چکیده:
urban poverty has long been a concern of urban and development debates, and has been an important focus in social science research. Informal settlement in Mashhad city is highlighted because of its wide spreading and severity. This study aimed to determine the causes of urban poverty in informal settlement regions. The data were collected from household level questionnaire in 2016 and the Logistic Regression Model was performed to identify the determinants of urban poverty. The data were obtained from 220 households who settled in Shahid Ghorbani quarter using the questionnaire through the Systematic Random technique. Nearly 87 of households of the studied area were below absolute poverty line and 20 of them were below extreme poverty line. Given that all household heads in the sample were married men, significant relationships were observed between poverty and characteristics like “age of household head”, “being self-employed”, “household size”, “the ratio of worker in household”, “ownership of house” and “having social security”, while factors like “Access to services and infrastructures” and “education” had no significant impact on the likelihood of moving out of poverty. The results also revealed that if the household head is older and self–employed, the likelihood of being poor is gradually diminished. Also if the family members had some kind of social security or owned their houses, household welfare would improve; however, increasing in household size and ratio of worker in household would decrease household welfare. Eventually, the marginal effects of variables were interpreted.
خلاصه ماشینی:
The Determinants of Poverty in Informal Settlement Areas of Mashhad (Case Study: Shahid Ghorbani Quarter) Sahar Soltani1, Javad Baraty*2, Farzaneh Razaghian3, Simin Foroughzadeh4 Received: 2017, November 14 Accepted: 2018, January 5 rban poverty has long been a concern of urban and development debates,and has been an important focus in social science research.
The data were collected from household level questionnaire in 2016 and the Logistic Regression Model was performed to identify thedeterminants of urban poverty.
Given that all household heads in the sample were married men, significant relationships were observed between poverty and characteristics like “age of household head”, “being self-employed”, “household size”, “the ratio of worker in household”, “ownership of house” and “having social security”, while factors like “Access to services and infrastructures” and “education” had no significant impact on the likelihood of moving out of poverty.
This study aimed to examine the factors generating poverty in Shahid Ghorbani quarter in Mashhad city using Logit regression model.
Their findings suggested that factors like being man, being married, higher level of education, higher level of age, improvement in health status, being employer and self-employed, having social security will reduce the probability of poverty in Turkey.
Dartanto and Nurkholis (2013) used an ordered Logit model to examine the determinants of poverty dynamics in Indonesia by using the National Socio-Economic Survey balanced-panel data sets of 2005 and 2007.
Dependent variable was defined as households who were below or beyond of Orshansky Poverty Thresholds in 2016 in the studied quarter of informal settlement in Mashhad.