Abstract:

Purpose- Firstly, this paper examines how current measurements of consumer confidence might be used to forecast future household spending by using economic variable (i.e. unemployment rate, national adjusted income per capita) data in China, with the help of statistic tools (i.e. Python and Pandas) for the job of data cleaning and analyzing. Secondly, I will focus on the ways in which businesses alter their marketing mix in the face of economic hardship to survive by understanding the importance of utilizing effective marketing strategies during economic downturns. Methodology- This paper examines the predictive performance of consumer confidence index on change in consumption growth by constructing three different OLS regression models and by integrating several existing proposals for effective marketing strategies for businesses in times of low consumer confidence to help business managers to make wise and effective response to economic downturns. Findings- It is shown both 1 year lagged consumer confidence and 3 years lagged consumer confidence are good predictors for current change in consumption patterns, whereas 2 years lagged consumer confidence shows negative correlation with consumption change, and consumer confidence have their own predictive power regardless of the macroeconomic variables. Conclusion- Therefore, this paper contributes to the existing literature by providing empirical findings that consumer confidence cannot always fulfill the role of anticipating consumption change and by further providing concrete policy recommendations for consumer confidence’ revival during recessions in an effort to fill the gap.

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