Angelica Sbardella

Dr. Angelica Sbardella


Research Focus & Metrics

Academic Career Length

10Years (2017-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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19 September 2017 in PLOS ONE
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ASAngelica Sbardella
Angelica Sbardella
EPEmanuele Pugliese
Emanuele Pugliese
LPLuciano Pietronero
Luciano Pietronero
Adapting methods from complex system analysis, this paper analyzes the features of the complex relationship between wage inequality and the development and industrialization of a country. Development is understood as a combination of a monetary index, GDP per capita, and a recently introduced measure of a country’s economic complexity: Fitness. Initially the paper looks at wage inequality on a global scale, over the time period 1990–2008. Our empirical results show that globally the movement of wage inequality along with the ongoing industrialization of countries has followed a longitudinally persistent pattern comparable to the one theorized by Kuznets in the fifties: countries with an average level of development suffer the highest levels of wage inequality. Next, the study narrows its focus on wage inequality within the United States. By using data on wages and employment in the approximately 3100 US counties over the time interval 1990–2014, it generalizes the Fitness-Complexity metric for geographic units and industrial sectors, and then investigates wage inequality between NAICS industries. The empirical time and scale dependencies are consistent with a relation between wage inequality and development driven by institutional factors comparing countries, and by change in the structural compositions of sectors in a homogeneous institutional environment, such as the counties of the United States.

2 August 2022 in The Journal of Technology Transfer
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NBNicolò Barbieri
Nicolò Barbieri
DCDavide Consoli
Davide Consoli
LNLorenzo Napolitano
Lorenzo Napolitano
FPFrançois Perruchas
François Perruchas
EPEmanuele Pugliese
Emanuele Pugliese
ASAngelica Sbardella
Angelica Sbardella
The goal of the paper is to elaborate an empirical overview of green technological development in European regions. This is a timely pursuit considering the ambitious commitments stipulated in the recent European Green Deal to achieve climate neutrality by 2050. Our analysis is organised in three steps. First, we map the geographical distribution of innovative activities in Europe and profile regions in terms of technological capabilities. Second, we elaborate a metric to identify regions’ green innovation potential. Third, we check whether possessing a comparative advantage in specific, green and non-green, technological domains is associated with a region’s capacity to develop green technologies.

10 October 2018 in Entropy
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ASAngelica Sbardella
Angelica Sbardella
FPFrançois Perruchas
François Perruchas
LNLorenzo Napolitano
Lorenzo Napolitano
NBNicolò Barbieri
Nicolò Barbieri
DCDavide Consoli
Davide Consoli
The present study provides an analysis of empirical regularities in the development of green technology. We use patent data to examine inventions that can be traced to the environment-related catalogue (ENV-Tech) covering technologies in environmental management, water-related adaptation and climate change mitigation. Furthermore, we employ the Economic Fitness-Complexity (EFC) approach to assess their development and geographical distribution across countries between 1970 and 2010. This allows us to identify three typologies of countries: leaders, laggards and catch-up. While, as expected, there is a direct relationship between GDP per capita and invention capacity, we also document the remarkable growth of East Asia countries that started from the periphery and rapidly established themselves as key actors. This geographical pattern coincides with higher integration across domains so that, while the relative development of individual areas may have peaked, there is now demand for greater interoperability across green technologies.

1 June 2024 in Journal of Physics: Complexity
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BCBernardo Caldarola
Bernardo Caldarola
DMDario Mazzilli
Dario Mazzilli
LNLorenzo Napolitano
Lorenzo Napolitano
APAurelio Patelli
Aurelio Patelli
ASAngelica Sbardella
Angelica Sbardella
Economic Complexity (EC) methods have gained increasing popularity across fields and disciplines. In particular, the EC toolbox has proved particularly promising in the study of complex and interrelated phenomena, such as the transition towards a more sustainable economy. Using the EC approach, scholars have been investigating the relationship between EC and sustainability, and identifying the distinguishing characteristics of green activities and to assess the readiness of productive and technological structures for the sustainability transition. This article proposes to review and summarize the data, methods, and empirical literature that are relevant to the study of the sustainability transition from an EC perspective. We review three distinct but connected blocks of literature on EC and environmental sustainability. First, we survey the evidence linking measures of EC to indicators related to environmental sustainability. Second, we review articles that strive to assess the green competitiveness of productive systems. Third, we examine evidence on green technological development and its connection to non-green knowledge bases. Finally, we summarize the findings for each block, while identifying criticalities and avenues for further research in this recent and growing body of empirical literature.

16 November 2018 in Entropy
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ASAngelica Sbardella
Angelica Sbardella
EPEmanuele Pugliese
Emanuele Pugliese
AZAndrea Zaccaria
Andrea Zaccaria
PSPasquale Scaramozzino
Pasquale Scaramozzino
Development and growth are complex and tumultuous processes. Modern economic growth theories identify some key determinants of economic growth. However, the relative importance of the determinants remains unknown, and additional variables may help clarify the directions and dimensions of the interactions. The novel stream of literature on economic complexity goes beyond aggregate measures of productive inputs and considers instead a more granular and structural view of the productive possibilities of countries, i.e., their capabilities. Different endowments of capabilities are crucial ingredients in explaining differences in economic performances. In this paper we employ economic fitness, a measure of productive capabilities obtained through complex network techniques. Focusing on the combined roles of fitness and some more traditional drivers of growth—GDP per capita, capital intensity, employment ratio, life expectancy, human capital and total factor productivity—we build a bridge between economic growth theories and the economic complexity literature. Our findings show that fitness plays a crucial role in fostering economic growth and, when it is included in the analysis, can be either complementary to traditional drivers of growth or can completely overshadow them. Notably, for the most complex countries, which have the most diversified export baskets and the largest endowments of capabilities, fitness is complementary to the chosen growth determinants in enhancing economic growth. The empirical findings are in agreement with neoclassical and endogenous growth theories. By contrast, for countries with intermediate and low capability levels, fitness emerges as the key growth driver. This suggests that economic models should account for capabilities; in fact, describing the technological possibilities of countries solely in terms of their production functions may lead to a misinterpretation of the roles of factors.

17 November 2022 in Journal of Evolutionary Economics
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ACA. Cetrulo
A. Cetrulo
ASAngelica Sbardella
Angelica Sbardella
MVM. E. Virgillito
M. E. Virgillito
This paper analyses medium-term labour market trends from 1983 to 2018 in Italy relying on the “Rilevazione dei contratti di lavoro” from INPS archive which provides information on average salaries by professional category, age, gender, and geographical origin. Within an overall pattern of exacerbated wage inequalities, documented by means of different indicators, the empirical analysis highlights how thewithin-component of the wage variation prevails in the gender, age and geographical dimensions. By contrast, thebetween-component in terms of professional categories (trainees, blue-collar jobs, white-collar jobs, middle managers, executives) is the only between-variation attribute to prevail, corroborating the role played by a reduced class schema, excluding capitalists and the self-employed, in explaining wage inequality. Regression-based inequality estimations confirm the role played by managerial remuneration, the contradictory located class, in driving divergent patterns. Stratification of wage losses is recorded to be largely concentrated among blue-collar professional categories, women, youth, and in Southern regions.