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Publication Open Access Mapping causal relationships between migration and economic growth: A visual and empirical approach(Elsevier Ltd, 2025-09-19) Azmi, Y; Landersz, S; Dissanayake, P; Chloe, L; Jayathilaka, RThe focus of this study is to identify whether causal relationships exist between migration and economic growth across countries in the Asian continent. Real GDP per capita and net migration per capita were used to measure economic growth and net migration, respectively. A dataset comprising panel data from 1994 to 2023, covering 41 countries, was utilised. The Bootstrap Dumitrescu and Hurlin Granger non-causality test was conducted for a continental analysis of Asia. Further, the Granger causality Wald test was undertaken for in-depth country-level analysis. The empirical results indicate a unidirectional causality in Asian continent, and Eastern, and Western Asian sub reigns while other sub reigns indicated no causality. Additionally, while majority of the countries indicated no causality, seven countries namely, Saudi Arabia, Turkmenistan, Viet Nam, Sri Lanka, Macao SAR China, Malaysia and Rep. Korea indicated unidirectional causalities. Based on these findings, implications were made for policymakers when developing economic policies that leverage the economic potential of net migration.Publication Open Access Determining the influence of LPI, GCI and IR on FDI: A study on the Asia and Pacific Region(PLoS ONE, 2023-02-01) Wannisinghe, P; Jayakody, S; RathnayakeI, S; Wijayasinghe, D; Jayathilaka, R; Madhavika, NThis study examines the impact of the Logistics Performance Index (LPI), Global Competitiveness Index (GCI) and Interest Rates (IR) on Foreign Direct Investment (FDI) for the Asia & Pacific region. The study is original as extensive evidence on the impact of LPI, GCI and IR on FDI in the Asia & Pacific region are examined initially. For the years 2007, 2010, 2012, 2014, 2016 and 2018, data was gathered for 33 nations in the Asia and Pacific area. Data analysis was performed using a panel regression model and multiple linear regression. The findings of the study reveal that LPI, GCI and IR are the three major factors influencing FDI inflows into the economies. However, the impact of these factors varies from country to country. The results concluded that LPI positively impacts FDI in India, Korea, Lebanon, and Oman. In contrast, a negative influence was observed for China, Kuwait and the Philippines. GCI positively impacts FDI in China, Korea, Kuwait, Pakistan and the Philippines, while a negative impact was observed in Armenia, India, Lebanon. Furthermore, IR has a positive impact on FDI flows in China and Egypt while in Korea and Lebanon, a negative impact was observed. Therefore, policymakers should focus more on improving the infrastructural requirements and macroeconomic factors while considering the other countrylevel variables that influence the FDI in flow.
