Correlation between Upstreamness and Downstreamness in Random Global Value Chains

15 Pages Posted: 19 Feb 2024

See all articles by Pierpaolo Vivo

Pierpaolo Vivo

King’s College London - Faculty of Natural and Mathematical Sciences

Fabio Caccioli

University College London

Francesco Caravelli

Government of the United States of America - Theoretical Division

Silvia Bartolucci

University College London - Department of Computer Science; Imperial College Business School; University College London - Centre for Blockchain Technologies

Abstract

This paper is concerned with upstreamness and downstreamness of industries and countries in global value chains. Upstreamness and downstreamness measure respectively the average distance of an industrial sector from final consumption and from primary inputs, and they are computed from based on the most used global Input-Output tables databases, e.g., the World Input-Output Database (WIOD). Recently, Antr\`as and Chor reported a puzzling and counter-intuitive finding in data from the period 1995-2011, namely that (at country level) upstreamness appears to be positively correlated with downstreamness, with a correlation slope close to $+1$. This effect is stable over time and across countries, and it has been confirmed and validated by later analyses. We first analyze a simple model of random Input/Output tables, and we show that, under minimal and realistic structural assumptions, there is a natural positive correlation emerging between upstreamness and downstreamness of the same industrial sector/country, with correlation slope equal to $+1$. This effect is robust against changes in the randomness of the entries of the I/O table and different aggregation protocols. Secondly, we perform experiments by randomly reshuffling the entries of the empirical I/O table where these puzzling correlations are detected, in such a way that the global structural constraints are preserved. Again, we find that the upstreamness and downstreamness of the same industrial sector/country are positively correlated with slope close to $+1$, even though the random reshuffling has destroyed any underlying economic information about inter-sectorial connections and trends. Our results -- rooted in the Complexity Science approach to economic problems -- strongly suggest that the empirically observed puzzling correlation may rather be a necessary consequence of the few structural constraints (positive entries, and sub-stochasticity) that Input/Output tables and their surrogates must meet.

Keywords: Input-Output, Global Value Chain, Complexity Economics, Leontief, Upstreamness, Downstreamness

Suggested Citation

Vivo, Pierpaolo and Caccioli, Fabio and Caravelli, Francesco and Bartolucci, Silvia, Correlation between Upstreamness and Downstreamness in Random Global Value Chains. Available at SSRN: https://ssrn.com/abstract=4731592 or http://dx.doi.org/10.2139/ssrn.4731592

Pierpaolo Vivo (Contact Author)

King’s College London - Faculty of Natural and Mathematical Sciences ( email )

Strand
London, England WC2R 2LS
United Kingdom

Fabio Caccioli

University College London ( email )

Gower Street
London, WC1E 6BT
United Kingdom

Francesco Caravelli

Government of the United States of America - Theoretical Division ( email )

Los Alamos, NM 87545
United States

Silvia Bartolucci

University College London - Department of Computer Science ( email )

66-72 Gower Street
London, WC1E 6EA
United Kingdom

Imperial College Business School ( email )

South Kensington Campus
Exhibition Road
London SW7 2AZ, SW7 2AZ
United Kingdom

University College London - Centre for Blockchain Technologies ( email )

UCL CBT UCL Computer Science
Malet Place London WC
London, London WC1E 6BT
United Kingdom

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