A comparative analysis of alternative univariate time series models in forecasting Turkish inflation
AbstractThis paper analyses inflation forecasting power of artificial neural networks with alternative univariate time series models for Turkey. The forecasting accuracy of the models is compared in terms of both static and dynamic forecasts for the period between 1982:1 and 2009:12. We find that at earlier forecast horizons conventional models, especially ARFIMA and ARIMA, provide better one-step ahead forecasting performance. However, unobserved components model turns out to be the best performer in terms of dynamic forecasts. The superiority of the unobserved components model suggests that inflation in Turkey has time varying pattern and conventional models are not able to track underlying trend of inflation in the long run. --
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Bibliographic InfoPaper provided by Heinrich‐Heine‐Universität Düsseldorf, Düsseldorf Institute for Competition Economics (DICE) in its series DICE Discussion Papers with number 20.
Date of creation: 2011
Date of revision:
Inflation forecasting; Neural networks; Unobserved components model;
Find related papers by JEL classification:
- C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
- E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
This paper has been announced in the following NEP Reports:
- NEP-ALL-2011-06-18 (All new papers)
- NEP-ARA-2011-06-18 (MENA - Middle East & North Africa)
- NEP-CBA-2011-06-18 (Central Banking)
- NEP-CMP-2011-06-18 (Computational Economics)
- NEP-CWA-2011-06-18 (Central & Western Asia)
- NEP-ETS-2011-06-18 (Econometric Time Series)
- NEP-FOR-2011-06-18 (Forecasting)
- NEP-MON-2011-06-18 (Monetary Economics)
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