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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Article
Temporal Disaggregation of Time Series Revisited
Author(s)
Erin M. Hodgess
Kendra Mhoon
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DOI:10.17265/2328-2185/2019.04.004
Affiliation(s)
Western Governors University, Salt Lake City, USA
University of Houston-Downtown, Houston, USA
ABSTRACT
With the benefits of
increased computing power and much improved software, temporal disaggregation is examined. Disaggregation,
the process of obtaining high frequency data from low frequency data has been
discussed for many years. This study examines three methods which utilize the
autoregressive integrated moving average (ARIMA) model in a simulation study
comparing parameter estimation, disaggregation mean square error, and forecast
mean square error. Finally, the three methods are applied to a real-world time
series.
KEYWORDS
disaggregation, aggregation, ARIMA
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