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

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  • Atozou, Baoubadi
  • Tamini, Lota D.
  • Bergeronm, Stephane
  • Doyon, Maurice

Abstract

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.

Suggested Citation

  • Atozou, Baoubadi & Tamini, Lota D. & Bergeronm, Stephane & Doyon, Maurice, 2020. "Factors Explaining the Hypothetical Bias: How to Improve Models for Meta-Analyses," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 45(2), March.
  • Handle: RePEc:ags:jlaare:302460
    DOI: 10.22004/ag.econ.302460
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    Keywords

    Research Methods/ Statistical Methods;

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • H40 - Public Economics - - Publicly Provided Goods - - - General
    • Q00 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - General
    • Q20 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - General

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