Estimating Supply Response Function for Wheat: A Case Study

To increase wheat production, governments can subsidize wheat farmers by purchasing their produce at a price higher than the world price. This policy did not succeed in increasing wheat production in the Irbid Governorate of Jordan, our case study area. The agricultural sector in the study area was...

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Main Authors: M.S. EI-Habbab, K.H. Alwan
Format: Article
Language:English
Published: Sultan Qaboos University 2002-01-01
Series:Journal of Agricultural and Marine Sciences
Subjects:
Online Access:https://journals.squ.edu.om/index.php/jams/article/view/591
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spelling doaj-537b09b3ec0c4aee9f6b80db2bb272812020-11-25T03:25:48ZengSultan Qaboos UniversityJournal of Agricultural and Marine Sciences2410-10602410-10792002-01-0171293510.24200/jams.vol7iss1pp29-35577Estimating Supply Response Function for Wheat: A Case StudyM.S. EI-Habbab0K.H. Alwan1Department of Agricultural Economics and Agribusiness, University of Jordan, Postal Code 1 1942, Amman, JordanDepartment of Agricultural Economics and Agribusiness, University of Jordan, Postal Code 1 1942, Amman, JordanTo increase wheat production, governments can subsidize wheat farmers by purchasing their produce at a price higher than the world price. This policy did not succeed in increasing wheat production in the Irbid Governorate of Jordan, our case study area. The agricultural sector in the study area was characterized by risk in production and prices. In our study, the supply response function based on the Nerlovian Model was estimated for wheat produced in Irbid Governorate. Wheat area, in the model, was the dependent variable in the supply response function. The independent variables were: wheat planted area in Dunums in the current and previous year respectively, the weighted price of wheat in the previous year deflated by the Consumer Price Index (CPI), the holding fragmentation coefficient in the previous year, the yield risk, and the amount of rain in millimeters during the early months of the season (October, November, and December). The study reached the following conclusions: Firstly, holdings fragmentation was the major factor that negatively affects wheat production. Since the heritage system is the main factor that affects holding fragmentation, the policy makers need to find a way that can decrease this effect. Secondly, lagged weighted prices were found more suitable than the current weighted prices from an economic and statical point of view. Thirdly, the partial adjustment coefficient was low (i.e. less than one), which means that the farmers need more than one year to change their producing habits. Finally, the farmers were found to be risk-neutral, because their decisions depend mainly on the level and distribution of rainfall during the rainy season.https://journals.squ.edu.om/index.php/jams/article/view/591wheat production, nerlovian model, subsidy, holding fragmentation coefficient.
collection DOAJ
language English
format Article
sources DOAJ
author M.S. EI-Habbab
K.H. Alwan
spellingShingle M.S. EI-Habbab
K.H. Alwan
Estimating Supply Response Function for Wheat: A Case Study
Journal of Agricultural and Marine Sciences
wheat production, nerlovian model, subsidy, holding fragmentation coefficient.
author_facet M.S. EI-Habbab
K.H. Alwan
author_sort M.S. EI-Habbab
title Estimating Supply Response Function for Wheat: A Case Study
title_short Estimating Supply Response Function for Wheat: A Case Study
title_full Estimating Supply Response Function for Wheat: A Case Study
title_fullStr Estimating Supply Response Function for Wheat: A Case Study
title_full_unstemmed Estimating Supply Response Function for Wheat: A Case Study
title_sort estimating supply response function for wheat: a case study
publisher Sultan Qaboos University
series Journal of Agricultural and Marine Sciences
issn 2410-1060
2410-1079
publishDate 2002-01-01
description To increase wheat production, governments can subsidize wheat farmers by purchasing their produce at a price higher than the world price. This policy did not succeed in increasing wheat production in the Irbid Governorate of Jordan, our case study area. The agricultural sector in the study area was characterized by risk in production and prices. In our study, the supply response function based on the Nerlovian Model was estimated for wheat produced in Irbid Governorate. Wheat area, in the model, was the dependent variable in the supply response function. The independent variables were: wheat planted area in Dunums in the current and previous year respectively, the weighted price of wheat in the previous year deflated by the Consumer Price Index (CPI), the holding fragmentation coefficient in the previous year, the yield risk, and the amount of rain in millimeters during the early months of the season (October, November, and December). The study reached the following conclusions: Firstly, holdings fragmentation was the major factor that negatively affects wheat production. Since the heritage system is the main factor that affects holding fragmentation, the policy makers need to find a way that can decrease this effect. Secondly, lagged weighted prices were found more suitable than the current weighted prices from an economic and statical point of view. Thirdly, the partial adjustment coefficient was low (i.e. less than one), which means that the farmers need more than one year to change their producing habits. Finally, the farmers were found to be risk-neutral, because their decisions depend mainly on the level and distribution of rainfall during the rainy season.
topic wheat production, nerlovian model, subsidy, holding fragmentation coefficient.
url https://journals.squ.edu.om/index.php/jams/article/view/591
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