Summary:
Accurately measuring inflation is a fundamental prerequisite for achieving price stability and enhancing the effectiveness of macroeconomic governance. While the Consumer Price Index (CPI) has long served as the core indicator for inflation measurement, the “perception gap” between households' perceived cost of living and the official CPI has become increasingly salient. Specifically, as asset markets evolve and digital finance expands, the nexus between asset price fluctuations and inflation perception bias has emerged as a critical concern. In this context, refining the inflation measurement system is of profound theoretical and practical importance for bolstering the credibility of inflation indicators and optimizing monetary policy regulation. Existing studies have explored the determinants, measurement, and correction of inflation perception bias. However, in-depth analysis is still needed regarding the interconnected effects, underlying mechanisms, and the moderating role of digital finance in the relationship between asset price fluctuations and inflation perception bias. The Engel curve method represents a typical approach to measuring inflation perception bias by capturing the stable mapping between micro-level consumption structures and real purchasing power. Nevertheless, the standard Engel curve framework typically relegates unexplained systematic deviations to time-fixed effects, rendering the results a “residual” measurement. Taking housing prices as a representative asset price, we incorporate the impact of housing prices on households' real purchasing power into the classical Engel demand system. This allows us to identify a component of inflation perception bias linked to housing price fluctuations, enabling a revision of the CPI from the perspective of households' true cost of living. Moreover, we introduce digital financial development into the research framework to explore its moderating effect on the nexus between asset prices and inflation perception bias. Utilizing city-level panel data from 2011 to 2023 in China, we reveal a significant bias component induced by housing price fluctuations. We find that rising (falling) housing prices lead to a negative (positive) housing-price-related inflation perception bias (HPB). Based on these estimates, we construct a housing-price-adjusted cost-of-living index (HCI). During the housing boom from 2011 to 2020, the HCI remained consistently below the CPI, suggesting that housing appreciation buffered the perceived pressure from rising living costs. Following the market correction after 2021, this gap narrowed rapidly and then reversed. This implies that households' perceived inflation has outpaced official CPI figures, offering a partial explanation for the recent sluggishness in Chinese household consumption while highlighting the inherent synergy between policies aimed at stabilizing the housing market and those bolstering consumption. Mechanism analysis, using data from the China Household Finance Survey (CHFS), demonstrates that housing price fluctuations influence consumption decisions primarily through the wealth effect rather than the consumption substitution effect. Based on this, we integrate digital financial development into the empirical analysis, and find that digital finance amplifies the impact of asset price fluctuations on inflation perception bias by strengthening the wealth effect, implying that digital finance widens the gap between households' perceived cost of living and official inflation figures. These findings suggest that as digital finance continues to evolve, improving the inflation measurement system becomes increasingly imperative. Beyond refining the CPI basket, policymakers should account for the impact of asset prices on the perceived cost of living to better track changes in real purchasing power and stabilize market expectations. This study makes three primary contributions. First, we extend the standard Engel curve method by incorporating asset price effects on real purchasing power, offering a novel framework for the measurement of households' real cost of living. Second, from a micro-consumption perspective, we identify the key mechanism through which housing prices shape inflation perception, providing fresh insights into the micro-foundations of inflation perception bias. Third, we integrate digital finance into the analytical framework, presenting robust empirical evidence on how digital finance moderates housing-price-related inflation perception bias.
刘珺, 康立, 丁雨婷. 资产价格与通胀感知偏差——基于数字金融发展的再思考[J]. 金融研究, 2026, 552(6): 1-19.
LIU Jun, KANG Li, DING Yuting. Asset Prices and Inflation Perception Bias: A Reexamination Through the Lens of Digital Finance. Journal of Financial Research, 2026, 552(6): 1-19.
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