Abstract
The Ricardian model is a widely used approach based on cross-sectional regression analysis to estimate climate change impacts on agricultural productivity. Up until now, researchers have focused on the impacts of gradual changes in temperature and precipitation, even though climate change is known to encompass also changes in the severity and frequency of extreme weather events. This research investigates the impact of heatwaves on European agriculture, additional to the impact of average climate change. Using a dataset of more than 60,000 European farms, the study examines whether adding a measure for heatwaves to the Ricardian model influences its results. We find that heatwaves have a minor impact on agricultural productivity and that this impact is moderated by average temperature. In colder regions, farm productivity increases with the number of heatwave days. For warmer regions, land values decrease with heatwave frequency. Despite the moderating effect, the marginal effect of heatwave frequency, i.e. the percentage change in agricultural land values caused by one more heatwave day per year, is small in comparison to the effect of average temperature increases. Non-marginal effects are found to be relevant, but only in the case of increased heatwave frequency. According to our results, farms are not expected to suffer more from extreme weather than from mean climate change, as was claimed by several previous studies.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Acknowledgements
The authors would like to express their gratitute to the European Commission’s DG Agriculture and Rural Development for access to the Farm Accountancy Data Network (FADN).
References
Alimonti G, Mariani L, Prodi F, & Ricci R A (2022) A critical assessment of extreme events trends in times of global warming. Eur Phys J Plus, 137(1). https://doi.org/10.1140/epjp/s13360-021-02243-9
Annan F, Schlenker W (2015) Federal crop insurance and the disincentive to adapt to extreme heat. Am Econ Rev 105(5):262–266. https://doi.org/10.1257/aer.p20151031
Areas facing natural or specific constraints explained. Retrieved from https://ec.europa.eu/info/food-farming-fisheries/key-policies/common-agricultural-policy/income-support/additional-optional-schemes/anc_en
Bivand R, Keitt T, & Rowlingson B (2021) rgdal: Bindings for the 'Geospatial' Data Abstraction Library. Retrieved from https://CRAN.R-project.org/package=rgdal
Blanc E, Schlenker W (2017) The use of panel models in assessments of climate impacts on agriculture. Rev Environ Econ Pol 11(2):258–279. https://doi.org/10.1093/reep/rex016
Bouwer LM (2019) Observed and projected impacts from extreme weather events: implications for loss and damage. In: Mechler R, Bouwer LM, Schinko T, Surminski S, Linnerooth-Bayer J (eds) Loss and damage from climate change. Springer International Publishing, Cham, pp 63–82
Bozzola M, Massetti E, Mendelsohn R, Capitanio F (2018) A Ricardian analysis of the impact of climate change on Italian agriculture. Eur Rev Agric Econ 45(1):57–79. https://doi.org/10.1093/erae/jbx023
Breshears DD, Fontaine JB, Ruthrof KX, Field J P, Feng X, Burger JR, . . . Hardy G E. S. J. (2021) Underappreciated plant vulnerabilities to heat waves. New Phytologist 231(1) 32-39. https://doi.org/10.1111/nph.17348
Burnham KP, Anderson DR (2004) Multimodel inference: understanding AIC and BIC in model selection. Soc Methods Res 33(2):261–304. https://doi.org/10.1177/0049124104268644
Butler EE, Mueller ND, Huybers P (2018) Peculiarly pleasant weather for US maize. Proc Natl Acad Sci 115(47):11935–11940. https://doi.org/10.1073/pnas.1808035115
Chatzopoulos T, Lippert C (2015) Adaptation and climate change impacts: a structural Ricardian analysis of farm types in Germany. J Agric Econ 66(2):537–554. https://doi.org/10.1111/1477-9552.12098
Conley TG (1999) GMM estimation with cross sectional dependence. J Econ 92(1):1–45. https://doi.org/10.1016/S0304-4076(98)00084-0
Cornes RC, van der Schrier G, van den Besselaar EJM, Jones PD (2018) An ensemble version of the E-OBS temperature and precipitation data sets. J Geophys Res: Atmos 123(17):9391–9409. https://doi.org/10.1029/2017jd028200
Dall’erba S, Domínguez F (2016) The impact of climate change on agriculture in the Southwestern United States: the Ricardian approach revisited. Spat Econ Anal 11(1):46–66. https://doi.org/10.1080/17421772.2015.1076574
Deschênes O, Greenstone M (2007) The economic impacts of climate change: evidence from agricultural output and random fluctuations in weather. Ame Econ Rev 97(1):354–385. https://doi.org/10.1257/aer.97.1.354
Easterling, W. E., Aggarwal, P. K., Batima, P., Brander, K., Lin, E., Howden, S., . . . Tubiello, F. (2007). Food, fibre and forest products. In M. L. Parry, O. F. Canziani, J. P. Palutikof, P. J. van der Linden, & C. E. Hanson (Eds.), Climate change 2007: impacts, adaptation and vulnerability. contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (pp. 273–313). Cambridge, UK: Cambridge University Press.
EEA (2004) Impacts of Europe's changing climate: an indicator-based assessment. Retrieved from Luxembourg: https://www.eea.europa.eu/publications/climate_report_2_2004
European Commission. (n.d.-a). Areas facing natural or specific constraints explained. Retrieved from https://ec.europa.eu/info/food-farming-fisheries/key-policies/common-agricultural-policy/income-support/additional-optionalschemes/anc_en
European Commission. (n.d.-b). Farm accountancy data network. Retrieved from https://ec.europa.eu/info/food-farming-fisheries/farming/facts-and-figures/farms-farming-and-innovation/structures-and-economics/economics/fadn_en
FAO (2021). The impact of disasters and crises on agriculture and food security: 2021. Retrieved from Rome:
Fischer G, Nachtergaele F, Prieler S, van Velthuizen H T, Verelst L, & Wiberg D (2008) Global agro-ecological zones assessment for agriculture (GAEZ 2008).
Fischer E, Schär C (2010) Consistent geographical patterns of changes in high-impact European heatwaves. Nat Geosci 3(6):398–403. https://doi.org/10.1038/ngeo866
Fontana G, Toreti A, Ceglar A, De Sanctis G (2015) Early heat waves over Italy and their impacts on durum wheat yields. Nat Hazards Earth Syst Sci 15(7):1631–1637. https://doi.org/10.5194/nhess-15-1631-2015
Gassert F, Landis M, Luck M, Reig P, & Shiao T (2014) Aqueduct global maps 2.1. Retrieved from: http://www.wri.org/publication/aqueduct-metadata-global
Hijmans R J (2021) raster: Geographic Data Analysis and Modeling. Retrieved from https://CRAN.R-project.org/package=raster
Hooyberghs H, Berckmans J, Lefebre F, & De Ridder K (2019) C3S_422_Lot2 SIS European health: spells extra documentation. Retrieved from http://urban-climate.copernicus-climate.eu/documents/Spells_extra_documentation.pdf
IPCC (2012) Managing the risks of extreme events and disasters to advance climate change adaptation. A special report of Working Groups I and II of the Intergovernmental Panel on Climate Change. Cambridge, UK and New York, USA.
IPCC (2013) Summary for policymakers. Retrieved from Cambridge, UK and New York, NY, USA,:
Kurukulasuriya P, Mendelsohn R (2008) Crop switching as a strategy for adapting to climate change. Afr J Agric Res Econ 02(1):56970
Lobell DB, Hammer GL, McLean G, Messina C, Roberts MJ, Schlenker W (2013) The critical role of extreme heat for maize production in the United States. Nat Clim Chang 3(5):497–501. https://doi.org/10.1038/nclimate1832
Masoomi H, de van Lindt JW (2018) Fatality and injury prediction model for tornadoes. Nat Hazard Rev 19(3):04018009. https://doi.org/10.1061/(ASCE)NH.1527-6996.0000295
Massetti E, Mendelsohn R (2011) Estimating Ricardian models with panel data. Clim Change Econ 2(4):301–319. https://doi.org/10.1142/S2010007811000322
Massetti E, Mendelsohn R (2018) Measuring climate adaptation: methods and evidence. Rev Environ Econ Pol 12(2):324–341. https://doi.org/10.1093/reep/rey007
Massetti E, Mendelsohn R, Chonabayashi S (2016) How well do degree days over the growing season capture the effect of climate on farmland values? Energy Economics 60:144–150. https://doi.org/10.1016/j.eneco.2016.09.004
Massetti E, & Mendelsohn R (2017) Do temperature thresholds threaten American farmland? Fondazione Eni Enrico Mattei. https://doi.org/10.22004/ag.econ.263482
Massetti, E., Van Passel, S., & Apablaza, C. (2018). Is Western European agriculture resilient to high temperatures? CESifo Working Papers. Working Paper. Munich Society for the Promotion of Economic Research. Munich, Germany.
Mendelsohn R, Dinar A (2003) Climate, water, and agriculture. Land Econ 79(3):328–341. https://doi.org/10.2307/3147020
Mendelsohn R, Dinar A (2009) Climate change and agriculture: an economic analysis of global impacts, adaptation and distributional effects, vol 37. Edward Elgar, Cheltenham, UK
Mendelsohn R, Massetti E (2017) The use of cross-sectional analysis to measure climate impacts on agriculture: theory and evidence. Review of Environmental Economics and Policy 11(2):280–298. https://doi.org/10.1093/reep/rex017
Mendelsohn R, Nordhaus WD, Shaw D (1994) The impact of global warming on agriculture: a Ricardian analysis. Am Econ Rev 84(4):753–771
Mendelsohn R, Nordhaus W, Shaw D (1999) The impact of climate variation on US agriculture. In: Neumann JE, Mendelsohn R (eds) The impact of climate change on the United States Economy. Cambridge University Press, Cambridge, pp 55–74
Miller S, Chua K, Coggins J, Mohtadi H (2021) Heat waves, climate change, and economic output. J Eur Econ Assoc 19(5):2658–2694. https://doi.org/10.1093/jeea/jvab009
Moore FC, Lobell DB (2014) Adaptation potential of European agriculture in response to climate change. Nat Clim Chang 4(7):610–614. https://doi.org/10.1038/nclimate2228
NOAA. (1988). Data announcement 88-MGG-02, digital relief of the surface of the Earth. Retrieved from: www.eea.europa.eu/data-and-maps/data/world-digital-elevation-model-etopo5
Oster E (2019) Unobservable selection and coefficient stability: theory and evidence. J Bus Econ Stat 37(2):187–204. https://doi.org/10.1080/07350015.2016.1227711
Parent B, Leclere M, Lacube S, Semenov MA, Welcker C, Martre P, Tardieu F (2018) Maize yields over Europe may increase in spite of climate change, with an appropriate use of the genetic variability of flowering time. Proc Natl Acad Sci 115(42):10642–10647. https://doi.org/10.1073/pnas.1720716115
Perkins SE, Alexander LV (2013) On the measurement of heat waves. J Clim 26(13):4500–4517. https://doi.org/10.1175/jcli-d-12-00383.1
Perkins SE, Alexander LV, & Nairn JR (2012) Increasing frequency, intensity and duration of observed global heatwaves and warm spells. Geophys Res Let 39. https://doi.org/10.1029/2012gl053361
Perkins-Kirkpatrick SE, Gibson PB (2017) Changes in regional heatwave characteristics as a function of increasing global temperature. Scientific Reports (nature Publisher Group) 7:1–12. https://doi.org/10.1038/s41598-017-12520-2
R Core Team. (2020). R: a language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. Retrieved from https://www.R-project.org/
Ramamasy S (2007) Climate variability and change: adaptation to drought in Bangladesh. FAO, Rome
Russo, S., Dosio, A., Graversen, R. G., Sillmann, J., Carrao, H., Dunbar, M. B., . . . Vogt, J. V. (2014). Magnitude of extreme heat waves in present climate and their projection in a warming world. Journal of Geophysical Research: Atmospheres 119(22) 12,500–512,512. https://doi.org/10.1002/2014JD022098
Schlenker W, Hanemann WM, Fisher AC (2006) The impact of global warming on US agriculture: an econometric analysis of optimal growing conditions. Rev Econ Stat 88(1):113–12
Seneviratne SI, Zhang X, Adnan M, Badi W, Dereczynski C, Di Luca A, . . . Zhou B (2021) Weather and climate extreme events in a changing climate. In V. Masson-Delmotte, P. Zhai, A. Pirani, S. L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M. I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J. B. R. Matthews, T. K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, & B. Zhou (Eds.), Climate change 2021: the physical science basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (pp. 1513–1766). Cambridge, United Kingdom and New York, NY, USA: Cambridge University Press.
Seo S, Mendelsohn R (2008) A Ricardian analysis of the impact of climate change on South American farms. Chilean J Agric Res 68(1):69–79
Seo SN, Mendelsohn R (2008) Measuring impacts and adaptations to climate change: a structural Ricardian model of African livestock management. Agric Econ 38(2):151–165. https://doi.org/10.1111/j.1574-0862.2008.00289.x
Seo SN, Mendelsohn R, Dinar A, Hassan R, Kurukulasuriya P (2009) A Ricardian analysis of the distribution of climate change impacts on agriculture across agro-ecological zones in Africa. Environ Resource Econ 43(3):313–332. https://doi.org/10.1007/s10640-009-9270-z
Simolo C, Brunetti M, Maugeri M, Nanni T, & Speranza A (2010) Understanding climate change–induced variations in daily temperature distributions over Italy. Journal of Geophysical Research: Atmospheres, 115(D22110). https://doi.org/10.1029/2010JD014088
Thornton PK, Ericksen PJ, Herrero M, Challinor AJ (2014) Climate variability and vulnerability to climate change: a review. Glob Change Biol 20(11):3313–3328. https://doi.org/10.1111/gcb.12581
Timmins C (2006) Endogenous land use and the Ricardian valuation of climate change. Environ Resource Econ 33(1):119–142. https://doi.org/10.1007/s10640-005-2646-9
Vaitkeviciute J, Chakir R, Van Passel S (2019) Climate variable choice in Ricardian studies of European agriculture. [Climate variable choice in Ricardian studies of European agriculture]. Revue économique 70(3):375–401. https://doi.org/10.3917/reco.703.0375
Van Passel S, Massetti E, Mendelsohn R (2017) A Ricardian analysis of the impact of climate change on European agriculture. Environ Resource Econ 67(4):725–760. https://doi.org/10.1007/s10640-016-0001-y
Vanschoenwinkel J, Mendelsohn R, Van Passel S (2016) Do Western and Eastern Europe have the same agricultural climate response? Taking adaptive capacity into account. Glob Environ Chang 41:74–87. https://doi.org/10.1016/j.gloenvcha.2016.09.003
Vogel MM, Zscheischler J, Fischer EM, Seneviratne SI (2020) Development of future heatwaves for different hazard thresholds. J Geophy Res: Atmos 125(9):e2019JD032070. https://doi.org/10.1029/2019jd032070
White H (1980) A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity. Econometrica 48(4):817–838. https://doi.org/10.2307/1912934
Wieder WR, Boehnert J, Bonan GB, & Langseth M (2014). Regridded harmonized world soil database v1.2. data set. Retrieved from: http://daac.ornl.gov
Wreford A, Adger WN (2010) Adaptation in agriculture: historic effects of heat waves and droughts on UK agriculture. Int J Agric Sustain 8(4):278–289
Funding
This work was supported by the University of Antwerp’s University Research Fund in the form of a doctoral project (ID 42475).
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Competing interests
The authors declare no competing interests.
Additional information
Publisher's note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Information
Below is the link to the electronic supplementary material.
Rights and permissions
Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Fabri, C., Moretti, M. & Van Passel, S. On the (ir)relevance of heatwaves in climate change impacts on European agriculture. Climatic Change 174, 16 (2022). https://doi.org/10.1007/s10584-022-03438-4
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s10584-022-03438-4