Pemodelan Spasial Rasio Utang Pemerintah di Negara G20 Tahun 2003-2017

Saputro, Agung Eddy Suryo and Lukiswati, Intan and Soleh, Agus M Soleh and Andriansyah, Andriansyah (2018): Pemodelan Spasial Rasio Utang Pemerintah di Negara G20 Tahun 2003-2017.

Abstract

The ability to manage government debt is very important for a country. The government debt to GDP ratio, indicating a country ability to pay its debts, is often used as a limit to the amount that a government can issue. By using Geographically Weighted Panel Regression (GWPR) with location distance weighting, this study is aimed at describing the distribution pattern, classifying, and modelling the government debt ratios in G20 countries by observing spatial effects. The results show that the GWPR is the best model compared to the global panel regression in identifying that the government debt is influenced by inflation, final consumption, and population growth.

• Item Type: MPRA Paper
• English Title: Spatial Modelling Government Debt Ratios in G20 Countries 2003-2017
• Language: Indonesian
• Keywords: G20. GWPR, Ratio of Government Debt, Spatial
• Subjects: F - International Economics > F3 - International Finance > F34 - International Lending and Debt Problems; F - International Economics > F3 - International Finance > F37 - International Finance Forecasting and Simulation: Models and Applications

References

Abanyam, E.I., & Angahar, P.A. (2015). The Effect of The Global Financial Crisis and The Sovereign Debt Crisis on Public Sector Accounting: A Contextual Analysis. International Journal of Academic Research in Accounting, Finance, and Management Sciences, 5(1), 77-79.

Anselin, L. (1993). The Moran Scatterplot as An Esda Tool to Asses Local Instability in Spasial Association. Research Paper, 9330.

Baum, A., Cristina, C.W., & Philipp, R. (2013). Debt and Growth: New Evidence for The Euro Area. Journal of International Money and Finance, 32, 809-821.

[BPS] Badan Pusat Statistik. (2007). Memahami Data Strategis yang Dihasilkan BPS. Jakarta: BPS.

[BPS] Badan Pusat Statistik. (2017). Produk Domestik Bruto Triwulan 2013-2017. Jakarta: BPS.

Bruna, F., & Danlin, Y. (2016). Geographically Weighted Panel Regression and Development Accounting for European Regions. International Conference on Regional Science.

Calvo, G.A., Alejandro, I., & Ernesto, T. (2003). Sudden Stops, The Real Exchange Rate, and Fiscal Sustainability: Argentina’s Lessons. NBER Working Paper Series, 9838.

Dewi, RK. (2015). Kerjasama G20 dalam Mengatasi Krisis Keuangan Global. Tesis. Yogyakarta: Universitas Gajah Mada.

Egert, B. (2015). Public Debt, Economic Growth and Nonlinear Effecrs: Myth or Reality? Journal of Macroeconomics, 43, 226-238.

Elhorst, J.P. (2010). Spatial Panel Data Models. Fischer MM, Getis A, editor, Handbook of Applied Spatial Analysis. New York: Springer.

Forslund, K., Lycia, L., & Ugo, P. (2011). The Determinants of The Composition of Public Debt in Developing and Emerging Market Countries. Reviews of Develompment Finance, 1, 207-222.

Fotheringham, A. S., Brunsdon, C., & Charlton M. (2002). Geographically Weighted Regression the Analysis of Spatially Varying Relationships. Chichester: Wiley.

Guscina, A. (2008). Impact of Macroeconomic, Political, and Institutional Factors on The Structure of Government Debt in Emerging Market Countries. IMF Working Paper, WP/08/205.

[Kemenkeu] Kementerian Keuangan. (2016). Profil Utang Pemerintah Pusat (Pinjaman dan Surat Berharga Negara). Jakarta: Kemenkeu.

[Kemenkeu] Kementerian Keuangan. (2017). Infografis Utang 2017. Jakarta: Kemenkeu.

[Kemenlu] Kementerian Luar Negeri. (2016). Diplomasi Ekonomi pada G20: Perkembangan pada Sherpa Track. Jakarta: Kemenlu.

Reinhart, C., Vincent, R.R., & Kenneth, S.R. (2012). Public Debt Overhangs: Advanced Economy Episodes Since 1800. Journal of Economic Perspectives, 26(3), 69-86.

Swamy, V. (2015). Goverment Debt and Its Macroeconomic Determinants – An Empirical Investigation. Munich Personal RePEc Archive Paper, 64106.

Wiennata, PP. (2014). Faktor-Faktr yang Mempengaruhi Pertumbuhan Ekonomi pada Negara G20. Skripsi. Semarang: Universitas Diponegoro.

Yu, D. (2010). Exploring Spatiotemporally Varying Regressed Relationships: The Geographically Weighted Panel Regression Analysis. The International Archives of The Photogrammetry, Remote Sensing and Spatial Information Sciences, 38(2),134-139.

Yudiatmaja, W.E. (2012). Jebakan Utang Luar Negeri Bagi Beban Perekonomian dan Pembangunan Indonesia. Jurnal Ilmiah Administrasi Publik dan Pembangunan, 3(1), 453-462.