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"A Comparative Analysis of Alternative Univariate Time Series Models in Forecasting Turkish Inflation" was published by DICE in 2011 - Düsseldorf, it has 25 pages and the language of the book is English.


“A Comparative Analysis of Alternative Univariate Time Series Models in Forecasting Turkish Inflation” Metadata:

  • Title: ➤  A Comparative Analysis of Alternative Univariate Time Series Models in Forecasting Turkish Inflation
  • Author:
  • Language: English
  • Number of Pages: 25
  • Is Family Friendly: Yes - No Mature Content
  • Publisher: DICE
  • Publish Date:
  • Publish Location: Düsseldorf

“A Comparative Analysis of Alternative Univariate Time Series Models in Forecasting Turkish Inflation” Subjects and Themes:

Edition Specifications:

  • Pagination: 25 S.

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"A Comparative Analysis of Alternative Univariate Time Series Models in Forecasting Turkish Inflation" Description:

Open Data:

This 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. -- Inflation forecasting ; Neural networks ; Unobserved components model

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