M. Di Maio, V. Leone Sciabolazza (2023), Conflict exposure and labour market outcomes: Evidence from longitudinal data from the Gaza Strip, Labour Economics, 85, 102439

This paper documents the effect of variations in the individual-level intensity of conflict exposure on various labour market outcomes for Palestinians living in the Gaza Strip. Combining individual-level longitudinal employment data and geolocalised information on conflict-related events, we show that an increase in conflict exposure of the individual, while it does not affect the employment status on average, it has a heterogeneous impact on job transitions depending on the worker being employed in the private or the public sector. We also find that, for those in the private sector, higher conflict exposure reduces the labour income and the number of hours worked. For those in the public sector, the effect of conflict is instead null on both the labour income and the number of hours worked and it is positive on wages. Finally, we provide suggestive evidence that these results are explained by the combination of two mechanisms, namely the conflict-induced change in the health conditions of the workers (which affects the labour supply) and in the level of the local economic activity (which affects the labour demand).


L. Forastiere, D. Del Prete, V. Leone Sciabolazza (2024), Causal Inference on Networks under Continuous Treatment Interference: an application to trade distortions in agricultural markets, Social Networks, 76, 88-111

This paper investigates the case of interference, when a unit’s treatment also affects other units’ outcome. When interference is at work, policy evaluation mostly relies on the use of randomized experiments under cluster interference and binary treatment. Instead, we consider a non-experimental setting under continuous treatment and network interference. In particular, we define spillover effects by specifying the exposure to network treatment as a weighted average of the treatment received by units connected through physical, social or economic interactions. Building on Forastiere et al. (2021), we provide a generalized propensity score-based estimator to estimate both direct and spillover effects of a continuous treatment. Our estimator also allows to consider asymmetric network connections characterized by heterogeneous intensities. To showcase this methodology, we investigate whether and how spillover effects shape the optimal level of policy interventions in agricultural markets. Our results show that, in this context, neglecting interference may underestimate the degree of policy effectiveness.

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M. Di Maio, F. Fasani, V. Leone Sciabolazza, V. Molini (2023), Facing Displacement and a Global Pandemic: Evidence from a Fragile State, Journal of Demographic Economics, 1-26. Previous version: CEPR discussion paper, DP17104

We use novel survey data to assess the impact of COVID-19 pandemic on the Libyan population. In our sample, 9.5% of respondents report that a household member has been infected by COVID-19, while 24.7% of them have suffered economic damages and 14.6% have experienced negative health effects due to the pandemic. Our analysis focuses on the differences between IDPs and non-displaced individuals, controlling for individuals and household characteristics, geo-localized measures of economic activity and conflict intensity. Displaced individuals do not experience higher incidence of COVID-19 relative to comparable non-displaced individuals, but are about 60% more likely than non-displaced respondents to report negative economic and health impacts caused by the pandemic. Our results suggest that the larger damages suffered by IDPs can be explained by their weaker economic status – which leads to more food insecurity and indebtedness – and by the discrimination they face in accessing health care.


M. Battaglini, V. Leone Sciabolazza, E. Patacchini (2023), Abstentions and Social Networks in Congress, The Journal of Politics, forthcoming. Previous version: NBER Working Paper 27822

We study the extent to which personal connections among legislators influence abstentions in the U.S. Congress. Our analysis is conducted by observing representatives’ abstention for the universe of roll call votes held on bills in the 109th-113th Congresses. Our results show that a legislator’s propensity to abstain increases when the majority of his or her alumni connections abstains, even after controlling for other well-known predictors of abstention choices and a vast set of fixed effects. We further reveal that a legislator is more prone to abstain than to take sides when the demands from personal connections conflict with those of the legislator’s party.

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M. Di Maio , V. Leone Sciabolazza , V. Molini (2023), Migration in Libya: a spatial network analysis, World Development, 163, 106139. Previous version: World Bank, Policy Research Working Paper 9110

This paper provides the first systematic analysis of migration to, within, and from Libya. The data used in the analysis are from the Displacement Tracking Matrix data set of the International Organization for Migration. The analysis uses this unique source of data, combining several techniques to analyze various dimensions of migration in Libya. First, the paper provides a detailed description of the demographic characteristics and national composition of the migrant populations in Libya. Next, it discusses the determinants of migration flow within Libya. The findings show that migration in Libya can be characterized as forced migration, because conflict intensity is the main determinant of the decision to relocate across provinces. Finally, the paper describes the direction, composition, and evolution of international migration flows passing through Libya and identifies the mechanisms of location selection by migrants within Libya by identifying hotspots and cluster provinces.

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M. Fontana, M. Iori, V. Leone Sciabolazza, D. F. De Souza (2022), The interdisciplinarity dilemma: public versus private interests, Research Policy, 51(7), 104553

Researchers often receive contrasting incentives when conducting their work. On the one hand, an interdisciplinary approach is required to produce scientific advances and access to funding. On the other, academic scholarships and evaluation mechanisms are still organized following the criteria of traditional disciplinary fields. If pursuing interdisciplinary research results in contrasting outcomes, science may face an interdisciplinarity dilemma: should researcher pursue their own private interest to build a reputation? Or should they endeavor towards public interest? How costly in terms of reputation is to choose interdisciplinarity research (IDR) over (more) specialized research?
We answer these questions by exploiting data on 23,926 articles published by 6,105 researchers affiliated with the University of Florida in the period 2008-2013. Through individual fixed-effect, we compare articles of the same scholar to roll out the influence of individual characteristics on the scientific impact of their research.
We find that the diverse dimensions of IDR (Variety, Balance, and Disparity) have a different effect on the reputation of a scholar and on her contribution to societal research. We confirm the existence of trade-off between private and public interest. We also point out that the increase of IDR aiming at connecting distant disciplines reduces the usefulness of the resulting knowledge. Results are robust to various specifications and apply to all scholars, regardless of their gender, collaboration behavior, discipline, and performance. These findings pose challenging questions to policymakers.

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M. Battaglini, V. Leone Sciabolazza, E. Patacchini, S. Peng (2022), An R Package for the Estimation of Parameter-Dependent Network Centrality Measures, Journal of Statistical Software, 102(8), 1-30.

The R package econet provides methods for estimating parameter-dependent network centrality measures with linear-in-means models. Both nonlinear least squares and maximum likelihood estimators are implemented. The methods allow for both link and node heterogeneity in network effects, endogenous network formation and the presence of unconnected nodes. The routines also compare the explanatory power of parameter-dependent network centrality measures with those of standard measures of network centrality. Benefits and features of the econet package are illustrated using data from Battaglini and Patacchini (2018), which examine the determinants of US campaign contributions when legislators care about the behavior of other legislators to whom they are socially connected.

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V. Costantini, V. Leone Sciabolazza, E. Paglialunga (2022), Network-driven positive externalities in clean energy technology production: The case of energy efficiency in the EU residential sector, Journal of Technology Transfer, 1-33.

In this paper, we propose a model of national innovation production that formalizes the role of trade partnerships as a channel of knowledge spillovers across countries. The model is used to investigate the energy efficiency technological domain in the European Union (EU) using a panel database covering 19 EU countries for the time span 1990-2015. The model is estimated by using a new empirical strategy which allow to assess the knowledge spillover effects benefiting a country depending on its relative position in the trade network, and correct for common endogeneity concerns. We show that being central in the trade network is a significant determinant of a country’s innovative performance, and that learning-by-exporting is responsible for positive knowledge spillovers across countries. We further reveal that neglecting network effects may significantly reduce our understanding of domestic innovation patterns. Finally, we find that the benefits obtained from knowledge diffusion varies with the domestic absorptive capacity and policy mix composition. Our main implication is that policy mix design informed by network-based case studies could help maximizing the exploitation of positive knowledge spillovers.


V. Leone Sciabolazza, L. Riccetti (2022), Diffusion Delay Centrality: decelerating diffusion processes across networks, Industrial and Corporate Change, 31(4), 980–1003

This paper presents a new measure (the Diffusion Delay Centrality – DDC) to identify agents who should be put into isolation to decelerate a diffusion process spreading throughout a network. We show that DDC assigns a high rank to agents acting as the gatekeepers of the fringe of the network. We also show that the ranking of nodes obtained from the DDC is predicted by the difference in the values of betweenness and eigenvector centrality of network agents. The findings presented might constitute a useful tool to reduce diffusion processes both for policy makers and for corporate managers in the organization of production.


M. Di Maio, V. Leone Sciabolazza (2021), Conflict exposure and health: Evidence from the Gaza Strip, Health Economics, 30(9), 2287-2295

Using individual-level longitudinal data and geo-localized information on conflict-related violent events, we study the impact of conflict on health in the Gaza Strip. Results show that individuals living in localities exposed to more conflict events have a higher probability of suffering from a physical impairment and a chronic disease. The effect is larger for men and older individuals. Two mechanisms contribute to explain why living in conflict-affected area increases the incidence of physical impairment: conflict increases the difficulty to reach health facilities and it decreases individual income. The conflict-induced increase in the probability of having high blood pressure is instead consistent with the development of Post-Traumatic Stress Disorder (PTSD) due to the exposure to conflict-related violent events.