This dissertation analyzes the effects of non-traditional endowments (R&D stock and biotech land) on trade of genetically-modified sensitive industries. The study also explores the effects of differences in institutional endowments (intellectual property rights and regulatory regimes) on genetically modified sensitive industries.
In particular, I ask, do the non-traditional endowments confer comparative advantage to a country in exporting to the rest of the world (ROW)? I pursue this hypothesis by looking at whether a country's true non-traditional endowments (R&D and biotech land) correspond with net export of embodied non-traditional endowments. I employ the factor-content model of the Heckscher-Ohlin-Vanek (HOV) as the underlying theoretical framework. The empirical implementation and method include examination of this relationship via non-parametric and parametric methods using 2006 cross-section data of three-digit level of the Standard International Trade Classification (SITC).
Further, I examine the causal relationship between non-traditional endowments and countries' bilateral trade of genetically modified-based industries. In addition, I analyze the effect of institutional measures of policy on bilateral trade in GMO-based industries and account for ways in which these institutional factors interact with non-traditional endowments (R&D and biotech land). I employ the Gravity model of international trade to examine these relationships.
Findings show countries with higher non-traditional endowments than the world average have embodied net exports of these endowments. In other words, this finding is an indication that such countries have revealed comparative advantage in goods that make intensive use of these factors. In particular, results show that the causal relationship between trade in genetically modified-sensitive products and biotech land of a country is informative. In aggregate and subaggregates trade, the biotech land factor consistently shows positive and statistically significant parameter estimates indicating that indeed it confers comparative advantage. Accordingly, the relationship between trade in GMO-based industries and GMO land is genuinely causal rather than just correlation. This implies that the variation of trade in GMO-based industries is not attributable to either unmeasured characteristics or the traditional endowments. However, the relationship between trade in genetically modified-sensitive industries and R&D stock is less definitive. R&D stock confers comparative advantage in one (fats or vegetable related) of the four main subaggregates while it neither confers comparative advantage nor comparative disadvantage in others. There is evidence that R&D stock (knowledge capital) does not fit the traditional immobility assumption. Knowledge capital spillovers may take place. Thus, the importance of knowledge capital is not showing up in the statistical results.
I found mixed evidence on the effect of institutional endowments (relevant regulatory regimes and intellectual property rights) on bilateral trade in GMO-based industries. Using different levels of data aggregations (for comparability and concordance) and estimation methods (for robustness checks), the results showed that strengthening of patent protection in the destination country relative to the source country reduces exports of genetically modified-sensitive products. This demonstrates a market power effect where strengthening intellectual property protection grants monopoly power to economic agents of importing country relative to exporting country. Finally, results show that even when there are marked regulatory differences and policies, there is little evidence of diversion of trade in GMO-sensitive industries.
The dissertation is organized as follows. Chapter 1 provides an introduction and overview of GMO-intensive industries. This chapter also summarizes patterns of international data on trade in GMO-intensive industries, R&D, GMO land use, and policies including regulatory regimes and intellectual property rights. Chapter 2 then analyzes determinants of trade in GMO-intensive industries using the Heckscher-Ohlin model. This analysis focuses on determinants of a country's trade with the rest of the world. Chapter 3 analyzes determinants of trade in GMO-intensive industries using the Gravity model. This analysis focuses on the determinants of a country's bilateral trade with each trading partner. Chapter 2 and 3 both focus on the role of the non-traditional endowments as determinants of trade. These non-traditional endowments include: (1) the knowledge stock of countries, (2) the land endowments of countries including the GMO component of land, (3) regulatory regimes of countries related to GMO policies, and (4) the intellectual property right policies of countries. I refer to the knowledge stock variable as an R&D stock through much of the dissertation. I also refer to the two policy variables as `institutional endowments' throughout the dissertation. Chapter 4 then provides a conclusion, discussion of policy implications of the research, elucidates the limitations, and proposes areas of further research.
University of Minnesota Ph.D. dissertation. January 2011. Major: Applied Economics. Advisor: Dr. Pamela J. Smith. 1 computer file (PDF); xiv, 216 pages. Ill. (some col.)
Da'ar, Omar Bundid.
International trade in genetically modified-sensitive industries: a cross-country analysis..
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