SIGNATURE WORK
CONFERENCE & EXHIBITION 2024

This project aims at examining the impacts of price change on individuals’
consumption patterns within the specific population of urban China. The Ordinary
Least Squares(OLS) regression model is applied in this research. The specific
regression model used in this research is: ln(Qcategory) = a + b*ln(Pcategory) +
c*ln(AIcategory), where “Qcategory” represents the Quantity consumed for each
category, “Pcategory” represents the relative Price of each category (calculated using
urban CPI data of China), and “AIcategory” represents the Adjusted Income of urban
China population (calculated using nominal Income divided by category Price). This
research mainly focuses on examining the different Price elasticities of each category
of consumed goods. The results and conclusions of the research further analyze the
possible factors that cause the distinct consumption patterns to Price change for each
category, mainly including consumer confidence, wealth effect and income effect.
Potential limitations of the specific model used in the research and policy implications
from the research are also discussed in the paper.