 Intervention analysis based on exponential smoothing methods: Applications to 9/11 and COVID-19 effectsByeongchan Seong and Kiseop Lee Economic Modelling, 2021, vol. 98, issue C, 290-301 Abstract: This study extends intervention analysis beyond the ARIMA models, which are currently used by most scholars and practitioners, to exponential smoothing models. This allows us to obtain the benefits of exponential smoothing modeling in analyzing time series with interventions. Exponential smoothing modeling allows for easier seasonal adjustments, and complex seasonality can be more readily incorporated into the analysis. In this study, we propose a method of intervention analysis based on exponential smoothing models through an innovational state-space model, and we obtain maximum likelihood estimates by maximizing the likelihood function of the state-space model. We analyze two applications: the 9/11 effect on U.S. airlines and the COVID-19 effect on the current population of Seoul, Korea. From the proposed method, we estimate the intervention effects and seasonal components in each series. This results in seasonally-adjusted time series with both intervention and seasonality removed. Keywords: Innovational state-space model; Seasonal adjustment; Holt-Winters method; Air traffic passenger miles; Current population (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:ecmode:v:98:y:2021:i:c:p:290-301 DOI: 10.1016/j.econmod.2020.11.014 Access Statistics for this article Economic Modelling is currently edited by S. Hall and P. Pauly More articles in Economic Modelling from Elsevier |
Is your work missing from RePEc? Here is how to contribute.
Questions or problems? Check the EconPapers FAQ or send mail to .
EconPapers is hosted by the
School of Business at Örebro University.