A STUDY OF SMALL AREA ESTIMATION TO MEASURE MULTIDIMENSIONAL POVERTY WITH MIXED MODEL POISSON, ZIP, AND ZINB

  • Satria June Adwendi Division of IPDS, BPS of North Sulawesi Province, BPS, Indonesia
  • Asep Saefuddin Department of Statistics, FMIPA, IPB University, Indonesia
  • Budi Susetyo Department of Statistics, FMIPA, IPB University, Indonesia
Keywords: poisson, mix model, multidimensional poverty, overdispersion, zero inflated, negative binomial

Abstract

The research began with calculating the value of multidimensional poverty at the district level in West Java Province from SUSENAS 2021. The calculation of multidimensional poverty was based on individuals in each district or city household. The dimensional weights are weighed the same, and the indicators in the dimensions are also weighed the same. Furthermore, the simulation study used the Poisson, ZIP, and ZINB mixed models to examine the model's performance on data with cases of excess zero values and overdispersion. The simulation was by generating data without overdispersion and with overdispersion. Overdispersion data was generated with parameters of ω (0.1, 0.3, 0.5, and 0.7), and the model was evaluated from the AIC value. The best method in the simulation study was used to estimate multidimensional poverty in sub-districts in West Java Province using PODES 2021. Simulation studies on data without overdispersion showed no difference in the model's goodness. Overdispersion data shows Mixed Model ZIP and ZINB are better than Mixed Model Poisson. The percentage of the multidimensional poverty population at the sub-district level in West Java Province is quite diverse, from 0.04% to 75.54%.

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Published
2023-04-20
How to Cite
[1]
S. Adwendi, A. Saefuddin, and B. Susetyo, “A STUDY OF SMALL AREA ESTIMATION TO MEASURE MULTIDIMENSIONAL POVERTY WITH MIXED MODEL POISSON, ZIP, AND ZINB”, BAREKENG: J. Math. & App., vol. 17, no. 1, pp. 0439-0448, Apr. 2023.