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The Impact of Climate Change on Agriculture : Nonlinear Effects and Aggregation Bias in Ricardian Models of Farm Land Values
Fezzi, Carlo - 2013
Ricardian (hedonic) analyses of the impact of climate change on farmland values typically assume additively separable effects of temperature and precipitation. Model estimation is implemented on data aggregated across counties or large regions. We investigate the potential bias induced by such...
Persistent link: https://www.econbiz.de/10013072687
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The impact of climate change on agriculture : nonlinear effects and aggregation bias in Ricardian models of farm land values
Fezzi, Carlo; Bateman, Ian - 2013
Ricardian (hedonic) analyses of the impact of climate change on farmland values typically assume additively separable effects of temperature and precipitation. Model estimation is implemented on data aggregated across counties or large regions. We investigate the potential bias induced by such...
Persistent link: https://www.econbiz.de/10010203412
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Valuing provisioning ecosystem services in agriculture : the impact of climate change on food production in the United Kingdom
Fezzi, Carlo; Bateman, Ian; Askew, Tom; Munday, Paul; … - In: Environmental & resource economics : the official … 57 (2014) 2, pp. 197-214
Persistent link: https://www.econbiz.de/10010343534
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Non-linear effects and aggregation bias in Ricardian models of climate change
Fezzi, Carlo; Bateman, Ian - 2012
Ricardian models predicting the impact of climate change on agriculture are typically estimated on data aggregated across counties and assuming additively separable effects of temperature and precipitation. We investigate the potential bias induced by such assumptions by using a large panel of...
Persistent link: https://www.econbiz.de/10009546008
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Estimating the range of economic impacts on farms of nutrient leaching reduction policies
Fezzi, Carlo; Rigby, Dan; Bateman, Ian; Hadley, David; … - In: Agricultural economics : the journal of the … 39 (2008) 2, pp. 197-205
Persistent link: https://www.econbiz.de/10003766942
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The Impact of Climate Change on Agriculture: Nonlinear Effects and Aggregation Bias in Ricardian Models of Farm Land Values
Fezzi, Carlo; Bateman, Ian - 2013
Ricardian (hedonic) analyses of the impact of climate change on farmland values typically assume additively separable effects of temperature and precipitation. Model estimation is implemented on data aggregated across counties or large regions. We investigate the potential bias induced by such...
Persistent link: https://www.econbiz.de/10010328685
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Non-linear effects and aggregation bias in Ricardian models of climate change
Fezzi, Carlo; Bateman, Ian - 2012
Ricardian models predicting the impact of climate change on agriculture are typically estimated on data aggregated across counties and assuming additively separable effects of temperature and precipitation. We investigate the potential bias induced by such assumptions by using a large panel of...
Persistent link: https://www.econbiz.de/10011379911
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The Impact of Climate Change on Agriculture: Nonlinear Effects and Aggregation Bias in Ricardian Models of Farm Land Values
Fezzi, Carlo; Bateman, Ian - Fondazione ENI Enrico Mattei (FEEM) - 2013
Ricardian (hedonic) analyses of the impact of climate change on farmland values typically assume additively separable effects of temperature and precipitation. Model estimation is implemented on data aggregated across counties or large regions. We investigate the potential bias induced by such...
Persistent link: https://www.econbiz.de/10010732283
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Valuing Climate Change Effects Upon UK Agricultural GHG Emissions: Spatial Analysis of a Regulating Ecosystem Service
Abson, David; Termansen, Mette; Pascual, Unai; Aslam, Uzma - In: Environmental & Resource Economics 57 (2014) 2, pp. 215-231
This article provides estimates of the physical and economic value of changes in greenhouse gas (GHG) emissions projected to arise from climate change induced shifts in UK agricultural land use during the period 2004–2060. In physical terms, significant regional differences are predicted with...
Persistent link: https://www.econbiz.de/10010862769