Toward Consistent Cross-Hauling Estimation for Input-Output Regionalization

Although the literature has provided steps in the right direction, conceptual shortcomings still exist in the cross-hauling adjustment methods that are currently being applied in the literature. This paper represents an attempt to 1) characterize the cross-hauling adjustment methods that exist in the literature; 2) identify the shortcomings that exist with the most widely applied method, CHARM; 3) provide an empirical analysis to tackle the notion of just how ubiquitous crosshauling is and the potential impact it has on input-output multiplier estimates; and 4) suggest directions for future conceptual and theoretical development that will lead to consistent cross-hauling measures for use

A Role for Regional Science in Analyzing Water Issues

The World Economic Forum has consistently ranked water crises as one of the top five most impactful issues facing humanity, alongside but not completely separate from issues such as climate change and natural disasters (World Economic Forum, 2019). A growing population and changing climate will only further stress the constrained water system. Acute and ongoing societal disruptions, caused by significant declines in the available quality and quantity of fresh water around the globe, underscore the importance of water to human life and a functional society. The papers in this special issue highlight the role that regional scientists can and should play in informed decision-making related to water at the local, regional, and national scale

The Role of Regional Science in Shale Energy Development

The most recent boom in fossil fuel extraction is noteworthy through its extensive use of advanced technologies called hydraulic fracturing and horizontal drilling. The papers in this issue demonstrate the role that regional science can and should play in guiding policy, usefully complementing research from physical science and engineering disciplines that focuses on the important geological and environmental consequences of shale energy production. Furthermore, we underscore the need for expanding the traditional regional science focus in policy discussions pertaining to shale energy

Extending the Macroeconomic Impacts Forecasting Capabilities of the National Energy Modeling System

To comprehensively model the macroeconomic impacts that result from changes in long-term energy-economy forecasts, the United States Department of Energy’s National Energy Technology Laboratory (NETL) partnered with West Virginia University’s (WVU) Regional Research Institute to develop the NETL/WVU econometric input-output (ECIO) model. The NETL/WVU ECIO model is an impacts forecasting model that functions as an extension of the U.S. energy-economic models available from the United States (U.S.) Energy Information Administration’s National Energy Modeling System (NEMS) and the U.S. Environmental Protection Agency’s Market Allocation (MARKAL) model. The ECIO model integrates a macroeconomic econometric forecasting model and an input-output accounting framework along derived forecast scenarios detailing a baseline of the U.S. energy-economy and an alternative forecast on how power generation resources can meet future levels of energy demand to generate estimates of the impacts to gross domestic product, employment, and labor income. This manuscript provides an overview of the model design, assumptions, and standard outputs

Erratum to: Methods for evaluating medical tests and biomarkers

[This corrects the article DOI: 10.1186/s41512-016-0001-y.]

Evidence synthesis to inform model-based cost-effectiveness evaluations of diagnostic tests: a methodological systematic review of health technology assessments

Background: Evaluations of diagnostic tests are challenging because of the indirect nature of their impact on patient outcomes. Model-based health economic evaluations of tests allow different types of evidence from various sources to be incorporated and enable cost-effectiveness estimates to be made beyond the duration of available study data. To parameterize a health-economic model fully, all the ways a test impacts on patient health must be quantified, including but not limited to diagnostic test accuracy. Methods: We assessed all UK NIHR HTA reports published May 2009-July 2015. Reports were included if they evaluated a diagnostic test, included a model-based health economic evaluation and included a systematic review and meta-analysis of test accuracy. From each eligible report we extracted information on the following topics: 1) what evidence aside from test accuracy was searched for and synthesised, 2) which methods were used to synthesise test accuracy evidence and how did the results inform the economic model, 3) how/whether threshold effects were explored, 4) how the potential dependency between multiple tests in a pathway was accounted for, and 5) for evaluations of tests targeted at the primary care setting, how evidence from differing healthcare settings was incorporated. Results: The bivariate or HSROC model was implemented in 20/22 reports that met all inclusion criteria. Test accuracy data for health economic modelling was obtained from meta-analyses completely in four reports, partially in fourteen reports and not at all in four reports. Only 2/7 reports that used a quantitative test gave clear threshold recommendations. All 22 reports explored the effect of uncertainty in accuracy parameters but most of those that used multiple tests did not allow for dependence between test results. 7/22 tests were potentially suitable for primary care but the majority found limited evidence on test accuracy in primary care settings. Conclusions: The uptake of appropriate meta-analysis methods for synthesising evidence on diagnostic test accuracy in UK NIHR HTAs has improved in recent years. Future research should focus on other evidence requirements for cost-effectiveness assessment, threshold effects for quantitative tests and the impact of multiple diagnostic tests

Erratum to: Methods for evaluating medical tests and biomarkers

[This corrects the article DOI: 10.1186/s41512-016-0001-y.]

Can hazardous waste supply chain 'hotspots' be identified using an input-output framework?

The paper examines a method to attribute hazardous waste streams to regional production and consumption activity, and to connect these same waste streams through to different management options. We argue that a method using an input–output framework provides useful intelligence for decision makers seeking to connect elements of the management of the hazardous waste hierarchy to production and to different patterns and types of final consumption (of which domestic household consumption is one). This paper extends application of conventional demand driven input–output attribution methods to identify hazardous waste ‘hotspots’ in the supply chains of different final consumption goods and consumption groups. Using a regional case study to exposit the framework and its use, we find that domestic government final consumption of public administration production indirectly drives hazardous waste generation that goes to landfill, particularly in the domestic construction and sanitary services sectors, but also in the manufacture of wood products