Funding institution: European Union – NextGenerationEU.

This project assesses infrastructural and territorial accessibility, addressing data challenges for both ex-ante and ex-post evaluations. It leverages real-time activity data obtained from private entities (e.g., Google, Meta, Telegram, X, LinkedIn) alongside traditional demographic and territorial data. By applying Machine Learning (ML) and Big Data Analytics, the project aims to create innovative indicators for evaluating infrastructure accessibility. In alignment with recent economic literature showcasing ML’s potential in predicting socio-economic outcomes, the project contributes to predictive models in infrastructure accessibility using real-time and historical data. ML techniques investigate determinants and incorporate user feedback from social networks. This interdisciplinary initiative engages specialists in Digital Methods, Big Data Analytics, Machine Learning, Text Mining, and Impact Evaluations, fostering collaboration across diverse fields. This innovative approach ensures the development of indicators for a thorough and timely assessment of infrastructure accessibility policies. The project introduces innovative accessibility indicators at the national level in Italy, delivering specific outcomes at a more granular territorial level to enhance overall value. These results will be communicated through interactive maps, providing insights for policymakers, practitioners, and citizens.

Funding institution: Italian Ministry of University and Research, National Interest Research Projects (PRIN 2022).

This research project aims to evaluate the performances of the Italian regional healthcare system along the dimensions of efficiency and equity following its evolution over the last twenty years. 
The analysis will combine empirical and theoretical approaches and will focus on three key aspects: 
1) The evolution of hospital efficiency in the light of the reorganization of hospitals in the territory, differentiating between public hospitals and private hospitals and taking into account the regional heterogeneity and different needs of the population at regional level.
2) Equity in access to hospital services through an analysis of patient mobility between regions.
3) The allocation of regional expenditure, analyzing the healthcare spending method currently adopted at the central level, and using an alternative proposal that takes the needs of the population more into account. The project plans to apply state-of-the-art econometric methods and new microeconomics tools to contribute new empirical evidence to the debate on the effectiveness of a decentralized healthcare system.

Funding institution: European Union – NextGenerationEU.

Age-It is a research partnership that aims to represent the reference standard in terms of socio-economic, biomedical, political, and technological solutions to improve the potential for inclusion in the aging processes of societies, making Italy the main scientific hub in the research on aging and a cutting-edge empirical laboratory on the aging process in line with the objectives and priorities of the PNRR 2021-2027. By applying a holistic, interdisciplinary and problem-solving oriented approach, Age-It allows to overcome the fragmentation of different perspectives on aging, creating a new collaboration platform with the involvement of partners, including research and education institutes, assistance and associations of civil society, businesses and industries.

Funding institution: International Center for Tropical Agriculture (CIAT).

Research contracted for scientific support as part of research activities involving the development of a permanent observatory on the crisis climate in Africa (Climate Security Observatory). The long-term goal is to transfer to a dynamic platform that can be consulted by policymakers all the economic research conducted on the climate change issue by the organization.

Funding institution: Italian Ministry of University and Research, National Interest Research Projects (PRIN 2020).

The project addresses the following broad research questions:

i) identification in the literature of frailty indicators for older people which could be used to stratify population;

ii) implementation of the stratification procedures both in terms of health and socio-economic conditions with different administrative health databases, and possibly identifying a standard procedure;

iii) evaluation of the different stratification procedures in terms of adverse health outcomes; iv) socioeconomic characterisation of different strata within different longitudinal studies, and identification of the critical points in health and socio-economic trajectories associated with frail health conditions in old age;

v) disentanglement of the possible mechanisms that lead social and health frailty to unhealthy ageing and finally

vi) implementation of a macro demo-economic model to estimate and project regional populations by demographic, socioeconomic variables and health status.hat lead social and health frailty to unhealthy ageing and finally vi) implementation of a macro demo-economic model to estimate and project regional populations by demographic, socioeconomic variables and health status.

Funding institution: Department for Cohesion Policies at the Italian Presidency of the Council of Ministers.

The purpose of the assignment is to provide strategic support to the Department for Cohesion Policies at the Italian Presidency of the Council of Ministers through the preparation of quantitative analysis of the Cohesion Policies, using statistical information and granular databases for the definition of new policies and related economic and financial planning.

Funding institution: European Commission, Joint Research Center.

Research contracted to assess the possibility of using web-based data to acquire useful information to enrich structural statistics on small and medium-sized enterprises. The main web-based data sources are: Google searches, data from Twitter and Vacancy-Cedefop. These data complement Eurostat data for spatial estimates on the number of enterprises, the number of employees, and value added. The project aims to study possible synergies and complementarities among differentiated sources and methods within official statistics European Union.

Funding institution: International Center for Tropical Agriculture (CIAT).

Research contracted for scientific support in research activities involving analysis of the impact of the COVID-19 pandemic on production systems agriculture, natural resources, biodiversity and local economies in countries belonging to the Southern African Development Community (SADC - Angola, Botswana, Comoros, Democratic Republic of Congo, Eswatini, Lesotho, Madagascar, Malawi, Mauritius, Mozambique, Namibia, Seychelles, South Africa, Tanzania, Zambia and Zimbabwe).

Funding institution: CIMMYT (International Maize and Wheat Improvement Center).

Research entrusted for a data-driven approach to monitoring the generation and dissemination of knowledge by development research organizations and an evaluation of CIMMYT’s activities on climate change.

Funding institution: International Center for Tropical Agriculture (CIAT).

Research commissioned to explore how climate shocks affect food security and conflict risk in different countries and whether and how the World Food Program’s climate-related programming is mitigating conflict risk. Geographic coverage includes the Dry Corridor and Ethiopia.

Funding institution: International Fund for Agricultural Development (IFAD).

As part of the proposal ”Innovation Challenge proposal Leveraging Artificial Intelligence and Big Data for IFAD2.0,” the activity research concerns an analysis of IFAD’s economic management based on the study of the official documents produced by the organization from 1981 to 2020. The economic techniques used to make use of innovative machine learning tools make it possible to identify the main trends and themes of the organization, particularly the share of resources that have been devoted to sustainable development.

Funding institution: CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS).

Research commissioned to study the latent impact of economic policies adopted by the organization. This impact is studied through the use of a set of keywords attributable to the fight against inequality and climate change that are used on the social media and websites of the partners of the projects.

Funding institution: European Union’s Horizon 2020.

The activities are part of the SoBigData.eu project, which has received funding from the European Union’s Horizon 2020 research and innovation program under Grant Agreements Nos. 654024 and 871042, the main purpose of the project is to promote the use of innovative algorithms derived from engineering computer science in economic analysis. It has been developed an algorithm for learning (machine learning) that makes it possible to predict the financial distress of local governments on the basis of financial, institutional, and socio-economic data.

Funding institution: European Union’s Horizon 2020.

The activities are part of the SoBigData.eu project, which received funding from the European Union’s Horizon 2020 research and innovation program under grant agreements Grant Nos. 654024 and 871042. The main purpose of the project is to promote the use of Big Data in economic analysis. Thematic trends were used on a large amount daily Twitter posts to estimate how much the community values the eleven dimensions of well-being in the Better Life Index (OECD).