The Relationship between Foreign Direct Investment and Environmental Pollution in Developing Countries: Evidence from simultaneous equations estimation | ||
| المجلة العلمية للإقتصاد و التجارة | ||
| Article 12, Volume 52, Issue 3, October 2022, Pages 429-464 PDF (505.27 K) | ||
| Document Type: المقالة الأصلية | ||
| DOI: 10.21608/jsec.2022.260526 | ||
| Author | ||
| Amira Tohamy Eltayb | ||
| Faculty of Commerce, Zagazig University Arab Republic of Egypt | ||
| Abstract | ||
| This study aimed at measuring the impact of Foreign Direct Investment (FDI) on four pollutant emissions in developing countries. To achieve this goal, the researcher used the unbalanced panel data of 73 developing countries, representing different regions and income levels, during the time period 1990 – 2016 with a total number of 1641 observations. Following the steps of Copeland and Taylor (2003) and Bao, Chen and Song (2011), an econometric model of six simultaneous equations was designed and the 3 SLS method was applied to estimate the scale, technique and composition effects of Foreign Direct Investment on pollutant emissions in the countries under study. According to the study results, Foreign Direct Investment reduces carbon emissions through encouraging the adoption of less polluting modern techniques and speeding up structural economic changes in developing countries. However, its positive effect through increasing the scale of the economy clearly outweighs its other two negative effects. Briefly, Foreign Direct Investment has a positive total effect on carbon emissions due to its large scale effect. On the other hand, the negative FDI technique and composition effects on the rest of the pollutants by far exceed the corresponding FDI positive scale effect. Hence, the total FDI effect varies according to the kind of pollutant under consideration. | ||
| Keywords | ||
| Foreign Direct Investment; Environmental Pollution; Carbon Emissions; The Simultaneous Equations System; Developing Countries; The Scale Effect; The Technique Effect; The Composition Effect; The Three-Stages Least Squares (3SLS) Method; The Two-Stages Least Squares (2SLS) Method | ||
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