Learning Residents’ Consumption Structures Based on the ELES Model

Abstract

AbstractThe worldwide spread of COVID-19 has greatly hit global economy by now. The world’s major economies including both developed and developing countries have felt the resulting impact on their financial markets. Accordingly, learning residents’ consumption structure is significant for boosting consumption demand and recovering financial market. In this paper, the Extend Linear Expenditure System (ELES) model is explored to learn both urban and rural residents’ consumption structures of China during COVID-19. In specific, the indices of marginal propensity to consume, income elasticity of demand, and price elasticity can be yielded via the ELES model based on the disposable income and the consumption data. Furthermore, the consumption structures before and during the corona virus epidemic can be quantitatively compared. Extensive experimental results demonstrate that the epidemic has made profound impacts on the consumption structure of residents. Among them, the marginal propensities on food and medical services have greatly increased, while the proportions of other expenditures have been decreased.KeywordsConsumption structureExtend linear expenditure systemMachine learning