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Updated: Jun 1, 2025

Watershed Planning within a Quantitative Scenario Analysis Framework
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Upstreamness and downstreamness in input-output analysis from local and aggregate information.

Silvia Bartolucci1, Fabio Caccioli1,2,3, Francesco Caravelli4

  • 1Department of Computer Science, University College London, 66-72 Gower Street, London, WC1E 6EA, UK.

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|January 21, 2025
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Summary

Estimating supply chain roles is crucial for economic analysis. This study introduces a method using partial data to accurately rank countries and sectors, bypassing complex input-output tables.

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Area of Science:

  • Economics
  • Network Science
  • Econometrics

Background:

  • Accurate ranking of economic sectors and countries within global value chains is vital for risk assessment and growth forecasting.
  • Traditional methods rely on complete input-output (I-O) tables, which are often incomplete or inaccurate, hindering analysis.

Purpose of the Study:

  • To develop a method for accurately estimating the roles of sectors and countries in supply chain networks without requiring full input-output tables.
  • To provide a computationally efficient and analytically tractable framework for economic network analysis.

Main Methods:

  • Employing a rank-1 approximation of input-output tables.
  • Utilizing local and aggregate information, such as total intermediate demand per sector.
  • Analyzing the spectral properties of I-O tables, specifically spectral gaps, to understand approximation accuracy.

Main Results:

  • The proposed method accurately reconstructs upstreamness and downstreamness rankings for countries and sectors using partial data.
  • Empirical testing on the World Input-Output Database validates the performance of the rank-1 approximation.
  • The accuracy of the approximation is linked to the spectral properties of the I-O tables.

Conclusions:

  • A simplified approach using partial economic data can effectively rank entities in global value chains.
  • This method offers a faster, more accessible alternative to traditional input-output analysis for complex economies.
  • The findings highlight the importance of spectral properties in approximating economic network structures.