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Published by: Allied Business Academies
Published in: "Academy of Marketing Studies Journal", 1997
Length: 13 pages

Abstract

This 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 different horizons. As representative time series models I employ a random walk with drift (Naive), a univariate ARIMA, a near-VAR (n-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 n-VAR and the BVAR models more accurate. With regard to these models, the BVAR model is the best for longer forecasts (12-steps ahead), while the n-VAR is superior over a shorter horizon of one to six steps.

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Abstract

This 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 different horizons. As representative time series models I employ a random walk with drift (Naive), a univariate ARIMA, a near-VAR (n-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 n-VAR and the BVAR models more accurate. With regard to these models, the BVAR model is the best for longer forecasts (12-steps ahead), while the n-VAR is superior over a shorter horizon of one to six steps.

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