نوع مقاله : مقاله پژوهشی
نویسندگان
دانشگاه تهران
چکیده
کلیدواژهها
عنوان مقاله [English]
Nowadays, continuous growth of developed countries and the rapid growth in developing countries owe to use of energy. But in recent decades, the need to move towards sustainable development, public thought to increase energy productivity to upgrade the production by the specific energy consumption. On the other hand, researchers believe that the move to a diversified production system and economies of scope due to it can increase the productivity of inputs. Hence, the present study has been checked the causal relationship between energy productivity and diversity of activities in the agricultural sector by the Toda-Yamamoto causality and Bounds tests. The results indicate the existence of a unidirectional causal relationship from energy productivity to diversity of activities. So, due to the positive influence of energy productivity from diversity of agricultural activities, it is suggested that government encourage agricultural system to more diversification instead of various supporting policies from specific products.
کلیدواژهها [English]
10. Narayan, P.K., & Smyth, R. (2006). Higher education, real income and real investment in China: evidence from Granger causality tests. Educ Econ, 14, 107–125.
11. Odhiambo, N. (2009). Energy Consumption And Economic Growth Nexus In Tanzania: An ARDL Bounds Testing Approach. Energy Policy, 37(2), 617–622.
12. Odhiambo, N. (2010). Energy consumption, prices and economic growth in three SSA countries: A comparative study. Energy Policy, 38(5), 2463–2469.
13. Pesaran, M., Shin, Y., Smith, J. (2001), Bounds Testing Approaches To The Analysis Of Level Relationships, Journal Of Applied Econometrics, 16(3), 289–326.
14. Sims, C. (1972). Money, Income and causality, American Economic Review, 62, 540- 552.
15. Tang, T. C. 2003. Japanese Aggregate Import Demand Function: Reassessment from ‘Bound’ Testing Approach, Japan and the World Economy, 4(15), 419–436.
16. Toda, H.Y., & Yamamoto, T. (1995). Statistical inference in vector auto regressions with possibly integrated processes, Journal of econometrics, 66, 225- 250.
17. Zapata, H. O., & Rambaldi, A. N. (1997). Monte - Carlo evidence on cointegration and Causation, Oxford Bulletin of Economics and Statistics, 59, 285- 298.
18. Langeveld, H., Rufino, M., Hengsdijk, H., Ruben, R., Dixon, J., Verhangen, J., and Giller, K. (2007). Evaluation of economic and environmental performance of two farm household strategies: diversification and integration, conceptual model and case studies. Quantitative Approaches in Systems Analysis, 29.
19. Kim, K., Chavas, J. P., Barham, B., Foltz, J. (2012). Specialization, diversification, and productivity: a panel data analysis of rice farms in Korea. Agricultural Economics, 43: 687–700.
20. Salami, H. (2000). Determining the optimal size grasslanding firms units with a total productivity factor indicator: A Case Study of Fars Province. Journal of Agricultural Economics and Development, 32: 51-67.
Mehrabi Boshr Abadi, H. & Esmaeeli, A. (2011). Analysis of input-outpot of energy in agriculture. Journal of Agricultural Economics and Development, 74, 1-28.