Market Selection in Global Value Chains
14 October 2021 4:00 pm CEST
Simone Vannuccini, University of Sussex Business School (UK)
Venue
This is an online event via Zoom. Please register using the registration link below.
Description
The presentation is based on a paper co-authored with Philipp Mundt, Uwe Cantner, Hiroyasu Inoue, and Ivan Savin.
Abstract:
The idea that market selection promotes survival and expansion of the “fittest” producers is a key principle underlying theories of competition. Yet, despite its intuitive appeal, the hypothesis that companies with superior productivity also exhibit higher growth lacks empirical support. One reason for this is that companies are not “islands” that produce goods and services in isolation but depend on their suppliers in value chains, implying that excessive growth can also originate in the superior productive performance of these value-chain partners. Neglecting these dependencies in empirical tests of the selection hypothesis leads to measurement errors and may impair the identification of competition for the market.
In this paper, we use data from the World Input-Output Database to capture these global value-chain relationships in an empirical test for market selection, studying competition between country-sectors for a global market share in different economic activities. Compared to the conventional view that focuses on individual productivities, our value-chain perspective on the productivity-growth nexus provides stronger empirical support for market selection. This suggests that the scope of selection reaches beyond the level of individual producers and requires a systemic analysis of production networks. Our findings contribute to a better understanding of the determinants of selection in competitive environments and also represent a novel application of global value-chain data.
The presentation, when available, will be posted online after the event.
Registration link:
https://us06web.zoom.us/webinar/register/WN_Nch_T53NQSKm34AWeBsrvw
Simone Vannuccini is a Lecturer in the Economics of Innovation at the Science Policy Research Unit (SPRU), University of Sussex Business School. At the University of Sussex, he co-convenes the Research Mobilisation Group on Artificial Intelligence, is the Deputy Director of the Future of Work Hub, and the convenor of the SPRU Freeman Seminar series. Simone is also an Associated Fellow of the Graduate College 'The Economics of Innovative Change', Friedrich Schiller University Jena (Germany) and has been Adjunct Professor of Economics of Innovation at the University of Insubria (Italy), where currently is a Faculty Board Member of the PhD Program in Methods and Models for Economic Decisions. He also collaborates with the Center for Studies on Federalism in Turin (Italy). Before joining SPRU in February 2018, Simone has been working as Research Fellow (Post-doc) at the Friedrich Schiller University Jena (Germany), where he also obtained his PhD in a joint programme with the Max Planck Institute of Economics. Simone’s research focuses on microeconomics of innovation and more precisely on the 'regular irregularities' of technical change: in particular, he studies the nature of 'general-purpose technologies' and their impact on industrial dynamics. More recently, he is working on the economics of artificial intelligence, especially the current AI-driven evolution of the semiconductor industry. Further themes of interest are the general-purposeness of AI, the economics of digitalisation and the industrial organisation of multi-sided platforms, and the modelling of industry life-cycles.
Related literature:
Cantner, U., Savin, I., & Vannuccini, S. (2019). Replicator dynamics in value chains: explaining some puzzles of market selection. Industrial and Corporate Change, 28(3), 589-611. Available at: https://academic.oup.com/icc/article-abstract/28/3/589/5270858
Mazzucato, M. (1998). A computational model of economies of scale and market share instability. Structural Change and Economic Dynamics, 9(1), 55-83.
Keywords: competition; country–sector dynamics; input–output analysis; replicator dy- namics; productivity decomposition
JEL classification: C67; D22; L14; L16; L20