Reference list
Please note that this is a non-exhaustive reading list useful to engage with the Economic Fitness and Complexity literature. This list is constantly evolving; highlighted core readings will help you in the comprehension of the EFC Summer School lectures and coding labs.
Methods
Tacchella, A., Cristelli, M., Caldarelli, G. et al. (2012). A New Metrics for Countries' Fitness and Products' Complexity. Sci Rep 2, 723.
Hidalgo, C. A., and Hausmann, R. (2009). The building blocks of economic complexity. Proceedings of the national academy of sciences, 106(26), 10570-10575.
Tacchella, A., Mazzilli, D., and Pietronero, L. (2018). A dynamical systems approach to gross domestic product forecasting. Nature Physics, 14(8), 861-865.
Neffke, F., Sbardella, A., Schetter, U., and Tacchella, A. (2024). Economic Complexity Analysis (No. 2430). Utrecht University, Department of Human Geography and Spatial Planning, Group Economic Geography.
Cristelli M, Gabrielli A, Tacchella A, Caldarelli G, Pietronero L (2013) Measuring the Intangibles: A Metrics for the Economic Complexity of Countries and Products. PLoS ONE 8(8): e70726.
Servedio, Vito D. P., Paolo Buttà, Dario Mazzilli, Andrea Tacchella, and Luciano Pietronero (2018). A New and Stable Estimation Method of Country Economic Fitness and Product Complexity Entropy 20, no. 10: 783.
Pietronero, L., Cristelli, M., Gabrielli, A., Mazzilli, D., Pugliese, E., Tacchella, A., and Zaccaria, A. (2017). Economic Complexity:" Buttarla in caciara" vs a constructive approach. arXiv preprint arXiv:1709.05272.
Mazzilli, D., Mariani, M. S., Morone, F., and Patelli, A. (2024). Equivalence between the Fitness-Complexity and the Sinkhorn-Knopp algorithms. Journal of Physics: Complexity, 5(1), 015010.
Balland, P. A., Broekel, T., Diodato, D., Giuliani, E., Hausmann, R., O'Clery, N., and Rigby, D. (2022). Reprint of The new paradigm of economic complexity. Research Policy, 51(8), 104568.
Operti F., Pugliese E., Andrade J. S., Pietronero L, Gabrielli A., (2018). Dynamics in the Fitness - Income plane: Brazil states vs World countries, PLOS ONE, 14(5), e0217034.
Pugliese, E., Zaccaria, A. and Pietronero, L. (2016). On the convergence of the Fitness-Complexity algorithm. Eur. Phys. J. Spec. Top. 225, 1893–1911.
Balassa R. (1965). Trade Liberalisation and "Revealed" Comparative Advantage, 33(2), 99-123.
Economic growth and development
Tacchella, A., Cristelli, M., Caldarelli, G., Gabrielli, A., and Pietronero, L. (2012). A new metrics for countries' fitness and products' complexity. Scientific reports, 2(1), 1-7.
Cristelli, M., Tacchella, A., and Pietronero, L. (2015). The heterogeneous dynamics of economic complexity. PloS one, 10(2), e0117174.
Zaccaria, A., Cristelli, M., Tacchella, A., and Pietronero, L. (2014). How the taxonomy of products drives the economic development of countries. PloS one, 9(12), e113770.
Pugliese, E., Chiarotti, G. L., Zaccaria, A., and Pietronero, L. (2017). Complex economies have a lateral escape from the poverty trap. PloS one, 12(1), e0168540.
Castañeda, G., Pietronero, L., Romero-Padilla, J., and Zaccaria, A. (2022). The complex dynamic of growth: Fitness and the different patterns of economic activity in the medium and long terms. Structural Change and Economic Dynamics, 62, 231-246.
Sbardella, A., Pugliese, E., Zaccaria, A., and Scaramozzino, P. (2018). The role of complex analysis in modelling economic growth. Entropy, 20(11), 883.
Ferrarini, B., and Scaramozzino, P. (2016). Production complexity, adaptability and economic growth. Structural change and economic dynamics, 37, 52-6.
Justin Yifu Lin, New Structural Economics: A Framework for Rethinking Development, The World Bank Research Observer, Volume 26, Issue 2, August 2011,193–221.
Lin, J., Cader, M., and Pietronero, L. (2020). What African Industrial Development Can Learn from East Asian Successes.
Cristelli, M. C. A., Tacchella, A., Cader, M. Z., Roster, K. I., and Pietronero, L. (2017). On the predictability of growth. World Bank Policy Research Working Paper, (8117).
Zaccaria, A., Mishra, S., Cader, M. Z., and Pietronero, L. (2018). Integrating services in the economic fitness approach. World Bank Policy Research Working Paper, (8485).
Roster, K., Harrington, L., and Cader, M. (2018). Country case studies in economic fitness: Mexico and Brazil. Entropy, 20(10), 753.
McNerney, J., Li, Y., Gomez-Lievano, A., and Neffke, F. (2021). Bridging the short-term and long-term dynamics of economic structural change. arXiv preprint arXiv:2110.09673.
Cimoli, M., Dosi, G., and Stiglitz, J. E. (2009). Industrial policy and development: The political economy of capabilities accumulation. Oxford University Press, Oxford.
Relatedness
Hidalgo, C. A., Klinger, B., Barabási, A. L., and Hausmann, R. (2007). The product space conditions the development of nations. Science, 317(5837), 482-487.
Pugliese, E., Cimini, G., Patelli, A., Zaccaria, A., Pietronero, L., and Gabrielli, A. (2019). Unfolding the innovation system for the development of countries: coevolution of Science, Technology and Production. Scientific reports, 9(1), 1-12.
Tacchella, A., Zaccaria, A., Miccheli, M., and Pietronero, L. (2023). Relatedness in the era of machine learning. Chaos, Solitons & Fractals, 176, 114071.
Neffke, F., Henning, M., and Boschma, R. (2011). How Do Regions Diversify over Time? Industry Relatedness and the Development of New Growth Paths in Regions, Economic Geography, 87:3, 237-265.
Neffke, F. and Henning, M. (2013). Skill relatedness and firm diversification. Strat. Mgmt. J., 34: 297-316.
Hidalgo, C. et al. (2018). The Principle of Relatedness. In: Morales, A., Gershenson, C., Braha, D., Minai, A., Bar-Yam, Y. (eds) Unifying Themes in Complex Systems IX. ICCS 2018. Springer Proceedings in Complexity.
Albora, G., Pietronero, L., Tacchella, A., and Zaccaria, A. (2023). Product Progression: a machine learning approach to forecasting industrial upgrading. Scientific Reports 13 (1), 1481.
Aufiero, S., De Marzo, G., Sbardella, A., and Zaccaria, A. (2024). Mapping job fitness and skill coherence into wages: an economic complexity analysis. Scientific Reports, 14(1), 11752.
Diodato, D., Neffke, F., and O’Clery, N. (2018). Why do industries coagglomerate? How Marshallian externalities differ by industry and have evolved over time. Journal of Urban Economics, 106, 1-26.
Sustainability
Caldarola, B., Mazzilli, D., Napolitano, L., Patelli, A., and Sbardella, A. (2024). Economic complexity and the sustainability transition: A review of data, methods, and literature. Journal of Physics: Complexity.
Sbardella, A., Perruchas, F., Napolitano, L., Barbieri, N., and Consoli, D. (2018). Green technology fitness. Entropy, 20(10), 776.
de Cunzo, F., Petri, A., Zaccaria, A., and Sbardella, A. (2022). The trickle down from environmental innovation to productive complexity. Scientific Reports, 12(1), 22141.
Napolitano, L., Sbardella, A., Consoli, D., Barbieri, N., and Perruchas, F. (2022). Green innovation and income inequality: A complex system analysis. Structural Change and Economic Dynamics, 63, 224-240.
Sbardella, et al. (2022). The regional green potential of the European innovation system. Joint Research Centre (Seville site).
Barbieri, N., Consoli, D., Napolitano, L., Perruchas, F., Pugliese, E., and Sbardella, A. (2022). Regional technological capabilities and Green opportunities in Europe. The Journal of Technology Transfer, 1-30.
de Cunzo, F., Consoli, D., Perruchas, F., and Sbardella, A. (2023). Mapping Critical Raw Materials in Green Technologies (No. 2322). Utrecht University, Department of Human Geography and Spatial Planning, Group Economic Geography.
Inequality
Sbardella, A., Pugliese, E., and Pietronero, L. (2017). Economic development and wage inequality: A complex system analysis. PloS one, 12(9), e0182774.
Napolitano, L., Sbardella, A., Consoli, D., Barbieri, N., and Perruchas, F. (2020). Green innovation and income inequality: A complex system analysis.
Caldarola, B., Mazzilli, D., Patelli, A., and Sbardella, A. (2024). Structural Change, Employment, and Inequality in Europe (No. 2024-033). United Nations University-Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
Firms
Coad, A., Mathew, N., and Pugliese, E. (2021). Positioning firms along the capabilities ladder (No. 2021-031). United Nations University-Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
Pugliese, E., Napolitano, L., Zaccaria, A., and Pietronero, L. (2019). Coherent diversification in corporate technological portfolios. PloS one, 14(10), e0223403.
Straccamore, M., Zaccaria, A., and Pietronero, L. (2022). Which will be your firm’s next technology? Comparison between machine learning and network-based algorithms. Journal of Physics: Complexity, 3(3), 035002.
Albora G, Zaccaria A . (2022). Machine Learning to Assess Relatedness: The Advantage of Using Firm-Level Data, Complexity, vol. 2022, Article ID 2095048.
Costa, S., De Santis, S., Dosi, G., Monducci, R., Sbardella, A., and Virgillito, M. E. (2023). From organizational capabilities to corporate performances: at the roots of productivity slowdown. Industrial and Corporate Change, 32(6), 1217-1244.
Laudati, D., Mariani, M. S., Pietronero, L., and Zaccaria, A. (2023). The different structure of economic ecosystems at the scales of companies and countries. Journal of Physics: Complexity, 4(2), 025011.
Dosi, G., Nelson, R. R., and Winter, S. G. (Eds.). (2000). The nature and dynamics of organizational capabilities. Oxford University Press, Oxford.
Patents and Technology
Pugliese, E., Cimini, G., Patelli, A., Zaccaria, A., Pietronero, L., and Gabrielli, A. (2019). Unfolding the innovation system for the development of countries: coevolution of Science, Technology and Production. Scientific reports, 9(1), 1-12.
Napolitano, L., Evangelou, E., Pugliese, E., Zeppini, P., and Room, G. (2018). Technology networks: the autocatalytic origins of innovation. Royal Society open science, 5(6), 172445.
Sbardella, A., Perruchas, F., Napolitano, L., Barbieri, N., andConsoli, D. (2018). Green technology fitness. Entropy, 20(10), 776.
Pugliese, E. and Tübke, A. (2019). Economic complexity to address current challenges in innovation systems: a novel empirical strategy for regional development Industrial R&I – JRC Policy Insights.
Pezzoni, M., Veugelers, R. and Visentin, F. (2022) How fast is this novel technology going to be a hit? Antecedents predicting follow-on inventions. Research Policy, 51(3).
Dosi, G., Pavitt, K., and Soete, L. (1990). The economics of technical change and international trade. LEM Book Series.
Science
Patelli A., Napolitano, L., Cimini, G. and Gabrielli, A. (2023) Geography of science: competitiveness and inequality, Journal of Informetrics, 17(1), 101357.
Cimini, G., Gabrielli, A., and Sylos Labini, F. (2014). The scientific competitiveness of nations. PloS one, 9(12), e113470.
Patelli, A., Napolitano, L., Cimini, G., Pugliese, E., and Gabrielli, A. (2022). The Evolution of Competitiveness across Economic, Innovation and Knowledge production activities. arXiv preprint arXiv:2206.00368.
Patelli, A., Cimini, G., Pugliese, E., and Gabrielli, A. (2017). The scientific influence of nations on global scientific and technological development. Journal of Informetrics, 11(4), 1229-1237.
Corsini, A., Pezzoni, M., and Visentin, F. (2022). What makes a productive Ph. D. student?. Research Policy, 51(10), 104561.
Patsali, S., Pezzoni, M., and Visentin, F. (2021). The impact of research independence on PhD students' careers: Large-scale evidence from France. Maastricht Economic and Social Research Institute on Innovation and Technology (UNU-MERIT).
EU Policy Briefs
Pugliese, E. and Tübke, A. (2019). "Economic complexity to address current challenges in innovation systems: a novel empirical strategy for regional development" Industrial R&I – JRC Policy Insights.
Pugliese, E. and Tacchella, A. (2020). "Economic Complexity for competitiveness and innovation: a novel bottom-up strategy linking global and regional capacities" Industrial R&I – JRC Policy Insights.
Pugliese, E. and Tacchella, A., Economic Complexity Analytics: Country factsheets, EUR 30711 EN, Publications Office of the European Union, Luxembourg, 2021, ISBN 978-92-76-37869-3.
Sbardella, A., Barbieri, N., Consoli, D., Napolitano, L., Perruchas, F. and Pugliese, E. (2022). The regional green potential of the European innovation system, European Commission, JRC124696.
Network Methods, Projections and Null Models
Cimini, G., Squartini, T., Saracco, F., Garlaschelli, D., Gabrielli, A., and Caldarelli, G. (2019). The statistical physics of real-world networks. Nature Reviews Physics, 1(1):58–71.
Saracco, F., Di Clemente, R., Gabrielli, A., and Squartini, T. (2015). Randomizing bipartite networks: the case of the World Trade Web. Scientific Reports, 5:10595.
Saracco, F. Straka, M. J., Di Clemente, R., Gabrielli, A., Caldarelli, G., and Squartini, T.. (2017). Inferring monopartite projections of bipartite networks: an entropy-based approach. New Journal of Physics, 19:053022.
Vallarano, N., Bruno, M., Marchese, E., Trapani, G., Saracco, F., Cimini, G., Zanon, M., and Squartini, T. (2021). Fast and scalable likelihood maximization for exponential random graph models with local constraints. Scientific Reports, 11(1):15227.
Cimini, G., Carra, A., Didomenicantonio, L., and Zaccaria, A. (2022). Meta-validation of bipartite network projections. Communications Physics, 5(1):76.
Bruno, M., Mazzilli, D., Patelli, A., Squartini, T., and Saracco, F. (2023). Inferring comparative advantage via entropy maximization. Journal of Physics: Complexity, 4(4), 045011.
Garlaschelli, D., and Loffredo, M. I. (2018). Maximum likelihood: Extracting unbiased information from complex networks, Phys. Rev. E 78, 015101(R).
Handbooks
Diodato D., Napolitano, L., Pugliese, E., and Tacchella, A. Editor(S), (2024). Handbook of Economic Complexity for Policy. Publications Office Of The European Union, Luxembourg, 2024, Https://Data.Europa.Eu/Doi/10.2760/9006857, JRC138666.
Dosi, G. (2023). The Foundations of Complex Evolving Economies. Part One: Innovation, Organization and Industrial Dynamics. Oxford University Press, Oxford.