Binary Logit Regression Research Articles

The built environment and overweight in Shanghai: Examining differences in urban and rural contexts

Overweight is a serious threat to public health. Although many studies have examined the association of the built environment with overweight, it remains unclear whether the relationship varies by urban and rural contexts. This study applied binary logit regression models to explore how the built environment was associated with overweight, using a sample of 1350 adults from urban (the built-up area) and rural (Chongming Island) areas in Shanghai. The results show that mixed land use and fewer supermarkets are positively related to overweight in both urban and rural areas. Higher road density has a negative association with overweight in urban areas, but is not significantly related to overweight in rural areas. We conclude that associations of the built environment with overweight differ in urban and rural contexts.

EFFECT OF SOCIAL CAPITAL ON THE HEALTH STATUS OF RURAL FARMERS IN GWER-EAST LOCAL GOVERNMENT AREA, BENUE STATE, NIGERIA

The study examined the effect of social capital on the health status of rural farmers in Gwer East local government area of Benue State, Nigeria. Multi-stage sampling technique was used to select a total of 120 respondents. Data were collected through the use of a well-structured questionnaire and analyzed using descriptive statistics, social capital index, the index was estimated from the different forms of social capital constructed and WHO self-assessment scale for health status. Also, Binary Logit regression model was used. Results showed that the farmers were still young with an average age of 41 years old. Most of the respondents (68.33%) were married and more than half, (60.83%) were males. The social network of the respondents showed that the density of membership with mean of 1.43, average meeting attendance 44.83%, cash contribution with mean of N36,103.33, labour contribution with mean of 7.86, participation in decision making with mean of 34%, heterogeneity index with mean of 44%, social capital index with mean of 0.31. The health status of the respondents showed that majority (41.67%) were in very good health status. The regression Pseudo R2 value of 0.5733 indicates that the variables included in the model explained 57% of the dependent variable. The result revealed that social capital increases the probability of household head being healthy. Also, gender, household size, farming experience, and age significantly influenced health status of the respondents. Given the close linkages between self-rated health and social capital in this study, the study, therefore, concluded that, social capital positively and significantly influences health status in the study area.

Determinants of Tomato Farmers Participation in Agricultural Services and Training Centre (ASTC) Activities

Agricultural production have remained rudimentary despite many years’ of technology development and transfer; to reverse this declining trend, several agricultural policies and programmes aimed at ensuring sustainable production, improved income and farm expansion with added value output have become very germane. This study therefore analyzed tomato farmers’ participation in ASTC activities in Jos-south local Government Area of Plateau state, Nigeria. This study adopted multi stage sampling techniques. Primary was data collected from 80 respondents, during the 2017/2018 farming season and were analyzed using descriptive statistics, participation index, weighted average index analysis and Binary Logit regression. The result of the study revealed that 73.8% were male; 88.75% had access to extension contact. The estimated mean for educational training, household size, farm income and farming experience were 6 years; 8 people; ₦108,500/ha and 12 years respectively. Also, most (68.7%) of the farmers have low participation index of ≤0.45; this trend is responsible for the existing low farm productivity of this crop in the area. Furthermore, the benefits derived from participating in ASTC activities among the respondents were significant as indicated by their weighted average index. In addition, the estimated coefficient of multiple determination (R2) was 0.7602. Also, the coefficients of household size (0.421), education (0.559), experience (0.808), income (0.485) and extension contact (0.376) were statistically significant; implying that these factors in the regression model affected the likelihood of farmer’s decision to participate in ASTC activities. Adequate labour supply; establishment of pilot farms; capacity training; access to agricultural credit, extension services, agro service centres, agricultural information, input supply and cooperative formation are strongly recommended.

STUDY ON THE INFLUENCE OF RESIDENTS' INTELLIGENT DEMAND RESPONSE WILLINGNESS AND EMOTIONAL BEHAVIOR CHANGE BASED ON BINARY LOGIT REGRESSION MODEL

Abstract Background Residential power consumption is the main component of power consumption in China. With the rapid development of China's power industry and the continuous improvement of residents' living standards, residents' power consumption has increased significantly. With the construction of smart grid, the further development of Internet of things and artificial intelligence technology in China, and the further popularization of smart appliances, the intelligent power consumption environment of residents will be gradually improved, and their power consumption will break through the limitations of time and space. Through the application of refined power information and intelligent control in smart appliances, residents will be more flexible in the choice of using appliances. With the continuous popularization of power construction, the change of regional emotional behavior is particularly significant when residents promote smart appliances. Research Objects and Methods Study the influence mechanism of residents' psychological willingness to participate in demand response, convert residents' psychological willingness to participate in demand response into binary variables, and use binary logit regression model to analyze the influencing factors of psychological willingness such as personal statistical factors, social factors and social factors, consumption concept reflected by mobile phone use preference, and residents' use of rice cooker and washing machine, The demand for air conditioners and electric vehicles responds to the payment of electricity bills. This study also uses the method of questionnaire to investigate the emotional micro behavior of intelligent power consumption in various countries and regions. Using atq-30 and atq-100 to evaluate the thinking related to intelligent power consumption and depression, but atq-30 has less content and short time, so it is better than atq-100 Atq-30 can be used as a screening tool. On the one hand, it is highly correlated with the self rating Depression Scale (especially BDI), on the other hand, it has a wide range of application. Unlike the Attributive Style Questionnaire (ASQ) and cognitive bias questionnaire, it is not limited to specific groups or specific social backgrounds. However, it is worth noting that although atq allows subjects to recall their thoughts in the recent week, this retrospective self-evaluation can not completely and truly directly reflect the evaluation of self cognition. Results The higher the proportion of residents' income and the higher the frequency of electricity consumption, the stronger the psychological willingness of residents to demand fried rice; The higher the residents' psychological response to the demand for cooking electricity, they prefer to use the built-in electric gas vehicle intelligent control program for charging response when charging the electric vehicle, while other factors have no significant impact on whether residents use the electric vehicle intelligent program for charging response. For residents who like to use free mobile data, they are more willing to adjust air conditioning temperature and respond to power demand; Among them, the tendency to use free traffic behavior shows that users will encounter large sustainable consumption decisions and pay more attention to cost saving, so they are more willing to adjust the air conditioning temperature to save electricity. Age has a significant impact on Residents' willingness to respond to the power demand of washing machines, while older young people are more likely to respond to the power demand of washing machines. There was significant difference in the total score of as between residents who used smart appliances or not (P < 0.05), that is, residents who tended to use smart appliances had better psychological elasticity; The total score of SCL-90 is only different in willingness. Conclusion The research results can provide policy guidance and reference for guiding residents' energy-saving demand response, and enrich the research on Residents' psychological will or power demand response behavior choice. The research of this paper provides a certain policy reference value for power grid enterprises and power saving management departments. In short, we should give full play to the important role of irrational factors in power construction elements, actively pay attention to the changes of residents' psychology, emotion and behavior and their impact on power consumption and power consumption mode, and be a good builder, manager, coordinator and collaborator of design mode. According to the psychological characteristics of these groups, actively and flexibly organize rich and colorful activities, strive to create a relaxed and harmonious living atmosphere, create a friendly and mutual aid social atmosphere, and promote their good cognition and healthy development of life. Acknowledgments Supported by National Natural Science Foundation of China (Grant No. 72071077), Beijing Social Science Foundation under Grant (Grant No. 19GLB024), and the Fundamental Research Funds for the Central Universities (Grant No. 2020FR001).

Impact of Entrepreneurship Development on Employment Generation in SabonGari Local Government, Kaduna State

Purpose: The purpose of the study is to examine the effect of entrepreneurship development on job creation with primary data inputs drawn from Sabon Gari Local Government Area, Kaduna State Nigeria.
 Methodology: Two forms of entrepreneurship- innovative and replicative are considered with a view to contributing to the debate through the lens of binary logit regression analysis. A sample of 331 entrepreneurs were selected using simple random sampling technique and were analyzed using descriptive statistics and binary logit regression.
 Findings: Despite the role of entrepreneurship towards job creation in a developing country like Nigeria, youth unemployment remains high as at 55.4% in the third quarter of 2018. The literature on the entrepreneurship-employment nexus is scanty primarily due to data limitations and lack of appropriate quantifiable measures of entrepreneurship. The result showed that about 79.7% of the sampled entrepreneurs have employed one or more persons; suggesting that entrepreneurship development has led to a reduction in unemployment. The result also shows that innovation, education and start-up capital exert a positive and significant impact on enterprise development.
 Unique Contribution to Theory, Practice and Policy: The results highlight the need for sustained efforts by government and non-government institutions towards developing entrepreneurship programs in order to create jobs and attain inclusive growth.

Factors Affecting Climate-Smart Agriculture Practice Adaptation of Farming Households in Coastal Central Vietnam: The Case of Ninh Thuan Province

Agriculture is a sector with a long tradition and an important contribution to economic growth in Vietnam, providing food security and generating revenue for the country's exports. However, agricultural activities in Vietnam are significantly affected by climate change. In Vietnam, the central coastal area in general and Ninh Thuan province in particular are the most vulnerable areas to natural disasters. In that context, climate-smart agriculture (CSA) is a good strategy to help local famers coping with climate change while securing food security. This study has two main objectives: to assess farmers' awareness on disasters and to analyze factors affecting the decision to apply CSA practices of farming households in Ninh Thuan. The study conducted focus group discussion, in-depth interview and survey of 436 households in 3 districts of Ninh Thuan to collect data. Research results showed that local farmers have a high awareness of natural disasters trends and impacts on agricultural livelihoods. Facing with disasters in the context of climate change, farming households have applied some models of CSA such as minimal tillage, intercropping, crop rotation, crop transformation, and the use of plant varieties. Binary logit regression analysis indicated that age, education level, household income, membership of local associations, training attendance, and support policies were variables significantly influencing the farmers' decision to apply CSA. Challenges for CSA adoption include lack of capital, information, technical support and land ownership institutions in Vietnam. The study also made recommendations to promote CSA in Vietnam, including reforming the legal system, strengthening agricultural extension services, and providing technical and capital support to farmers.

Perceptions, Profitability and Determinants of Granulated Cassava Packaging in Kumasi Metropolis, Ghana

Packaging does not only protect a product but also provides directions for using the product, as well as relevant information about its content and nutritional value. This study was undertaken to assess Granulated Cassava (Gari) sellers’ perception, profitability and determinants of packaging in Ashanti Region. The study area was purposively selected because of the active participation and contribution of marketing activities. A structured questionnaire was administered in the form of interview to obtain primary data from the respondents. Data was generated using binary and multinomial logit regression model and Garret ranking technique. The results showed that there is 0.11% difference in the gross margin of both ventures which is also statistically significant at 1%. Years of education, legal requirement, and durability of the packaging material and cost of packaging material were the significant factors that influence sellers’ choice of packaging. Lack of technical know-how, cost of capital equipment and lack of knowledge on packaging equipment and/or material were the most limiting constraints affecting Gari packaging. The study recommends that investors should invest in the Gari packaging business since it has a relatively higher rate of returns as compared to the unpackaged one.

UNMET MEDICAL CARE NEEDS DUE TO PAYMENT DIFFICULTY

Objective: This study aims to determine the effects of chronic diseases and socio-economic factors on payment difficulty in medical care.
 Methods: The variables used in the analysis were obtained from the “2016 TURKSTAT Health Survey” micro data set. Three models were established to determine the degree of chronic disease data and socio-economic variables affecting the payment difficulty in medical care. Binary Logit Regression analysis was used to analyze the models.
 Findings: In terms of payment difficulty in medical care; age, education, household income, social security institution (SGK) treatment cost, general health insurance (GSS) treatment cost, other treatment cost, reason for not working, work continuity, working method, overall health status, being sick longer than 6 months, vital activity restriction, asthma, bronchitis, coronary heart failure, arthrosis, waist and neck disorders, allergy, liver failure, kidney disease, depression, other chronic diseases, wearing glasses, physical pain state, pain preventing life, feeling worthless, receiving bed service for the last 12 months, receiving daily service for the last 12 months, drug use by his own decision, cholesterol measurement status, blood glucose measurement status, stool occult blood test measurement status, being late for appointment, payment difficulty in dental care, in drug and in spiritual treatment, tobacco use status and exposure to tobacco smoke were effective (p 0,8).
 Conclusions: According to the results of the research, it was determined that chronic diseases and socio-economic variables are effective in the payment difficulty of medical care. Policymakers can benefit from evidence-based on econometric models of the comparative burden of different chronic conditions, demographic and economic structure.

Does Retirement Make People Happier?-Evidence From China.

To investigate whether people's happiness will increase after retirement, this paper empirically investigates 2012, 2015, and 2017 China General Social Survey (CGSS) data using Ordinary Least Squares, Binary logit, and Fuzzy regression discontinuity Design. The results all show that retirement will significantly increase the happiness of men in urban China. The paper also validates these findings by testing the continuity of the reference and covariates at the cut–off point, changing the model settings, and using a more rigorous sample classification method. In addition, the article further analyzes the heterogeneity of the study and finds that retirement brings more happiness to those who have a college degree or less and have multiple children. The better the health status, the smaller the effect of retirement on happiness. The more social interactions, the smaller the effect of retirement on happiness. The policy implication of this paper is that when implementing a delayed retirement policy, special care should be taken for groups with greater welfare impairment, and it needs to be introduced together with other supporting measures to reduce people's worries. This paper analyzes the relationship between retirement and happiness in China and makes suggestions for the implementation of a delayed retirement policy, enriching the theoretical and empirical work on the effects of retirement on people's happiness and contributing to the world's response to aging and welfare policies for the older person.

Influence of Meru CBEF Membership Capacity in Executing Their Role on Public Participation

Establishment of the CBEF at the county level via the Public Finance Management Act (PFMA) 2012 was designed to increase public involvement in the financial management of the county. The study was anchored under elite mass stakeholder theory. The study employed a descriptive survey with a target population of 76 respondents consisting of 21 members of CBEF and 55 representatives of various groups. A sample size of 69 respondents was selected through purposive sampling for the CBEF members and a simple random sampling for the representatives, the study used questionnaire for data collection which were administered to the participants by the researcher. The collected data was coded; analyzed using a SPSS software inferential statistics were presented in frequencies, tables and figures while descriptive statistics was presented in Mean and standard deviation, a binary logit regression model was suitable to establish the relationship between the study variables. The study stablished that there was a balanced representation in the formation of the Forum with a good balancing between the county executive and non-state representatives with 51.61% being county executive representatives and 48.39% were non- state representatives. The study revealed that an increase in representation can increase the chances of public participation in the budget making process by 2.812 times (Odds Ratio = 2.812). The study concluded that members of the Meru CBEF are involved in county budget making process, and this may have enhanced the public participation since their representatives are given a voice in the process of budget making. The study recommends that the county government of Meru to take in to account the various parameter of public participation in this study for implementation to enhance public participation in budget making process.

Lane-Level Regional Risk Prediction of Mainline at Freeway Diverge Area.

Real-time regional risk prediction can play a crucial role in preventing traffic accidents. Thus, this study established a lane-level real-time regional risk prediction model. Based on observed data, the least squares-support vector machines (LS-SVM) algorithm was used to identify each lane region of the mainline, and the initial traffic parameters and surrogate safety measures (SSMs) were extracted and aggregated. The negative samples that characterized normal traffic and the positive samples that characterized regional risk were identified. Mutual information (MI) was used to determine the information gain of various feature variables in the samples, and the key feature variables affecting the regional conditions were tested and screened by means of binary logit regression analysis. Upon screening the variables and corresponding labels, the construction and verification of a lane-level regional risk prediction model was completed using the catastrophe theory. The results showed that lane difference is an important parameter to reduce the uncertainty of regional risk, and its odds ratio (OR) was 16.30 at the 95% confidence level. The 10%-quantile modified time to collision (MTTC) inverse, the speed difference between lanes, and 10%-quantile headway (DHW) had an obvious influence on regional status. The model achieved an overall accuracy of 86.50%, predicting 84.78% of regional risks with a false positive rate of 13.37% and 86.63% of normal traffic with a false positive rate of 15.22%. The proposed model can provide a basis for formulating individualized active traffic control strategies for different lanes.

Do Female CFOs Reduce Disclosure Violations in Listed Companies? Empirical evidence from China's capital market

Abstract This paper selects the data of China's listed companies from 2007 to 2016 as the sample and uses the binary logit regression method to explore whether the gender of the CFO has an impact on the company's information disclosure violations. The results show that female CFOs significantly reduce the probability and number of information disclosure violations of listed companies, and the stronger their own ability, female CFOs have a significant incremental impact on restraining information disclosure violations of listed companies. The research conclusion provides a reference for enterprises to select and hire CFOs. JEL classification numbers: G34, M4. Keywords: CFO, Female executives, Violation of information disclosure.

Pakistan's solar mission: Do solar finance and subsidy remove the barriers to solar installations?

This work investigates the impact of solar finance and solar subsidy in removing the barriers to solar installations among households (on-grid and off-grid), the agriculture sector, and small and medium enterprises (SMEs) in Pakistan. This study used step-wise parametric and non-parametric approaches to identify and analyze the nature, grouping, and classification of barriers in the three sectors. First, binary logit regression results confirm that amongst the economic factors, solar finance, solar subsidy, finance lending, solar pay-off periods, consumer wealth, and monthly electricity expenses significantly (positively) related to the solar installations. Second, ranking analysis results reveal that solar finance and solar subsidy significantly lower the barriers to solar installations among the agriculture sector and SMEs as they face only 6 and 8 out of 23 barriers, respectively. Third, the results of factor analysis grouped 16 common critical barriers into five components: 1) economic barriers, 2) green energy policy-related barriers, 3) technological barriers, 4) information and human resource-related barriers, and 5) social barriers. Finally, we used MICMAC analysis to classify critical barriers to each sector based on their driving and dependence power. By doing so, this study comprehensively sheds light on the interrelations of barriers across three sectors and provides practical solutions to meet SDG 7 in developing countries.

The survival of bike-sharing startups in China: an empirical analysis of the influencing factors

PurposeBike-sharing is popular worldwide, and it has led to a new development direction in green transportation. However, the collapse of many bike-sharing startups and residual social problems has brought about contradictions and challenges to the development of the industry. The purpose of this paper is to determine how internal factors affect the survival of bike-sharing startups.Design/methodology/approachThe authors used binary logit regression as the measurement model to conduct an empirical analysis based on 137 bike-sharing startups in China. The study focuses on using traditional theoretical evidence and considers the uniqueness of the industry to jointly explore the survival factors that influence the emerging business model of bike-sharing.FindingsThe results show that entrepreneurial team size and differentiation strategy positively influence survival. Founder-CEOs have a negative impact on survival. Founders' entrepreneurial experience and venture capital have no significant influence on survival.Originality/valueThe results verify the role of traditional survival factors in the new business model of sharing economy and fill the research gap on the survival strategy of startups. This study offers a unique perspective for researchers to better understand the sharing economy industry and provides practical guidance for entrepreneurs and investors to enter the market.

The effect of financial inclusion on open defecation and sharing of toilet facilities among households in Ghana.

Globally, and in Ghana, a lot of people do practice open defecation as well as share toilet facilities with other households. Meanwhile, open defecation in particular, is associated with numerous negative health and economic effects. To this end, a number of empirical studies have been conducted on the determinants of access to sanitation facilities among households in Ghana. Nonetheless, while financial inclusion (sustainable ways of ensuring easier accessibility to cheap and useful financial products and services among individuals/firms) can enhance the ability of households or individuals to afford toilet facilities, hence, could help in curbing open defecation and sharing of toilet facilities among households, the previous studies on Ghana did not pay attention to it. This study therefore uses data from the 7th round of the Ghana Living Standards Survey (GLSS7) to examine the association of financial inclusion with open defecation and sharing of toilet facilities among households in Ghana. The binary logit regression is used as the empirical estimation technique. The results show that, financial inclusion in general is associated with lesser likelihood of open defecation and sharing of toilet facilities among households in Ghana after controlling for welfare quintile, urban or rural residence and other covariates. Moreover, while informal financial inclusion is statistically insignificant, formal financial inclusion is found to be associated with reduced open defecation and sharing of toilet facilities among households. Thus, in the attempt to eliminate open defecation as well as reduce the sharing of toilet facilities among households in Ghana, conscious efforts should be devoted towards enhancing formal financial inclusion.

PARENTAL PREDISPOSITION TO EDUCATION INFLUENCING FEMALE ENROLMENT IN ENGINEERING AND TECHNOLOGY IN ANGLO-SAXON STATE UNIVERSITIES IN CAMEROON

Parental predisposition to education extends beyond the engagement with schools to the home life, and the expectations of values for education that are communicated directly or indirectly to children. The objective of this study is to assess the influence of parental predispositions to education on female enrolment in Engineering and Technology programmes in the Anglo-Saxon state universities of Cameroon. The study used an explanatory sequential mixed method research design, and a multi-stage sampling technique was used to randomly select 276 respondents from the universities of Bamenda and Buea. Both quantitative and qualitative data were collected using structured questionnaires and interview schedules with 10 parents whose children are admitted to engineering and technology programs in these English-speaking state universities. Content analysis was used to analyse the qualitative data. Descriptive statistics, point biserial and binary logit regression analysis were used to analyse the quantitative data and to test the hypothesis at p<.05 level of significance. The findings revealed that parental predisposition to education correlates significantly to students’ enrolment in engineering and technology. The null hypothesis was rejected and it was recommended that parents should engage prominently in children’s education through the provision of support both at home and in school.<p> </p><p><strong> Article visualizations:</strong></p><p><img src="/-counters-/edu_01/0919/a.php" alt="Hit counter" /></p>

Employment Status during the COVID-19 Pandemic: Evidence from Ethiopia.

Since the beginning of the year 2020, the world has been suffering from an unprecedented situation due to the Corona Virus Disease (COVID-19). The negative impact of COVID-19 is one of the worrisome issues across the globe. Among others, employment is one area affected during the COVID-19, which requires considerable scientific studies to identify factors affecting employment status throughout the disease crisis. Therefore, this study has mainly aimed to investigate the factors affecting the employment status during the COVID-19 pandemic in Ethiopia, taking a total of 2,396 respondents who had jobs before the COVID-19 outbreak. To achieve the stated objectives, the study has employed a binary logit regression model considering the employment status of respondents who lost their job (unemployed) and who secured their job (employed) during the pandemic. The model result indicates that females were more likely to be unemployed than males, persons living in a rural area were more likely to be unemployed than persons living in an urban area, and persons engaged in industry, service, and trade were more likely to be unemployed than people engaged in agriculture during the pandemic. Furthermore, during the pandemic, people living in the capital city of Ethiopia (Addis Ababa) were more likely to be unemployed compared to people living in the other regions of the country. Finally, based on these findings, critical recommendations were forwarded to the government and policymakers for their intervention.

Factors Affecting Loan Repayment Performance of Smallholder Farmers: The Case of Microfinance Institutions in Toke Kutaye District, West Shoa Zone, Ethiopia

The main purpose of this study was to identify the factors determining loan repayment performance of smallholder farmers; and to evaluate the based performance of the Microfinance Institutions operating in Toke Kutaye district. Primary data were collected using structured questionnaires from 122 randomly selected smallholder farmer clients. Secondary data were obtained from the annual reports and financial statements of the Microfinance Institutions. The data were analyzed using descriptive statistics and binary logit regression models. The results of the descriptive analysis revealed a significant mean difference between the defaulter and non-defaulter households in terms of total annual farm income, expense on social ceremonies, livestock units, and distance from credit sources. Although the repayment status in the study area was insignificant, there was a variation among institutions where the numbers of non-defaulters decline from Oromia Credit and Saving Share Company, Vision Fund Microfinance and Eshet Microfinance successively along with ratio statistics result. The logit model revealed that age, education level, tropical livestock unit, participation in off-farm activities, repayment period suitability, and sex found to be have positive effects whereas expense on social ceremony, family size, loan diversion found to have negative effects on loan repayment performance of the smallholder farmers. Our findings suggest, in order minimizing loan defaults in the study area, microfinance institutions, non-governmental organizations and policy makers have to effectively work on improving the constraining factors. Keywords: Binary Logit; Customers: Defaulters, Loan repayment; Smallholder farmers DOI: 10.7176/JESD/13-3-04 Publication date: February 28 th 2022

Woman labor force participation in off-farm activities and its determinants in Afar Regional State, Northeast Ethiopia

Women have driven economic development around the globe through higher returns on human capital and education. However, woman’s involvement in labor market was weak over time, generally in Ethiopia and particularly in Afar region. Therefore, this study intended to identify and analyze the determinants of woman’s participation decisions in off-farm activities. The data was collected from 473 sampled women using a multistage sampling technique. Both descriptive and logistic regression model was employed to analyze the determinants of woman participated decision in off-farm activities. Descriptive statistics revealed that, from the total sample, 270 (57.08%) of woman have participated in an off-farm activity, while, 203 (42.92%) of them do not participate. Whereas, the binary logit regression result that woman level of education and dependency ratio was positively and significantly determine woman labor force participation decision; however, a woman who had children less than five years aged, nonfarm training, distance to the market, woman marital status, access to credit, ownership of livestock and safety net adversely affected the participation decision of woman on off-farm activities. This study was recommended that: special attention for woman educational development, adopted family planning and parental benefits, provide and properly follow up nonfarm training, developed marketplace nearby, provide credit for only productive activities, create awareness about off-farm activities in addition to livestock husbandry (mixed-farming), and provide safety net for only eligible woman.

Assessing emerging beef farmers participation in high-value market and its impact on cattle sales in South Africa

The participation of emerging farmers in high-value agricultural markets in South Africa cannot be over-emphasized. It is one of the objectives of the government to assist emerging farmers with the necessary resources and programmes to enable them to meet the requirements and participate in high-value markets. The study investigated the impact of participation in the high-value market on cattle production (cattle sold). A systematic random probabilistic sampling technique was used to obtain a sample of 55 emerging beef farmers. Interviews were undertaken using questionnaires to collect data. Descriptive statistics and econometric methods such as Tobit model and a treatment effect model using propensity score matching estimator were employed for the data analysis. The results of binary logit regression from the PSM revealed that participation in a high-value market was significantly affected by age, household size, years of farming and difficulty accessing a high-value market. The average treatment effect of the treated showed a negative impact and decreases the number of cattle sold by 58%. The recommendations informed by the findings from the study are that youth in the study area should be involved in beef farming, appropriate training should be given to the farmers and farmer's advisor should motivate farmers to sell more cattle and participate in a high-value market, and educate them about the requirements to participate in the high value markets. The DARD lease assistance should continue and include the lease of more land. Int. J. Agril. Res. Innov. Tech. 11(2): 27-36, Dec 2021