DaY 5

Constructing a genotypic product space

Speaker: Dario Diodato

Economic complexity analysis has shown that one can predict the diversification of countries (or regions) into new activities. This is thanks to an empirical tool known as the product space, which infers the similarity of activities from output patterns. While these methods are underpinned by a theory of capabilities, economic complexity is grounded in outcome-based metrics and remains — using a metaphor from biology — phenotypic in nature. In this paper we show how to conduct economic complexity analysis directly on capabilities, by interpreting input requirements of industries as genetic code. We exploit our framework to empirically (i) build a genotypic product space, (ii) to infer countries’ capabilities, and (iii) measure the capabilities that a country is missing for diversifying into a given industry. We then discuss the many advantages of this framework in terms of understanding the development process and of designing policies. 

The AI impact on the job market: A signal from startups

Speaker: Enrico Fenoaltea

Multi-dimensional canonical economic complexity

Speaker: Bart Verspagen

We propose to use canonical correspondence analysis (CCA) as a way to summarize the main trends in the dynamics of economic growth and development. CCA is a descriptive method that extends the algorithm (non-canonical correspondence analysis) that is widely used for calculating the economic complexity index. Both techniques (CCA and economic complexity) are aimed at reducing the dimensionality of large cross-country datasets on international trade. CCA has the advantage that the correlation between the derived indicator(s) to a set of underlying economic variables (in our case at the country level) is included in the derivation of the summary indicators. This facilitates the use of >1 dimensions to summarize the trade dataset. We illustrate this by relating the summary trade indicators (CCA dimensions) to a set of variables about development and economic growth.

Break 10:30 - 11:00

Measuring Novel Scientific Ideas and their Impact in Publication Text

Speaker: Reinhilde Veugelers

New scientific ideas fuel economic progress, yet their identification and measurement remains challenging. In this paper, we use natural language processing to identify the origin and impact of new scientific ideas in the text of scientific publications. To validate the new techniques and their improvement over traditional metrics based on citations, we first leverage Nobel prize papers that likely pioneered new scientific ideas with a major impact on scientific progress. Second, we use literature review papers that typically summarize existing knowledge rather than pioneer new scientific ideas. Finally, we demonstrate that papers introducing new scientific ideas are more likely to become highly cited by both publications and patents. We provide open access to code and data for all scientific papers up to December 2020.

Structural Change, Employment, and Inequality in Europe: an Economic Complexity Approach

Speaker: Bernardo Caldarola

Structural change consists of industrial diversification towards more productive, knowledge-intensive activities. However, changes in the productive structure bear inherent links with job creation and income distribution. In this paper, we investigate the consequences of structural change – defined in terms of labour shifts towards more complex industries – on employment growth, wage inequality and functional distribution of income. The analysis is conducted for European countries using data on disaggregated industrial employment shares over the period 2010 -- 2018. First, we identify patterns of industrial specialisation by validating a country-industry industrial employment matrix using a bipartite weighted configuration model (BiWCM). Secondly, we introduce a country-level measure of labour-weighted Fitness, which can be decomposed in such a way as to isolate a component that identifies the movement of labour towards more complex industries – the structural change component. Thirdly, we link structural change to i) employment growth, ii) wage inequality, and iii) labour share of the economy. The results indicate that our structural change measure is associated negatively with employment growth. However, it is also associated with lower income inequality. As countries move to more complex industries, they drop the least complex ones, so the (low-paid) jobs in the least complex sectors disappear,. Finally, structural change predicts a higher labour ratio of the economy; however, this is likely to be due to the increase in salaries rather than by job creation. 

Technological trajectories: Antecedents predicting their diffusion over time and space 

Speaker: Fabiana Visentin

Despite scholars’ high interest in identifying inventions that have a big impact, little attention has been devoted to investigating what drives how (fast) novel technologies embodied in these inventions are re-used in subsequent inventions. We overcome this limitation by empirically identifying novel technologies, mapping their reuse trajectories, and examining the characteristics of the novel technologies affecting trajectories’ shape. Using patent data, we identify on a large scale novel technologies as new combinations of existing technological components. The first invention using the new combination marks the origin of the trajectory, while all the subsequent inventions re-using the same new combination shape the technological trajectory. In our study sample, we identify 10,782 technological trajectories. For each of these trajectories, we identify its take off time and its maximum technological impact, as defined by its maximum number of follow-on inventions. We find that an S-shaped curve provides high goodness of fit for our trajectories, but that there is substantial heterogeneity in take off time and maximum technological impact. In searching for the antecedent characteristics of the novel technologies shaping their trajectories, we find that complex novel technologies resulting from combining dissimilar technological components with strong science-based content are associated with trajectories showing a long take off time but with a high technological impact. In contrast, combining similar components that are familiar to inventors, results in a short take off time but a low technological impact. 

Lunch 12:30 - 13:30

Optimal Transport in Economic Complexity

Speaker: Dario Mazzilli

Inspired by the recent finding that links the Sinkhorn algorithm to the Fitness & Complexity algorithm, we explore the intriguing relationship between the robust theory of Optimal Transport and Economic Complexity. Our study demonstrates how to conceptualize an optimization process within the realm of international trade. This approach potentially establishes a 'microfoundation' for the Fitness indicator and enables its extension, such as within a tripartite network involving exporters, importers, and products.

From the technology space to the innovation space: a cross-relatedness framework

Speaker: Carolina Castaldi

Research inspired by the ‘principle of relatedness’  is recently moving towards a multidimensional take, whereby relatedness is not only studied in one ‘space’ at a time, but rather across multiple spaces of knowledge and economic activities.In this talk I will discuss my own research efforts towards defining relatedness in the innovation space, which I consider as spanning not only technology but also market activities. The notion of an innovation space allows to take into account more phases and types of innovation that firms or regions can specialize in. At the same time, it acknowledges complementarities between different innovation activities, through the idea of ‘cross-relatedness’.I will cover the framework proposed in the paper Castaldi and Drivas (2023) in Economic Geography and ongoing work where I apply similar ideas to understand the emergence of green innovation specializations across European regions.

The Changing Global Division of Labor in Software: Emergence and Diffusion of New Programming Tasks across IT Hubs

Speaker: Frank Neffke

With the advent of new industries, we often see the emergence of new jobs and job tasks. Industry life cycle perspectives predict that these activities first emerge in a limited number of cities to then diffuse to other locations as tasks and job descriptions become more standardized. However, the limited resolution of current task and skill datasets complicates studying this process. Here, we focus on a particularly important new industry: software development. The software industry is economically important, quickly changing, and has a very pronounced spatial concentration in a small number of global IT hubs. We propose a methodology to study whether places specialize in software tasks in predictable ways and how software tasks diffuse across cities. We find that having related tasks in a city is highly predictive of future entry to a new task. At the same time, we observe the rapid diffusion and adoption of multiple new tasks, including tasks related to deep learning, graph databases, blockchain, dev-ops, and cloud computing technologies. These new tasks often emerge in established centers of the software industry, most prominently Silicon Valley, and then diffuse relatively unhindered by geographical distance. 

Overview of EFC group

Speaker: Emanuele Pugliese

This talk will present an in-depth overview of the research lines pursued by the EFC group, highlighting the frontier applications of the Economic Fitness and Complexity framework introduced at the school. Particular focus will be given to areas such as the integration of the EFC approach and information on Global Value Chains (GVCs), labour-market based complexity indicators and the impact of AI on jobs, the dynamics of multi-scale and multi-dimensional fitness and complexity indicators, the evaluation of firm-level complexity indicators, different applications linked to socio-economic sustainability, and the interplay between complexity, employment, and inequality.

Break 15:30 - 16:00