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 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.

Analysis of arable crop farmers’ awareness to causes and effects of climate change in south western Nigeria

2015 ◽  
Vol 42 (7) ◽  
pp. 614-628 ◽  
Author(s):  
Shakirat Bolatito Ibrahim ◽  
Idris Akanbi Ayinde ◽  
Aisha Olushola Arowolo
Keyword(s):  
Climate Change ◽  
Sampling Technique ◽  
Household Size ◽  
Farm Size ◽  
Primary Data ◽  
Survey Method ◽  
Tobit Regression ◽  
Content Type ◽  
Mitigation And Adaptation ◽  
Arable Crop

Purpose – The purpose of this paper is to empirically analyze the determinants of arable crop farmers’ awareness to causes and effects of climate change in south western Nigeria. Design/methodology/approach – Using primary data, 150 arable crop farmers in Ogun State were selected through a multi stage sampling technique. Survey method was used to elicit information on farmers’ socioeconomic, production characteristics, and their level of awareness to causes and effects of climate change. The data collected were analyzed using descriptive statistics, environmental awareness index (EAI), and Tobit regression analysis. Findings – Most (81.08 percent) of the arable crop farmers were males with an average household size of eight persons, farming experience of 24 years and farm size of approximately 1 ha. The computed climate change EAI showed that only 47 percent of the respondents were aware of causes of climate change, while 68 percent were aware of its effects. Results further revealed that age, income from secondary occupation (p < 0.10), marital status, household size (p < 0.05), years of farming experience, frequency of extension contact, land size in hectare, and farm revenue (p < 0.01) were the determinants of respondents awareness to causes and effects of climate change. Practical implications – The study recommended among others that, awareness should be created among arable crop farmers on climate change causes and effects for appropriate mitigation actions to be taken for improved agricultural productivity. Originality/value – The study provided new empirical evidence on the awareness level of respondents to causes and effects of climate change on their production activities and livelihood in general. Implications for policy will be to provide a public education program that will target females, the poor, the illiterate, and the people in the economically active age group among others in order to create awareness and provide information and adequate knowledge on the causes and effects of climate change for proper mitigation and adaptation options.

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 Effects of the reward of internal migration on poverty status of rural households left behind in Ogun and Osun States, Nigeria

2019 ◽  
Vol 52 (3-4) ◽  
pp. 129-138
Author(s):  
Esther Toluwatope Tolorunju ◽  
Adewale Oladapo Dipeolu ◽  
Rahman Akintayo Sanusi ◽  
Dare Akerele
Keyword(s):  
Internal Migration ◽  
Rural Households ◽  
Multidimensional Poverty ◽  
Farm Size ◽  
Primary Data ◽  
Poverty Index ◽  
Multidimensional Poverty Index ◽  
South West ◽  
Binary Logit ◽  
Poverty Status

AbstractIn this study we analysed the effect of the reward of internal migration on the poverty status of rural households in South-West Nigeria. The types and channels of internal remittances received by rural households as well as the poverty profile and effect of internal remittances on the poverty status of rural households in South-West, Nigeria were assessed. Structured questionnaire was used to obtain primary data from respondents. Data were analysed using descriptive statistics, Multidimensional Poverty Index and Binary Logit regression. Findings revealed that 56.2% of the household heads were male, 67.4% were married, 42.3% had primary education and 58.3% received internal remittances through personal delivery (69%) with a mean age and household size of 55 years and 5 persons, respectively. However, based on Multidimensional Poverty Index benchmark of 0.333, 80.0% of the rural households were poor with a poverty intensity of 0.863. Binary Logit showed that age squared, remittance receipt, rearing of small livestock and farm size increased households’ likelihood of escaping poverty. In conclusion, internal remittances reduced poverty of rural households in the study area and as such continuous flow of remittances into rural households should be enhanced in order to facilitate improved standard of living.

Role of Finance in Resource use Efficiency and Constraints in Banana Cultivation in Uttar Pradesh

2020 ◽  
pp. 437-441
Keyword(s):  
Resource Use ◽  
Uttar Pradesh ◽  
Sampling Technique ◽  
Farm Size ◽  
Primary Data ◽  
Resource Use Efficiency ◽  
Regular Source ◽  
Block Level ◽  
Use Efficiency ◽  
Secondary Information

The study was conducted using purposive cum random sampling technique and two hundred respondents comprised of 100 each borrowers and non-borrowers were selected from two block of district including marginal, small and medium categories of farm size. Primary data were collected through personal interview technique and required secondary information was taken from the record available at district and block level. Simple tabular and functional analysis and Garrett ranking were done to draw inferences. As per the result obtained from the study, no much difference was seen between the resource use efficiency of borrower and non-borrower farms and constraints faced by borrower. Since banana is a cash crop and it needs initial costs for its establishment, and after harvesting the crop regular source of income was generated by selling of suckers (seed) plant and its fruits. It’s by-product, leaves, etc. also used for various purposes. Minute inspection of the analysis showed that finance played important role for initiating the cultivation of banana crops showed the resource use efficiency that there is no considerable difference found on sample farms of borrower and non-borrower categories. Constraints faced by majority of the farmers were mainly delay in disbursement of loan and lack of the repayment period insufficient and improper management for withdraws on KCC.

scholarly journals Determinants of Rural Out-Migration in Habru District of Northeast Ethiopia

2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
Beneberu Assefa Wondimagegnhu ◽  
Mesfin Eshetu Zeleke
Keyword(s):  
Rural Communities ◽  
Sampling Technique ◽  
Positive Outcome ◽  
Individual Characteristics ◽  
Primary Data ◽  
Scarce Resources ◽  
Northeast Ethiopia ◽  
Household Heads ◽  
Nonfarm Employment ◽  
Land Size

Migration has become a cause of concern at the global, regional, and national levels. Like the case of many developing countries, Ethiopia has been facing increasing challenges related to rural out-migration. This study aimed to analyze factors that determine rural communities’ decision to migrate to internal and international destinations in Habru district of Northeast Ethiopia. Stratified sampling technique has been employed to select a total of 200 household heads in three agroecologies of the study area. Structured questionnaires have been used as a principal primary data collection method and logistic regression has been employed for analysis. The results of the study showed that intravillage conflict, absence of relief assistant, livestock ownership, farm land size, access to information, and household and individual characteristics including family size, sex, and age of the migrants are the dominant determinant factors for rural out-migration. Migration can have a positive outcome in improving livelihoods if comprehensive and holistic policies and strategies are in place. There is also a need to strengthen the link between rural development policy and the disadvantaged groups by designing and implementing different livelihood alternatives including reducing pressure on scarce resources particularly land, integrating health and education services, and creating nonfarm employment opportunities.

scholarly journals Determinants of Households’ Market Participation around Community Milk Cooling Plants, Western Kenya

2018 ◽  
Vol 10 (3) ◽  
pp. 204
Author(s):  
Justus I. Emukule ◽  
Mary J. Kipsat ◽  
Caroline C. Wambui
Keyword(s):  
Dairy Cow ◽  
Sampling Technique ◽  
Structured Interview ◽  
Household Size ◽  
Sub Saharan Africa ◽  
Primary Data ◽  
Market Participation ◽  
Household Characteristics ◽  
Sub Saharan ◽  
Multistage Sampling

Market participation in sub-Saharan Africa has been assessed mainly based on already producing households by looking at whether they sold or not, and if they sold, what quantities. The objective of this study was to determine the socio economic factors that influenced households’ decisions on market participation in terms of dairy cow ownership and quantity of milk sold while taking into consideration the non-producers using Heckman two stage model. The model allowed for not only determination of the effects of household characteristics on volume of milk surplus sold by already producing households but also drew inferences on the effect of household characteristics on probabilities of dairy cow ownership whileadding new information to literature by generating the truncation effect. A multistage sampling technique was used to select 544 producer and non-producer households and primary data collected using a semi structured interview schedule through personal interviews. From the results, probit marginal effects for dairy cow ownership were associated positively and statistically significant with household size, the level of education and land size owned by the households. The Heckman selection estimates revealed that increased number of dairy cows per household positively influenced the volumes of milk sold, while household size influenced negatively the quantity of milk sold. In conclusion, milk sales conditional on dairy cow ownership suffered from negative selectivity bias whereby a household with sample average characteristics who selected into dairy cow ownership secured 40% lower quantity of milk sold than would a household drawn at random.

scholarly journals Value Chain Analysis of Artisanal Fishing in Ilaje Local Government Area of Ondo State, Nigeria

2019 ◽  
pp. 1-7
Author(s):  
O. O. Ilemobayo ◽  
J. O. Ijigbade
Keyword(s):  
Local Government ◽  
Value Chain ◽  
Sampling Technique ◽  
Household Size ◽  
The Other ◽  
Primary Data ◽  
Artisanal Fishing ◽  
Gross Margin ◽  
Socioeconomic Characteristic ◽  
Net Return

To bridge the demand supply gap in the Nigerian fishing industry, the value chain analyses in artisanal fishing in the coastal area of Ondo States were investigated. Primary data was used in the study. Purposive sampling technique was used to select four fishing communities in Ilaje local government, where 35 (fishermen, processors and marketers) were each selected randomly from the communities. Data were analyzed using Descriptive Statistics and Gross Margin Analysis. The socioeconomic characteristic indicated that 68.6% of the fishermen, 77.2% processors and 65.7% marketers were less than 50 years of age. Result revealed that all the fishermen were male, 91.2 % processors and 97.10% marketers were female. 62.9% of the fishermen have household greater than 4, the processors has 54.3% household size above 4 and 60% of the marketers have household size above 4. 94.3% of the fishermen have one form of education or the other, 77.1% of the processors have one form of education or the other and 65.7% of the marketers were also educated. All the marketers are into one association or the other. Budgeting analysis indicated positive margin by the two categories of marketers was ₦300.54 and ₦1,866.00 per basket respectively, a net return of 1.04 and 1.30 respectively. Processors had a positive gross margin of ₦43.871.54 and a net return of 1.12. Most influential actor is the marketer.

scholarly journals Analysis of Household Participation in Urban Agriculture: Empirical Evidence from Urban Households in Kogi State, Nigeria

2020 ◽  
pp. 23-31
Author(s):  
M. K. Ibrahim ◽  
M. Haruna ◽  
U. M. Shaibu
Keyword(s):  
Urban Agriculture ◽  
Household Income ◽  
Sampling Technique ◽  
Simple Random Sampling ◽  
Primary Data ◽  
Easy Access ◽  
Farm Income ◽  
Urban Farm ◽  
Household Heads ◽  
Sufficient Food

The study analysed household participation in urban agriculture in Kogi State, Nigeria. It specifically; described the socioeconomic characteristics of the respondents; determined the factors that influence household participation in urban agriculture; and determined the effect of urban agriculture on household income. Simple random sampling technique was used to select 60 respondents each from four purposively selected peri-urban/urban centres in Kogi State: Lokoja (Zone A), Anyigba (Zone B), Okene (Zone C), and Idah (Zone D). Primary data obtained through questionnaire administration were analysed using descriptive and inferential statistical tools. Findings from the study revealed that 61.7% of the respondents were males and a mean age of 43 years was recorded. Married (90%) household heads dominated the respondents with a mean household size of 7 members. Education (β = -0.862), dependent (β = 1.904), marital status (β = 2.544), access to sufficient food (β = -2.495), employment status (β = 1.307) and access to land (β = 0.505) statistically influenced household participation in urban agriculture, while the OLS output indicated that urban farm income (β = 17.539) and non-farm income (β = 848.798) had significant effect on total household income. The study concluded that urban agriculture has the potential of improving the livelihood of urban dwellers. The study therefore recommends the integration of urban agriculture into urban development plan; easy access to land and other production inputs.

scholarly journals Nexus between Poverty and Child Labor: A Case Study in Narayanganj Area of Bangladesh Using Binary Logistic Regression

2021 ◽  
Vol 7 (11) ◽  
pp. 194
Author(s):  
Shamima Akter ◽  
Wasim Akram
Keyword(s):  
Logistic Regression ◽  
Child Labor ◽  
Odds Ratio ◽  
Group Discussion ◽  
Binary Logistic Regression ◽  
Sampling Technique ◽  
Drop Out ◽  
Poor People ◽  
Binary Logistic Regression Model ◽  
Household Heads

<p>The purpose of the study is to see how poverty influences child labor. To carry out the study, moderate poor people have been considered as respondents. Kalibazar and Langalband regions of Narayanganj district have been selected. Random sampling technique and Focused Group Discussion with children have been taken to conduct the study. Data has been collected from 50 Household Heads and 50 Children (male and female). For economic analysis, the Binary Logistic Regression model has been undertaken to see the relationship between poverty and child labor.  The analysis shows that the odds ratio indicates that drop-out children from school are 11.34 times more likely to go for taking the occupation of child labor due to poverty (major cause) than those children who have been dropped out due to other reasons (reference category). The study also shows that the families having no loan are 0.444 times less likely to go for child labor due to major causes (poverty) than that of the families having a loan. Moreover, the odds ratio corresponding to the children who use their income to help their families is 3.26. It means that the children who use their income for family purposes go 3.26 times more likely to take the occupation of child labor due to a major cause (poverty) than those children who do not use their income for family purposes. At the same time, the children who use their income for treatment purposes go 1.45 times more likely to take the occupation of child labor due to poverty (a major cause) than those children who do not use their income for treatment purposes.</p>

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