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.

Language
Englisch

Bibliographic citation
Series: IDB Working Paper Series ; No. IDB-WP-897

Classification
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
Subject
MIDAS
Distributed lags
Core inflation
Forecasting

Event
Geistige Schöpfung
(who)
Libonatti, Luis
Event
Veröffentlichung
(who)
Inter-American Development Bank (IDB)
(where)
Washington, DC
(when)
2018

DOI
doi:10.18235/0001250
Handle
Last update
10.03.2025, 11:44 AM CET

Data provider

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Object type

  • Arbeitspapier

Associated

  • Libonatti, Luis
  • Inter-American Development Bank (IDB)

Time of origin

  • 2018

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