Survey of tourist apartment occupancy

Instituto Nacional de Estadística

Monthly statistics on the activity of tourist apartments in Spanish territory registered as such on the corresponding Tourism Councils of the Autonomous Regions.

Definitions:

  • Tourist area:

    The group of municipalities in which there is an abundance of tourists. Information on the main areas of tourist interest is offered. In the document “List of municipalities included in each area” from INE, the main tourism áreas of interest are detailed, along with the municipalities that form these areas.
    Throughout the history of the EOH there have been changes to the territorial composition of tourism areas, such as the Barcelona coast. In January 2015 the municipalities making up the Costa Barcelona area were changed, meaning that data from before and after January 2015 cannot be compared.

  • Tourist site:

    Municipality with a significant tourist offer. Municipality with a significant concentration of tourism offer. The publication of the results meets statistical criteria according to the number of establishments in the sample that are located in the municipality and respond to the survey. In the specific case of hotels, responses from at least 8 establishments are required.

  • Value “Null”:

    This value appears on the map when filtering for “Tourism areas” or “Tourist points” and placing the cursor over an Autonomous Region that does not have any tourist areas or points.

  • Apartment :

    A tourist apartment (unit) is defined as a property that is rented out on a regular basis for the purpose of accommodation for tourists. A group of such units forms a tourist apartment establishment.

  • Estimated number of apartments :

    Estimated number of apartments belonging to tourism establishments or tourism operators, that are open on a seasonal basis.

  • Average annual variables:

    Annual average of the variables: estimated number of places, estimated number of apartments and employees: If selecting the filter for a full year, divide the aggregate annual data by the number of months to see the annual average of the variables.

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