Arbeitspapier
MIDAS modeling for core inflation forecasting
A forecasting exercise is presented to assess the predictive potential of a daily price index based on online prices, compiled by web scrapping by the private company PriceStats in cooperation with a finance research corporation, State Street Global Markets, as a predictor for a measure of the monthly core inflation rate in Argentina, known as "resto IPCBA" and published by the Statistics Office of the Government 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 tested. Various classes of MIDAS models are found to produce a slight boost in terms of out-of-sample predictive performance at immediate horizons when compared to benchmark naïve models and estimators. Additionally, an analysis of intraperiod forecasts, reveals a slight trend towards increased forecast accuracy as the daily variable approaches a full month for certain horizons.
- Sprache
-
Englisch
- Erschienen in
-
Series: Economic Research Working Papers ; No. 72
- Klassifikation
-
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
-
MIDAS
distributedlags
coreinflation
forecasting
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Libonatti, Luis
- Ereignis
-
Veröffentlichung
- (wer)
-
Banco Central de la República Argentina (BCRA), Investigaciones Económicas (ie)
- (wo)
-
Buenos Aires
- (wann)
-
2017
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:42 MEZ
Datenpartner
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Libonatti, Luis
- Banco Central de la República Argentina (BCRA), Investigaciones Económicas (ie)
Entstanden
- 2017
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