Beschreibung:
Ricardian analyses of farmland values have become a cornerstone of the literature valuing the impacts of climate change on agriculture. However, concerns about the lack of a formal econometric strategy to deal with omitted farmland characteristics have raised doubts about the identification of such impacts. This paper proposes an original method for estimating Ricardian models with plot fixed effects to control for confounding omitted variables. Specifically, we use plot-level repeat-sales French data from 1996 to 2019 to investigate how differences in farmland prices between two sale dates are explained by differences in climate conditions. We show that our repeat-Ricardian estimates suggest greater benefits of climate change than those found with standard Ricardian analyses. In particular, our repeat-Ricardian estimates indicate that warmer summers benefit French agriculture, in complete opposition to our pooled Ricardian estimates or to the remainder of the literature. Our repeat-Ricardian results are robust to several specifications, length-definitions of climate and sub-samples. We provide elements suggesting that the repeat-Ricardian analysis is better able to capture crop-switching towards high-value crops requiring particular soil conditions (e.g. vineyards). Our simulations suggest that omitted variable biases in standard Ricardian analyses lead to underestimations of the impacts of IPCC's climate change scenarios by 56%-95%