Trips of EU residents - annual data (tour_dem)

National Reference Metadata in Euro SDMX Metadata Structure (ESMS)

Compiling agency: Federal Statistical Office Germany


Eurostat metadata
Reference metadata
1. Contact
2. Metadata update
3. Statistical presentation
4. Unit of measure
5. Reference Period
6. Institutional Mandate
7. Confidentiality
8. Release policy
9. Frequency of dissemination
10. Accessibility and clarity
11. Quality management
12. Relevance
13. Accuracy
14. Timeliness and punctuality
15. Coherence and comparability
16. Cost and Burden
17. Data revision
18. Statistical processing
19. Comment
Related Metadata
Annexes (including footnotes)
 



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1. Contact Top
1.1. Contact organisation

Federal Statistical Office Germany
1.2. Contact organisation unit

Unit E 26 - Tourism
1.5. Contact mail address

Gustav-Stresemann-Ring 11, 65189 Wiesbaden


2. Metadata update Top
2.1. Metadata last certified 21/03/2024
2.2. Metadata last posted 21/03/2024
2.3. Metadata last update 21/03/2024


3. Statistical presentation Top
3.1. Data description

[Optional]
3.2. Classification system

Not applicable.
3.3. Coverage - sector

National tourism: domestic tourism and outbound tourism (trips made by residents of the reporting country).
3.4. Statistical concepts and definitions
3.4.1 Statistical concepts and definitions

See Regulation 692/2011, Delegated Regulation 2019/1681 and Methodological Manual for Tourism Statistics
3.4.2 Additional comments (e.g. country-specific deviations)
3.5. Statistical unit
3.5.1 Statistical unit 

Participation in tourism: the individual.

Tourism trips: the tourism trip with at least one overnight stay made by the individual.

Same-day visits: the SDV made by the individual.
3.5.2 Reporting unit One person in the selected household (within the age scope)
3.5.3 If other or additional comments, please specify

The following details refer to the main survey and not to SDV, if not otherwise indicated.
3.6. Statistical population
3.6.1 Statistical population

Participation in tourism: All residents aged 15 or over.

Tourism trips: All tourism trips of at least one overnight stay made outside the usual environment by the residents aged 15 or over.
3.6.2 Additional comments (e.g. deviating coverage in terms of age groups, multiple surveys with different subpopulation, inclusion of domestic same-day visits in years where this is not compulsory)

SDV collected by survey of Deutsche Bundesbank ("Reiseausgaben im Ausland")
3.7. Reference area

Entire territory of Germany
3.8. Coverage - Time

Coverage - Time [data comparable since (YYYY)]

3.8.1 Participation in tourism (Year)

2013
3.8.2 Tourism trips (Year)

1999 
3.8.3 Same-day visits (outbound) (Year)

2014
3.8.4 Same-day visits (domestic) (Year)

2018
3.8.5 Additional comments (e.g. longer series for subgroups)
3.9. Base period

Not applicable.


4. Unit of measure Top

Not applicable.


5. Reference Period Top

2022


6. Institutional Mandate Top
6.1. Institutional Mandate - legal acts and other agreements
6.1.1 European level

Regulation 692/2011, lastly updated by Delegated Regulation 2020/1569 https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A02011R0692-20200101 

Regulation 1051/2011, lastly updated by Regulation 81/2013 https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A02011R1051-20210808

Delegated Regulation 2019/1681
6.1.2 National level

There are no legal acts or other agreements on a national level.
6.2. Institutional Mandate - data sharing

Not applicable.


7. Confidentiality Top
7.1. Confidentiality - policy

The individual data collected are generally kept secret in accordance with Article 16 of the Federal Statistics Law (BStatG). Only in a small number of exceptional cases explicitly regulated by law may individual data be passed on. The names and addresses of the respondents are never passed on to third parties. Pursuant to Article 16, para. 6 of the Federal Statistics Law (BStatG), individual data may be passed on to institutions of higher education or other institutions entrusted with independent scientific research for the purpose of carrying out scientific projects, if such data have been anonymised in a way that identifying the relevant respondents or parties concerned would require an unreasonable effort in terms of time, cost and manpower. Persons receiving individual data are also obliged to adhere to the principle of confidentiality. 

https://www.gesetze-im-internet.de/bstatg_1987/__16.html
7.2. Confidentiality - data treatment

The collected individual information is protected under § 16 BStatG by using cell suppression.


8. Release policy Top
8.1. Release calendar

There is no release calendar.
8.2. Release calendar access

-
8.3. Release policy - user access

-


9. Frequency of dissemination Top

Annual


10. Accessibility and clarity Top
10.1. Dissemination format - News release

-
10.2. Dissemination format - Publications

-
10.3. Dissemination format - online database

https://www-genesis.destatis.de/genesis/online/link/tabellen/45413
10.4. Dissemination format - microdata access

-
10.5. Dissemination format - other

-
10.6. Documentation on methodology
  • Preparation and implementation of data collection: Random selection of landline and mobile phone numbers, telephone interviews on a random basis.
  • Data preparation: Imputation of failures and correction of implausible data.
  • Response time: Around 5-10 minutes per interview.
10.7. Quality management - documentation

The collection of statistical data is based on the quality standards of the Arbeitskreis Deutscher Markt- und Sozialforschungsinstitute e.V. (Working Group of German Market and Social Research Institutes). (ADM). Data collection and processing is completely documented. Pretests and test data are used to rule out survey errors in the main study. The interviewers will be cared by a supervising team. This team is acquainted with the methodological requirements of the survey and the CATI survey technique (CATI = Computer Assisted Telephone Interview). 

See annex (in German): "Quality report on tourism survey": https://www.destatis.de/DE/Methoden/Qualitaet/Qualitaetsberichte/Gastgewerbe-Tourismus/tourismus-reiseverhalten.pdf?__blob=publicationFile


11. Quality management Top
11.1. Quality assurance

Our data provider uses its own testing tools for pretesting the data quality.
11.2. Quality management - assessment
11.2.1 Main strengths

Minimized undercoverage of the target population due to the dual-frame approach.
11.2.2 Main weaknesses

The sampling size is very low regarding the overall population. Therefore the bias could be rather high in some cases.

Overcoverage in frame for cell phone users aged 14 years and less.
11.2.3 Quality improvements compared with previous reference year

No modification


12. Relevance Top
12.1. Relevance - User Needs
12.1.1 European level

See: Regulation 692/2011, lastly updated by Delegated Regulation 2020/1569 https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A02011R0692-20200101 
12.1.2 Main users on a national level

The primary users of the results are the Federal and State Ministries responsible for tourism. They use the figures to make policy decisions relating to tourism and for infrastructure planning. They are also used by local, regional and national tourist organisations, associations and interest groups which use the results for advertising in the field of tourism and for market research. In the educational sector, school pupils and students constitute an important user group. In depth discussion with representatives of the most important user groups (associations, public authorities, institutes) takes place every two years in the specialist ‘Travel and Tourism Statistics’ committee. Ad-hoc questions from individual users are also answered through the divisional information service. 
12.2. Relevance - User Satisfaction

[Optional]
12.3. Completeness
12.3.1 Completeness

Compliant with the requirements of Regulation on tourism statistics 692/2011, Delegated Regulation 2019/1681, as well as recommendations laid down in the Methodological Manual for tourism statistics.
12.3.2 If not, please specify why and list deviations from Reg.


13. Accuracy Top
13.1. Accuracy - overall
  • An unclustered probability sample of randomly generated (RDD) telephone numbers is used. The sample probability can be calculated for each unit of the sample.
  • A dual-frame approach (landline telephone numbers and cell phone numbers) is used. Thus each unit of the population has a known sampling probability >0 (no coverage problem). This means that indeed all residents in private households do have either a landline phone or a cell phone. That does not apply for individuals in institutions, e.g. prisons and nursing homes.
  • A dual-frame weighting procedure was necessary, resulting in higher variance of the weighting factors (design effect) and thus in larger standard errors of population estimates.
  • The refusal rate is highest among expenditure variables (item non-response). Thus, these variables may be somewhat biased by item-non-response.
  • The unit non-response rate is 93%, the refusal rate is 46% of all eligible persons. However, a relevant part of the non-contacts might be ineligible units, what is unknown due to the RDD approach. To deal with systematic effects of non-response the data are calibrated.
  • Men and women aged 15-44 years are slightly underrepresented in 2022. Contrarily, individuals aged 45-74 years are slightly overrepresented. Also, single person as well as, less pronounced, two person households are somewhat overrepresented and 3 and more person households are somewhat underrepresented. Further, individuals living in big cities are slightly overrepresented. The weighting factors correct these deviations.
13.2. Sampling error

13.2.1 Sampling errors - indicators

Information on Sampling errors may also be provided in the attached file.  Estimated value Coefficient of variation
13.2.1.1 Participation in tourism for personal purposes: number of residents, aged 15 or over, having made at least 1 trip of at least 1 overnight stay (all age groups)

49762712

2.557%
13.2.1.2 Participation in tourism for personal purposes: number of residents, aged 65 or over, having made at least 1 trip of at least 1 overnight stay

9669416

4.540%
13.2.1.3 Tourism trips - Total number of trips

221691722

1.958%
13.2.1.4 Domestic trips

135068582

2.450%
13.2.1.5 Outbound trips

86623140 

2.833%
13.2.1.6 Private/Personal trips

191695483

2.065%
13.2.1.7 Professional/business trips

29996240

5.483%
13.2.1.8 Domestic trips spent at rented accommodation

83128554

2.673%
13.2.1.9 Domestic trips spent at non-rented accommodation

51940029

4.032%
13.2.1.10 Tourism trips - Total expenditure excluding durables and valuable goods

144151813521

3.093%
13.2.1.11 Expenditure on accommodation

60464259136

3.216%


13.2.2 Additional comments on sampling error

The coefficient of variation is given in %. The coefficients of variation are corrected for the survey design. cv for coefficient b: cv(b) = 100*SE(b)/b





 
13.3. Non-sampling error

13.3.1 Coverage errors

13.3.1.1 Over-coverage

Overcoverage for cell phone users aged 14 years and less. A dual-frame weighting approach is used to calculate the sampling probability correctly and to correct for the double sampling probability (to be part of the sample via Frame1 and Frame2): p(Frame1) + p(Frame2) - p(Frame1) * p(Frame2)  p(Frame1) depends on the number of target persons living in the (landline phone) household and the number of landline phone numbers of the household. p(Frame2) depends on the number of cell phone numbers used by the target person.
13.3.1.2 Under-coverage

No undercoverage due to the dual-frame approach.


13.3.2 Unit non-response for TRIPS dataset

  Unit non-response
13.3.2.1 Number of ineligible units/ elements

355067
13.3.2.2 Number of eligible units/elements

152082
13.3.2.3 Number of non-contacts

67658
13.3.2.4 Number of refusals

70675
13.3.2.5 Number of rejected questionnaires

778
13.3.2.6 Number of other types of non-response

2923
13.3.2.7 Total non-response (= sum of 13.3.2.3 to 13.3.2.6)

142034


13.3.3 Unit non-response rate

13.3.3.1 Unit non-response rate for TRIPS dataset (= 13.3.2.7 divided by 13.3.2.2)

93%
13.3.3.2 Unit non-response rate for PARTIC dataset

93%
13.3.3.3 Unit non-response rate for SDVOUT dataset

No information available
13.3.3.4 Methods used for dealing with/minimising unit non-response

Methods used for minimising unit non-response

  • Maximization of the return rate through argumentation against demur
  • contacting the telephone-numbers until a clear return-state is given
  • telephone-time until 9pm and after appointment

Methods used for dealing with unit non-response

Weighting procedure/Calibration is used: Generalized regression estimator (GREG). Auxiliary Variables:

  • Age group x Sex
  • Household size
  • Federal state
  • Categorized Municipality size


13.3.4 Item non-response

13.3.4.1 Item non-response

Overall Item non-response is very low on almost all variables. However, the item non-response rate reaches appreciable size on expenditure variables. The highest item non-response rate is 10,8% on the variable " F16_ver" (expenditures for transportation).
13.3.4.2 Methods used for dealing with/minimising item non-response

Since the item non-response rate is fairly low overall, no additional effort was made to further reduce the item non-response. Only among the expenditure variables the item non-response rate is appreciably high. Since culturally expenditure and income questions in Germany are difficult and do have high rates of refusals in all non-obligatory surveys, we do not see satisfactory methodological measures to further reduce the (already comparatively low) item non-response rate.

Therefore, hot-deck imputation using imputation classes is used to impute item non-response.


13.3.5 Additional comments on non-sampling error 

Non-response error:

No other types of non-response.

The refusal rate is highest among expenditure variables (item non-response). Thus, these variables may be somewhat biased by item-non-response.

The unit non-response rate is 93%, the refusal rate is 46% of all eligible persons. However, a relevant part of the very high proportion of non-contacts might be ineligible units, what is unknown due to the RDD approach. To deal with systematic effects of non-response the data are calibrated.

Men and women aged 15-44 years are slightly underrepresented in 2022. Contrarily, individuals aged 45-74 years are slightly overrepresented. Also, single person as well as, less pronounced, two person households are somewhat overrepresented and 3 and more person households are somewhat underrepresented. Further, individuals living in big cities are slightly overrepresented. The weighting factors correct for these deviations.

 

Imputation rate:

Field1=1.21%
Field2=0.55%
Field3=0.05%
Field4=0.84%
Field5=0.49%
Field6=0.45%
Field7=0.23%
Field8=0.23%
Field9=0.23%
Field10=0.23%
Field11=0.23%
Field12=0.49%
Field13=0.4%
Field14=0.42%
Field15=1.29%
Field16=0%
Field17=0%
Field18=0.56%
Field19=0%
Field20=0%
Field21=1.01%
Field22=0.23%
Field23=1.89%
Field24=10.76%
Field25=13.73%
Field26=8.52%
Field27=6.23%
Field28=0.77%
Field29=0%
Field30=0.89%
Field31=0%
Field32=0%
Field33=0%
Field34=0%
Field35=0%
Field36=0%


(in case of second survey please briefly describe 13.3.1-13.3.4 here)


14. Timeliness and punctuality Top
14.1. Timeliness
14.1.1 Participation in tourism

The data are disseminated in Germany through the Genesis database (https://www-genesis.destatis.de/genesis/online/link/tabellen/45413) in August.
14.1.2 Tourism trips

The data are disseminated in Germany through the Genesis database (https://www-genesis.destatis.de/genesis/online/link/tabellen/45413) in August.
14.1.3 Same-day visits (outbound)

The data (sample data or extrapolation results) are not disseminated in Germany.
14.2. Punctuality
14.2.1 Participation in tourism

-4
14.2.2 Tourism trips

-4
14.2.3 Same-day visits (outbound)

-4


15. Coherence and comparability Top
15.1. Comparability - geographical

No problems of comparability between regions
15.2. Comparability - over time
15.2.1 Participation in tourism

See 3.8.1

Data are comparable since 2012 (NUTS 0) only, because of the totally modified methodological approach with dual-frame approach (landline telephone numbers and cell phone numbers) after the change of the external data provider at the end of 2011. Until 2011 only landline telephone numbers have been considered.
15.2.2 Tourism trips

See 3.8.2

Data are comparable since 2012 (NUTS 0) only, because of the totally modified methodological approach with dual-frame approach (landline telephone numbers and cell phone numbers) after the change of the external data provider at the end of 2011. Until 2011 only landline telephone numbers have been considered.
15.2.3 Same-day visits (outbound)

See 3.8.3

Data are comparable since 2001.
15.3. Coherence - cross domain

We cannot make any comparisons with our supply side statistic, because of the totally different data collection approach. There are no references to other official statistics.
15.4. Coherence - internal

Not applicable.


16. Cost and Burden Top

Cost and burden are not systematically collected.


17. Data revision Top
17.1. Data revision - policy

Data set is the result of a randomised sample survey. Therefore a data revision is not applicable.
17.2. Data revision - practice

Data set is the result of a randomised sample survey. Therefore a data revision is not applicable.


18. Statistical processing Top
18.1. Source data

18.1.1. Source data

18.1.1.1 Source data

Randomised sample survey.
18.1.1.2 Name of data collection in national language

Erhebung statistischer Daten über das Reiseverhalten der in Deutschland ansässigen Bevölkerung
18.1.1.3 Name of data collection in English

Collection of statistic data about the travel behaviour of the population residing in Germany
18.1.1.4 Survey vehicle Stand-alone survey
18.1.1.5 If "Embedded in another survey", please indicate which other survey. In case both options were ticked, please describe here separately the approach for PARTIC, TRIPS, SDVOUT


18.1.2. Population frame

18.1.2.1 Population frame Dual frame: Generate random digit-dialing land and cell phone number
18.1.2.2 Update of population frame Annually
18.1.2.3 If other frequency or additional comments, please specify

The Frames are part of the ADM-Sampling-System for Telephone Surveys provided by the "ADM Arbeitskreis Deutscher Markt- und Sozialforschungsinstitute e.V."
18.1.2.4 Coverage errors of population frame
  • No undercoverage due to the dual-frame approach.
  • A dual-frame weighting approach is used to calculate the sampling probability correctly and to correct for the double sampling probability to be part of the sample via Frame1 and Frame2: p(Frame1) + p(Frame2) - p(Frame1) * p(Frame2). p(Frame1) depends on the number of target persons living in the (landline phone) household and the number of landline phone numbers of the household. p(Frame2) depends on the number of cell phone numbers used by the target person.


18.1.3. Gross sample size (year, individuals)

18.1.3.1 Gross sample size for trips (= 13.3.2.1 + 13.3.2.2)

Gross sample size:

  • Randomly generated landline phone numbers: 334718
  • Randomly generated cell phone numbers: 172431
  • Estimated 68% of the randomly generated landline numbers and estimated 77% of the randomly generated cell phone numbers are not valid telephone numbers.
18.1.3.2 Gross sample size for participation in tourism

Gross sample size:

  • Randomly generated landline phone numbers: 334718
  • Randomly generated cell phone numbers: 172431
  • Estimated 68% of the randomly generated landline numbers and estimated 77% of the randomly generated cell phone numbers are not valid telephone numbers.
18.1.3.3 Gross sample size for (outbound) same-day visits

Gross sample size: 

  • landline phonenumbers: ca. 90 000 per year as reported by Deutsche Bundesbank (BOP Statatistic)
18.1.3.4 Additional comments


18.1.4. Net sample size (year, individuals)

18.1.4.1 Net sample size for trips (= 13.3.2.2 – 13.3.2.7)

Net sample size: 10048 individuals in the year 2022.
18.1.4.2 Net sample size for participation in tourism

Net sample size: 10048 individuals in the year 2022.
18.1.4.3 Net sample size for (outbound) same-day visits

Net sample size: ca. 90000 individuals per year as reported by Deutsche Bundesbank (BOP Statistic)
18.1.4.4 Additional comments


18.1.5. Sampling design

18.1.5.1 Sampling design Random sampling
18.1.5.2 If other or additional comments (also when more than one options is chosen in 18.1.5.1), please specify. Links to national methodology documentation can also be inserted here.
  • Frame 1: Landline phone numbers: Two-stage sample. Stage 1: Random selection of landline phone number, implicit stratification by Federal State x Municipality size categories. Stage 2: Random selection of a target person out of all target persons of the household.
  • Frame 2: Simple random sample of cell phone numbers.


18.1.6. Second survey or source

18.2. Frequency of data collection
18.2.1 Frequency of data collection Quarterly
18.2.2 Other frequency or additional comments
18.3. Data collection

18.3.1. Type of survey

Household survey


18.3.2. Data collection methods

18.3.2.1 Data collection methods CATI (computer-assisted telephone interview)
18.3.2.2 If other or additional comments, please specify. In case a combination of data collection methods is used, please give an indication of the importance of the different methods (in terms of number of respondents) 

Houshold CATI survey (CATI = Computer assisted telephone interviewing); last-birthday (LB) method of selecting respondents aged 15 years and older from within a sampled household in the landline sample; regular interviewer training obligatory
18.3.2.3 Questionnaire in national language (Annex/Link)

See the attached questionnaire in the Annexes below
18.3.2.4 Questionnaire in English (Annex/Link)

Not available
18.3.2.5 Interviewer instructions in English (Annex/Link)


18.3.3. Proxy interviews

18.3.3.1 Proxy interviews Never
18.3.3.2 If "Allowed" or "Only in exceptional cases", please indicate for which variables in particular proxy interviews were used (it not all questions); If 4. "Not applicable", please explain why.


18.3.4. Average interview time (The average interview time is X minutes.)

18.3.4.1 Average interview time

5,7
18.3.4.2 Average interview time for respondents that reported trips

9,66


18.3.5 Second survey or source


Annexes:
Questionaire in national language
18.4. Data validation
18.4.1 Data validation
  • Supervision during the telephone-interviews
  • Checking extreme values consistency by case analysis
  • Data editing according to Eurostat rules
18.4.2 Second survey or source (In case a second survey or source is used for collecting data on participation, trips or same-day visits, please briefly describe 18.4.1 here in relation to those surveys/sources)
18.5. Data compilation
18.5.1 Data compilation
  • Hot-Deck imputation using imputation classes; dual-frame probability weighting
  • Calibration using GREG
18.5.2 Second survey or source (In case a second survey or source is used for collecting data on participation, trips or same-day visits, please briefly describe 18.5.1 here in relation to those surveys/sources)
18.6. Adjustment

Not applicable.


19. Comment Top

[Optional]


Related metadata Top


Annexes Top