B5141 - URBAN AND REGIONAL ECONOMICS

Learning outcomes

This course equips students with a comprehensive understanding of economic principles applied to urban and regional contexts. Students will use the notions and tools acquired in previous courses of economics to delve into the complexities of urban and regional economies, exploring topics such as regional development, industrial clustering and agglomeration, inter-regional mobility of workers and, more generally, the tension between the local and global dimension of the modern economic systems. By the end of the course, students will be adept at analyzing the dynamics of cities and regions, evaluating economic challenges, and proposing effective solutions informed by the insights gained in this course.

Course contents

The course provides an introduction to urban and regional economics, with a specific emphasis on cities, urban markets and urban policy. After an introductory discussion on the historical emergence and evolution of cities, the course studies how economic forces shape the location choices of households and firms, the internal structure of cities, and the relationship between cities and their surrounding regions. Core topics include agglomeration economies, industrial clustering, local labour markets, urban amenities, land and housing markets, zoning, urban sprawl, transport, commuting, congestion and local public goods.

Particular attention will be devoted to the economic trade-offs generated by urban density. Cities offer productivity advantages, consumption opportunities and better matching between workers and firms, but they also generate high housing costs, congestion, pollution, inequality and pressure on public services. The course will analyse how these forces affect urban growth, real estate prices, neighbourhood change and the distribution of welfare across residents, firms and local governments.

The course will also examine the relationship between urban economies and tourism. Tourism will be analysed as a source of local demand, employment and amenities, but also as a potential cause of congestion, housing pressure, conflicts over public space and changes in resident welfare. Case studies may include Rimini and other Italian and European tourism cities, with attention to overtourism, short-term rentals and visitor-flow regulation.

Further topics include urban inequality, segregation, neighbourhood effects, crime, urban governance, climate change, coastal risk, smart cities and digital twins. Throughout the course, theoretical models will be combined with academic papers, policy reports and applied case studies, in order to show how urban and regional economics can help interpret real policy problems and design effective interventions in cities and regions.

Readings/Bibliography

The main reference for the course will be selected chapters from:

Kahn, M. E., An Introduction to Urban Economics, University of Southern California, 2024.

Additional readings will be selected from the following books:

Brueckner, J. K., Lectures on Urban Economics, MIT Press.
O’Sullivan, A., Urban Economics, McGraw-Hill.
Glaeser, E., Triumph of the City, Penguin.
Cheshire, P., Nathan, M. and Overman, H., Urban Economics and Urban Policy, Edward Elgar.
Small, K. and Verhoef, E., The Economics of Urban Transportation, Routledge.
Moretti, E., The New Geography of Jobs, Mariner Books.

Selected academic papers and policy-oriented readings will be assigned during the course. They may include contributions on agglomeration economies, housing supply, transport, neighbourhood effects, tourism, short-term rentals, overtourism, climate adaptation, smart cities and digital twins. Additional materials may include reports by international organizations and short policy articles from sources such as VoxEU/CEPR, OECD, World Bank, among others.

Teaching methods

Theoretical and applied lectures, discussion of case studies, and teamwork presentations held by students and discussed in class.

Assessment methods

There will be a midterm exam over the first part of the program and another midterm over the second part. Alternatively, at the end of the course there will be a final exam on the whole program. There will be the possibility to enroll in a teamwork project to earn additional extrapoints.

The maximum possible score is 30 cum laude. The grade is graduated as follows:

<18: failed

18-23: sufficient

24-27: good

28-30: very good

30 cum laude: excellent

AI can be a useful tool to assist individual study with in-depth analysis, summaries, and self-assessment paths. Regarding assessment of learning, a limited, declared, and non-substantial use of AI is permitted for supporting activities (summaries, reformulations). Substantial use for completing parts of the exam is not permitted.

Teaching tools

Materials will be uploaded on the course page on the Moodle platform (http://virtuale.unibo.it)

Office hours

See the website of Giovanni Prarolo