Arbeitspapier
MIDAS modeling for core inflation forecasting
This paper presents a forecasting exercise that assesses the predictive potential of a daily price index based on online prices. Prices are compiled using web scrapping services provided by the private company PriceStats in cooperation with a finance research corporation, State Street Global Markets. This online price index is tested as a predictor of the monthly core inflation rate in Argentina, known as "resto IPCBA" and published by the Statistics Office of the City of Buenos Aires. Mixed frequency regression models offer a convenient arrangement to accommodate variables sampled at different frequencies and hence many specifications are evaluated. Different classes of these models are found to produce a slight boost in out-of-sample predictive performance at immediate horizons when compared to benchmark näive models and estimators. Additionally, an analysis of intra-period forecasts, reveals a slight trend towards increased forecast accuracy as the daily variable approaches one full month for certain horizons.
- Sprache
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Englisch
- Erschienen in
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Series: IDB Working Paper Series ; No. IDB-WP-897
- Klassifikation
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Wirtschaft
Single Equation Models; Single Variables: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
Forecasting Models; Simulation Methods
Prices, Business Fluctuations, and Cycles: Forecasting and Simulation: Models and Applications
- Thema
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MIDAS
Distributed lags
Core inflation
Forecasting
- Ereignis
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Geistige Schöpfung
- (wer)
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Libonatti, Luis
- Ereignis
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Veröffentlichung
- (wer)
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Inter-American Development Bank (IDB)
- (wo)
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Washington, DC
- (wann)
-
2018
- DOI
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doi:10.18235/0001250
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:44 MEZ
Datenpartner
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Objekttyp
- Arbeitspapier
Beteiligte
- Libonatti, Luis
- Inter-American Development Bank (IDB)
Entstanden
- 2018