DaY 4

THu 11 July 2024

9:00 - 9:30

The EC economic rationale I

Lecturer: Bernardo Caldarola 

9:30 - 10:00

The EC economic rationale II

Lecturer: Nanditha Mathew

10:00 - 10:30

The EC economic rationale III

Lecturer: Emanuele Pugliese

Break 10:30 - 11:00

11:00 - 12:30

Group work tutorial

Lunch 12:30 - 13:30

13:30 - 14:00

Meso structure in network models of urban industrial diversification

Speaker: Neave O'Clery

This talk will discuss a number of recent papers on the theme of modelling urban and regional industry agglomeration patterns. In particular, we will focus on the role of meso or community structure as encoded in the topology of industry networks or ’spaces', typically ignored in most common models of industry agglomeration dynamics. Using data for the US and the UK, we show that we can delineate clusters of industries which share similar capabilities, whether it be skills, knowledge or value chain linkages, and show we can predict industrial diversification dynamics based on a model which captures the presence of localised 'skill basins'. Finally, we derive a suite of methods to compare the modular structure of industry networks across countries, finding consistent structure particularly across northern Europe.  

14:00 - 14:30

Firm-level production networks

Speaker: Francois Lafond 

In this lecture, I will provide an overview of what is known about the full structure of production networks (“supply chains”), and provide a structured agenda toward mapping the global firm-level supply network. After a brief motivation, I will review existing datasets and show what we have learned from looking at “gold standard” datasets based on country-level VAT reporting. Next, I will introduce the field of network reconstruction methods and its current use for supply chain data, focusing on the end-goal for a macroeconomic use case: developing statistically reasonable synthetic populations of firm networks for the world.

Bacilieri, A., Borsos, A., Astudillo-Estevez, P., & Lafond, F. (2023). Firm-level production networks: what do we (really) know?. INET Oxford Working Paper, 2023.

Mungo, L., Brintrup, A., Garlaschelli, D., & Lafond, F. (2024). Reconstructing supply networks. Journal of Physics: Complexity, 5(1), 012001.

Mungo, L., Lafond, F., Astudillo-Estévez, P., & Farmer, J. D. (2023). Reconstructing production networks using machine learning. Journal of Economic Dynamics and Control, 148, 104607.

Pichler, A., Diem, C., Brintrup, A., Lafond, F.,... & Thurner, S. (2023). Building an alliance to map global supply networks. Science, 382(6668), 270-272.

14:30 - 15:00

Positioning firms along the capabilities ladder

Speaker: Nanditha Mathew 

We develop and apply a novel methodology for quantifying the capability development of firms, and putting these capabilities (and hence also the firms) in a hierarchy, that we refer to as their position on the capabilities ladder. Our nestedness algorithm, inspired by biology and network science, defines a capability as complex if it is performed by only a few firms at the upper rungs of the ladder. We analyze balance sheet and innovation data of almost 40’000 Indian firms for the time period 1988-2015, and observe significant nestedness. Lower rungs of the capabilities ladder correspond to basic managerial and production capabilities. Mid-level rungs correspond to internationalization and acquiring absorptive capacity. Higher level rungs are more related to M&A and innovation. ICT capabilities have become more fundamental lower-level rungs on the capabilities ladder in recent years. We find that capability ranking can explain future growth patterns and survival probability of firms, summing up in one number their future potential trajectories.

15:00 - 15:30

Economic complexity and firm performance in the cultural and creative sector: Evidence from Italian provinces

Speaker: Chiara Burlina

Several studies have detected a positive relationship between the spatial dynamics of cultural and creative industries (CCIs) and their social and economic outcomes. In this article, we draw upon the Economic Complexity Index (ECI) as a proxy to capture the social interactive nature that characterises CCIs and the way this affects firm performance. Our assumption is that more complex locations, endowed with different types of more sophisticated production capabilities, allow CCI firms to perform more strongly. This can depend on the higher opportunities of complex knowledge sharing and cross-fertilisation processes among different types of CCI firms or with non-CCI firms. The focus is on Italy, a country with a long-standing historical tradition in culture and creativity. We draw upon an original panel database at firm and province level (for the period 2010–2016) to compute two different ECIs, one for the CCIs and another one for the rest of the economy. Moreover, we analyse the effects these two types of complexity on the performance of firms within sectors with different levels of cultural and commercial value. We find that economic complexity of CCIs but not economic complexity of the rest of the economy matters for CCI firm performance. However, the effect is relatively weak. The same finding applies to all CCI firms, irrespective of their type of sector. Policy implications and directions for future research are discussed. Paper: https://doi.org/10.1177/09697764221125336

Break 15:30 - 16:00

16:00 - 16:30

The impact of skill mismatch on long-run earnings – A complexity approach

Speaker: Ljubica Nedelkoska 

Downsizing and closures of firms are an integral part of the Schumpeterian creative destruction and are often a consequence of technological change, organizational change or the geographic reallocation of industries. These closures have profound impacts on workers. When workers are displaced from their jobs in the course of firm or establishment closures, they typically face large and persistent earnings losses. In this work, we put forward new measures of occupational skill redundancy and skill shortage that are multidimensional, and which capture the mismatch in skill portfolios and skill levels between occupations. We then show that firm closures lead to occupational mismatch, and that skill mismatch exacerbates the long run earnings losses of displaced workers. We study the heterogeneity of these losses and explain what trajectories can minimize such losses. Based on the paper: Neffke, F., Nedelkoska, L., & Wiederhold, S. (2024). Skill mismatch and the costs of job displacement. Research Policy, 53(2), 104933.

16:30 - 18:00

Policy roundtable 

Panellists: Robert Marschinski, Masud Cader, Reinhilde Veugelers
Moderator: Emanuele Pugliese

Free time 18:00 - 20:00

Social dinner 20:00 at Loetje