Univariate vs. Multivariate: Comparing Univariate Panel Data and Panel SUR Approaches in Modeling Stunting, Wasting, and Underweight in Indonesia
DOI:
https://doi.org/10.36456/jstat.vol18.no2.a10840Keywords:
Malnutrition, Multivariate Panel Data, Panel-SURAbstract
Objective: To support Indonesia’s progress toward the SDG Zero Hunger target, this study compares the performance of univariate panel data regression against the Panel Seemingly Unrelated Regression (Panel SUR) model in analyzing stunting, wasting, and underweight (2007–2023). Method: Using a two-way Feasible Generalized Least Squares (FGLS) approach, the study simultaneously estimates the malnutrition system to account for cross-equation error correlations. Results: The results demonstrate that Panel SUR outperforms the univariate model by correcting the theoretical inconsistency of the Low Birth Weight (LBW) coefficient—switching it from a counterintuitive negative to a positive sign while significantly increasing the explanatory power for the wasting equation and achieving superior estimation efficiency as evidenced by a lower Mean Square Error (MSE). Implications: These methodological improvements are substantively critical; correcting the LBW sign ensures that policy interventions accurately prioritize prenatal nutrition as a determinant of acute malnutrition, avoiding misleading inferences common in isolated modeling approaches. Conclusion: Consequently, Panel SUR offers a more robust empirical framework for formulating integrated nutrition policies than traditional univariate methods.
References
[1] Bappenas, “Berdaulat, Maju, Adil , dan Makmur,” Kementeri. PPN / Bappenas, vol. 32, pp. 1–25, 2019, [Online]. Available: https://perpustakaan.bappenas.go.id/e-library/file_upload/koleksi/migrasi-data-publikasi/file/Policy_Paper/Ringkasan Eksekutif Visi Indonesia 2045_Final.pdf
[2] Unicef, Laporan Tahunan 2023. United Nations Children’s Fund, 2023. [Online]. Available: https://www.unicef.org/indonesia/media/21331/file/UNICEF Laporan Tahunan 2023.pdf.pdf
[3] Ministry of Health of the Republic of Indonesia, “Indonesian Health Survey (IHS) 2023 - Health Development Policy Agency | BKPK Kemenkes,” 2023. [Online]. Available: https://www.badankebijakan.kemkes.go.id/hasil-ski-2023/
[4] F. R. Fadmi, B. W. Otok, Kuntoro, S. Melaniani, and R. Sriningsih, “Segmentation of stunting, wasting, and underweight in Southeast Sulawesi using geographically weighted multivariate Poisson regression,” MethodsX, vol. 12, no. April, p. 102736, 2024, doi: 10.1016/j.mex.2024.102736.
[5] Kemenkes, “Laporan Nasional Riskesdas 2007,” Lap. Nas. 2007, pp. 1–384, 2007, [Online]. Available: http://labdata.litbang.kemkes.go.id/images/download/laporan/RKD/2007/lap_rkd07.pdf
[6] Kemenkes RI, “Hasil Riset Kesehatan Dasar Tahun 2018,” Kementrian Kesehat. RI, vol. 53, no. 9, pp. 1689–1699, 2019.
[7] Kementerian Kesehatan RI, “Laporan Riskesdas 2018,” Lap. Nas. Riskesdas 2018, vol. 53, no. 9, pp. 154–165, 2018.
[8] Kemenkes, “Survei Kesehatan Indonesia Dalam Angka 2023,” Survei Kesehat. Indones., pp. 1–68, 2023.
[9] Badi H. Baltagi, Econometric Analisys Of Panel Data, vol. 5, no. 7. 1975.
[10] B. Haile and D. Headey, “Growth in milk consumption and reductions in child stunting: Historical evidence from cross-country panel data,” Food Policy, vol. 118, no. June, p. 102485, 2023, doi: 10.1016/j.foodpol.2023.102485.
[11] Z. Ramahaimandimby, S. Shiratori, J. Rafalimanantsoa, and T. Sakurai, “Animal-sourced foods production and early childhood nutrition: Panel data evidence in central Madagascar,” Food Policy, vol. 121, no. October, p. 102547, 2023, doi: 10.1016/j.foodpol.2023.102547.
[12] S. Platoni, L. Barbieri, D. Moro, and P. Sckokai, “Heteroscedastic stratified two-way EC models of single equations and SUR systems,” Econom. Stat., vol. 15, pp. 46–66, 2020, doi: 10.1016/j.ecosta.2019.03.004.
[13] D. Venosia, T. Saifudin, and N. Chamidah, “The Modeling of The Poverty Rate In Indonesia From 2018 to 2023 Using A Panel Data Regression Approach,” vol. 18, no. 1, pp. 798–807, 2025.
[14] A. Bella et al., “Do parental Smoking Behaviors Affect Children’s Thinness, Stunting, and Overweight Status in Indonesia? Evidence from a Large-Scale Longitudinal Survey,” J. Fam. Econ. Issues, vol. 44, no. 3, pp. 714–726, 2023, doi: 10.1007/s10834-022-09864-x.
[15] B. K. Datta and S. Phillips, “Long COVID and the Higher Risk of Food Insecurity Among Participants and Nonparticipants of Food Assistance Programs in the United States,” J. Acad. Nutr. Diet., vol. 125, no. 4, pp. 555–566, 2025, doi: 10.1016/j.jand.2024.07.171.
[16] S. K. C. Kyire, S. S. Dhaka, R. K. Bannor, and J. K. Asare, “Climate change and food security nexus in Ghana: The role of renewable energy,” Sci. Total Environ., vol. 963, no. July 2024, p. 178454, 2025, doi: 10.1016/j.scitotenv.2025.178454.
[17] A. Fitriana, W. Pramesti, E. Mustikawati, P. Hermanto, J. L. Dukuh, and M. Xii, “PEMODELAN SEEMINGLY UNRELATED REGRESSION ( SUR ) PADA FAKTOR PERTUMBUHAN PEREKONOMIAN DI PROVINSI JAWA TIMUR TAHUN 2018,” vol. 13, no. 2, pp. 12–19, 2020.
[18] W. H. Greene, Econometric Analysis. in Econometric Analysis. Pearson, 2018. [Online]. Available: https://books.google.co.id/books?id=xGZRvgAACAAJ
[19] J. M. Wooldridge, Introductory Econometrics: A Modern Approach - Standalone Book Sixth Edition. 2015. [Online]. Available: www.cengage.com/highered
[20] B. W. Yap and M. R. Nornadiah, “Power comparisons of Shapiro-Wilk, Kolmogorov-Smirnov, Lilliefors and Anderson-Darling tests,” J. Stat. Model. Anal., vol. 2, no. November, pp. 21–33, 2011.
[21] O. O. ILORI and F. O. TANIMOWO, “Heteroscedasticity Detection in Cross-Sectional Diabetes Pedigree Function: A Comparison of Breusch-Pagan-Godfrey, Harvey and Glejser Tests,” Int. J. Sci. Manag. Res., vol. 05, no. 12, pp. 150–163, 2022, doi: 10.37502/ijsmr.2022.51211.
[22] C. Baum, “XTTEST2: Stata module to perform Breusch-Pagan LM test for cross-sectional correlation in panel data model,” 2023. [Online]. Available: https://econpapers.repec.org/RePEc:boc:bocode:s415702
[23] B. H. Baltagi, “The Two-Way Error Component Regression Model BT - Econometric Analysis of Panel Data,” B. H. Baltagi, Ed., Cham: Springer International Publishing, 2021, pp. 47–74. doi: 10.1007/978-3-030-53953-5_3.
[24] A. Jahan-mihan et al., “The Impact of Parental Preconception Nutrition , Body Weight , and Exercise Habits on Offspring Health Outcomes : A Narrative Review,” pp. 1–30, 2024.
[25] I. L. Gabain, A. S. Ramsteijn, and J. P. Webster, “Parasites and childhood stunting – a mechanistic interplay with nutrition, anaemia, gut health, microbiota, and epigenetics,” Trends Parasitol., vol. 39, no. 3, pp. 167–180, 2023, doi: https://doi.org/10.1016/j.pt.2022.12.004.
