Estimation and Comparative Analysis of Generalized Ordered Logit and Multinomial Logit Models

Hilmi Karaalioğlu

Article Details

Estimation and Comparative Analysis of Generalized Ordered Logit and Multinomial Logit Models

Authors:

Hilmi Karaalioğlu

Publisher:

Alanya Alaaddin Keykubat Üniversitesi

Main Topics:

Yöneylem | Ekonometrik ve İstatistiksel Yöntemler | Ekonomik Modeller ve Öngörü | Uygulamalı Mikro Ekonometri

Journal:

Alanya Akademik Bakış Vol.8 Issue 1, pp.1-14

Document Type:

Article

Publication Date:

1/2024

Document Language:

English

Document ID (Org No.):

2001311075

pISSN:

2651-4192

Keywords:

Abstract:

 Although both OLOGIT and MLOGIT models are from the logit model family and their mathematical form is similar, these models have many different aspects besides their similarities. In this context, two dependent variables, one nominal and the other ordinal, measuring the same information were placed in the same data set and these models were compared from various perspectives by making these variables dependent variables. These are the significance of the parameters, their suitability for estimation, ease of implementation, and the provision of assumptions. During the implementation, GOLOGIT was put into practice because Ordered Logit did not provide the parallel regression assumption. Although the number of significant parameters is the same in both models, GOLOGIT stands out in terms of providing detailed analysis for each level of each qualitative independent variable and making fewer model estimations than MLOGIT.

 Although both OLOGIT and MLOGIT models are from the logit model family and their mathematical form is similar, these models have many different aspects besides their similarities. In this context, two dependent variables, one nominal and the other ordinal, measuring the same information were placed in the same data set and these models were compared from various perspectives by making these variables dependent variables. These are the significance of the parameters, their suitability for estimation, ease of implementation, and the provision of assumptions. During the implementation, GOLOGIT was put into practice because Ordered Logit did not provide the parallel regression assumption. Although the number of significant parameters is the same in both models, GOLOGIT stands out in terms of providing detailed analysis for each level of each qualitative independent variable and making fewer model estimations than MLOGIT.

 Although both OLOGIT and MLOGIT models are from the logit model family and their mathematical form is similar, these models have many different aspects besides their similarities. In this context, two dependent variables, one nominal and the other ordinal, measuring the same information were placed in the same data set and these models were compared from various perspectives by making these variables dependent variables. These are the significance of the parameters, their suitability for estimation, ease of implementation, and the provision of assumptions. During the implementation, GOLOGIT was put into practice because Ordered Logit did not provide the parallel regression assumption. Although the number of significant parameters is the same in both models, GOLOGIT stands out in terms of providing detailed analysis for each level of each qualitative independent variable and making fewer model estimations than MLOGIT.

 Her ne kadar OLOGIT ve MLOGIT modelleri logit model ailesine ait olsalar ve matematiksel yapıları benzer olsa da bu modeller benzerlikleri dışında birçok farklı yönü de içermektedir. Bu bağlamda, aynı bilgiyi ölçen biri nominal diğeri sıralı iki bağımlı değişken, aynı veri setine yerleştirilmiş ve bu değişkenler bağımlı değişkenler yapılarak bu modeller çeşitli perspektiflerden karşılaştırılmıştır. Bu perspektifler arasında parametrelerin anlamlılığı, tahmini için uygunluk, uygulama kolaylığı ve varsayımların sağlanması yer almaktadır. Uygulama sırasında, Paralel Regresyon Varsayımını sağlamadığı için Sıralı Logit tercih edilemediğinden GOLOGIT uygulamaya konulmuştur. Her iki modelde de anlamlı parametre sayısı aynı olsa da GOLOGIT, her bir kalitatif bağımsız değişkenin her düzeyi için ayrıntılı analiz sağlaması ve MLOGITten daha az model tahmini yapması açısından öne çıkmaktadır.

Article Details

Estimation and Comparative Analysis of Generalized Ordered Logit and Multinomial Logit Models

Authors:

Hilmi Karaalioğlu

Publisher:

Alanya Alaaddin Keykubat Üniversitesi

Main Topics:

Yöneylem | Ekonometrik ve İstatistiksel Yöntemler | Ekonomik Modeller ve Öngörü | Uygulamalı Mikro Ekonometri

Journal:

Alanya Akademik Bakış Vol.8 Issue 1, pp.1-14

Document Type:

Article

Publication Date:

1/2024

Document Language:

English

Document ID (Org No.):

2001311075

pISSN:

2651-4192

Revisit intention

Parallel Lines

Multinomial logit

Generalized Ordered logit

IIA AssumptionYeniden Ziyaret Niyeti

Paralel Regresyon

Multinomial Logit

Genelleştirilmiş Sıralı Logit

IIA Varsayımı

Issues

Article Details

Authors: Hilmi Karaalioğlu

Publisher: Alanya Alaaddin Keykubat Üniversitesi

Main Topics: Yöneylem | Ekonometrik ve İstatistiksel Yöntemler | Ekonomik Modeller ve Öngörü | Uygulamalı Mikro Ekonometri

Journal: Alanya Akademik Bakış Vol.8 Issue 1, pp.1-14

Document Type: Article

Publication Date: 1/2024

Document Language: English

Document ID (Org No.): 2001311075

pISSN: 2651-4192

Issues

Authors:

Hilmi Karaalioğlu

Publisher:

Alanya Alaaddin Keykubat Üniversitesi

Main Topics:

Yöneylem | Ekonometrik ve İstatistiksel Yöntemler | Ekonomik Modeller ve Öngörü | Uygulamalı Mikro Ekonometri

Journal:

Alanya Akademik Bakış Vol.8 Issue 1, pp.1-14

Document Type:

Article

Publication Date:

1/2024

Document Language:

English

Document ID (Org No.):

2001311075

pISSN:

2651-4192