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Forecasting Inflation by Using the Sub-Groups of both CPI and WPI: Evidence from Auto Regression (AR) and ARIMA Models

Author

Listed:
  • Rizwan Raheem AHMED

    (Faculty of Management Sciences, Indus University, Block-17, Gulshan, Karachi, Pakistan)

  • Dalia STREIMIKIENE

    (Lithuanian Sports University, Institute of Sport Science and Innovations, Sporto str. 6, Kaunas, Lithuania)

  • Saghir Pervaiz GHAURI

    (Faculty of Economics & Management, The Jinnah University for women, 5-C, Block-5, Nazimabad, Karach-74600, Pakistan)

  • Muhammad AQIL

    (Faculty of Management Sciences, Shaheed Zulfikar Ali Bhutto Institute of Science & Technology, Block-5, Clifton, Karachi, Pakistan)

Abstract

The undertaken study is conducted to forecast the inflation of Pakistan for the financial year FY2018-19 using two different time series techniques. In this research, we used consumer price index (CPI) and wholesale price index (WPI) with their sub-groups as inflation indicators for Pakistan. The undertaken research analyzes the proficiency of two important econometrics time series approaches such as Autoregressive (AR) with seasonal dummies, and Autoregressive integrated moving averaged (ARIMA) models by using root mean square (RMSE) criteria. In any economy, inflation and its forecasting are an imperative factor for the fiscal and monetary policies. The study is pertinent, as the forecasted figures of inflation start before the FY2018-19, which helps the policy makers to set the inflation target for FY2018-19. The month-to-month data has been considered for this study for the period from July 2008 to June 2018, and this research is concentrated on forecasting for the year 2018-19. In order to forecast CPI, we use 12 sub-groups and for WPI we use 5 sub-groups in both baskets for the 2007-08 base year. The result of this study reveals that the forecasted value of period average of CPI for the period FY2018-19 is 6.23 percent, however, for WPI is 8.96 percent.

Suggested Citation

  • Rizwan Raheem AHMED & Dalia STREIMIKIENE & Saghir Pervaiz GHAURI & Muhammad AQIL, 2021. "Forecasting Inflation by Using the Sub-Groups of both CPI and WPI: Evidence from Auto Regression (AR) and ARIMA Models," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 144-161, June.
    • Handle: RePEc:rjr:romjef:v::y:2021:i:2:p:144-161
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    References listed on IDEAS

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    More about this item

    Keywords

    inflation forecasting; sub-groups of CPI; sub-groups of WPI; AR model with seasonal dummies; ARIMA model; RMSE technique;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies

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