2019
DOI: 10.4236/ajibm.2019.96091
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The Casual Relationship between China’s Financial Stress and Economic Policy Uncertainty: A Bootstrap Rolling-Window Approach

Abstract: This study explores the causal relationship between China's financial stress and economic policy uncertainty. Considering structural changes in two series, we find that long-run nexus using full-sample data are unstable, suggesting that causality tests cannot be relied upon. Then, we employ a time-varying rolling window estimation to reexamine the dynamic causalities. The empirical results show that financial stress has both positive and negative impacts on economic policy uncertainty in several sub-periods, m… Show more

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Cited by 5 publications
(4 citation statements)
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References 30 publications
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“…According to Table 4, the change in green innovation significantly predicts the energy transition in the United Kingdom at a 10% significance level. The findings are similar to the study result of Li et al (2019) for OECD economies and Khan et al (2020) for G7 countries. These studies argue that green innovation drives energy, therefore, holding a significant causal association.…”
Section: Empirical Findings and Discussionsupporting
confidence: 92%
See 1 more Smart Citation
“…According to Table 4, the change in green innovation significantly predicts the energy transition in the United Kingdom at a 10% significance level. The findings are similar to the study result of Li et al (2019) for OECD economies and Khan et al (2020) for G7 countries. These studies argue that green innovation drives energy, therefore, holding a significant causal association.…”
Section: Empirical Findings and Discussionsupporting
confidence: 92%
“…For the full‐sample causality test, it has generally assumed that the VAR model parameters are consistent over time, whereas in reality, the parameters of VAR become inconsistent with the structural change. As a result, the predictive movements from one variable to another become unstable, and the outcomes derived from the full sample causality test are considered invalid (Balcilar & Ozdemir, 2013; Li et al, 2019). The study overcomes the issue of parameter inconsistency by applying the short‐run and long run tests of parameter stability.…”
Section: Data and Empirical Methodologymentioning
confidence: 99%
“…The bootstrap rolling-window approach is a statistical application used to overcome parameter nonconstancy by running the econometric model with partitions of full-sample via setting sub-sample windows. By selecting a sub-sample rolling window with K observations, the full sample with T observations can be altered to a series of T-K sub-samples, in other words, ψ-K+1, ψ-K, …, T for ψ=K, K+1, …, T (Li et al, 2019). In the dynamic analysis, the window size (K) is set as 100 trading days, and the window sliding is performed by shifting one trading day in each analysis.…”
Section: Resultsmentioning
confidence: 99%
“…Sun, Yao and Wang (2017) examine the dynamic interaction between EPU and financial stress under a multiscale correlation framework (Sun, Yao, and Wang 2017). Li, Zhang and Wang (2019) explore the causal relationship between EPU and financial stress in China by using a bootstrap rollingwindow approach (Li, Zhang, and Wang 2019). The uncertainty of economic policy has also been proved to be the determinant of financial risk and has corresponding predictive ability (Liu and Zhang 2015;Ma et al 2018;Fang et al 2018a;.…”
Section: Introductionmentioning
confidence: 99%