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, 11:36:51am WEST
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Daily Overview |
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B12: Fertility, Urban Health, and Work-Life Balance Location: Room 113 (Francesinhas 1) | |
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Optimal City Size with Endogenous Fertility 1: University of Potsdam, Germany; 2: Kindai University, Japan; 3: University of Tokyo, Japan We build a dynamic quantitative spatial model with mobile households and endogenous fertility to analyze the efficiency of equilibrium fertility choices and city size distribution. City size affects the economy through three channels: a larger city population increases productivity, affects amenity levels (positively or negatively), and increases the cost of child care. We find that the competitive equilibrium is inefficient due to the intergenerational externality and excessively large cities have excessively low fertility rates. We calibrate our model to German county data and find that the resulting welfare losses amount to 14% of income.
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