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Forecasting market shares using VAR and BVAR models: A comparison of their forecasting performance

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  • Francisco F. R. Ramos

    (Faculty of Economics, University of Porto, Portugal)

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    Abstract

    This paper develops a Bayesian vector autoregressive model(BVAR) for the leader of the Portuguese car market to forecast the market share. The model includes five marketing decision variables.The Bayesian prior is selected on the basis of the accuracy of the out-of-sample forecasts. We find that our BVAR models generally produce more accurate forecasts of market share. The out-of-sample accuracy of the BVAR forecasts is also compared with that of forecasts from an unrestricted VAR model and of benchmark forecasts produced from univariate (e.g., Box-Jenkins ARIMA) models. Additionally, competitive dynamics of the market place are revealed through variance decompositions and impulse response analysis.

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    Bibliographic Info

    Paper provided by EconWPA in its series Econometrics with number 9601003.

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    Length: 41 pages
    Date of creation: 23 Jan 1996
    Date of revision:
    Handle: RePEc:wpa:wuwpem:9601003

    Note: Type of Document - Winword 2.0; prepared on IBM PC ; to print on HP/Epson; pages: 41 ; figures: included. Word for Windows document submitted by ftp
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    Web page: http://128.118.178.162

    Related research

    Keywords: Automobile market; BVAR models; Forecast accuracy; Impulse response analysis; Marketing decision variables; Specification of marketing priors; variance decomposition; VAR models;

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