No Arabic abstract
This paper proposes a public-private insurance scheme for earthquakes and floods in Italy in which property-owners, the insurer and the government co-operate in risk financing. Our model departs from the existing literature by describing a public-private insurance intended to relieve the financial burden that natural events place on governments, while at the same time assisting individuals and protecting the insurance business. Hence, the business is aiming at maximizing social welfare rather than profits. Given the limited amount of data available on natural risks, expected losses per individual have been estimated through risk-modeling. In order to evaluate the insurers loss profile, spatial correlation among insured assets has been evaluated by means of the Hoeffding bound for r-dependent random variables. Though earthquakes generate expected losses that are almost six times greater than floods, we found that the amount of public funds needed to manage the two perils is almost the same. We argue that this result is determined by a combination of the risk aversion of individuals and the shape of the loss distribution. Lastly, since earthquakes and floods are uncorrelated, we tested whether jointly managing the two perils can counteract the negative impact of spatial correlation. Some benefit from risk diversification emerged, though the probability of the government having to inject further capital might be considerable. Our findings suggest that, when not supported by the government, private insurance might either financially over-expose the insurer or set premiums so high that individuals would fail to purchase policies.
We develop an agent-based simulation of the catastrophe insurance and reinsurance industry and use it to study the problem of risk model homogeneity. The model simulates the balance sheets of insurance firms, who collect premiums from clients in return for ensuring them against intermittent, heavy-tailed risks. Firms manage their capital and pay dividends to their investors, and use either reinsurance contracts or cat bonds to hedge their tail risk. The model generates plausible time series of profits and losses and recovers stylized facts, such as the insurance cycle and the emergence of asymmetric, long tailed firm size distributions. We use the model to investigate the problem of risk model homogeneity. Under Solvency II, insurance companies are required to use only certified risk models. This has led to a situation in which only a few firms provide risk models, creating a systemic fragility to the errors in these models. We demonstrate that using too few models increases the risk of nonpayment and default while lowering profits for the industry as a whole. The presence of the reinsurance industry ameliorates the problem but does not remove it. Our results suggest that it would be valuable for regulators to incentivize model diversity. The framework we develop here provides a first step toward a simulation model of the insurance industry for testing policies and strategies for better capital management.
This paper presents a model where intergenerational occupational mobility is the joint outcome of three main determinants: income incentives, equality of opportunity and changes in the composition of occupations. The model rationalizes the use of transition matrices to measure mobility, which allows for the identification of asymmetric mobility patterns and for the formulation of a specific mobility index for each determinant. Italian children born in 1940-1951 had a lower mobility with respect to those born after 1965. The steady mobility for children born after 1965, however, covers a lower structural mobility in favour of upper-middle classes and a higher downward mobility from upper-middle classes. Equality of opportunity was far from the perfection but steady for those born after 1965. Changes in income incentives instead played a major role, leading to a higher downward mobility from upper-middle classes and lower upward mobility from the lower class.
With the costs of renewable energy technologies declining, new forms of urban energy systems are emerging that can be established in a cost-effective way. The SolarEV City concept has been proposed that uses rooftop Photovoltaics (PV) to its maximum extent, combined with Electric Vehicle (EV) with bi-directional charging for energy storage. Urban environments consist of various areas, such as residential and commercial districts, with different energy consumption patterns, building structures, and car parks. The cost effectiveness and decarbonization potentials of PV + EV and PV (+ battery) systems vary across these different urban environments and change over time as cost structures gradually shift. To evaluate these characteristics, we performed techno-economic analyses of PV, battery, and EV technologies for a residential area in Shinchi, Fukushima and the central commercial district of Kyoto, Japan between 2020 and 2040. We found that PV + EV and PV only systems in 2020 are already cost competitive relative to existing energy systems (grid electricity and gasoline car). In particular, the PV + EV system rapidly increases its economic advantage over time, particularly in the residential district which has larger PV capacity and EV battery storage relative to the size of energy demand. Electricity exchanges between neighbors (e.g., peer-to-peer or microgrid) further enhanced the economic value (net present value) and decarbonization potential of PV + EV systems up to 23 percent and 7 percent in 2030, respectively. These outcomes have important strategic implications for urban decarbonization over the coming decades.
Literature about the scholarly impact of scientific research offers very few contributions on private sector research, and the comparison with public sector. In this work, we try to fill this gap examining the citation-based impact of Italian 2010-2017 publications distinguishing authorship by the private sector from the public sector. In particular, we investigate the relation between different forms of collaboration and impact: how intra-sector private publications compare to public, and how private-public joint publications compare to intra-sector extramural collaborations. Finally, we assess the different effect of international collaboration on private and public research impact, and whether there occur differences across research fields.
The ambitious Net Zero aspirations of Great Britain (GB) require massive and rapid developments of Variable Renewable Energy (VRE) technologies. GB possesses substantial resources for these technologies, but questions remain about which VRE should be exploited where. This study explores the trade-offs between landscape impact, land use competition and resource quality for onshore wind as well as ground- and roof-mounted photovoltaic (PV) systems for GB. These trade-offs constrain the technical and economic potentials for these technologies at the Local Authority level. Our approach combines techno-economic and geospatial analyses with crowd-sourced scenicness data to quantify landscape aesthetics. Despite strong correlations between scenicness and planning application outcomes for onshore wind, no such relationship exists for ground-mounted PV. The innovative method for rooftop-PV assessment combines bottom-up analysis of four cities with a top-down approach at the national level. The results show large technical potentials that are strongly constrained by both landscape and land use aspects. This equates to about 1324 TWh of onshore wind, 153 TWh of rooftop PV and 1200-7093 TWh ground-mounted PV, depending on scenario. We conclude with five recommendations that focus around aligning energy and planning policies for VRE technologies across multiple scales and governance arenas.