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| dc.title | MIDAS Modeling for Core Inflation Forecasting |
| dc.contributor.author | Libonatti, Luis |
| dc.contributor.orgunit | Department of Research and Chief Economist |
| dc.coverage | Argentina |
| dc.date.available | 2018-08-06T00:00:00 |
| dc.date.issue | 2018-07-31T00:00:00 |
| dc.description.abstract | 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 naïve 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. |
| dc.format.extent | 32 |
| dc.identifier.doi | http://dx.doi.org/10.18235/0001250 |
| dc.identifier.url | https://publications.iadb.org/publications/english/document/MIDAS-Modeling-for-Core-Inflation-Forecasting.pdf |
| dc.language.iso | en |
| dc.medium | Adobe PDF |
| dc.publisher | Inter-American Development Bank |
| dc.subject | Inflation |
| dc.subject.jelcode | C22 - Time-Series Models • Dynamic Quantile Regressions • Dynamic Treatment Effect Models • Diffusion Processes |
| dc.subject.jelcode | C53 - Forecasting and Prediction Methods • Simulation Methods |
| dc.subject.jelcode | E37 - Forecasting and Simulation: Models and Applications |
| dc.subject.keywords | Forecasting;Inflation;MIDAS |
| dc.type | Working Papers |
| idb.identifier.pubnumber | Working Papers |
| idb.operation | RG-T2426 |