Ben Jebli, Mehdi and Ben Youssef, Slim (2017): Investigating the interdependence between non-hydroelectric renewable energy, agricultural value added, and arable land use in Argentina.
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Abstract
We examine the dynamic relationships between per capita carbon dioxide (CO2) emissions, real gross domestic product (GDP), non-hydroelectric renewable energy (NHRE) consumption, agricultural value added (AVA), and agricultural land (AGRL) use for the case of Argentina over the period 1980-2013 by employing the autoregressive distributed lag (ARDL) bounds approach to cointegration and Granger causality tests. The Wald test confirms the existence of a long-run cointegration between variables. There are long-run bidirectional causalities between all considered variables. The short-run Granger causality suggests bidirectional causality between AVA and agricultural land use; unidirectional causalities running from AGRL to NHRE and from NHRE to AVA. Long-run elasticity estimates suggest that increasing AVA increases GDP and reduces both pollution and NHRE; increasing NHRE reduces AVA and AGRL. Thus it seems that agriculture and renewable energy are substitute activities and compete for land use. We recommend that Argentina should continue to encourage agricultural production. The substitutability between agricultural and non-hydroelectric renewable energy productions, and their competition for agricultural land use, should be at least reduced or even stopped by encouraging R&D in second-generation (or even in third-generation) biofuels production and in new renewable energy technologies more efficient in land use.
Item Type: | MPRA Paper |
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Original Title: | Investigating the interdependence between non-hydroelectric renewable energy, agricultural value added, and arable land use in Argentina |
Language: | English |
Keywords: | Autoregressive distributed lag; Granger causality; non-hydroelectric renewable energy; agricultural value added; agricultural land; Argentina. |
Subjects: | C - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models ; Multiple Variables > C32 - Time-Series Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes ; State Space Models 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 > Q4 - Energy > Q42 - Alternative Energy Sources Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q5 - Environmental Economics > Q54 - Climate ; Natural Disasters and Their Management ; Global Warming |
Item ID: | 77513 |
Depositing User: | Slim Ben Youssef |
Date Deposited: | 17 Mar 2017 10:31 |
Last Modified: | 02 Oct 2019 18:02 |
References: | Al-Mulali, U., Solarin, S.A., Ozturk, I., 2016a. Biofuel energy consumption-economic growth relationship: an empirical investigation of Brazil. Biofuels, Bioproducts & Biorefining, 10, 753–775. Al-Mulali, U., Solarin, S.A., Sheau-Ting, L., Ozturk, I., 2016b. Does moving towards renewable energy causes water and land inefficiency? An empirical investigation. Energy Policy, 93, 303–314. Apergis, N., Payne, J.E., 2010a. Renewable energy consumption and economic growth: Evidence from a panel of OECD countries. Energy Policy, 38, 656-660. Apergis, N., Payne, J.E., 2010b. Renewable energy consumption and growth in Eurasia. Energy Economics, 32, 1392-1397. Apergis, N., Payne, J.E., 2011. The renewable energy consumption–growth nexus in Central America. Applied Energy, 88, 343-347. Apergis, N., Payne, J.E., Menyah, K., Wolde-Rufael, Y., 2010. On the causal dynamics between emissions, nuclear energy, renewable energy, and economic growth. Ecological Economics, 69, 2255-2260. Ben Jebli, M., 2016. On the causal links between health indicator, output, combustible renewables and waste consumption, rail transport, and CO2 emissions: The case of Tunisia. Environmental Science and Pollution Research, 22, 16699–16715. Ben Jebli, M., Ben Youssef, S., 2015. The environmental Kuznets curve, economic growth, renewable and non-renewable energy, and trade in Tunisia. Renewable and Sustainable Energy Reviews, 47, 173-185. Ben Jebli, M., Ben Youssef, S., 2016. Combustible renewables and waste consumption, agriculture, CO2 emissions and economic growth in Brazil. MPRA Paper No. 69694. Accessed at: https://mpra.ub.uni-muenchen.de/69694/. Ben Jebli, M., Ben Youssef, S., 2017a. Renewable energy consumption and agriculture: evidence for cointegration and Granger causality for Tunisian economy. International Journal of Sustainable Development & World Ecology, 24, 149-158. Ben Jebli, M., Ben Youssef, S., 2017b. The role of renewable energy and agriculture in reducing CO2 emissions: Evidence for North Africa countries. Ecological Indicators, 74, 295-301. Ben Jebli, M., Ben Youssef, S., 2017c. Renewable energy, arable land, agriculture, CO2 emissions, and economic growth in Morocco. MPRA Paper No. 76798. Brown, R.L., Durbin, J., Evans, J.M., 1975. Techniques for testing the constancy of regression relations over time.Journal of the Royal Statistical Society, Series B, 37, 149–63. Dickey, D.A., Fuller, W.A., 1979. Distribution of the estimators for autoregressive time series with a unit root. Journal of the American Statistical Association, 74, 427-431. Diogo, V., Hilst, F.V.D., Eijck, J.V., Verstegen, J.A., Hilbert, J., Carballo, S., Volante, J., Faaij, A., 2014. Combining empirical and theory-based land-use modelling approaches to assess economic potential of biofuel production avoiding iLUC: Argentina as a case study. Renewable and Sustainable Energy Reviews, 34, 208–224. Di Sbroiavacca, N., Nadal, G., Lallana, F., Falzon, J., Calvin, K., 2016. Emissions reduction scenarios in the Argentinean energy sector. Energy Economics, 56, 552–563. Dogan, E., 2016. Analyzing the linkage between renewable and non-renewable energy consumption and economic growth by considering structural break in time-series data. Renewable Energy, 99, 1126-1136. Dogan, E., Sebri, M., Turkekul, B., 2016. Exploring the relationship between agricultural electricity consumption and output: New evidence from Turkish regional data. Energy Policy, 95, 370–377. Energy Information Administration, 2017. International Energy Outlook. Accessed at: www.eia.gov/forecasts/aeo. Engle, R.F., Granger C.W.J., 1987. Co-integration and error correction: Representation, estimation, and testing. Econometrica, 55, 251-276. International Renewable Energy Agency, 2015. Renewable Energy Policy Brief: Argentina. Accessed at: http://www.irena.org/DocumentDownloads/Publications/IRENA_RE_Latin_America_Policies_2015_Country_Argentina.pdf. Karkacier, O., Goktolga, Z.G., Cicek, A., 2006. A regression analysis of the effect of energy use in agriculture. Energy Policy, 34, 3796-3800. Menyah, K., Wolde-Rufael, Y., 2010. CO2 emissions, nuclear energy, renewable energy and economic growth in the US. Energy Policy, 38, 2911–2915. Mushtaq, K., Abbas, F., Ghafour, A., 2007. Energy use for economic growth: Cointegration and causality analysis from the agriculture sector of Pakistan. The Pakistan Development Review, 46, 1065–1073. Navia, T., Sewell, A., Avila, J., 2016. Argentina launches innovative renewables program. Accessed at: http://www.renewableenergyworld.com/articles/2016/06/argentina-launches-innovative-renewables-program.html. Omri, A., Daly, S., Nguyen, D.K., 2015. A robust analysis of the relationship between renewable energy consumption and its main drivers. Applied Economics, 47, 2913-2923. Pao, H.T., Fu, H.C., 2013a. Renewable energy, non-renewable energy and economic growth in Brazil. Renewable and Sustainable Energy Reviews, 25, 381-392. Pao, H.T., Fu, H.C., 2013b. The causal relationship between energy resources and economic growth in Brazil. Energy Policy, 61, 793-801. Pesaran, M.H., Pesaran, B., 1997. Working With Microfit 4.0: Interactive Econometric Analysis. Oxford University Press, Oxford. Pesaran, M.H., Smith, R.P., 1998. Structural analysis of cointegratingVARs. Journal of Economic Survey, 12, 471–505. Pesaran, M.H., Shin, Y., Smith, R.J., 2001. Bounds testing approaches to the analysis of level relationships. Journal of Applied Econometrics, 16, 289–326. Phillips, P.C.B., Perron, P., 1988. Testing for a unit root in time series regressions.Biometrika, 75, 335-346. Qureshi, M.I., Awan, U., Arshad, Z., Rasli, A.M., Zaman, K., Khan, F., 2016. Dynamic linkages among energy consumption, air pollution, green house gas emissions and agricultural production in Pakistan: Sustainable agriculture key to policy success. Nat Hazards, DOI: 10.1007/s11069-016-2423-9. Rafiq, S., Salim, R., Apergis, N., 2016. Agriculture, trade openness and emissions: An empirical analysis and policy options. Australian Journal of Agricultural and Resource Economics, 60, 348-365. REN21, 2012. Renewables 2012 Global Status Report. Accessed at: www.ren21.net. Sebri, M., Abid, M., 2012. Energy use for economic growth: A trivariate analysis from Tunisian agriculture sector. Energy Policy, 48, 711-716. Shahbaz, M., Islam, F., Butt, M.S., 2016. Finance–growth–energy nexus and the role of agriculture and modern sectors: Evidence from ARDL bounds test approach to cointegration in Pakistan. Global Business Review, 17, 1037–1059. Sadorsky, P., 2009. Renewable energy consumption and income in emerging economies. Energy policy, 37, 4021-4028. Tan, K.T., Lee, K.T., Mohamed, A.R., 2008. Role of energy policy in renewable energy accomplishment: The case of second-generation bioethanol. Energy Policy, 36, 3360– 3365. Tang, C.F., Shahbaz, M., 2013. Sectoral analysis of the causal relationship between electricity consumption and real output in Pakistan. Energy Policy, 60, 885–891. Tugcu, C.T., Ozturk, I., Aslan, A., 2012. Renewable and non-renewable energy consumption and economic growth relationship revisited: Evidence from G7 countries. Energy Economics, 34, 1942-1950. Turkekul, B., Unakitan, G., 2011. A co-integration analysis of the price and income elasticities of energy demand in Turkish agriculture. Energy Policy, 39, 2416–2423. Viglizzo, E.F., Frank, F.C., 2014. Energy use in agriculture: Argentina compared with other countries (Chapter 4). In: Energy Consumption: Impacts of Human Activity, Current and Future Challenges, Environmental and Socio-Economic Effects (S. Reiter, Editor). NOVA Science Publishers, Inc. N York Pp 77-98. World Bank, 2017. World Development Indicators.Accessed at: http://www.worldbank.org/data/onlinedatabases/onlinedatabases.html. World Bank; CIAT; CATIE, 2014. Supplementary material to climate-smart agriculture in Argentina. CSA country profiles for Latin America series. Washington D.C.: The World Bank Group. Zivot, E., Andrews D., 1992. Further evidence of great crash, the oil price shock and the unit root hypothesis. Journal of Business and Economic Statistics, 10, 251-270. |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/77513 |