scholarly journals Environmental Regulation and Foreign Direct Investment: Evidence from China’s Eleventh and Twelfth Five-Year Plans

2020 ◽  
Vol 12 (6) ◽  
pp. 2528 ◽  
Author(s):  
Yuqing Ge ◽  
Yucai Hu ◽  
Shenggang Ren
Keyword(s):  
Foreign Direct Investment ◽  
Environmental Policy ◽  
Environmental Regulation ◽  
Direct Investment ◽  
So2 Emissions ◽  
Negative Effects ◽  
Environmental Enforcement ◽  
Fdi Inflows ◽  
Pollution Haven ◽  
Pollution Haven Effect

This paper investigates environmental regulation and its impact on inward foreign direct investment (FDI) in developing countries. Based on the Chinese province-industry-level panel data in the period 2001 to 2015, we use a difference-in-difference-in-differences (DDD) model to evaluate pollution haven behavior in the context of China’s 11th and 12th Five-Year Plans SO2 emissions reduction policy. The results show that the policy leads to fewer FDI inflows to its highly-polluting industries in provinces with tougher pollution reduction targets. In addition, the environmental policy has significantly inhibited FDI inflows in provinces with stricter environmental enforcement, while investment in provinces with worse environmental enforcement is insensitive to environmental policy. These findings are consistent with pollution haven behavior. In contrast, FDI in industries with high levels of technology is not significantly influenced by the policy, whereas the FDI in industries with low levels of technology shows a negative response to environmental policy. This is overall evidence confirming a pollution haven effect (PHE), although technology differences could alleviate the negative effects of environmental regulation on inward FDI.

scholarly journals Environmental Regulation, Two-Way Foreign Direct Investment, and Green Innovation Efficiency in China’s Manufacturing Industry

2018 ◽  
Vol 15 (10) ◽  
pp. 2292 ◽  
Author(s):  
Zhijun Feng ◽  
Bo Zeng ◽  
Qian Ming
Keyword(s):  
Foreign Direct Investment ◽  
Panel Data ◽  
Environmental Regulation ◽  
Direct Investment ◽  
Manufacturing Industry ◽  
Green Innovation ◽  
Negative Effects ◽  
Positive Effects ◽  
The Impact ◽  
Positive Effect

This paper adopts 2009 to 2015 panel data from 27 manufacturing industries in China. A Super-SBM model is used to measure the green innovation efficiency (GIE) of China’s manufacturing industry. A panel data model is then built to systematically examine the impact of environmental regulation (ER) and two-way foreign direct investment (FDI) on the GIE of China’s manufacturing industry under a unified analysis framework. The results are as follows: (1) the overall level of the green innovation efficiency in China’s manufacturing is low, and there is still great potential for improvement. Considering industry heterogeneity, the green innovation efficiency of patent-intensive manufacturing is significantly higher than that of non-patent-intensive manufacturing; (2) in terms of the whole manufacturing industry, ER and the interaction between ER and outward foreign direct investment (OFDI) have significantly negative effects on GIE, OFDI has significantly positive effects on GIE. (3) when considering industry heterogeneity, for patent-intensive manufacturing, ER and the interaction between ER and inward foreign direct investment (IFDI) have significantly negative effects on GIE, while IFDI has significantly positive effect on GIE. For non-patent-intensive manufacturing, ER and the interaction between ER and OFDI have significantly negative effects on GIE, while IFDI and the interaction between ER and IFDI have significantly positive effects on GIE.

scholarly journals Does Foreign Direct Investment Affect Tropospheric SO2 Emissions? A Spatial Analysis in Eastern China from 2011 to 2017

2020 ◽  
Vol 12 (7) ◽  
pp. 2878 ◽  
Author(s):  
Yuxiang Yan ◽  
Wusheng Hu
Keyword(s):  
Foreign Direct Investment ◽  
Direct Investment ◽  
Spatial Regression ◽  
Eastern China ◽  
Spillover Effect ◽  
Air Pollutant ◽  
Pollution Haven Hypothesis ◽  
So2 Emissions ◽  
Pollution Haven ◽  
Spatial Regression Analysis

Air pollution has attracted much attention worldwide. Sulfur dioxide (SO 2 ) is a major air pollutant in cities and affects human health seriously. The purpose of this paper is to examine how foreign direct investment affects SO 2 emissions and whether the pollution haven hypothesis exists in eastern China. On basis of the detailed data, we performed the spatial autocorrelation analysis and the spatial regression analysis. The results show that an increase in the foreign direct investment in a city is associated with a decline in SO 2 emissions in the same city, indicating that the pollution haven hypothesis does not hold in eastern China. But the spillover effect of the foreign direct investment is positive, indicating that a larger foreign direct investment in neighboring cities tends to raise SO 2 emissions in the local city.

Economic and legal instruments for the realization of foreign direct investment in infrastructure sectors of the economy

2020 ◽  
pp. 47-55
Author(s):  
Orshanska Marіana
Keyword(s):  
Foreign Direct Investment ◽  
Direct Investment ◽  
High Growth ◽  
Well Being ◽  
Gradual Improvement ◽  
Fdi Inflows ◽  
Investment Projects ◽  
Analysis And Synthesis ◽  
High Level ◽  
Fdi Attraction

The purpose of the article is to determine the nature, characteristics and keyproblems of the main types of economic and legal instruments for the realizationof foreign direct investment (FDI). the methodological basis of the study is asystematic approach to the processing and compilation of statistics and indicators,as well as methods for their comparison, analysis and synthesis and a method offorecasting decisions on the use of investment potential to increase the attractivenessand volume of FDI attraction. The scientific novelty of the research lies in theanalysis of greenfield and brownfield strategies as the main forms of FDIimplementation, the disclosure of the content and interpretation of data on thereal state of FDI attraction, the search for opportunities to improve the investmentclimate and effective mechanisms for attracting foreign investors. conclusions. Itis confirmed that the investment attractiveness and rating of the country in theinternational market are the main factors for attracting investors. Inaccessibleinfrastructure, inefficient judicial system, high level of corruption and imperfectlegislation are the main obstacles that need to be overcome in order to attractforeign investors’ funds, providing a full package of assistance and support ateach stage of the implementation of investment projects. Greenfield and brownfield(M&A) are the most effective forms of FDI in order to achieve high growth ratesof the domestic economy, improve the level of population well-being andinternationally enter Ukraine. An analysis of the statistics on the effectiveness ofinnovative enterprise development projects, the characteristics of economic andlegal instruments indicate the gradual improvement of the investment climate andthe promotion of FDI inflows into the region’s economy through the implementationof greenfield and brownfield strategies. Examples of effective implementation ofthese strategies in the creation of new enterprises, companies of foreignrepresentation, which are expanding their capacity and entering new domesticmarkets are given. Examples of the brownfield strategy have been analyzed torestart existing and high-quality structural and organizational changes in inefficiententerprises, which have given impetus to improving the economic environment,investment attractiveness of the economy of the region and the country as a whole.

An Empirical Investigation of India’s Outward Foreign Direct Investment: A Macro Perspective

2019 ◽  
Vol 5 (2) ◽  
pp. 79-88
Author(s):  
Dikshita Kakoti
Keyword(s):  
Foreign Direct Investment ◽  
Direct Investment ◽  
Real Effective Exchange Rate ◽  
Outward Foreign Direct Investment ◽  
Fdi Inflows ◽  
Long Run ◽  
Increasing Trend ◽  
Effective Exchange ◽  
Short Run ◽  
Effective Exchange Rate

Since 1990, globalization of Indian economy led to a speedy growth of foreign direct investment (FDI) inflows and simultaneously outward foreign direct investment (OFDI) also shows an increasing trend. However, India’s OFDI has attracted a little attention from the researchers and they have considered the OFDI in terms of commitments or approved equities. The motivation of this article is to investigate the India’s macro factors influencing actual OFDI flows from India by empirically recognizing four factors, namely gross domestic product, inward FDI, real effective exchange rate, and real interest rate over the period 1980–2016. The study has used Augmented Dicky-Fuller (ADF) and Phillips–Perron (PP) Unit root tests for checking the stationarity of the variable of the model. Later on, autoregressive distributive lag (ARDL) model and error correction mechanism is used for testing the long-run as well as short-run dynamics of the model. The result shows that all the selected variables have positive and significant influence on India’s outward investment flows.

scholarly journals Causal Links between Trade Openness and Foreign Direct Investment in Romania

2021 ◽  
Vol 14 (3) ◽  
pp. 90
Author(s):  
Malsha Mayoshi Rathnayaka Mudiyanselage ◽  
Gheorghe Epuran ◽  
Bianca Tescașiu
Keyword(s):  
Foreign Direct Investment ◽  
Direct Investment ◽  
Trade Openness ◽  
Test Procedure ◽  
Real Effective Exchange Rate ◽  
Foreign Direct Investments ◽  
Causality Test ◽  
Fdi Inflows ◽  
Distributed Lag ◽  
Long Run

In this increasingly globalized era, foreign direct investments are considered to be one of the most important sources of external financing for all countries. This paper investigates the causal relationship between trade openness and foreign direct investment (FDI) inflows in Romania during the period 1997–2019. Throughout this study, Trade Openness is the main independent variable, and Gross Domestic Product (GDP), Real Effective Exchange Rate (EXR), Inflation (INF), and Education (EDU) act as control variables for investigating the relationships between trade openness (TOP) and FDI inflow in Romania. The Auto Regressive Distributed Lag (ARDL) Bounds test procedure was adopted to achieve the above-mentioned objective. Trade openness has negative and statistically significant long-run and short-run relationships with FDI inflows in Romania throughout the period. Trade openness negatively affects the FDI inflow, which suggest that the higher the level of openness is, the less likely it is that FDI will be attracted in the long run. The result of the Granger causality test indicated that Romania has a unidirectional relationship between trade openness and FDI. It also showed that the direction of causality ran from FDI to trade openness.

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.

Effects of Infrastructure Development on Foreign Direct Investment in Kenya

2016 ◽  
Vol 8 (2) ◽  
pp. 93-110 ◽  
Author(s):  
Carol Teresa Wekesa ◽  
Nelson H. Wawire ◽  
George Kosimbei
Keyword(s):  
Foreign Direct Investment ◽  
Direct Investment ◽  
Time Series Data ◽  
Trade Openness ◽  
Transport Infrastructure ◽  
Series Data ◽  
Infrastructure Development ◽  
Fdi Inflows ◽  
Year 2000 ◽  
Quality Infrastructure

Kenya’s foreign direct investment (FDI) inflows as a percentage of GDP have been increasing negligibly over the last 4 years, increasing from 0.4 per cent in 2010 to 0.9 per cent in 2013. And yet evidence shows that quality infrastructure lowers the cost of doing business and thus attracts FDI. Kenya has visible signs of infrastructure inadequacy and inefficiencies despite the fact that since the year 2000, there has been increased budgetary allocation to the infrastructure sector. This study, therefore, sought to determine the effects of transport, energy, communication and water and waste infrastructure development on FDI inflows in Kenya. The study used annual time series data sourced from Central Bank of Kenya, World Bank and the United Nations Conference on Trade and Development (UNCTAD). Using multiple regression analysis, it was established that improved transport infrastructure, communication infrastructure, water and waste infrastructure, exchange rate, economic growth and trade openness are important determinants of FDI inflows into Kenya. Hence, for Kenya to attract more FDI, continued infrastructural development is key since quality infrastructure affords investors a conducive investment climate in which to operate.

scholarly journals Dynamic Causal Relationships among GDP, Exports, and Foreign Direct Investment (FDI) in the Developing Countries

2013 ◽  
Vol 14 ◽  
pp. 1-19 ◽  
Author(s):  
Mohsen Mehrara ◽  
Amin Haghnejad ◽  
Jalal Dehnavi ◽  
Fereshteh Jandaghi Meybodi
Keyword(s):  
Economic Growth ◽  
Developing Countries ◽  
Foreign Direct Investment ◽  
Strong Evidence ◽  
Direct Investment ◽  
The Other ◽  
Fdi Inflows ◽  
Long Run ◽  
Short Run ◽  
Growth Hypothesis

Using panel techniques, this paper estimates the causality among economic growth, exports, and Foreign Direct Investment (FDI) inflows for developing countries over the period of 1980 to 2008. The study indicates that; firstly, there is strong evidence of bidirectional causality between economic growth and FDI inflows. Secondly, the exports-led growth hypothesis is supported by the finding of unidirectional causality running from exports to economic growth in both the short-run and the long-run. Thirdly, export is not Granger caused by economic growth and FDI inflow in either the short run or the long run. On the basis of the obtained results, it is recommended that outward-oriented strategies and policies of attracting FDI be pursued by developing countries to achieve higher rates of economic growth. On the other hand, the countries can increase FDI inflows by stimulating their economic growth.

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