scholarly journals Poverty Dynamics in Turkey: A Multinomial Logit Model

Ekonomika ◽  
2021 ◽  
Vol 100 (2) ◽  
pp. 133-143
Author(s):  
Senem Çakmak Şahin ◽  
İbrahim Engin Kılıç

The availability of longitudinal data allows researchers to analyse the dynamics of poverty. By using the Turkish Statistical Institute’s (TurkStat) Income and Living Conditions Survey micro dataset, we analyse the households’ long-term monetary poverty conditions. We categorise poverty as transitory and chronic and employ the multinomial logit method to analyse determinants of each types of poverty. Results indicate that education and household size are the most effective factors for reducing transitory poverty, and for chronic poverty, the most effective factors are having a regular job and having a skilled occupation; insurance, home ownership, and number of children are important determinants for both types of poverty.

2016 ◽  
Vol 7 (13) ◽  
pp. 253-241
Author(s):  
ابوذر پرهیزکاری ◽  
محمدمهدی مظفری ◽  
مهدی حسینی خدادادی ◽  
رویا پرهیزکاری ◽  
◽  
...  

2014 ◽  
Vol 23 (11) ◽  
pp. 2023-2039 ◽  
Author(s):  
Paat Rusmevichientong ◽  
David Shmoys ◽  
Chaoxu Tong ◽  
Huseyin Topaloglu

2008 ◽  
Vol 27 (3) ◽  
pp. 319-331 ◽  
Author(s):  
Leslie S. Stratton ◽  
Dennis M. O’Toole ◽  
James N. Wetzel

2019 ◽  
Vol 11 (10) ◽  
pp. 39
Author(s):  
Jean D. Gumirakiza ◽  
Mara E. Schroering

Online shopping is changing ways in which offline markets operate. As the online shopping for fresh produce takes off, it is important to investigate its effects on existing physical market outlets. The main objective for this study is to explain how often online shoppers attend farmers’ markets. The study uses data that was collected in 2016 from a sample of 1,205 consumers residing in the south region of the United States who made at least two online purchases within six months prior to participating in this study. This study employed a multinomial Logit model and Stata was used to run the regression. Results show that the majority of these online shoppers never attended a farmers’ market. The relative probabilities for the online shoppers to “never” attend farmers’ markets, attend “occasionally”, and “frequently” are 0.54, 0.28, and 0.18 respectively. We found that the lack of awareness, inconvenient place and/or time, and low interests are major reasons for nonattendance. This study suggests that farmers’ markets could greatly benefit by developing marketing strategies targeting online shoppers.


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