DETERMINAN PENANAMAN MODAL ASING LANGSUNG DI ASEAN

2012 ◽  
Vol 7 (1) ◽  
pp. 75
Author(s):  
Joko Susanto
Keyword(s):  
Foreign Direct Investment ◽  
Panel Data ◽  
Data Model ◽  
Direct Investment ◽  
Multinational Enterprises ◽  
Statistical Data ◽  
Regression Equation ◽  
Panel Data Model ◽  
Market Size ◽  
Research Analysis

This research analysis the factors’ that determine the foreign directinvestment (FDI) in ASEAN’s countries especially Indonesia, Malaysia, Philippine and Thailand during 1990-2009. Multinational Enterprises’ (MNE) must decideto choose a locationfor relocating its’ factory by market seeking dan resources seeking strategy. Based on this statement, it can be obtained the regression equation with foreign direct investment is a function of market size, worker’s productivity and infrastructure of road. Statistical data of UNESCAP was used in this research. The regression was base on the panel data model, while the estimation was based on common effects model. This results showthat the market size, worker’s productivity and availability of infrastructure road could be an importance consideration for MNE’s in their choice for FDI.Keywords: foreign direct investment, market size, worker’s productivity, infrastructure of road

scholarly journals Main Determinants Influencing Inward and Outward Foreign Direct Investments in Thailand: Comparisons and Vital Implications

2021 ◽  
pp. 1-25
Author(s):  
Hsiang-Hsi Liu ◽  
Pitprapha Dejphanomporn
Keyword(s):  
Foreign Direct Investment ◽  
Panel Data ◽  
Data Model ◽  
Direct Investment ◽  
Bilateral Trade ◽  
Important Determinant ◽  
Trade Agreements ◽  
Panel Data Model ◽  
Market Size ◽  
Main Determinants

Abstract Foreign direct investment (FDI) has played an important role in the evolution of globalization and is the cornerstone of industrial expansion and economic development. From 1988 to 1990 till now, Thailand has been one of the main destinations of FDI, namely inward FDI (IFDI). However, outward foreign direct investment (OFDI) increased rapidly from 2003 to 2011, and it continues to grow. Although initially a net importer, Thailand has transformed into a net exporter of direct investment in 2011. Since 2003, Thailand has entered a stage of re-emergence of OFDI, and this growth trend of OFDI will continue in the future. The purpose of this study is to investigate the main determinants of Thailand's IFDI and OFDI, and apply a panel data model to determine which determinants have a significant impact on Thailand's IFDI and OFDI. We considered the FDI flows between Thailand and its five FDI partners (Japan, Hong Kong, the Netherlands, Singapore and the United States) from 1997 to 2014, where IFDI was 1997-2014, and 2004-2014 was OFDI. Regarding the determinants of Thailand's IFDI and OFDI, the market size (relative per capita GDP), Thailand's openness, relative R&D intensity and bilateral trade agreements have a positive impact on FDI decisions for both IFDI and OFDI. Relative wages and geographic distance have opposite effects on Thailand's IFDI and OFDI. Specifically, our empirical results show that market size is the most important determinant of IFDI inflows into Thailand, while the most important determinant of Thai OFDI is bilateral trade agreements. JEL classification numbers: F14, F23, F43. Keywords: Foreign Direct Investment, Panel Data Model, Fixed Effects, Generalized Least Squares (GLS).

scholarly journals Allocation of foreign direct investment across brazilian states

2013 ◽  
Vol 43 (2) ◽  
pp. 241-269 ◽  
Author(s):  
Maurício Mesquita Bortoluzzo ◽  
Sergio Naruhiko Sakurai ◽  
Adriana Bruscato Bortoluzzo
Keyword(s):  
Foreign Direct Investment ◽  
Panel Data ◽  
Foreign Investment ◽  
Direct Investment ◽  
Transport Infrastructure ◽  
Market Size ◽  
Consumer Market ◽  
Determining Factors ◽  
Econometric Study

Foreign direct investment (FDI) has become increasingly important for the Brazilian economy: the ratio of FDI inflow to the country's gross domestic product (GDP) increased from a 0.6% average in the 1980's to 2.5% from 2001 to 2010, according to data from UNCTAD. However, there is great inequality in the distribution of this investment among Brazilian federation units. This study aims at investigating the determining factors for the location of foreign direct investment across Brazilian states, based on an econometric study with panel data for the years 1995, 2000 and 2005. The results showed that foreign investment responded positively to consumer market size, quality of labor and transport infrastructure, but negatively to cost of labor and tax burden.

Empirical Analysis of the Impact of FDI on China‘s Environment

2013 ◽  
Vol 726-731 ◽  
pp. 1001-1005
Author(s):  
Yang Xu ◽  
Wen Bin Shang
Keyword(s):  
Foreign Direct Investment ◽  
Environmental Effects ◽  
Data Model ◽  
Direct Investment ◽  
Panel Data Model ◽  
The West ◽  
Fdi Inflows ◽  
Policy Suggestions ◽  
Negative Environmental Impact ◽  
The Impact

In this paper, the panel data model of China's 29 provinces from 2000 to 2008,to study the environmental effects of foreign direct investment, and analysis the differences of the environmental effects of foreign direct investment.from the eastern, central and western three economic belts. Empirical results show that, FDI inflows have a negative environmental impact to China, and this effect is weaker in the east and stronger in the west. Relative policy suggestions are given based on the research.

scholarly journals The Location Choice of Foreign Direct Investment and Economic Development in Africa

2021 ◽  
Vol 13 (10) ◽  
pp. 69
Author(s):  
Abdisalan Salad Warsame
Keyword(s):  
Economic Development ◽  
Foreign Direct Investment ◽  
Natural Resource ◽  
Direct Investment ◽  
Multinational Enterprises ◽  
Developing Economies ◽  
Location Choice ◽  
Market Size ◽  
Location Choices ◽  
Large Market

Foreign Direct Investment (FDI) inflow to Africa has unevenly distributed investment location choices of multinational enterprises because of some exogenous economic factors associated with the locations, which vary across countries in Africa. The data used in the paper comes from Financial Times, World Bank, African Development Bank. This paper investigated what determines the location choice of FDI inflow to Africa using data on 3,768 firms from 88 countries making location choices in 54 African countries using a multicategory logistic regression. The findings show that: (1) the natural resource seeking enterprises invest more in landlocked countries relative to manufacturing and tertiary sector; (2) the natural resource seeking firms are less concerned about local market size and location’s economic condition comparing to manufacturing and service industries; (3) despite the accusation against the multinational enterprises (MNEs) for exploiting Africa’s natural resources, most of the MNEs choose locations with a large market size and better economic development; (4) the MNEs from developed economies prefer the location with a large market size and a better-developed economy comparing to those from the developing economies.

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