Abstract
Based on a Ricardian analysis accounting for spatial autocorrelation and relying on recent climate change forecasts at a low spatial scale, this study assesses the impact of climate change on German agriculture. Given the limited availability of data (e.g., the unknown average soil quality at the district level), a spatial error model is used in order to obtain unbiased marginal effects. The Ricardian analysis is performed using data from the 1999 agricultural census along with data from the network of German weather observation stations. The cross-sectional analysis yields an increase of land rent along with both a rising mean temperature and a declining spring precipitation, except for in the Eastern part of the country. The subsequent simulation of local land rent changes under three different IPCC scenarios is done by entering into the estimated regression equations spatially processed data averages for the period between 2011 and 2040 from the regional climate model REMO. The resulting expected benefits arising from climate change are represented in maps containing the 439 German districts; the calculated overall rent increase corresponds to approximately 5–6% of net German agricultural income. However, in the long run, when temperature and precipitation changes will be more severe than those simulated for 2011–2040, income losses for German agriculture cannot be excluded.
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Lippert, C., Krimly, T. & Aurbacher, J. A Ricardian analysis of the impact of climate change on agriculture in Germany. Climatic Change 97, 593–610 (2009). https://doi.org/10.1007/s10584-009-9652-9
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DOI: https://doi.org/10.1007/s10584-009-9652-9