ADAPTIVE-COMPREHENSIVE POLICY: LEVERS OF LONG-TERM HUMAN DEVELOPMENT IN LOCAL GOVERNMENT
The trend of increasing HDI in Indonesia for the last few decades does not exceed 2% annually. In fact, human development is a critical factor in increasing the nation’s quality of life. Although a bunch of studies have been done dealing with its determining factors, there is no available generalized conclusion on such determinants. This article aims to find out the empirical factors determining human development in Indonesia. The regression data panel analyzed data from 34 provinces between 2010 and 2024, sourced from the Ministry of Finance and Statistics Indonesia, utilizing STATA 17.0. The results showed that there were seven factors that influenced the success of human development in Indonesia by 85.31%. This finding also indicates that each factor has different strengths and directions of influence simultaneously or partially, implying the need to increase HDI with selective action in the form of determining policy priorities. Such policies can be a lever for the success of long-term human development, and in turn, become the foundation for the development of adaptive and comprehensive policies in local governments. The future study that needs to be carried out on the Gini ratio, which represents inequality, should have implications for HDI and local spending anomalies as a continuation of the findings of this study.
Downloads
Acheampong, A. O., Opoku, E. E. O., Dzator, J., & Kufuor, N. K. (2022). Enhancing human development in developing regions: Do ICT and transport infrastructure matter? Technological Forecasting and Social Change, 180, 121725. https://doi.org/10.1016/j.techfore.2022.121725
Acock, A. C. (2023). A Gentle Introduction to Stata (6th ed.). Stata Press.
Adshead, D., Paszkowski, A., Gall, S. S., Peard, A. M., Adnan, M. S. G., Verschuur, J., & Hall, J. W. (2024). Climate threats to coastal infrastructure and sustainable development outcomes. Nature Climate Change. https://doi.org/10.1038/s41558-024-01950-2
Amaluis, D., Ronald, J., Amelia, M., Stevani, S., Syamra, Y., & Eprillison, V. (2024). Analysis of income inequality (gini ratio) and its impact on the human development index (hdi) in West Sumatra Province. Economica: Journal of Economic and Economic Education, 11(2), 110–117.
Amate-Fortes, I., Guarnido-Rueda, A., & Molina-Morales, A. (2017). Economic and Social Determinants of Human Development: A New Perspective. Social Indicators Research, 133(2), 561–577. https://doi.org/10.1007/s11205-016-1389-z
Amini, S., Delgado, M. S., Henderson, D. J., & Parmeter, C. F. (2012). Fixed vs Random: The Hausman Test Four Decades Later. In Advances in Econometrics (pp. 479–513). https://doi.org/10.1108/S0731-9053(2012)0000029021
Anand, S., & Sen, A. (2000). Human development and economic sustainability. World Development, 28(12), 2029–2049.
Aswanto, A., & Arif, E. (2024). The Effect of Local Original Income and Economic Growth on the Human Development Index. Asian Journal of Multidisciplinary Research, 1(1), 1–10. https://doi.org/10.59613/4qj4t543
Baltagi, B. H., Kao, C., & Peng, B. (2015). On testing for sphericity with non-normality in a fixed effects panel data model. Statistics & Probability Letters, 98, 123–130. https://doi.org/10.1016/j.spl.2014.12.017
Baltagi, B. H., & Liu, L. (2007). Alternative ways of obtaining Hausman’s test using artificial regressions. Statistics & Probability Letters, 77(13), 1413–1417. https://doi.org/10.1016/j.spl.2007.02.003
Bin-Nashwan, S. A., Hassan, M. K., & Muneeza, A. (2022). Russia–Ukraine conflict: 2030 Agenda for SDGs hangs in the balance. International Journal of Ethics and Systems. https://doi.org/10.1108/ijoes-06-2022-0136
Breuer, M., & Dehaan, E. (2024). Using and Interpreting Fixed Effects Models. Journal of Accounting Research, 62(4), 1183–1226. https://doi.org/10.1111/1475-679X.12559
Castells‐Quintana, D., Royuela, V., & Thiel, F. (2019). Inequality and sustainable development: Insights from an analysis of the human development index. Sustainable Development, 27(3), 448–460. https://doi.org/10.1002/sd.1917
Castilla, E., Martín, N., Muñoz, S., & Pardo, L. (2020). Robust Wald-type tests based on minimum Rényi pseudodistance estimators for the multiple linear regression model. Journal of Statistical Computation and Simulation, 90(14), 2655–2680. https://doi.org/10.1080/00949655.2020.1787410
Cifuentes, M., Sembajwe, G., Tak, S., Gore, R., Kriebel, D., & Punnett, L. (2008). The association of major depressive episodes with income inequality and the human development index. Social Science & Medicine, 67(4), 529–539.
Das, P. (2019). Econometrics in theory and practice: analysis of cross section, time seriesand panel data with Stata 15.1. Springer Nature, Singapore.
De Vos, I., & Westerlund, J. (2019). On CCE estimation of factor-augmented models when regressors are not linear in the factors. Economics Letters, 178, 5–7. https://doi.org/10.1016/j.econlet.2019.02.001
Dewi, S. P. P., & Prasojo, E. (2021). The impact of state budget transparency and information dissemination to maintain public trust. Natapraja, 9(2). https://doi.org/10.21831/natapraja.v9i2.40474
Eren, M., Celik, A. K., & Kubat, A. (2014). Determinants of the Levels of Development Based on the Human Development Index: A Comparison of Regression Models for Limited Dependent Variables. Review of European Studies, 6(1). https://doi.org/10.5539/res.v6n1p10
Ernanto, Sriyana, J., Hakim, A., & Sidiq, S. (2024). Enhancing Human Capital in Indonesia: Does Economic Policy Work? International Journal of Sustainable Development and Planning, 19(5), 1963–1969. https://doi.org/10.18280/ijsdp.190535
Fernandez, V. (2006). Specification tests for a parsimonious random-effects model. Applied Economics Letters, 13(15), 1009–1012. https://doi.org/10.1080/13504850500425766
Firmansyah, D., Susetyo, D. P., Suryana, A., & Saepuloh, D. (2022). Volume Penjualan: Analisis Pendekatan Regresi Data Panel. Asian Journal of Management Analytics, 1(2), 109–124. https://doi.org/10.55927/ajma.v1i2.1479
Fitrianti, R., Zaenal, M., Fattah, S., & Hidayah, N. (2025). Flypaper effect: Analysis of financial transfers from the central government to provincial regions in Indonesia. Public and Municipal Finance, 14(1), 54–64. https://doi.org/10.21511/pmf.14(1).2025.05
Grech, V., & Calleja, N. (2018). WASP (Write a Scientific Paper): Multivariate analysis. Early Human Development, 123, 42–45. https://doi.org/10.1016/j.earlhumdev.2018.04.012
Gujarati, D. (2015). Econometrics by example. PALGRAVE.
Gujarati, D., & Porter, D. (2009). Essentials of econometrics 4e. McGraw Hill.
Hanna, T., Hughes, B. B., Irfan, M. T., Bohl, D., Solórzano, J. R., Abidoye, B. O., Patterson, L., & Moyer, J. D. (2024). Sustainable Development Goal Attainment in the Wake of COVID-19: Simulating an Ambitious Policy Push. Sustainability. https://doi.org/10.3390/su16083309
Herianingrum, S., Hadi, M. N., Fauzy, Q., Afifa, F. U., & Laila, N. (2019). The effect of government expenditure on islamic human development index. Opción, 35(88), 685–703.
Huang, M. (2020). Theory and Implementation of linear regression. 2020 International Conference on Computer Vision, Image and Deep Learning (CVIDL), 210–217. https://doi.org/10.1109/CVIDL51233.2020.00-99
Humaira, U. H., & Nugraha, J. (2018). Analysis of Factors Affecting the Human Development Index in West Kalimantan Province using Data Panel Data Regression. EKSAKTA: Journal of Sciences and Data Analysis, 97–105. https://doi.org/10.20885/eksakta.vol18.iss2.art2
Jäntschi, L., Bálint, D., & Bolboacă, S. D. (2016). Multiple Linear Regressions by Maximizing the Likelihood under Assumption of Generalized Gauss-Laplace Distribution of the Error. Computational and Mathematical Methods in Medicine, 2016, 1–8. https://doi.org/10.1155/2016/8578156
Jasmina, T., & Oda, H. (2022). Nonlinear Relation between Government Spending and Education: Theoretical and Empirical Evidence from Districts in Indonesia. Southeast Asian Journal of Economics, 10(1), 1–36. https://www.scopus.com/inward/record.uri?eid=2-s2.0-85128911817&partnerID=40&md5=864eb61a2954a1e1daaa24157dc00d62
Khan, N. H., Ju, Y., & Hassan, S. T. (2019). Investigating the determinants of human development index in Pakistan: an empirical analysis. Environmental Science and Pollution Research, 26(19), 19294–19304. https://doi.org/10.1007/s11356-019-05271-2
Khasanah, L., & Suryanto, S. (2023). The Impact of Air Pollution on the Happiness Index of ASEAN Communities. Iop Conference Series Earth and Environmental Science, 1165(1), 12044. https://doi.org/10.1088/1755-1315/1165/1/012044
Kizilkaya, O., Kizilkaya, O., Akar, G., & Mike, F. (2024). The Role of Energy Consumption and Economic Growth on Human Development in Emerging (E-7) Countries: Fresh Evidence from Second-Generation Panel Data Analyses. Problemy Ekorozwoju, 19(2), 186–202. https://doi.org/10.35784/preko.5798
Kothari, P. (2015). Data analysis with STATA. Packt Publishing Ltd.
Kusharjanto, H., & Kim, D. (2011). Infrastructure and human development: the case of Java, Indonesia. Journal of the Asia Pacific Economy, 16(1), 111–124. https://doi.org/10.1080/13547860.2011.539407
Kwak, S. (2023). Are only p-values less than 0.05 significant? A p-value greater than 0.05 is also significant! Journal of Lipid and Atherosclerosis, 12(2), 89.
Larbi, Y. O., Halimi, R. El, Akharif, A., & Mellouk, A. (2021). Optimal Tests for Random Effects in Linear Mixed Models. Hacettepe Journal of Mathematics and Statistics, 50(4), 1185–1211. https://doi.org/10.15672/hujms.773667
Lee, K. J., & Thompson, S. G. (2008). Flexible parametric models for random‐effects distributions. Statistics in Medicine, 27(3), 418–434. https://doi.org/10.1002/sim.2897
Liu, K., Wang, R., Schrijver, I., & Hoekstra, R. (2024). Can we project well-being? Towards integral well-being projections in climate models and beyond. Humanities & Social Sciences Communications, 11, 1–11. https://doi.org/10.1057/s41599-024-02941-6
Márquez, H. F., Santibáñez, A. L. V., & Castillo, O. N. (2020). Corruption and Development in China and Latin-America. México y La Cuenca Del Pacífico, 9(27), 15–51. https://doi.org/10.32870/mycp.v9i27.684
Melgiana, A. C., Rupa, I. W., & Riasning, N. P. (2020). Pengaruh Pendapatan Asli Daerah, Dana Alokasi Umum Dan Dana Alokasi Khusus Terhadap Indeks Pembangunan Manusia Dengan Belanja Modal Sebagai Variabel Intervening (Studi Empiris Di Kabupaten/Kota Di Provinsi Bali). Jurnal Riset Akuntansi Warmadewa, 1(1), 45–49. https://doi.org/10.22225/jraw.1.1.1543.45-49
Ministry of Education and Culture. (2023). Neraca pendidikan daerah 2023. https://npd.kemdikbud.go.id/
Ministry of Investment. (2024). Press release realisasi inverstasi triwulan II 2024. https://ppid.bkpm.go.id/wp-content/uploads/2024/10/Data-Realisasi-Investasi-Triwulan-II-dan-Semester-I-2024.pdf
Mohamed, B. H., Disli, M., Al-Sada, M. S., & Koç, M. (2022). Investigation on Human Development Needs, Challenges, and Drivers for Transition to Sustainable Development: The Case of Qatar. Sustainability, 14(6), 3705. https://doi.org/10.3390/su14063705
N Pillai, V. (2017). Panel Data Analysis with Stata Part 1: Fixed Effects and Random Effects Models.
Nayyar, D., & Malhotra, R. (2023). Economic and Social Policies for Human Development. Journal of Human Development and Capabilities. https://doi.org/10.1080/19452829.2023.2252645
Nguyen, H. T., & Nguyen, H. T. X. (2025). The Factors Affect Financial Performance of Companies Listed On Ho Chi Minh Stock Exchange in Vietnam. Quality-Access to Success, 26(205). https://doi.org/10.47750/QAS/26.205.10
Ningrum, J. W., Khairunnisa, A. H., & Huda, N. (2020). Pengaruh Kemiskinan, Tingkat Pengangguran, Pertumbuhan Ekonomi dan Pengeluaran Pemerintah Terhadap Indeks Pembangunan Manusia (IPM) di Indonesia Tahun 2014-2018 dalam Perspektif Islam. Jurnal Ilmiah Ekonomi Islam, 6(2), 212. https://doi.org/10.29040/jiei.v6i2.1034
Paetzold, R. L. (1992). Multicollinearity and the use of regression analyses in discrimination litigation. Behavioral Sciences & the Law, 10(2), 207–228.
Pforr, K. (2014). Femlogit—Implementation of the Multinomial Logit Model with Fixed Effects. The Stata Journal: Promoting Communications on Statistics and Stata, 14(4), 847–862. https://doi.org/10.1177/1536867X1401400409
Rashmi, R., & Paul, R. (2024). Insights on Poverty-based Inequality in Old-age Mortality in India. Discover Public Health, 21(1), 110. https://doi.org/10.1186/s12982-024-00223-9
Sabilla, T. M., & Sumarsono, H. (2022). Pengaruh Belanja Pemerintah, Pendapatan Asli Daerah, Penanaman Modal Dalam Negeri, Indeks Pembangunan Manusia Terhadap PDRB. Forum Ekonomi, 24(1), 54–64. https://doi.org/10.30872/jfor.v24i1.10382
Shieh, G. (2005). On power and sample size calculations for Wald tests in generalized linear models. Journal of Statistical Planning and Inference, 128(1), 43–59. https://doi.org/10.1016/j.jspi.2003.09.017
Sijabat, R. (2024). Impact of economic growth, village funds, and poverty on human development in Indonesia: An analytical study from 2015 to 2022. International Journal of ADVANCED AND APPLIED SCIENCES, 11, 238–250. https://doi.org/10.21833/ijaas.2024.03.023
Sileshi, G. W. (2015). The relative standard error as an easy index for checking the reliability of regression coefficients. August). DOI, 10.
Silveira, F., Miranda, W., & Sousa, R. P. de. (2024). Post-COVID-19 health inequalities: Estimates of the potential loss in the evolution of the health-related SDGs indicators. PLOS ONE, 19(7), e0305955. https://doi.org/10.1371/journal.pone.0305955
Sofilda, E., Hermiyanti, P., & Hamzah, M. (2015). Determinant variable analysis of human development index in Indonesia (Case for high and low index at period 2004-2013). OIDA International Journal of Sustainable Development, 8(09), 11–28.
Sriyanto, S., Tambunan, M. R. U. D., & Arifin, B. (2024). The impact of triple f-crises (fuel, food, and finance) on household consumption in Indonesia. Natapraja, 11(2), 109–124. https://doi.org/10.21831/natapraja.v11i2.60121
Statistics Indonesia. (2024). [Metode Baru] Indeks Pembangunan Manusia menurut Provinsi, 2022-2024. Https://Www.Bps.Go.Id/. https://www.bps.go.id/id/statistics-table/2/NDk0IzI=/-metode-baru-indeks-pembangunan-manusia-menurut-provinsi.html
Statistics Indonesia. (2025). [Metode Baru] Indeks Pembangunan Manusia menurut Provinsi, 2022-2024. Https://Www.Bps.Go.Id/.
Sumiyarti, S., Firdayeti, & Handayani, K. (2022). Determinants of Human Development Index: Case Study of Provinces in Indonesia. Proceedings of the First Lekantara Annual Conference on Public Administration, Literature, Social Sciences, Humanities, and Education, LePALISSHE 2021, August 3, 2021, Malang, Indonesia. https://doi.org/10.4108/eai.3-8-2021.2315091
Taresh, A., Sari, D., & Purwono, R. (2021). Analysis of the relationship between income inequality and social variables: Evidence from Indonesia. Economics & Sociology, 14(1), 103–119. https://doi.org/10.14254/2071-789X.2021/14-1/7
Tauchmann, H. (2023). lgrgtest: Lagrange multiplier test after constrained maximum-likelihood estimation. The Stata Journal: Promoting Communications on Statistics and Stata, 23(2), 386–401. https://doi.org/10.1177/1536867X231175265
UNDP. (2024). Human development report 2023/2024. https://hdr.undp.org/system/files/documents/global-report-document/hdr2023-24reporten.pdf
Varona-Castillo, L., & Gonzales-Castillo, J. R. (2025). Human Development , Productivity, and Economic Growth. Journal of Human Development and Capabilities, 1–26. https://doi.org/10.1080/19452829.2024.2439947
Verma, A., Giri, A. K., & Debata, B. (2022). The role of ICT diffusion in sustainable human development: an empirical analysis from SAARC economies. Environmental Science and Pollution Research, 30(6), 14518–14532. https://doi.org/10.1007/s11356-022-23174-7
Yuliana, U. A. (2022). Pemodelan Regresi Data Panel Untuk Memprediksi Ketersediaan Beras Di Kabupaten Bojonegoro. Jurnal Statistika Dan Komputasi, 1(1), 1–11. https://doi.org/10.32665/statkom.v1i1.447
Yulianti, S., Widyanigsih, Y., & Nurrohmah, S. (2021). Spatial panel data model on human development index at Central Java. Journal of Physics: Conference Series, 1722(1), 012090. https://doi.org/10.1088/1742-6596/1722/1/012090
Copyright (c) 2025 Mutia Rahmah, Riska Amelia, Muchlis Hamdi, Amy Yayuk Sri Rahayu
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
