Modelling the Consumer Price and Producer Price Indices with Related Economic Variables

This research intends to assess the relationship between Consumer Price Index (CPI) and Producer Price Index (PPI) in Sri Lanka with the related macroeconomic variables such as Broad Money Supply, Imports, and Exchange Rate for the period of January 2014 to June 2021. The multivariate time series an...

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Bibliographic Details
Main Authors: De Silva, M.T.T.T., Mathugama, S.C., Jayasinghe, Bimali
Format: Conference Proceeding
Language:English
Subjects:
Broad Money Supply
Consumer Price Index
Data models
Economic indicators
Economics
Estimation
Exchange rates
Johansen co-integration
Predictive models
Producer Price Index
Stochastic processes
VEC model
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Summary:This research intends to assess the relationship between Consumer Price Index (CPI) and Producer Price Index (PPI) in Sri Lanka with the related macroeconomic variables such as Broad Money Supply, Imports, and Exchange Rate for the period of January 2014 to June 2021. The multivariate time series analysis methods and stochastic forecasting methods based on the Root Mean Square Error (RMSE) are engaged in the analysis. The log transformation is used to stabilize the variation of data in each variable. The Johansen co-integration test results confirmed that the Consumer Price Index, Producer Price Index, Imports and Broad Money Supply have a significant long run equilibrium relationship. In the long run, the Producer Price Index and the Broad Money Supply both have a positive effect on the Colombo Consumer Price Index, while Imports have a negative effect. The Vector Error Correction (VEC) model's short run estimation results show that the Producer Price Index, Imports and Broad Money Supply are weakly exogenous to the Consumer Price Index. The Akaike Information Criteria (AIC), Schwarz Criteria (SC) and F-statistics indicated a fairly good fit of the VEC model. The diagnostic tests of the VEC model proved that the residual assumptions of no serial correlation, no heteroskedasticity and multivariate normally distributed are satisfied. The RMSE evaluated by the stochastic forecast under the dynamic method revealed that the fitted model is validated to the test data set showing the actual CPI figures from July 2021 to December 2021 are in both the forecast upper and lower bounds.
ISSN:2691-364X
DOI:10.1109/MERCon60487.2023.10355449