Ricardian (hedonic) analyses of the impact of climate change on farmland values typically assume additively separable effects of temperature and precipitation with model estimation being implemented on data aggregated across counties or large regions. We use a large panel of farm-level data to investigate the potential bias induced by such approaches. Consistent with the literature on plant physiology, we observe significant non-linear interaction effects, with more abundant precipitation acting as a mitigating factor for increased heat stress. This interaction disappears when the same data is aggregated in the conventional manner, leading to predictions of climate change impacts which are significantly distorted.
|Number of pages||36|
|Journal||Journal of the Association of Environmental and Resource Economists|
|Publication status||Published - Mar 2015|
- Climate Change
- Ricardian Analysis
- Aggregation Bias
- Semi-parametric models