Abstract
ABSTRACT This paper builds a short-term inflation projections (STIP) model for Latvia. The model is designed to forecast highly disaggregated consumer prices using cointegrated ARDL approach of [Pesaran, M., & Shin, Y. (1998). An Autoregressive Distributed Lag Modelling Approach to Cointegration Analysis. Econometric Society Monographs, 31, 371–413.]. We assess the forecast accuracy of STIP model using out-of-sample forecast exercise and show that our model outperforms both aggregated and disaggregated AR(1) benchmarks. Across inflation components, the forecast accuracy gains are 20–30% forecasting 3 months ahead and 15–55% forecasting 12 months ahead.
Highlights
Price stability is the ultimate goal of monetary policy in the euro area
In addition to global food commodity prices and domestic labour costs, some processed food prices are linked to the respective unprocessed food prices and nominal exchange rate developments
Higher car fuel prices translate to transportation costs, which indirectly increase consumer prices of food and some services (0.1 pp)
Summary
This paper develops a Short-Term Inflation Projections (STIP) model, which captures cointegrated relationships between highly disaggregated consumer prices and their determinants. We document a significant pass-through of domestic labour costs, crude oil and global food commodity prices to consumer prices in Latvia. We assess the model's forecast accuracy of Latvia's inflation during 2014–2018 and find that the STIP model statistically significantly outperforms a naïve benchmark model in real time
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