The SHP data, the SHP LIVES Vaud data as well as the LIVES FORS Cohort data can be downloaded free of charge on SWISSUbase. All instructions can be found here.

You can find all the information about how to access the CNEF data here. The CNEF variables from the SHP can be downloaded here.

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 (swisspanel@fors.unil.ch).

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).

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.

Here you can find additional support for your data management using SPSS and Stata.

In addition to our website, we strongly encourage you to refer to the questionnaires and the user guide. The latter gives a good overview of the design and the implementation of the study and also documents the data extensively and describes the quality of 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.

The unique samples can be distinguished using the variable FILTER$$.

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).

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.

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.

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).

Information can be found here for the SHP LIVES Vaud and here for the LIVES FORS Cohort.

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.

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.

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.