RMB misalignment: What does a meta‐analysis tell us?

Cheung, Yin‐Wong; He, Shi

doi:10.1111/roie.12593

Cited by 6 publications

(2 citation statements)

References 88 publications

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“…The time-varying importance of the potential drivers, which is indicated by the PIP, is plotted in Figure 6. We follow Cheung and He (2022) and treat the variables with a PIP larger than 0.5 or 0.75 as acceptably or substantially important variables.…”

Section: Drivers Of Connectedness From Cryptocurrencies To Energymentioning

confidence: 99%

Asymmetric volatility connectedness between cryptocurrencies and energy: Dynamics and determinants

Yang

Song

Zhang

et al. 2023

Front. Environ. Sci.

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We explore the dynamics and determinants of volatility connectedness between cryptocurrencies and energy. We employed a block dynamic equicorrelation model and a group volatility connectedness measurement to measure the cross-equicorrelation and volatility connectedness between cryptocurrencies and energy. We also adopted dynamic model averaging to identify the time-varying drivers. The results suggest that changes in cross-equicorrelation between the two groups were affected by influential global events and increased after the COVID-19 pandemic. Volatilities were transmitted in both directions between cryptocurrencies and energy, but the transmission from energy to cryptocurrencies is by far the strongest. The driver identification implies that the factors related to cryptocurrencies and global financial markets had important roles in explaining the volatility connectedness from cryptocurrencies to energy in some periods after the COVID-19 pandemic, but the effects were marginal. In contrast, factors such as electricity consumption, cryptocurrency turnovers, and VIX were important in affecting the volatility connectedness from energy to cryptocurrencies, and the effects depended on factors and changed over time.

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Section: Drivers Of Connectedness From Cryptocurrencies To Energymentioning

confidence: 99%

Asymmetric volatility connectedness between cryptocurrencies and energy: Dynamics and determinants

Yang

Song

Zhang

et al. 2023

Front. Environ. Sci.

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“…Furthermore, Hua (2020) highlights that the RMB was systematically undervalued between the periods of 1984 to 1993. More recently, Cheung and He (2022) employ Meta‐analysis on RMB misalignment and find a strong evidence that, China devalued its currency deliberately which result in a high growth of its holding of foreign reserves and persistent trade surplus of about 10% of GDP in 2008, as such, the probability of observing RMB undervaluation estimate for the period of 1998–2008 is high. Likewise, the authors discover a weak evidence that, the RMB undervaluation estimate for the period of 2009–2014 is probable to be found due to intensive international pressures for the valuation of RMB especially from the U.S.…”

Section: Introductionmentioning

confidence: 99%

An empirical investigation of the relationship between real exchange rate and innovation: Evidence from China

Wen

Usman

2023

Int. J Fin Econ

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The aims of this study is to investigate the relationship between real exchange rate and innovation in China for the period spanning from 1985 to 2020 using an annual time series data collected from different sources. The study employs autoregressive distributed lag bound test and other econometrics techniques to analyse the short‐run and long‐run relationship among the variables. The findings of the study reveal the existence of short‐run and long‐run relationship between real exchange rate (undervalued RMB) and technological innovation. Furthermore, real exchange rate (undervalued RMB) has positive effect on innovation while real exchange rate volatility is negatively affect innovation. Based on the above empirical findings, the study suggests some policy implications which are considered important for fostering rapid and sustainable economic growth.

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The “real” exchange rate regime in China since 2015′s exchange rate reform

Chen

2023

Asia and the Global Economy

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RMB misalignment: What does a meta‐analysis tell us?

Abstract: On January 1, 1994, China merged the official and swap exchange rates of its currency-the Renminbi (RMB) and replaced the dual-rate arrangement with a managed floating exchange rate

Cited by 6 publications

References 88 publications

Asymmetric volatility connectedness between cryptocurrencies and energy: Dynamics and determinants

Asymmetric volatility connectedness between cryptocurrencies and energy: Dynamics and determinants

An empirical investigation of the relationship between real exchange rate and innovation: Evidence from China

The “real” exchange rate regime in China since 2015′s exchange rate reform

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