{"title":"外国直接投资流入的决定因素:东盟+3国家的案例研究","authors":"Syrizal Kamis, Dayang Hasliza Muhd Yusuf","doi":"10.35631/ijemp.622009","DOIUrl":null,"url":null,"abstract":"Foreign direct investment (FDI) has the potential to stimulate economic growth and create employment opportunities. The recent significant decline in FDI inflows within Asean+3 (AS3) countries raise concerns about its potential impact on regional economic development. Numerous prior studies have examined a wide range of factors that can affect FDI, including interest rate, market size, inflation, and infrastructure. Notably, innovation has been overlooked as a potential factor in these previous studies. In this review, the patent serves as a proxy for innovation. The sophistication of the research and development can be of interest to foreign investors. This study examines whether improvements in terms of research and development can significantly affect foreign direct investment in the region. Based on previous empirical research, the results the decision is not yet conclusive for determinants of FDI inflows in AS3 countries. However, it's worth highlighting that there is currently a dearth of research in the context of AS3 countries on this subject. For the sake of examining the long-run relationship between the independent and dependent variables the auto regressive distributed lag (ARDL) model is applied in this study. The Panel Autoregressive Distributed Lag (Panel ARDL) is a statistical model employed for analyzing the connections between variables in a panel dataset.","PeriodicalId":486062,"journal":{"name":"International Journal of Entrepreneurship and Management Practices","volume":"46 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"DETERMINANTS OF FOREIGN DIRECT INVESTMENT INFLOWS: CASE STUDY OF ASEAN+3 COUNTRIES\",\"authors\":\"Syrizal Kamis, Dayang Hasliza Muhd Yusuf\",\"doi\":\"10.35631/ijemp.622009\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Foreign direct investment (FDI) has the potential to stimulate economic growth and create employment opportunities. The recent significant decline in FDI inflows within Asean+3 (AS3) countries raise concerns about its potential impact on regional economic development. Numerous prior studies have examined a wide range of factors that can affect FDI, including interest rate, market size, inflation, and infrastructure. Notably, innovation has been overlooked as a potential factor in these previous studies. In this review, the patent serves as a proxy for innovation. The sophistication of the research and development can be of interest to foreign investors. This study examines whether improvements in terms of research and development can significantly affect foreign direct investment in the region. Based on previous empirical research, the results the decision is not yet conclusive for determinants of FDI inflows in AS3 countries. However, it's worth highlighting that there is currently a dearth of research in the context of AS3 countries on this subject. For the sake of examining the long-run relationship between the independent and dependent variables the auto regressive distributed lag (ARDL) model is applied in this study. The Panel Autoregressive Distributed Lag (Panel ARDL) is a statistical model employed for analyzing the connections between variables in a panel dataset.\",\"PeriodicalId\":486062,\"journal\":{\"name\":\"International Journal of Entrepreneurship and Management Practices\",\"volume\":\"46 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-09-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Entrepreneurship and Management Practices\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.35631/ijemp.622009\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Entrepreneurship and Management Practices","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.35631/ijemp.622009","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
DETERMINANTS OF FOREIGN DIRECT INVESTMENT INFLOWS: CASE STUDY OF ASEAN+3 COUNTRIES
Foreign direct investment (FDI) has the potential to stimulate economic growth and create employment opportunities. The recent significant decline in FDI inflows within Asean+3 (AS3) countries raise concerns about its potential impact on regional economic development. Numerous prior studies have examined a wide range of factors that can affect FDI, including interest rate, market size, inflation, and infrastructure. Notably, innovation has been overlooked as a potential factor in these previous studies. In this review, the patent serves as a proxy for innovation. The sophistication of the research and development can be of interest to foreign investors. This study examines whether improvements in terms of research and development can significantly affect foreign direct investment in the region. Based on previous empirical research, the results the decision is not yet conclusive for determinants of FDI inflows in AS3 countries. However, it's worth highlighting that there is currently a dearth of research in the context of AS3 countries on this subject. For the sake of examining the long-run relationship between the independent and dependent variables the auto regressive distributed lag (ARDL) model is applied in this study. The Panel Autoregressive Distributed Lag (Panel ARDL) is a statistical model employed for analyzing the connections between variables in a panel dataset.