Structural Cointegrating Vector Autoregression Analysis of International Trade, with Application to Commodity Exports
2015-12
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Structural Cointegrating Vector Autoregression Analysis of International Trade, with Application to Commodity Exports
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2015-12
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This research examines the structural relationship between volume of exports, economic growth, and real exchange rate volatility, and the impact of temporal and permanent shocks on the evolution of export volume, foreign income, and real exchange rate. The conceptual framework is applied to U.S. agricultural exports to examine the sector’s international competitiveness and opportunities for export extensification. Results show that on average, growth in foreign income leads to a greater increase in exports to developing countries than in exports to developed countries. Furthermore, depreciation of the U.S. dollar leads to a more than proportionate increase in exports of most commodities. In addition, developing countries are more sensitive to disequilibrating shocks, and more than half of the deviation from the equilibrium level of exports is adjusted within one year. HASH(0x7f7fa2e58050) Results suggest that the present concentration of U.S. agricultural commodity exports to a few developed countries is increasingly problematic, and that U.S. agricultural exports may benefit not only from policies intended to increase trade with existing developing country importers (expanding exports along the intensive margin) but also from policies that aim to export agricultural commodities to hitherto unexplored emerging markets (expanding exports along the extensive margin). The paper provides quantitative estimates to project the evolving composition of food demand and the location of future markets; these estimates can help to design policies to avail of the market opportunities for growth latent in emerging economies, and mitigate effects of country specific shocks on aggregate exports. HASH(0x7f7fa2e58230) Finally, results suggest that the cointegrating vector autoregressive framework is shown to incorporates insights from economic theory and both short- and long-run parameter estimates. This accounts for the complex interrelationships among the core macroeconomic variables and provides a rich analysis of the short-run dynamics of the model in response to unexpected changes in economic variables.
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University of Minnesota Ph.D. dissertation. December 2015. Major: Applied Economics. Advisor: Terry Roe. 1 computer file (PDF); x, 229 pages.
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Jha, Jaya. (2015). Structural Cointegrating Vector Autoregression Analysis of International Trade, with Application to Commodity Exports. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/178953.
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