Do Market Prices Improve the Accuracy of Inflation Forecasting in Poland? : a Disaggregated Approach
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. (original abstract)
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