Forecasting Macroeconomic Indicators for Selected European Union Countries
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- Tkacz, Greg, 2001. "Neural network forecasting of Canadian GDP growth," International Journal of Forecasting, Elsevier, vol. 17(1), pages 57-69.
- Urasawa, Satoshi, 2014. "Real-time GDP forecasting for Japan: A dynamic factor model approach," Journal of the Japanese and International Economies, Elsevier, vol. 34(C), pages 116-134.
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More about this item
Keywords
Economic indicators; GDP; final consumption expenditures; export of goods and services; European Union.;All these keywords.
JEL classification:
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
- E2 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment
- O11 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Macroeconomic Analyses of Economic Development
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