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| A New Measure of Inflation Uncertainty and Its Domestic Demand Effects: Theoretical Mechanisms and Empirical Evidence |
| HE Fumei, LIU Bing, OUYANG Zhigang
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School of Finance, Nanjing University of Finance and Economics;
School of Economics and Management, East China Jiaotong University;
School of Finance, Zhongnan University of Economics and Law |
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Abstract Expanding domestic demand serves as the strategic foundation for facilitating the domestic economic cycle, promoting domestic and international dual circulation, consolidating China's advantage of hypermarket, and safeguarding against uncertainties in the external environment. As dual engines for domestic demand expansion, the comprehensive unleashing of consumption potential and the elimination of investment barriers constitute critical components for ensuring the effective implementation of this strategy. However, future inflation expectations are highly uncertain due to the intertwining and interplay of many factors, such as escalating geopolitical risks, disrupted global supply chains, and intensified great-power competition. Economic theory has demonstrated that inflation uncertainty significantly influences consumption behavior and investment decisions of economic agents (Dixit & Pindyck, 1994), implying that such uncertainty inevitably impacts China's domestic demand expansion strategy. Particularly under the current complex and volatile environment, the driving factors of inflation uncertainty and its transmission mechanisms affecting the dual engines of domestic demand-consumption and investment-have become increasingly intricate. This necessitates enhanced precision in identifying inflation uncertainty and evaluating its impact on domestic demand, presenting novel requirements for policy formulation and academic research.
Research Content: First, based on a high-dimensional price index system, this study constructs China's inflation uncertainty index from 2006 to 2022 using a Factor-Augmented Vector Autoregression with Stochastic Volatility (FAVAR-SV) model that incorporates factor volatility characteristics. Second, given the ambiguous nature of inflation uncertainty, we theoretically extend the real options model from known probability measure spaces to unknown probability spaces, exploring the transmission mechanisms and effects of inflation uncertainty on the dual engines of domestic demand—consumption and investment. Finally, drawing on theoretical insights, we employ a Time-Varying Parameter FAVAR (TVP-FAVAR) model to empirically investigate the dynamic impact of China's inflation uncertainty on these dual engines. All raw data utilized in the research are sourced from the WIND database, which is widely adopted by Chinese scholars.
Research Findings: First, the dynamic evolution of inflation uncertainty in China is closely linked to major economic disruptions such as financial crises and the COVID-19 pandemic. Since the outbreak of COVID-19 in 2020, inflation uncertainty has risen significantly without signs of abatement, though it remains lower than during the 2008 global financial crisis. Second, theoretical analysis reveals that the penalty effect and wealth value disturbances serve as transmission mechanisms through which inflation uncertainty influences consumption and investment decisions of economic agents. However, the strength of these transmission effects varies with shifts in macroeconomy. Third, empirical results align with theoretical conclusions. During periods of stable economic growth, the impact of inflation uncertainty on consumption and investment is relatively muted. In contrast, distinct inhibitory effects emerge after financial crises and during the “new normal” of economic development, with a notably intensified suppression effect observed in the post-COVID-19 era.
Policy Implications:First, although China is currently experiencing a low-inflation scenario, the increasingly volatile geopolitical and economic landscape—particularly the intensifying rivalry between China and the U.S. in finance, technology, and trade tariffs—is likely to amplify stochastic information shocks that drive inflation uncertainty. Policymakers should remain vigilant in monitoring the dynamic characteristics of inflation uncertainty. The measurement methodology proposed in this study can be adopted to establish and refine a more sensitive and precise inflation uncertainty monitoring system. Second, regulatory authorities should enhance communication with the public, improving the transparency of macroeconomic policies to guide the formation of rational inflation expectations. This approach would help mitigate economic agents' perceived uncertainty regarding future inflation at its source. Third, the intensity of domestic demand policies should be adjusted flexibly in response to macroeconomic conditions. During major economic disruptions—such as financial crises, the COVID-19 pandemic, and trade disputes—policymakers must ensure the timeliness and potency of demand-stimulating measures. Policy interventions should prioritize stabilizing wealth levels, including maintaining the value of assets such as stocks, bonds, and real estate, to counteract the negative effects of inflation uncertainty on domestic demand.
Research Contributions: First, this study advances the measurement of inflation uncertainty in the existing literature. By employing a FAVAR-SV model capable of accommodating high-dimensional price indicator systems, it addresses the information omission problem inherent in prior studies that rely solely on CPI volatility as a proxy. Furthermore, defining uncertainty through the volatility of latent common factors-which are inherently unobservable-resolves the limitation of GARCH-type models in filtering out predictable components from disturbance terms in price variables. Second, the paper refines the real options model, enhancing its applicability for analyzing economic agents' optimal decision-making under uncertainty shocks. Lastly, the findings not only provide a policy foundation for China's domestic demand expansion strategy but also contribute novel theoretical and empirical evidence to the study of macroeconomic uncertainty in the Chinese context.
Research Prospects: First, the digital economy era presents new opportunities to enhance inflation uncertainty measurement through big data and artificial intelligence, offering a novel methodological approach for more precise monitoring. Second, the heterogeneous impacts of high-, medium-, and low-level inflation uncertainty across regions, firm types, and household demographics constitute important avenues for future investigation.
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Received: 19 November 2023
Published: 05 April 2025
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