Causal Links between Trade Openness and Foreign Direct Investment in Romania

Mudiyanselage, Malsha Mayoshi Rathnayaka; Epuran, Gheorghe; Tescașiu, Bianca

doi:10.3390/jrfm14030090

Cited by 36 publications

(30 citation statements)

References 30 publications

(42 reference statements)

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“…For instance, Saleem et al (2018) found bidirectional causality between labor cost and FDI in China. Lastly, this paper reveals bidirectional causality between FDI and TO in Bangladesh, which is consistent with Rathnayaka Mudiyanselage et al (2021) in the case of Romania but different from Saleem et al (2020) in the case of Bangladesh. Moreover, "TO causes FDI" and "FDI causes TO" both are natural relationships.…”

Section: Analysis Of Var Results and Granger Causality Testsupporting

confidence: 80%

Causality analysis of the determinants of FDI in Bangladesh: fresh evidence from VAR, VECM and Granger causality approach

Morshed

Hossain

2022

SN Bus Econ

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We tested the causality between FDI and its determinants in Bangladesh in the presence of structural break harnessing Vector Autoregression (VAR) model and Granger causality test. Regressors such as GDP growth rate, inflation, interest, corporate tax, exchange and wage rate, and trade openness (TO) have been used. VAR model finds that interest, tax, wage, and exchange rate do not affect inward FDI. However, the inflation rate and TO significantly impact the inward FDI in Bangladesh. The Granger causality test reveals a bidirectional causality in the FDIinflation and FDI-TO nexus, whereas other explanatory variables do not cause the FDI granger. Variance decomposition (VDC) and impulse response function (IRF) assessment approve strong, moderate, and poor or no explanatory power of TO, inflation, and other explanatory variables, respectively. Regarding FDI-inflation bidirectional causality, we observed both natural (inflation truly causes FDI) and fake causality (FDI does not necessarily cause inflation). Therefore, when inflation causes FDI, then Bangladeshi Taka (BDT) becomes strong against USD, which increases import and reduces export (import > export). Due to the negative trade balance, this is true for Bangladesh. However, if FDI causes inflation, it will depreciate BDT; consequently, the export will surpass the total import, which is not the case in Bangladesh. Therefore, inflation causes FDI in Bangladesh, and this punch line ends the ongoing debate in the FDI-inflation-exchange rate nexus in Bangladesh. Finally, we recommend decreasing the lending interest rates to encourage further investment, adopting tax holidays, developing a skilled and semi-skilled workforce to harness the advantage of lower wage rates, and being more open to facilitating FDI-led development.

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Section: Analysis Of Var Results and Granger Causality Testsupporting

confidence: 80%

Causality analysis of the determinants of FDI in Bangladesh: fresh evidence from VAR, VECM and Granger causality approach

Morshed

Hossain

2022

SN Bus Econ

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“…It confirms that inflation cannot account for major variations in FDI inflows to Sri Lanka throughout the years. This result support to the findings of [71][72][73][74].Surprisingly, the results in our study demonstrate no substantial association between FDI inflows and human capital, despite the fact that the function of human capital in attracting FDI is well recognized in the literature [31,39,50,78,83,86]. Finally, the R squared value associated the selected long run model is 0.871925.…”

Section: Resultssupporting

confidence: 89%

“…According to economic and investment theories, inflation encourages FDI through local and global shocks and influences other macroeconomic factors [43]. In most empirical investigations [3,7,43,57,69,70] there was a negative association between inflation and FDI inflows, while other studies [71][72][73][74] found no significant impact of inflation rate on FDI inflows. Human capital: Theoretical literature has reflected that human capital in host nations is a determinant of foreign investment in emerging countries.…”

Section: Literature Reviewmentioning

confidence: 99%

Determinants of FDI Inflows: Bounds Testing Approach

Adikari¹

2022

ijmei

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Nowadays, heightened academic interest in foreign direct investment (FDI) inflows derives from a shift in host-country policymakers' perspectives on encouraging and attracting more FDI, which would generate possibilities and assist developing nations in achieving sustainable development. This study analyzes the determinants of FDI inflows in Sri Lanka using secondary data from 1978 to 2019. We used the Autoregressive Distributed Lag (ARDL) bound testing procedure to examine the long-run relationships between variables. The result revealed that the gross domestic product (GDP) growth rate positively affects FDI inflows to Sri Lanka. A higher GDP paves the way to higher market size, leading to more FDI in Sri Lanka. Openness to trade also positively impacts foreign FDI inflows into Sri Lanka, and this effect is statistically significant. It means that trade liberalization policies implemented since 1978 have increased FDI inflows into Sri Lanka. The exchange rate has a significantly positive impact on FDI inflows to Sri Lanka.

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“…Impact of trade openness on environmental quality Trade openness has a connection and will influence FDI (Burange et al, 2019;Djulius, 2017;Makoni, 2018;Rakshit, 2022;Rathnayaka Mudiyanselage et al, 2021). Kumari et al (2021) found that there was a long term causal connection between FDI, trade openness and economic growth in India and FDI and trade openness influenced both ways.…”

Section: Literature Reviewmentioning

confidence: 99%

What are the factors that determine differing levels of environmental quality? Evidence from Java and other islands in Indonesia

Pujiati

Nurbaeti

Damayanti

2022

MEQ

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PurposeThis paper aims to identify variables that determine the differing levels of environmental quality on Java and other islands in Indonesia.Design/methodology/approachUsing a quantitative approach, secondary data were sourced from the Central Statistics Agency and the Ministry of Environment and Forestry. The data were obtained through the collection of documentation from 33 provinces in Indonesia. The analytical approach used was discriminant analysis. The research variables are Trade Openness, Foreign Direct Investment (FDI), industry, HDI and population growth.FindingsThe variables that distinguish between the levels of environmental quality in Indonesian provinces on the island of Java and on other islands are Industry, HDI, FDI and population growth. The openness variable is not a differentiating variable for environmental quality. The most powerful variable as a differentiator of environmental quality on Java Island and on other islands is the Industry variable.Research limitations/implicationsThis study has not classified the quality of the environment based on the Ministry of Environment and Forestry's categories, namely, the very good, good, quite good, poor, very poor and dangerous. For this reason, further research is needed using multiple discriminant analysis (MDA).Practical implicationsIndustry is the variable that most strongly distinguishes between levels of environmental quality on Java and other island, while the industrial sector is the largest contributor to gross regional domestic product (GDRP). Government policy to develop green technology is mandatory so that there is no trade-off between industry and environmental quality.Originality/valueThis study is able to identify the differentiating variables of environmental quality in two different groups, on Java and on the other islands of the Indonesian archipelago.

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Causal Links between Trade Openness and Foreign Direct Investment in Romania

Cited by 36 publications

References 30 publications

Causality analysis of the determinants of FDI in Bangladesh: fresh evidence from VAR, VECM and Granger causality approach

Causality analysis of the determinants of FDI in Bangladesh: fresh evidence from VAR, VECM and Granger causality approach

Determinants of FDI Inflows: Bounds Testing Approach

What are the factors that determine differing levels of environmental quality? Evidence from Java and other islands in Indonesia

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