Dynamic panel data modeling of Indonesia’s poverty level 2013-2022

Abstract

Poverty in Indonesia is a problem that needs special attention by the government. Poverty is due to the high level of inequality, unequal distribution of income, and the number of poor people, which continue to increase. Therefore, it can affect society’s economy. This research aims to identify incongruities between endogenous and exogenous variables that influence poverty levels in Indonesia. By applying a descriptive quantitative analysis approach for 2013-2022 in the form of secondary data from the Indonesian Central Statistics Agency, the research model uses dynamic panel data regression analysis based on the Generalized Method Of Moment method (GMM). The method was developed by Arellano-Bond, of which the two best models are First-Difference GMM and System GMM, which create an impartial, consistent, and efficient model for determining short-term ang long-term effects. The research results show that HDI has a significant negative impact on short-term and long-term relationships with poverty levels, resulting in low human resources. Exports have a significant negative impact on poverty levels in the short and long term. This means that if exports increase, poverty levels can be reduced. Imports have a significant positive impact on short-term and long-term with poverty levels. In import activities, the higher the price increases, the more people's purchasing power decreases. The results are declared to have a significant effect because the p-value is < significance of level 5% or 0.05. It is expected that the research will become reference material for macroeconomic development and further research regarding poverty alleviation.