five

Agricultural Transformation Performance and Inter-Sectoral Linkages in Ethiopia

收藏
DataCite Commons2024-06-07 更新2024-07-03 收录
下载链接:
https://ageconsearch.umn.edu/record/343263
下载链接
链接失效反馈
官方服务:
资源简介:
The motivation for agricultural transformation is basically linked with structural relationships among sectors of the economy; transforming one sector cannot be successful without the corresponding transformation of the other. Therefore, this study assessed the performance of agricultural transformation and analyzed the linkage between agricultural and other sectors of the economy in Ethiopia using time-series data retrieved from the World Bank (WB) and FAOSTAT databases (1981-2019). The study employed trend analysis and the Vector Error Correction Model (VECM) which incorporated inter-sectoral linkages in the Ethiopian economy. In the trend analysis, though positive changes have been observed, agricultural transformation did not achieve the intended outcomes in terms of sustainability, productivity technical change, food self-sufficiency, and expansion of agro-industries, which calls government attention to a swift shift to market-oriented commercial farming involving mechanization. The model result illustrates how the linkages across different sectors vary in the short-run and long-run. In the short-run, the industrial sector has a negative effect on the performance of the agricultural sector, whereas the agricultural sector in turn affects the value added in the industrial sector positively. In the longrun, there was exhibited a positive and significant linkage between industrial and agricultural sectors. Thus, it needs to strengthen the effective use and adoption of new agricultural technologies in Ethiopia due to the existing negative short-run agriculture-industry relationship. The macroeconomic policy should also take into account the possible long-run interdependencies between agriculture and other sectors of the economy by giving emphasis to the problem of transferring resources from agriculture to other sectors and vice versa.
提供机构:
Unknown
创建时间:
2024-06-07
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作