scholarly journals Determinan Kemiskinan Rumah Tangga di Jawa Timur

2020 ◽  
Vol 9 (2) ◽  
pp. 89-105
Author(s):  
Angga Erlando ◽  
Tri Haryanto ◽  
Verliana Rositawati
Keyword(s):  
Health Insurance ◽  
Agricultural Sector ◽  
Household Head ◽  
Household Size ◽  
Poor Health ◽  
Social Characteristics ◽  
Head Of Household ◽  
Poverty Status ◽  
Household Heads ◽  
Educational Variables

This study aims to determine the economic, demographic, and social characteristics that are determinants of poverty, and analyze how the level of tendency (probability) in shaping poverty in East Java. Using a quantitative approach, this research relies on a logistical model (logit). The logit model aims to find the probability of an event occurring, in this case the probability of a household heading into poverty or not. The result is that education of household heads, gender of household heads, household size, household head work sector, access to KUR, and access to poor health insurance have a tendency to be determinants for household heading to poverty status. Educational variables, gender of the head of household, and access to KUR from this paper empirically show a tendency to reduce the probability of households to poor. Meanwhile increasing household size, types of employment in the agricultural sector, and the ownership of poor health insurance tend to increase theprobability of households heading into poverty status.

The Dynamics of Poverty in Chile

2008 ◽  
Vol 40 (2) ◽  
pp. 251-273 ◽  
Author(s):  
CHRISTOPHER NEILSON ◽  
DANTE CONTRERAS ◽  
RYAN COOPER ◽  
JORGE HERMANN
Keyword(s):  
Household Head ◽  
Physical Capital ◽  
Poverty Line ◽  
Poverty Dynamics ◽  
Poverty Status ◽  
Poverty Lines ◽  
Transient Poverty ◽  
Household Heads ◽  
Definition Of ◽  
Transitory Component

AbstractThis paper uses the 1996–2001 National Socioeconomic Survey panel database to analyse poverty dynamics in Chile, drawing a distinction between chronic and transient poverty. We found that while 20 per cent of the population was living below the official poverty line both in 1996 and 2001, only 9 per cent of the population was poor at both dates. We also found that when the poverty line was raised, the amount of households which could be considered chronically poor rose steadily, whereas the transitory component of poverty remained more or less stable. Analysis of the direct reasons for changes in household poverty status leads us to the conclusion that labour dynamics are far more relevant than demographic changes. Household heads who suffered health problems are significantly less likely to leave poverty. Household human and physical capital are also relevant, as well as the sector in which the household head works. Simulating this exercise using different poverty lines reveals that some variables are not robust to changes in the definition of poverty, while others which originally appeared to be insignificant become so for most other possible poverty lines.

scholarly journals Determinants of Household Poverty Status in Kediri City

2021 ◽  
Vol 9 (2) ◽  
pp. 36-47
Author(s):  
Yennie Dwi Rozanti ◽  
Mohamad Khusaini ◽  
Ferry Prasetyia
Keyword(s):  
Household Head ◽  
Marginal Effect ◽  
Household Poverty ◽  
Poor Households ◽  
The Status ◽  
Poverty Status ◽  
Household Members ◽  
Household Heads ◽  
Productive Assets ◽  
Logit Regression Model

Analyses of the causes and the characteristics of poverty at micro levels provide more efficient strategies for the attainment of main Sustainable Development Goals. This study aimed to analyze the extent to which the characteristics of individuals, households, and communities influence the probability of household poverty status. The 2019 Social Welfare Integrated Data and Village Potential Data of Kediri City were analyzed using an ordered logit regression model and then interpreted based on marginal effect calculation. The study found that household heads’ squared-age, household members’ education, household members’ occupation, household head gender (female), ownership of assets, access to the internet, access to proper sanitation, and access to financial institutions reduced the probability of households being categorized as very poor and poor. This finding indicated that household productivity influenced by the household head’s characteristics in managing productive assets, supported by access to infrastructure, could increase the household's welfare. However, the household head’s age and marital status, dependency ratio, and access to health facilities increased household’s probability of being very poor and poor. Policies regarding poverty must be adjusted to the poverty characteristics and status. Improving access, equalizing education, and improving job opportunity and infrastructure management that ensure accessibility and enhancement in service quality need to be made to increase the status of households with the lowest 40% welfare in Kediri City. Policies regarding poverty should be focused more on social programs for very poor and poor households. Meanwhile, those near-poor and vulnerable-to-poor need more empowering programs.

scholarly journals Determinants of household preference for beef to pork in Umuahia Metropolis of Abia State, Nigeria

Agro-Science ◽  
2020 ◽  
Vol 19 (3) ◽  
pp. 15-18
Author(s):  
F.C. Okoronkwo ◽  
J.C. Efedua ◽  
T.A. Amusa
Keyword(s):  
Goodness Of Fit ◽  
Household Head ◽  
Meat Consumption ◽  
Positive Influence ◽  
Sampling Procedure ◽  
Study Data ◽  
Household Size ◽  
Least Square ◽  
Probit Regression ◽  
Household Heads

The study ascertained the determinants of households’ preference for beef to pork in Umuahia Metropolis of Abia State, Nigeria. Using multi-stage random sampling procedure, data were collected from eighty household heads for the study. Data collected were analyzed using descriptive  statistics, ordinary least square and probit regression analysis. Findings from the study showed that beef was most preferred with 63.75% of  households indicated preferences for beef to pork while 36.25% of households preferred port to beef. The study also revealed age of household head, and price of meat negatively influenced meat consumption while household size and average monthly income had positive influence and the R2 was 0.675 which implied 67.5% of the variation in the meat consumption was explained by the independent variables. From the probit regressionmodel the results showed age of household heads and price of pork had a negative coefficient and were significant at 10% and 5% level of probability respectively, while household size, education level, and household income had positive coefficient and were significant at 1%, 5%, and 1% level of probability, respectively. The Chi square was 135.485 which indicated the goodness of fit for the equation and was significant at 1% level of probability. The study recommended beef marketing as a good venture in the study area; beef was most preferred meat in the study. Hence, it is recommended that unemployed persons should be encouraged to venture into beef marketing; also, there is huge potential for pork marketing in the study area. Key words: preferences, household, beef, pork

scholarly journals Poverty and its Alleviating Strategies among Rural Farming Households in Benue State, Nigeria

2021 ◽  
Vol 21(36) (2) ◽  
pp. 33-44
Author(s):  
Samuel Upev ◽  
Amurtiya Michael ◽  
Shuaibu Mshelia ◽  
Justice Onu
Keyword(s):  
Social Protection ◽  
Household Head ◽  
Sampling Technique ◽  
Poverty Measurement ◽  
Farm Size ◽  
Binary Logistic Regression Model ◽  
Poverty Status ◽  
The Government ◽  
Household Heads ◽  
Farming Households

The study analysed rural farming households’ poverty status and alleviating strategies in Benue State, Nigeria. The specific objectives of the study were to: describes the rural household heads’ socio-economic characteristics; determine the poverty status of the respondents and its determinants; and identify poverty alleviating strategies of the respondents. Data for the study was collected from 420 respondents selected using a multi-stage sampling technique. Data collected were analysed using descriptive statistics, the Foster-Greer-Thorbecke poverty measurement index, and the Binary Logistic regression model. The findings of the study revealed a very high incidence of poverty (70%), having a gap of 0.34, and severity of 0.17. Poverty in the area is positively associated with the age of the household head and household size, while gender, educational level, off-farm activity, membership of a group, farm size, and land ownership are negatively associated with poverty. The common poverty alleviation strategies identified were agricultural wage labour (48.6%), rental services (45.0%), and transportation business (36.7%). Therefore, it was recommended that the government and other stakeholders should initiate sustainable social protection schemes that can assist rural residents in alleviating poverty until their condition improves.

scholarly journals Poverty status and its determinants in rural households of Enda-mohoni woreda, Northern Ethiopia

2021 ◽  
Vol 68 (3) ◽  
pp. 729-744
Author(s):  
Abadi Alemaw ◽  
Dagnew Kalayu ◽  
Kibrom Kahsu ◽  
Hadush Redae
Keyword(s):  
Household Head ◽  
Sampling Technique ◽  
Cluster Sampling ◽  
Northern Ethiopia ◽  
Estimation Model ◽  
Explanatory Variables ◽  
Tigray Region ◽  
Poverty Status ◽  
Household Heads ◽  
Index Estimation

This research generates specific, contextualized identification of existing poverty status and poverty causing factors in Enda-mohoni woreda in Tigray Region, Ethiopia. Agroecology based cluster sampling technique was employed to select 154 household heads. Logit model was used to analyze household poverty status and FGT poverty index estimation model for poverty incidence analysis. The poverty analysis found a 30.9% headcount ratio, 4.4% poverty gap ratio, and 1% poverty severity. Furthermore, the result of the logistic regression revealed that among the explanatory variables used in the model, family size and agroecological location of the household head were found to positively influence HHs' poverty status at (P<0.01) and (P<0.05) respectively. Whereas, owning livestock and marital status of the HHH were found to negatively influence HHs' poverty status at (P<0.05) and (P<0.1) respectively. It is with appropriate policies that recognize the importance of poverty features and trends would it be possible for more people to make positive exits from poverty risk.

scholarly journals ANALYSIS OF MULTIDIMENSIONAL POVERTY IN RURAL ADAMAWA STATE, NIGERIA

2019 ◽  
Vol 53 (3) ◽  
Author(s):  
Amurtiya Michael ◽  
Abdu Karniliyus Tashikalma ◽  
David Chinda Maurice ◽  
Ahmadu Abubakar Tafida
Keyword(s):  
Sampling Technique ◽  
Multidimensional Poverty ◽  
Demographic Characteristics ◽  
Household Size ◽  
Farm Size ◽  
Primary Data ◽  
Cluster Sampling ◽  
Binary Logistic Regression Model ◽  
Poverty Status ◽  
Household Heads

This study assessed multidimensional poverty in rural parts of Adamawa state, Nigeria. Specifically, the study objectives were to: describe the respondents’ socio-demographic characteristics, determine their multidimensional poverty status, and identify the determinants of multidimensional poverty in the sampled communities. Multi-stage cluster sampling technique was used to collect primary data from 480 household heads selected from 16 villages across the study area. Data collected were analysed using descriptive statistics, Multidimensional Poverty Analytical Tool (MPAT), and Binary Logistic regression model. The respondents’ socio-demographic characteristics described in the study showed that the mean age was 46.3 years, while the average household size was 7 persons. The study indicated that most (86.7%) of the respondents were male, who are mostly married (91.7%), and that majority (74%) are educated. The distribution of the respondents’ multidimensional poverty status revealed that majority (61.7%) of the households were poor. The study revealed that multidimensional poverty in the study area is influenced negatively by age, marital status, and household size. Similarly, gender, educational level, livelihood activities, farm size, livestock ownership, remittance, membership of group, and access to credit positively influence multidimensional poverty. Key among the recommendations of the study is the adequate provision of basic infrastructure in the area.

scholarly journals DETERMINAN TINGKAT KEMISKINAN DI KOTA BANDUNG

2021 ◽  
pp. 626
Author(s):  
Bayu Kharisma ◽  
Teguh Santoso
Keyword(s):  
Mobile Phones ◽  
Social Characteristics ◽  
Logit Regression ◽  
Household Poverty ◽  
The Status ◽  
Poverty Status ◽  
Household Heads ◽  
Logit Regression Model ◽  
The City ◽  
Positive Effect

This study aims to find the determinants of household poverty status in the city of Bandung by using the National Socioeconomic Survey (Susenas) of March 2018 Expenditure Consumption in Bandung. The methodology used is an ordered logit regression model. The results showed that the demographic characteristics variables that had a significant and positive effect on the poverty status of households in the city of Bandung were female household heads, marital head households and household size and dependency burden. Meanwhile, economic characteristics, namely household access to the internet, ownership of mobile phones (HP), ownership of one's own residence, and access to business credit have a negative and significant effect on household poverty status in the city of Bandung. Furthermore, social characteristics that negatively affect the status of household poverty in the city of Bandung are variable levels of school education as measured by the years of schooling.

Adoption and intensity of use of mobile money among smallholder farmers in rural Ghana

2021 ◽  
pp. 026666692199908
Author(s):  
Richard Kofi Asravor ◽  
Afia Boakye ◽  
John Essuman
Keyword(s):  
Mobile Phone ◽  
Marital Status ◽  
Household Head ◽  
Household Size ◽  
Sub Saharan Africa ◽  
Farm Size ◽  
Mobile Money ◽  
Rural Ghana ◽  
Household Heads ◽  
The Impact

The impact of mobile money services in sub-Saharan Africa have been largely recognised. However, empirical studies are principally lacking on the factors influencing the decision to own a mobile phone (first hurdle), register with mobile money (second hurdle) and the intensity of use of mobile money services (third hurdle). This study examined the determinants of the mobile phone ownership, drivers of registration (participation) of mobile money services, and the intensity of use of mobile money services in rural Ghana by employing the triple hurdle approach. The first and second hurdle were analysed using the logit model while quasi-poisson regression was used to analyse the third hurdle. The analysis from the cross-sectional data showed that the decision to own a mobile phone was driven by household size, marital status, the farm size, access to electricity, income status and the type of occupation engaged, whereas the decision to register with mobile money was influenced by the age, educational status, marital status, household size, farm size and the type of occupation engaged in by the household head. The intensity of usage of mobile money services was influenced by the age of the household head, higher educational level, marital status of the household head, household and farm size as well as the distance of the household heads from the mobile money agent which directly influences the intensity of use of mobile money services by household heads. The study recommends that strategies that promote access to electricity and occupation in the formal sector or both farming and trading in the rural communities should be promoted. Furthermore, policy attention should focus on location, farmers and farm characteristics.

A COMPARATIVE STUDY ON AWARENESS AND HEALTH INSURANCE COVERAGE IN RURALAND URBAN MEERUT

2021 ◽  
pp. 65-67
Author(s):  
Harivansh Chopra ◽  
Tanveer Bano ◽  
Niharika Verma ◽  
Gargi Pandey
Keyword(s):  
Health Insurance ◽  
Urban Area ◽  
Rural Area ◽  
Insurance Coverage ◽  
Health Insurance Coverage ◽  
Health Coverage ◽  
Rural And Urban ◽  
Economics Of Health ◽  
Poverty Status ◽  
Rural And Urban Area

Universal Health Coverage aims to provide essential health services to all while providing protection from catastrophic expenditure on health. To mitigate the economics of health expenditure, health insurance is one of the important tool. Hence, this study was conducted to nd out the awareness and practice of health insurance coverage in rural and urban Meerut.90 households were studied in both rural and urban area. Awareness was higher in urban area but coverage was higher in rural area. Awareness and coverage were found to be signicantly associated with poverty status in rural area of Meerut.

scholarly journals Determinants of Cocoa (Cacao Theobroma) Farmers Uptake of Crop Insurance: Evidence from Ekiti State

2020 ◽  
pp. 96-104
Author(s):  
Olatomide Waheed Olowa ◽  
Omowumi Ayodele Olowa
Keyword(s):  
Crop Insurance ◽  
Risk Preferences ◽  
Household Size ◽  
Farm Income ◽  
Cocoa Bean ◽  
Agricultural Insurance ◽  
Processing Technologies ◽  
Significant Difference ◽  
Household Heads ◽  
Cocoa Farmers

Cocoa farmer faces increasing challenging environment through exposure to risks factors which have impacted negatively on their production or output. Since farmers are primary producers and often times lack capacity to control risks factor, it is important to manage this factors. This study examines the cocoa farmers’ risk preferences and crop insurance perception and isolates the drivers of decision to uptake crop insurance among cocoa farmers in Ekiti state. The sample for the study consist of 200 cocoa farmers who were household heads selected through multi-stage sampling across four Local government areas of Ekiti State who are predominantly cocoa producers. Data collected on socio-demographic characteristics, perception of crop insurance and risk preferences, were analyzed using descriptive statistics and binary logistic model. Results showed that majority of the cocoa farmers were without crop insurance, with higher enrolment in Membership of cooperative society, owned their land, larger household size and lower educational level but higher level of farm experience when compared to cocoa farmers who are holding crop insurance. Farmers risk preferences showed no significant difference between farmers with or without insurance. Education (β=0.59), Household size (β=0.0029) and Debt use (β=0.02), Membership of cooperative (β=-4.53), Farming Experience (β=-2.51), Owned Land (β=-2.19) and Non-Farm Income (β=-0.65) were among the significant determinants of insurance uptake. Risk mitigating measures such as provision of necessary incentives such as improved varieties of cocoa seedling, as well as provision of fertiliser and approved pesticides, financial assistance, and simple processing technologies that produce standard cocoa bean plus a re-jigged Nigeria Agricultural Insurance Corporation (NAIC) for an improved discharge of its function are recommended.

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