Econometric Model of the Cyclic Behavior of Consumer in the Market of Durable Goods

Abstract Recently, the classical theory is faltering in predicting economic behavior, as individuals, as entire industries and states. Traditional economics considers man as logical thinking machine. Surely, the model of the human - machine that is capable of accepting an ideal rational decisions , and take into account all possible risks and to maximize their own utility , is very comfortable. However, real life is more complicated simple than mathematical model: it has a place for emotions, feelings, mistakes. And then the question arises: how important are psychological factors affecting human decision making, and whether they outweigh the tangible benefits, such as, for example, money? And, if so, how much? Whether consumers are prone to cyclical behavior on the durable goods market? And what factors caused this behavior? Answers on these questions tries give a new direction in economic science - behavioral economics, which combines psychology and economics. In this work will be conducted econometric analysis of the impact of consumer sentiment on consumer spending on durables. The Object of the study in this work are Russian consumers. The subject of this study is their behavior on the durable goods market . The purpose of the research is to build an econometric model of the cyclic behavior of consumers in the market for durable goods and the study of how psychological factors accounting affects the predictive value of the model. The main objectives of this study is to test the adequacy of the model and the construction of the forecast expenditure patterns for durable goods using models ARIMA. In the research will be used ARIMA models, which allow to model more complex relationships that are present in a number of speakers, in contrast to the trend- seasonal models. For analysis, we used quarterly data on household spending on durable goods for the period Q1 2004 to Q1 2014. Data were taken from the site of Rosstat. Model calculations were carried out in Eviews and SPSS.