The destructive effect of corruption on economic growth in Indonesia: A threshold model

摘要

A growing number of corruption cases in Indonesia have raised awareness of corruption's destructive effect on economic development, although no existing studies have considered the threshold value at which corruption hampers economic growth. This study assesses the effect of corruption on economic growth by taking a nonlinear approach to determine the corruption threshold. By analyzing the effect of corruption on economic growth across provinces in Indonesia over the 2004–2015 period, this study examines whether corruption works to the benefit of the provinces with low-corruption levels by supporting their economic growth when the number of corruption cases is below the corruption threshold. In contrast, corruption worsens economic growth in provinces with high levels of corruption when corruption exceeds the threshold. Different from other corruption studies in Indonesia, this study utilizes the number of corruption cases investigated by (KPK; Indonesia Corruption Eradication Commission) as the corruption measure. The corruption threshold effect is assessed using a sample-splitting and threshold model developed by Hansen (2000), and the endogeneity issue is properly addressed using the instrumental variable two-stage least squares (2SLS) estimator. The estimation results reveal that the impact of corruption indicates a growth-deteriorating effect for provinces with corruption levels below the threshold of 1.765 points, and the destructive effect of corruption appears stronger for provinces with corruption levels above the threshold. Another finding is that most provinces struggle with corruption problems, even while they have succeeded in maintaining their corruption levels below the threshold over time. Some provinces, such as Riau and West Java, experience severe corruption problems and have been in a high-corruption group over the last three years. However, some provinces, such as Lampung and North Sulawesi, manage to lower their corruption levels and shift to a low-corruption group.