Forecasting Russian Foreign Trade Comparative Advantages in the Context of a Potential WTO Accession
Abstract
For the private and public sector in any particular country it is crucial to know, which industries may exhibit comparative advantages, that for some reasons are not realized. This can efficiently help all current and potential actors to improve their economic strategy both at the micro- and macroeconomic level. In this paper we propose an approach of forecasting comparative advantages dynamics in foreign trade. The instrument is based on relative price differences and is efficient for countries in the process of economic liberalization. An empirical analysis based on the example of Central and East European countries confirms a good performance in the sense of predictive power of this instrument. On the example of Russia, experiencing a period of economic liberalization and with the prospect to join the WTO agreements, we demonstrate which sectors are most likely to contain comparative advantages in the near future.Download Info
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Article provided by CEJEME in its journal Central European Journal of Economic Modelling and Econometrics.
Volume (Year): 1 (2009)
Issue (Month): 2 (November)
Pages: 111-138
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Web page: http://cejeme.org/
Related research
Keywords: comparative advantage; economy in transition; Balassa index; Lafay index;Other versions of this item:
- Ivan Savin & Peter Winker, 2009. "Forecasting Russian Foreign Trade Comparative Advantages in the Context of a Potential WTO Accession," MAGKS Papers on Economics 200914, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
- F15 - International Economics - - Trade - - - Economic Integration
- F17 - International Economics - - Trade - - - Trade Forecasting and Simulation
- F43 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Economic Growth of Open Economies
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Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.Cited by:
- Ivan Savin & Peter Winker, 2010.
"Heuristic Optimization Methods for Dynamic Panel Data Model Selection. Application on the Russian Innovative Performance,"
Working Papers
027, COMISEF.
- Ivan Savin & Peter Winker, 2012. "Heuristic Optimization Methods for Dynamic Panel Data Model Selection: Application on the Russian Innovative Performance," Computational Economics, Society for Computational Economics, vol. 39(4), pages 337-363, April.
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