Modelling the Relationship between Whole Sale Price and Consumer Price Indices: Cointegration and Causality Analysis for India
AbstractIn 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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Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 27333.
Date of creation: 14 Nov 2010
Date of revision:
CPI and WPI; Granger causality; cointegration VDs; IRFs.;
Find related papers by JEL classification:
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
- E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
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