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GARCH model to estimate the impact of agricultural greenhouse gas emissions per sociodemographic factors and CAP in Spain

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Abstract

This contribution analyses the Common Agricultural Policy (CAP) and focuses on agricultural emissions in Spain regarding sociodemographic characteristics (age and sex). Spanish CAP covers emissions regulation based on the application of agriculture management according to the EU-ETS and agricultural management (soil and energy). The analysis of the Spanish legal rules and policy identified empirical environmental attitudes as provided by the EUROSTAT and MINETUR databases between 1990 and 2013. The developed empirical–analytical GARCH model measures the impact between the soil and energy management indicators per capita based on CAP (as independent variables) and emissions per capita (as dependent variable). The selected criteria of the models are sociodemographic variables corresponding to employee in agriculture: interval of age and sex (total, men and women who work in agriculture). The research findings demonstrate high significance between emissions per age interval, sex and total population, and fertilizers, herbicides and non-renewable energy or gases consumption. The CAP’s proposed use of new machinery per capita does not influence directly the reduction of emissions. The model provides a good estimation for discussion about future policy trends of EU’s long-term objectives for Rural Development Policy related to CAP principles (i.e. fertilizers, pesticides, land use and energy consumption in crops), the impact of machinery in agriculture and the open debate of extending work life in agricultural older population.

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Notes

  1. World Meteorological Organization (WMO).

  2. George’s theorem argues that the natural resources belong equally to all; therefore, land rent should be shared equally by people. Hence, he introduces the concept of the economic tax based on rents of the natural resources due to the allocation land. According to Stiglitz, this theorem is “[…] the single tax to finance the public good and also externalities such as carbon emissions […]” (Stiglitz 2010).

  3. Data for transport were available only for EU-27 and only for the years from 2005 to 2010.

  4. Fertilizers include nitrogen, phosphorus, phosphate, potassium and potash.

  5. Pesticides include herbicides, fungicides, bactericides and insecticides.

  6. Agriculture and agricultural energy management include total of new tractors, tillers and cereal harvesters, consumption of energy from coals, fossil fuel oils, gases resources and non-renewable electrical resources.

  7. Agricultural management evolves farmers’ practices to adapt land use and production practices in order to contribute GHG mitigation, adaptation to climate change and to improve the environment (OECD 2012).

  8. See congress celebrated in Zafra, on 29 and 31 May 2019: https://www.mapa.gob.es/es/pac/la-arquitectura-verde-de-la-PAC-POST-2020-eco-esquemas/.

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Correspondence to Vanesa Zorrilla-Muñoz.

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Zorrilla-Muñoz, V., Petz, M. & Agulló-Tomás, M.S. GARCH model to estimate the impact of agricultural greenhouse gas emissions per sociodemographic factors and CAP in Spain. Environ Dev Sustain 23, 4675–4697 (2021). https://doi.org/10.1007/s10668-020-00794-y

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