Volume 19, Issue 4 (2019)
QJER 2019, 19(4): 51-76 |
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gerivani F, Falahi M, ahmadai shadmehri M T, Raghfar H. Dynamic Poverty Analysis in Urban Areas of Iran Based on Synthetic Panel Data Method. QJER 2019; 19 (4) :51-76
URL: http://ecor.modares.ac.ir/article-18-21107-en.html
URL: http://ecor.modares.ac.ir/article-18-21107-en.html
1- Ph.D. Candidate of Economics, Ferdowsi University of Mashhad
2- Professor of Economics, Faculty Member, Ferdowsi University of Mashhad ,falahi@um.ac.ir
3- Associate Professor, Department of Economics -ferdowsi university, Mashhad, Iran
4- Faculty Member, Alzahra University, Tehran, Iran
2- Professor of Economics, Faculty Member, Ferdowsi University of Mashhad ,
3- Associate Professor, Department of Economics -ferdowsi university, Mashhad, Iran
4- Faculty Member, Alzahra University, Tehran, Iran
Abstract: (6170 Views)
Panel data constitutes a cornerstone for dynamic analysis, especially in poverty mobility studies. In developing countries such as Iran, household income and expenditure data are collected on a cross-sectional basis because of various reasons. As a result, households’ panel data are not available. Due to the concerns of policymakers in understanding the status of mobility of the poor, researchers have developed several approaches to study poverty mobility among countries using cross-sectional data. In 2013, the World Bank's Poverty Studies Group introduced a synthetic panel data method for poverty dynamics analysis, which provides relatively accurate estimates of poverty mobility. First, the present study calculates the absolute poverty line of urban areas of Iran in 2012, 2015 and 2016. Then, it uses the method of synthetic panel data in order to study the status of poverty mobility. The results show that there is a kind of status dependency in the urban poverty, so that the poor (non-poor) households in 2012/ 2015 were also poor (non-poor) in 2016 with a probability of more than 80 percent. Only with a probability of less than 20 percent, the poor (non-poor) households in 2012/2015 were non-poor (poor) in 2016.
Article Type: Original Research |
Subject:
Economics
Received: 2018/05/21 | Revised: 2019/12/21 | Accepted: 2019/12/18 | Published: 2019/12/18
Received: 2018/05/21 | Revised: 2019/12/21 | Accepted: 2019/12/18 | Published: 2019/12/18
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