Do farmer and credit specific characteristics matter in microfinance programmes’ participation? Evidence from smallholder farmers in Ada west and east districts

2019 ◽  
Vol 79 (3) ◽  
pp. 353-370 ◽  
Author(s):  
Emmanuel Tetteh Jumpah ◽  
Yaw Osei-Asare ◽  
Emmanuel Kodjo Tetteh
Keyword(s):  
Logistic Regression ◽  
Interest Rate ◽  
Regression Model ◽  
Urban Areas ◽  
Logistic Regression Model ◽  
Smallholder Farmers ◽  
Household Head ◽  
Sampling Technique ◽  
Content Type ◽  
Factors Affecting

Purpose Users of smallholder farmer microfinance are able to make enough returns to repay credits advanced to them. However, they are in dire need of financial capital such that they are inconsiderate of farmer- and credit-specific characteristics when participating in a microfinance programme. This study analyses perceptions of stakeholders regarding select farmer and credit characteristics within the microfinance industry. The study identifies and analyses the factors that influence participation in a microfinance programme by farmers using the logistic regression model. The purpose of this paper is to widen the knowledge base of rural agricultural finance, including factors that influence participation in microfinance intervention(s) thereof. Design/methodology/approach A total of 104 participants and 120 non-participant farmers in microfinance programmes were interviewed using a semi-structured questionnaire by applying the multistage sampling technique. The paper applied the logistic regression model in which farmer- and credit-specific characteristics were used to estimate the probabilities of participation. Findings The logistic regression results showed that distance, interest rate, experience, membership of farmer-based organisation, number of dependants, household, gender and age were statistically significant farmer- and credit-specific characteristics that influence participation in microfinance programmes. Interest rate and distance exact negative significance influence on participation, whereas membership of farmer-based organisations, experience, gender, household head and age influence participation positively. Reduction in the interest rate and expansion of microfinance to very remote areas rather than locations in urban areas are crucial in terms of improving participation. Research limitations/implications The paper used data from only farmers so there is a limit to which the results can be generalised for all microfinance users. It may be relevant to undertake a study that considers non-farm enterprises. Practical implications This paper brings to light the need to develop well-structured microfinance facilities that meet the specific needs of the rural poor in transitioning economies while taking into consideration critical factors affecting participation before the establishment of such programmes. Originality/value This paper provides empirical evidence to show that farmer- and credit-specific characteristics are essential to ensure participation and success of microfinance programmes thereof.

scholarly journals Determinants of adaptation strategies to climate change among the smallholder farmers in Adama District, Ethiopia

2020 ◽  
Vol 12 (4) ◽  
pp. 463-476
Author(s):  
Hurgesa Hundera Hirpha ◽  
Sylvester Mpandeli ◽  
Amare Bantider
Keyword(s):  
Climate Change ◽  
Logistic Regression ◽  
Regression Model ◽  
Climate Change Adaptation ◽  
Logistic Regression Model ◽  
Smallholder Farmers ◽  
Binary Logistic Regression ◽  
Adaptation Strategies ◽  
Binary Logistic Regression Model ◽  
Content Type

Purpose The Ethiopian economy is mainly based on the rain-fed agriculture practiced by smallholder farmers. The sector is highly vulnerable to climate change impacts. This study aims to examine the determinants of adaptation strategies to climate change among the smallholder farmers in Adama District, Ethiopia. Design/methodology/approach A cross-sectional survey design was used to collect quantitative data using questionnaire with 351 randomly selected smallholder farmers. To collect qualitative data focus group discussions, key informant interviews and field observations were also used. Triangulated with thematic analysis, descriptive statistics and binary logistic regression model were used for the analysis. Findings The result indicated that the majority of the smallholder farmers use at least one climate change adaptation strategy in their local areas though the strategy is generally weak. In this regard, some of the dominant climate change adaptation activities identified in the study area are using improved crop varieties, planting trees, watershed management, adjusting planting date and terracing. The result from binary logistic regression model showed that age and sex of household head, as well as their education, family size, access to agricultural extension services and training on climate change significantly influence the practices of adaptation measures. Originality/value This study would help the practitioners to modify the existing weak adaptation activities by introducing advanced and technological-based adaptation strategies to the rural farming communities.

Understanding the contract structure for mango and empirical analysis of its determinants

2015 ◽  
Vol 117 (8) ◽  
pp. 2161-2181
Author(s):  
Jabir Ali ◽  
Sushil Kumar
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Future Research ◽  
Contract Management ◽  
Snowball Sampling ◽  
Content Type ◽  
Factors Affecting ◽  
Contract Structure ◽  
Contract Attributes

Purpose – The purpose of this paper is to analyze the structure of contractual arrangements in mango orchards and factors affecting the mango contract design in India. Design/methodology/approach – The study is based on personal structured questionnaire survey of 83 contractors in one of the major mango growing areas in India. A snowball sampling approach was adopted to select suitable respondents for the study. Descriptive statistics have been computed to understand the contractor’s response on contract attributes. Factor analysis was used to categorize the contractors’ responses on various attributes of the mango contract. Further, a logistic regression model has been developed to determine the factors affecting the contract decisions. Findings – The study identifies nine aspects of mango contracting covering orchard owner, orchard and contract management characteristics. Further, a logistic regression model has been developed to assess the factors affecting the contractor’s decision on the time of entering into mango contracting, i.e. pre-flowering or post-flowering stage. Regression analysis results clearly indicate that contractors who prefer pre-flowering contracts pay significantly higher attention to contract management attributes. On the other hand, those contractors who normally enter in contract once the mango trees have flowered are more likely to pay attention to orchard-related features. Practical implications – Specifically, the results have implications for contract terms, contract efficiency and effectiveness and overall performance. Finally, the study provides suggestions for a future research agenda to analyze mango production contracts. Originality/value – Though contracting in mango growing is a common phenomena, there is limited analysis on identifying the key contract attributes and factors affecting the contract structure.

A STUDY ON PREVALENCE OF POSTPARTUM DEPRESSION AT TERTIARY HOSPITAL, WEST BENGAL.

2021 ◽  
pp. 33-36
Author(s):  
Chandrima Maity ◽  
Debasish Sanyal ◽  
Arati Biswas ◽  
Sudarsan Saha
Keyword(s):  
Logistic Regression ◽  
Postpartum Depression ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Depression Scale ◽  
Sampling Technique ◽  
Simple Random Sampling ◽  
Background Information ◽  
Stepwise Logistic Regression ◽  
Postpartum Mothers

The investigators assessed the prevalence of Postpartum Depression (PPD), its clinical features and relationship of PPD with socio-demographical and obstetrical factors. The samples were selected from the OPD and IPD, of a Medical college in Kolkata.. Observational study was performed on 500(N=500) postpartum mothers who were selected by using Simple Random Sampling Technique within the six weeks of postpartum period. Data were collected by using the Structured Questionnaire for background information, Edinburgh Postnatal Depression Scale (Bengali Version of EPDS) for postpartum depression. Data analysis was performed using Descriptive Statistics, Chi-square, Logistic Regression and Decision Tree. A total of 112 (Prevalence Rate 22.4%) postpartum mothers had PPD. Stepwise logistic regression model correctly classied 92.2% of women who developed PPD. Using logistic regression model, postpartum depression is best predicted by: No. of Postpartum days p< 0.001***, Age of the mother p<0.024**, Religion p<0.003**, Type of family p<0.020**, Education of the mother p<0.001***, Monthly Income of the family p<0.001***, No of other living children p<0.001***, Pregnancy outcome p<0.033**, Any complication during pregnancy / delivery/ postpartum p< 0.001*** and Problems with family members p< 0.001***. The study recommends that evaluation should be carried out for Postpartum Depression and its risk factors to prevent and treat PPD in a timely manner.

Institutions, entrepreneurial adaptation, and the legal form of the organization

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Indu Khurana ◽  
Dmitriy Krichevskiy ◽  
Gregory Dempster ◽  
Sean Stimpson
Keyword(s):  
Logistic Regression ◽  
Survival Rate ◽  
Regression Model ◽  
Economic Freedom ◽  
Logistic Regression Model ◽  
Legal Form ◽  
Content Type ◽  
Legal Structure ◽  
The Usa ◽  
Over Time

PurposeThis paper aims to examine how economic freedom impacts the initial choice of legal structure for startup firms. The authors do this by first exploring whether economic freedom is an essential determinant of the initial legal form of organization (LFO). The authors then explore the impact of economic freedom on firms' choice of changing their initial legal structure over time and how this change impacts their survival rate.Design/methodology/approachThe authors employ a multinomial logistic regression model to measure the initial determinants of LFO by utilizing an eight-year panel data set of 4,928 startups in the USA through the Kauffman firm survey and merge it with the Economic Freedom in North American index from the Fraser Institute. The authors then employ a logistic regression model to examine the determinants facilitating a change in legal structure over time.FindingsThe results show that economic freedom is a significant determinant in the choice of legal structure. The findings also report that the majority of startups do not change their legal form, but of those that do change the legal structure show a higher survival rate.Research limitations/implicationsMajor limitations are the size of the data and the nature of somewhat limited economic freedom differences with the USA. More nuanced measures of economic freedom would be highly desirable.Practical implicationsPolicymakers should take note that limited red tape, smoothly working labor markets and straightforward processes for changes of legal structures of organizations would improve survival and growth odds for entrepreneurs.Originality/valueDrawing on the theory of institutions, the authors attempt to bridge a gap in the literature by explicitly analyzing the determinants of the legal structure in startups in light of economic freedom. Institutional factors do not work in isolation; therefore, the authors also employ traditional entrepreneur-specific variables that affect the choice of legal structure in addition to the institutional framework.

Procurement planning as a strategic tool for public procurement effectiveness: Experience from selected public procuring entities in Dodoma city, Tanzania

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ismail Abdi Changalima ◽  
Gift Onesmo Mushi ◽  
Shadrack Samwel Mwaiseje
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Public Procurement ◽  
Binary Logistic Regression ◽  
Binary Logistic Regression Model ◽  
Cross Sectional ◽  
Content Type ◽  
Survival And Development ◽  
Procurement Planning

Purpose The significance of the public procurement function is on the survival and development of procuring entities and that of a nation at large. This study aims to focus on examining the influence of procurement planning on the effectiveness of public procurement, experience from selected public procuring entities in Dodoma city, Tanzania. Design/methodology/approach A cross-sectional design was adopted from which data were collected from 146 respondents who were purposively chosen from several public procuring entities located at Dodoma city in the United Republic of Tanzania by using a survey structured questionnaire and analysed through a binary logistic regression model. Findings Findings revealed that procurement planning as a strategic function significantly influences the effectiveness of public procurement. The binary logistic regression model included the implementation of prepared procurement plans (p = 0.039), the involvement of users as stakeholders and important institutional actors in public procurement (p = 0.033), compliance to procurement laws and regulations when planning (p = 0.016) and adequacy of budget (p = 0.042) as predictors of procurement planning were tested to be significantly related to the effectiveness of public procurement. It was concluded that public procuring entities can achieve public procurement effectiveness through procurement planning. Social implications The implications and policy recommendations of the findings of this study would be useful to procurement practitioners mostly in public procuring entities. Originality/value This study contributes to adding knowledge to the existing body of knowledge on procurement planning as an imperative activity in public procurement in Tanzania.

Factors determining child mortality in Uganda

2017 ◽  
Vol 44 (5) ◽  
pp. 633-642 ◽  
Author(s):  
Will Kaberuka ◽  
Alex Mugarura ◽  
Javan Tindyebwa ◽  
Debra S. Bishop
Keyword(s):  
Health Care ◽  
Logistic Regression ◽  
Birth Weight ◽  
Regression Model ◽  
Marital Status ◽  
Birth Order ◽  
Child Mortality ◽  
Logistic Regression Model ◽  
Household Wealth ◽  
Content Type

Purpose The purpose of this paper is to establish socio-economic factors and maternal practices that determine child mortality in Uganda. Design/methodology/approach The paper examines the role of sex, birth weight, birth order and duration of breastfeeding of a child; age, marital status and education of the mother; and household wealth in determining child mortality. The study employs a logistic regression model to establish which of the factors significantly impacts child mortality in Uganda. Findings The study established that education level, age and marital status of the mother as well as household wealth significantly impact child mortality. Also important are the sex, birth weight, birth order and breastfeeding duration. Research limitations/implications Policies aimed at promoting breastfeeding and education of female children can make a significant contribution to the reduction of child mortality in Uganda. Practical implications Health care intervention programs should focus on single, poor and uneducated mothers as their children are at great risk due to poor and inadequate health care utilization. Originality/value This paper could be the first effort in examining child mortality status in Uganda using a logistic regression model.

scholarly journals Modeling and Analyzing the Factors Affecting the Mortality of Pedestrians in Urban Accidents

2018 ◽  
Vol 14 (4) ◽  
pp. 10-21
Author(s):  
Ahmet Tortum ◽  
Alireza Motamadnia
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Motor Vehicle ◽  
Binary Logistic Regression ◽  
Education Level ◽  
Road Surface ◽  
Binary Logistic Regression Model ◽  
Factors Affecting ◽  
Surface Conditions

Abstract The nature of urban and rural accidents has been different from each other in some of the factors and even the severity of damage rate, mayhem, and death. In this research, using statistical methods and binary logistic regression model, we have addressed to analyze important parameters such as age, gender, education level, the color of the pedestrian dress, season of accident, time of accident, the speed of the vehicle colliding with pedestrians and road surface conditions at the time of accident on the way of death (at the scene of the incident or in the hospital) pedestrians who have been traumatized. After the creation of the binary logistic regression model, it was determined that only the parameters of speed and the accident time have been significant in the level less than 5%. And other parameters such as age, gender, the season of accident occurrence, the color of the pedestrian dress, road surface conditions and education level had no significant effect in terms of statistical on the incidence of mortality arising from a pedestrian accident with the motor vehicle. The results revealed that by adopting decisions related to the traffic calming, attention to passages lighting and brightness the mortality rate of a pedestrian due to the urban accidents can be reduced.

scholarly journals Effects of the Agri-environmental Program Implemented in Sultan Reeds Area of Kayseri, Turkey

2019 ◽  
Vol 7 (12) ◽  
Author(s):  
Ismet Boz
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Agricultural Practices ◽  
Farm Size ◽  
Chi Square ◽  
Factors Affecting ◽  
Environmental Program ◽  
Chi Square Test ◽  
Sustainable Agricultural Practices

This study was initiated to evaluate the effects of agri-environment program implemented in the Sultan reeds area of Kayseri province, Turkey. The specific objectives of the study were to compare the farmers who enrolled in the program with those who didn’t enroll regarding their application of different sustainable agricultural practices, and to determine factors affecting their enrolment in the program. The main comparative indicators were selected from different sustainable agricultural practices either promoted by the agri-environmental program or not promoted but considered very useful for the locality. Two stratified samples of farmers (enrolled and not enrolled) were selected based on their farm size. Chi-square tests of independence were used to compare farmers on the selected sustainable agricultural practices. Logistic regression model was used to determine factors affecting the enrolment of the agri-environment program. The findings of the chi-square test showed that enrolled farmers use grow more forage legumes, are more conscious about pesticides use and chemical applications, and they use more pressurized irrigation systems. Findings of the logistic regression model sowed that using rental land negatively, but contacts with extension personnel, and using long term loans for farming investments positively influenced the enrolment of the agri-environment program. Governmental effort must concentrate on these issues when promoting agri-environmental programs in the region.

scholarly journals Negative Impact of Amphetamine-Type Stimulant Use on Opioid Agonist Treatment Retention in Ontario, Canada

2021 ◽  
Vol 12 ◽  
Author(s):  
Kristen A. Morin ◽  
Frank Vojtesek ◽  
Shreedhar Acharya ◽  
David C. Marsh
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Drug Screening ◽  
Urban Areas ◽  
Logistic Regression Model ◽  
Opioid Agonist ◽  
Stimulant Use ◽  
Urine Drug ◽  
The Impact ◽  
Urine Drug Screening

Objective: The objective of this study was to evaluate epidemiological trends of co-use patterns of amphetamine-type stimulants and opioids and the impact of co-use patterns on Opioid Agonist Treatment (OAT) retention in Ontario, Canada. The secondary objective was to assess geographical variation in amphetamine-type stimulant use in Northern Rural, Northern Urban, Southern Rural and Southern Urban Areas of Ontario.Methods: A retrospective cohort study on 32,674 adults receiving OAT from ~70 clinics was conducted between January 1, 2014, and December 31, 2020, in Ontario, Canada. Patients were divided into four groups base on the proportion of positive urine drug screening results for amphetamine-type stimulants during treatment: group 1 (0–25%), group 2 (25–50%), group 3 (50–75%), and groups 4 (75–100%). A Fractional logistic regression model was used to evaluate differences over time in amphetamine-type stimulant use with urine drug screening results. A Cox Proportional Hazard Ratio model was used to calculate the impact of amphetamine-type stimulant use on retention in OAT and adjusted for sociodemographic characteristics, drug use and clinical factors. Lastly, a logistic regression model was used on a subgroup of patients to assess the impact of geography on amphetamine-type stimulant use in Northern Rural, Northern Urban, Southern Rural and Southern Urban Areas of Ontario.Results: There were significant differences in amphetamine-type stimulant positive urine drug screening results year-over-year from 2015 to 2020. Significant differences were observed between amphetamine-type stimulant groups with regards to sociodemographic, clinical and drug use factors. Compared to those with no amphetamine-type stimulant use, the number of days retained in OAT treatment for amphetamine-type stimulant users was reduced (hazard ratio 1.19; 95% confidence interval = 1.07–1.17; p &lt; 0.001). Lastly, an adjusted logistic regression model showed a significant increase in the likelihood of amphetamine-type stimulant use in Northern Rural regions compared to Southern Urban areas.Conclusion: There was a significant increase in amphetamine-type stimulant use among individuals in OAT from 2014 to 2020, associated with decreased OAT retention. Research is required to determine if tailored strategies specific to individuals in OAT who use amphetamine-type stimulants can improve OAT outcomes.

Adoption of rural bank credit programs among smallholder farmers in Ghana: an average treatment effect estimation of rates of exposure and adoption and their determinants

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Arnold Missiame ◽  
Patrick Irungu ◽  
Rose Adhiambo Nyikal ◽  
Grace Darko Appiah-Kubi
Keyword(s):  
Treatment Effect ◽  
Smallholder Farmers ◽  
Household Head ◽  
Sampling Technique ◽  
Average Treatment Effect ◽  
Bank Credit ◽  
Content Type ◽  
Average Treatment ◽  
Credit Programs ◽  
Effect Estimation

PurposeThe study aims to estimate the rates of exposure to, and adoption of, rural bank credit programs by smallholder farmers in rural Ghana and the factors responsible for those rates.Design/methodology/approachThe study used a random sample of 300 smallholder farmers in the Fanteakwa District of Ghana, obtained through the multistage sampling technique. The study also employed the average treatment effects approach to estimate the average treatment effect of farmers’ exposure to rural bank credit programs, on their adoption of such programs.FindingsThe actual adoption rate is approximately 41%, and the potential, conditional on the whole population being aware of rural bank credit programs, is approximately 61%. Accordingly, there is a gap of about 20% in the adoption of rural bank credit programs, and is due to the incomplete exposure of smallholder farmers to the rural bank credit programs. Age of the household head, access to extension services, membership in farmer-based organizations and active savings accounts with a rural bank are the major contributors to smallholder farmer exposure to and the adoption of rural bank credit programs.Originality/valueThe current study is the first of its kind to be conducted in Ghana on rural bank credit programs. It takes into account the extent to which smallholder farmers are exposed to such credit programs and how it influences their decisions to access or adopt.

Sign in / Sign up

Export Citation Format

Share Document