Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/267593 
Erscheinungsjahr: 
2021
Quellenangabe: 
[Journal:] Baltic Journal of Economics [ISSN:] 2334-4385 [Volume:] 21 [Issue:] 2 [Publisher:] Taylor & Francis [Place:] London [Year:] 2021 [Pages:] 184-204
Verlag: 
Taylor & Francis, London
Zusammenfassung: 
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.
Schlagwörter: 
autoregressive distributed lag model
disaggregated approach
food commodity prices
Inflation forecasting
labour costs
oil prices
JEL: 
C32
C51
C52
C53
E31
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