Abstract

Economic growth is measured by changes in a country's Gross Domestic Product (GDP) which can be broken down into population and economic elements. This research was conducted to determine the conditions of economic growth in the country of Indonesia with a total of 34 provinces in the 2016-2021 observation period, a total of 204 samples. The data collection technique was carried out by downloading files on the official website of the Central Bureau of Statistics in Indonesia for 2016-2021, while data analysis was carried out using econometric models by comparing the FD-GMM Arellano-Bond and Sys-GMM Blundell-Bond models, then for the second stage determining which model is the best to use in modeling. Data processing in research using Stata software version 17.0. In panel data, economic variables are dynamic, meaning that the value of a variable can be influenced by the value of another variable and the value of the variable concerned, in the previous period, in addition to knowing the short-term and long-term impacts of economic growth. Based on panel data regression estimation, the best model is obtained. -GMM Blundell-Bond). The results of the study revealed that researchers found the results of data processing using the System Generalized Method of Moment (Sys-GMM Blundell-Bond) and FD-GMM ARELLANO-BOND economic growth in Indonesia is influenced by the human development index, poverty level, agglomeration, with the impact of elasticity on economic growth short term and long term.

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