Suchergebnisse

This paper aims to present an extension of the ICES model to capture the public sector. Departing from a demand system mainly derived from the GTAP model, ICES-XPS model disentangles the private and the public actors. The paper reviews the changes in both the database and the model equations following the existing literature and considering the availability of data as well. The model is then tested with a series of simple experiments to highlight its contribution to economic analysis in which the public sector may play an important role. Finally, we show the flexibility in the closure rule of the public sector that allows addressing different policy research questions.

This paper estimates the direct and indirect socio-economic impacts of the 2000 flood that took place in the Po river basin (Italy) using a combination of Computable General Equilibrium (CGE) model and Spatial and Multi-Criteria Analysis. A risk map for the whole basin is generated as a function of hazard, exposure and vulnerability. The indirect economic losses are assessed using the CGE model, whereas the direct social and economic impacts are estimated with spatial analysis tools combined with Multi-Criteria Analysis. The social impact is expressed as a function of physical characteristics of the extreme event, social vulnerability and adaptive capacity. The results indicate that the highest risk areas are located in the mountainous and in the most populated portions of the basin, which are consistent with the high values of hazard and vulnerability. Considerably economic damages occurred to the critical infrastructure of all the sectors with the industry/commercial sector having the biggest impact. A negative variation in the country and industry Gross Domestic Product (GDP) was also reported. Our study is of great interest to those who are interested in estimating the economic impact of flood events. It can also assist decision makers in pinpointing factors that threaten the sustainability and stability of a risk-prone area and more specifically, to help them understand how to reduce social vulnerability to flood events.

Extreme heat undermines the working capacity of individuals, resulting in lower productivity, and thus economic output. Here we analyse the present and future economic damages due to reduced labour productivity caused by extreme heat in Europe. For the analysis of current impacts, we focused on heatwaves occurring in four recent anomalously hot years (2003, 2010, 2015, and 2018) and compared our findings to the historical period 1981-2010. In the selected years, the total estimated damages attributed to heatwaves amounted to 0.3-0.5% of European gross domestic product (GDP). However, the identified losses were largely heterogeneous across space, consistently showing GDP impacts beyond 1% in more vulnerable regions. Future projections indicate that by 2060 impacts might increase in Europe by a factor of almost five compared to the historical period 1981-2010 if no further mitigation or adaptation actions are taken, suggesting the presence of more pronounced effects in the regions where these damages are already acute. ; D.G.L. acknowledges financial support from the European Commission (H2020-MSCA-IF-2015) under REA grant agreement no. 705408. A.B., A.C., A.F., and L.N. received funding from the European Union's Horizon 2020 research and innovation program under the grant agreement no. 668786

Abstract. A variety of models have been applied to assess the economic losses of disasters, of which the most common ones are input–output (IO) and computable general equilibrium (CGE) models. In addition, an increasing number of scholars have developed hybrid approaches: one that combines both or either of them in combination with noneconomic methods. While both IO and CGE models are widely used, they are mainly compared on theoretical grounds. Few studies have compared disaster impacts of different model types in a systematic way and for the same geographical area, using similar input data. Such a comparison is valuable from both a scientific and policy perspective as the magnitude and the spatial distribution of the estimated losses are born likely to vary with the chosen modelling approach (IO, CGE, or hybrid). Hence, regional disaster impact loss estimates resulting from a range of models facilitate better decisions and policy making. Therefore, this study analyses the economic consequences for a specific case study, using three regional disaster impact models: two hybrid IO models and a CGE model. The case study concerns two flood scenarios in the Po River basin in Italy. Modelling results indicate that the difference in estimated total (national) economic losses and the regional distribution of those losses may vary by up to a factor of 7 between the three models, depending on the type of recovery path. Total economic impact, comprising all Italian regions, is negative in all models though.