Gamma Regression for the Poverty Rate in Türkiye

Müge Borazan; Serpil Aktaş

Makale detayları

Gamma Regression for the Poverty Rate in Türkiye

Yazarlar:

Müge Borazan | Serpil Aktaş

Yayıncı:

Istanbul University

Ana Başlıklar:

İstatistik (Diğer)

Dergi:

EKOIST Journal of Econometrics and Statistics Issue 42, pp.22-35

Belge Tipi:

Makale

Yayın Tarihi:

6/2025

Belge Dili:

İngilizce

Document ID (Org No.):

2001356011

pISSN:

2651-396X

Anahtar kelimeler:

Özet:

 The family of gamma regression models makes the assumption that a linear predictor with unknown coefficients and a link function, such as an identity, inverse, or logarithmic function, are related to a set of predictors by means of the mean of the dependent variable with a gamma distribution. This model also has a shape parameter, which can either depend on a collection of regressors via a link function or be constant like a logarithm function. The analysis of positive random variables can make extensive use of the gamma distribution. When the dependent variable has a real value between 0 and , gamma regression makes sense. In this study, a gamma regression model is used to examine the relationship between poverty rates and household education levels in Türkiye for the period 20062023. The Turkish Statistical Institute TurkStat provided the study data set. According to TurkStats definition of poverty, which is 50 of the comparable household disposable median income, the poverty rates in the data set indicate the percentage of people who are at danger of becoming impoverished. The Gamma Regression Model reveals that the poverty rate is significantly influenced by education level. Furthermore, there are notable variations in poverty rates among education levels, according to the post hoc anlayses we performed to compare poverty rates across educational levels.

 The family of gamma regression models makes the assumption that a linear predictor with unknown coefficients and a link function, such as an identity, inverse, or logarithmic function, are related to a set of predictors by means of the mean of the dependent variable with a gamma distribution. This model also has a shape parameter, which can either depend on a collection of regressors via a link function or be constant like a logarithm function. The analysis of positive random variables can make extensive use of the gamma distribution. When the dependent variable has a real value between 0 and , gamma regression makes sense. In this study, a gamma regression model is used to examine the relationship between poverty rates and household education levels in Türkiye for the period 20062023. The Turkish Statistical Institute TurkStat provided the study data set. According to TurkStats definition of poverty, which is 50 of the comparable household disposable median income, the poverty rates in the data set indicate the percentage of people who are at danger of becoming impoverished. The Gamma Regression Model reveals that the poverty rate is significantly influenced by education level. Furthermore, there are notable variations in poverty rates among education levels, according to the post hoc anlayses we performed to compare poverty rates across educational levels.

 The family of gamma regression models makes the assumption that a linear predictor with unknown coefficients and a link function, such as an identity, inverse, or logarithmic function, are related to a set of predictors by means of the mean of the dependent variable with a gamma distribution. This model also has a shape parameter, which can either depend on a collection of regressors via a link function or be constant like a logarithm function. The analysis of positive random variables can make extensive use of the gamma distribution. When the dependent variable has a real value between 0 and , gamma regression makes sense. In this study, a gamma regression model is used to examine the relationship between poverty rates and household education levels in Türkiye for the period 20062023. The Turkish Statistical Institute TurkStat provided the study data set. According to TurkStats definition of poverty, which is 50 of the comparable household disposable median income, the poverty rates in the data set indicate the percentage of people who are at danger of becoming impoverished. The Gamma Regression Model reveals that the poverty rate is significantly influenced by education level. Furthermore, there are notable variations in poverty rates among education levels, according to the post hoc anlayses we performed to compare poverty rates across educational levels.

 The family of gamma regression models makes the assumption that a linear predictor with unknown coefficients and a link function, such as an identity, inverse, or logarithmic function, are related to a set of predictors by means of the mean of the dependent variable with a gamma distribution. This model also has a shape parameter, which can either depend on a collection of regressors via a link function or be constant like a logarithm function. The analysis of positive random variables can make extensive use of the gamma distribution. When the dependent variable has a real value between 0 and , gamma regression makes sense. In this study, a gamma regression model is used to examine the relationship between poverty rates and household education levels in Türkiye for the period 20062023. The Turkish Statistical Institute TurkStat provided the study data set. According to TurkStats definition of poverty, which is 50 of the comparable household disposable median income, the poverty rates in the data set indicate the percentage of people who are at danger of becoming impoverished. The Gamma Regression Model reveals that the poverty rate is significantly influenced by education level. Furthermore, there are notable variations in poverty rates among education levels, according to the post hoc anlayses we performed to compare poverty rates across educational levels.

Makale detayları

Gamma Regression for the Poverty Rate in Türkiye

Yazarlar:

Müge Borazan | Serpil Aktaş

Yayıncı:

Istanbul University

Ana Başlıklar:

İstatistik (Diğer)

Dergi:

EKOIST Journal of Econometrics and Statistics Issue 42, pp.22-35

Belge Tipi:

Makale

Yayın Tarihi:

6/2025

Belge Dili:

İngilizce

Document ID (Org No.):

2001356011

pISSN:

2651-396X

Gamma regression

parameter estimation

poverty

poverty rate

Sayı

Makale detayları

Gamma Regression for the Poverty Rate in Türkiye

Yazarlar: Müge Borazan | Serpil Aktaş

Yayıncı: Istanbul University

Ana Başlıklar: İstatistik (Diğer)

Dergi: EKOIST Journal of Econometrics and Statistics Issue 42, pp.22-35

Belge Tipi: Makale

Yayın Tarihi: 6/2025

Belge Dili: İngilizce

Document ID (Org No.): 2001356011

pISSN: 2651-396X

Gamma regression

parameter estimation

poverty

poverty rate

Sayı

Yazarlar:

Müge Borazan | Serpil Aktaş

Yayıncı:

Istanbul University

Ana Başlıklar:

İstatistik (Diğer)

Dergi:

EKOIST Journal of Econometrics and Statistics Issue 42, pp.22-35

Belge Tipi:

Makale

Yayın Tarihi:

6/2025

Belge Dili:

İngilizce

Document ID (Org No.):

2001356011

pISSN:

2651-396X