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Languages: English
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This thesis is concerned with understanding the factors responsible for the vast differences in per capita income levels and growth rates evident across countries. As part of this inquiry, it examines the role played by international trade both singly and in combination with geography, institutions and foreign R&D. One line of inquiry revisits the contentious issue of the relationship between trade openness and growth. It examines this issue from two standpoints. First, the sensitivity of the openness-growth nexus to alternative measures of TFP growth is considered. This approach departs from previous research on this subject which has focused mainly on the right hand side variables, namely the measures of openness and other growth determinants. Drawing on the current competing arguments over the performance of homogeneous versus heterogeneous estimators, three alternative sets of TFP growth estimates were generated; one for the each of the extremes of heterogeneity and homogeneity and an intermediate measure. Despite being highly correlated amongst themselves and with alternative TFP estimates generated by other researchers, we find some of the measures used to proxy trade openness are sensitive to the measurement of TFP growth. Moreover, this sensitivity extends to other dimensions such as whether one performs cross-section or panel estimations and whether one assumes the openness indicators to be exogenous or endogenous. Our preference however, is for panel estimations with the alternative proxies for trade openness entered simultaneously instead of sequentially. Second, the nature of the openness-growth relationship is examined by searching for contingent relationships between these two variables, linked to geography and institutional quality. Of the alternative methods employed for capturing contingent effects, we argue that the endogenous threshold model of Hansen (2000), best captures these effects. Using this methodology, we find evidence in support of contingent relationships between trade openness and natural barriers (institutional quality). More specifically, we find that there exists threshold level(s) of natural barriers and institutional quality above and below which the contribution to TFP growth from openness differs. However, support for the latter finding is weaker than that for the former. A separate line of inquiry simultaneously examines the role of trade in the diffusion of foreign technology (embodied in capital goods) and its effect on technical efficiency levels. Using the methodology of stochastic frontier analysis which allows for such a dual consideration, we find evidence that trade and trade policy openness have contributed positively to both technology diffusion and raising efficiency levels in developing countries. Additionally, coinciding with improvements in the policy environment and trade liberalisation there is evidence of convergence in efficiency levels amongst developing countries.
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    • 1985. This finding formed the basis for Mankiw's claim that "Put simply, most 47. Korea 48. Kuwait 49. Libya 50. Sri Lanka 51. Luxembourg 52. Morocco 53. Madagascar 54. Mexico 55. Mali 56. Malta 57. Myanmar 58. Mozambique 59. Mauritius 60. Malawi 61. Malaysia 62. Nigeria 63. Nicaragua 64. Netherlands 65. Norway 66. New Zealand 67. Pakistan 68. Panama 69. Peru 70. Philippines 71. Portugal 72. Paraguay 73. Rwanda 74. Sudan 75. Senegal 76. Sin~apore 77. Sierra Leone 78. El Salvador 79. Sweden 80. Thailand 81.Trinidad & Tobal!;o 82. Tunisia 83. Turkey 84. Taiwan 85. Tanzania 86. Uganda 87. Uruguay 88. USA 89. Venezuela 90. South Africa 91. Zaire 92. Zambia 93. Zimbabwe TO CHAPTER 4 TO CHAPTER 0.830 0.154
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