Analysing Materials and Energy Flows in an Industrial District using an Enterprise Input–Output Model

Recent approaches to sustainable development leave much room for policies at a local level. In fact, it is becoming evident that targets such as increasing resource productivity, preserving natural cycles, or extending the present level of welfare, are best pursued within the confines of a local area. In particular, environmental changes are best brought about by considering local systems of firms as cornerstones of cooperative strategies and using data on materials and energy use in physical terms. In this paper, an enterprise input–output model is developed for an industrial district, i.e. a local group of firms specialized in the production of a single final output. The model allows for a detailed quantitative analysis of materials and energy flows and the consequent generation of waste and pollution. As a planning tool, the model may be used to evaluate alternative scenarios, such as the possibility of re- using waste taking account of sustainability requirements. An empirical case study applies the model to an industrial district in Southern Italy producing leather sofas.     

Environmental,Social and Governance investing: Does rating matter?

In the last decade, the demand for sustainable and social investments has improved. The mutual funds industry has responded to market needs by offering a number of investment products focused on Environmental, Social and Governance (ESG) companies. The aim of this article is to understand if an ESG score can actually be considered a valid criterion that portfolio managers could adopt, along with traditional risk–return optimisation, in selecting asset portfolios. The paper analyses the link between the performance and the ESG score of different sectoral portfolios (one for each sector of the Global Industry Classification Standard), entirely composed of ESG assets, in the search for a clear and strong positive correlation that could suggest an overall advantage to focus on an ex ante choice of assets with high ESG scores.     

North–South terms‐of‐trade trends from 1960 to 2006

The composition of exports of developing countries is increasingly dominated by manufactured goods. This has not changed the fact that their major trading partners continue to be the developed countries. In order to properly assess the distribution of gains from trade, there is a pressing need to analyze the movements in the terms of trade of developing countries with respect to the developed ones. A statistical analysis of the North–South terms of trade reveals that the terms of trade have turned against the South since the 1960s. However, the terms‐of‐trade deterioration is neither continuous nor evenly distributed over different country groupings. The existence of a structural break in the mid‐to‐late 1970s together with the greatest adverse terms‐of‐trade movements against the highly indebted and least developed countries attest the discontinuity and unevenness of this process.     

(De)Politicization Dynamics in Public–Private Partnerships (PPPs): Lessons from a comparison between UK and Flemish PPP policy

This article analyses the (de)politicization dynamics in complex and technical matters like public–private partnerships, which is necessary given its social impact and budgetary consequences for the years and generations to come. The global financial crisis provides an excellent window of opportunity to present this argument, because PPP policy needs to reinvent itself. We argue that PPP policy needs to be (re)politicized at the broader societal and discursive levels, which means that their public nature is recognized and that policy alternatives are debated in the public forums. The ‘Private Finance Initiative’ reassessment process in the UK may serve as an example.     

ANALYSING THE STRUCTURE OF THE ECONOMY USING PHYSICAL INPUT–OUTPUT TABLES

Analyses using physical input–output tables (PIOTs) are key to understanding the physical metabolism of economies, since they relate production to the generation of emissions and use of resources. Two methods have been developed to calculate the primary resources and emissions associated with a given final demand. However, one of these alters the PIOT, revealing different technical coefficients and Leontief inverse matrices. Which method should be used for structural analysis? In this paper, I compare both methods, explain the structural differences between them and illustrate the latter through a backward linkage analysis. I find that only one method is suited to the analysis of the physical structure of the economy, since it comprehends both the production of goods and associated emissions. The method is identified as a new model capable of tracing by-products as final outputs. Finally, I generalise both methods to analyse PIOTs including several emission types.     

The use–make framework and the derivation of functional forms in production theory

The use–make framework is employed to explain functional forms in production theory, including Cobb–Douglas and Leontief. Productivity and efficiency are interrelated by augmenting the framework with a linear program that determines the frontier output.     

Spatial statistical modelling of insurance risk: a spatial epidemiological approach to car insurance

Spatial models, such as the Besag, York and Mollie (BYM) model, have long been used in epidemiology and disease mapping. A common research question in these subjects is modelling the number of disease events per region; here the BYM models provides a holistic framework for both covariates and dependencies between regions. We use these tools to assess the relative insurance risk associated with the policyholders geographical location. A Bayesian modelling approach is presented and an elastic net is used to reduce the large number of possible geographic covariates. The final inference is performed using Integrated Nested Laplace Approximation. The model is applied to car insurance data from If P&C Insurance together with spatially referenced covariate data of high resolution, provided by Insightone. The entire analysis is performed using freely available R-packages. Including spatial dependence when modelling the number of claims significantly improves on the result obtained using ordinary generalised linear models. However, the support for adding a spatial component to the model for claims cost is weaker.