Tourism statistics - update by Eurostat

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1 Advisory Committee on Tourism Brussels, 15 December 2015 Tourism statistics - update by Eurostat August Götzfried DG EUROSTAT, Unit G-3 Short-term statistics; tourism

2 Outline of the presentation Employment in tourism Press Release and Statistics Explained article published on 14/12/2015 First estimates for 2015 (accommodation statistics) Use of big data Global Forum on Tourism Statistics 2016

14/12/2015 First estimates for 2015 (accommodation

3 Employment in tourism Data obtained from a wide range of Eurostat sources: Labour force survey (LFS) Annual structural business statistics (SBS) Earnings and labour cost survey (SES/LCS) Data on: Absolute figures on employment in tourism industries (sectors of the economy heavily relying on tourism but not necessarily on tourism only) 12 million persons employed Characteristics of employment in tourism (here: accommodation, air transport, TO/TA accounting for 3.3 mio persons employed) Where to find? Fresh Statistics Explained article on the Eurostat website Press Release on 14 December 2015

tourism but not necessarily on tourism only) 12 million persons employed Characteristics of employment in tourism (here: accommodation, air

4 Employment in tourism Tourism employment proved resistant to the crisis Employment in total economy dropped between 2008 and 2014 Employment in tourism (esp. accommodation) grew by 4 to 5% 108 Persons employed by economic activity, EU-28, , (index 100=2008) Total economy Services(²) Tourist accommodation(⁴) Non-financial business economy(¹) Selected tourism industries(³)

accommodation) grew by 4 to 5% 108 Persons employed by economic activity, EU-28, 2008-2014, (index 100=2008)

5 Employment in tourism Nearly 60% are women 13% are younger than 25 years (economy: 9%) % female workers % aged 15 to 24 70% 14% 60% 50% 58% 12% 10% 13% 40% 30% 20% 36% 41% 8% 6% 4% 9% 9% 10% 2% 0% Non-financial business economy Services Core tourism industries 0% Non-financial business economy Services Core tourism industries

40% 30% 20% 36% 41% 8% 6% 4% 9% 9% 10% 2% 0% Non-financial business economy

6 Employment in tourism One in seven are foreigners (8% other EU, 6.5% non-eu) ¼ of accommodation workers is lower educated % of foreign workers 16% 14% 12% 14% 30% % lower educated 10% 8% 6% 8% 10% 25% 20% 15% 20% 19% 20% 25% 4% 10% 2% 0% Non-financial business economy Services Core tourism industries 5% 0% Non-financial business economy Services Core tourism industries 7% Air transport Accommodation 8% TA/TO

lower educated 10% 8% 6% 8% 10% 25% 20% 15% 20% 19% 20% 25% 4% 10% 2% 0% Non-financial business

7 Employment in tourism Higher share of part-time workers (24%) Less stable jobs: temporary jobs (21%) and lower seniority in the job (23% have less than one year) % with a part-time job % temporary jobs < 1 year seniority 30% 25% 25% 25% 20% 15% 10% 17% 22% 24% 20% 15% 10% 14% 15% 21% 20% 15% 10% 15% 18% 23% 5% 5% 5% 0% Non-financial business economy Services Core tourism industries 0% Non-financial business economy Services Core tourism industries 0% Non-financial business economy Services Core tourism industries

24% 20% 15% 10% 14% 15% 21% 20% 15% 10% 15% 18% 23% 5% 5% 5% 0% Non-financial business economy Services Core tourism industries

8 Employment in tourism Earnings (and labour cost) are lower in tourism but also big differences within the sector Hourly gross earnings (in euro) 23, ,1 14,4 12,1 9,5 12,9 0 Non-financial business economy Services Core tourism industries Air transport Accommodation TA/TO

earnings (in euro) 23,6 15 10 5 14,1 14,4 12,1 9,5 12,9 0 Non-financial

9 Employment in tourism Highly touristic regions have lower unemployment rates (as compared to the national average)

10 First estimates for 2015 (accommodation statistics) Nights spent at tourist accommodation across the EU grew by 2.8 % in 2015 (+ 75 million nights) Higher than 2014/2013 growth (1.2 %) Positive growth figures for 20 out of 28 Member States Inbound tourists: +3.3 % (+ 40 million nights) Domestic tourists: +2.4 % (+ 35 million nights)

8 % in 2015 (+ 75 million nights) Higher than 2014/2013 growth (1.

11 First estimates for 2015 (accommodation statistics) Record number of tourism nights spent Nights spent expected to reach 2.75 billion nights in 2015 Up by 20 % since 2009 (+ 465 million nights) Foreign guest nights up by 33% since EU-28, (index: 2000=100) Total nights spent Nights spent by non-residents Nights spent by residents

75 billion nights in 2015 Up by 20 % since 2009 (+ 465 million nights) Foreign guest nights up by 33% since 2009 140

12 Use of big data The ESS (European Statistical System) is exploring the use of Big Data sources for official statistics Tourism statistics is a very promising area of statistics with regard to using big data, for example: Tourism accommodation - capacity and occupancy Webscraping of booking websites for hotels or other types of accommodation (eg. airbnb), hotel chains, possibly monitoring a sample of smaller establishments and campsites Smart meters for holiday dwellings, second homes

accommodation - capacity and occupancy Webscraping of booking websites for hotels or other types of accommodation (eg.

13 Use of big data Flows of tourists (overnight trips, same-day visits) Mobile phone data Traffic loops (cars), reservation data (plane, long-distance train) Social media, web searches Expenditure Prices for tourism products (e.g. hotel prices, flight tickets) Payment card data (also as data source for physical flows) in combination with surveys Not everything can be retrieved from big data (e.g. purpose of trips, gender, age, detailed expenditure)

(e.g. hotel prices, flight tickets) Payment card data (also as data source for physical flows) in combination

14 Use of big data The tourism statistics system of the future? Now Exclusively based on household and business surveys Short term evolution Big data sources slowly becoming auxiliary information Mid term evolution Weight of surveys decreases in favour of big data Surveys no longer 'main source' but 'one of the sources' Longer term evolution Further 'replacement' of surveys New sources bring new statistics

becoming auxiliary information Mid term evolution Weight of surveys decreases in favour of big data

15 Use of big data Tourism related initiatives ESS pilot projects on big data Grant agreement involving a consortium of 20 countries Projects not directly linked to tourism, but methodological developments can serve future applications for tourism statistics Smaller scale initiatives Continuation of work with mobile phone data for tourism statistics (possibly a project for Belgium in 2016) Exploratory work on using Wikipedia page views as a source (pilot project on UNESCO World Heritage Sites closely linked to tourism?) Web scraping to collect data on capacity/occupancy of accommodation offered on internet platforms (e.g. via airbnb)

phone data for tourism statistics (possibly a project for Belgium in 2016) Exploratory work on using Wikipedia page views as a source (pilot project on UNESCO

Use of big data Wikipedia small test for Albania (2 World Heritage Sites) 160 140 120 100 80 60 40 20 sq non-sq Seasonal index (per year) for Albanian versus all other page languages: inverse pattern

16 Use of big data Wikipedia small test for Albania (2 World Heritage Sites) sq non-sq Seasonal index (per year) for Albanian versus all other page languages: inverse pattern for summer months Analysis of page views by language Albanian (sq) versus all other languages Reveals an inverse seasonal pattern for Albanian visitors of Wikipedia (and visitors of the attractions?) 0 janv févr mars avr mai juin juil août sept oct nov déc janv févr mars avr mai juin juil août sept oct nov déc janv févr mars avr mai juin juil août sept oct nov déc janv févr mars avr mai juin juil août sept

seasonal pattern for Albanian visitors of Wikipedia (and visitors of the attractions?

17 Use of big data airbnb data found online (insideairbnb.com), e.g. Brussels 4900 listings 65% entire homes/apartments, 34% private rooms, 1% shared rooms Estimate for occupancy: on average 83 nights per year Estimate for price: on average 73 euro per night 35% of the listings are multi-listings (= one host having more than one offer, so most likely a commercial activity and not an occasional offer) Eurostat will explore further (airbnb and others) directly via the providers/platforms or indirectly using big data sources and methods. Objective: get an insight in the size per country and at EU level

Brussels 4900 listings 65% entire homes/apartments, 34% private rooms, 1% shared rooms Estimate for occupancy: on average 83 nights per year Estimate

18 Global Forum on Tourism Statistics 2016 The 14 th Forum will be hosted by Italy most probably in November 2016 (exact date to be confirmed) co-organisation with OECD and Eurostat Call for Papers to be launched at the end of January 2016 Please distribute to your contacts! Your input on relevant forum themes is certainly welcome (preparatory meeting Italy / OECD / Eurostat will take place on 12/01/2016) The Forum gathers tourism researchers from governments, the industry and academia as well as decision makers from businesses and the policy level. Don't miss it!

Your input on relevant forum themes is certainly welcome (preparatory meeting Italy / OECD / Eurostat will take place on 12/01/2016) The

19 Thank you for your attention!

Inbound Tourism: December 2014

Inbound Tourism: December 2014 30 January 2015 1100 hrs 021/2015 Total inbound tourist trips for December 2014 were estimated at 66,619, an increase of 1.4 per cent when compared to the corresponding month of 2013. Excluding the passengers