The decline in the demand for coal has led to significant negative impacts in areas throughout Appalachia. Consider the integrated effects across components of the coal industry ecosystem (CIE). As extraction activity is diminished, there are ripples through the industry supply chain that extends to a wide number of sectors, occupations, and county and multi-county regions of the Appalachian economy. As these suppliers are impacted, jobs are imperiled, and the fiscal health of communities i s weakened. Displaced workers will need to seek alternative employment opportunities that may entail investments in formal education and training, and this takes both time and resources. As the economic base suffers, state and local governments will see their capacity to fund education weaken as well. The decline in natural gas prices and increasing environmental concerns, along with the age of the capital stock, has affected coal-fired power generation in the Appalachian Region. When capacity is replaced by natural gas, the demand for the Region’s coal is further distressed. The shifting structure and spatial location of power generation creates additional impacts on the economic base, tax base, and employment prospects. A vibrant rail transportation infrastructure has developed to support coal-related commerce and this regional asset is now at risk. Retirement of portions of the railroad capital stock may translate into higher transportation costs and diminished opportunities for economic development tied to the movement of bulk commodities, inputs, and final products.
This report describes an effort to provide for the Appalachian Region a clearer picture of the implications for the Power Industry Ecosystem (PIE) of power generating technology transitions and the geographical variations in PIE impacts. We develop and implement three measures that reveal meaningful characteristics of the PIE at the county level in terms of industry and place-based PIE dependence, changes in PIE-dependent employment, and susceptibility to impacts from a continued energy sector transition. We then use these three measures-Dependence, Impact, and Risk-to form a typology that we apply to identify and focus on counties in three identifiable categories: Hardship counties, Vulnerable counties, and Depressed counties.
The interest in this paper lies in the environmental costs of the European Union (EU). EU membership requires a series of economic and political changes that should impact the country’s production and consumption structures and its trade relationships. These, in turn, will affect CO2 emissions sources and levels. This is especially true for the former Soviet Union countries that recently joined the EU, given the difference in their levels of development and production structure.Using a structural decomposition analysis we are able to quantify the main drivers of changes in emissions differentiating six components, namely: emissions intensity, industrial structure and sourcing,consumer preferences, final demand sourcing and consumption level. Grouping the countries into five clubs, New European Union countries, Old European Union countries, the United States of America, China, and the Rest of the World, we measure trading pattern changes and their impact on CO2 emission levels.
This part of the project identifies existing industrial clusters for the Potomac Highlands region in West Virginia and seeks potential industries or clusters for economic development. We also evaluate strengths and gaps of existing industry clusters. Our cluster analysis comprises three parts, including (1) location quotient (LQ) analysis, (2) shift-share analysis, and (3) input-output (I-O) analysis. Results of both location quotient and shift-share analyses are used for industry targeting, whereas input-output analysis measures existing cluster strengths and bottlenecks for potential cluster diversification strategies based on Jackson’s(2015) cluster and diversification strategy (CADS).
Competition for local economic development has increased dramatically in the past 20 years. This competition is in many cases extremely costly to states and communities, while the benefits are uncertain. If regions whose economic fortunes are complementary could work with instead of against one another, costs of competition could be eliminated, while returns to economic development investments could be enhanced. This paper presents a method by which the underlying spatial economic relationships among areas within a region can be identified. Economic development policy can then be guided by the identification of the competitive or complementary links that exist among areas. The Dendrinos-Sonis (DS) model of relative social spatial dynamics is used to determine these relationships, in aggregate and on an industry-by- industry basis, in the Cincinnati metropolitan region. Sets of competitive and complementary region pairs are identified.
This report examines the impact of the decline in coal production on supply chain industries at the county level across Appalachia. It offers, and uses, a typology to classify counties based on their dependence on the CIE, recent employment changes due to reduced coal production, and their risk for further impacts due to any future declines in the coal industry.
This paper presents a method by which issues associated with the impact of the corporate‐conglomerate structure on regional economic health and performance can be assessed. An alternative measure of the impact of external ownership based on intraregional commodity flows is introduced. A review of previous measures of external economic dominance with respect to the analysis of regional economic health and development is followed by a description of the new measurement method and directions for research application.
The year 2015 marked the fiftieth anniversary of West Virginia University’s (WVU) Regional Research Institute (RRI), which has played an important role in many scientific collaboration networks. Through social network analysis (SNA) focusing on the RRI research community since its inception in 1965, this article illustrates the role that organizations and the networks they promote can play in scientific problem domains, promoting scholarly collaborations and coauthorship in the field of regional science. We analyzed an evolving WVU RRI coauthorship network that has grown and gained in complexity over time in terms of (1) global metrics, (2) components and cluster analysis, (3) centrality, and (4) PageRank and AuthorRank. The results of these analyses depict a well-developed and influential scientific collaboration structure within both WVU and the regional science research community.
This document presents the basis for the price adjustment mechanisms in a time series IO model. The essentials of the price adjustment and price change propagation algorithms are presented, along with a matrix permutation algorithm that facilitates the implementation of the price adjustment mechanism. The Matlab function is provided.
Regional economic structure is uniquely represented in the input–output matrix of interindustry transactions. Although changes in this matrix representation reflect certain changes in economic structure, there is no consensus on the measurement and interpretation of these changes. This paper assesses the utility of constant causative matrix methods for measuring, for interpreting, and potentially for forecasting structural economic change. The paper concludes with a discussion of special considerations and future research directions.
