Analysis of Factors Affecting Marketing of Sheep in Ahar County: Application of Generalized Poisson Regression

Introduction: Animal husbandry as an economic sub-sector is one of the most successful productive activities of the agricultural sector, which plays a very effective role in providing food for society. On the other hand, the economic growth of society, the increase in household consumption of livestock products and the population growth have caused an increase in demand for these products. The transition from traditional to modern agriculture and the distance of the centers of consumption from the production areas, mostly located in marginal and rural areas, has led to an importance of the marketing of agricultural products. Marketing methods of agricultural and animal products in Iran are expensive and incompatible with the goals of sustainable development of the rural economy. Therefore, there are many problems such as price volatility, high production costs, the presence of merchants, as well as the insufficient government support about market development and marketing policy for rural products, also in relation to the marketing of agricultural and animal products in Ahar County. Therefore, this research attempts to analyze the factors affecting marketing of sheep in Ahar County using the generalized Poisson regression method.
Material and methods: The purpose of this study is analysis of factors affecting marketing of sheep in Ahar County using the generalized Poisson regression method. In this study, the dependent variable is numerical. Linear regression methods cannot be used in studies where the dependent variable is countable because the dependent variable in these models must follow a normal distribution and be continuous. Therefore, using the Poisson regression model is considered to be a suitable method for conducting investigations where the dependent variable is numerical in nature. To achieve the research goal, the normal Poisson regression was first estimated, but due to the fact that the mean and variance of the dependent variables were not equal, the surrogate model, that is, the generalized Poisson regression, was also estimated. Next, the Akaike and Schwartz-Bayesian information criteria were used to ensure the adequacy of the generalized Poisson model. Considering that the amount of the Akaike and Schwartz-Bayes statistic was smaller in the generalized Poisson model, the generalized Poisson model was considered to be an appropriate model. Data were collected by completing a questionnaire from 100 Ahar County ranchers using a simple random sampling procedure. Stata15 software was used to estimate the models.
Results and discussion: Because the mean (52.84) and variance (2576.70) of the dependent variable are not equal, the normal Poisson model is not appropriate and the generalized Poisson model must be used. Also, Akaike’s statistic (AIC) and Schwartz-Bayesian (BIC) in the Poisson model are 1132/912 and 1161/569, respectively, while in the generalized Poisson model they are 838/432 and 869/694. Therefore, the generalized Poisson model is better than the Poisson model. The coefficients of all variables in the generalized Poisson model are significant. Since Poisson regression coefficients are difficult to interpret directly, their incidence risk ratio (IRR) values were calculated. The results of the incidence risk ratio estimation indicate that living in the city (0.674) and distance to the nearest sheep market (0.988) had a negative effect and having a suitable corral (2.004), attitude of breeders to improve breeds (1.373), having of farm income (1.329), access to credits (1.217), prepare animal feed in time (1.212), access to veterinary services (1.212), access to suitable pastures (1.210) and number of sheep (1.003) had a positive effect on the number of sheep marketed.
Conclusion: The results showed that several factors are involved in the amount of sheep sales in the study area. One of these factors is the attitude of the region's breeders to the improved and high-yielding breeds of sheep and, accordingly, their willingness to buy and breed these sheep. Because improved sheep increase the market power of the ranchers through their characteristics such as twins and the production of higher products. Another factor that is effective in rancher marketing is the distance between the rancher and the sheep market. The rancher thinks a longer distance as higher marketing costs, resulting in a decrease in sales. Ranchers who live in the city and whose primary residence is far from where their sheep are raised cannot take good care of their sheep, resulting in a drop in production and ultimately a drop in the productivity of the individual in the thing leads of marketing. Based on the results, farmers who have more sheep can sell more. Farmers who have other economic activities besides animal husbandry can use the income from these activities to expand and improve sheep farming and increase the number of sales and their income levels. Access to pastures and credit will lead to higher income levels. Having a suitable corral for keeping livestock has the greatest impact on the number of sheep sold. It is obvious that if the rancher does not have a suitable place to keep the livestock, he will not be able to continue his activity. The results indicated that appropriate measures to facilitate access to credit may be through finance the construction of suitable corral, provide cattle feed and increase the number of flocks, can be an effective measure to increase the number of sheep offered on the market. In addition, improving veterinary care and conducting educational and extension courses to eliminate negative attitudes towards improved sheep are considered effective management measures.
Keywords: Generalized Poisson regression, Marketing, Sheep
Keywords: Generalized Poisson regression, Marketing, Sheep
Keywords: Generalized Poisson regression, Marketing, Sheep
Keywords: Generalized Poisson regression, Marketing, Sheep