Knowns, Unknowns, and Impacts

On the occasion of the 50th anniversary of the SRSA, Jackson sums up what we regional scientists do and do not know at this stage in the field’s development

Knowns, Unknowns, and Impacts

Jouke van Dijk opened the most recent issue of Papers in Regional Science with “Long lasting knowledge in Regional Science,” an editorial highlighting the role that the Association”s journal has played in documenting much of the key regional science research since its inception. Publications obviously provide a long lasting chronicle of research in regional science, but I had rather hoped to find in his editorial an actual identification and enumeration of examples of specific long lasting knowledge gleaned from the regional science record. My hopes stemmed from having spent the past year contemplating appropriate content for this Presidential Address on the occasion of our own 50th Anniversary of the Southern Regional Science Association, which itself seemed to be a appropriate time for reflection and contemplation. The choice had narrowed to three related questions. 1. What do we know? 2. What do we want to know? 3. Do we make a difference? I will offer a set of axioms that I believe underlie a wide range of regional science knowledge, identify a set of unknowns that flow from them, and content that for any of what we know to have an impact, to be meaningfully long lasting, its relevance must be actively extended beyond the boundaries of the regional science community. Only then will our knowledge have made a difference. Citing a prominent example of recent national policy directions, I contend that the opportunity to demonstrate regional science relevance has never been greater, and conclude by calling for us to do so

Are Industry Clusters and Diversity Strange Bedfellows?

In this address, I review industry clustering and diversification strategies to compare and contrast their underlying foundations. The lack of a consensus choice of one or the other for regional economic development strategies along with the recognition that in the dynamic process of development these two processes are related leads me to conclude that clusters and diversity need not be such strange bedfellows after all, and that a rational approach to economic development can leverage the strengths of each and offset weaknesses. I follow this discussion by introducing a cluster assessment diversification strategy (CADS) apparatus that can be used to measure existing cluster strength, identify industrial strengths and deficit bottlenecks, and explore the regional consequences of potential cluster diversification strategies

Integrated Modeling Frameworks

This document is intended to clarify the foundations of the IO and CGE analytical frameworks and procedures that underlie the NSF and USDA/NIFA funded research projects. It covers environmental data, life cycle assessment (LCA), input-output models (IO), structural decomposition analysis (SDA), social accounting matrix models (SAMs), and computable general equilibrium modeling (CGE)

Technical Document for Computing Coal Dependent Employment Estimates

This document presents the basis for estimating coal-dependent employment in a reference region, then establishing a weighting factor for each industry that can be used to provide a quantitative estimate of the existing employment or employment change in a county that can be attributed to existing or change in coal employment. The Matlab function is provided. Although coal is the industry of interest in this document, any other industry could be targeted for similar study

Cross-Hauling in Input-Output Tables: Comments on CHARM

This brief note draws further attention to cross-hauling in regional input-output table estimation, and specifically identifies conceptual issues associated with Kronenberg”s CHARM method for adjusting input-output regionalization methods. Despite the shortcomings of the CHARM approach as it now stands, this is a very important line of research. I believe that progress made on the CHARM method is encouraging, and hope that future work will resolve remaining issues

Composite Input-Output Production Functions

This document describes the algorithm used for creating an aggregated linear production function for an industry by weighting subsector production functions. The result can be used as a column in an interindustry (I ×I) coefficients table or in a standard Use table (C × I) depending on the units (C or I) of the input data

Fellows Address: Are Industry Clusters and Diversity Strange Bedfellows?

In this address, I review industry clustering and diversification strategies to compare and contrast their underlying foundations. The lack of consensus choice of one or the other for regional economic development strategies along with the recognition that in the dynamic process of development these two processes are related leads me to conclude that clusters and diversity need not be such strange bedfellows after all, and that a rational approach to economic development can leverage the strengths of each and offset weaknesses. I follow this discussion by introducing a cluster assessment diversification strategy (CADS) apparatus that can be used to measure existing cluster strength, to identify industrial strengths and deficit bottlenecks, and to explore the regional consequences of potential cluster diversification strategie

An Integrated Environmental and Economic Modeling Framework for Technological Transitions

There is an increasing demand for models that address both environment and economy, and that also estimate or forecast the impacts of introducing new and markedly different technologies from those already existing in the systems under study. Because most conventional models are calibrated to recent data characterizing current economic structure and conditions, their standard turn-key operation will need to be replaced by more comprehensive algorithms and procedures designed to explicitly accommodate shifts in technology and economic structure. This paper lays out one viable alternative for integrating environmental and economic modeling frameworks, and focuses specifically on one of the major challenges to this kind of modeling, that of dovetailing life cycle assessment and input-output modeling frameworks