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A Ricardian Analysis of the Impact of Climate Change on European Agriculture

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Abstract

This research estimates the impact of climate on European agriculture using a continental scale Ricardian analysis. Climate, soil, geography and regional socio-economic variables are matched with farm level data from 41,030 farms across Western Europe. We demonstrate that a median quantile regression outperforms OLS given farm level data. The results suggest that European farms are slightly more sensitive to warming than American farms with impacts from \(+\)5 to \(-\)32 % by 2100 depending on the climate scenario. Farms in Southern Europe are predicted to be particularly sensitive, suffering losses of \(-\)5 to \(-\)9 % per degree Celsius.

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Notes

  1. Comparing the ratio of the predicted value using OLS to the actual value in each decile, we found that the log-linear model has a more uniform predictive power compared to the linear model.

  2. FADN is well documented on http://ec.europa.eu/agriculture/rica/index.cfm. and the information about weighting can be found on http://ec.europa.eu/agriculture/rica/methodology3_en.cfm.

  3. The following farms are removed: 2230 duplicates, 654 farms in out or range islands (e.g. Azores, Tenerife, Madeira), 1700 farms with missing spatial information, 3203 farms under glass, 8864 farms with less than 1 hectare land in ownership, 597 farms with low total land value (\(<\)50 €), and 82 outliers (e.g. farms with zero output or with a high output with (nearly) no farmland).

  4. The grid sizes for the three climate models are considerably larger than the NUTS3 regions. The statistical downscaling we rely on generates a smooth prediction across space. It should be understood that these local predictions are plausible but highly uncertain.

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Acknowledgments

The authors would kindly want to express their gratitude towards DG AGRI for access to the Farm Accountancy Data Network (FADN). Steven Van Passel also thanks FWO for funding his research stay at Yale University. Steven Van Passel is also obliged to the OECD for awarding a fellowship of the co-operative research program ‘Biological Resource Management for Sustainable Agricultural Systems’. Emanuele Massetti gratefully acknowledges funding from the Marie Curie IOF Cli-EMA “Climate change impacts—Economic modelling and analysis”.

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Authors and Affiliations

  1. Departement of Engineering Management, Faculty of Applied Economics, University of Antwerp, Prinsstraat 13, 2000, Antwerpen, Belgium

    Steven Van Passel

  2. School of Forestry and Environmental Studies, Yale University, 195 Prospect Street, New Haven, CT, 06511, USA

    Steven Van Passel & Robert Mendelsohn

  3. Faculty of Business Economics, Centre for Environmental Sciences, Hasselt University, Martelarenlaan 42, 3500, Hasselt, Belgium

    Steven Van Passel

  4. Georgia Institute of Technology, 685 Cherry Street, Atlanta, GA, 30332 – 0345, USA

    Emanuele Massetti

Authors
  1. Steven Van Passel
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  2. Emanuele Massetti
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  3. Robert Mendelsohn
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Corresponding author

Correspondence to Steven Van Passel.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (doc 1875 KB)

Appendices

Appendix 1: Overview of the Model Variables and Descriptive Statistics

See Tables 4, 5 and 6.

Table 4 Descriptive statistics all farms
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Table 5 Descriptive statistics of farm types
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Table 6 Overview of the model variables
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Appendix 2: Overview of the Current Climate and Climate Scenarios

See Table 7.

Table 7 Mean temperature and precipitation values of the current climate and climate scenarios used
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Appendix 3: Additional Regression Estimates

See Tables 8 and 9.

Table 8 EU-15 Ricardian quantile regressions
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Table 9 Alternative EU-15 Ricardian regressions
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Van Passel, S., Massetti, E. & Mendelsohn, R. A Ricardian Analysis of the Impact of Climate Change on European Agriculture. Environ Resource Econ 67, 725–760 (2017). https://doi.org/10.1007/s10640-016-0001-y

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