Education Level Of Household Head Research Articles

The rich-poor divide: Unravelling the spatial complexities and determinants of wealth inequality in India

This study presents the first in-depth analysis of spatial differences and factors influencing wealth distribution among households in India. It uses data from the latest National Family Health Survey, covering 707 districts. Techniques like the Lorenz curve, Gini coefficient, Location Quotient, Morans statistics, and Univariate and Bivariate LISA methods explore inequalities, concentration, and clustering patterns of rich-poor households at the district level. Additionally, spatial regression models such as OLS, GWR, and MGWR help to uncover spatial disparities and variability. Our findings demonstrate significant regional disparities, with the affluent household concentration being notably higher in north-western and southern India, while central, eastern, and northeastern regions exhibit greater inequality. Key factors impacting wealth inequality include rurality, low female literacy rates, educational level of household heads and prevalence of Scheduled Castes/Tribes. This study highlights the spatial dimensions of wealth inequality and provides a nuanced understanding of the factors contributing to these patterns. The GWR and MGWR models prove most effective, explaining more than 90% of the variation in wealth distribution factors. This study sheds light on the spatial dynamics and factors behind wealth disparities in India, offering strategic insights for equitable growth initiatives targeting diverse socio-economic sectors.

Differential impacts of electricity access on educational outcomes: Evidence from Uganda

We investigate the differential impact of electricity access on educational outcomes in Uganda using the Uganda National Panel Survey data and employ instrumental panel probit techniques. The findings indicate that reliable electricity is associated with high school enrolment and completion. Also, the results show that education level of household head, marital status, gender, and good housing conditions are associated with better education outcomes. Our results provide evidence for designing supportive policies for increased access to reliable electricity especially among rural households where there are high disproportionately lower education outcomes. Also, the results suggest that policies to eliminate all barriers to reliable electricity access can greatly enhance educational outcomes in Uganda.

Research on farmers' adoption of additional technology combinations: Practice from Chongqing, China.

Tobacco farmers often adopt additional multiple agricultural technologies (AMATs) in addition to implementing the standardized technical system in China. Based on the cross-sectional micro data of 346 households of Chongqing, China, this paper assesses the determinants and impacts of the adoption of AMATs on income by using a multinomial endogenous treatment effects model to correct for selection bias and endogeneity caused by observed and unobserved heterogeneity. The results show that (1) the adoption of combinations of AMATs is determined by the household head's education level, experience in tobacco growing, the shortest distance to nearby town, the amount of technical training, the ratio of land available for mechanical cultivation to tobacco land, the distance to extension station, and the ratio of leased land. (2) The adoption of combinations of AMATs has heterogeneous effects on farmers' income through yield and quality improvement. (3) The comprehensive combination of AMATs is not necessarily the best option for farmers. Due to the interaction between technologies such as complementary, substitute or supplementary effects, the moderate implementation of fertilizers and soil improvement is the most effective combination. The results of this research provide a scientific basis for improving the adoption efficiency of AMATs in China.

DETERMINANTS OF HOUSEHOLDS’ EDUCATIONAL EXPENDITURE IN THE MEKONG DELTA OF VIETNAM

This study investigates the determinants of households’ educational expenditure in the Mekong Delta through the Viet Nam Living Standard Survey (VHLSS) data in 2022. The Tobit model is used to identify factors that may influence and explain the households’ expenditure on education in the Mekong Delta. The findings found that eight factors have a statistically significant impact of 1% to 10% on the households' educational expenditure. They include 06 factors (age of household head, ethnicity of household head, household’s size, place of residence, households with additional studying members and household’s average income) which positively impact on the households’ educational consumption and the other factors (educational level of household head and participation in local government) which have negative impacts on the educational consumption of the households. Given findings enable us to propose various suggestions to optimize the investment and expenditure for the education of households in the Mekong Delta.

Impact of Agroforestry Adoption among Smallholder Farmers’ Households in Zambia: An Expenditure Approach

The environmental, economic, and social effects of climate change are expected to be profound for smallholder farmers, especially in developing countries like Zambia, whose way of life is largely dependent on the natural world. Many developing countries have realized that climate-smart agricultural practices such as agroforestry are a solution to existing problems caused by climate change. Agroforestry technologies incorporate tree crops in farming systems that benefit farmers with fodder for animals and fruits, reduce erosion, and reclaim soil fertility. This study investigated the impacts of agroforestry adoption on smallholder farmers’ crop productivity and household expenditure in Nyimba district, Zambia. The study further explored the factors influencing the adoption of agroforestry among smallholder farmers in the study area. Data was collected from July to August of 2022 from 325 randomly selected smallholder farmers’ households in four villages in the Nyimba district of Zambia. A binary logistic regression model was used in this study to determine factors influencing the adoption of agroforestry among smallholder farmers. The results revealed that smallholder farmers’ household head education level, access to extension services, household size, access to credit, farming experience, farmland size, and distance to the nearest market had an influence on agroforestry adoption. Propensity score matching was performed to determine the impacts of agroforestry adoption on smallholder farmers’ household expenditure and crop productivity. The results revealed that smallholder farmers’ household adopters had 1,929.040 kilograms of crop yield (Zea mays L.) higher than non-adopters by 817.43 kilograms. Household expenditure for smallholder farmers adopters was ZMW 8,873.47 higher than non-adopters by ZMW 5,617.91 in the study area. The findings imply that smallholder farmers’ households should implement agroforestry in the long term to improve their household welfare. Therefore, the study suggested that efforts should be focused concomitantly on the diffusion of agroforestry options and the lifting of their adoption barriers among smallholder farmers

Analysing the Influence of Caste, Gender, Religion, and Household Characteristics on Enrolment Status and Student Dropout in Assam: A Logistic Regression Study

This study investigates the factors contributing to enrolment status and dropout rates in Assam using a binomial logistic regression model. The dependent variable, enrolment status, is categorized into currently enrolled and dropout or no enrolment. Explanatory variables encompass religion, gender, social group, sex of the head of the household, household head's education level, family income, and household size.
 Our objectives include assessing the influence of religion, gender, social group, household leadership, head's education level, family income, and household size on enrolment and dropout likelihood. Dummy variables are used for religious affiliations, social group categories, head's education, and family income groups.
 The results reveal significant associations between gender, education level of the head of the household, and family income with enrolment and dropout likelihood. Muslims exhibit a higher likelihood of dropout or no enrolment compared to Hindus. Female-headed households and individuals in households with higher-educated heads display increased odds of no enrolment or dropout. Lower family income levels are associated with higher odds of dropout.

Patterns and Determinants of Households' Energy Choices for Cooking as Well as Their Implications for Poverty Eradication in Nigeria

ABSTRACT: Adequate access to environmentally-friendly energy sources is crucial for addressing the problems of environmental degradation and adverse climate change as well as other developmental challenges. The literature on the patterns and determinants of households' energy choices for cooking is very scanty. Essentially, the scanty literature, in general, did not adequately cater for household composition and economies of scale in household consumption as well as give adequate consideration to the impact of ownership of education/entertainment appliances and means of communication by households on households' energy choices for cooking. It is very important to utilize adult equivalence scales and estimate of economies of scales in household consumption in the analysis of household consumption in order to make such analysis highly robust. It is also very important to include ownership of education/entertainment appliances and means of communication in the analysis of households' energy choices for cooking because they (the appliances and means of communication) are expected to provide adequate awareness on the harmful effects of dirty energy sources and such awareness can influence households' energy choices. Furthermore, none of the studies in the scanty literature discussed the major implications for poverty eradication of the patterns and determinants of households' energy choices for cooking. This study adequately addressed the highlighted research gaps. The study analyzed the patterns and determinants of households' energy choices for cooking in Nigeria and discussed their implications for poverty eradication in the country using, among other things, descriptive statistics and multinomial logistic regression technique. The study was based on a nationally representative survey data, obtained from the National Bureau of Statistics. The study found that the patterns of households' energy choices for cooking in Nigeria exhibit the operation of energy ladder hypothesis. The study also found that increased educational level of household head, ownership of electric food preservation appliance by household and satisfactory housing condition are among the factors that increase the likelihoods of the uses of transition fuels and very clean energy sources as well as reduce the likelihood of the use of traditional biomass fuels. Adequate measures should therefore be put in place to sufficiently increase households' incomes and guarantee optimal access to environmentally-friendly energy sources for cooking in the country; this will pave the way for poverty eradication in the country.

Determinants of transitions in drinking water service systems in developing economies: a case study of Uganda

Abstract Limited research has been undertaken on significant factors associated with transitions between drinking water supply systems (DWSS) ladders. In this paper, we applied panel ordered logistic multinomial logistic regression models to seven datasets of the Uganda Demographic and Health Survey (1988–2021), with the SDG6 categorical levels of DWSS (unimproved, improved and piped into dwelling) as transition levels, and various socio-economic and demographic characteristics as covariates. Sex and education level of household head, toilet facility, electricity access, size of agricultural land and wealth index are significant factors. The main implication is the need to address socio-economic disparities in developing economies.

Determinants of household poverty in Arsi Nagelle town, West Arsi Zone, Ethiopia

The struggle to achieve above the poverty line at the household level in the urban areas of Ethiopia dates back an extended period. In this regard, this study was conducted to identify and analyze the determinants of urban household poverty in the case of Arsi Nagele town. The study employed both primary and secondary data. Preliminary data was collected from 337 randomly selected households in two sub-cities by questionnaire. Both descriptive and Logit regression model was used for data analysis. From the three schools of thought, the basic needs approach is employed to identify households as poor and non-poor. Sixteen (14) explanatory variables, four continuous and ten discrete, were included in the logit regression model. Out of these variables, the sex of the household head, age of the household head, marital status of the household head, family size of household head, education level of household head, household head house tenure, household head access to electricity, household head access to the market center, household head access to credit, household head access to clear and sufficient water, the existence of solid institution was among the significant variables affecting the level of household's poverty. The research found that the area's food poverty line and the total poverty line were 13,788 Birr and 14,436 Birr per adult per year, respectively. Accordingly, the incidence of poverty, poverty gap, and severity was found to be 40 percent, 26.5 percent, and 7 percent, respectively. The research found that the area's food poverty line and the total poverty line are 13,788 Birr and 14,436 Birr per adult per year, respectively. Keywords: poverty, Logit, Poverty line, poverty gap, and severity

Factors influencing paddy producers’ profitability and sale to markets: evidence from Battambang Province, Cambodia

While rice farming is essential for livelihoods of smallholder farmers and the economy, there is limited evidence of specific socioeconomic determinants of paddy sale and profitability of Cambodian farmers. The study analyzes factors influencing sale and profitability of paddy production in Battambang Province using primary data collected from randomly selected 242 paddy farmers in the northwest of Cambodia. The data were analyzed using the log-linear ordinary least squares regression. The results show that paddy farming is profitable with the benefit-cost ratio of around 2.0. Besides, smallholders obtained larger profitability than medium- and large-scale farmers due to the diseconomies of scale. Fertilizer, pesticide, harvesting, and seed costs were major cost items for paddy production in the study area. Education level of household heads, household size, land are under paddy, the quantity of paddy consumed at home, the quantity of paddy retained for seed recycling, varieties of rice, and distance to markets significantly influenced paddy sale to markets, while education level of household heads, farming experience, household size, varieties of rice, selling price, cost of seed, and cost of fertilizer were found to influence the profitability of paddy production. Farm policies should aim at increasing paddy fields, expanding irrigation systems, promoting premium rice varieties, and supporting the farm gate price of paddy produce, while reducing the prices of inputs, particularly seed and fertilizer.

Synthetic Minority Over-sampling Technique (SMOTE) for handling imbalanced data in poverty classification

Poverty data in official statistics data is important for development planning. The lower percentage of the poor recorded yearly indicates good development of a country. Moreover, there is always a problem when performing an inferential and classification analysis because of the imbalanced data, thereby leading to biases in the estimation results and prediction errors in the classification. One of the solutions to this problem is using Synthetic Minority Over-sampling Technique (SMOTE). Therefore, this study aims to evaluate the inference and classification quality using the binary logistic regression model without and with SMOTE. The data utilized was the poverty status of households in the rural and urban areas in East Java, Indonesia as contained in the 2019 National Socio-Economic Survey. Furthermore, the variables used are poverty status of the household, the age of the household head (HH), the ratio of household members who are employed, gender of the HH, number of household members, education level of HH, and occupation of the HH. It was concluded that the model with SMOTE approach was better at inference and classifying the results.

Access to inclusive sanitation and participation in sanitation programs for people with disabilities in Indonesia

Access to inclusive sanitation for people with disabilities (PWDs) remains a global challenge, including in Indonesia, where 10–15% of its population is disabled. Inclusive sanitation facilities can be achieved when PWDs are involved in the sanitation-related decision-making process, e.g., designing toilet that meets their needs. This study aims to investigate the situation of the sanitation facility in houses of PWDs and understand knowledge, attitude, and practices related to PWD participation in sanitation programs using a case study in two provinces in Indonesia: Nusa Tenggara Barat and Nusa Tenggara Timur. Quantitative data were taken from 129 PWD households, and qualitative data were from in-depth interviews with relevant stakeholders. The latter was presented in a causal loop diagram. Less than 5% had inclusive sanitation at home, mainly due to no supportive tools and bins. The knowledge levels related to sanitation and PWDs participation in sanitation programs were relatively low. Economic condition was one of the barriers for PWDs to participate in the sanitation program. Statistical analysis found that a higher household head education level was associated with a more positive attitude and higher PWD participation in sanitation programs. Although Indonesian law supports PWD participation, the implementation remains a challenge. This study also underlines the need for capacity building in facilitating PWDs’ involvement in sanitation programs and community meetings. Finally, barriers to PWD participation can come from different levels and actors, e.g., the family, the community, the district level, and the PWD itself, indicating the need to involve actors at all levels to enhance PWD participation in the sanitation program that leads to inclusive sanitation facilities for all groups.

Factors Affecting Maize Productivity: In Case of Bedele District of Buno Bedele Zone, Oromia Regional State, Ethiopia

Though agriculture remains to be the most important sector of the Ethiopian economy, its performance has been disappointing and food production has been lagging behind population growth. This gap between demand for and supply of food can be reduced by improving crop production and productivity. As maize is a significant contributor to the Ethiopian economy, increasing production and productivity in maize production could be taken as an important step in attaining food security. This study was conducted in Bedele district of Buno Bedele zone of Oromia National Regional State with the aim of identifying factors affecting the productivity of maize production. This study used cross sectional data which was collected from a total of 174 farm households which were randomly and proportionally selected from 4kebeles of the Woreda using two stage sampling technique. The primary data were collected through individual interviews of respondents using semi-structure questionnaire. Secondary data was collected from different relevant literatures such as district reports, publications, journals and other documents relevant for the study. Descriptive statistics and Econometric model were used to assess the collected data. The result of Descriptive statistics indicated that the mean amount of maize produced by households in quintal per hectare is about 19.76 quintal. Results of Cobb- Douglas production function revealed that Variability of weather condition, Extension Contact, Land allocated for maize, Mode of sowing, Amount of fertilizer used, Farm Income, labor cost, Number of Oxen, and educational level of household head positively and significantly affected the productivity of maize production. Whereas Soil fertility, occurrence of pests and diseases, over cultivation are negatively and significantly affected the productivity of maize production. Therefore, attention should be given to major factors that affect the productivity of maize production to increase production and productivity of maize.

Fuel adoption in rural heating: a field study on northern China

PurposePromoting clean heating in rural areas is crucial for achieving a low-carbon transition of energy consumption and China's dual-carbon target. The study aims to consider the energy stacking behavior in heating energy use, reveals the determinants that affect household cleaner heating choices under the winter clean heating plan (WCHP), and proposes policy recommendations for the sustainable promotion of clean heating.Design/methodology/approachWith unique rural household survey data covering the clean heating pilot regions in northern China in 2020, this study estimates the relationship between driving factors and heating energy choices through binary and multivariate probit models.FindingsThe regression estimates show that the main drivers of heating energy choices include household income per capita, education level of household head, knowledge of the WCHP, access to heating subsidies and perception of indoor air pollution. There is energy stacking behavior in rural household heating energy use. Household decisions to adopt electricity or clean coal heating are correlated with firewood or soft coal use.Originality/valueThis study is one of the few to investigate the heating energy use of rural households by allowing for the adoption of multiple energy types. Combined with a unique microsurvey dataset, it could provide rich information for formulating proper energy transition planning. The findings also shed light on the importance of heating subsidies, households' knowledge of WCHP and awareness of environmental health in choosing clean heating energy, which has not been fully valued in related research.

Smallholders' resilience-building adaptation and its influencing factors in rainfed agricultural areas in China: based on random forest model.

In recent years, extreme events and risks have increased under the background of global warming, which influenced agricultural production significantly. Adaptation has been considered as a key pathway to enhancing smallholders' climate resilience. We selected a total of 903 smallholders using the multi-stage random sampling technique in rainfed areas in China, and then collected the survey data through the structured questionnaire and focus group discussion. Three resilience-building adaptation indices (RBAS-A, RBAS-D and RBAS-I) were constructed by the entropy method, whose mean values were 0.378, 0.336, and 0.602, respectively. Furtherly, the random forest model was used to explore influencing factors of climate-resilient adaptation strategies. The results revealed that education level of household head, family size, farmland size, access to information by mass media and kith and kin, perception of temperature change in summer and winter, and perception of crop yield change were the significant factors influencing smallholders' alteration strategies. Meanwhile, age and education level of household heads, off-farm income, farmland size, mass media, and perception of winter temperature changes had significant effects on the diversification strategies. Moreover, demographic characteristics, socioeconomic characteristics, information access and climate change perceptions, and impacts had significant impacts on intensification strategies. Importantly, we found that there was a certain threshold for the impact of several factors on the constructed composite indices. And the impacts of the perceptions of temperature on alteration and intensification strategies showed a V-shape. Finally, we proposed targeted suggestions for improving smallholders' climate-resilient adaptation in the rainfed agricultural areas in China.

Unidimensional versus Multidimensional Poverty: A Case Study of Haryana

Poverty does not encompass a single deprivation but involves a system of multiple interconnected deprivations. The present study attempted to investigate if the unidimensional measure of poverty based on the consumption expenditure approach can capture the actual state of poverty in Haryana. The study was based on the sixty-eighth round of the National Sample Survey on consumer expenditure. A total of eight indicators of poverty were chosen, namely; consumption expenditure, occupational security, educational level of head of household, educational level of the individual, lighting, cooking fuel, dwelling unit, and land ownership. These indicators were clubbed into three broad dimensions, namely, material well-being, education, and standard of living. The results revealed that consumption expenditure as a proxy to judge an individual's welfare in Haryana was unreliable as it under-represents deprivations across other indicators and had a low degree of association with them. A multidimensional measure of poverty was thus more suitable to capture the actual state of poverty. Further, it was found that education contributed the highest to Multidimensional Poverty Index (MPI), followed by material well-being and standard of living. Among individual indicators, the most significant contributors to MPI in Haryana were the educational level of household-head as well as other members, cooking fuel, occupational security, and consumption expenditure.

Determinants of food insecurity in food aid receiving communities in Ethiopia

This study analyzed households' food security and its determinants along with the coping mechanisms opted against food insecurity while assessing the food security interventions in southern Ethiopia. Combination of emergency and project food aids are the two major intervention strategies enforced to alleviate food insecurity in the area. The results from descriptive statistics show that 74.17% of the surveyed households were food insecure. The logit model result revealed that sex, age, education level of household head, family size and access to remittance were significant factors that affect the status of household's food security. Finally, empowering women, fair aid targeting on older households, strengthening formal and informal education, awareness creation on effective family planning and reducing the dependency syndrome and encouraging entrepreneurship were identified to factors that potentially improve food security on the households. • Food aid cannot achieve food security by itself. • Some of the food aid is stolen and sold in the market place. • Cash for work provides employment opportunities and generate public goods. • Food aid program participation had an association with social connection. • Prolonged aid-dependency results loss of skills and aspiration failure.

Adaptation Strategies and Livelihood Vulnerability of Ethnic Minorities in Vietnam: A Case of the Khmer Community in Mekong Delta

This study investigates the impact of climate change adaptation strategies on the livelihood vulnerability of ethnic minority households in Vietnam, specifically the Khmer people in the Mekong River Delta. Research data were collected from 426 Khmer farming households in three provinces—namely Tra Vinh, Soc Trang, and Kien Giang—which comprise the largest Khmer population. Vulnerability is measured using the Livelihood Vulnerability Index (LVI) with weights based on Principal Component Analysis (PCA). The results show that Khmer households have a moderate level of vulnerability, and that Khmer households in Tra Vinh province have a significantly higher level of vulnerability than the other two localities. Multivariate regression analysis reveals that adaptation strategies have a significant impact on reducing livelihood vulnerabilities. Moreover, results highlight the relationship of the livelihood vulnerability level to factors such as education level of household head, gender of household head, household's land area, household labor force, dependency ratio, poor household, housing status, agricultural and nonagricultural income, information access, social network access, local support policies, credit access, climatic shocks, and perception of climate change.

Push and pull factors of red pepper (capsicum) market supply: Evidence from south western Ethiopia

The growth and development of the spices sector depend upon market-oriented production system and good marketing infrastructure. However, for smallholder farmers, it is difficult to supply theirs produces to markets because of different problems and barriers. Therefore, this study was aimed at analyzing the push and pulls factors of red pepper market supply in Southwest Ethiopia. The primary data were collected from 267 randomly selected sample households’. The Tobit model was used to determine the volume of red pepper supplied to the market. The results shows that the education level of household head, land allocated for red pepper production, access to credit, and lagged price of red pepper significantly affect the volume of red pepper supplied to the market. The major production constraints that hamper red pepper yield were red pepper disease, lack of fertilizer supply, lack of improved variety, lack of pesticide, harvesting before maturity, and poor post-harvest handling. The marketing constraints were lack of marketplace, low and unstable price of the product, and low quality of product, improper scale, lack of government support, and lack of transport. Therefore, Policies that give more emphasis on the provision of modern inputs, improving infrastructure, strengthening institutions of collective action, and improving the marketing extension system are recommended. • Push and pull factors are direct and indirect cause of market supply. • An efficient marketing system is the building block of economic growth. • Proper and stable pricing system increase producer's net gain. • Red pepper is the second most important vegetable.

Socioeconomic factors influencing farmers’ willingness to replant trees: evidence from smallholder rubber farming in Sri Lanka

ABSTRACT Planting trees is a source of income for many smallholders worldwide and is critical for providing a range of ecosystem services. The effectiveness of the policies and incentives to encourage tree farming by smallholder farmers depends on the socioeconomic context of the farm households. The study investigates smallholder farmers’ willingness to replant rubber after reaching its economic lifespan while also examining the impact of farm households’ socioeconomic factors on willingness to replant. Using the utility maximization theory and logit model, the paper analyses household-level data collected from 404 smallholder farmers in Sri Lanka. The empirical findings show that about 71% of farmers are willing to replant rubber. Socioeconomic characteristics of farm households are significantly associated with the willingness to replant rubber. Considering the increase in the probability of willingness, factors such as education level of household head, share-cropping, family labour, income generation from rubber farming, non-farm income, other agricultural income, farmers group participation, and institutional support, positively affect farmers’ willingness to replant rubber. The findings suggest that considering these factors in the formulation of appropriate incentives and strategies for rubber farm diversification would foster a beneficial environment for smallholder rubber farming.