Pusparini, Wiendu Andaru (2025) Analisis Peran Foreign Direct Investment Dalam Mendorong Transisi Ekonomi Hijau Di Indonesia Melalui Pendekatan Autoregressive Distributed Lag - Error Correction Model. Other thesis, Institut Teknologi Sepuluh Nopember.
![[thumbnail of 5006211035-Undergraduate_Thesis.pdf]](http://repository.its.ac.id/style/images/fileicons/text.png) |
Text
5006211035-Undergraduate_Thesis.pdf - Accepted Version Restricted to Repository staff only Download (4MB) | Request a copy |
Abstract
Indonesia berkomitmen untuk menurunkan emisi karbon melalui berbagai kebijakan strategis. Salah satu langkah konkret yang diambil adalah mengadopsi konsep ekonomi hijau sebagai dasar pembangunan yang fokus pada transisi menuju sistem yang lebih ramah lingkungan dan berkelanjutan. Penelitian ini bertujuan untuk menganalisis Foreign Direct Investment (FDI) pada empat sektor prioritas yang mendorong transisi ekonomi hijau, yaitu sektor energi & ekstraktif, manufaktur, konektivitas, dan sumber daya alam terbarukan (SDAT). Analisis dilakukan melalui pendekatan metode Autoregressive Distributed Lag - Error Correction Model untuk mengkaji hubungan jangka pendek dan jangka panjang FDI terhadap konsentrasi CO2 di Indonesia. Data yang digunakan mencakup data triwulanan dari tahun 2010 hingga 2023. Hasil penelitian menunjukkan bahwa sektor manufaktur dan SDAT berpengaruh signifikan terhadap konsentrasi CO₂ dalam jangka panjang, dengan sektor manufaktur berpengaruh positif dan sektor SDAT berpengaruh negatif. Sementara itu, dalam jangka pendek investasi di sektor energi & ekstraktif dan manufaktur cenderung menurunkan konsentrasi CO₂, sedangkan investasi di sektor SDAT justru mendorong peningkatan konsentrasi CO₂. Dengan demikian, pemerintah harus mengarahkan kebijakan investasi untuk meningkatkan daya tarik FDI di sektor SDAT dengan strategi yang mempertimbangkan dampak jangka pendeknya. Selain itu, diperlukan pengawasan dan regulasi yang ketat untuk aliran FDI di sektor energi & ekstraktif serta manufaktur. Langkah ini dapat mempercepat transisi menuju ekonomi hijau di Indonesia.
============================================================================================================================================
Indonesia is committed to reducing carbon emissions through various strategic policies. One concrete step taken is the adoption of the green economy concept as the foundation for development, focusing on the transition toward a more environmentally friendly and sustainable system. This study aims to analyze Foreign Direct Investment (FDI) in four priority sectors that drive the transition to a green economy: the energy & extractive sector, manufacturing, connectivity, and renewable natural resources (SDAT). The analysis is conducted using the Autoregressive Distributed Lag-Error Correction Model (ARDL-ECM) approach to examine the short-term and long-term relationships between FDI and CO₂ concentration in Indonesia. The study uses quarterly data from 2010 to 2023. The results indicate that the manufacturing and SDAT sectors significantly influence CO₂ concentration in the long run, with the manufacturing sector having a positive effect and the SDAT sector having a negative effect. In the short term, however, investment in the energy & extractive and manufacturing sectors tends to reduce CO₂ concentration, while investment in the SDAT sector appears to increase CO₂ concentration. Therefore, the government should direct investment policies to enhance the attractiveness of FDI in the SDAT sector with strategies that account for its short-term impacts. In addition, strict supervision and regulation are necessary for FDI flows in the energy & extractive and manufacturing sectors. These measures can accelerate the transition to a green economy in Indonesia.
| Item Type: | Thesis (Other) |
|---|---|
| Uncontrolled Keywords: | ARDL, ECM, ekonomi hijau, emisi karbon, FDI, carbon emissions, ECM, FDI, green economy |
| Subjects: | H Social Sciences > HA Statistics H Social Sciences > HA Statistics > HA31.3 Regression. Correlation. Logistic regression analysis. |
| Divisions: | Faculty of Science and Data Analytics (SCIENTICS) > Actuaria > 94203-(S1) Undergraduate Thesis |
| Depositing User: | Wiendu Andaru Pusparini |
| Date Deposited: | 04 Aug 2025 00:21 |
| Last Modified: | 04 Aug 2025 00:21 |
| URI: | http://repository.its.ac.id/id/eprint/126078 |
Actions (login required)
 |
View Item |