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The effect of weather conditions on fertilizer applications: A spatial dynamic panel data analysis

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  • Anna Gloria Billé
  • Marco Rogna

Abstract

Given the extreme dependence of agriculture on weather conditions, this paper analyses the effect of climatic variations on this economic sector, by considering both a huge data set and a flexible spatiotemporal model specification. In particular, we study the response of N‐fertilizer application to abnormal weather conditions, while accounting for other relevant control variables. The data set consists of gridded data spanning over 21 years (1993–2013), while the methodological strategy makes use of a spatial dynamic panel data (SDPD) model that accounts for both space and time fixed effects, besides dealing with both space and time dependences. Time‐invariant short‐ and long‐term effects, as well as time‐varying marginal effects are also properly defined, revealing interesting results on the impact of both GDP and weather conditions on fertilizer utilizations. The analysis considers four macroregions—Europe, South America, Southeast Asia and Africa—to allow for comparisons among different socio‐economic societies. In addition to finding both spatial (in the form of knowledge spillover effects) and temporal dependences as well as a good support for the existence of an environmental Kuznets curve for fertilizer application, the paper shows peculiar responses of N‐fertilization to deviations from normal weather conditions of moisture for each selected region, calling for ad hoc policy interventions.

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  • Anna Gloria Billé & Marco Rogna, 2022. "The effect of weather conditions on fertilizer applications: A spatial dynamic panel data analysis," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(1), pages 3-36, January.
    • Handle: RePEc:bla:jorssa:v:185:y:2022:i:1:p:3-36
    DOI: 10.1111/rssa.12709
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    1. Yu, Jihai & de Jong, Robert & Lee, Lung-fei, 2008. "Quasi-maximum likelihood estimators for spatial dynamic panel data with fixed effects when both n and T are large," Journal of Econometrics, Elsevier, vol. 146(1), pages 118-134, September.
    2. Yu, Jihai & de Jong, Robert & Lee, Lung-fei, 2012. "Estimation for spatial dynamic panel data with fixed effects: The case of spatial cointegration," Journal of Econometrics, Elsevier, vol. 167(1), pages 16-37.
    3. Ding, Ya & Schoengold, Karina & Tadesse, Tsegaye, 2009. "The Impact of Weather Extremes on Agricultural Production Methods: Does Drought Increase Adoption of Conservation Tillage Practices?," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 34(3), pages 1-17, December.
    4. Paul Elhorst & Eelco Zandberg & Jakob De Haan, 2013. "The Impact of Interaction Effects among Neighbouring Countries on Financial Liberalization and Reform: A Dynamic Spatial Panel Data Approach," Spatial Economic Analysis, Taylor & Francis Journals, vol. 8(3), pages 293-313, September.
    5. Pandey, S. & Bhandari, H. & Hardy, B., 2007. "Economic Costs of Drought and Rice Farmers’ Coping Mechanisms: A Cross-Country Comparative Analysis," IRRI Books, International Rice Research Institute (IRRI), number 281814.
    6. Jan Mutl & Michael Pfaffermayr, 2011. "The Hausman test in a Cliff and Ord panel model," Econometrics Journal, Royal Economic Society, vol. 14, pages 48-76, February.
    7. Li, Liyao & Yang, Zhenlin, 2021. "Spatial dynamic panel data models with correlated random effects," Journal of Econometrics, Elsevier, vol. 221(2), pages 424-454.
    8. Nicolas DEBARSY (CERPE De Namur) & Cem ERTUR & James P. LeSAGE, 2010. "Interpreting Dynamic Space-Time Panel Data Models," LEO Working Papers / DR LEO 800, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    9. Jeffrey M Wooldridge, 2010. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232588, April.
    10. E. M. Fischer & R. Knutti, 2015. "Anthropogenic contribution to global occurrence of heavy-precipitation and high-temperature extremes," Nature Climate Change, Nature, vol. 5(6), pages 560-564, June.
    11. Croissant, Yves & Millo, Giovanni, 2008. "Panel Data Econometrics in R: The plm Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 27(i02).
    12. Baltagi, Badi H. & Song, Seuck Heun & Koh, Won, 2003. "Testing panel data regression models with spatial error correlation," Journal of Econometrics, Elsevier, vol. 117(1), pages 123-150, November.
    13. Corey Lesk & Pedram Rowhani & Navin Ramankutty, 2016. "Influence of extreme weather disasters on global crop production," Nature, Nature, vol. 529(7584), pages 84-87, January.
    14. Lee, Lung-fei & Yu, Jihai, 2014. "Efficient GMM estimation of spatial dynamic panel data models with fixed effects," Journal of Econometrics, Elsevier, vol. 180(2), pages 174-197.
    15. Jinyong Hahn & Guido Kuersteiner, 2002. "Asymptotically Unbiased Inference for a Dynamic Panel Model with Fixed Effects when Both "n" and "T" Are Large," Econometrica, Econometric Society, vol. 70(4), pages 1639-1657, July.
    16. Pardeep Pall & Tolu Aina & Dáithí A. Stone & Peter A. Stott & Toru Nozawa & Arno G. J. Hilberts & Dag Lohmann & Myles R. Allen, 2011. "Anthropogenic greenhouse gas contribution to flood risk in England and Wales in autumn 2000," Nature, Nature, vol. 470(7334), pages 382-385, February.
    17. Monica Fisher & Tsedeke Abate & Rodney Lunduka & Woinishet Asnake & Yoseph Alemayehu & Ruth Madulu, 2015. "Drought tolerant maize for farmer adaptation to drought in sub-Saharan Africa: Determinants of adoption in eastern and southern Africa," Climatic Change, Springer, vol. 133(2), pages 283-299, November.
    18. Hubert Jayet & Julie Le Gallo & Luc Anselin, 2008. "Spatial Econometrics and Panel Data Models," Post-Print hal-02389412, HAL.
    19. N/A, 2004. "Index for 2004," European Union Politics, , vol. 5(4), pages 511-512, December.
    20. Meredith J. Soule & Abebayehu Tegene & Keith D. Wiebe, 2000. "Land Tenure and the Adoption of Conservation Practices," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 82(4), pages 993-1005.
    21. Millo, Giovanni & Piras, Gianfranco, 2012. "splm: Spatial Panel Data Models in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 47(i01).
    22. Bai, Jushan & Li, Kunpeng, 2021. "Dynamic spatial panel data models with common shocks," Journal of Econometrics, Elsevier, vol. 224(1), pages 134-160.
    23. Lee, Lung-fei & Yu, Jihai, 2011. "Estimation of Spatial Panels," Foundations and Trends(R) in Econometrics, now publishers, vol. 4(1–2), pages 1-164, April.
    24. Baylis, Katherine R. & Paulson, Nicholas D. & Piras, Gianfranco, 2011. "Spatial Approaches to Panel Data in Agricultural Economics: A Climate Change Application," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 43(3), pages 1-14, August.
    25. Md. Nazir Hossain & Swapna Chowdhury & Shitangsu Kumar Paul, 2016. "Farmer-level adaptation to climate change and agricultural drought: empirical evidences from the Barind region of Bangladesh," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 83(2), pages 1007-1026, September.
    26. Peter A. Stott & D. A. Stone & M. R. Allen, 2004. "Human contribution to the European heatwave of 2003," Nature, Nature, vol. 432(7017), pages 610-614, December.
    27. Xu, Xingbai & Lee, Lung-fei, 2015. "Maximum likelihood estimation of a spatial autoregressive Tobit model," Journal of Econometrics, Elsevier, vol. 188(1), pages 264-280.
    28. Nash, John C. & Varadhan, Ravi, 2011. "Unifying Optimization Algorithms to Aid Software System Users: optimx for R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 43(i09).
    29. Federico Belotti & Gordon Hughes & Andrea Piano Mortari, 2017. "Spatial panel-data models using Stata," Stata Journal, StataCorp LP, vol. 17(1), pages 139-180, March.
    30. Parent, Olivier & LeSage, James P., 2012. "Spatial dynamic panel data models with random effects," Regional Science and Urban Economics, Elsevier, vol. 42(4), pages 727-738.
    31. Shi, Wei & Lee, Lung-fei, 2017. "Spatial dynamic panel data models with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 197(2), pages 323-347.
    32. Lee, Lung-fei & Yu, Jihai, 2010. "A Spatial Dynamic Panel Data Model With Both Time And Individual Fixed Effects," Econometric Theory, Cambridge University Press, vol. 26(2), pages 564-597, April.
    33. Stephen Devereux, 2007. "The impact of droughts and floods on food security and policy options to alleviate negative effects," Agricultural Economics, International Association of Agricultural Economists, vol. 37(s1), pages 47-58, December.
    34. Lung-fei Lee & Jihai Yu, 2020. "Initial conditions of dynamic panel data models: on within and between equations," The Econometrics Journal, Royal Economic Society, vol. 23(1), pages 115-136.
    35. Millo, Giovanni, 2017. "A simple randomization test for spatial correlation in the presence of common factors and serial correlation," Regional Science and Urban Economics, Elsevier, vol. 66(C), pages 28-38.
    36. Lee, Lung-fei & Yu, Jihai, 2010. "Some recent developments in spatial panel data models," Regional Science and Urban Economics, Elsevier, vol. 40(5), pages 255-271, September.
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    1. Teerachai Amnuaylojaroen & Pavinee Chanvichit, 2022. "Application of the WRF-DSSAT Modeling System for Assessment of the Nitrogen Fertilizer Used for Improving Rice Production in Northern Thailand," Agriculture, MDPI, vol. 12(8), pages 1-15, August.
    2. Christian Glocker & Matteo Iacopini & Tam'as Krisztin & Philipp Piribauer, 2023. "A Bayesian Markov-switching SAR model for time-varying cross-price spillovers," Papers 2310.19557, arXiv.org.

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