Efficiently reducing natural hazard risks requires a thorough understanding of the costs of natural hazards. Current methods to assess these costs employ a variety of terminologies and approaches for different types of natural hazards and different impacted sectors. This may impede efforts to ascertain comprehensive and comparable cost figures. In order to strengthen the role of cost assessments in the development of integrated natural hazard management, a review of existing cost assessment approaches was undertaken. This review considers droughts, floods, coastal and Alpine hazards, and examines different cost types, namely direct tangible damages, losses due to business interruption, indirect damages, intangible effects, and the costs of risk mitigation. This paper provides an overview of the state-of-the-art cost assessment approaches and discusses key knowledge gaps. It shows that the application of cost assessments in practice is often incomplete and biased, as direct costs receive a relatively large amount of attention, while intangible and indirect effects are rarely considered. Furthermore, all parts of cost assessment entail considerable uncertainties due to insufficient or highly aggregated data sources, along with a lack of knowledge about the processes leading to damage and thus the appropriate models required. Recommendations are provided on how to reduce or handle these uncertainties by improving data sources and cost assessment methods. Further recommendations address how risk dynamics due to climate and socio-economic change can be better considered, how costs are distributed and risks transferred, and in what ways cost assessment can function as part of decision support

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There has been increasing interest in the so-called 'resource curse', i.e. the tendency of resourcerich countries to underperform in several development outcomes. This has generated a mountain of (often contradictory) evidence leaving many floundering in the flood of information. The special issue compiles eight papers from some of the most prominent contributors to this literature, combining original research with critical reflection on the current stock of knowledge. The studies collectively emphasize the complexities and conditionalities of the 'curse' -its presence/intensity is largely context-specific, depending on the type of resources, socio-political institutions and linkages with the rest of the economy.

The resource curse literature has necessarily evolved in a rather fragmented way.While economists, political economists and political scientists have largely focused on the role of mineral abundance in long-term growth with the analysis largely confined to the country (macro) or regional (meso) level, anthropologists, sociologists and other social scientists have explored the development impacts of extractive industries at the community (micro) level. While this has provided a rigorous and comprehensive exploration of extractive industries and their impacts, causal factors that bridge and/or leap-frog these levels tend not to be accounted for.In this paper we examine the evolution of literature across disciplinary lines and different levels of scale to assess the current status of resource curse debates. In so doing, we aim to explore how an integration of the various multi-scale approaches can help address the persistent problem of the resource curse.

Surprisingly, there has been little research conducted about the cross-country relationship between oil dependence/abundance and income inequality. At the same time, there is some tentative evidence suggesting that oil rich nations tend to under-report data on income inequality, which can potentially influence the estimated empirical relationships between oil richness and income inequality. In this paper we contribute to the literature in a twofold manner. First, we explore in depth the empirical relationship between oil and income inequality by making use of the Standardized World Income Inequality Database -the most comprehensive dataset on income inequality providing comparable data for the broadest set of country-year observations. Second, this is the first study to our knowledge that adopts an empirical framework to examine whether oil rich nations tend to under-report data on income inequality and the possible implications thereof. We make use of Heckman selection models to validate the tendency of oil rich countries to under-report and correct for the bias that might arise as a result of this -we find that oil is associated with lower income inequality with the exception of the very oil-rich economies.

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