Conference Agenda
Overview and details of the sessions of this conference.
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Some information on the session logistics:
If not stated otherwise, the discussant is the following speaker, with the first speaker being the discussant of the last paper. The last speaker of each session is the session chair. (Exception: invited sessions)
Presenters should speak for no more than 20 minutes, and discussants should limit their remarks to no more than 5 minutes. The remaining time should be reserved for audience questions and the presenter’s responses. We suggest following these guidelines also in the (less common) 3-paper sessions in a 2-hour slot, to allow participants to move between sessions. Discussants are encouraged to avoid summarizing the paper. By focusing on a few questions and comments, the discussants can help start a broader discussion with the audience.
Only registered participants can attend this conference. Further information available on the congress website https://www.iseg.ulisboa.pt/en/event/iipf/ .
Venue address: ISEG - Lisbon School of Economics & Management, R. Francesinhas 21, 1200-675 Lisboa, Portugal
Please note that all times are shown in the time zone of the conference. The current conference time is: 17th Sept 2026, 11:38:51am WEST
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A12: Artificial Intelligence and Local Government Performance Location: Room 113 (Francesinhas 1) | |
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Mobility-based gerrymandering: Theory and evidence 1: Simon Fraser University, Canada; 2: University of Torino, Italy, UEH Ho Chi Minh City and CESifo; 3: Aix-Marseille School of Economics, France; 4: University of Torino, Italy This paper models theoretically and tests empirically the hypothesis that the decision about the location of a public bad within a multi-tiered structure of government can be driven by strategic electoral considerations exploiting the heterogeneous migration responses to the location of the public bad by voters of different ideologies - a sort of mobility-based gerrymandering. As long as the average utility loss from living close to the public bad is larger for progressives than it is for conservatives, conservative and progressive central governments will pursue opposite strategies. The former locate the public bad in an electorally tight region to induce exit of progressive voters and gain the region to the conservative party, while the latter attempt to spread progressive voters out of safe and towards electorally tight regions. An application to waste treatment plant locations across Italian municipalities returns evidence in support of the model’s main hypotheses.
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