Pregled bibliografske jedinice broj: 1141535
Calendar adjustments of retail time-series
Calendar adjustments of retail time-series // The 7th International Conference on Time Series and Forecasting - ITISE 2021
Kanarski otoci, Španjolska, 2021. (predavanje, međunarodna recenzija, neobjavljeni rad, znanstveni)
CROSBI ID: 1141535 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Calendar adjustments of retail time-series
Autori
Arnerić, Josip ; Čeh Časni, Anita ; Dumančić Kosjenka
Vrsta, podvrsta i kategorija rada
Sažeci sa skupova, neobjavljeni rad, znanstveni
Skup
The 7th International Conference on Time Series and Forecasting - ITISE 2021
Mjesto i datum
Kanarski otoci, Španjolska, 19.07.2021. - 21.07.2021
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
Time-series ; calendar adjustments ; retail trade
Sažetak
Fluctuations in economic activity are often influenced by calendar-based various factors. Such factors are non-working (non-trading) days, leap years, public holidays and the like. Most economic series are observed on a monthly or quarterly basis, but months (aggregated into quarters) are not comparable due to the different number of working and non-working days (different number of Mondays, Tuesdays, etc.). If the calendar effects are not properly adjusted, the identification of the ARIMA model for a given time series might not be correct, and the quality of seasonal adjustment is poor. An inappropriate calendar adjustment can generate false signals and negatively affect interpretation of adjusted data, which is particularly important for time series of retail sales and industrial productions. However, there is no general or unique procedure for correcting calendar effects in a pre-adjustment process of a time series. Therefore, this paper compares various regression models using alternative explanatory variables that take into account calendar effects and applied them to the time series of real retail trade turnover (RRT), i.e. monthly data observed from January 2000 to December 2019. The paper seeks to define a new explanatory variable (a regressor with time varying ratio between the average number of working days and the average number of non- working days) providing the most accurate correction of a RRT time series influenced by calendar effects.
Izvorni jezik
Engleski
Znanstvena područja
Ekonomija
POVEZANOST RADA
Ustanove:
Ekonomski fakultet, Zagreb