Regional income inequality in France : what does history teach us?

This paper studies regional income inequality in France since mid-nineteenth century. Given the dominant role played by Île-de-France and the city of Paris, which inspired the publication of “Paris et le désert française” (Gravier, 1947) and a debate on regional development in the aftermath of World War II, France seems an ideal scenario to examine the dynamics of regional income. In doing so, we first document the existing evidence before and after the development of national accounting. Using different approaches, several studies have produced regional (département, NUTS3) Gross Domestic Product (GDP) estimates from 1840 to 1930. Thus, our first contribution is to present these findings, assess the appropriateness of each methodology, and address potential concerns. The comparison of existing estimates for 1861-1930 raises some doubts about the pattern of regional inequality followed since 1861 to 1911. Hence we present new estimates for 1860-1930 based in the Geary and Stark (2002) method. In short, our estimates sum up new evidence in favour of an incessant decline in regional inequality since mid 19th up to 1930 and turn down the hypothesis of a potential U-shaped pattern in France since mid 19th century to nowadays. Additionally, we found that the use of nominal relative wages could overestimate the level or regional income inequality

Technology-Agnostic Assessment of Wave Energy System Capabilities

Developing new wave energy technologies is risky, costly and time-consuming. The large diversity of concepts, components and evaluation criteria creates a vast design space of potentially feasible solutions. This paper aims to introduce a novel methodology for the holistic assessment of wave energy capabilities in various market applications based on sound Systems Engineering methods. The methodology provides a consistent hierarchy of performance metrics relevant to the given system of reference, design activity and development stage under consideration as a means to scrutinise wave energy requirements. Full traceability of system requirements and performance metrics is then facilitated by multi-criteria decision tools and aggregation logic, respectively. The qualitative assessment in the case studies has resulted in very different rankings of System Drivers and Stakeholders for the two market applications considered. However, the Stakeholder Requirements and Functional Requirements present a small variation in the weights for the two application markets which results in a quantitative assessment with very similar Global Merit. Finally, the performance benchmark using the Commercial Attractiveness and Technical Achievability concepts enables a more objective comparison in the utility-scale and remote generation markets and a way to concentrate innovation efforts before proceeding to the next development stage.This research received no external fundin

Review of Systems Engineering (SE) Methods and Their Application to Wave Energy Technology Development

The design of effective and economically viable wave energy devices involves complex decision-making about the product based on conceptual design information, including stakeholder requirements, functions, components and technical parameters. The great diversity of concepts makes it extremely difficult to create fair comparisons of the relative merits of the many different designs. Conventional design approaches have proved insufficient to guarantee wave energy technologies meet their technical and economic goals. Systems engineering can provide a suitable framework to overcome the obstacles towards a successful wave energy technology. The main objective of this work is to review the well-established systems engineering approaches that have been successfully implemented in complex engineering problems and to what extent they have been applied to wave energy technology development. The paper first reviews how system information can be organised in different design domains to guide the synthesis and analysis activities and the definition of requirements and metrics, as well as the search for solutions and decision-making. Then, an exhaustive literature review on the application of systems engineering approaches to wave energy development is presented per design domain. Finally, a set of conclusions is drawn, along with some suggestions for improving the effectiveness of wave energy technology development.Authors would like to thank the Basque Government through the research groups IT1314‐19 and GIU19/276 and the Scottish Government for the support of Wave Energy Scotland

The origins of economic growth and regional income inequality in South-West Europe 1870-1950

This study focuses on South-West Europe, an area comprising France, Italy, Spain and Portugal, to evaluate inequality in regional income between 1870 and 1950. To do this, information on a decadal basis on regional population and Gross Domestic Product (GDP) for 171 regions (84 French départements, 22 Italian regioni, 18 Portuguese distritos and 49 Spanish provincias) has been collected. Regional inequalities increased between 1870 and 1910 but subsequently tended to flatten out through until 1950. In the first period, regional disparities increased mainly driven by a handful of French and Spanish regions in northern France, such as the Paris basin, Catalonia, the Basque-Country and northern Italy. In the second period, inequality flattened out, driven by the incorporation of new regions on the path of modern economic growth. The study also shows the evolution towards a bimodal, polarized pattern of regional income distribution in 1910-1950 with two convergence clubs. The richest regions were clustering in northern France, the Paris basin and the north of Italy. Meanwhile, most of southern Italy and the vast majority of the Spanish and Portuguese regions already occupied the bottom positions in the income distribution ranking. This point to the emergence of the core-periphery pattern that characterizes much of South-West Europe today

Estimating Future Costs of Emerging Wave Energy Technologies

The development of new renewable energy technologies is generally perceived as a critical factor in the fight against climate change. However, significant difficulties arise when estimating the future performance and costs of nascent technologies such as wave energy. Robust methods to estimate the commercial costs that emerging technologies may reach in the future are needed to inform decision-making. The aim of this paper is to increase the clarity, consistency, and utility of future cost estimates for emerging wave energy technologies. It proposes a novel three-step method: (1) using a combination of existing bottom-up and top-down approaches to derive the current cost breakdown; (2) assigning uncertainty ranges, depending on the estimation reliability then used, to derive the first-of-a-kind cost of the commercial technology; and (3) applying component-based learning rates to produce the LCOE of a mature technology using the upper bound from (2) to account for optimism bias. This novel method counters the human propensity toward over-optimism. Compared with state-of-the-art direct estimation approaches, it provides a tool that can be used to explore uncertainties and focus attention on the accuracy of cost estimates and potential learning from the early stage of technology development. Moreover, this approach delivers useful information to identify remaining technology challenges, concentrate innovation efforts, and collect evidence through testing activities

The long-term relationship between economic development and regional inequality: South-West Europe, 1860-2010

This paper analyses the long-term relationship between regional inequality and economic development. Our data set includes information on national and regional per capita GDP for four countries: France, Italy, Portugal and Spain, compiled on a decadal basis for the period 1860–2010. Using parametric and semiparametric regressions, our results confirm the rise and fall of regional inequalities over time although in recent decades they are on the rise again. Finally, we identify structural change as being a significant transmission mechanism of the inverted-U relationship. The arrival of technological shocks, beginning during the onset of industrialization, and the transition from agrarian to industrial economies, would explain this result

Advanced Exergy Analysis of an Integrated SOFC-Adsorption Refrigeration Power System

In this chapter, an exergy analysis applied to a solid oxide fuel cell (SOFC)/vapor adsorption refrigeration (VAR) system is presented. The influences of four significant parameters (current density, inlet fuel temperature, fuel utilization and steam-to-carbon ratio) on the exergy efficiency of both the SOFC stack and the SOFC-VAR system are investigated. In order to do so, a mathematical model is constructed in Engineering Equation Solver (EES) software to generate the simulations. The analysis shows that the calculated exergy efficiency is around 8% lower than the energy efficiency for both cases. Moreover, it is found that most of the causes of irreversibilities in the system are due to electronic and ionic conduction in the components. It is also shown that the exergy efficiency is substantially sensitive to fuel inlet temperature, which is evidenced by a bending-over behavior. Finally, in accordance with the calculated efficiency defects, the main exergy destructions are present in the heat exchangers, the SOFC, the afterburner and the generator

On building physics-based AI models for the design and SHM of mooring systems

Expert systems in industrial processes are modelled using physics-based approaches, data-driven models or hybrid approaches in which however the underlying physical models generally constitute a separate block with respect to the Artificial Intelligence (AI) technique(s). This work applies the novel concept of “imbrication”-a physics-based AI approach-to the mooring system of offshore renewable energy devices to achieve a complete integration of both perspectives. This approach can reduce the size of the training dataset and computational time while delivering algorithms with higher generalization capability and explicability. We first undertake the design of the mooring system by developing a surrogate model coupled with a Bayesian optimiser. Then, we analyse the structural health monitoring of the mooring system by designing a supervised Deep Neural Network architecture. Herein, we describe the characteristics of the imbrication process, analyse preliminary results of our investigation and provide considerations for orienting further research work and sector applicability