Corruption and foreign direct investment: Bayesian analysis approach

Abstract

The paper is aimed to analyze the impact of corruption control on foreign direct investment (FDI). The dataset is collected from ten Association of Southeast Asian Nations (ASEAN) countries (including Brunei Darussalam, Indonesia, Cambodia, Lao PDR, Myanmar, Malaysia, Philippines, Singapore, Thailand, and Vietnam) during the period 2002–2021. The paper utilizes the Bayesian method for estimation in the research model, highlighting its superiority in estimating regression results as a probability distribution and enhancing the stability of estimation outcomes (McNeish, 2016). Moreover, to test the robustness of the estimation results, the paper also conducts the estimation using traditional methods, including the generalized method of moments (GMM) proposed by Arellano and Bond (1991). By employing various estimation methods, the research results ensure robustness, increase reliability, and offer a more detailed explanation of the findings. Both the Bayesian and other traditional estimation methods reveal a positive impact of corruption control on FDI in the ASEAN countries. Particularly, the Bayesian estimation results show a 93.7 percent probability of this impact, which is an interesting finding compared to previous studies. Additionally, FDI is positively influenced by economic growth and trade openness while negatively affected by unemployment. The findings are significant for these countries, especially in enhancing their abilities to attract FDI.