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SAR probit regression modeling using the fisher scoring approach: A case study of poverty levels on the island of Sumatra Panji Jiblathar; Germansah Germansah; Fadhlul Mubarak; Ellys Agustina; Nabilla Rida Tri Nisa
Priviet Social Sciences Journal Vol. 6 No. 4 (2026): April 2026
Publisher : Privietlab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55942/pssj.v6i4.1727

Abstract

The probit model is commonly used to study categorical response data. However, failing to account for spatial autocorrelation factors between regions can lead to inconsistent and biased parameter estimation results. This study focuses on examining the parameter estimation of the Spatial Autoregressive (SAR) Probit model through the Maximum Likelihood Estimation (MLE) method using the Fisher Scoring numerical iteration scheme. The model was implemented on poverty data across 131 regencies/cities in the Sumatra region for 2022. Empirical findings indicate that the GRDP growth rate, open unemployment rate, per capita expenditure, and expected years of schooling significantly affect the poverty rate. The results of this model development provide a prediction accuracy of 83.97%. This achievement is superior to that of the RIS Simulator technique, which only yields an accuracy of 74.05%. These results emphasize the advantages of the efficiency and accuracy of the Fisher Scoring approach in representing spatial dependencies in the poverty phenomenon in Sumatra.
Risk Measurement of Islamic Banking Financing Portfolio in Indonesia Based on Value at Risk Variance–Covariance Germansah Germansah; Panji Jiblathar; Fadhlul Mubarak
Benefit: Journal of Bussiness, Economics, and Finance Vol. 4 No. 2 (2026): BENEFIT: Journal Of Business, Economics, and Finance
Publisher : Lembaga Penelitian Dan Publikasi Ilmiah (lppi) Yayasan Almahmudi Bin Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70437/benefit.v4i2.1783

Abstract

This research is motivated by the importance of risk measurement of Islamic banking financing portfolios that have different contract characteristics. The purpose of this study is to analyze the risk of the financing portfolio based on the type of contract using the Value at Risk approach based on variance-covariance. The method used is a quantitative approach with data on the time sequence of Islamic banking financing in Indonesia, which is analyzed through the measurement of returns, volatility, and correlations between financings. The findings show that portfolio risk is heterogeneous, with project-based financing showing the highest level of risk, while asset-based financing shows a greater level of stability. Furthermore, it can be seen that interactive relationships can be leveraged to facilitate risk diversification. In conclusion, Value at Risk-based risk measurement is able to provide a more comprehensive picture of potential portfolio losses and support more effective risk management.