The Forecasting Accuracy of Five Time Series Models: Evidence from the Portuguese Car Market
AbstractThis paper compares the out-of-sample forecasting accuracy of five classes of time series models for market shares of the six most important Portuguese car market competitors over differents horizons. As representative time series models I employ a random-walk with drift (Naive), a univariate ARIMA, a near-VAR and a general BVAR. The out-of- sample forecasts are also compared against forecasts generated from structural econometric market share models (SEM). Using four accuracy measures I find the forecasts from the near-VAR and the BVAR models really more accurate. With regard to these models, I could say that the BVAR model is the best for longer forecasts (12-steps ahead), while the n-VAR is superior over the shorter horizon of one to six steps.
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Bibliographic InfoPaper provided by EconWPA in its series Econometrics with number 9604002.
Length: 21 pages
Date of creation: 09 Apr 1996
Date of revision:
Note: Type of Document - Word for Windows 2.0; prepared on IBM PC ; to print on HP Laser Jet; pages: 21 ; figures: one figure and one table
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Accuracy measures; ARIMA; Automobile market; BVAR; Market share; Portugal; Random-walk; SEM; VAR;
Find related papers by JEL classification:
- C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
- C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
- C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
- C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
- C5 - Mathematical and Quantitative Methods - - Econometric Modeling
- C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs
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