The Tourism Industry Association New Zealand (TIA) has recently released an array of regionally-tailored media releases in conjunction with its Tourism 2014 Election Manifesto. Although we welcome healthy debate on economic issues in regional New Zealand, we are dubious of the methodology used to estimate regional tourism employment and advise extreme caution beforeutilising any of the TIA’s regional data.
The TIA’s report generates extremely unusual results. For example, the Association claims that 15%of Upper Hutt residents’ jobs depend on the tourism industry, while only 9% of residents’ jobs in Queenstown-Lakes District depend on tourism. This result defies logic and an assessment of the TIA’s methodology suggests that it should be taken with a grain of salt.
The TIA uses Statistics New Zealand’s Tourism Satellite Account as a starting point for their assessment of regional tourism employment. Although it makes sense to begin with the TSA when looking at aggregate tourism employment in New Zealand, this is where our support for the TIA’s methodology ends.
The TIA uses flawed methodology to disaggregate the TSA’s national level tourism employment data into territorial authority level tourism employment. The Association disaggregates the data by using each territorial authority share of total national employment across all industries from the Census and then applying this share to national tourism employment in the TSA. The key problem with this crude method of decomposition is that these employment shares are unrelated to the tourism industry and can vary due to any number of reasons. For example, using the TIA’s method, if a 100% export-orientated firm decided to locate a factory in Upper Hutt that created 1,000 new jobs then a portion of these jobs would automatically be attributed to the tourism industry in Upper Hutt.
In contrast, when we calculate tourism employment in a territorial authority, we have an economic model that makes use of a range of data sources including the Tourism Satellite Account, guest nights, visitor expenditure data from MBIE, and Infometrics’ regional GDP estimates. As a result, variation in our modelling of tourism employment between regions is driven by regional-specific tourism data that contains actual information on visitor spending patterns and accommodation demand.