Determinasi Ketimpangan Pendapatan di Indonesia: Peran Pendidikan, Zakat, dan Korupsi
DOI:
https://doi.org/10.23969/jrie.v5i3.358Keywords:
Corruption, Income Inequality, Education, Zakat, ARDLAbstract
This study examines the influence of Zakat, Infaq, and Alms (ZIS), corruption, and education on income inequality in Indonesia. Utilizing a quantitative approach with time-series data from 2011 to 2022, the research employs the Autoregressive Distributed Lag (ARDL) framework to analyze both long-term and short-term dynamics. Findings indicate that ZIS and corruption exert a negative and significant impact on income inequality, whereas education shows a positive but insignificant effect. The study concludes that religious philanthropy and institutional integrity are pivotal in narrowing the economic gap. Policy implications suggest that the government should optimize zakat management systems and intensify anti-corruption measures to ensure more equitable income distribution. Additionally, strategic improvements in educational quality are essential to support sustainable and long-term economic equality.
References
Acemoglu, D., & Robinson, J. A. (2019). The narrow corridor: States, societies, and the fate of liberty. Penguin Press.
Acemoglu, D., Naidu, S., Restrepo, P., & Robinson, J. A. (2015). Democracy, redistribution, and inequality. Handbook of Income Distribution, 2, 1885–1966. https://doi.org/10.1016/B978-0-444-59429-7.00022-4
Amani, A., & Majid, M. S. A. (2022). Analisis pengaruh zakat, infak, dan sedekah (ZIS), inflasi, dan pertumbuhan ekonomi terhadap ketimpangan pendapatan dan kemiskinan di Indonesia. Jurnal Ilmiah Mahasiswa Ekonomi Pembangunan, 7(3), 152–163. https://doi.org/10.24815/jimekp.v7i3.22963
Anshari, M., Azhar, Z., & Ariusni, A. (2019). Analisis pengaruh pendidikan, upah minimum provinsi dan belanja modal terhadap ketimpangan pendapatan di seluruh provinsi di Indonesia. Jurnal Ecogen, 1(3), 494–504. https://doi.org/10.24036/jmpe.v1i3.4990
Ascarya, & Yumanita, D. (2018). Analisis rendahnya penghimpunan zakat di Indonesia dan alternatif solusinya. Bank Indonesia Working Paper.
Badan Pusat Statistik. (2023). Statistik Indonesia 2023. https://www.bps.go.id/id/publication/2023/02/28/18018f9896f09f03580a614b/statistik-indonesia-2023.html
Barro, R. J. (2000). Inequality and growth in a panel of countries. Journal of Economic Growth, 5(1), 5–59. https://doi.org/10.1023/A:1009850119319
Bauer, D. (2023). Information-Criterion-Based Lag Length Selection in Vector Autoregressive Approximations for I(2) Processes. Econometrics, 11(2), 11. https://doi.org/10.3390/econometrics11020011
BAZNAS. (2022). Laporan Zakat Nasional 2022. Badan Amil Zakat Nasional. https://ppid.baznas.go.id/laporan/laporan-pengelolaan-zakat
Beik, I. S., & Arsyianti, L. D. (2016). Measuring zakat impact on poverty and welfare using CIBEST model. Journal of Islamic Monetary Economics and Finance, 1(2), 141–160. https://doi.org/10.21098/jimf.v1i2.524
Chang, B. H., Rajput, S. K. O., & Bhutto, N. A. (2019). Impact of exchange rate volatility on the US exports: A new evidence from multiple threshold nonlinear ARDL model. Journal of International Commerce, Economics and Policy, 10(2). https://doi.org/10.1142/S1793993319500091
Damanik, A. M., Zulgani, & Rosmeli. (2018). Faktor-faktor yang mempengaruhi ketimpangan pendapatan melalui pertumbuhan ekonomi di Provinsi Jambi. E-Jurnal Perspektif Ekonomi dan Pembangunan Daerah, 7(1), 15–25. https://doi.org/10.22437/pdpd.v7i1.4533
Gujarati, D. N., & Porter, D. C. (2009). Basic Econometrics (5th ed.). McGraw-Hill Irwin.
Gupta, S., Davoodi, H., & Alonso-Terme, R. (2002). Does corruption affect income inequality and poverty? Economics of Governance, 3(1), 23–45. https://doi.org/10.1007/s101010100039
Hacker, R. S., & Hatemi-J, A. (2021). Model selection in time series analysis: using information criteria as an alternative to hypothesis testing. Journal of Economic Studies, 49(6), 1055–1075. https://doi.org/10.1108/JES-09-2020-0469
Hanushek, E. A., & Woessmann, L. (2015). The knowledge capital of nations: Education and the economics of growth. MIT Press.
Hanushek, E. A., Piopiunik, M., & Wiederhold, S. (2019). The value of smarter teachers. Journal of Human Resources, 54(4), 857–899. https://doi.org/10.3368/jhr.54.4.0317.8619R1
Heiss, F. (2020). Using R for introductory econometrics (2nd ed.). CreateSpace Independent Publishing Platform.
Hindun, H., Soejoto, A., & Hariyati, H. (2019). Pengaruh pendidikan, pengangguran, dan kemiskinan terhadap ketimpangan pendapatan di Indonesia. Jurnal Ekonomi Bisnis dan Kewirausahaan (JEBIK), 8(3), 250–265. https://doi.org/10.26418/jebik.v8i3.34721
Kripfganz, S., & Schneider, D. C. (2023). ARDL: Estimating autoregressive distributed lag and equilibrium correction models. The Stata Journal, 23(1), 192–219. https://doi.org/10.1177/1536867X231162002
Narayan, P. K. (2005). The saving and investment nexus for China: Evidence from cointegration tests. Applied Economics, 37(17), 1979–1990. https://doi.org/10.1080/00036840500278103
Neudorfer, N. S., & Theuerkauf, U. G. (2014). The paradox of plenty: Another resource curse? Corruption and inequality in resource-rich countries. Journal of Public Policy, 34(2), 251–280. https://doi.org/10.1017/S0143814X1400003X
OECD. (2018). Equity in education: Breaking down barriers to social mobility. PISA, OECD Publishing. https://doi.org/10.1787/9789264073234-en
OECD. (2019). PISA 2018 results (Volume II): Where all students can succeed. PISA, OECD Publishing. https://doi.org/10.1787/b5fd1b8f-en
Pesaran, M. H., Shin, Y., & Smith, R. J. (2001). Bounds testing approaches to the analysis of level relationships. Journal of Applied Econometrics, 16(3), 289–326. https://doi.org/10.1002/jae.616
Prihatini, R. (2021). Pengaruh ZIS dan Korupsi Terhadap Ketimpangan Pendapatan Tahun 2010-2019 Di Indonesia [Tesis Doktoral, Universitas Pembangunan Nasional Veteran Jakarta]. https://repository.upnvj.ac.id/15279/
Ravallion, M. (2018). Inequality and globalization: A review essay. Journal of Economic Literature, 56(2), 620–642. https://doi.org/10.1257/jel.20171419
Romdhoni, A. H. (2017). Zakat dalam mendorong pertumbuhan ekonomi dan pengentasan kemiskinan. Jurnal Ilmiah Ekonomi Islam, 3(01), 41–51. https://doi.org/10.29040/jiei.v3i01.98
Shrestha, M. B., & Bhatta, G. R. (2018). Selecting appropriate methodology for time-series data analysis: Autoregressive Distributed Lag (ARDL) boundary testing a better approach. MethodsX, 5, 114–124. https://doi.org/10.1016/j.mex.2018.01.005
Stewart, C. (2025). Demonstrating that the autoregressive distributed lag bounds test can detect a long-run levels relationship when the dependent variable is I(0). Econometrics, 13(4), 39. https://doi.org/10.3390/econometrics13040039
Suryahadi, A., Al Izzati, R., & Suryadarma, D. (2020). Estimating the impact of Covid-19 on poverty in Indonesia. Bulletin of Indonesian Economic Studies, 56(2), 175–192. https://doi.org/10.1080/00074918.2020.1779390
Transparency International. (2022). Corruption Perceptions Index 2021. Transparency International.
Uslaner, E. M. (2017). The historical roots of corruption: Foraging, farming, and institutions. Cambridge University Press.
Widiastuti, T., Robani, A., Sukmaningrum, P. S., Mawardi, I., & Herianingrum, S. (2022). Governance and zakat graduation in Indonesia. International Journal of Ethics and Systems, 38(3). https://doi.org/10.1108/IJOES-04-2021-0081
World Bank. (2018). World Development Report 2018: Learning to realize education's promise. World Bank. https://doi.org/10.1596/978-1-4648-1096-1
World Bank. (2020). Indonesia economic prospects: The long road to recovery. World Bank.
Xuan, J., et al. (2025). An ARDL Approach to Investigating the Relationship between FDI, Renewable Energy, Economic Growth, Trade Openness, and CO₂ Emissions. Results in Engineering, 27.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Jurnal Riset Ilmu Ekonomi
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
