An Investigation of an Adaptive Neuro-Fuzzy Inference System to Model the Relationship among Natural Resources, Islamicity and Financial Development

• Published in: Revista argentina de clínica psicológica 2020-01, Vol.29 (4), p.524
• Main Authors: Hafezali Iqbal Hussain, Haider, Jahanzaib, Qayyum, Abdul, Kamarulzaman, Rashidah, Nazratul Aina Mohamad Anwar
• Format: Article
• Language: English
• Subjects: Exports; Natural resources
• ISSN: 0327-6716; 1851-7951
• DOI: 10.24205/03276716.2020.859

Understanding the relations among natural resources, Islamicity and financial development helps economies to formulate policies and develop sources to improve the financial development. The current study aims to apply a novel Adaptive Neuro-Fuzzy Inference System (ANFIS) to explore financial development in 6 Asian economies (Pakistan, Indonesia, Philippines, Qatar, Bahrain and Thailand). It is a model used for prediction that depends on fuzzy guidelines findings in the information and creates a link among criterion and predictor variables. In doing so, the study considers the data from 2005 to 2019 to construct the forecasting framework of financial development in selected Asian economies using two predictor variables (natural resources and Islamicity). The findings of the study show that financial development increases with the decline in natural resources in all the sample countries. The selected countries are similar with respect to natural resources as a predictor versus financial development as criterion. With respect to Islamicity index, the findings are similar in Pakistan, Indonesia and Thailand and alike in Philippines, Qatar and Bahrain. For concern, in Pakistan, Indonesia and Thailand, financial development increases with the decline in Islamicity index while it increases with the increase in Islamicity index in Philippines, Qatar and Bahrain. It is concluded that resource-centered nations have negative relationship with financial development. It seems that the economies with abundant natural resources increases the exports of these resources instead of using them in the process of production. The study concludes that this soft computing approach can be implemented as an efficient and effective tool for predicting financial development for future period based on anticipated targets of rising financial development in Asian economies. Moreover, the method established in this study can be utilized to find out the solutions of different prediction problems in the similar domains.