A Systematic Review of Key Spatial Econometric Models for Assessing Climate Change Impacts on Agriculture

AMOUZAY, Hassan and El Ghini, Ahmed (2024): A Systematic Review of Key Spatial Econometric Models for Assessing Climate Change Impacts on Agriculture.

Abstract

This paper explores the limitations of traditional econometric models, such as the Ricardian and profit approaches, in accurately quantifying the impacts of climate change on agriculture. While these models offer valuable insights, they often neglect spatial dependencies, heterogeneity, and spillover effects. We argue that spatial econometrics provides a more comprehensive and robust approach to analyzing climate change impacts. By explicitly incorporating spatial relationships between agricultural units, spatial econometric models capture the influence of factors such as proximity to markets, resource sharing, information diffusion, and spatial correlation of climatic variables. We review pioneering studies employing spatial econometric models, including SAR, SEM, SLX, SARAR and SDM, which reveal significant discrepancies between spatial and non-spatial estimations. These studies demonstrate that neglecting spatial dependence can lead to biased estimations and inaccurate predictions of climate change impacts. Moreover, the incorporation of spatial effects often results in smaller marginal effects of climate variables, suggesting that traditional non-spatial models may overestimate negative consequences. This paper contributes to the ongoing research on climate change impacts on agriculture by highlighting the significance of spatial econometrics and emphasizing its potential to inform robust and effective adaptation strategies.

• Item Type: MPRA Paper
• Language: English
• Keywords: Climate change, econometrics approaches, agriculture, adaptation, spatial econometrics.
• Subjects: Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q1 - Agriculture > Q15 - Land Ownership and Tenure ; Land Reform ; Land Use ; Irrigation ; Agriculture and Environment; Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q5 - Environmental Economics > Q51 - Valuation of Environmental Effects; Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q5 - Environmental Economics > Q54 - Climate ; Natural Disasters and Their Management ; Global Warming; R - Urban, Rural, Regional, Real Estate, and Transportation Economics > R1 - General Regional Economics > R12 - Size and Spatial Distributions of Regional Economic Activity

References

Albouy, D., Graf, W., Kellogg, R., and Wolff, H. (2016). Climate amenities, climate change, and american quality of life. Journal of the Association of Environmental and Resource Economists, 3(1):205–246.

Amouzay, H., Chakir, R., Dabo-Niang, S., and El Ghini, A. (2023). Structural changes in temperature and precipitation in MENA countries. Earth Systems and Environment, 7(2):359–380.

Amouzay, H., Chakir, R., Dabo-Niang, S., and El Ghini, A. (2024). Impact of climate change on agriculture in the MENA region: A spatial panel econometric analysis. https: // www. econometricsociety. org/ event_ papers/ download/ 265/ 439/ 1/Impacts_ of_ climat_ change_ on_ MENA_ agriculture_ 23_ 09_ 24. pdf.

Amouzay, H. and El Ghini, A. (2024). Climate variability impact on agricultural production in Morocco: New evidence from a spatial econometric analysis. Article in press.

Anselin, L. (2001a). Spatial econometrics. a companion to theoretical econometrics. Hoboken NJ: Blackwell Publishing Ltd.

Anselin, L. (2001b). Spatial effects in econometric practice in environmental and resource economics. American Journal of Agricultural Economics, 83(3):705–710.

Anselin, L. (2013). Spatial econometrics: methods and models, volume 4. Springer Science & Business Media.

Anselin, L. and Bera, A. K. (1998). Introduction to spatial econometrics. Handbook of applied economic statistics, 237(5).

Anselin, L., Le Gallo, J., and Jayet, H. (2008). Spatial panel econometrics. In The econometrics of panel data, pages 625–660. Springer.

Arbia, G. and Baltagi, B. H. (2008). Spatial econometrics: Methods and applications. Springer Science & Business Media.

Auffhammer, M. (2018). Quantifying economic damages from climate change. Journal of Economic Perspectives, 32(4):33–52.

Auffhammer, M., Hsiang, S. M., Schlenker, W., and Sobel, A. (2013). Using weather data and climate model output in economic analyses of climate change. Review of Environmental Economics and Policy. 22

Baylis, K., Paulson, N. D., and Piras, G. (2011). Spatial approaches to panel data in agricultural economics: a climate change application. Journal of Agricultural and Applied Economics, 43(3):325–338.

Blanc, E. and Reilly, J. (2017). Approaches to assessing climate change impacts on agriculture: an overview of the debate. Review of Environmental Economics and Policy, 11(2):247–257.

Carter, C., Cui, X., Ghanem, D., and Mérel, P. (2018). Identifying the economic impacts of climate change on agriculture. Annual Review of Resource Economics, 10:361–380.

Chatzopoulos, T. and Lippert, C. (2015). Adaptation and climate change impacts: a structural ricardian analysis of farm types in germany. Journal of Agricultural Economics, 66(2):537–554.

Chatzopoulos, T. and Lippert, C. (2016). Endogenous farm-type selection, endogenous irrigation, and spatial effects in ricardian models of climate change. European Review of Agricultural Economics, 43(2):217–235.

Chen, S., Chen, X., and Xu, J. (2016). Impacts of climate change on agriculture: Evidence from china. Journal of Environmental Economics and Management, 76:105–124.

Cline, W. R. (1996). The impact of global warming of agriculture: comment. The American Economic Review, 86(5):1309–1311.

Conley, T. G. (1999). Gmm estimation with cross sectional dependence. Journal of econometrics, 92(1):1–45.

Darwin, R. (1999). The impact of global warming on agriculture: A ricardian analysis: Comment. American Economic Review, 89(4):1049–1052.

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

Druckenmiller, H. and Hsiang, S. (2018). Accounting for unobservable heterogeneity in cross section using spatial first differences. Technical report, National Bureau of Economic Research.

Elhorst, J. P. (2003). Specification and estimation of spatial panel data models. International regional science review, 26(3):244–268.

Elhorst, J. P. (2010). Applied spatial econometrics: raising the bar. Spatial economic analysis, 5(1):9–28.

Elhorst, J. P. (2014). Spatial econometrics from cross-sectional data to spatial panels. Springer.

Elhorst, P., Fisher, M., and Getis, A. (2010). Spatial panel data models. handbook of applied spatial analysis: Soft-ware tools, methods and applications.

Emediegwu, L. E., Wossink, A., and Hall, A. (2022). The impacts of climate change on agriculture in sub-saharan africa: a spatial panel data approach. World Development, 158:105967.

Le Gallo, J. (2002). Econométrie spatiale: l’autocorrélation spatiale dans les modèles de régression linéaire. Economie prevision, 155(4):139–157.

LeSage, J. and Pace, R. K. (2009). Introduction to spatial econometrics. Chapman and Hall/CRC.

Mendelsohn, R., Nordhaus, W., and Shaw, D. (1996). Climate impacts on aggregate farm value: accounting for adaptation. Agricultural and Forest Meteorology, 80(1):55–66.

Mendelsohn, R., Nordhaus, W. D., and Shaw, D. (1994). The impact of global warming on agriculture: a ricardian analysis. The American economic review, pages 753–771.

Mendelsohn, R. O. and Dinar, A. (2009). Climate change and agriculture: an economic analysis of global impacts, adaptation and distributional effects. Edward Elgar Publishing.

Mendelsohn, R. O. and Massetti, E. (2017). The use of cross-sectional analysis to measure climate impacts on agriculture: theory and evidence. Review of Environmental Economics and Policy.

Ortiz-Bobea, A. (2021). Climate, agriculture and food. arXiv preprint arXiv:2105.12044.

Ortiz-Bobea, A. and Just, R. E. (2013). Modeling the structure of adaptation in climate change impact assessment. American Journal of Agricultural Economics, 95(2):244–251.

Ricardo, D. (1817). The principles of political economy and taxation.-london: John murray (albemarle-street).

Vaitkeviciute, J., Chakir, R., and Van Passel, S. (2019). Climate variable choice in ricardian studies of european agriculture. Revue économique, 70(3):375–401.

Van Passel, S., Massetti, E., and Mendelsohn, R. (2017). A ricardian analysis of the impact of climate change on european agriculture. Environmental and Resource Economics, 67(4):725–760.

Von Thünen, J. H. (1826). Der isolierte staat in beziehung auf landwirtschaft und nationalökonomie (the isolated state).

Ward, P. S., Florax, R. J., and Flores-Lagunes, A. (2014). Climate change and agricultural productivity in sub-saharan africa: a spatial sample selection model. European Review of Agricultural Economics, 41(2):199–226.

Yun, S. D. and Gramig, B. M. (2022). Spatial panel models of crop yield response to weather: Econometric specification strategies and prediction performance. Journal of Agricultural and Applied Economics, 54(1):53–71.

Zouabi, O. and Peridy, N. (2015). Direct and indirect effects of climate on agriculture: an application of a spatial panel data analysis to tunisia. Climatic change, 133(2):301–320.