Kunst, Robert M.ORCID: https://orcid.org/0000-0001-6831-2471 and Franses, Philip Hans
(2015)
Asymmetric time aggregation and its potential benefits for forecasting annual data.
Empirical Economics, 49, pp. 363-387.
https://doi.org/10.1007/s00181-014-0864-0
Abstract
For many economic time-series variables that are observed regularly and frequently, for example weekly, the underlying activity is not distributed uniformly across the year. For the aim of predicting annual data, one may consider temporal aggregation into larger subannual units based on an activity timescale instead of calendar time. Such a scheme may strike a balance between annual modeling (which processes little information) and modeling at the finest available frequency (which may lead to an excessive parameter dimension), and it may also outperform modeling calendar time units (with some months or quarters containing more information than others). We suggest an algorithm that performs an approximate inversion of the inherent seasonal time deformation. We illustrate the procedure using two exemplary weekly time series. (author's abstract)
Item Type: | Article in Academic Journal |
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Keywords: | Seasonality, Forecasting, Time deformation, Time series |
Former Research Units: | Divisions > All Research Groups > Old Former Research Groups > Former Departments (until 2015) > Department of Economics and Finance > Academic Research |
Date Deposited: | 29 Jan 2015 11:27 |
Last Modified: | 11 Feb 2025 03:45 |
DOI: | 10.1007/s00181-014-0864-0 |
ISSN: | 0377-7332 |
URI: | https://irihs.ihs.ac.at/id/eprint/2677 |