Forecasting the Penetration of a New Product--A Bayesian Approach

Scott E Pammer, Duncan K H Fong and Steven F Arnold

Journal of Business & Economic Statistics, 2000, vol. 18, issue 4, 428-35

Abstract: We adopt a Bayesian approach to forecast the penetration of a new product into a market. We incorporate prior information from an existing product and/or management judgments into the data analysis. The penetration curve is assumed to be a nondecreasing function of time and may be under shape constraints. Markov-chain Monte Carlo methods are proposed and used to compute the Bayesian forecasts. An example on forecasting the penetration of color television using the information from black-and-white television is provided. The models considered can also be used to address the general bioassay and reliability stress-testing problems.

Date: 2000
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Persistent link: https://EconPapers.repec.org/RePEc:bes:jnlbes:v:18:y:2000:i:4:p:428-35

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