Measuring Pattern, Amplitude and Timing Differences between Monetary and Non-Monetary Seasonal Factors of Tourism - the Case of Aruba
Seasonality is a frequent and important occurrence in the tourism industry, with simultaneous effects on both the volume and financial flows of tourism. The seasonal characteristics of these monetary and non-monetary tourism indicators can show diverging paths. Lack of synchronization between the seasonal patterns of these two types of indicators of tourism development can produce suboptimal situations, with less than best choices when formulating and implementing anti-seasonal policies. The purpose of this study is to measure pattern, amplitude and timing differences between the seasonal fact... Mehr ...
Verfasser: | |
---|---|
Dokumenttyp: | doc-type:workingPaper |
Erscheinungsdatum: | 2013 |
Verlag/Hrsg.: |
Amsterdam and Rotterdam: Tinbergen Institute
|
Schlagwörter: | ddc:330 / O11 / C13 / O29 / Y10 / Z18 / seasonality / Aruba / seasonal patterns / amplitude / timing / monetary and non-monetary tourism indicators |
Sprache: | Englisch |
Permalink: | https://search.fid-benelux.de/Record/base-28481279 |
Datenquelle: | BASE; Originalkatalog |
Powered By: | BASE |
Link(s) : | http://hdl.handle.net/10419/87387 |
Seasonality is a frequent and important occurrence in the tourism industry, with simultaneous effects on both the volume and financial flows of tourism. The seasonal characteristics of these monetary and non-monetary tourism indicators can show diverging paths. Lack of synchronization between the seasonal patterns of these two types of indicators of tourism development can produce suboptimal situations, with less than best choices when formulating and implementing anti-seasonal policies. The purpose of this study is to measure pattern, amplitude and timing differences between the seasonal factors of monetary and non-monetary indicators of tourism development in Aruba. The study contributes to the gap in the literature on the dynamics in the co-movement of these two types of seasonal factors, while concurrently incorporating three measurement dimensions of this relation. Moreover, the study introduces novel calculation techniques in two of the three measurement dimensions. The methodology involves decomposing time series on both monetary and non-monetary variables using Census X12-ARIMA, with subsequent calculation of Pearson’s correlation coefficients, median relative differences, and median timing differentials. The results show important quarterly differences in pattern, amplitude and timing of the seasonal factors, in terms of the applied timeframe, periodicity, variables and markets involved. The findings implicate the need for synchronizing strategies and a differentiated anti-seasonal policy.