By Saskia Sassen
The 3rd variation of towns in an international economic system indicates how definite features of our turn-of-the-millennium flows of cash, details, and folks have ended in the emergence of a brand new social formation: worldwide towns. those advancements supply new aspiring to such furnishings of city sociology because the centrality of position and the significance of geography in our social global.
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Additional info for Cities in a World Economy
From a policy perspective, therefore, it is important to know whether an economic series is highly stable or not through time. For example, if the shock is a new policy, how long the policy would impact the variable has a significant weight during the decision process, or if the shock were a fluctuation in the exchange rates, the impact of it on supply and demand sides of an industry would change company policies or consumer behavior. For the purposes of this study if the inbound tourist series are stationary and, therefore, has little or no asymptotic autocorrelation, the number of inbound tourists would not affect the series behavior in the long run.
Some measures have been proposed and implemented since the 1990s about diversifying the tourism services or creating alternative tourism regions; however they seem to be insufficient to prevent seasonality and to spread the tourism activities throughout the year. Structural seasonality needs complex measures and complete actions to be dissolved. This structure seems to continue, unless the government and decision-makers successfully manage to apply appropriate measures. Therefore, fundamental changes such as large-scale incentives for alternative types of tourism, removal of permits to new holiday mass tourism investments, increasing prices of accommodation services by enhanced quality in a peak season and so on, should be taken into consideration at once altogether.
For this purpose, the TRAMO/SEATS method is used and the resulting seasonally adjusted series are illustrated in Fig. 4. As seen in the figure, seasonality is filtered out, leaving only the three other components of a time series (trend, cyclical and random components) behind. The seasonally adjusted data is then subjected to traditional unit root testing procedures, where the null hypothesis is “the series has unit root”. 3. In the table, both tests are conducted with level and first difference series.
Cities in a World Economy by Saskia Sassen