This Author published in this journals
All Journal JSTAR
Liguori Yuridis Ledhe
Badan Pusat Statistik Provinsi Nusa Tenggara Timur

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : JSTAR

Analisis Kemiskinan Multidimensi di Nusa Tenggara Timur Tahun 2023 Liguori Yuridis Ledhe
Jurnal Statistika Terapan (ISSN 2807-6214) Vol 4 No 1 (2024): Jurnal Statistika Terapan
Publisher : Badan Pusat Statistik Provinsi NTT

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64930/jstar.v4i1.57

Abstract

One of the overarching sustainable development goals in fighting poverty is to eradicate poverty in all its forms everywhere. This pose a great challenge for areas where insidence and intensity of poverty is high. This study aimed to estimate and anlyze multidimentional poverty index in Nusa Tenggara Timur province based on Alkire and Foster framework using March 2023 microdata obtained from National Socio-Economic Survey (Susenas). The result showed that 34.80 percent of the population in NTT were multidimentionally poor and 10.25 percent were severely poor. In terms of intensity, poor people in NTT deprived in 44 percent of total weighted indicators. The multidimentional poverty index in province level was 0.15 and varied between 0.06 to 0.25 in regencies and municipality. By analyzing the contribution of each dimensions and indicators toward MPI, this research found that 49 percent of MPI was attributed to health aspect while living standard and education contributed 31 and 20 percent respectively. Among this aformentioned dimensions, there were four dominant indicators namely calory intake, years of schooling, food insecurity and asset ownership with cummulative contribution of 77.23 percent toward MPI. Furthermore, this study compared multdimentional porvery in urban and rural areas and concluded that the insidence and intensity of multidimentional poverty were much higher in rural than urban areas. The value of MPI for rural and urban areas were 0.18 and 0.07 respectively. Lastly, the comparison between multdimentional and monetary approach was conducted. The results were 30 percent mismatch and the multidimentional method predicted 1.7 times higher poverty headcount ratio than the monetary measure.