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• W3005684902 abstract "Abstract Tourism statistic data can is an important source for measuring touristic patterns. As this area became more and more dynamic with the globalisation process, business owners, business analysts, policy makers as well as researchers are highly interested in having accurate, reliable and diverse data on tourism in order to perform analysis. Seasonal adjustment presents a real challenge for all researchers that operate with data sources from tourism sector. Usage of time series presents both opportunities and may contribute to improvement of forecasting touristic specifics relaying on demand and supply side of seasonality phenomenon. However, seasonally adjusted data is viewed as major challenge for businesses operating in the touristic sector. The present research focuses on a methodology that includes monthly tourist data arrivals in Romania. The seasonal adjustment process is performed with JDemetra+ , both considering and excluding calendar effect. JDemetra+ is the software officially recommended by Eurostat for seasonal adjustment, being tested extensively by many experts in the field, from various organisations. The seasonal adjustment process pointed out promising and qualitative results, as no Easter and trading days effect were present, suggesting effect of calendar omission from the process. Our obtained results showed up significantly better results for the 5 years series span. The similarities for TRAMO-SEATS and X13 obtained results indicate that in order to minimise sensitivity and choose correctly between the two packages, further revisions may be considered. This paper provides an excellent starting point for further research aimed at improving data on tourism. The methodology tested in this research can be further improved and applied on other data regarding tourism." @default.
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• W3005684902 date "2019-10-01" @default.
• W3005684902 modified "2023-10-10" @default.
• W3005684902 title "Seasonal adjustment of tourism data for Romania using JDemetra+" @default.
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• W3005684902 doi "https://doi.org/10.2478/icas-2019-0002" @default.
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