Foreign Direct Investment and Host Country Wages: New Evidence from Irish Plant Level Panel Data

2004 ◽  
Author(s):  
Frances Ruane ◽  
Ali Ugur
Keyword(s):  
Foreign Direct Investment ◽  
Panel Data ◽  
Host Country ◽  
Direct Investment ◽  
Plant Level ◽  
New Evidence

scholarly journals The Relationship Between Information & Communication Technology and Foreign Direct Investment Inflow to Africa

2021 ◽  
Vol 13 (5) ◽  
pp. 22
Author(s):  
Abdisalan Salad Warsame
Keyword(s):  
Foreign Direct Investment ◽  
Panel Data ◽  
Communication Technology ◽  
Host Country ◽  
Direct Investment ◽  
Foreign Direct Investment Inflow ◽  
Information Communication ◽  
Difference In Differences ◽  
Ict Infrastructure ◽  
The Relationship

This paper examined the relationship between the increasing Information & Communication Technology (ICT) infrastructure in Africa and foreign direct investment inflow to Africa using panel data sourced from ITU and WDI over 17 years (1998-2014). The paper applies both the fixed-effect and difference-in-differences models. The results indicate that there is a positive correlation between FDI inflow and ICT level in the host country.  The surge in ICT infrastructure in 2009 has substantially increased the FDI inflow to Africa. This increase in FDI inflow was more in the countries that have access to the sea than the countries that have no access to the sea. In other words, the average scale change in FDI inflow to the countries with no access to the sea is smaller than the countries with the coastline.

Determinants of foreign direct investment inflow to the agricultural sector: a panel-data analysis

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Seyed Reza Zeytoonnejad Mousavian ◽  
Seyyed Mehdi Mirdamadi ◽  
Seyed Jamal Farajallah Hosseini ◽  
Maryam Omidi NajafAbadi
Keyword(s):  
Developing Countries ◽  
Foreign Direct Investment ◽  
Panel Data ◽  
Host Country ◽  
Direct Investment ◽  
Agricultural Sector ◽  
Fdi Inflows ◽  
Content Type ◽  
Main Determinants ◽  
Determinants Of Fdi

PurposeForeign Direct Investment (FDI) is an important means of boosting the agricultural sectors of developing economies. The first necessary step to formulate effective public policies to encourage agricultural FDI inflow to a host country is to develop a comprehensive understanding of the main determinants of FDI inflow to the agricultural sector, which is the main objective of the present study.Design/methodology/approachIn view of this, we take a comprehensive approach to exploring the macroeconomic and institutional determinants of FDI inflow to the agricultural sector by examining a large panel data set on agricultural FDI inflows of 37 countries, investigating both groups of developed and developing countries, incorporating a large list of potentially relevant macroeconomic and institutional variables, and applying panel-data econometric models and estimation structures, including pooled, fixed-effects and random-effects regression models.FindingsThe general pattern of our findings implies that the degree of openness of an economy has a negative effect on FDI inflows to agricultural sectors, suggesting that the higher the degree of openness in an economy, the lower the level of agricultural protection against foreign trade and imports, and thus the less incentive for FDI to inflow to the agricultural sector of the economy. Additionally, our results show that economic growth (as an indicator of the rate of market-size growth in the host economy) and per-capita real GDP (as an indicator of the standard of living in the host country) are both positively related to FDI inflows to agricultural sectors. Our other results suggest that agricultural FDI tends to flow more to developing countries in general and more to those with higher standards of living and income levels in particular.Originality/valueFDI inflow has not received much attention with respect to the identification of its main determinants in the context of agricultural sectors. Additionally, there are very few panel-data studies on the determinants of FDI, and even more surprisingly, there are no such studies on the main determinants of FDI inflow to the agricultural sector. We have taken a comprehensive approach by studying FDI inflow variations across countries as well as over time.

scholarly journals Is Russia successful in attracting foreign direct investment? Evidence based on gravity model estimation

2016 ◽  
Vol 16 (3) ◽  
pp. 245-267 ◽  
Author(s):  
Oleg Mariev ◽  
Igor Drapkin ◽  
Kristina Chukavina
Keyword(s):  
Foreign Direct Investment ◽  
Gravity Model ◽  
Host Country ◽  
Direct Investment ◽  
Recipient Country ◽  
Developed Countries ◽  
Likelihood Method ◽  
Empirical Estimation ◽  
Fdi Inflows ◽  
Russian Economy

Abstract The aim of this paper is twofold. First, it is to answer the question of whether Russia is successful in attracting foreign direct investment (FDI). Second, it is to identify partner countries that “overinvest” and “underinvest” in the Russian economy. We do this by calculating potential FDI inflows to Russia and comparing them with actual values. This research is associated with the empirical estimation of factors explaining FDI flows between countries. The methodological foundation used for the research is the gravity model of foreign direct investment. In discussing the pros and cons of different econometric methods of the estimation gravity equation, we conclude that the Poisson pseudo maximum likelihood method with instrumental variables (IV PPML) is one of the best options in our case. Using a database covering about 70% of FDI flows for the period of 2001-2011, we discover the following factors that explain the variance of bilateral FDI flows in the world economy: GDP value of investing country, GDP value of recipient country, distance between countries, remoteness of investor country, remoteness of recipient country, level of institutions development in host country, wage level in host country, membership of two countries in a regional economic union, common official language, common border and colonial relationships between countries in the past. The potential values of FDI inflows are calculated using coefficients of regressors from the econometric model. We discover that the Russian economy performs very well in attracting FDI: the actual FDI inflows exceed potential values by 1.72 times. Large developed countries (France, Germany, UK, Italy) overinvest in the Russian economy, while smaller and less developed countries (Czech Republic, Belarus, Denmark, Ukraine) underinvest in Russia. Countries of Southeast Asia (China, South Korea, Japan) also underinvest in the Russian economy.

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

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