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Aggregating input–output systems with minimum error

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  • Manfred Lenzen

Abstract

Recent advances in multi-region input-output (IO) table construction have led to large databases becoming available. Some of these databases currently demand too much computer memory or user cognition to be handled effectively outside high-performance environments, especially for applications such as virtual laboratories, computable general equilibrium modelling, linear programming, series expansion, or structural decomposition analysis, thus inhibiting their widespread use by analysts and decision-makers. Aggregation is an obvious solution; but there is a need for structured approaches to aggregating an IO system in a way that does not compromise the ability to effectively answer the research question at hand. In this article, I describe how structural path analysis can be used to realise a computationally inexpensive method for aggregating IO systems whilst minimising aggregation errors. I show that there exists no one-fits-all strategy, but that optimal aggregation depends on the research question at hand.

Suggested Citation

  • Manfred Lenzen, 2019. "Aggregating input–output systems with minimum error," Economic Systems Research, Taylor & Francis Journals, vol. 31(4), pages 594-616, October.
  • Handle: RePEc:taf:ecsysr:v:31:y:2019:i:4:p:594-616
    DOI: 10.1080/09535314.2019.1609911
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