Conference Agenda
Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).
Please note that all times are shown in the time zone of the conference. The current conference time is: 24th Aug 2026, 01:53:15am WEST
External resources will be made available 30 min before a session starts. You may have to reload the page to access the resources.
|
Daily Overview |
| Session | |
|
Climate Change Adaptation: Food and Agriculture 2 Location: B003 Session Chair: Liyuan Zhang, Texas A&M University | |
    | |
Red Queen Under Uncertainty: Optimal Climate Adaptation with Information Frictions 1: School of Data Science, Fudan University, Shanghai, 200433, China; 2: Fudan Development Institute, Fudan University, Shanghai, 200433, China; 3: School of Economics, Fudan University, Shanghai, 200433, China; 4: Shanghai Innovation Institute, Shanghai, 200433, China; 5: Institute for Big Data, Fudan University, Shanghai, 200433, China; 6: MOE Laboratory for National Development and Intelligent Governance, Fudan University, Shanghai, 200433, China This paper estimates firm-level climate damages when adaptation is costly, gradual, and latent. We define a Red Queen gap, $g_{ct}=T^{obs}_{ct}-\tau_{ct}$, between realized local climate and the climate target embodied in production. The target is generated by a model in which firms learn about local climate from noisy weather histories and adjust production subject to reconfiguration costs. The framework distinguishes weather shocks, belief updating, target movement, and productivity-relevant mismatch. We estimate the model using county weather histories from 1961--2022 and 4,558,300 Chinese firm-year observations from 2007--2020. In the baseline maximum-temperature construction, firms update beliefs about the climate level, separate trend learning is weakly identified, and target adjustment is slow: the implied error-correction half-life is about 30.5 years. The estimated damage curvature implies a TFP loss of about 1.59% for a one-degree Red Queen gap. The generated gap has more productivity content than raw temperature, Kalman weather surprises, and a 30-year-normal gap in otherwise comparable fixed-effects specifications. Robustness checks and validation exercises using operating margins and heterogeneity patterns support the interpretation that the estimated state captures economically meaningful mismatch. The results show that adaptation can be active while still leaving firms persistently exposed to a moving climate. | |