Russia's Comparative Advantages in Foreign Trade
Forecasting Potential Dynamics and Identifying Stimulation Measures
(Sprache: Englisch)
Identifying factors which stimulate regional growth and international competitiveness and using them for forecasting are the aims of this book. The author proposes the use of heuristic optimization techniques, Monte Carlo simulation experiments and...
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Identifying factors which stimulate regional growth and international competitiveness and using them for forecasting are the aims of this book. The author proposes the use of heuristic optimization techniques, Monte Carlo simulation experiments and Lasso-type estimators to avoid bias or misleading findings.
Klappentext zu „Russia's Comparative Advantages in Foreign Trade “
Identifying factors which stimulate regional growth and international competitiveness and using them for forecasting are the aims of this book. Departing from the theory of comparative advantages and their impact, the author demonstrates that such an approach has to be based on a sound theoretical foundation and on appropriate, advanced econometric methods. He proposes the use of heuristic optimization techniques, Monte Carlo simulation experiments and Lasso-type estimators to avoid bias or misleading findings, which might be the result of applying standard regression methods when key assumptions are not satisfied. In addition, the author demonstrates how some heuristic optimization-based methods can be used to obtain forecasts of industrial production in Russia and Germany founded on past observations and some leading indicators.
Inhaltsverzeichnis zu „Russia's Comparative Advantages in Foreign Trade “
Contents: Forecasting Russian Foreign Trade - Comparative Advantages in the Context of a Potential WTO Accession - Heuristic Optimization Methods for Dynamic Panel Data Model Selection: Application on the Russian Innovative Performance - Heuristic Model Selection for Leading Indicators in Russia and Germany - A comparative study of the Lasso-type and heuristic methods - Business Cycle Forecasts - Comparative Advantage - Dynamic Panel Data - Economy in Transition - Genetic Algorithms - Heuristic Methods - Innovation - Lasso - Leading Indicators - Model Selection - Threshold Accepting.
Autoren-Porträt von Ivan Savin
Ivan Savin studied International Economics at the Ural State University in Yekaterinburg (Russia) and at the University of Passau. In 2011 he obtained a PhD from the Department of Statistics and Econometrics at the University of Giessen. He is a postdoctoral researcher at the DFG Research Training Group 1411 «The Economics of Innovative Change» at the University of Jena. His research interests include computational econometrics, optimal control and technological change.
Bibliographische Angaben
- Autor: Ivan Savin
- 2012, Neuausgabe, 135 Seiten, Maße: 14,9 x 21,6 cm, Gebunden, Englisch
- Verlag: Peter Lang Ltd. International Academic Publishers
- ISBN-10: 3631639937
- ISBN-13: 9783631639931
- Erscheinungsdatum: 29.11.2012
Sprache:
Englisch
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