Testing purchasing power parity for the Renminbi-U.S. dollar rate: A time-varying factor-augmented analysis

Shu Wang, Jingyi Wang and Xinyao Wang

Central Bank Review, 2026, vol. 26, issue 2

Abstract: Purchasing Power Parity (PPP), a cornerstone of international economics, has undergone extensive empirical scrutiny and theoretical refinement since its inception. Despite its limitations, it remains a vital analytical framework. Historically, it provided benchmarks for exchange rate equilibrium during periods of monetary instability; today, it is instrumental for international comparisons by organizations like the United Nations and the International Monetary Fund (IMF), particularly in assessments such as the GDP comparison between China and the United States. This enduring relevance underscores the importance of rigorously testing its validity in contemporary contexts, especially for dynamically evolving economies like China. Aligning with modern methodological advances, this study moves beyond static tests by employing a Stochastic Volatility Time-Varying Parameter Factor-Augmented Vector Autoregression (SV-TVP-FAVAR) model. This dynamic framework is applied to empirically assess the validity of PPP for the Renminbi against the U.S. dollar (RMB/USD) from the first quarter of 1997 to the second quarter of 2025. The model's key strength lies in its capacity to capture evolving economic relationships while systematically incorporating a broad spectrum of macroeconomic information through latent common factors, thereby mitigating omitted variable bias. The extracted factors demonstrably track major real-world economic fluctuations, confirming their representative power. The selected sample period is comprehensive, encompassing pivotal events including exchange rate reforms, global financial crises, and recent health emergencies, which ensures the robustness and general relevance of the findings.

Keywords: Purchasing power parity; RMB/USD exchange rate; Time-varying model; SV-TVP-FAVAR (search for similar items in EconPapers)
Date: 2026
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