Small Area Estimation of Maluku and Papua Island Child Poverty Levels in 2023

Priatmadani Priatmadani; Putri Puspita  Sari; Ervan Nur  Rahmat; Puput Budi  Aji; Faried Akbar  Nafiis; Nofita  Istiana

doi:10.20956/j.v21i1.35293

Authors

Priatmadani Priatmadani Politeknik Statistika STIS
Putri Puspita Sari Program Studi DIV Statistika, Politeknik Statistika STIS
Ervan Nur Rahmat Program Studi DIV Statistika, Politeknik Statistika STIS
Puput Budi Aji Program Studi DIV Statistika, Politeknik Statistika STIS
Faried Akbar Nafiis Program Studi DIV Statistika, Politeknik Statistika STIS
Nofita Istiana Program Studi DIV Statistika, Politeknik Statistika STIS

DOI:

https://doi.org/10.20956/j.v21i1.35293

Keywords:

child poverty, small area estimation, EBLUP, HB Beta

Abstract

Child welfare issues such as child poverty pose a challenge for Indonesia. The provinces in Maluku and Papua have the highest rates of child poverty. Data on child poverty at regencies/municipalities level is needed to address this issue through targeted policies. The direct estimations have a Relative Standard Error (RSE) value of more than 25 percent, necessitating the use of an indirect method, Small Area Estimation (SAE). This study aims to compare the results of indirect estimates of the percentage of children aged 0-17 living in poverty at the regencies/municipalities level in Maluku and Papua using SAE Empirical Best Linear Unbiased Prediction (EBLUP) and Hierarchical Bayes Beta (HB Beta) methods. Susenas KOR March 2023 data is used to produce direct estimates, while Podes 2021 data is used to form auxiliary variables. The results indicate that the SAE HB Beta method provides estimates with better RSE compared to SAE EBLUP. All regencies/municipalities in the Maluku and Papua have a fairly good level of accuracy.

Downloads

Download data is not yet available.

References

Beers, L. S., Szilagyi, M. A., Goza, S. H., Seigel, W. M., & Del Monte, M., 2021. Ending Child Poverty by Investing in Children and Families. Academic Pediatrics, 21(8), S92–S93. https://doi.org/10.1016/j.acap.2021.09.002

BPS, 2017. Analisis Kemiskinan Anak dan Deprivasi Hak-Hak Dasar Anak di Indonesia. Badan Pusat Statistik, Jakarta.

BPS, 2023. Persentase Penduduk Miskin September 2022 naik menjadi 9,57 persen. https://www.bps.go.id/id/pressrelease/2023/01/16/2015/persentase-penduduk-miskin-september-2022-naik-menjadi-9-57-persen.html [22 Juli 2024]

Foster, J., Greer, J., & Thorbecke, E., 1984. A Class of Decomposable Poverty Measures. Econometrica, 52(3), 761. https://doi.org/10.2307/1913475

Gemede, B., Alamirew, B., & Emana, B., 2023. Child Poverty and Its Determinants: The Case of Negele Arsi Woreda, Oromia Regional State, Ethiopia. Cogent Food & Agriculture, 9(1). https://doi.org/10.1080/23311932.2023.2211809

Gordon, D., Nandy, S., Pantazis, C., Pemberton, S., & Townsend, P., 2003. The Distribution of Child Poverty in Developing World. Centre for International Poverty Research, Bristol.

Kemen PPA, & BPS, 2022. Indeks Perlindungan Anak Tahun 2022. Kementerian Pemberdayaan Perempuan dan Perlindungan Anak, Jakarta.

National Academies of Sciences Engineering and Medicine, 2019. A Roadmap to Reducing Child Poverty. National Academies Press, Washington D.C.

Nisa, K., & Budiarti, W., 2020. Pengaruh Teknologi Informasi dan Komunikasi terhadap Tingkat Kemiskinan di Indonesia Tahun 2012 - 2017. Seminar Nasional Official Statistics, 2019(1), 759–768. https://doi.org/10.34123/semnasoffstat.v2019i1.186

Oxford Poverty and Human Development Initiative (OPHI), 2018. Global Multidimensional Poverty Index. https://ophi.org.uk/multidimensional-poverty-index/ [28 Mei 2024]

Pemerintah RI, 2020. Peraturan Presiden Nomor 18 Tahun 2020 Tentang Rencana Pembangunan Jangka Menengah Nasional Tahun 2020–2024. https://peraturan.go.id/id/perpres-no-18-tahun-2020 [28 Mei 2024]

Permatasari, N., & Larasati, Widya., 2022. Perbandingan Metode SAE EBLUP dan SAE HB Pada Pendugaan Area Kecil (Studi Kasus Pendugaan Kemiskinan di Provinsi Jawa Timur). Jurnal Statistika Dan Aplikasinya, 6(1), 96–108. https://doi.org/10.21009/JSA.06109

Rao, J. N. K., & Molina, I., 2015. Small Area Estimation: Second Edition. John Wiley & Sons, Inc., New Jersey.

Salis, D. R., & Ubaidillah, A., 2023. Estimasi Tingkat Kemiskinan Anak Level Kabupaten/Kota di Provinsi Banten Tahun 2018-2021 dengan Small Area Estimation (SAE) Rao-Yu Pendekatan Hierarchical Bayes. Seminar Nasional Official Statistics, 2023(1), 515–524. https://doi.org/10.34123/semnasoffstat.v2023i1.1709

Sharfstein, J. M., & Thornton, R. L. J., 2021. US Healthcare Policy and Child Poverty. Academic Pediatrics, 21(8), S88–S89. https://doi.org/10.1016/j.acap.2021.07.013

United Nations Children’s Fund, 2017. Children in Indonesia: An analysis of poverty, mobility and multidimensional deprivation. UNICEF, Jakarta.

von Fintel, M., 2021. Chronic Child Poverty and Health Outcomes in South Africa Using a Multidimensional Poverty Measure. Child Ind Res 14, 1571–1596. https://doi.org/10.1007/s12187-021-09817-0

Wulansari, J., Permatasari, N., & Ubaidillah, A., 2022. Pendugaan Area Kecil Persentase Anak-anak Usia Kurang dari 18 Tahun yang Hidup di Bawah Garis Kemiskinan Tingkat Kabupaten/Kota di Indonesia Tahun 2020. Seminar Nasional Official Statistics, 2022(1), 383–394. https://doi.org/10.34123/semnasoffstat.v2022i1.1467

Yuniarty, T., Indahwati, I., & Wigena, A. H., 2024. Small Area Estimation With Hierarchical Bayes For Cross-Sectional And Time Series Skewed Data. Barekeng: Jurnal Ilmu Matematika Dan Terapan, 18(1), 0493–0506. https://doi.org/10.30598/barekengvol18iss1pp0493-0506