Functional Structure and Approximation in Econometrics (book front matter)

This is the front matter from the book, William A. Barnett and Jane Binner (eds.), Functional Structure and Approximation in Econometrics, published in 2004 by Elsevier in its Contributions to Economic Analysis monograph series. The front matter includes the Table of Contents, Volume Introduction, and Section Introductions by Barnett and Binner and the Preface by W. Erwin Diewert. The volume contains a unified collection and discussion of W. A. Barnett's most important published papers on applied and theoretical econometric modelling.consumer demand, production, flexible functional form, functional structure, asymptotics, nonlinearity, systemwide models

Analyzing Divisia Rules Extracted from a Feedforward Neural Network

This paper introduces a mechanism for generating a series of rules that characterize the money-price relationship, defined as the relationship between the rate of growth of the money supply and inflation. Division component data is used to train a selection of candidate feedforward neural networks. The selected network is mined for rules, expressed in human-readable and machine-executable form. The rule and network accuracy are compared, and expert commentary is made on the readability and reliability of the extracted rule set. The ultimate goal of this research is to produce rules that meaningfully and accurately describe inflation in terms of Divisia component dataset

Multiple‑Purchaser Payments for Ecosystem Services: An Exploration Using Spatial Simulation Modelling

This is the final version. Available on open access from Springer via the DOI in this recordThis paper focuses on the issue of payments for ecosystem services (PES) mechanism design when the activity incentivised through the scheme benefits multiple groups, each of whom might be prepared to contribute to payments made through the scheme. In particular, we examine spatial coordination on the demand side of the market; that is to say, the question of which beneficiary of the PES scheme buys land-management changes on which land parcels. We show through spatial simulation modelling that it is possible for negotiation to lead to Pareto improvements when compared to solutions reached through non-cooperative strategic solutions; however, we also show that this result is not universal and only holds under certain conditions. In particular, the spatial correlation and spatial interdependence of the ecosystem service benefits are key in determining whether negotiation between beneficiaries is optimal and therefore if policy makers and designers of PES schemes should be prioritising bringing together multiple beneficiaries of ecosystem services

Valuing the social and environmental contribution of woodlands and trees in England, Scotland and Wales

Final published report. This publication is also available on the Foresty Commission website at: www.forestry.gov.uk/publicationsFirst published by the Forestry Commission in 2017.A second edition of this report is available in ORE: http://hdl.handle.net/10871/36539The diverse resources provided by trees and woodlands contribute to the production of a wide array of benefits ranging from timber to wildlife habitats and from carbon storage to water purification. This diversity is further complicated by the fact that, while some of the goods associated with forests are traded in markets and hence have associated prices, others arise outside markets and, while valuable, lack prices. The need to make evidencebased decisions regarding woodlands, including decisions such as how much public funding should be allocated to support the non-market benefits they generate, has necessitated the estimation of the value of those benefits. This scoping study provides a structured review of the state of knowledge regarding the economic valuation of social and environmental benefits derived from trees and woodlands in order to support policy and practice. Particular (although not exclusive) attention is paid to recent extensions to the literature since previous reviews (especially Eftec, 2011)

Early Detection of Mass Disaster Events Using Social Media Data

During a mass disaster, social media are a major source of information providing first-hand accounts of the unfolding situation. Automated ways to discover and collate this information in real-time can be of critical value for humanitarian operations. Prior work on this task largely focused on developing message classifiers restricted to particular types of disasters, such as storms or wildfires. In this paper we investigate machine-learning methods to detect crisis-related messages where the type of the crisis is not known in advance. The methods are potentially of a much greater practical value, as they can provide the means to deal with a wide range of crisis situations, including those that involve combinations of disaster types and types that were unknown at the training stage. The key challenge with this task is the fact that events of potential relevance are extremely diverse and correspondingly both training and test data are highly heterogeneous. The data heterogeneity causes significant difficulties for machine learning algorithms to generalize and accurately label incoming data. Our main contributions are an investigation of the scope of this problem in the context of disaster management, and novel message classification methods to overcome data heterogeneity based on ensemble methods, semi-supervised learning and feature selection. We evaluate the proposed methods on an academic benchmark dataset comprising twenty-six different disaster events, as well as in a case study where we assess the performance of the methods on real-world data. The experimental evaluation shows that the methods achieve quality of classification superior to methods previously used for this task

Valuing the social and environmental contribution of woodlands and trees in England, Scotland and Wales. Second edition: to 2018

The first edition of this report is available in ORE: http://hdl.handle.net/10871/25958Woodlands and forests constitute arguably the most diverse environments on earth; diverse not only in terms of the plethora of characteristics and habitats they embrace, but also through the variety of benefits and values that they offer to people. While this diversity of benefits is now widely recognised, incorporating these values into decisions regarding the management and extension of woodland remains a challenge. While the value of some forest products, such as timber, is readily reflected within market prices, this is the exception rather than the rule. Most of the benefits provided by woodlands are not traded through markets and are therefore unpriced public goods. The UK Forestry Commission have for many years directly addressed the problem of incorporating the non-market benefits of woodland within conventional economic decision making through the application of techniques to estimate the economic value of these benefits (e.g. Willis, et al., 2003). As part of this initiative, in 2015 the Forestry Commission began working with the authors of the present report to provide a review of the research, policy and grey literature concerned with the economic valuation of the social and environmental benefits of woodlands and trees. This review, subsequently published as Binner et al., (2017) also included the development of a spreadsheet based decision support tool to facilitate the use of valuation estimates within decision making. The present report provides a second edition of that report, updating both the literature review and the accompanying spreadsheet decision support tool. In preparing this study, the research team at the University of Exeter undertook a structured reviewed of how technical and methodological developments are transforming the potential for robust valuation of non-market benefits and allied decision-making. The methods, data and modelling techniques, which underpin the existing evidence base on the value of woodlands and trees were critically evaluated, so as to provide a practical set of actionable options for enhancing that evidence base and improving decision making

Assessing extraterrestrial regolith material simulants for in-situ resource utilization based 3D printing

This research paper investigates the suitability of ceramic multicomponent materials, which are found on the Martian and Lunar surfaces, for 3D printing (aka Additive Manufacturing) of solid structures. 3D printing is a promising solution as part of the cutting edge field of future in‐situ space manufacturing applications. 3D printing of physical assets from simulated Martian and Lunar regolith was successfully performed during this work by utilising laser‐based powder bed fusion equipment. Extensive evaluation of the raw regolith simulants was conducted via Optical and Electron Microscopy (SEM), Visible‐Near Infrared/Infrared (Vis‐NIR/IR) Spectroscopy and thermal characterisation via Thermogravimetric Analysis (TGA) and Differential Scanning Calorimetry (DSC). The analysis results led to the characterisation of key properties of these multicomponent ceramic materials with regards to their processability via powder bed fusion 3D printing. The Lunar and Martian simulant regolith analogues demonstrated spectral absorbance values of up to 92% within the Vis‐NIR spectra. Thermal analysis demonstrated that these materials respond very differently to laser processing, with a high volatility (30% weight change) for the Martian analogue as opposed to its less volatile Lunar counterpart (<1% weight change). Results also showed a range of multiple thermal occurrences associated with melting, glass transition and crystallisation reactions. The morphological features of the powder particles are identified as contributing to densification limitations for powder bed fusion processing. This investigation has shown that – provided that the simulants are good matches for the actual regoliths – the lunar material is a viable candidate material for powder bed fusion 3D printing, whereas Martian regolith is not

Scoping the strengths and weaknesses of different auction and PES mechanisms for Countryside Stewardship

This is the final version. Available from Defra (Department for Environment, Food and Rural Affairs) via the link in this recordThe majority of farmers in England currently receive a fixed fee for managing their land under an agrienvironment scheme (Environmental Stewardship), which is based on an estimate of the typical income forgone by participating. The aim of this research is to explore alternative mechanisms for allocating agri-environment contracts with a view to achieving a more cost-efficient and effective use of funds. The focus is on reverse auctions, whereby farmers opt into a bidding process, offering to manage their land under prescribed management options at a price that more closely reflects their cost of doing so. The researchers have used a combination of laboratory experiments, simulation modelling and farmer workshops to consider the opportunity for efficiency gains, aspects of auction design and farmer responses to auctions. A secondary objective of the work is to explore opportunities for the private sector to engage in agrienvironment actions by leveraging match-funding where there are common goals and mutual benefits for private firms and society. This has entailed a review of the payment for ecosystem services (PES) literature and consultations with a number of relevant private firms. A particular focus for the latter has been the water companies, as they have already established some initiatives on PES around improving water quality

Mechanical behaviour of additively manufactured lunar regolith simulant components

Additive manufacturing and its related techniques have frequently been put forward as a promising candidate for planetary in-situ manufacturing, from building life-sustaining habitats on the Moon to fabricating various replacements parts, aiming to support future extra-terrestrial human activity. This paper investigates the mechanical behaviour of lunar regolith simulant material components, which is a potential future space engineering material, manufactured by a laser-based powder bed fusion additive manufacturing system. The influence of laser energy input during processing was associated with the evolution of component porosity, measured via optical and scanning electron microscopy in combination with gas expansion pycnometry. The compressive strength performance and Vickers microhardness of the components were analysed and related back to the processing history and resultant microstructure of the lunar regolith simulant build material. Fabricated structures exhibited a relative porosity of 44 – 49% and densities ranging from 1.76 – 2.3 g cm-3, with a maximum compressive strength of 4.2 ± 0.1 MPa and elastic modulus of 287.3 ± 6.6 MPa, the former is comparable to a typical masonry clay brick (3.5 MPa). The 2AM parts also had an average hardness value of 657 ± 14 HV0.05/15, better than borosilicate glass (580 HV). This study has shed significant insight into realizing the potential of a laser-based powder bed fusion AM process to deliver functional engineering assets via in-situ and abundant material sources that can be potentially used for future engineering applications in aerospace and astronautics