Academic journal article Journal of the Statistical and Social Inquiry Society of Ireland

Extending Supply Side Statistics for the Tourism Sector: A New Approach Based on Linked-Administrative Data

Academic journal article Journal of the Statistical and Social Inquiry Society of Ireland

Extending Supply Side Statistics for the Tourism Sector: A New Approach Based on Linked-Administrative Data

Article excerpt

INTRODUCTION

Tourism activity is a complex, demand driven, phenomena. The tourism sector, as defined by the 2008 International Recommendations for Tourism Statistics or IRTS (United Nations Statistics Division, 2010), reflects this complexity by classifying a comprehensive but fragmented set of industries to tourism. This complexity poses challenges for many domains within official statistics as it requires a fine level of disaggregation of activity; the equivalent of ISIC (2) or NACE class level. (3) For many published series, at least in Ireland, this level of disaggregation is not available.

Tourism, as a sector, is also unusual or even unique in that the unit of analysis tends to be the customer or 'visitor' rather than the service provider or producer. In large measure this is a consequence of the complexity noted above. Tourism activity and consumption expenditure tends to be dispersed across a wide arc of industries: transport, accommodation, catering, retail, culture and sports. In some cases tourism expenditure occurs well before the trip begins and payment is often deferred until well after the trip and as a consequence it can be very difficult to measure properly. The net result is that traditional tourism statistics have put greater emphasis on demand side surveys (i.e. on the visitor rather than on the service provider) as many tourism industries would not naturally consider themselves as such, and are not in a position to distinguish tourist and non-tourist activity. As a result, there has been relatively less focus on supply side statistics, and here the emphasis has been on arrival and bed-night statistics at 'collective accommodation'.

For the reasons noted above, only two of the nine chapters in the 2008 IRTS are dedicated to supply-side and employment issues. (4) While this is understandable, it has meant that tourism statistics have become very sector specific and are consequently very difficult to compare with other economic sectors; 'arrivals' or 'bed-nights' do not mean much, and are not relevant, to anyone outside the tourism sector. The economic rationale for having a tourism sector is to provide jobs, generate incomes and profit and to support the national economy. Yet from a business or economy perspective the existing suite of tourism statistics say little about the overall performance of the sector. Equally, little is known or understood about the real contribution of tourism to national and regional economies (Kenneally and Jakee, 2012). This 'isolation' of tourism statistics was part of the reason why the UNWTO has invested so much effort in carefully developing the Tourism Satellite Accounts or TSA (United Nations and World Tourism Organisation, 2010) and ensuring their consistency with the UN System of National Accounts 2008 (United Nations Statistics Division, 2009) and the 6th and latest edition of the IMF Balance of Payments and International Investment Position Manual or BPM6 (International Monetary Fund, 2009). The TSA has put tourism on a comparable analytical footing with other economic sectors or industries from a macro-economic perspective, facilitating credible analyses and providing meaningful information to policy and decision makers.

At sub-national level, the challenges inherent in compiling national tourism statistics magnify. Not only can tourism not be identified owing to problems of sectoral disaggregation noted above, but furthermore, many of the sample sizes employed in traditional official statistical surveys cannot support sub-national breakdowns. Equally, the challenges of compiling a TSA multiply considerably below national aggregation (Frechtling, 2008; Jones, 2009; Jones et al, 2009). This poses a particular challenge for tourism as it is a very place specific or local phenomenon where the tourism product and the relative contribution to the regional economy can differ quite significantly from region to region.

There are however a range of data sources, not typically associated with tourism, already in existence from which a range of useful complementary tourism indicators can be derived that could overcome some of the challenges noted above, namely; structural business statistics (SBS), labour force surveys (LFS) and administrative and similar large public service datasets and structured commercial 'big data'. …

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