Gabriele Standardi

Assessing direct and indirect economic impacts of a flood event through the integration of spatial and computable general equilibrium modelling

In this paper we developed and tested an integrated methodology for assessing direct and indirect economic impacts of flooding. The methodology combines a spatial analysis of the damage to the physical stock with a general economic equilibrium approach using a regionally-calibrated (to Italy) version of a Computable General Equilibrium (CGE) global model. We applied the model to the 2000 Po river flood in Northern Italy. To account for the uncertainty in the induced effects on regional economies, we explored three disruption and two recovery scenarios. The results highlight that: i) the flood event produces indirect losses in the national economic system, which are a significant share of the direct losses, and ii) the methodology is able to capture both positive and negative economic effects of the disaster in different areas of the same country. The assessment of indirect impacts, in particular, is essential for a full understanding of the economic outcomes of natural disasters. Rarely the accounting of flood losses includes indirect economic impacts.The proposed method integrates spatial and computable general equilibrium modelling for the estimation of indirect impacts.We analyse a flood event in Northern Italy, reporting indirect economic impacts as around 20 percent of direct impacts.Economic benefits arise in non-flooded sub-regions of Italy.

Policy-Relevant Assessment Method of Socio-Economic Impacts of Floods: An Italian Case Study

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.

A sub-national CGE model for Italy.

This paper describes a methodology to develop a Computable General Equilibrium model with a sub-national detail starting from a global database and model presenting the country-level as the highest resolution. This procedure is demonstratively applied to Italy, but can be transferred to any country/macro-region, provided regional data availability. Increasing the spatial resolution of a CGE model can be particularly useful to capture local specificities not only in response to given policy shocks, but also to environmental impacts, as, for instance, those originated by climate change, which are highly differentiated spatially. Conceptual and practical issues are treated: we use an innovative method to estimate bilateral trade flows across sub-national areas and analyse the implications of different assumptions on both factor and good intra-country mobility. We carry out a simple experiment to test the robustness of our regionalized structure.

Extending the Public Sector in the ICES Model with an Explicit Government Institution

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.

Sensitivity of Modeling Results to Technological and Regional Details: The Case of Italy's Carbon Mitigation Policy

Model differences in technological and geographical scales are common, but their contributions to uncertainties have not been systematically quantified in the climate policy literature. This paper carries out a systematic assessment on the sensitivity of Computable General Equilibrium models to technological and geographical scales in evaluating the economic impacts of carbon mitigation policies. Taking Italy as an example, we find that the estimation for carbon price and the economic cost of a de-carbonization pathway by means of a model with technological and regional details can be lower than a model without such details by up to 40%. Additionally, the effect of representing regional details appears to be far more important than the effect of representing the details of electricity technology in both the estimated carbon prices and the estimated economic impacts. Our results for Italy highlight the importance of modeling uncertainties of these two key assumptions, which should be appropriately acknowledged when applying CGE models for policy impact assessment. Our conclusions can be generalized to different countries and policy scenarios not in terms of absolute numbers but in terms of economic explanations. In particular, intra-national trade and the sub-national sectoral/technological specialization are important variables for understanding the economic dynamics behind these outcomes.

Data on Fiscal Systems of Countries Represented in the ICES Model, with Focus on Fossil Fuel Subsidies and First Test Run

This study details the first experiment conducted to couple the information relative to fossil fuel subsidies with the database and structure of the ICES CGE model developed at the CMCC, and to test the general performance of the model simulating their potential removal. Data for multi country and multi-fuel analysis derive from a “reconstruction process” based upon the price gap method, created by the IEA. The policy exercise consists in an instantaneous phasing out of existing subsidies in 2050. Removals are implemented imposing an ad valorem tax exactly equal to subsidies estimated by IEA (2009). We also compare our results with Burniaux and Chateau (2011) which conducted a similar analysis with the OECD ENV-Linkages model. Both models predict the expected decrease in CO2 emissions which is more pronounced in countries where the subsidy size is larger (Russian Federation, Former Soviet Union Countries and Oil exporting Countries). On the contrary the EU, where subsidies are small, increases its emissions due to a leakage effect. In the next phase of the research fossil fuel subsidies will be introduced explicitly in the price structure of ICES model.