Open AccessThe Effect of Foreign Direct Investment Human Capital and Community Welfare
Author(s) -
Ifqi Khairunnisa,
Sri Hartojo,
Yeti Lis Purnamadewi
Publication year - 2021
Publication title -
international journal of scientific research in science, engineering and technology
Language(s) - English
Resource type - Journals
eISSN - 2395-1990
pISSN - 2394-4099
DOI - 10.32628/ijsrset218523
Subject(s) - foreign direct investment , economics , gross domestic product , human capital , per capita , unemployment , poverty , labour economics , welfare , gross private domestic investment , economic inequality , simultaneous equations model , gross fixed capital formation , investment (military) , per capita income , real gross domestic product , macroeconomics , inequality , return on investment , economic growth , open ended investment company , market economy , production (economics) , population , mathematical analysis , demography , mathematics , sociology , politics , political science , law , econometrics
National development goals are not merely to create growth in Gross Domestic Product (GDP) and high per capita income. But more than that, it expected to alleviate poverty levels and income inequality in every class of society. Foreign Direct Investment (FDI) one of the most important investment to accelerate economic growth. The advantages of FDI inflow for host country are: capital accumulation; job creation; transfer of technology and management; and access to international market networks. This study aims to determine the relationship between FDI, economic growth, human capital, and community welfare. The quantitative analysis method in this study uses a simultaneous equation system model with six structural equations: domestic investment, economic growth, public consumption, education, health, unemployment and poverty. In addition, there are 3 identity equations: investment equation, the labour force, and economic growth. All data is a combination of cross-sectional and time-series data. The cross-section data used are 33 provinces in Indonesia and the time series data for the period 2010 to 2019.