The Role of Agricultural Inputs on Crop Productivity: The Case of Zigam Woreda
In spite of the importance of agriculture in Ethiopia, it is characterized by low productivity and has been unable to produce sufficient quantities of output to feed the country’s population. In light of this various development strategies has been undertaken to improve the performance of agricultur...
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Veröffentlicht in: | International journal of business and economics research (Print) 2024-10, Vol.13 (5), p.133-141 |
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Format: | Artikel |
Sprache: | eng |
Online-Zugang: | Volltext |
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Zusammenfassung: | In spite of the importance of agriculture in Ethiopia, it is characterized by low productivity and has been unable to produce sufficient quantities of output to feed the country’s population. In light of this various development strategies has been undertaken to improve the performance of agriculture. Intensification of agriculture through the use of new agricultural technologies has been emphasized over the last three decades. This study attempted to examine the contribution of agricultural input for crop productivity. The data for the study was collected from 91 sample farmers. This study was the study used both primary and secondary data. In this study researcher was used simple random sampling techniques. This research was use cross sectional approach and econometric method of data analysis to investigate the role of age, sex, land size, labor force, fertilizer, improved seed, extension service, and access to credit, education level and pesticides for crop production by collecting data from the household. In econometric method of data analysis researcher was used ordinary least square (OLS) Model. The econometric result show that land size, labor force, improved seed, fertilizer, credit service, extension service and education level have positive and significant effect on crop production. However, pesticide has a negative and significant impact on crop production. From the explanatory variables, education level has a higher coefficient. This indicates education level is more significant for crop production. According regression result R 2 is 0.97, which implies 97% of output function is explained by the selected ten (10) explanatory variables. The policy implication is that to reduce farmers resistant to use farm inputs and to create knowledge about the optimal input use educate and training of farmers is necessary. |
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ISSN: | 2328-7543 2328-756X |
DOI: | 10.11648/j.ijber.20241305.12 |