Feedback between Wholesale and Consumer Price Inflation: A Reexamination of the Evidence

Cushing, Matthew J.; McGarvey, Mary G.

doi:10.2307/1059891

Cited by 46 publications

(43 citation statements)

References 9 publications

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“…They document that variables are integrated at I (1) and cointegration for long run exists. Their results report that wholesale prices and consumer prices Granger-cause each other but causal relation is dominant from wholesale prices to consumer prices validating the hypothesis documented by Cushing-McGarvey (1990). Rao and Bukhari (2011) also examine the causal relation between wholesale price and consumer price indices by using month frequency data for the period 1978-2010.…”

Section: Literature Reviewmentioning

confidence: 66%

“…However, Figure 2 provides no evidence of Granger-causality from WPI to CPI at 5% level of significance at all levels of frequencies 7 . Though some business cycles are evident in the CPI at the intermediate level yet WPI does not show significant evidence of Granger-causality to CPI (with the only exception of the frequency level 1.4).…”

Section: Empirical Results and Their Discussionmentioning

confidence: 87%

“…This implies that unidirectional causality should run from wholesale prices to consumer prices. For example, Hatanaka and Wallace (1979), Engle (1978), Silver and Wallace (1980), Guthrie (1981), Colclough and Lange (1982), Cushing and McGarvey (1990), Clark (1995) and, Samanta and Mitra (1998) Shahbaz et al (2010) conduct a study to test the causality between wholesale prices and consumer prices. They document that variables are integrated at I (1) and cointegration for long run exists.…”

Section: Literature Reviewmentioning

confidence: 99%

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Does CPI Granger-cause WPI? New extensions from frequency domain approach in Pakistan

2012

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Abstract:The present study significantly contributes to the economic literature by investigating the direction of causality between WPI and CPI by applying frequency domain causality approach developed by Lemmens et al. (2008) based on spectral approach. We use monthly frequency data covering the period of 1961-2010 in case of Pakistan. Our results provide evidence of cointegration between the variables. Furthermore, we find unidirectional causal relationship running from CPI to WPI that varies across frequencies i.e., CPI Granger-causes WPI at lower, medium as well as higher level of frequencies reflecting long-run, medium and short-run cycles. This implies that CPI should be a leading indicator for important policy decisions pertaining to monetary or fiscal policies in Pakistan.

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Section: Literature Reviewmentioning

confidence: 66%

Section: Empirical Results and Their Discussionmentioning

confidence: 87%

Section: Literature Reviewmentioning

confidence: 99%

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Does CPI Granger-cause WPI? New extensions from frequency domain approach in Pakistan

2012

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“…Addition to that, author recommended that for bivariate model consisting of CPI and WPI simultaneous equation approach is the appropriate way to estimation. Cushing and McGarvey (1990) indicated that feedback from WPI to CPI is greater than that from CPI to WPI and therefore it can be concluded that WPI has high incremental power vis-à-vis CPI. Contrarily, Clark (1995) concluded that even though passthrough effect from producer prices to consumer prices is weak but causality is unidirectional that runs from WPI to CPI.…”

Section: A Brief Review Of Literaturementioning

confidence: 99%

“…Further, price of production inputs depends upon the domestic demand and domestic supply of the production inputs in one hand and imported inputs on the other hand which in turn depends upon the prices of the imported goods, the nominal exchange rate, the level of indirect taxes, the marginal cost of retail production and interest rates. Cushing and McGarvey (1990) 1 have developed theoretical basis for causal relationship running from wholesale price to consumers' prices. They argued that since primary goods are used as input with lag period in production process of consumption goods that's why wholesale prices will lead consumer prices independently.…”

Section: Introductionmentioning

confidence: 99%

Modelling the Relationship between Whole Sale Price and Consumer Price Indices: Cointegration and Causality Analysis for India

Tiwari

Shahbaz

2013

Global Business Review

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In this study we attempted to analyze the static and dynamic causality between producers' prices measured by WPI and consumers' prices measured by CPI in the context of India. We did our analysis in the framework of time series and for analysis, we applied ARDL bounds testing approach to cointegration and robustness of ARDL approach is examined through Johansen and Juselius (1990) maximum likelihood approach over the period of 1950-2009. We found the evidence of bidirectional causality between WPI and CPI in both cases i.e., in the short-run and long-run. Furthermore, outside sample forecast analysis reveals that in India, WPI leads CPI. This implies that WPI is determined by market forces and also a leading indicator of consumers' prices and inflation. This gives an indication to the Indian policy analysts to control for factors affecting WPI in order to have control on CPI since CPI is used for indexation purposes for many wage and salary earners including government employees and hence it will be helpful in cutting down the excess government expenditure.

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Forecasting CPI with multisource data: The value of media and internet information

Zheng,

Fan,

Jin

et al. 2023

Journal of Forecasting

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Using a large Chinese news corpus and Internet search data, we conduct an in‐depth out‐of‐sample forecasting study of Consumer Price Index (CPI) with the monthly macroeconomic database. For this purpose, we combine penalized regression and mixed‐frequency data sampling (MIDAS) methods to deal with the mixed‐frequency and high‐dimensional problems. Then we measure the time‐varying contributions of data from different sources and industries via dynamic model averaging. The results show that different types of data all provide enhancement in CPI forecasting, and the inclusion of media and Internet data further improves CPI forecasts' accuracy and timeliness due to their thorough coverage and fast update. In particular, the importance of alternative data is highlighted when the economy experiencing downturn or high uncertainty.

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Feedback between Wholesale and Consumer Price Inflation: A Reexamination of the Evidence

Cited by 46 publications

References 9 publications

Does CPI Granger-cause WPI? New extensions from frequency domain approach in Pakistan

Does CPI Granger-cause WPI? New extensions from frequency domain approach in Pakistan

Modelling the Relationship between Whole Sale Price and Consumer Price Indices: Cointegration and Causality Analysis for India

Forecasting CPI with multisource data: The value of media and internet information

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