Massimo Riccaboni

• IMT School for Advanced Studies Lucca

Analyzing and predicting innovation in global cities, i.e. cities with a high degree of economic integration into the world economy, can help identify emerging technologies and inform investment decisions that facilitate talent attraction and urban planning. In this context, the contribution of this paper is to analyze the technological complexity...

In high-tech industries, where intellectual property is crucial, the acquisition of intangible assets and tacit knowledge of employees is one of the main motivations for Mergers and Acquisitions (M&As). The takeover wave in the biotechnology industry in the 1990s following the molecular biology revolution is a well-known example of how M&As were us...

The quality of entrepreneurial ecosystems not only enables local startups, but also affects the attraction and supply of non-local founders. We conceptualize entrepreneurial ecosystems as open systems with inflows and outflows of entrepreneurial talent. Beyond individual agency, these talent flows are driven by the quality of the origin and destina...

Despite the negative externalities on the environment and human health, today’s economies still produce excessive carbon dioxide emissions. As a result, governments are trying to shift production and consumption to more sustainable models that reduce the environmental impact of carbon dioxide emissions. The European Union, in particular, has implem...

With the increasing pervasiveness of Information and Communication Technology (ICT) in the fabric of economic activities, the corporate digital divide has become a crucial issue for the assessment of Information Technology (IT) competencies and the digital gap between firms and territories. With little granular data available to measure the phenome...

BACKGROUND Since the spread of the SARS-CoV-2 virus and the lockdown measures went hand-in-hand, it is difficult to distinguish how public opinion reacted to the lockdown measures from the reactions to COVID-19. OBJECTIVE We analyze the causal effect of COVID-19 lockdown policies on sentiment and uncertainty using the Italian lockdown in February...

Background As the spread of the SARS-CoV-2 virus coincided with lockdown measures, it is challenging to distinguish public reactions to lockdowns from responses to COVID-19 itself. Beyond the direct impact on health, lockdowns may have worsened public sentiment toward politics and the economy or even heightened dissatisfaction with health care, imp...

The European Union is facing a major challenge: irregular migration. Our aim in this paper is to shed light on a past EU migration policy through the lens of a rigorous analysis of its impact. To this end, we look at the EU-Turkey statement, an agreement reached in March 2016 to contrast irregular migration from Turkey to the EU. Despite the intent...

Despite the negative externalities on the environment and human health, today’s economies still produce excessive carbon dioxide emissions. As a result, governments are trying to shift production and consumption to more sustainable models that reduce the impact of carbon dioxide emissions. The European Union, in particular, has implemented an innov...

We review models of compositional growth, which were introduced to explain the growth statistics of various quantities ranging from firm sizes to GDP. In these models, entities are decomposed into units that grow independently. Thus, the growth rate of the entity is the addition of the growth rates of the composing units, with possibly heterogeneou...

The literature unanimously agrees that industrial diversification is path dependent: new industries build on the pre-existing capabilities of regions that are partly embodied and reflected in the skills of the region’s workforce. This paper explicitly accounts for regional capabilities as workforce skills to build skill relatedness and skill comple...

This paper examines the impact of the arrival of Airbnb on local consumption amenities in Madrid. We exploit the exogenous variation created by the timing and uneven distribution of Airbnb listings in the city to determine the impact on food and beverage establishments. Using an instrumental variable strategy, we find positive local effects on both...

Plain English Summary Participating in a network agreement is a valuable solution for improving long-term revenues and operating margins. Our analysis shows that network agreements introduced into the Italian legal system in 2009 yield increasing benefits that become larger in the third year of cooperation and stabilize thereafter. Moreover, the in...

In this contribution, we propose machine learning techniques to predict zombie firms. First, we derive the risk of failure by training and testing our algorithms on disclosed financial information and nonrandom missing values of 304,906 firms active in Italy from 2008 to 2017. We then identify the highest financial distress conditional on predictio...

In the recent past, annual CO $$_2$$ 2 emissions at the international level were examined from various perspectives, motivated by rising concerns about pollution and climate change. Nevertheless, to the best of the authors’ knowledge, the problem of dealing with the potential inaccuracy/missingness of such data at the country and economic sector le...

Economic complexity and machine learning have recently become popular approaches for analysing international trade. However, for effective use of machine learning in relation to economic complexity and policymaking, it is important to understand what are the key features for predictions. In this framework, this article addresses the issue of the in...

In this contribution, we propose machine learning techniques to predict zombie firms. First, we derive the risk of failure by training and testing our algorithms on disclosed financial information and non-random missing values of 304,906 firms active in Italy from 2008 to 2017. Then, we spot the highest financial distress conditional on predictions...

This paper investigates the unequal effect of Airbnb on the spatial organisation of economic activity in Madrid, Spain. Using establishment-level data from Madrid City Council and consumer-facing information from this short-term rental company, we find that Airbnb reshapes the urban space by encouraging tourist-oriented businesses, defined as busin...

Social soft skills are crucial for workers to perform their tasks, yet it is hard to train people on them and to readapt their skill set when needed. In the present work, we analyze the possible effects of the COVID-19 pandemic on social soft skills in the context of Italian occupations related to 88 economic sectors and 14 age groups. We leverage...

Eye movement data has been extensively utilized by researchers interested in studying decision-making within the strategic setting of economic games. In this paper, we demonstrate that both deep learning and support vector machine classification methods are able to accurately identify participants’ decision strategies before they commit to action w...

In the recent past, yearly CO\(_2\) emissions at the international level were studied from different points of view, due to their importance with respect to concerns about climate change. Nevertheless, related data (available at country-industry level and referred to the last two decades) often suffer from missingness and unreliability. To the best...

This paper tackles the prediction problem of firm default based on financial accounts and other firm features. We propose to exploit a novel machine-learning algorithm, the Bayesian Additive Regression Tree with Missingness Incorporated in Attributes (BART-MIA), which has been recently shown to outperform many traditional algorithms in analogous pr...

In many countries, β-thalassemia (β-THAL)is not uncommon; however, it qualifies as a rare disease in the USA and in European Union (EU), where thalassemia drugs are eligible for Orphan Drug Designation (ODD). In this review, we evaluate all 28 ODDs for β-THAL granted since 2001 in the USA and the EU: of these, ten have since been discontinued, 12 a...

Technological progress has been recently associated with a crowding-out of cognitive-skill intensive jobs in favour of jobs requiring soft skills, such as ones related to social intelligence, flexibility and creativity. The nature of soft skills makes them hardly replaceable by machine work and among subsets of soft skills, creativity is one of the...

This work applies Matrix Completion (MC) – a class of machine-learning methods commonly used in recommendation systems – to analyze economic complexity. In this paper MC is applied to reconstruct the Revealed Comparative Advantage (RCA) matrix, whose elements express the relative advantage of countries in given classes of products, as evidenced by...

Multi-regional input–output (I/O) matrices provide the networks of within- and cross-country economic relations. In the context of I/O analysis, the methodology adopted by national statistical offices in data collection raises the issue of obtaining reliable data in a timely fashion and it makes the reconstruction of (parts of) the I/O matrices of...

The literature reaches a unanimous agreement that industrial diversification is path-dependent because new industries build on preexisting capabilities of regions that are partly embodied and reflected in the skills of regions’ workforce. This paper explicitly accounts for regional capabilities as workforce skills to build skill relatedness and com...

With the increasing availability of online scholarly databases, publication records can be easily extracted and analysed. Researchers can promptly keep abreast of others’ scientific production and, in principle, can select new collaborators and build new research teams. A critical factor one should consider when contemplating new potential collabor...

The short squeeze of Gamestop (GME) has revealed to the world how retail investors pooling through social media can severely impact financial markets. In this paper, we devise an early warning signal to detect suspicious users' social network activity, which might affect the financial market stability. We apply our approach to the subreddit r/WallS...

In high-tech industries, where intellectual property plays a crucial role, the acquisition of intangible assets and employees' tacit knowledge is an integral part of the motivation for Mergers and Acquisitions (M&As). Following the molecular biology revolution, the wave of takeovers in the biotechnology industry in the Nineties is a well-known exam...

The world’s premier metropolitan areas (‘global cities’) are key nodes in international business networks and function as important international innovation hubs. They are prominent spaces for knowledge exchange and collaboration on innovation yet their specific and changing role in global innovation networks has not received due attention. This ch...

World Input-Output (I/O) matrices provide the networks of within- and cross-country economic relations. In the context of I/O analysis, the methodology adopted by national statistical offices in data collection raises the issue of obtaining reliable data in a timely fashion and it makes the reconstruction of (part of) the I/O matrices of particular...

The short squeeze of Gamestop (GME) has revealed to the world how retail investors pooling through social media can severely impact financial markets. In this paper, we devise an early warning signal to detect suspicious users' social network activity, which might affect the financial market stability. We apply our approach to the subreddit r/WallS...

This paper analyzes the impact of the Italian Start Up Act which entered into force in October 2012. This public policy provides a unique bundle of benefits, such as tax incentives, public loan guarantees, and a more flexible labor law, for firms registered as “innovative startups” in Italy. This legislation has been implemented by the Italian gove...

With pharmaceutical health policy striving for fair and sustainable pricing under increasing budgetary pressures, public stakeholders are more and more willing to be involved in transparent access decision-making related to novel medicines, considered by them to be a societal good. Full net price transparency (NPT) is believed by many to promote pr...

The COVID-19 outbreak has posed an unprecedented challenge to humanity and science. On the one side, public and private incentives have been put in place to promptly allocate resources toward research areas strictly related to the COVID-19 emergency. However, research in many fields not directly related to the pandemic has been displaced. In this p...

This paper investigates the impact of the arrival of Airbnb on the local consumption amenities in Madrid. We exploit the exogenous variation created by the timing and the unequal distribution of Airbnb listings across the urban geography to identify its effects on food and beverage establishments. Using an instrumental variable strategy, we find po...

This paper investigates the impact of the arrival of Airbnb on the local consumption amenities in Madrid. We exploit the exogenous variation created by the timing and the unequal distribution of Airbnb listings across the urban geography to identify its effects on food and beverage establishments. Using an instrumental variable strategy, we find po...

The idea that research investments respond to market rewards is well established in the literature on markets for innovation (Schmookler, 1966; Acemoglu and Linn, 2004; Bryan and Williams, 2021). Empirical evidence tells us that a change in market size, such as the one measured by demographical shifts, is associated with an increase in the number o...

This paper investigates the key driving features of the evolving long-term division of innovative labor in biotechnology and pharmaceuticals from 1981 to 2012. Our main goal is to find if technological trajectories and mechanisms discovered by Orsenigo et al. (Res Policy 30(3): 485–508, 2001) as the main drivers of the structural configuration of t...

We propose an ensemble learning methodology to forecast the future US GDP growth release. Our approach combines a Recurrent Neural Network (RNN) and a Dynamic Factor model accounting for time-variation in the mean with a Generalized Autoregressive Score (DFM-GAS). We show how our approach improves forecasts in the aftermath of the 2008-09 global fi...

This paper starts by observing that many licensing contracts contain explicit organizational arrangements for transferring the licensed technology, involving repeated and close interaction between the licensing partners. We argue that these interactions provide opportunities for the licensor to learn from the licensee. Using data on 1861 licensing...

We present a one principal/two agents model of price-volume agreement, which involves one buyer (the principal) and competition between two manufacturers (the two agents). A theoretical analysis is presented, showing that, in accordance with empirical evidence from the literature on price-volume agreements in the pharmaceutical sector, manufacturer...

This paper analyzes the impact of mobility contraction on employee furlough and excess deaths in Italy during the COVID-19 crisis. Our approach exploits rainfall patterns across Italian administrative regions as a source of exogenous variation in human mobility to pinpoint the causal effect of mobility restrictions on excess deaths and furlough wor...

We investigate the impact of product innovation announcements on firm value using an extensive data set of bio-pharmaceutical products. We find that two main effects shape observed firm value changes: a ‘probability effect’, which depends on how investors perceive the product’s likelihood of success, and a ‘portfolio effect’ that depends on the rel...

This paper investigates how guests' preferences in peer-to-peer (P2P) accommodations changed during the COVID-19 summer season. Specifically, we test the importance of attributes that better allow for preserving the social distancing. To this end, we adopt a semi-parametric hedonic pricing model. We take the city of Madrid as a compelling case stud...

MNCs often engage in international research collaborations with foreign universities through one of their central R&D laboratories (at headquarters or elsewhere) even though they operate a local R&D unit close to that university, and hence forego the benefits of geographic proximity and local collaboration. Drawing on the knowledge-based theory of...

By interpreting exporters' dynamics as a complex learning process, this paper constitutes the first attempt to investigate the effectiveness of different Machine Learning (ML) techniques in predicting firms' trade status. We focus on the probability of Colombian firms surviving in the export market under two different scenarios: a COVID-19 setting...

In this paper,we present an original study on the use of social media data to analyze the structure of the global health networks (GHNs) relative to health organizations targeted to malaria, tuberculosis (TBC) and pneumonia as well as twitter popularity, evaluating the performance of their strategies in response to the arising health threats. We us...

We design an experiment to study investment behavior in different repeated contest settings, varying the uncertainty of the outcomes and the number of participants in contests. We find decreasing over-expenditures and a higher rate of ‘dropout’ in contests with high uncertainty over outcomes (winner-take-all contests), while we detect a quick conve...

This paper contributes to the literature on the relationship between innovation and exports by developing a model that emphasizes the role of product innovation in explaining heterogeneity in export behaviour both across and within firms. The dynamic model assumes that firms invest to maintain and increase the portfolio of products they sell: innov...

In pharmaceutical research, assessing drug candidates' odds of success as they move through clinical research often relies on crude methods based on historical data. However, the rapid progress of machine learning offers a new tool to identify the more promising projects. To evaluate its usefulness, we trained and validated several machine learning...

Proponents describe stem Cell Replacement Therapy and related technologies to be a significant step forward for medicine. However, due to the inherent ethical problems in human Embryonic Stem Cell Research (hESC), it is strictly regulated around the world. The US has passed at the federal and state level, both supportive and restrictive laws over t...

The COVID-19 outbreak has posed an unprecedented challenge to humanity and science. On the one side, public and private incentives have been put in place to promptly allocate resources toward research areas strictly related to the COVID-19 emergency. But on the flip side, research in many fields not directly related to the pandemic has lagged behin...

We analyze data from Twitter to uncover early-warning signals of COVID-19 outbreaks in Europe in the winter season 2019–2020, before the first public announcements of local sources of infection were made. We show evidence that unexpected levels of concerns about cases of pneumonia were raised across a number of European countries. Whistleblowing ca...

Global cities boast higher rates of innovation as measured through patent and scientific production. However, the source of the location advantage of innovation hubs is still debated in the literature, with arguments ranging from localized knowledge spillovers to network effects. Thanks to an extensive data set of individual scientist career paths,...

This paper investigates the effect of P2P accommodations on the local economy of the city of Madrid. We find that the arrival of Airbnb has fostered food and beverage services. We exploit the exogenous variation created by the timing and the unequal distribution of Airbnb listings across the urban geography to identify its effects on the number and...

The merits of greater or lesser net price transparency (NPT) for innovative biopharmaceuticals has been a topic for discussion for many years across business and industry in general. There are clearly very different views on the merits of NPT: the purpose of this analysis is to understand these different perspectives and look for consensus.

With the increasing availability of online scholarly databases, publication records can be easily extracted and analysed. Researchers can promptly keep abreast of others' scientific production and, in principle, can select new collaborators and build new research teams. A critical factor one should consider when contemplating new potential collabor...

An important issue in social network analysis refers to the development of algorithms for estimating parameters of a social network model, using data available from the network itself. This entails solving an optimization problem. In the paper, we propose a new method for parameter estimation in a specific social network model, namely, the so‐calle...

Thanks to the increasing availability of granular, yet high-dimensional, firm level data, machine learning (ML) algorithms have been successfully applied to address multiple research questions related to firm dynamics. Especially supervised learning (SL), the branch of ML dealing with the prediction of labelled outcomes, has been used to better pre...

Thanks to the increasing availability of granular, yet high-dimensional, firm level data, machine learning (ML) algorithms have been successfully applied to address multiple research questions related to firm dynamics. Especially supervised learning (SL), the branch of ML dealing with the prediction of labelled outcomes, has been used to better pre...

We analyze social network data from Twitter to uncover early-warning signals of COVID-19 outbreaks in Europe in the winter season 2020, before the first public announcements of local sources of infection were made. We show evidence that unexpected levels of concerns about cases of pneumonia were raised across a number of European countries. Whistle...

Abstract Global mobility and migration of scientists is an important modern phenomenon with economic and political implications. As scientists become ever more footloose it is important to identify general patterns and regularities at a global scale and how it impacts a country’s scientific output. The analysis of mobility and brain circulation pat...

Abstract Networks of portfolio holdings exemplify how interdependence both between the agents and their assets can be a source of systemic vulnerability. We study a real-world holdings network and compare it with various alternative scenarios from randomization and rebalancing of the original investments. Scenarios generation relies on algorithms t...

In this paper, we test the contribution of foreign management on firms' competitiveness. We use a novel dataset on the careers of 165,084 managers employed by 13,106 companies in the United Kingdom in the period 2009-2017. We find that domestic manufacturing firms become, on average, between 7% and 12% more productive after hiring the first foreign...

We study peer influence of production and consumption of projects in the Scratch community, an online platform developed by MIT Media Lab and targeted for young children, where users collectively learn programming by creating and sharing projects. We investigate if Scratchers are influenced by the popularity of their peers’ projects and their peers...

Cambridge Core - Econophysics and Financial Physics - The Rise and Fall of Business Firms - by S. V. Buldyrev

Abstract In this work we introduce and analyze a new and comprehensive multilayer dataset covering a wide spectrum of international relationships between coutries. We select two cross sections of the dataset corresponding to years 2003 and 2010 with 19 layers and 112 nodes to study the structure and evolution of the network. Country centrality is m...

Corporate groups or networks, which are defined as collections of two or more legally independent firms connected through ownership ties, are prevalent in both developed and developing countries. The separate effects of firm centrality and corporate group size on firm performance have been largely discussed in the literature. However, the effect of...

Network theory proved recently to be useful in the quantification of many properties of financial systems. The analysis of the structure of investment portfolios is a major application since their eventual correlation and overlap impact the actual risk by individual investors. We investigate the bipartite network of US mutual fund portfolios and th...

Global health networks (GHNs) of organizations fighting major health threats represent a useful strategy to respond to the challenge of mobilizing and coordinating different types of health organizations across borders toward a common goal. In this paper we start from the work of [Shiffman16] and we reconstruct the GHNs of malaria, tuberculosis and...

The exact shape of the distribution of city size is subject to considerable scholarly debate, as competing theoretical models yield different implications. The alternative distributions being tested are typically the Pareto and the log-normal, whose finite sample upper tail behavior is very difficult to tell apart. Using data at different levels of...

We analyze peer influence of production and consumption of projects in the Scratch community, an online platform developed by MIT Media Lab, where users collectively learn to program by creating and sharing projects. Scratchers can follow others’ activities on the platform; in the followers network, we investigate if Scratchers’ production populari...

Classifying patents by the technology areas they pertain is important to enable information search and facilitate policy analysis and socio-economic studies. Based on the OECD Triadic Patent Family database, this study constructs a cohort network based on the grouping of IPC subclasses in the same patent families, and a citation network based on ci...

An important issue in social network analysis refers to the development of algorithms for estimating optimal parameters of a social network model, using data available from the network itself. This entails solving an optimization problem. In the paper, we propose a new method for parameters estimation in a specific social network model, namely, the...

This paper investigates the relations between festivals and their institutional settings, and how these relations shape festival management. We analyze institutional logics and work practices in a complex project, Lucca Comics & Games, which is the biggest festival dedicated to fantasy culture in Italy. Our results, based on archival research, medi...

When studying patent data as a way to understand innovation and technological change, the conventional indicators might fall short, and categorizing technologies based on the existing classification systems used by patent authorities could cause inaccuracy and misclassification, as shown in literature. Gao et al. (International Workshop on Complex...

Business cycles modify firms’ incentives to innovate and the direction of innovation. By introducing a new measure of patent unconventionality this paper explores the impact of the business cycle on firms’ technological search strategies. We find that during upturns firms generate inventions characterized by a higher level of technological unconven...

Modern production is increasingly fragmented across countries. To disentangle the world production system at sector level, we use the World Input–Output Database to construct the World Input–Output Network (WION) where the nodes are the individual sectors in different countries and the edges are the transactions between them. In order to explore th...

This paper investigates the relationship between international trade and migration with the specific aim of estimating direct and indirect effect of the latter on cross-border flows of both homogeneous and differentiated goods. Adopting a spatial econometric approach along with a gravity model set-up, we account for the role of ethnic communities i...

The issue of water access and security has been emphasized in the recent policy debate on sustainable development (Sustainable Development Goal No. 6) and adaptation to climate change (CoP21 in Paris, 2015). This study provides new evidence about the Blue Virtual Water Input-Output Network. The main novelty of our approach is the combination of Str...

Network theory proved recently to be useful in the quantification of many properties of financial systems. The analysis of the structure of investment portfolios is a major application since their eventual correlation and overlap impact the actual risk diversification by individual investors. We investigate the bipartite network of US mutual fund p...