This paper presents a meta-analysis of hypothetical bias in stated preference valuation studies, focusing on 28 studies that report monetary willingness-to-pay and use the same mechanism for eliciting both hypothetical and actual values. The analysis generates 83 observations with a median ratio of hypothetical to actual value of 1.35, indicating significant hypothetical bias. The study explores various explanatory variables based on previous research, finding that choice-based elicitation mechanisms are effective in reducing bias. However, the limited number of studies and confounding variables prevent a detailed characterization of individual mechanisms. The paper also suggests that using student subjects may contribute to bias, though this is highly correlated with group experimental settings. There is weak evidence that bias increases when valuing public goods and that calibration methods can reduce bias. The results are sensitive to model specification, highlighting the need for a comprehensive theory of hypothetical bias. The study concludes that hypothetical bias may not be as significant a problem in stated preference analyses as commonly believed, especially for smaller hypothetical values.This paper presents a meta-analysis of hypothetical bias in stated preference valuation studies, focusing on 28 studies that report monetary willingness-to-pay and use the same mechanism for eliciting both hypothetical and actual values. The analysis generates 83 observations with a median ratio of hypothetical to actual value of 1.35, indicating significant hypothetical bias. The study explores various explanatory variables based on previous research, finding that choice-based elicitation mechanisms are effective in reducing bias. However, the limited number of studies and confounding variables prevent a detailed characterization of individual mechanisms. The paper also suggests that using student subjects may contribute to bias, though this is highly correlated with group experimental settings. There is weak evidence that bias increases when valuing public goods and that calibration methods can reduce bias. The results are sensitive to model specification, highlighting the need for a comprehensive theory of hypothetical bias. The study concludes that hypothetical bias may not be as significant a problem in stated preference analyses as commonly believed, especially for smaller hypothetical values.