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170408s2017 dcu o 000 0 eng d |
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|z 9781475585490
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|a UAMI
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|a Ding, Xiaodan,
|e author.
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|a Composition of Trade in Latin America and the Caribbean /
|c Xiaodan Ding and Metodij Hadzi-Vaskov.
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|a Washington, D.C. :
|b International Monetary Fund,
|c 2017.
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|a 1 online resource (45 pages)
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|a text
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|a online resource
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|a IMF Working Paper,
|x 1018-5941 ;
|v WP/17/42
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|a Print version record.
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|a Cover; CONTENTS; Abstract; I. Introduction; II. Dimensions of Trade Composition; III. Dataset and Data Description; IV. Trends in Trade Composition; A. Revealed Comparative Advantage; B. Diversification; C. Sophistication; D. Economic Complexity; V. Product Proximity and Predicting Future Composition of Trade; A. Product Proximity; B. Predicting Composition of Trade; C. Prediction Performance; VI. Regression Analysis; A. Methodology; B. Results; VII. Impact of Trade Agreements; VIII. Concluding Remarks; IX. References; Tables; 1: Determinants of the Composition of Trade.
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|a 2: Determinants of the Composition of Trade: IV Regressions3: Regression Results: Impact of Trade Agreements on Export Composition; Figures; 1: Revealed Comparative Advantage for Latin America and the Caribbean; 2: Revealed Comparative Advantage for LA6; 3: Revealed Comparative Advantage for CAPDR; 4: Revealed Comparative Advantage for the Caribbean; 5: Revealed Comparative Advantage for Different Regions; 6: Revealed Comparative Advantage in Different Product Categories; 7. Export Concentration Index (Overall); 8: Export Concentration Index (Median).
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|a 9: Export Concentration Index (by Country)10: Export Concentration Index for the Caribbean; 11: Export Sophistication Index; 12: Standardized Export Sophistication Index; 13: Product Complexity of Exports; 14: Actual and Predicted Areas of Comparative Advantage; 15: Performance of Predictions for Comparative Advantage; 16: Actual and Predicted Areas of Comparative Advantage (Dynamic); 17: Performance of Predictions for Comparative Advantage (Dynamic); 18: Event Studies: Impact of Trade Agreements on Export Composition; Boxes.
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|a 1: Skill and Technology-Intensity Product Classification from UNCTAD2. Standard International Trade Classification (SITC); Appendices; I. Country Groupings; II. Distribution of Product Complexity Allowing Movements Across Quintiles; III. Robustness of Predictions for RCAs Across Product Groups to Alternative Time Horizons; IV. Additional Regression Results; V. Panel Vector Autoregressive Model.
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|a This study analyzes composition of goods trade in Latin America and the Caribbean (LAC) along four main dimensions: revealed comparative advantage, product complexity, sophistication, and diversification. After describing some key trade patterns over the last half century, it compares the findings for LAC with other regions. Second, the study investigates how infrastructure quality, education, and tariff levels affect export composition. Third, using an approach based on product proximity, it aims to predict changes in LAC's future composition of exports. The study concludes that policies to upgrade human capital and infrastructure are essential for increasing LAC's export share in high-skill products.
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|a eBooks on EBSCOhost
|b EBSCO eBook Subscription Academic Collection - Worldwide
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|a Commerce
|x Mathematical models.
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|a Hadzi-Vaskov, Metodij,
|e author.
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776 |
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|i Print version:
|a Ding, Xiaodan.
|t Composition of Trade in Latin America and the Caribbean.
|d Washington, D.C. : International Monetary Fund, ©2017
|z 9781475585490
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830 |
|
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|a IMF working paper ;
|v WP/17/42.
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856 |
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