The following questions and answers should help you with your research based on the SHP data. Between 2013 and 2019, the SHP was also involved in the associated studies SHP LIVES Vaud and LIVES FORS Cohort. The following information applies to all three studies.
How can I obtain the data?
How much does the data cost?
The data is available free of charge on SWISSUbase.
The SHP data is available free of charge for the entire research community.
However, you are required to cite the study correctly in all publications that are based on the SHP. Publications in paper or electronic form based on SHP data must carry the following mention: “This study has been realised using data collected by the Swiss Household Panel (SHP), which is based at the Swiss Centre of Expertise in the Social Sciences FORS. The project is supported by the Swiss National Science Foundation.” For more information, see Tillmann et al. 2016 and 2021. Tables and figures of publications based on SHP data in paper or electronic form must carry the following mention: “Source: Swiss Household Panel (SHP)”.
In addition, you are required to send a copy of your research output to the SHP (firstname.lastname@example.org).
Am I allowed to share the data with others?
No part of the data may be shared with any other person unless that person is an authorised user. An authorised user is someone who has signed the contract and has been granted access to the SHP. Individuals working on a research project together need to apply for the dataset separately.
I am teaching a course/seminar. Am I allowed to share the data with my students?
Yes, under certain conditions. You are responsible for ensuring that your students adhere to our data protection policy. You must also ensure that the dataset is appropriately disposed of once your course/seminar is over. In order to use the SHP data in a course/seminar, you must sign the “teaching contract” in addition to the usual user contract on FORSbase. If you are in any doubt about the use of the data in a teaching context, please enquire by e-mail to email@example.com.
What are master files (SHP_MP and SHP_MH)?
Master files are data files that contain time-invariant information such as the year of birth or the sex of the respondents. In addition, master files contain information on the respondents’ participation in each wave. You can match these data files with other data files using the identifiers idpers or idhous$$.
Despite its time-invariant character, the variable sex can be found not only in the individual master file (SHP_MP) but also in the annual individual data files (sex99, sex00, sex01 etc. in SHP$$_P_USER).
How can I merge several data files?
If you want to merge several data files (for example merging data from several years, combining individual and household information or combining data from couples/families), you can use the model syntaxes that can be found on SWISSUbase.
If you want to merge vertical biographic data files with horizontal individual data files, you can also find examples of syntaxes on SWISSUbase.
What is the best way to gain an overview of the SHP?
Which is the most appropriate method to analyse the data?
Our longitudinal analysis guide short introductions of different methods to analyse longitudinal data. It also provides coding examples and recommendations for further reading.
How can the unique samples of the SHP be distinguished?
The unique samples can be distinguished using the variable FILTER$$.
Why are there so many missing values in my data?
The data files always contain all individuals who are part of the samples and do not consider if they took part in the respective wave. Most of the missing values are due to household members who did not take part in the respective wave or who are under 14 years of age and thus not yet eligible for an individual interview. You can easily select only valid cases using the variables:
- STATHH$$ at the household level (where 1 = household questionnaire completed) and
- STATUS$$ at the individual level (where 0 = individual questionnaire completed).
Can I compare the data from the Swiss Household Panel with data from other countries?
The SHP is part of the Cross-National Equivalent Files (CNEF) as well as of the Comparative Panel File (CPF). More information can be found here.
Where is the best place to obtain information about the SHP survey weights?
What is the difference between cross-sectional and longitudinal weights?
If you use cross-sectional weights (at the individual or the household level), the weighted data refers to the respective year of the survey. Cross-sectional weights correct the data to reflect the distribution in the Swiss population with regard to characteristics such as age, sex and region in the respective year. If you use longitudinal weights (only possible at the individual level), weighted data refers to the Swiss population of the year when the sample was drawn (i.e. 1999 for the SHP_I, 2004 for the SHP_II, 2013 for the SHP_III, and 2021 for the SHP_IV). Further information regarding the use of weights can be found in the weights section.
Why do some cases have a weight of 0 or -3?
There are cases that have a weight of 0 or -3. This means that these individuals are disregarded when the data is weighted. This happens when an individual does not belong to the respective sample or does not have the necessary characteristics to be given a positive weight (for example if the respondent is too young).
Why do I sometimes obtain contradictory results when comparing different variables concerning, for example, the educational level of the respondents?
Contradictory results can occur when you compare information from different SHP questionnaires. For example, both the household grid questionnaire and the individual questionnaire collect information such as the educational attainment of household members. Both sources of information are included in the individual files. Mostly, this concerns the variables edugr$$, edgr$$ and occupa$$ that are gathered from the reference person of the household. If you compare this information with the information from the individual interview (educat$$, edcat$$, edu_1_$$, wstat$$, etc.) differences can occur. Information from the individual interview should always be given priority.
Which education variable should I use?
There are seven variables relating to the level of education in the individual data file. This sometimes leads to confusion about which variables should be used for analysis. We generally advise to use the constructed variables that combine data from the individual and the grid questionnaire: educat$$, edcat$$, isced$$ or edyear$$. For information about how these variables are constructed, please refer to the user guide.
Variables with one source of information:
- edgr$$: The information in this variable originates from the grid questionnaire. The reference person of the household indicates the highest level of education achieved for each member of the household (17 categories).
- edugr$$: Same as edgr$$, but with only 11 categories.
- edu_1_$$: The information in this variable originates from the individual questionnaire. The respondent indicates his or her own highest level of education achieved. This information is considered more reliable than the information provided by the reference person (grid questionnaire)
Constructed variables (two sources of information):
- edcat$$: This variable combines information from the individual questionnaire (ed_1_$$) and the grid questionnaire (edgr$$) whereby the individual interview is considered more reliable than the grid interview (17 categories).
- educat$$: This variable combines information from the individual questionnaire (edu_1_$$) and the grid questionnaire (edugr$$) whereby the individual interview is considered more reliable than the grid interview (11 categories).
- isced$$: Based on edcat$$, this variable re-constructs the International Standard Classification of Education (ISCED, 10 categories)
- edyear$$: Based on isced$$, this variable estimates the number of years based on the highest completed type of education.
Why does the SHP often use questions with answers on an 11-point scale?
The 11-point scale has proved successful in survey research because it provides participants with neither too many nor too few response categories. It makes it possible to differentiate between individuals and nobody is forced into a category due to insufficient availability of response alternatives. Therefore this type of scale improves the data quality. Moreover, such variables can be treated as continuous rather than ordinal during statistical analysis.
Further information can be found in Annette Scherpenzeel’s working paper.
Why is the SHP conducted annually?
The SHP is conducted annually for several reasons. First, respondents are better able to remember an event if it occurred recently. Second, an annual survey reduces the risk of confusing dates in between two waves of data collection. Third, it is important for panel surveys to have frequent contact with sample members to avoid attrition.
Further reasons can be found here.
Is it possible to add questions to the SHP questionnaire?
For the time being, the procedure regarding the possibility to introduce questions in the SHP is under review. Consquently, this possibility is suspended under further notice.