Direct and indirect effects of climate on agriculture: an application of a spatial panel data analysis to Tunisia

Abstract

North African countries (NACs) are particularly concerned with climate change because of their geographical position (close to deserts) and their economic dependence on agriculture. We aim to provide additional insight into the impact of climate on agriculture for NACs, through the example of Tunisia. We first use disaggregated data, both at the geographical level (for 24 regions in Tunisia) and at the product level (cereals, olives, citrus fruit, tomatoes, potatoes and palm trees). Second, through spatial panel data analysis, we explore both the time and spatial dimensions of the data. This makes it possible to consider spatial interactions in agricultural production and the role of climate in these spatial spillover effects. Finally, the model not only includes direct climate variables, such as temperature and precipitation, but also indirect climate-related variables such as the stock of water in dams and groundwater. Results show that Tunisian agriculture is strongly dependent on the direct effects of temperature and precipitation for all the products considered at the regional level. The presence of dams and groundwater generally has a positive effect on agricultural production for irrigated crops with interesting spillover effects with neighboring regions. However, this impact is still considerably lessened in the case of detrimental climate conditions (indirect effect). These results raise the question of the sustainability of the growth in agricultural production in Tunisia in the case of significant climate change.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3

Notes

  1. 1.

    Rapport annuel sur les caractéristiques économiques pour chaque gouvernorat 1990–2012

  2. 2.

    http://www.itceq.tn/fr/index.php?rub=281&srub=398

  3. 3.

    Annuaire statistique de la Tunisie 2012, page 121, page 302, http://www.ins.nat.tn/indexfr.php

  4. 4.

    : http://www.onagri.nat.tn/statistiques

  5. 5.

    Annuaire statistique du secteur agricole en Tunisie from 1980 to 2013. (available at the library of Ministère de l'Agriculture.

  6. 6.

    Bulletin statistique de la température et des précipitations (1979-2013).

  7. 7.

    As a sensitivity analysis, other types of spatial weight matrix have been used, namely the second-order contiguity matrix and the inverse distance matrix. Results are similar to those found with the nearest neighbor matrix.

  8. 8.

    Given that the sign and the magnitude of the other variables are unchanged and due to space limitation, parameter estimates corresponding to the P*T effect only are presented in Table 5.

References

  1. Ajewole O, Ogunlade I, Adewumi M (2010) Empirical analysis of agriculture production and climate change: a case study of Nigeria. J Sustain Dev Africa 12(6):275–283

    Google Scholar 

  2. Anselin L (2008) Spatial effects in econometric practice in environmental and resource economics. Am J Agric Econ 83(3):705–10

    Article  Google Scholar 

  3. Ben Zaied Y, Ben Cheikh N (2015) Long-run versus short-run analysis of climate change impacts on agricultural Crops. Environ Model Assess 20(3):259–271

    Article  Google Scholar 

  4. Bsaies A, Mokadem L (2009) L’impact du changement climatique sur l’agriculture et la croissance économique : Cas de la Tunisie In : Energie, changement climatique et développement durable : Le cas des pays Maghrébins, Centre de publication universitaire

  5. Debarsy N, Ertur C (2010) Testing for spatial autocorrelation in a fixed effects panel data model. Reg Sci Urban Econ 40(6):453–470

    Article  Google Scholar 

  6. Deschênes O, Greenstone M (2012) The economic impacts of climate change: evidence from agricultural output and random fluctuations in weather: reply. Am Econ Rev 102(7):3761–3773

    Article  Google Scholar 

  7. Deschênes O, Greenstone M (2007) The economic impacts of climate change: evidence from agricultural output and random fluctuations in weather. Am Econ Rev 97(1):354–385

    Article  Google Scholar 

  8. Elhorst J (2003) Specification and estimation of spatial panel data models. Int Reg Sci Rev 26(3):244–68

    Article  Google Scholar 

  9. Fisher A, Haneman W, Roberts M, Schlenker W (2012) The economic impacts of climate change: evidence from agricultural output and random fluctuations in weather: comment. Am Econ Rev 102(7):3749–60

    Article  Google Scholar 

  10. Giannakopoulos S, Moriondo M, Lesager P, Tin T (2005) Climate change impacts in the Mediterranean resulting from a 2 °C global temperature rise. A report for a WWF

  11. IPCC (2013) Intergovernmental panel on climate change, climate change 2013: the Physical science basis, fifth assessment report (AR5)

  12. Kabubo M, Karanja K (2007) The economic impact change on Kenyan crop agriculture: a Ricardian approach, world bank policy research working paper No.4334

  13. Lee J, Nadolnya D, Hartarska V (2012) Impact of climate change on agricultural in Asian countries: Evidence from panel study”. Southern Agricultural Economics Association Annual Meeting, Birmingham, February 4–7, 2012

    Google Scholar 

  14. Mendelsohn RN, Shaw D (1994) The Impact of global warming on agriculture: a Ricardian analysis. Am Econ Rev 84(4):753–771

    Google Scholar 

  15. Muchena P (1994) Implications of climate change for maize yields in Zimbabwe, In: Implications of Climate Change for International Agriculture: Crop Modeling Study. Nature 367:133–138

    Article  Google Scholar 

  16. Nefzi A, Bouzidi F (2009) Evolution de l’impact économique du changement climatique sur l’agriculture au Maghreb, Cinquième collègue international Hammamet Tunisie : Énergie, changement climatique et développement durable

  17. Péridy N, Brunetto M, Ghoneim M. A (2012) Le coût économique du changement climatique dans les pays MENA: une évaluation quantitative micro-spatiale et une revue des politiques d’adaptation. FEMISE Report, FEM 34–03.

  18. Temesgen T (2007) Measuring the economic impact of climate change on Ethiopian agriculture: a Ricardian approach, World Bank Policy Research Paper No. 4342

  19. Thapa S, Joshi G (2010) A Ricardian analysis of climate change impact on Nepalese agriculture, MPRA (paper no29785)

Download references

Author information

Affiliations

Authors

Corresponding author

Correspondence to Nicolas Peridy.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Annex 1

(DOCX 215 kb)

Annex 2

(DOCX 18.6 kb)

Annex 3

(DOCX 18 kb)

Annex 4

(DOCX 21 kb)

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Zouabi, O., Peridy, N. Direct and indirect effects of climate on agriculture: an application of a spatial panel data analysis to Tunisia. Climatic Change 133, 301–320 (2015). https://doi.org/10.1007/s10584-015-1458-3

Download citation

Keywords

  • Citrus Fruit
  • Neighboring Region
  • Spatial Interaction
  • Palm Tree
  • Irrigate Crop