Seasonal dynamics and ARIMA forecasting of China’s consumer confidence index (2000-2024): An empirical analysis

International Business Economics, University of Nottingham Ningbo China, 199 Taikang East Road, Ningbo, China

^* Corresponding author: hnyzl15@nottingham.edu.cn

Abstract

China’s Consumer Confidence Index (CCI) is a key barometer of household sentiment and a leading indicator of future consumption. This study presents an empirical analysis of China’s quarterly CCI from 2000 to 2024, and forecasting its trajectory using seasonal ARIMA modeling. The CCI data were aggregated to quarterly frequency and analyzed with time-series decomposition and Box-Jenkins methods. Key turning points in CCI align with major economic events-for instance, a sharp drop during the 2003 SARS outbreak, a dip in 2008-2009 amid the global financial crisis, and an unprecedented collapse in 2022 under zero-COVID lockdowns. An ARIMA model with seasonal adjustments was fitted to capture the underlying structure; while the model’s fit indicates the CCI largely follows a non-stationary downward drift in recent years, it provides a reasonable short-term forecast. Results show consumer confidence remaining subdued into 2025 (forecasted CCI 89-94), suggesting a slow recovery. The study’s findings underscore the CCI’s value in gauging economic sentiment and the importance of accounting for seasonality and structural breaks, and providing a comprehensive time-series analysis which could help policymakers and businesses understand and anticipate shifts in consumer confidence.