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Issues With A Chained-Type Price Index: An Analysis With The Producer Price Index

Author

Listed:
  • Deockhyun Ryu

    (Department of Economics, Chung-Ang University)

  • Cheolbeom Park

    (Department of Economics, Korea University)

Abstract

Regarding the recent switch from the fixed base price index to the chained-type price index in many countries, we examine important issues including the selection of the weight to produce more accurate chained-type price indices and to maintain statistical consistency in the time series of a price index in this study. We determine that the actual weight from year t-3 data better produces a more correct chained-type producer price index at t between two available methods of selecting the weights. This weighting method also provides generally better statistical consistency and stability for the chained-type producer price index. We also compare the MAE and RMSE of the price equations of the fixed base and chain indices. Both the unit root test and comparison of the model performance evaluation reveal no critical difference, thus confirming a stability over the two indices. In particular, the substitutability of the chain index for the fixed base index is highly obtained, regardless of the time horizon. Overall, we can confidently assert that the chain index provides a statistical consistency and stability over a fixed base index.

Suggested Citation

  • Deockhyun Ryu & Cheolbeom Park, 2011. "Issues With A Chained-Type Price Index: An Analysis With The Producer Price Index," Journal of Economic Development, Chung-Ang Unviersity, Department of Economics, vol. 36(3), pages 47-78, September.
    • Handle: RePEc:jed:journl:v:36:y:2011:i:3:p:47-78
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    References listed on IDEAS

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    1. Robert Engle & Clive Granger, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
    2. Elliott, Graham & Rothenberg, Thomas J & Stock, James H, 1996. "Efficient Tests for an Autoregressive Unit Root," Econometrica, Econometric Society, vol. 64(4), pages 813-836, July.
    3. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    4. Andrews, Donald W K, 1991. "Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation," Econometrica, Econometric Society, vol. 59(3), pages 817-858, May.
    5. Pesaran, M. Hashem & Schuermann, Til & Smith, L. Vanessa, 2009. "Forecasting economic and financial variables with global VARs," International Journal of Forecasting, Elsevier, vol. 25(4), pages 642-675, October.
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    JEL classification:

    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E01 - Macroeconomics and Monetary Economics - - General - - - Measurement and Data on National Income and Product Accounts and Wealth; Environmental Accounts

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