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All Journal Enthusiastic : International Journal of Applied Statistics and Data Science
Yudhani, Nidya Putri
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering Mathematics

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A Zero-Inflated Ordered Probit Approach to Modeling Household Poverty Levels Yudhani, Nidya Putri; Vita Ratnasari; Santi Puteri Rahayu
Enthusiastic : International Journal of Applied Statistics and Data Science Volume 5 Issue 1, April 2025
Publisher : Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/enthusiastic.vol5.iss1.art6

Abstract

This research addressed the limitations of the ordered probit (OP) regression model in handling data that contains an excessive number of zero responses. The zero-inflated ordered probit (ZIOP) model was employed to overcome this issue. This model separates the estimation of structural zeros and ordinal outcomes through two distinct components: a binary probit for zero inflation and an OP for ordered categories. Due to the absence of closed-form solutions, parameter estimation was conducted using the maximum likelihood estimation (MLE) method with the Berndt-Hall-Hall-Hausman (BHHH) iterative algorithm. The analysis was based on 4,067 household-level observations from Indonesia’s National Socio-Economic Survey, incorporating indicators of health, education, and standard of living derived from the multidimensional poverty index (MPI) framework. The result of the Vuong test (4.56) confirmed that the ZIOP model significantly outperformed the conventional OP model for zero-inflated ordinal data. Therefore, the ZIOP model is considered more appropriate for analyzing household poverty classifications with a high prevalence of zero observations.
Co-Authors Santi Puteri Rahayu Vita Ratnasari