Econometric Model of Economic Growth In Indonesia Using Dynamic Panel Data Using the FD-GMM Arellano-Bond and SYS-GMM Blundell-Bond Approaches

Ashari Gunawan, F. A. Triansyah, Reyna Karlina, Gustina Yusuf, Aulia Rachma Dinantika, Anung Wahyudi
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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.
使用FD-GMM Arellano-Bond和SYS-GMM Blundell-Bond方法的动态面板数据的印度尼西亚经济增长计量经济模型
经济增长是通过一个国家的国内生产总值(GDP)的变化来衡量的,GDP可以分为人口和经济因素。本研究以2016-2021年观察期共有34个省份的印度尼西亚为研究对象,共204个样本,确定该国的经济增长状况。数据收集技术是通过在印度尼西亚中央统计局官方网站下载2016-2021年的文件进行的,而数据分析是通过比较FD-GMM Arellano-Bond和Sys-GMM Blundell-Bond模型来使用计量经济模型进行的,然后在第二阶段确定哪种模型最适合用于建模。本研究使用Stata 17.0版本软件进行数据处理。在面板数据中,经济变量是动态的,这意味着一个变量的值除了知道经济增长的短期和长期影响外,还可能受到另一个变量的值和有关变量在前一时期的值的影响。基于面板数据回归估计,得到最佳模型。gmm Blundell-Bond)。研究结果表明,采用系统广义矩法(Sys-GMM Blundell-Bond)和FD-GMM ARELLANO-BOND进行数据处理后发现,印度尼西亚的经济增长受到人类发展指数、贫困水平、集聚的影响,弹性对经济增长的影响有短期和长期。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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