Fix effect sur to analyze economic growth in developed and developing countries

Authors

  • Muhamad Liswansyah Pratama Department of Statistics, Faculty of Mathematics and Science, Universitas Brawijaya, East Java https://orcid.org/0000-0003-4749-1823
  • Rahma Fitriani Department of Statistics, Faculty of Mathematics and Science, Universitas Brawijaya, East Java
  • Suci Astutik Department of Statistics, Faculty of Mathematics and Science, Universitas Brawijaya, East Java

DOI:

https://doi.org/10.18196/jesp.v24i1.17821

Keywords:

Fix Effect SUR, Panel SUR, Developed and Developing Country, World Economics, Economic Growth

Abstract

This study aims to identify the relationship between population density, inflation, and unemployment rates on the human development index, GNP, export-import, and urbanization in the developed and developing countries category using the Fix Effect Seemingly Unrelated Regression (FE SUR) with a dummy variable as the slope component. This research necessitates the development of the Seemingly Unrelated Regression model, specifically the Panel Seemingly Unrelated Regression (Panel SUR) model with a dummy variable as the slope component, due to the dynamic nature of the data and the fact that the same set of predictor variables explains the five response variables. The Panel, the Seemingly Unrelated Regression model with dummy variables, can accommodate research objectives where the SUR model can explain the influence between variables, differences in characteristics between countries can be explained by fixed effect models, and differences in the effect of population density, inflation, and unemployment rates on the human development index, GNP, exports imports and urbanization in the categories of developed and developing countries can be explained by slope dummy variables. The results showed that 98.46% of the diversity of response variables (human development index, GNP, exports, imports, and urbanization) could be explained by predictor variables (population density, inflation, and unemployment rate), while the other 1.54% was explained by other factors not included in the fixed effect SUR model. In addition, the results show that population density has a significant positive relationship with GNP, imports, and exports. However, there is a significant negative relationship between unemployment and GNP. There are large differences in the relationship between the unemployment rate and GNP in developed and developing countries, whereas in developed countries, there is a larger and negative relationship compared to developing countries.

References

Adim, A. (2021). Pengaruh Jumlah Penduduk dan Pendapatan Perkapita Terhadap Indeks Pembangunan Manusia (IPM) Provinsi Jawa Timur Kurun 2017-2019. Jurnal Ekonomi dan Bisnis, 22(1), 1-11. Retrieved from http://jurnal.unissula.ac.id/index.php/ekobis/article/view/13388

Alaba, O. O., Adepoju, A. A., & Olaomi, O. E. (2019). Seemingly Unrelated Regression with Decomposed Variance-Covariance Matrix: A Bayesian Approach. Journal of the Nigerian Association of Mathematical Physics, 51, 137-144.

Antara, I. M. Y., & Suryana, I. M. E. 2020. Pengaruh Tingkat Kepadatan Penduduk Terhadap Indeks Pembangunan Manusia di Provinsi Bali. Media Komunikasi Geografi, 21(1), 63-73. https://doi.org/10.23887/mkg.v21i1.22958

A'yun, I. Z., & Khasanah, U. 2022. The Impact of Economic Growth and Trade Openness on Environmental Degradation: Evidence from A Panel of ASEAN Countries. Jurnal Ekonomi & Studi Pembangunan, 23(1), 81-92. https://doi.org/10.18196/jesp.v23i1.13881

Baltagi, B. H. (2008). Econometrics Analysis of Panel Data (4th Edition). New York: John Wiley and Sons.

Biørn, E. (2004). Regression systems for unbalanced panel data: a stepwise maximum likelihood procedure. Journal of Econometrics, 122(2), 281–291. https://doi.org/10.1016/j.jeconom.2003.10.023

Bowerman, B. L. & O'connel, R. T. (1990). Linear Statistical Models and Applied Approach (2nd Edition). Boston: PWS-KNT.

Effendi, A., Wardhani, N. W. S., Fitriani, R., & Sumarningsih, E. (2020). Analisis Regresi: Teori dan Implementasi dengan R. Malang: Universitas Brawijaya Press.

Fernandes, A. A. R., & Solimun, S. (2019). Analisis Regresi dalam Pendekatan Fleksibel: Ilustrasi dengan Paket Program R. Malang: Universitas Brawijaya Press.

Fitriani, R., Nurjannah & Pusdikasari, Z. F. (2021). Dasar-Dasar Ekonometrika dan Terapannya dengan GRETL. Malang: Universitas Brawijaya Press.

Greene, W. H. (2012). Econometric Analysis (7th ed.). Boston, MA: Pearson Education.

Heshmati, A., Kim, J., & Park, D. (2014). Fiscal Policy and Inclusive Growth in Advanced Countries: Their Experience and Implications for Asia. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.2558908

Kuncoro, M. (2006). Ekonomika Pembangunan: Teori. Masalah, dan Kebijakan, Edisi, 4. Jakarta: Penerbit Salemba Empat.

Mahardika, A., & Yuliarmi, N. (2018). Pengaruh Jumlah Penduduk, Produksi, PDB dan Kurs Dollar Amerika Serikat Terhadap Impor Cabai Indonesia. E-Jurnal Ekonomi Pembangunan Universitas Udayana, 7(3), 502 - 530. Retrieved from https://ojs.unud.ac.id/index.php/eep/article/view/37842

Moon, H. R., & Perron, B. (2008). Seemingly Unrelated Regressions. The New Palgrave Dictionary of Economics, 1–6. https://doi.org/10.1057/978-1-349-95121-5_2296-1

Morrison, T. K. (1977). The Effects of Population Size and Population Density on the Manufactured Exports of Developing Countries. Southern Economic Journal, 43(3), 1368. https://doi.org/10.2307/1057796

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

Nisak, S. C. (2016). Seemingly Unrelated Regression Approach for GSTARIMA Model to Forecast Rain Fall Data in Malang Southern Region Districts. CAUCHY: Jurnal Matematika Murni Dan Aplikasi, 4(2), 57–64. https://doi.org/10.18860/ca.v4i2.3488

Novriansyah, M. A. (2018). Pengaruh Pengangguran dan Kemiskinan Terhadap Pertumbuhan Ekonomi di Provinsi Gorontalo. Gorontalo Development Review, 1(1), 59. https://doi.org/10.32662/golder.v1i1.115

Pangesti, I., & Susanto, R. (2018). Pengaruh Inflasi terhadap Indeks Pembangunan Manusia (IPM) di Indonesia. JABE (Journal of Applied Business and Economic), 5(1), 70. https://doi.org/10.30998/jabe.v5i1.3164

Pramoedyo, H., Ashari, A., & Fadliana, A. (2020). Forecasting and Mapping Coffee Borer Beetle Attacks Using GSTAR-SUR Kriging and GSTARX-SUR Kriging Models. ComTech: Computer, Mathematics and Engineering Applications, 11(2), 65–73. https://doi.org/10.21512/comtech.v11i2.6389

Silitonga, D. (2021). Pengaruh Inflasi Terhadap Produk Domestik Bruto (PDB) Indonesia Pada Periode Tahun 2010-2020. Esensi: Jurnal Manajemen Bisnis, 24(1), 111-122. Retrieved from https://ibn.e-journal.id/index.php/ESENSI/article/view/231

Sukirno, S. (2008). Mikroekonomi Teori Pengantar, (3rd Ed). PT. RajaGrafind Persada. Jakarta.

Wafiq, A. N., & Suryanto, S. (2021). The Impact of Population Density and Economic Growth on Environmental Quality: Study in Indonesia. Jurnal Ekonomi & Studi Pembangunan, 22(2), 301–312. https://doi.org/10.18196/jesp.v22i2.10533

Wau, T. (2022). Economic Growth, Human Capital, Public Investment, and Poverty in Underdeveloped Regions in Indonesia. Jurnal Ekonomi & Studi Pembangunan, 23(2), 189-200. https://doi.org/10.18196/jesp.v23i2.15307

Xu, X., Šarić, Ž., Zhu, F., & Babić, D. (2018). Accident severity levels and traffic signs interactions in state roads: a seemingly unrelated regression model in unbalanced panel data approach. Accident Analysis & Prevention, 120, 122–129. https://doi.org/10.1016/j.aap.2018.07.037

Zellner, A. (1962). An Efficient Method of Estimating Seemingly Unrelated Regressions and Tests for Aggregation Bias. Journal of the American Statistical Association, 57(298), 348–368. https://doi.org/10.1080/01621459.1962.10480664

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Published

2023-05-30

How to Cite

Pratama, M. L., Fitriani, R., & Astutik, S. (2023). Fix effect sur to analyze economic growth in developed and developing countries. Jurnal Ekonomi &Amp; Studi Pembangunan, 24(1), 164–181. https://doi.org/10.18196/jesp.v24i1.17821

Issue

Vol. 24 No. 1: April 2023

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Articles

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