Estimating new product demand from biased survey data

Roger Klein, Robert Sherman

Research output: Contribution to journalArticlepeer-review

16 Scopus citations

Abstract

Market researchers often conduct surveys asking respondents to estimate their future demand for new products. However, projected demand may exhibit systematic bias. For example, the more respondents like a product, the more they may exaggerate their demand. We found evidence of such exaggeration in a recent survey of demand for a potential new video product. In this paper, we develop a computationally tractable procedure that corrects for a general form of systematic bias in demand projections. This general form is characterized by a monotonie transformation of projected demand, and covers exaggeration bias as a special case.

Original languageEnglish (US)
Pages (from-to)53-76
Number of pages24
JournalJournal of Econometrics
Volume76
Issue number1-2
DOIs
StatePublished - 1997

All Science Journal Classification (ASJC) codes

  • Economics and Econometrics

Keywords

  • Censored models
  • Misreporting
  • New product demand
  • Survey data
  • Transformation models

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