Artikel
Time series forecasting using a moving average model for extrapolation of number of tourist
Time series is a collection of observations made at regular time intervals and its analysis refers to problems in correlations among successive observations. Time series analysis is applied in all areas of statistics but some of the most important include macroeconomic and financial time series. In this paper we are testing forecasting capacity of the time series analysis to predict tourists' trends and indicators. We found evidence that the time series models provide accurate extrapolation of the number of guests, quarterly for one year in advance. This is important for appropriate planning for all stakeholders in the tourist sector. Research results confirm that moving average model for time series data provide accurate forecasting the number of tourist guests for the next year.
- Sprache
-
Englisch
- Erschienen in
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Journal: UTMS Journal of Economics ; ISSN: 1857-6982 ; Volume: 9 ; Year: 2018 ; Issue: 2 ; Pages: 121-132
- Klassifikation
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Wirtschaft
Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
- Thema
-
seasonality
trend
regression
forecasting
centered moving average
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Ivanovski, Zoran
Milenkovski, Ace
Narasanov, Zoran
- Ereignis
-
Veröffentlichung
- (wer)
-
University of Tourism and Management
- (wo)
-
Skopje
- (wann)
-
2018
- Handle
- Letzte Aktualisierung
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10.03.2025, 11:46 MEZ
Datenpartner
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Artikel
Beteiligte
- Ivanovski, Zoran
- Milenkovski, Ace
- Narasanov, Zoran
- University of Tourism and Management
Entstanden
- 2018
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