Dynamic causality between PPI and CPI in China: A rolling window bootstrap approach

Abstract

The relationship between PPI and CPI is one of the hot spots in the study of macroeconomics. Taking China as an example, the paper tests dynamic causality between PPI and CPI during the period of 2000:M1-2019:M12. In view of structural mutations in time series variables, the bootstrap rolling-window causality test is applied to restudy the dynamic causal relationship. As a result, it exists bidirectional transmission mechanism between CPI and PPI, both positive transmission of PPI to CPI and reverse transmission of CPI to PPI. In addition to putting more emphasis on transmission mechanism and causality between PPI and CPI, formulation of macroeconomic policy needs to focus on the correlation between PPI and CPI, and then the government can implement more targeted measures, such as strengthening the comprehensive application of monetary policy and fiscal policy, further deepening the supply-side reform, optimizing the industrial structure to strengthen internal relationship between CPI and PPI.

International Trade Price Index: A Leading Indicator for Indonesia's Inflation?

“…However, from the model, it appears that only the variables LN_CPI(-2), LN_CPI(-3), LN_PPI, LN_PPI(-3), LN_PPI(-4), LN_WPI, LN_WPI(-1), and LN_WPI(-4) which has a significant effect on changes in inflation. The results of this study support the results of the study from Li et al (2019), Kara and Keskin (2021), Anggraeni and Irawan 2018), Meyer and Habanabakize (2018), Sun et al (2021), (Tiwari, 2012), (Ghauri, 2020;Mallick, Behera and Dash, 2020).…”

“…Anggraeni and Irawan (2018) also pointed out a one-way link between PPI and CPI. A two-way transmission mechanism between PPI and CPI has also been shown by Sun et al (2021). Longrun and short-run cointegration relationships between PPI and CPI were demonstrated by Meyer and Habanabakize (2018).…”

Do green innovation and financial globalization contribute to the ecological sustainability and energy transition in the United Kingdom? Policy insights from a bootstrap rolling window approach

“…The study overcomes the issue of parameter inconsistency by applying the short‐run and long run tests of parameter stability. The study employs SUP‐LR (supremum likelihood ratio), Mean‐LR (“mean likelihood ratio”), and EXP‐LR (“exponential likelihood ratio”) tests to determine the constancy of parameters in the short‐run (Shi et al, 2017; Sun et al, 2021; Sunday Adebayo et al, 2022). Likewise, in the VAR process, the Lc parameter constancy test, also known as the “Nyblom statistic,” is employed to determine the parameter constancy for the long run (Hansen, 1992; Nyblom, 1989).…”

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“…This third approach is validated by Nilcan (2023) for Turkey, Topuz et al (2018) for Turkey and England, Su and al. (2016) for Slovakia, Tiwari and Shahbaz (2013) for India, Cerquera-Losada et al (2018) for Peru, Akcay (2011) for Germany and Sun et al (2023) for China.…”