TY - GEN
T1 - ASEAN foreign trade analysis using dynamic panel data and simultaneous regression model
AU - Kusrini, Dwi Endah
AU - Wildani, Zakiatul
AU - Azizah, Nur
N1 - Publisher Copyright:
© 2022 American Institute of Physics Inc.. All rights reserved.
PY - 2022/10/11
Y1 - 2022/10/11
N2 - Modeling of foreign trade, especially between ASEAN countries, needs to be done to determine the effect of changes in factors affecting foreign trade in this case measured by the amount of Foreign Direct Investment (FDI) to the growth of Gross Domestic Product (Growth GDP), Exports and Imports. Therefore, this study aims to review the simultaneous regression of panel data and dynamic panel data regression and analyze the results of modeling to get an idea of the influence between variables on short term and long term conditions on foreign trade in ASEAN. The study used two models: simultaneous regression modeling of panel data for FDI models, and dynamic panel data regression modeling for Export and Import. The results of simultaneous modeling of panel data for FDI show that there is an influence of Growth GDP, Degree of Openness and Labor Force on FDI on GDP with the goodness of fit model is 96.40%, and there is an influence of FDI on GDP, Gross Fixed Capital Formation on GDP and Balance of Trade on GDP Growth with determinant coefficient value is 88.29%, while the results of dynamic panel data modeling for exports and imports show that variables that have a significant positive effect on the ASEAN export model are Growth GDP, Real Effective Exchange Rate (REER) while gross fixed capital formation (GFCF) variables negatively affect. In addition, variables that have a significant positive effect on the ASEAN import model are Growth GDP and Real Effective Exchange Rate. The variable that provides the highest long-term elasticity to the import model is the Growth GDP variable.
AB - Modeling of foreign trade, especially between ASEAN countries, needs to be done to determine the effect of changes in factors affecting foreign trade in this case measured by the amount of Foreign Direct Investment (FDI) to the growth of Gross Domestic Product (Growth GDP), Exports and Imports. Therefore, this study aims to review the simultaneous regression of panel data and dynamic panel data regression and analyze the results of modeling to get an idea of the influence between variables on short term and long term conditions on foreign trade in ASEAN. The study used two models: simultaneous regression modeling of panel data for FDI models, and dynamic panel data regression modeling for Export and Import. The results of simultaneous modeling of panel data for FDI show that there is an influence of Growth GDP, Degree of Openness and Labor Force on FDI on GDP with the goodness of fit model is 96.40%, and there is an influence of FDI on GDP, Gross Fixed Capital Formation on GDP and Balance of Trade on GDP Growth with determinant coefficient value is 88.29%, while the results of dynamic panel data modeling for exports and imports show that variables that have a significant positive effect on the ASEAN export model are Growth GDP, Real Effective Exchange Rate (REER) while gross fixed capital formation (GFCF) variables negatively affect. In addition, variables that have a significant positive effect on the ASEAN import model are Growth GDP and Real Effective Exchange Rate. The variable that provides the highest long-term elasticity to the import model is the Growth GDP variable.
UR - http://www.scopus.com/inward/record.url?scp=85140244113&partnerID=8YFLogxK
U2 - 10.1063/5.0117377
DO - 10.1063/5.0117377
M3 - Conference contribution
AN - SCOPUS:85140244113
T3 - AIP Conference Proceedings
BT - 3rd International Conference on Mathematics and Sciences, ICMSc 2021
A2 - Nugroho, Rudy Agung
A2 - Allo, Veliyana Londong
A2 - Siringoringo, Meiliyani
A2 - Prangga, Surya
A2 - Wahidah, null
A2 - Munir, Rahmiati
A2 - Hiyahara, Irfan Ashari
PB - American Institute of Physics Inc.
T2 - 3rd International Conference on Mathematics and Sciences 2021: A Brighter Future with Tropical Innovation in the Application of Industry 4.0, ICMSc 2021
Y2 - 12 October 2021 through 13 October 2021
ER -