This study analyzes human development convergence and the impact of funds transfer to the regions using σ and β-convergence analysis method. Observations were made in all Indonesia’s provinces in the period 2010-2019. The coefficient of variation calculation shows a dispersion in the inequality of human development, which means that convergence occurred. This is also documented by the clustering analysis results developed in the study. The results are in line with the hypothesis of neoclassical theory, which shows the tendency for provinces with lower human development levels to grow relatively faster. The dynamic panel data approach with the GMM model shows that a model built with explanatory variables for transfer of funds to regions may lead to the process of convergence of human development – 2.21% per year or 31 years to cover the half-life of convergence. This is a consequence of the Special Allocation Fund and the Village Fund, which positively impact the convergence process, and the General Allocation Fund and the Revenue Sharing Fund with negative signs slowing the convergence process. This evidence opens opportunities to review the justification of the weighting component in determining the amount of funds transferred to the region to accelerate the convergence process of human development.

This paper examines how human capital and other economic variables, such as private investment, economic growth, government investment, inflation, and unemployment influence inequality in Indonesia’s provinces. We apply panel data model with fixed effect estimation for the data of 34 provinces from the period 2013 to 2019. We develop a new index for human capital using the education index approach. The results show that human capital has a negative and significant effect on income inequality. An increase in human capital is related to an increase in knowledge and competence due to the longer average school year and expectations of the school year. Human capital has increased the possibility of a person being accepted into the job market and earning a higher income; hence, it lowers income inequality. We also find that inflation leads to a higher gap of income distribution. A further implication of this situation is that the rise in inflation causes an increase in low-income people, and as a consequence, makes their lives worse off. This paper will be beneficial for policy-makers for whom human capital, which is measured using an education index, is an important factor that significantly affects income inequality, in addition to other economic factors.