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Comparative Environmental Economic Assessment

Edited by Raymond J.G.M. Florax, Peter Nijkamp and Kenneth G. Willis

Over the last decade, economists have increasingly recognized the role of meta-analysis and value transfer in synthesizing knowledge and efficiently exploiting the existing pool of knowledge. Comparative Environmental Economic Assessment explores the potential significance of using these techniques, particularly in environmental economics. Both meta-analysis and value transfer constitute major research tools which efficiently use knowledge previously acquired from other studies. The book focuses on the potential role and usefulness of these tools in environmental economic research, and goes on to address their validity, relevance and applicability
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Chapter 10: Methodological pitfalls in meta-analysis: publication bias

Raymond J.G.M. Florax


179 pling of studies for the meta-analysis may still have a negative impact on the validity of the meta-analysis. Selectivity can refer to various aspects of the sampling process: the meta-sample may be biased in terms of, for instance, theoretical perspectives, spatial and / or temporal coverage, data type, publication outlet and statistical techniques. The negative connotation that we usually attach to ‘sample selection bias’ is indicative of the harmful effect on the validity of the meta-analysis. The latter occurs when there is a systematic relationship between characteristics of the sampling process and the significance or magnitude of the effect size. The issue of publication bias did not generate a sizeable discussion in the economic literature. Among the few exceptions are Card and Krueger (1995) and Ashenfelter et al. (1999), who systematically investigate the occurrence and impact of publication bias with respect to studies on minimum wages and studies on the relation between schooling and earnings, respectively. In the area of environmental economics, specifically in the field of environmental valuation that constitutes the prime area in which meta-analysis has been applied, publication bias received some attention as well.1 Smith and Huang (1995), for instance, stress the disturbing effect that sample selection bias may have on the outcome of the metaanalysis. They use a two-stage Heckman-like probit model to determine the likelihood of sample selection bias, and subsequently include the inverse Mill’s ratio in the meta-regression. The ratio is related to the estimated probability of including...

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