Determinants Of Urban Poverty Research Articles

Determinants of Household Poverty: The Case of Shashemene Town, Oromia, Ethiopia

Ethiopia is one of the world’s poorest countries by any standards. As a result government, multilateral agencies and other stakeholders consider poverty as their priority issues. This study is the study on determinants of urban poverty with the objective of identifying the poor from non poor households and main factors those push them to the poverty trap. Cost of Basic Needs (CBN) approach is used to calculate food poverty line and total poverty line respectively. Out of the 381 surveyed household heads, 170(44.62%) of them were found poor. A total of 381 respondents were included in the survey and the main data for the study was collected through structured questionnaire. Binary Logit model was employed to analyze the determinants of households’ poverty. Fourteen explanatory variables were taken in to account in the model’s equation. The result of logit regression using STATA13.1 software confirmed that nine variables were found statistically significant; age of households (1%), income of house hold head (1%), marital status of households(1%), house tenure of households(1%), household family size (1%), households employment status(1%),educational level of households(5%),access to credit(5%) and saving(10%). From these significant variables; age of households, households’ family size, households’ marital status and households housing tenure were positively correlated with probability of being poor. While households education, households income, households saving, households employment status and households access to credits were negatively correlated with probability of being poor. Two sample t-test and chi-squared test was employed to compare non-poor and poor. The poverty head count ratio is extensive among the surveyed households that calls for urgent interventions aimed at solving the problems of the poor. Hence efforts should be made to increase the real income of households through well paying and better job creation by the set up of micro and small scale enterprises, with the increased provision of economic and social infrastructure. Thus, stakeholder interventions to tackle the determinant factors are important measures to be undertaken. Keywords: Poverty, Household, Logit Model, Shashemene, Ethiopia DOI: 10.7176/JESD/12-7-01 Publication date: April 30 th 2021

Determinants of Urban Poverty in Oromia: A Case Study in Some Selected District, Ethiopia

The study was conducted in south west Shewa zone districts, Oromia National Region, Ethiopia. Stratified sampling techniques were applied in order to obtain a representative sample were selected to collect data by using these strata since in study there were constituted 3 urban areas were selected from a total of 4 towns in Waliso districts. Based on this condition sampling will be conducted separately in each subgroup or stratum. Descriptive statistics and binary logit were employed to determine factors that influence the economic status of households. A sum of twelve explanatory variables for the binary logit model was used, out of which eight variables were found to significantly affect the economic returns of households at 5%. These are: household family size, education of household head, the gender of household head, marital status, age of household head, , income of household head, house ownership, previous residence, and four of the following were at 10% like household health status, household head occupation, dependency ratio and saving of household and the other variables like household health status, household head occupation, and dependency ratio were not significant at a maximum of 10% significance level . The study recommends that the strong negative relationship between income and the probability of being poor point out that there must be a need to consider households income character by government and non-government organization in designing policies targeted to curb urban poverty intervening to household health status, household head occupation, dependency ratio and saving of household. Keywords: Rural poverty, Binary Logit Model, Waliso district. DOI: 10.7176/JPID/56-03 Publication date: November 30 th 2020

Determinates of Urban Poverty at Household Level: The Case of Wolaitta Soddo Town, SNNPRS, Ethiopia

Poverty is daily experience of citizens in Ethiopia and the government has implemented different poverty reducing policies and strategies in the intention to reach middle income countries in the coming 7 years. This Study aimed at analyzing the determinants of urban poverty At household level in terms of demographic, economic and social practices in soddo Town. The study was conducted under cross sectional research design. The approach that was used is a mixed approach which makes the use of both quantitative and qualitative methods. Samples of 227 households were drawn from the target population by adopting systematic random sampling technique and 18 of them were discarded from further consideration due to lack of response. Data collecting instruments like questionnaire, semi-structured interview, document analysis and focus group discussions were used to collect data. .A Logistic regression model was employed and estimated based on the primary data, with the probability of a household being poor as a dependent variable and a set of demographic and socioeconomic variables as the explanatory parameters. By making use of Food Energy Intake (FEI) approach the surveyed households are identified as the poor and non-poor. Based on this, Birr 3246 was computed as food poverty line per adult equivalent per month and out of the 209 respondent household heads, 94(45%) were found to be poor. The poverty gap index of 8 percent and poverty severity index of 3 percent were estimated. The variables that are positively correlated with the probability of being poor are family size whose number of members are 5 and above, education, age, sex, saving, electricity connection, unemployment and marital status. The variables that are negatively correlated with the probability of being poor are family size whose numbers of members are less than 5, house tenure, water pipe connection, employment status. These calls for urgent interventions aimed at curbing the problems of the people through creating employment opportunities, family planning, provision of market based short term trainings, empowering females and distribution of social service, improving education services, health services, and creating access to credit facilities need to be promoted for poor urban household in the study area. Keywords: - Poverty, poverty line, poverty incidence, poverty gap, poverty severity DOI : 10.7176/JAAS/60-02 Publication date: January 31 st 2020

Determinants of Urban Poverty in Muklami Town of West Wellega Zone of Oromia, Ethiopia

Ethiopia is known all over the world where citizens live in very chronic condition of poverty. Urban poverty has been given less attention on research and development agenda of Ethiopia and particularly, for medium towns like Muklami. The purpose of this study is to measure the magnitude and identify determinants of poverty in Muklami town. Both primary and secondary data sources were use. A cross-sectional survey 143 household heads were carried-out by a using proportional random sampling method. To calculate total poverty line, a Cost of Basic Needs (CBN) approach was utilized. In addition both simple descriptive statistics and econometrics model such as Logit model were employed to analyses the data. The result to the study shows that head count poverty, poverty gap and severity of poverty indices are 35.6%, 12.7%, and 50.8%, respectively. The variables that are positively correlated with the probability of being poor are: sex, family size, health status, and house tenure. Variables negatively correlated with the probability of being poor are: income, educational level, marital status, age, employment status, saving habit, water source, and access to credit. Based on the result of the study, the following recommendation was made. Efforts should be made to raise the real income of households through well-paying and steady job creation by the setup of micro and small scale enterprises, with the increased provision of economic and social infrastructure of houses, education, and better water sanitation services for poverty reduction. Keywords: Urban Poverty, Cost of Basic Needs, Logit model and Muklami town DOI : 10.7176/JRDM/57-01 Publication date :July 31 st 2019

Assessment of the Determinants of Urban Household Poverty in North Shewa Zone, Ethiopia: Evidence from Debre Berhan Town

Poverty has turned out to be a great global social and economic problem. In Ethiopia, it is multifaceted and deep rooted. The strategies aimed at reducing poverty need to identify and analyze the factors that influence poverty. In this regard, this study was conducted to identify and analyze the extent and determinants of urban poverty in the case of Debre Berhan town. The study made use of cross-sectional household survey data collected from total of 333 randomly selected households in three urban Kebeles of the town. The collected data were analyzed using FGT index and logistic regression. The binary logit model was fitted to identify determinants of poverty. In this case the probability of a household being poor is taken as a dependent variable whiles the set of demographic and socio economic variables were explanatory variables. Using cost of basic needs approach the study found that total poverty line (food and non-food poverty line) of the area using the price deflated national average poverty line is 5,220 birr per year per adult equivalent. Using this poverty line as bench mark the study indicated that 62 percent of sample households are poor. The head count ratio, poverty gap, and severity indices of the survey households were 0.62, 0.14 and 0.30, respectively. Econometric results of the binary logit regression model revealed that age of household head, education, saving, access to credit, and remittance were found to be as theoretically expected, have negative and significant effect on the probability of a household being poor whereas age square of head of household and dependency ratio alone were found to have positive and significant effect on poverty. Since most of the poor are concentrated around the poverty line as we observe from the poverty gap, policies should focus on absolute poverty rather than relative poverty among the poor. Promoting adult education and saving habit of households, and ensure better access to formal credit through micro credit financing and banks, are indispensable policy interventions to better target urban poverty. Keywords: Urban household poverty, Per Capita Consumption, Determinants, Logistic Regression. DOI : 10.7176/JPID/50-03 Publication date :June 30 th 2019

Determinants of Urban Poverty: The Case of Medium Sized City in Pakistan

The process of urbanisation has dual impact on the development process of an economy. Initially, it encourages the workers to switch from low productive sector i.e. agriculture to high productive sectors like services and manufacturing [Becker, et al. (1994)]. Subsequently, it generates formidable problems for residents by depriving them of access to essential basic needs [Egziabher (2000)]. It is also observed that the poor try to urbanise faster as compared to the whole population [Ravallion (2007)] and this urbanisation process leads toward the emergence of urban poverty. Urban poverty is distinct from the rural poverty with respect to its incidence, economic, demographic and political aspects. The urban poverty can be controlled by developing the clear understanding of its nature, magnitude and intensity

Urban poverty in Vietnam: determinants and policy implications

PurposeThe objective of the paper is to examine the profile and determinants of urban poverty in the two largest cities in Vietnam – Hanoi and Ho Chi Minh. The paper also investigates the dynamic aspect of urban poverty in Vietnam.Design/methodology/approachThe authors use regression and data from the 2009 Urban Poverty Survey to examine the determinants of poverty in Vietnam. To analyse the poverty dynamics, an approach by Carter and May is used to decompose poverty into structural and stochastic poverty.FindingsUsing the poverty line of 12,000 thousand VND/person/year, the poverty incidence is estimated at 17.4 percent for Hanoi and 12.5 percent for Ho Chi Minh (HCM) City. There is a large proportion of the poor who are found stochastically poor. Hanoi has higher rates of structural poverty than HCM City. The proportion of structurally poor and stochastically non‐poor is rather small. Overall, the poor have fewer assets than the non‐poor. The poor also have poorer housing conditions, especially substantially lower access to tap water than the non‐poor. Heads of the poor households tend to have lower education and unskilled work than the heads of the non‐poor households.Originality/valueIn cities of Vietnam, a large proportion of the poor are found stochastically poor.

Does Higher Economic Growth Reduce Poverty and Increase Inequality? Evidence from Urban India

This paper calculates select urban inequality and poverty indices and finds their policy linkages. In addition, the determinants of urban poverty and inequality are estimated by using data of 52 large cities in India. The main results show that higher city economic growth and large city population agglomeration are associated with reduction in city poverty and increase in inequality between cities.