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Do market prices improve the accuracy of inflation forecasting in Poland? A disaggregated approach

Author

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  • Łukasz Lenart

    (Narodowy Bank Polski, Economic Institute
    Cracow University of Economics, Department of Mathematics)

  • Agnieszka Leszczyńska-Paczesna

    (Narodowy Bank Polski, Economic Institute
    University of Lodz, Department of Econometrics)

Abstract

This paper investigates short-term forecasts of Polish year-on-year (y-o-y) inflation using current market data and a disaggregated month-on-month (m-o-m) consumer price index (CPI). We propose a model based on a set of multivariate exponential smoothing models (ESM in short) and a simple nonlinear switching model. To this end, the total m-o-m CPI is disaggregated to six COICOP (4-digit) components (with an approx. 25% contribution in the total CPI) and the remaining part of the CPI. To improve forecasts accuracy (in particular in nowcasting) for each COICOP we use the available current market data on electricity, gas, food and petrol prices. We investigate and test the forecasting accuracy of the models with market data against benchmark models (without market prices) in a pseudo real-time framework. Our findings suggest that for most of the m-o-m components, the models with market prices outperform the considered benchmark models that use CIOCOP data sets only.

Suggested Citation

  • Łukasz Lenart & Agnieszka Leszczyńska-Paczesna, 2016. "Do market prices improve the accuracy of inflation forecasting in Poland? A disaggregated approach," Bank i Kredyt, Narodowy Bank Polski, vol. 47(5), pages 365-394.
    • Handle: RePEc:nbp:nbpbik:v:47:y:2016:i:5:p:365-394
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    References listed on IDEAS

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    Cited by:

    1. Łukasz Lenart, 2017. "Examination of Seasonal Volatility in HICP for Baltic Region Countries: Non-Parametric Test versus Forecasting Experiment," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 9(1), pages 29-67, March.

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    More about this item

    Keywords

    inflation forecasting; multivariate exponential smoothing models; switching model; nowcasting; current market prices;
    All these keywords.

    JEL classification:

    • 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
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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