PREDICTION OF THE PROBABILITIES FOR CHANGING OF THE AGRICULTURAL LOANS USING MARKOV CHAIN MODEL | ||
| Egyptian Journal of Agricultural Research | ||
| Article 25, Volume 96, Issue 3, September 2018, Pages 1229-1257 PDF (965.17 K) | ||
| Document Type: Original Article | ||
| DOI: 10.21608/ejar.2018.141162 | ||
| Author | ||
| YEHIA ABD. YEHIA | ||
| Agricultural Economics Research Institute, ARC, Giza. | ||
| Abstract | ||
| The Agricultural Bank of Egypt (ABE) has the right to perform all credit portfolio of the commercial banks. In this context, the ABE faces a problem in making a balance between practicing regular activities that achieve high returns and those with high costs from one side, and providing farmers with their needs of agricultural loans, as well. Therefore, the current research attempts to answer a question on how well the ABE can succeed in achieving these goals without affecting the size of loans provided to the agricultural sector as productive and investment loans. Hence, this research aimed at analyzing credit decisions made by the ABE in terms of the distribution of credit portfolio of agricultural loans, including productive and investment loans and predicting the size of these loans based on market mechanisms, as well. In order to achieve this objective, the research used the Markov series analysis for the period (1999/2000-2015/2016). The results predict an increase of 75% in the of loans provided to plant production in 2016/2017 whereas, the decrease in the of loans provided to plant production will reach about 25% in the same year. Even with the increase in the of plant production loans in general, the estimates expect that it will decline till the year 2019/2020, then it will stabilize over the rest of the period. Likewise, the estimates cited an increase of 81% in the of agricultural investment loans in 2016/2017. It is also expected that investment loans will decrease by about 19% in the same year. Despite the increase in the value of agricultural investment loans in general, the estimates expect that its decline in 2017/2018 and then move towards stability starting from 2019/2020 until the end of the period. Finally, the research recommends providing liquidity to meet the increasing demand on agricultural loans, especially with theprediction of increasing the number of borrowers. Besides, the expected increase of plant production loans largely mirrors the need to devote much efforts in reconsidering the geographical distribution of credit areas with respect to indicative and actual cultivated areas within the framework of the Sustainable Agricultural Development Strategy towards 2030 (SADS) | ||
| Keywords | ||
| PROBABILITIES; MARKOV CHAIN MODEL | ||
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