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.

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.

Leseprobe

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.