for example, if firm engages on economic activities other than agriculture (Oke et al.,…...

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  • ...…1996), loan repayment method (Derban et al., 2005), loan repayment period (Derban et al., 2005), loan transaction cost (Nawai and Shariff, 2010; Papias and Ganesan, 2009; Oke et al., 2007), time laps between loan application and disbursement (Kohansal and Mansoori, 2009), collateral value…...

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  • ...…2009; Afolabi, 2008; Oladeebo and Oladeebo, 2008; Oni et al., 2005), level of education (Oladeebo and Oladeebo, 2008; Eze and Ibekwe, 2007), gender (Papias and Ganesan, 2009; Roslan and Karim, 2009; Eze and Ibekwe, 2007; Arene, 1992), experiences – including experiences in farming, credit use,…...

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01 Jan 2014
TL;DR: In this article, the authors identify the challenges facing SACCOs in Mombasa such as lack of finance, discrimination, problems with the city council, multiple duties, poor access to justice, lack of education, among others and initiatives put in place to counter the challenges.
Abstract: SACCOs (Savings and Credit Co-operative Societies) are predominant form of external financing for small and micro enterprises in most of the developing countries. Contemporary studies show that SACCOS’ role towards developing these enterprises is increasing rapidly. Statistics show that there are 10,800 registered Co-operative Societies in Kenya with a membership of about 6 million. Out of this, 46% are Agricultural, 38% Financial-based (SACCOS) and, 16% are others. 63% of the Kenyan population depends on Co-operative related activities for their livelihood with over 250,000 benefiting through direct employment. SACCOS have been noted to contribute over 45% GDP and it is estimated that at least one out of every two Kenyans directly or indirectly derives his /her livelihood from these kinds of Cooperatives. From this insight, the study sought to identify the challenges facing SACCOs in Mombasa such as lack of finance, discrimination, problems with the city council, multiple duties, poor access to justice, lack of education, among others and initiatives put in place to counter the challenges. The study realized that despite the challenges, opportunities were available for SACCOs and their impact to the economic development, including capital accumulation and agency business largely arising from access to Government funds for on-ward transmission to youth and women groups. The study employed desktop research. The data in this study was analyzed using statistical package for social sciences. The findings of this study are important for the particular organizations under study to address the challenges so as to improve their service delivery, the industry to anticipate and endeavour to overcome the challenges. This paper recommends policy makers and governments to come-up with policies and strategies that will support the growth of SACCOS which is a pertinent alternative solution for financing micro and small businesses. Further research is however recommended in this area.

44 citations

References
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Book
01 Jan 1983
TL;DR: In this Section: 1. Multivariate Statistics: Why? and 2. A Guide to Statistical Techniques: Using the Book Research Questions and Associated Techniques.
Abstract: In this Section: 1. Brief Table of Contents 2. Full Table of Contents 1. BRIEF TABLE OF CONTENTS Chapter 1 Introduction Chapter 2 A Guide to Statistical Techniques: Using the Book Chapter 3 Review of Univariate and Bivariate Statistics Chapter 4 Cleaning Up Your Act: Screening Data Prior to Analysis Chapter 5 Multiple Regression Chapter 6 Analysis of Covariance Chapter 7 Multivariate Analysis of Variance and Covariance Chapter 8 Profile Analysis: The Multivariate Approach to Repeated Measures Chapter 9 Discriminant Analysis Chapter 10 Logistic Regression Chapter 11 Survival/Failure Analysis Chapter 12 Canonical Correlation Chapter 13 Principal Components and Factor Analysis Chapter 14 Structural Equation Modeling Chapter 15 Multilevel Linear Modeling Chapter 16 Multiway Frequency Analysis 2. FULL TABLE OF CONTENTS Chapter 1: Introduction Multivariate Statistics: Why? Some Useful Definitions Linear Combinations of Variables Number and Nature of Variables to Include Statistical Power Data Appropriate for Multivariate Statistics Organization of the Book Chapter 2: A Guide to Statistical Techniques: Using the Book Research Questions and Associated Techniques Some Further Comparisons A Decision Tree Technique Chapters Preliminary Check of the Data Chapter 3: Review of Univariate and Bivariate Statistics Hypothesis Testing Analysis of Variance Parameter Estimation Effect Size Bivariate Statistics: Correlation and Regression. Chi-Square Analysis Chapter 4: Cleaning Up Your Act: Screening Data Prior to Analysis Important Issues in Data Screening Complete Examples of Data Screening Chapter 5: Multiple Regression General Purpose and Description Kinds of Research Questions Limitations to Regression Analyses Fundamental Equations for Multiple Regression Major Types of Multiple Regression Some Important Issues. Complete Examples of Regression Analysis Comparison of Programs Chapter 6: Analysis of Covariance General Purpose and Description Kinds of Research Questions Limitations to Analysis of Covariance Fundamental Equations for Analysis of Covariance Some Important Issues Complete Example of Analysis of Covariance Comparison of Programs Chapter 7: Multivariate Analysis of Variance and Covariance General Purpose and Description Kinds of Research Questions Limitations to Multivariate Analysis of Variance and Covariance Fundamental Equations for Multivariate Analysis of Variance and Covariance Some Important Issues Complete Examples of Multivariate Analysis of Variance and Covariance Comparison of Programs Chapter 8: Profile Analysis: The Multivariate Approach to Repeated Measures General Purpose and Description Kinds of Research Questions Limitations to Profile Analysis Fundamental Equations for Profile Analysis Some Important Issues Complete Examples of Profile Analysis Comparison of Programs Chapter 9: Discriminant Analysis General Purpose and Description Kinds of Research Questions Limitations to Discriminant Analysis Fundamental Equations for Discriminant Analysis Types of Discriminant Analysis Some Important Issues Comparison of Programs Chapter 10: Logistic Regression General Purpose and Description Kinds of Research Questions Limitations to Logistic Regression Analysis Fundamental Equations for Logistic Regression Types of Logistic Regression Some Important Issues Complete Examples of Logistic Regression Comparison of Programs Chapter 11: Survival/Failure Analysis General Purpose and Description Kinds of Research Questions Limitations to Survival Analysis Fundamental Equations for Survival Analysis Types of Survival Analysis Some Important Issues Complete Example of Survival Analysis Comparison of Programs Chapter 12: Canonical Correlation General Purpose and Description Kinds of Research Questions Limitations Fundamental Equations for Canonical Correlation Some Important Issues Complete Example of Canonical Correlation Comparison of Programs Chapter 13: Principal Components and Factor Analysis General Purpose and Description Kinds of Research Questions Limitations Fundamental Equations for Factor Analysis Major Types of Factor Analysis Some Important Issues Complete Example of FA Comparison of Programs Chapter 14: Structural Equation Modeling General Purpose and Description Kinds of Research Questions Limitations to Structural Equation Modeling Fundamental Equations for Structural Equations Modeling Some Important Issues Complete Examples of Structural Equation Modeling Analysis. Comparison of Programs Chapter 15: Multilevel Linear Modeling General Purpose and Description Kinds of Research Questions Limitations to Multilevel Linear Modeling Fundamental Equations Types of MLM Some Important Issues Complete Example of MLM Comparison of Programs Chapter 16: Multiway Frequency Analysis General Purpose and Description Kinds of Research Questions Limitations to Multiway Frequency Analysis Fundamental Equations for Multiway Frequency Analysis Some Important Issues Complete Example of Multiway Frequency Analysis Comparison of Programs

53,113 citations

Journal ArticleDOI
01 Jan 1973
TL;DR: In this paper, a six-step framework for organizing and discussing multivariate data analysis techniques with flowcharts for each is presented, focusing on the use of each technique, rather than its mathematical derivation.
Abstract: Offers an applications-oriented approach to multivariate data analysis, focusing on the use of each technique, rather than its mathematical derivation. The text introduces a six-step framework for organizing and discussing techniques with flowcharts for each. Well-suited for the non-statistician, this applications-oriented introduction to multivariate analysis focuses on the fundamental concepts that affect the use of specific techniques rather than the mathematical derivation of the technique. Provides an overview of several techniques and approaches that are available to analysts today - e.g., data warehousing and data mining, neural networks and resampling/bootstrapping. Chapters are organized to provide a practical, logical progression of the phases of analysis and to group similar types of techniques applicable to most situations. Table of Contents 1. Introduction. I. PREPARING FOR A MULTIVARIATE ANALYSIS. 2. Examining Your Data. 3. Factor Analysis. II. DEPENDENCE TECHNIQUES. 4. Multiple Regression. 5. Multiple Discriminant Analysis and Logistic Regression. 6. Multivariate Analysis of Variance. 7. Conjoint Analysis. 8. Canonical Correlation Analysis. III. INTERDEPENDENCE TECHNIQUES. 9. Cluster Analysis. 10. Multidimensional Scaling. IV. ADVANCED AND EMERGING TECHNIQUES. 11. Structural Equation Modeling. 12. Emerging Techniques in Multivariate Analysis. Appendix A: Applications of Multivariate Data Analysis. Index.

37,124 citations

Book
01 Jan 1989
TL;DR: Hosmer and Lemeshow as discussed by the authors provide an accessible introduction to the logistic regression model while incorporating advances of the last decade, including a variety of software packages for the analysis of data sets.
Abstract: From the reviews of the First Edition. "An interesting, useful, and well-written book on logistic regression models... Hosmer and Lemeshow have used very little mathematics, have presented difficult concepts heuristically and through illustrative examples, and have included references."- Choice "Well written, clearly organized, and comprehensive... the authors carefully walk the reader through the estimation of interpretation of coefficients from a wide variety of logistic regression models . . . their careful explication of the quantitative re-expression of coefficients from these various models is excellent." - Contemporary Sociology "An extremely well-written book that will certainly prove an invaluable acquisition to the practicing statistician who finds other literature on analysis of discrete data hard to follow or heavily theoretical."-The Statistician In this revised and updated edition of their popular book, David Hosmer and Stanley Lemeshow continue to provide an amazingly accessible introduction to the logistic regression model while incorporating advances of the last decade, including a variety of software packages for the analysis of data sets. Hosmer and Lemeshow extend the discussion from biostatistics and epidemiology to cutting-edge applications in data mining and machine learning, guiding readers step-by-step through the use of modeling techniques for dichotomous data in diverse fields. Ample new topics and expanded discussions of existing material are accompanied by a wealth of real-world examples-with extensive data sets available over the Internet.

35,847 citations

Journal ArticleDOI
TL;DR: Applied Logistic Regression, Third Edition provides an easily accessible introduction to the logistic regression model and highlights the power of this model by examining the relationship between a dichotomous outcome and a set of covariables.
Abstract: \"A new edition of the definitive guide to logistic regression modeling for health science and other applicationsThis thoroughly expanded Third Edition provides an easily accessible introduction to the logistic regression (LR) model and highlights the power of this model by examining the relationship between a dichotomous outcome and a set of covariables. Applied Logistic Regression, Third Edition emphasizes applications in the health sciences and handpicks topics that best suit the use of modern statistical software. The book provides readers with state-of-the-art techniques for building, interpreting, and assessing the performance of LR models. New and updated features include: A chapter on the analysis of correlated outcome data. A wealth of additional material for topics ranging from Bayesian methods to assessing model fit Rich data sets from real-world studies that demonstrate each method under discussion. Detailed examples and interpretation of the presented results as well as exercises throughout Applied Logistic Regression, Third Edition is a must-have guide for professionals and researchers who need to model nominal or ordinal scaled outcome variables in public health, medicine, and the social sciences as well as a wide range of other fields and disciplines\"--

30,190 citations

Journal ArticleDOI
TL;DR: This chapter discusses Structural Equation Modeling: An Introduction, and SEM: Confirmatory Factor Analysis, and Testing A Structural Model, which shows how the model can be modified for different data types.
Abstract: I Introduction 1 Introduction II Preparing For a MV Analysis 2 Examining Your Data 3 Factor Analysis III Dependence Techniques 4 Multiple Regression Analysis 5 Multiple Discriminate Analysis and Logistic Regression 6 Multivariate Analysis of Variance 7 Conjoint Analysis IV Interdependence Techniques 8 Cluster Analysis 9 Multidimensional Scaling and Correspondence Analysis V Moving Beyond the Basic Techniques 10 Structural Equation Modeling: Overview 10a Appendix -- SEM 11 CFA: Confirmatory Factor Analysis 11a Appendix -- CFA 12 SEM: Testing A Structural Model 12a Appendix -- SEM APPENDIX A Basic Stats

23,353 citations