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The relationship between agricultural technologies and carbon emissions in Pakistan: Peril and promise

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  • Zaman, Khalid
  • Khan, Muhammad Mushtaq
  • Ahmad, Mehboob
  • Khilji, Bashir Ahmad
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    Abstract

    The objective of the study is to investigate the influence of agricultural technologies on carbon emissions in Pakistan by using annual data from 1975 to 2010. Data is analyzed by some econometrics techniques including cointegration theory, Granger causality test, variance decomposition, etc. The results reveal that agricultural technologies act as an important driver for increase in carbon emissions in Pakistan. Results indicate that unidirectional causality runs from agriculture machinery to carbon emissions but not vice versa. Agricultural technologies are closely associated with economic growth and carbon emissions in Pakistan. Variance decomposition analysis shows that among all the agricultural technologies, granting subsidies to the agriculture sector have exerts the largest contribution to changes in carbon emissions. Conversely, agricultural irrigated land seems relatively the least contributors on changes in carbon emissions due to infertility of total irrigated land available in Pakistan.

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    File URL: http://www.sciencedirect.com/science/article/pii/S0264999312001459
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    Bibliographic Info

    Article provided by Elsevier in its journal Economic Modelling.

    Volume (Year): 29 (2012)
    Issue (Month): 5 ()
    Pages: 1632-1639

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    Handle: RePEc:eee:ecmode:v:29:y:2012:i:5:p:1632-1639

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    Web page: http://www.elsevier.com/locate/inca/30411

    Related research

    Keywords: Agricultural technologies; Carbon emissions; Economic growth; Tractors; Pakistan;

    References

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    1. Acemoglu, Daron & Aghion, Philippe & Bursztyn, Leonardo & Hemous, David, 2010. "The Environment and Directed Technical Change," Seminar Papers 762, Stockholm University, Institute for International Economic Studies.
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    7. Granger, C. W. J., 1988. "Causality, cointegration, and control," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 551-559.
    8. Toda, Hiro Y. & Yamamoto, Taku, 1995. "Statistical inference in vector autoregressions with possibly integrated processes," Journal of Econometrics, Elsevier, vol. 66(1-2), pages 225-250.
    9. Zaman, Khalid & Khan, Muhammad Mushtaq & Ahmad, Mehboob & Rustam, Rabiah, 2012. "The relationship between agricultural technology and energy demand in Pakistan," Energy Policy, Elsevier, vol. 44(C), pages 268-279.
    10. Johansen, Soren & Juselius, Katarina, 1990. "Maximum Likelihood Estimation and Inference on Cointegration--With Applications to the Demand for Money," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 52(2), pages 169-210, May.
    11. World Bank, 2010. "World Development Indicators 2010," World Bank Publications, The World Bank, number 4373, March.
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