Accurately measuring willingness to pay for consumer goods: a meta-analysis of the hypothetical bias

Jonas Schmidt*, Tammo H. A. Bijmolt

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

22 Citations (Scopus)
79 Downloads (Pure)


Consumers' willingness to pay (WTP) is highly relevant to managers and academics, and the various direct and indirect methods used to measure it vary in their accuracy, defined as how closely the hypothetically measured WTP (HWTP) matches consumers' real WTP (RWTP). The difference between HWTP and RWTP is the "hypothetical bias." A prevalent assumption in marketing science is that indirect methods measure WTP more accurately than do direct methods. With a meta-analysis of 77 studies reported in 47 papers and resulting in 115 effect sizes, we test that assumption by assessing the hypothetical bias. The total sample consists of 24,347 included observations for HWTP and 20,656 for RWTP. Moving beyond extant meta-analyses in marketing, we introduce an effect size metric (i.e., response ratio) and a novel analysis method (i.e., multivariate mixed linear model) to analyze the stochastically dependent effect sizes. Our findings are relevant for academic researchers and managers. First, on average, the hypothetical bias is 21%, and this study provides a reference point for the expected magnitude of the hypothetical bias. Second, the deviation primarily depends on the use of a direct or indirect method for measuring HWTP. In contrast with conventional wisdom, indirect methods actually overestimate RWTP significantly stronger than direct methods. Third, the hypothetical bias is greater for higher valued products, specialty goods (cf. other product types), and within-subject designs (cf. between-subject designs), thus a stronger downward adjustment of HWTP values is necessary to reflect consumers' RWTP.

Original languageEnglish
Pages (from-to)499-518
Number of pages20
JournalJournal of the Academy of Marketing Science
Issue number3
Publication statusPublished - May-2020


  • Willingness to pay
  • Reservation price
  • Pricing
  • Conjoint analysis
  • Measurement accuracy
  • Hypothetical bias
  • Meta-analysis
  • Response ratio
  • Stochastically dependent effect sizes

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