Proceedings: 1st International Conference on Food and Agricultural Economics: DETERMINATION OF SOCIOECONOMIC AND DEMOGRAPHIC FACTORS AFFECTING HOUSEHOLD RED MEAT CONSUMPTION BY CHAID ANALYSIS

The aim of this study is to describe the Turkish household red meat consumption profile by CHAID method which is one of the Decision Tree algorithms. The data used in this study have been gathered from Turkish Statistical Institute’s Household Budget Survey. A total of 40.033 observations were used in CHAID Analysis. The result shows that the number of households consuming red meat is 19,838 and the rate is 49.55%. It has been observed that the most significant factor that affects red meat consumption is income level. The ratio of households consuming red meat is 37,194% among low-income households, 55,525% among the lower middle income households, 72,137% among the upper middle households, and 80,815% among the high income households consuming red meat. As a result, it can be seen that as the income level of household increases the red meat consumption rates also increase. In each income group, how the consumption differs according to household characteristics, and details have been shown. According to the results of the model; the income, the age and educational background of the head of the household, whether the household has an automobile, whether there is an individual between zero and fourteen and an individual over fifty years of age, rural/urban situation, ownership status of the household and the most common type of fuel used by the household have been seen as the socioeconomic and demographic factors affect the household red meat consumption in Turkey. Although the marital and insurance status of the head of the household, the household ownership, the household size, the facilities of reaching the bank for the location of the household, and presence of an individual between zero and five years of age have been included as independent variables in the model, they have not been seen as distinctive features and not been included in the decision tree.