Oil volatility–inflation pass through in China: Evidence from wavelet analysis

Xiang, Lijin; Zhang, He; Gao, Ke; Xiao, Zumian

doi:10.1016/j.egyr.2021.04.021

Cited by 18 publications

(9 citation statements)

References 39 publications

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“…Another strand of literature has substantially used the MWC and PWC methods to examine the level of coherencies (time and frequency dependence) on risk connectedness. For instance, Xiang et al (2021) found a positive pass-through from oil price volatility to in ation in China in the short run, but in the medium and long run, the pass-through persists over time. Choi (2022) found evidence of interdependence between the global geopolitical risks (GPR) and the volatility of stock markets indices of the three East-Asian countries (China, South Korea, and Japan) in the short run, and concluded that the connectedness between GPR and volatility a time dependence behavior.…”

Section: Literature Reviewmentioning

confidence: 99%

Did real economic uncertainty drive risk connectedness in the oil–stock nexus during the COVID-19 outbreak? A partial wavelet coherence analysis

Al-Shboul

Maghyereh

2023

Preprint

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The paper extends the literature by examining whether real economic policy (the business condition risk (ADS)) can derive the risk connectedness in the oil–stock nexus during the COVID-19 outbreak using the multivariate wavelet coherency (MWC) and partial wavelet coherency (PWC) methods. The wavelet methods allow to isolate the effect of different global risk indices (such as the US economic uncertainty index (EPU), the crude oil volatility index (OVX), and the geopolitical risk index (GPR)) on the level of risk connectedness. Based on the daily data for the period January 2018–December 2020, we find that very strong impact of real economic uncertainty indices on risk connectedness. This impact is time-varying and frequency-sensitive, and it exhibits event-specific patterns. We find stronger MWC and PWC between real economy uncertainty indices and risk connectedness at lower frequencies. However, during the coronavirus disease 2019 (COVID-19) crisis, higher coherencies are found at higher frequencies; conditional to the effect of each global risk factor (EPU, GRP, and OVX), we also find higher PWC between oil and equity volatilities at lower frequencies. This study provides useful guidance to regulators and portfolio risk diversifiers. JEL Classifications : G12; G15; G18 ; G01; F3; E44

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Section: Literature Reviewmentioning

confidence: 99%

Did real economic uncertainty drive risk connectedness in the oil–stock nexus during the COVID-19 outbreak? A partial wavelet coherence analysis

Al-Shboul

Maghyereh

2023

Preprint

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“…Also, another group has engaged the other traditional models. price and inflation at time-varying and depending on time-frequency using wavelet coherence methods (Su et al, 2020;Xiang et al, 2021). However, economists disagree on the specific effect of oil prices on inflation change.…”

Section: The Effect Of the Oil Prices On The Inflation Ratementioning

confidence: 99%

“…Santacreu and Labelle (2022) Additionally, several studies have investigated the effect of oil prices on inflation. (Cunado et al, 2015;Sek, 2017;Sharif et al, 2023;Xiang et al, 2021) Found a positive impact of oil prices on the inflation rate, while Su et al (2020) and Elsayed et al (2021) noted that an increase in oil prices has a negative effect. This impact was limited in other studies (Irz et al, 2013;Köse & Ünal, 2021).…”

Section: Introductionmentioning

confidence: 99%

The effect of the global supply chain and oil prices on the inflation rates in advanced economies and emerging markets

Mohammed

Tiwari

et al. 2023

Geological Journal

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This study investigates the effect of global supply chain pressures and crude oil prices on the consumer price index from October 1997 to February 2022 using panel linear and nonlinear autoregressive distributed lags (ARDLs, NARDLs). The results showed that the asymmetric effect of the global supply chain on the inflation rate is stronger when the supply chain increases than when it decreases in the long run for advanced economies and vice versa in emerging markets. A one standard deviation of the supply chain pressures has rebounded the inflation rate by about 1.7% and 0.71% for advanced economies and emerging markets, respectively. The findings establish that a 10 U.S. dollar increase in oil prices leads the inflation rate to rise by 0.1%–0.6% for all countries in the short run. However, the impact of the global supply chain index fits much better with the inflation rate than the oil prices in the short and long run, including the subprime crisis, such as the COVID‐19 outbreak, and the beginning of the Russo–Ukrainian conflict. Thus, the empirical results of the current study provide acumens for policymakers of advanced economies and emerging markets to consume green energy and make use of green technology and environmental innovations for counterbalancing the inflation issues induced by the higher rates of oil prices without halting the economic growth and sustainable development.

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“…The stock market may be identified as an indicator of economic performance. So many studies have been performed earlier (Khan et al, 2020;Wu et al, 2020;Khraief et al, 2021;Xiang et al, 2021) to investigate how the oil price impacts an economy. Hence, distributing the investment among different sectors will allow diversification of the portfolio and management of risk (Arouri et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

“…Magazzino et al (2021) used wavelet decomposition and "Granger Causality" to deal with Italy's economic growth concerning oil price. Xiang et al (2021) have used wavelet analysis to study the time-varying linkage between the inflation and fluctuation of oil prices in China. Most frequency-based (wavelet) studies have investigated overall economic activities, not sector-specific ones.…”

Section: Introductionmentioning

confidence: 99%

Analysing Time-frequency Relationship between Oil price and Sectoral Indices in India using Wavelet Techniques

Mandal

Datta²

2022

IJEEP

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Oil is considered an essential factor of any economy. This paper examines the time-varying correlation between oil price return, BSE SENSEX, and 14 sectoral indexes in India using multiscale wavelet decomposition and wavelet coherence analysis. The maximal wavelet discrete wavelet transform analysis shows a feedback relationship between 13 sectors at higher time horizons (dC4, dC5, and dC6). Based on the wavelet coherence plot, the oil price and sectoral index return show a high co-movement at 32 to 128 weeks. The wavelet coherence plot shows that the oil price and sectoral index return show a high co-movement during the period of Mar-May 2020 (especially during the period of financial crisis widely spread due to the COVID19 pandemic and nationwide lockdown notification announced by the Government of India). We discuss the implications of these studies in detail.

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Oil volatility–inflation pass through in China: Evidence from wavelet analysis

Cited by 18 publications

References 39 publications

Did real economic uncertainty drive risk connectedness in the oil–stock nexus during the COVID-19 outbreak? A partial wavelet coherence analysis

Did real economic uncertainty drive risk connectedness in the oil–stock nexus during the COVID-19 outbreak? A partial wavelet coherence analysis

The effect of the global supply chain and oil prices on the inflation rates in advanced economies and emerging markets

Analysing Time-frequency Relationship between Oil price and Sectoral Indices in India using Wavelet Techniques

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