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Wetlands are highly productive ecosystems, providing a number of functions (products and services) that are of value to people. The open-access nature and the public-good characteristics of wetlands often result in wetlands being undervalued in decisions relating to their use and conservation. There is now a substantial literature on wetland valuation, including two meta-analyses. These meta-analyses examine subsets of the available wetland valuation literature, focusing on temperate wetlands, a limited set of wetland functions, and a limited set of valuation techniques. We collect over 190 wetland valuation studies, providing 215 value observations, in order to present a more comprehensive meta-analysis of the valuation literature that includes tropical wetlands (e.g., mangroves), estimates from diverse valuation methodologies, and a broader range of wetland functions (e.g., biodiversity value).We also aim for a more comprehensive geographical coverage. We find that socioeconomic variables, such as income and population density, that are often omitted from such analyses are important in explaining wetland value. We also assess the prospects for using this analysis for out of sample value transfer, and find average transfer errors of 74%, with just under one-fifth of the transfers showing errors of 10% or less. This overall performance is, however, dominated to a considerable extent by transfer to small sites. The performance of value transfer for medium to large wetlands on average shows transfer errors smaller than 30%.

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Accident costs are an important component of external costs of traffic, a substantial part is related to fatal accidents. The evaluation of fatal accident costs crucially depends on the availability of an estimate for the economic value of a statistical life. The aim of the current paper is to present an overview of estimates contained in the empirical literature on the economic valuation of statistical life in road safety. Meta-analysis is used to determine which variables are appropriate to explain the variance of the value of statistical life (VOSL) estimates. The analysis shows, among other things, that the magnitude of estimates of the VOSL depends on the research method, as there is a significant difference between stated and revealed preference studies. It also shows that VOSL estimates cannot simply be averaged over studies, as the magnitude of a VOSL estimate is directly related to the initial level of risk to be caught up in a fatal traffic accident as well as the risk decline implied by the research setup .

The topic of convergence is at the heart of a wide-ranging debate in the growth literature, and empirical studies of convergence differ widely in their theoretical backgrounds, empirical specifications, and in their treatment of cross-sectional heterogeneity. Despite these differences, a rate of convergence of about 2% has been found under a variety of different conditions, resulting in the widespread belief that the rate of convergence is a natural constant. We use meta-analysis to investigate whether there is substance to the 'myth' of the 2% convergence rate and to assess several unresolved issues of interpretation and estimation. Our data set contains approximately 600 estimates taken from a random sample of empirical growth studies published in peer-reviewed journals.The results indicate that it is misleading to speak of a natural convergence rate since estimates of different growth regressions come from different populations, and we find that correcting for the bias resulting from unobserved heterogeneity in technology levels leads to higher estimates of the rate of convergence. We also find that correcting for endogeneity of the explanatory variables has a substantial effect on the estimates and that measures of financial and fiscal development are important determinants of long-run differences in per capita income levels. We show that although the odds of a study being published is not uniform for studies with different p-values, publication bias has no significant effect on the conclusions of the analysis.