The Department of Economics and Management of the University of Ferrara and the Italian Association of Environmental and Resource Economists (IAERE) are delighted to announce the 10th edition of the IAERE School on “Patent Data Analysis for Environmental and Resource Economics”.

The School will be held on 15-18 September 2026 at Palazzo Bevilacqua Costabili in Ferrara. The programme of the School will consist of four days (Tuesday morning to Friday afternoon) of teaching by prominent academics.

Please notice that the registration to the School is reserved for IAERE Members. Participants who are not yet IAERE Members will be kindly requested to register for IAERE Membership

Aim

Patent data analysis has become one of the most widely used approaches to study technological change, innovation dynamics, knowledge diffusion, and the green and digital transitions. Patent databases provide rich information on inventive activity, technological trajectories, and the behavior of firms, inventors, and institutions. In recent years, the increasing availability of large-scale patent datasets and advances in computational methods have further expanded the use of patent analytics in economics, management, and innovation studies.

The aim of the summer school is twofold. The course intends to introduce the fundamentals of patent analysis, combining theoretical foundations with practical applications based on real-world patent data. Recent methodological developments and applications of patent analytics for the study of innovation, sustainability, and technological change will be presented and discussed.

• Foundations of patents, intellectual property rights, and innovation systems

• Patent databases and data sources (PATSTAT, USPTO, EPO, Lens, Google Patents)

• Patent indicators for measuring innovation, technological specialization, and competitiveness

• Patent classification systems (IPC, CPC) and technology mapping

• Text analysis and natural language processing of patent documents

• Measuring novelty, technological complexity, and knowledge recombination

• Patent citations, knowledge flows, and technology diffusion

• Green, digital, and deep-tech innovation through patent data

• Patent networks and network analysis of inventors, organizations, and technologies

• Machine learning and artificial intelligence applications in patent analytics

• Patent analysis for policy evaluation and technology forecasting

Hands-on sessions using patent data and computational tools for innovation research

Target

Graduate students, PhD candidates, and working professionals from any university, research institute, or other organization (private companies, government agencies, NGOs) with an interest in environmental issues and ability to read and write fluently in English. Advanced undergraduates will also be considered.

Structure

The School will be organized in 12 teaching modules and 4 discussion sessions:

• 9:30-11:00 Teaching module

• 11:00-11:30 Coffee break

• 11:30-13:00 Teaching module

• 13:00-14:30 Light lunch

• 14:30-16:00 Teaching module

• 16:00-17:00 Discussion

Number of Students

The minimum number of students for the activation of the program in person is 15. The maximum number is 30. Participation to School will be in person.