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Montenegro: tourism time series plots

In this blog post graphic methods are used to describe tourism time series in Montenegro.

Two types of a line graph could be used to show changes in tourist demand over time. The first displays all three time series (total, domestic and foreign tourists) on a single graph. This graph shows the relative position of time series to each other. However, if the time series levels are disproportional in size then on this graph is difficult to spot patterns in time series.

The second graph displays each series on a separate panel. On such graph any persistent pattern related to trend or seasonal factors should be clearly visible.

Figure 1 shows line graphs of tourists arrival and overnight stay in Montenegro.

Montenegro tourism time series (same panel)
Figure 1. Montenegro tourism time series (same panel)

Similarly to tourism time series in Croatia, from Figure 1 is quite clear that the foreign tourists made a major contribution to total tourists arrival and overnight stay. While both total and foreign tourists arrival series show, as expected, almost identical seasonal patterns, this pattern is not clear for the domestic tourists arrival series because the level of this series is much lower than the levels of the remaining two series on this graph.

Figure 2 shows each tourism time series in Montenegro on separate panels.

Montenegro tourism time series (separate panels)
Figure 2. Montenegro tourism time series (separate panels)

Now on the graphs in Figure 2 we can see that the seasonal patterns of domestic and foreign tourists arrival and overnight stay are very similar. This observation could be confirmed after examining times series using the seasonal plots. Trends, as another feature of domestic and foreign tourists arrival and overnight stay series seem different. While foreign tourists time series display an increasing trend in the whole period, the domestic time series show an increase until 2015 and then some drop in the level of series. This might not be quite clearly visible on the graphs because the seasonal component dominates the time series. But, when the trend component is extracted, after decomposing time series into trend, season and residual series, then this feature of the trend will be more clearly visible.

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Zlatko Kovacic
Director of Wellington based My Statistical Consultant Ltd company. Retired Associate Professor in Statistics. Has a PhD in Statistics and over 35 years experience as a university professor, international researcher and government consultant.