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Generating Spatial Time Series on Interstate Commodity Flows

In: The Co-evolution of Commodity Flows, Economic Geography, and Emissions

Author

Listed:
  • Kieran Donaghy

    (Cornell University)

  • Arash Beheshtian

    (Altum Group Advisors)

  • Ziye Zhang

    (Princeton University)

  • Benjamin Brown-Steiner

Abstract

This chapter presents and demonstrates a methodology for generating spatial time series on interregional (interstate) inter-industry sales (or commodity flows). The methodology embodies an approach to benchmarking and estimating a dynamic multiregional econometric input–output model (or REIM) with annual data, backing out annual interregional inter-industry sales coefficients from the estimated model, and using the coefficients to generate annual observations on commodity flows. The application of this methodology is demonstrated with a REIM that has been estimated for 13 Midwestern, New England, and North Atlantic states and the rest of the United States and 13 industries using time-series data published by the US Bureau of Economic Analysis and the US Bureau of Labor Statistics. The chapter concludes with brief observations on patterns of change in interregional inter-industry commodity flows and sales coefficients.

Suggested Citation

  • Kieran Donaghy & Arash Beheshtian & Ziye Zhang & Benjamin Brown-Steiner, 2021. "Generating Spatial Time Series on Interstate Commodity Flows," Advances in Spatial Science, in: The Co-evolution of Commodity Flows, Economic Geography, and Emissions, chapter 0, pages 25-46, Springer.
    • Handle: RePEc:spr:adspcp:978-3-030-78555-0_3
    DOI: 10.1007/978-3-030-78555-0_3
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