Details

Autor(en) / Beteiligte

• Atozou, Baoubadi
• Tamini, Lota D.
• Bergeron, Stéphane
• Doyon, Maurice

Titel

Factors Explaining Hypothetical Bias: How to Improve Models for Meta-Analyses

Ist Teil von

• Journal of agricultural and resource economics, 2020-05, Vol.45 (2), p.376-395

Auflage

1835

Ort / Verlag

Logan: Western Agricultural Economics Association

Erscheinungsjahr

2020

Link zum Volltext

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• Using a set of 462 observations from 87 public and private goods economic valuation studies, this study reviews and updates meta-analyses on hypothetical bias using a metaregression hierarchical mixed-effect (MRHME) model that corrects the effects of the unobservable characteristics, within-study error correlation, and potential heteroskedasticity specific to each study. The findings indicate that the MRHME model is more efficient than the log-linear models used in previous meta-analyses. Moreover, this modeling approach and the use of interaction variables by type of goods highlight significant differences relative to previous meta-analyses in the explanatory variables' effects, significance levels, magnitudes, and signs.