Working papers
Here you can find the discussion papers of the REAL technical series and other works
2018
Economic Crisis and Youth Unemployment in Europe: the Role of Regional Specialization Through a Spatial Quantile Approach
André Carrascal Incera and Diana Gutiérrez Posada
Abstract: European youth unemployment exhibits a contrasting image between the Northern and the Southern regions, which leads the analysis towards the drivers behind the spatial clustering of areas with low or high unemployment rates. The aim of this article is to provide some hints about the structural causes of the spatial distribution of youth unemployment growth during the recent crisis, using a Spatial Quantile approach at NUTS2 level. Results suggest that the similarity in the productive structure, the specialization in sectors with a higher concentration of young workers, or the working time flexibility had a different effect in those regions at the top or the bottom of the youth unemployment growth distribution, being this effect significantly different from the result of the global spatial estimation.
The Impact of High-Speed Railway on Urban Growth: A Multi-Scale Spatiotemporal Approach
Haozhi Pan, Peng Chen, Sandy Dall'erba and Yina Zhang
Abstract: The literature offers conflicting evidence on the impact of high-speed railway (HSR) operations on urban growth. This paper argues that the source of the differences lies in the variety of spatial scales under study. In order to address this conundrum, this paper studies the impact on urban growth of the start-of-operation of two HSR lines built in the Yangtze River Delta, China. Based on a high spatial and temporal granularity dataset and a non-parametric spatiotemporal model, the findings suggest that HSR operations have a significant positive impact locally (<5 km) but not at the county level. In addition, this paper finds that the local spillovers of urban growth decay drastically 3 to 6 months after the beginning of the operations. The findings support the development of economic activities linked to passenger transportation at or near the train stations.
The Effects of Oil Price on Regional Trade in the United States
Wojciech W. Szewerniak, Yilan Xu and Sandy Dall'erba
Abstract: This paper studies the effect of the diesel price on trade flows across space within the United States. Using a structural gravity model with spatially autocorrelated flows applied to the inter-state trade, we find that an increase in diesel price reduces the volume of trade and that this effect increases with the distance between trade partners. Furthermore, such price shock increases trade within a state and with nearby partners. Finally, the social welfare effects of a 10% increase in diesel price vary by states, with the median corresponding to a 0.69% loss in the real GDP or $82 billion nationwide.
Socio-Natural Processes and Land-Use Modeling in Support of Integrated Water Resource Management Practices
Haozhi Pan, Brian Deal, Georgia Destouni, Yalei Zhang and Zahra Kalantari
Abstract: This paper argues that a systems thinking and explicit modeling approach is needed to address noted weaknesses (practicality and usefulness) in Integrated Water Resource Management projects. A pioneering effort in coupling land-use, regional economy, and water systems models is demonstrated with a proof of concept applications in 2 cities (Chicago and Stockholm). The analysis is conducted primarily through refining, applying, and integrating existing (stand-alone) models. The approach faces challenges that including data, deep uncertainties, and information constraints. Solutions including uncertainty analysis, mutual learning, and scenario building are discussed and demonstrated. The integrated model results reveal that the physical availability of land for economic activities forecasted via land use change probabilities can vary widely from sectoral regional economic forecasts, suggesting that both human (economic and land-use planning) and natural processes (land-cover evolution) need to be justified in order to reconcile integrated results. Moreover, land-use and water models both need to be adjusted when assessing one system’s impact on the other. For example, flood-zone regulations can divert land-use to other locations, while land-cover change affects the amount of impervious surfaces and alter future hydrological outcomes. Our results demonstrate that modeling social and natural processes with the appropriate feedback provides a more comprehensive understanding of both the causal mechanisms and the potential impacts of an Integrated Water Resource Management application.
Comparing the economic impact of natural disasters generated by different input-output models. An application to the 2007 Chehalis River Flood (WA)
Andre F. T. Avelino and Sandy Dall'erba
Abstract: Due to the concentration of assets in disaster-prone zones, changes in risk landscape and in the intensity of natural events, property losses have increased considerably in recent decades. While measuring these stock damages is common practice in the literature, the assessment of economic ripple effects due to business interruption is still limited and available estimates tend to vary significantly across models. This paper focuses on the most popular single-region input-output models for disaster impact evaluation. It starts with the traditional Leontief model and then compares its assumptions and results with more complex methodologies (rebalancing algorithms, the sequential interindustry model, the dynamic inoperability input-output model and its inventory counterpart). While the estimated losses vary across models, all the figures are based on the same event, the 2007 Chehalis river flood that impacted three rural counties in Washington State. Given that the large majority of floods take place in rural areas, this paper gives the practitioner a thorough review of how future events can be assessed and guidance on model selection.
2017
Do crop insurance programs preclude their recipients from adapting to new climate conditions?
Zhangliang Chen and Sandy Dall’Erba
Abstract: Concerns that federal crop insurance programs reduce the farmers’ willingness to adapt to adverse changes in climate are growing. However, current evidence is limited to a small number of specific crops and relies on proxies for insurance payments. Here, we show how crop insurance programs modify the theoretical predictions of the Ricardian framework that accounts for all types of crops and many forms of adaptation to climate change. Furthermore, we exploit panel data on actual crop insurance payments to demonstrate empirically to what extent their magnitude and frequency bias the impact of climate change and extreme events on farmland value.
The Challenge of Estimating the Impact of Disasters: many approaches, many limitations and a compromise
Andre F. T. Avelino and Geoffrey J. D. Hewings
Abstract: The recent upward trend in the direct costs of natural disasters is a reflection of both an increase in asset densities and the concentration of economic activities in hazard-prone areas. Although losses in physical infrastructure and lifelines are usually spatially concentrated in a few areas, their effects tend to spread geographically and temporally due to production chains and the timing and length of disruptions. Since the 1980’s, several techniques have been proposed to model higher-order economic impacts of disruptive events, most of which are based on the input-output framework. However, there is still no consensus for a preferred model to adopt. Available models tend to focus on just one side of the market or have theoretical flaws when incorporating both sides. In this paper, the Generalized Dynamic Input-Output framework (GDIO) is presented and its theoretical basis derived. It encompasses the virtues of intertemporal dynamic models with the explicit intratemporal modeling of production and market clearing, thus allowing supply and demand constraints to be simultaneously analyzed. Final demand is endogenized via a demo-economic extension to study the impact of displacement and unemployment post-disaster. The key roles of inventories, expectation’s adjustment, primary inputs, labor force and physical assets in disaster assessment are explored and previous limitations in the literature are addressed. It will be shown that the dynamic Leontief model, the sequential interindustry model and the traditional input-output model are all special cases of the GDIO framework.