Regularized Ordinal Regression with Elastic Net Approach (Case Study: Poverty Modeling in Yogyakarta Province 2018)

Autor: Pardomuan Robinson Sihombing, Yudhie Andriyana, Bertho Tantular
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: Cauchy: Jurnal Matematika Murni dan Aplikasi, Vol 6, Iss 4, Pp 296-308 (2021)
Druh dokumentu: article
ISSN: 2086-0382
2477-3344
DOI: 10.18860/ca.v6i4.11758
Popis: Generally, modeling poverty aims to obtain the best criteria for assessing poverty status. There are two approaches to model the factors that affect poverty, namely consumption approach and discrete choice model. The advantage of the discrete choice model compared to the consumption approach is that the discrete choice model provides a probabilistic estimate for classifying samples into different poverty categories. This study aims to examined how the factors that affect poverty in Yogyakarta through Regularized Ordinal Regression with elastic net approach both for parallel, non-parallel, and semi-parallel models. The data used in this study is Susenas March 2018 for Yogyakarta provinces. The result of this study shows that the best discrete choice model for Yogyakarta’s modelling is the parallel model. Households that live in villages, have a large number of household members, are headed by women, have elderly household heads, have low education, and work in the primary sector tend to be more vulnerable to poverty. Therefore, a simultaneous policy with inclusive economic development is needed to reduce cross-border, cross-gender, and cross-sector inequality
Databáze: Directory of Open Access Journals