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Swiss Household Panel User Guide (1999 - 2012)

1. 41 5 1 4 Last job file This file contains information on the last job of all individuals who were a inactive at the time of their first interview and b interviewed in person or by proxy in any ofthe waves since 1999 The information on the last job is collected within the individual interview if the following three conditions are simultaneously met e The person is interviewed for the first time e The person does not currently work P W01 P WO2 and P W03 1 e The person has already worked in a regular way in the past P W07 1 The information on the last job may also be collected in a proxy interview if the following three conditions are simultaneously met e Itis the person s first proxy e The person does not work i e in the household grid G OCC 1 or 2 e The person has already worked for at least one year X W05 Because this information is collected only once it is not necessary to display it in the in dividual file in every wave The information is rather combined in a file last job com prising the variables of the individual questionnaire and the proxy questionnaire in which the wave identifier is renamed by SPSS or __ Stata SAS A separate variable LJYY indicates the wave in which the information is collected Note that if a respondent is not working at a given wave but has been working in any of the previous waves this information is not included in the last job file but in the pr
2. education EDUCAT EDUCAT EDUCAT Hierarchical level man agement supervision production P W34 P W34 P W34 P W34 P W34 Hierarchical level man agement supervision production P W117 P W117 P W117 P W117 P W117 Number of employ ees of self employed P W31 P W31 P W31 P W31 P W31 P W31 Number of employ ees of self employed P W114 P W114 P W114 P W114 P W114 P W114 status self employed employee etc P W29 P W29 P W29 P W29 P W29 status self employed employee etc P W112 P W112 P W112 P W112 P W112 gender SEX gender SEX 14 Please note that the Oesch Class Schema is not included in the dataset as a variable Rather the com mands in SPSS in SAS and in STATA are provided for users to construct the variable See http www swisspanel ch spip php rubrigque264 amp lang en login required 51 Table 5 3 7 Variables used for classifications for father s and mother s occupation Variable profession education Hierarchical Number of status self employed name level man employees employee etc agement su of self pervision employed production WRIGHT3 WASFAJ IS4FAJ P 017 P 016 P 014 P 013 WASMOJ IS4MOJ P O34 P 033 P 031 P O30 GOLDTHORPE GLDFAJ 1IS4FAJ P 016 P 014 P 013 GLDMAJ 1S4MOJ P 033 P 031 P 030 ESeC ESECFA IS3FAJ P 016
3. 5 4 1 Subjective well being indicators and scales There exists a wide range of methods to assess subjective well being Kahn and Juster 2002 Moreover there are several separable components of subjective well being Sub jective well being or quality of life often taken as synonyms in the literature take into account two different dimensions a cognitive dimension which includes the participant s evaluation of his life in general or of a particular important area of life health profes sional life financial situation for instance and an affective dimension of subjective well being which considers positive and negative affects such as joy hope optimism wor ries anxiety anger Diener 2000 Diener Suh Lucas and Smith 1999 The SHP includes one indicator that allows the measurement of general satisfaction with life Additionally there are different indicators that measure a wide range of domain spe cific aspects of subjective well being Finally measures of affective well being such as positive or negative affect are available Below our indicators of well being are listed 1 A general measure of subjective well being which reflects the satisfaction with life in general According to the literature this question measures a global state of the quality of life of an individual combining a cognitive perception and some degree of positive and negative affect Table 5 4 1 Satisfaction with life in general Variable Label Availabl
4. We have produced a variable OSM with three categories OSM child of OSM and cohabitant This variable might help to do analyses by subgroups and to help to understand why some individuals have a longitu dinal weight while others do not as only OSM receive a longitudinal weight New variables nationality by world regions REG_1 _ REG_2_ REG_3_ These variables represent a grouping of the variables concerning nationality by world regions The definition of the categories has been done on the basis of the nomenclature of the Federal statistical office The variables have the following categories Switzerland Northern Europe Eastern Europe Central Europe Western Europe South West Eu rope Southern Europe South East Europe Africa Northern America Latin America Asia Oceania and Antarctica New variable participation status RNPX Currently there are various sources of information concerning the participation status of an individual or a household The new variable RNPX offer a summary of the already available variables concerning partici pation status and consider furthermore comments coming from the interviewers that are not available to the users This new variable allows researchers distinguish between non contact refusal or non response due to death institutionalisation emigration fami ly related difficulties language problems or age or health problems or because the indi vidual left the household tempora
5. Graf E 2009 Pond rations du Panel suisse de m nages PSM_1 vague 9 PSM_II vague 4 PSM_1 et PSM_II combin s Nech tel Office F d ral de la Statistique Groves R M 2006 Nonresponse rates and nonresponse bias in household surveys Public Opinion Quarterly 70 646 675 Groves R M and Peytcheva E 2008 The impact of nonresponse rates on nonre sponse bias Public Opinion Quarterly 72 167 189 Grund C and Sliwka D 2006 Performance pay and risk aversion IZA Discussion paper series N 2012 1 13 Guggemos F and Till Y 2010 Penalized calibration in survey sampling Design based estimation assisted by mixed models J Statist Plann Inference 2010 doi 10 1016 j jspi 2010 04 010 Haferkamp H 1990 Sozialstruktur und Kultur Frankfurt am Main Suhrkamp 73 H pflinger F Charles M and Debrunner A 1991 Familienleben und Berufsarbeit Zum Wechselverh ltnis zweier Lebensbereiche Z rich Seismo International Labour Office 1990 International Standard Classification of Occupations ISCO 88 Geneva ILO John O P Naumann L P and Soto C J 2008 Paradigm Shift to the Integrative Big Five Trait Taxonomy History Measurement and Conceptual Issues In O P John R W Robins and L A Pervin Eds Handbook of personality Theory and research pp 114 158 New York NY Guilford Press Joye D and Scherpenzeel A 1997 Observation a long terme Projet de pane
6. 8 Lower technical occupations Skilled workers 9 Routine occupations Semi and nonskilled workers 10 Never worked and long term unemployed Unemployed The primary distinction in an employment relations approach is that between employers who buy the labour of others and assume some degree of authority and control over them self employed or own account workers who neither buy labour nor sell their la bour to others and employees who sell their labour to employers This classification was developed by a consortium of nine institutes from the UK Germany France the Netherlands Sweden Italy and Ireland See for more information http www iser essex ac uk research esec 54 Employees are further differentiated according to the employment relations of their oc cupation employers are separated by size of establishment and the self employed ac cording to occupation Broadly speaking the kind of contracts employees have depend upon a how easily their work may be monitored and controlled by the employer and b asset specificity i e how specific and crucial their knowledge of technical and organiza tional issues is to the employer When monitoring is difficult and asset specificity is high a service relationship will be typical labour contracts apply where labour is more easily replaceable in these terms A complete user guide of the ESeC can be downloaded here http Awww iser essex ac uk research esec user quide D T
7. 876 1 811 1 739 KA A 100 81 69 57 50 39 34 31 28 26 25 24 23 22 B 100 81 86 83 87 79 85 91 92 93 95 96 97 96 These percentages are calculated on the basis of the number of interviews conducted in the first year 1999 or 2004 These percentages are calculated on the basis of the number of interviews conducted in the previous year They may therefore exceed 100 Since 2006 the number of interviews increases in some waves due to various measures taken to convert households who were abandoned earlier because of double refusals SHP_I fully longitu dinal n 3 654 2 395 1 930 1 601 1 400 1 289 1 220 1 155 1 102 KA A 100 66 53 44 38 35 33 32 30 100 66 81 83 87 92 95 95 95 26 4 1 2 Attrition Not only response rates are decisive in assessing quality of the data Of crucial im portance is the extent to which nonrespondents differ from respondents on relevant characteristics As a result nonresponse can cause nonresponse bias in survey esti mates Behr et al 2005 Groves 2006 Groves and Peytcheva 2008 Hence the central concern in the analysis of attrition is selection bias because selection bias results in a distortion of the estimation results due to non random patterns of attrition To guarantee the quality of the data it is important to closely monitor the impact of attrition on the rep resentativeness of the longitudinal sample and how thi
8. FORS hosted by the University of Lau sanne 1 3 Use of the SHP When analysing the research domains reported by the SHP data users n 1404 we found that 2046 topics of interest were mentioned Figure 1 shows the relative im portance of the single topic categories given by the SHP research network members The category with the topics Labour Market Employment Income leads the table More and more common is the data use in seminars and courses 205 data users men tioned using the data in their classes Poverty Living Conditions Quality of Life Health Physical Activity and Life Course Adolescence Retirement Aging are also frequently researched topics In conclusion the analysis shows that the active data users of the SHP research net work cover a very broad spectrum of research domains This is a strong indication that the multidisciplinary SHP survey serves the research needs of a very diversified and in terdisciplinary academic community both nationally and internationally Figure 1 Areas of interest mentioned by SHP data users Labour Market Employment Income P Course Seminar Poverty Living Conditions Quality of Life Health Physical Activity Lifecourse Adolescence Retirement Aging Education Social Capital Culture Macro Econ Econ Policy Social Justice Social Security Survey Methodology Longitudinal Analysis Democracy Party Political Behaviour Working Conditions Work Life Arr
9. P 014 P 013 ESECMO IS3MOJ P 033 P 031 P O30 CSP CSPFAJ P 012 P 017 P 016 P 014 P 013 CSPMAJ P 029 P 034 P 033 P 031 P 030 TREIMAN TR1IFAJ IS4FAJ P 016 P 014 P 013 TRIMOJ IS4MOJ P 033 P 031 P 030 CAMSIS CAIFAJ P 012 CAIMOJ P 029 A The Wright class structure Wright III The classification presented here was developed several years after the first and second versions cf Western and Wright 1994 It was used in particular for the study of social mobility Its main advantage already present in Wright s second classification is based on three dimensions authority expertise and property These dimensions form seven categories instead of the twelve that Wright proposed in his second version The reduc tion from twelve to only seven cells obviously increases the cell counts and thus statis tical power A number of choices were made for the operationalization and adaptation of this sche ma a few of which are to a certain extent necessarily somewhat arbitrary 7 a Most cases of self employment were unproblematic In some cases we attribut ed this status to family members employed in their own family business as well as to those who considered themselves employees of their own enterprise b The demarcation between middle class and the petty bourgeoisie is often based on whether or not the respondent has employees Here by homogeneity with other classificat
10. Since the beginning in 1999 the fieldwork for the Swiss Household Panel SHP is done by M I S Trend in Lausanne and Bern www mistrend ch conducting computer assisted telephone interviews CATI in German French and Italian 3 1 Approaching the participating households The fieldwork is scheduled from September to February and starts with sending a letter to the participating households informing them about the upcoming interviews To make sure that the first personal contact by an interviewer follows shortly after the initial mail approximately one week later the letters are sent in three mailings with an interim of one week Enclosed with the preliminary mail participants receive a newsletter containing some results of recent analyses of the SHP data as well as an unconditional incentive for further information see 3 3 4 Households that did not respond since at least one wave are contacted at a later point in time also divided in three groups They are treated like households refusing in the cur rent wave as part of the refusal conversion procedure see also 3 3 3 3 2 Selection and training of interviewers and supervisors To guarantee smooth functioning of the fieldwork M I S Trend employs a large group of interviewers plus especially trained supervisors Before the start of the fieldwork inter viewers and supervisors participate in a training consisting of two sessions The supervisors training aims to prepare the su
11. T1P Weights expanded to the resident Swiss population households of current year wh T1S Weights expanded to the sample size of individuals in the households Note corresponds to the two last digits of the year in question One should note that the longitudinal weights make reference to the first year that is 1999 for the first panel and 2004 for the combined panel However it is generally better to use a slightly imperfect longitudinal weight which will at least take into account inclu sion probabilities and non response then none at all It is also important to keep in mind that the household weights can be used in two differ ent manners First they can be used for analyses on the household level using the household files An extrapolation thus makes reference to the total number of house holds in a given year If one constructs a dataset containing both individual and house hold level data one should pay attention to the fact that each household weight needs to be divided by the number of individuals of the respective household in order to get valu able results at the household level The reason for this correction is that by merging the individual files and the household files each individual receives the household weight The weight of each household is thus multiplied by the number of household members An extrapolation to the household totals would in this case represent the number of indi viduals instead of the number of ho
12. age category One should note that values for age 0 13 are used only for the household cross sectional weights and that the number of married individuals is not available for the longitudinal weight for SHP I Weights calibrated using totals of the first type were the first panel lon gitudinal weight and the cross sectional household weight The remaining weights were calibrated using the second type 4 2 2 Overview of current weights and their construction Currently four types of weights are produced a individual longitudinal weights b in dividual cross sectional weights c household cross sectional weights and d transi tional factors The current SHP weights are based on the initial weight POIDINIT which is the weight at baseline 1999 for SHP_I and 2004 for SHP_II In a given wave longitudinal re spondents original sample members are modelled for response at the level of the grid The method of modelling is segmentation Graf 2008 Segmentation separates the indi viduals into response homogeneity groups RHG based on variables that are strong in dicators of response The inverse of the grid response rate for each RHG is the adjust ment factor for the weight Specifically this adjusted weight is POIDINIT P_NRGRII _ T HRG where 7 pgg IS the response rate for the given RHG This adjusted weight becomes the basis for all of the wave specific weights The three types of weights are all determined using the
13. fieldwork 3 3 3 Refusal conversion Households that have not participated in the survey for one year or more have been re approached progressively These households are sent a preliminary letter with the re quest to take part in the next wave of data collection Only the most successful and spe cially trained interviewers are selected to contact these households Similarly house holds and individuals who refuse participation in the current wave are re contacted at a later point by refusal conversion trained interviewers 22 The refusal conversion rate calculated as the percentage of completed individual inter views on all eligible individuals who refused previously amounts to about 45 Lipps 2011 3 3 4 Contacting respondents To avoid household drop out of the panel because of unsuccessful tracing due to mov ing changed phone numbers household splits etc several measures ensure that con tact can be established with the respondents in new waves First the participating households are informed annually by means of a newsletter en closed with the advance letter at the start of each fieldwork phase In 2009 the SHP has started the use of tailored leaflets designed for specific groups of households families with children couples without children people living alone and people of 65 years and older The leaflets treat topics that inform targeted households about study results that are of interest to them The newslett
14. in the pro portion of the population considered poor or a rise in unemployment but not gross transitions e g the number of unemployed still without a job one year later The data collected from household panels supplies unique information allowing not only to esti mate gross transitions but also providing an understanding of the transitions observed i e the circumstances family events a change in the activity status heath events etc causing movements in and out of a given state e g the fact that a household or an indi vidual is living below a defined poverty line In other words by observing the same indi viduals over the course of time it is not only possible to study the change in numbers but also the flow of movements between the various states of being and to establish links of causality between different factors and events Moreover the SHP has two other main characteristics that increase its analytic potential First it is a comprehensive survey covering a broad range of fields and a variety of topics This makes the SHP a valuable source of information for studies in different disciplines and also allows for cross domain analyses To keep up with changes in the field the SHP occasionally modifies the ques tionnaire as well as adds new constructed variables to the dataset Periodically modules of questions are evaluated and if needed revised following feedback of experts in the field A major criterion for any changes
15. partner of reference person a P individual questionnaire wave specific H household questionnaire wave specific MP master file individuals MH master file households V interviewer file so social origin CA activity calendar LJ last job BH biographical file horizontal BV biographical file vertical gt Attention The values of the variable idint in the Interviewer data files have been coded in order to protect the identity of the Interviewers Consequently the merging of the Interviewer data with the Household and Individual level files is only possible after de coding Please contact Oliver Lipps for more details oliver lipps fors unil ch On www swisspanel ch under SHP Data there are examples of programming in SAS SPSS and Stata of how to combine different files such as matching respondents across waves matching respondents to households matching couples etc 5 8 Changing the language of the variable and value labels Variables and values labels are available for each data file in French German Italian and English The files containing the syntax are Variable labels SHP_ WAVE QUEST LANGUAGES txt Value_labels SHP_ WAVE QUEST LANGUAGES txt WAVES is to be replaced by W1 Wave 1 W2 Wave 2 W3 Wave 3 W4 Wave 4 W5 Wave 5 W6 Wave 6 W7 Wave 7 W8 Wave 8 W9 Wave 9 W10 Wave 10 WA Waves ALL modules CA LJ MP MH OS 70 QUESTS is to be replaced by P Indi
16. question of quality Evaluating survey questions by multitrait multimethod studies Dissertation Leidschendam Royal PTT Nederland NV KPN Research Scherpenzeel A Zimmermann E Budowski M Tillmann R Wernli B and Gabad inho A 2002 Experimental pre test of the biographical questionnaire SHP Working Paper 5 02 Neuchatel Swiss Household Panel Schuler M Dessemontet P and Joye D 2005 Die Raumgliederungen der Schweiz Neuchatel Bundesamt fur Statistik Schuman H and Presser S 1981 Questions and answers in attitude surveys Exper iments on question form wording and context New York Academic Press Spoerri A Zwahlen M Egger M amp Bopp M 2010 The Swiss National Cohort A unique database for national and international researchers International Journal of Pub lic Health 55 239 242 76 Srivastava S Gosling S D and Potter J 2003 Development of personality in early and middle adulthood Set like plaster or persistent change Journal of Personality and Social Psychology 84 5 1041 1053 Stewart A Prandy K and Blackburn R M 1980 Social Stratification and Occupa tions London Macmillan Strodtbeck F L 1958 Family interactions values and achievement In D C McClel land et al Talent and Society pp 135 194 Princeton Van Nostrand Tougas F Brown R Beaton A M and Joly S 1995 Neosexism plus ca change plus c est pareil Personal
17. rows in the file one for every job An index variable episode_nr is in cluded to preserve the order of the episodes of respondents The eight vertical domain files 1 Trajectory of residence GHP IL plot RE User Sau 2 Residence permit information GHP II plot DM User Sau 3 Cohabitation trajectory SHP_III_pilot_LA_user sav 4 Couple relationships and civil status SHP_III_pilot_CS_user sav 5 Family events GHP II plot EA User Sau 6 Educational trajectory GHP IL plot ED user sau 7 Professional activities SHP_III_pilot_PROF_ACT_user sav 8 Health SHP_III_pilot_HEA_user sav The three vertical subjective files 9 Couple relationships and civil status SHP_III_pilot_EV_CS_user sav 45 10 Family events SHP_III_pilot_EV_FAM_user sav 11 Education Professional activities SHP_III_pilot_EV_PROF_ACT_user sav 5 1 7 Interviewer files These files contain information gathered from the interviewers who conducted the SHP interviews by means of paper and pencil questionnaires In all waves except wave 1 3 and 4 the interviewers answered a short questionnaire The questionnaires measure a number of interviewer characteristics demographic traits such as sex age language and education but also characteristics such as the attitude of the interviewers towards this type of study and towards sensitive questions According to the SHP research inter ests the questionnaires have been changing over time Attention The values of the variable i
18. same methodology which combines segmentation and calibration using popu lation characteristics 4 2 2a Individual longitudinal weights Here the segmentation is done on the response to the individual questionnaire for longi tudinal respondents conditional on having responded to the grid no individuals are questioned before the grid is completed First a basic longitudinal weight is produced from P_NRGRIL in the same way as above equation 1 Second to produce the final 33 longitudinal weight this weight is calibrated to reflect the distribution in the population at baseline regarding sex by age category nationality and region from ESPOP STATPOP 4 2 2b Individual longitudinal weights A weight sharing is performed in households that have non original sample members non OSMs The weight share depends on whether the non OSMs were present at the moment the sample was selected SHP_I 1999 SHP_II 2004 By present we mean that they were eligible for selection into the panel lived in an independent household in Swit zerland at the time of the selection If they were present the weight is the same for all individuals of the household and is equal to 3 P_NRGRIL PTI PAR 2 I P where L is the number of longitudinal individuals and P is the number of non OSMis ini tially present If the non OSMs were not present at baseline the weights are P_NRGRIL for longitudinal individuals PTI_ PAR AP _NRGRIL 3 for non O
19. section of the Swiss Federal Statistical Office drew a simple random sam ple in each of the seven major statistical regions of Switzerland on the basis of the Swiss telephone directory SRH Stichprobenregister fur Haushalterhebungen or sam ple frame for household surveys This produced a sample of households that was rep resentative of the various social groups in all regions of Switzerland In order to compen sate for the erosion of the original 1999 sample deaths hospitalisation migration re fusals a refreshment random sample of households was injected in 2004 SHP_II fol lowing the same methodology The sampling frame was CASTEM Cadre de Sondage 11 pour le Tirage d Echantillons de M nages the follow up register of SRH which is owned by the Swiss Federal Statistical Office and also represents a telephone directory A second refreshment sample was injected in 2013 SHP_III This sample was drawn from the SRPH Stichprobenrahmen fur die Personen und Haushaltserhebungen which consists of data coming from the cantonal and communal register of residents and which is owned by the Swiss Federal Statistical Office As this sampling frame is on an individual basis the selection units of the SHP_III weren t households as it was the case for the SHP_I and SHP_II but individuals 2 2 2 Sampling plan The samples of SHP_I SHP_II and SHP_III are stratified by major geographic region NUTS II in proportion to the number of hous
20. the analysis to obtain appropriate esti mates of the variance For SAS users the recommendation is to rely on the survey procedures for example PROC SURVEYFREQ PROC SURVEYMEANS PROC SUR VEYREG PROC SURVEYLOGISTIC For STATA users the commands svyset and svy have to be used For SPSS users the module complex sample is needed 4 3 Data cleaning Consistency checks and corrections Before the data is released a few consistency checks are performed First the filters used in the questionnaire are checked In the rare occasions in which a filter was applied wrongfully a question was either asked when it should not have been or was not asked when it should have been In the first situation the answer to the question is deleted and the value is set to 3 not applicable see missing value conventions In the second situ ation a code of 7 is given filter error see missing value conventions Second the value range of all questions with restricted response categories is verified Values out of range are usually related to recoding mistakes and are corrected The val ue ranges of open questions are not scrutinized because setting a limit beyond which point values become highly unlikely is always arbitrary Third the households and their individual members are examined to make sure there is information on all household members and the number of household members adds up to the same number as in the household questionna
21. the study Scherpenzeel and Saris 1995 In addition the reasons why this type of scale is especially suitable for CATI are 4 Time saving The number production scales do not consist of lists of alternatives that all have to be read aloud in a telephone interview Instead only the first and end point are read aloud and respondents are asked to produce a response alternative themselves This takes considerably less time than reading lists of fully labelled categories 5 No response order biases Response alternatives presented at the beginning and end of a list may be more likely to be recalled and therefore perhaps selected more often When no visual aids are pre sented and when the list is long memory effects may be important Schuman and Presser 1981 The number production scales do not consist of lists of alternatives Instead only the first and end point are read aloud and respondents are asked to produce a response al ternative themselves Since CATI is exclusively oral verbal category scales are likely to suffer from the response order biases Therefore number production scales are more appropriate in CATI 20 CHAPTER 3 FIELDWORK This chapter provides information on how the fieldwork for the SHP is carried out Start ing with the selection and training of the interviewers we describe the whole process from how the participating households are approached to the measures taken to in crease response and quality control
22. the weights as described in the constructions above These weights should be used when looking for population totals The second is to maintain the sample size That is to say that the weighted sum of sample members is equal to the un weighted sum These weights should be used when running regressions particularly logistic regressions These weights differ by multiplication of a constant factor only Table 4 5 gives a list of the names of all the weight variables as they appear in the data sets Furthermore it de scribes their primary use One should note that resident refers to the non institutionalized population residing in Switzerland 35 Table 4 5 List of weights contained in the dataset variable names and description Types of weights Variable name Description Longitudinal weights SHP individuals wp LP1P Weights for longitudinal adults expanded to the resi dent Swiss population of 1999 wp LP1S Weights expanded to the sample size of longitudinal adults in the first panel SHP I and SHP II combined wp L1P Weights for longitudinal adults expanded to the resi individuals dent Swiss population of 2004 wp L1S Weights expanded to the sample size of longitudinal adults in the combined panels Cross sectional weights SHP I and SHP II combined indi wp T1P Weights expanded to the resident Swiss population viduals of current year wp T1S Weights expanded to the sample size of the com bined panels SHP I and SHP II combined wh
23. to the questionnaire is that it should not compro mise comparability of the data over time A second strong feature of the SHP is that all members of the households in the panel aged 14 years and over are interviewed This allows for intra household studies such as the study of mutual influence of household members attitudes and behaviour over time 1 2 Institutional Setting To date the SHP has experienced three main periods In its first phase 1998 2003 when it was created by the Swiss Priority Program Switzerland Towards the Future the SHP was a joint project run by the Swiss National Science Foundation the Swiss Federal Statistical Office and the University of Neuchatel At the end of the SPP Swit zerland Towards the Future the SHP entered its second phase 2004 2007 Still locat ed at the University of Neuchatel the SHP developed a joint venture project Living in Switzerland 2020 aimed at conducting the Statistics of Income and Living Conditions SILC pilot study 2004 2005 in collaboration with the Swiss Federal Statistical Office The SILC pilot data were distributed by the SHP until the end of 2008 During the whole period at the University of Neuchatel the SHP contributed to academic teaching The third phase of the SHP is linked to the integration into the Swiss Centre of Expertise in the Social Sciences FORS Since 2008 the SHP continues to be funded by the Swiss National Science Foundation and is part of
24. 11 6 2 930 58 108 1 476 58 95 4 406 2010 12 7 2 985 59 102 1 557 61 105 4 542 2011 13 8 2 977 59 100 1520 60 97 4 495 2012 14 9 2 968 58 100 1 493 59 98 4 461 These percentages are calculated on the basis of the number of interviews conducted in the first year 1999 or 2004 These percentages are calculated on the basis of the number of interviews conducted in the previous year They may therefore exceed 100 Since 2006 the number of interviews increases due to various measures taken to convert households who were abandoned earlier because of double refusals 25 Table 4 2 Number of persons validly interviewed in SHP_I and SHP_II 1999 2012 Year 1999 7 799 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 Wave ar WD 6 1 7 2 8 3 9 4 10 5 11 6 12 7 13 8 14 9 SHP_I n 7 799 7 073 6 601 5 700 5 220 4 413 3 888 4 091 4 630 4 494 4 800 5 057 5 103 5 032 KA A 100 91 85 73 67 57 50 52 59 58 62 65 65 65 Yr B 100 91 93 86 92 85 88 105 113 97 107 105 101 99 SHP II n 3 654 2 649 2 568 2 350 2 410 2 309 2 489 2 481 2 414 KA A 100 72 70 64 66 63 68 68 66 Yr B 100 72 97 92 103 96 108 100 97 SHP_I Il n 8 067 6 537 6 659 6 980 6 904 7 109 7 546 7 584 7 446 SHP_I fully longitu dinal n 6 335 5 429 4 480 3 888 3 076 2 622 2 399 2 209 2 060 1 952 1
25. 163 1 085 1 029 Persons responding in 6 335 5 429 4 480 3 888 3 076 2 622 2 399 2 209 2 060 1 952 1 879 1 813 1 739 current and all previous waves Grid level net response 64 91 88 86 90 82 91 87 86 91 91 94 93 93 rates Individual level net re 85 84 88 89 88 85 87 81 81 82 81 85 84 84 Source Swiss Household Panel 1999 2012 http www swisspanel ch The SHP proxy interviews include information about children under 14 years and adult persons unable to respond to the survey old age handicap etc Referring to all gross households minus those with neutral problems neutral problems invalid telephone etc Referring to all called individuals minus those with neutral problems foreign language etc 1 Note SHP_I denotes the original households recruited in 1999 Table 2 Participation in the Living in Switzerland Panel Survey 2004 2012 SHP_II Number of partici SHPI SHPI SHPI SHP H SHP H SHP Il SHP _II SHP H SHP _II pating units 2004 w1 2005 w2 2006 w3 2007 w4 2008 w5 2009 w6 2010 w7 2011 w8 2012 w9 Households with 2 704 1 908 1 754 1 548 1663 1 540 1 609 1 561 1 561 grids completed Household inter 2 538 1 799 1 684 1 494 1546 1 476 1 557 1 520 1 493 view completed Persons living in 6 569 4 673 4 276 3 777 3984 3 686 3 855 3 728 3 696 participating households Persons aged 14 5 376 3 8
26. 2003 ECHP UDB description of variables Data Dictionnary codebook and differences between countries and waves Eurostat http circa europa eu Public irc dsis echpanel library l user_db pan166200312pdf _EN 1 0 anda d Farago P 1996 Gesellschaftliche dauerbeobachtung im SP Zukunft Schweiz Demain la Suisse Swiss Priority Programme Switzerland towards the future Bern Swiss Na tional Science Foundation Frick J R Jenkins S P Lillard D R Lipps O and Wooden M 2007 The Cross National Equivalent File CNEF and its Member Country Household Panel Studies Schmollers Jahrbuch 127 627 654 Ganzeboom H B G and Treiman D J 2003 Three Internationally Standardised Measures for Comparative Research on Occupational Status In J H P Hoffmeyer Zlotnik and C Wolf Eds Advances in cross national comparison A European working book for demographic and socio economic variables pp 159 193 New York Kluwer Academic Press Garner W R 1960 Rating scales Discriminability and information transmission Psychological Review 67 343 352 Goldthorpe J H 1987 Social Mobility and Class Structure in Modern Britain Oxford Clarendon Press Goldthorpe J and Hope K 1974 The social grading of occupations Oxford Cla rendon Press Graf E 2008 Pond rations du PSM PSM_1 vague 8 PSM_II vague 3 PSM_1 et PSM_II combin s N 338 0054 Neuchatel Office F d ral de la Statistique
27. 3 of these households In 1999 at the time of the selection of the sample for the SHP_I the SRH s coverage rate was about 95 The sampling frame SRH and CASTEM are subject to the following errors e undercoverage some households were not listed in the directory at the time of selection This includes households whose numbers are not listed or households that could not be contacted by telephone This problem may produce a bias namely differences between the estimates based on the actually observed popu lation SHP survey and those that would have been observed based on the tar get population all individuals living in private households in Switzerland at a giv en time see Lipps and Kissau 2012 e duplicates despite meticulous checking of the SRH to ensure that only one num ber is kept per household some households appear more than once in the sur vey frame This problem results in wrong initial selection probabilities In spite of this a correction factor is not calculated for households with several telephone lines The information is available but the effect is negligible e overcoverage selection of units outside the target population businesses homes prisons collective households second homes It should be noted that for a panel this problem is only encountered at wave 1 and that these ad dresses are usually considered as out of sample non sample cases 13 The SRPH is updated every three months by the com
28. 3 from 2004 I WY I WY I EMPY I EMPY I INDY I INDY I AVSY I OASIY I OASIY AIY AIY I PENY I PENY I STPY I STPY I UNEY I UNEY I WELY I WELY I GRAY I GRAY I INSY I INSY 8 S Ss I FAMY I STFY I STFY I PIHY I PIHY I PNHY I PNHY I OSY I OSY I OSY I OSY 59 Household income There are two different ways of constructing household income Firstly in the household questionnaire reference persons are asked to estimate total household income sum of all household members Secondly in the individual questionnaire household members from 14 years of age are asked about their personal income Total individual income amounts corrected for within household transfers are then added to calculate house hold income The constructed variables on household income listed below represent the sum of individual income in two cases either if all individuals have answered the in come questions in the individual questionnaire or if the sum of individual income is larger than the household income from the household questionnaire In the other cases household income from the household interview is taken Only if household income is based on individual income adjustments are made for gross and net income To better assess the income situation of a household equivalised household income takes account of the household size and household composition by converting house hold income into income of one person households T
29. 45 3 500 3 123 3291 3 033 3 184 3 136 3 115 years and older eligi ble for individual in terviewing Personal interview 3 654 2 649 2 568 2 350 2410 2 309 2 489 2 481 2 414 completed Proxy Interviews 1 117 772 745 639 647 624 655 572 565 Persons responding Con 2 395 1 930 1 601 1400 1 289 1 221 1 157 1 102 in current and all pre vious waves Grid level net re 65 81 78 84 81 91 88 90 85 sponse rates 2 Individual level net 76 75 78 80 80 81 83 84 81 response rates Source Swiss Household Panel 1999 2012 http www swisspanel ch Note SHP_II stands for the newly recruited SHP households in 2004 80 Appendix C Attrition by demographic characteristics and social involvement Tables 1 and 2 below present demographic characteristics and social involvement atti tudes and behaviour of both samples of the SHP for respondents with different response patterns A selection is made of respondents who have participated in an individual inter view at least once and who have not left the panel i e not deceased institutionalized or out of the country A distinction is made between respondents who are interviewed in every wave those who are interviewed irregularly and those who dropped out of the panel this implies the respondent was not interviewed in the last three waves Note that calcu lations are based on unweighted data Significant differences are tested by calcula
30. At present the SHP comprises two samples drawn by the Swiss Federal Statistical Office the SHP_I the sample of households and individuals selected in 1999 and interviewed for the first time that year and the SHP_II the sample of households and individuals selected and interviewed for the first time in 2004 A third sample SHP_III was drawn in August 2013 by the Swiss Federal Statistical Office In a household panel information is collected at various levels household individual for which several questionnaires are used The SHP uses three types of questionnaires the household grid lasting less than 10 minutes the household questionnaire lasting 15 minutes on average and the individual questionnaire including a proxy questionnaire for those who are absent for a long period who are handicapped too ill to respond or younger than 14 years All individuals aged 14 or more living in the household are eli gible to answer the individual questionnaire lasting around 35 minutes 2 2 Sample design The SHP consists currently of three different samples SHP_I was drawn in 1999 GHP Um 2004 and GHP Im 2013 Because of the temporal differences there are also some distinctions in the respective sampling frames and the sampling plans 2 2 1 Sampling frame The first sample SHP_I is a stratified random sample of private households whose members represent the non institutional resident population in Switzerland In 1999 the methodology
31. CH Duration of residence in CH since Grid and individual questionnaire when G YCH P D164 49 5 3 2 Education Table 5 3 4 shows the constructed variables related to level of education This list does not include the original or recoded variables related to education For all available varia bles on education we advise to go to our website www swisspanel ch under Documen tation Search by domains select education Table 5 3 4 Constructed variables related to education in the individual files Variable Description Information used for construction name EE EDUCAT Highest level of education achieved From household grid and individual inter 11 categories view Individual interview considered more reliable EDCAT Highest level of education achieved From household grid and individual inter 17 categories view Individual interview considered more reliable 5 3 3 Work status occupation and social position Work status WSTAT is constructed from P WO1 working for pay last week P W03 have a job although not working last week and P W0O6 can start work im mediately from the individual questionnaire All social stratification measures presented below are based on the respondents occu pational titles which were carefully coded by the Swiss Federal Office of Statistics This Swiss specific code was then recoded into the International Standard of Classifica tion of Occupations ISCO 88 developed by the Internati
32. D Zug ZG Zurich ZH 78 Appendix B Participation in the Swiss Household Panel Table 1 Participation in the Living in Switzerland Panel Survey 1999 2012 SHP_I sponse rates Number of participat SHP_I SHP_I SHP_I SHP_I SHP_I SHP_I SHP_I SHP_I SHP_I SHP_I SHP_I SHP_I SHP_I SHP I ing units 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 w1 w2 w3 w4 w5 w6 w7 w8 w9 w10 w11 w12 w13 w14 Households with grids 5 074 4 532 4 314 3 685 3 289 2 918 2 526 2 580 2 893 2 793 3 052 3 065 3 055 3 032 completed Household interview 5 074 4 425 4 139 3 582 3 227 2 837 2 457 2 537 2 817 2 718 2 930 2 985 2 977 2 968 completed Persons living in par 12 931 11 67 11 11 9 537 8 478 7 517 6 491 6 587 7 225 6 905 7 469 7 477 7 450 7 274 ticipating households 8 6 Persons aged 14 years 10 293 9 297 8 942 7 553 6 719 5 976 5 220 5 333 5 972 5 740 6 224 6 286 6 335 6 229 and older eligible for in dividual interviewing Personal interview 7 799 7 073 6 601 5 700 5 220 4 413 3 888 4 091 4 630 4 494 4 800 5 057 5 103 5 032 completed Proxy Interviews 2 638 2 381 2 174 1 984 1 724 1 482 1 241 1 237 1 226 1 127 1 216 1
33. EUETENEISHERERTEEEENTERSULNELHEENERTORULUTTIRNSUNUERERTIERFOELUHLTRRONBENEFEHRTERER 58 5 3 6 Geographical information nn 61 5 4 References for psychosocial variables nn 63 5 4 1 Subjective well being indicators and ecales nn 63 5 4 2 Personality traits Big Five Inventory 10 BFI 10 en 65 5 4 3 ge de 66 5 4 4 Gender role attitudes nnnnneeeeeesete tetere retre rtetttttrtetetttttrttrrtrtrtneerernnnenee erene 67 5 4 5 Risk aversion scale nn 68 5 5 Missing value Conventons nennen 68 5 6 Imputation procedures nn 69 5 7 Combining data Tes were ec cvs taco cen re gr tee eters 69 5 8 Changing the language of the variable and value labels ne 70 R IGKENCES EE 72 Appendix A List of cantons in Switzerland eseesseseeeeeeeertntererrrerrerrrrnrenrererrrneene 78 Appendix B Participation in the Swiss Household Panel 79 Appendix C Attrition by demographic characteristics and social involvement 81 CHAPTER 1 INTRODUCTION 1 1 Aims and Analytic Potential The principal aim of the Swiss Household Panel SHP is to observe social change in particular the dynamics of changing living conditions and social representations in the population of Switzerland During the years 1998 2007 The Swiss Household Panel was a joint project run by the Swiss National Science Foundation the Swiss Federal Statistical Office and the University of Neuchatel Since January 2008 the SHP is part o
34. If monthly income has been indicated by respondents annual income is calculated using information from the number of months the respondent has received this income and from the activity calendar All constructed variables have passed a se ries of manual plausibility checks These checks involve typing errors unplausibly high income increases or decreases with respect to the last wave extreme income incon sistencies between the sum of income sources and total income and inconsistencies be tween individual and household income Details on income construction and plausibility checks are described in the documentation Collection construction and plausibility checks of Income Data in the Swiss Household Panel see www swisspanel ch under Documentation then Methods and then income or direct link http Awww swisspanel ch spip php rubrique133 amp lang en Individual income Table 5 3 10 List of constructed income variables of individuals Variable Gross net Description I EMPYG gross Income from employment annual amount I EMPYN net social Takes account of 13 and 14 month salary bonuses and grati security contributions de fications ducted I INDYG gross Income from self employment annual amount I INDYN net social se Takes account of 13 and 14 month salary bonuses and grati curity contributions de fications if applicable ducted I EMPMG gross Income from employment monthly amount I EMPMN net soci
35. Living in Gwitzerland nenn 8 1 7 Getting more information nn 9 CHAPTER 2 STUDY DESIGN 2 322 222 11 2 1 General design of the GHP 11 2 2 Sample design BEE 11 2 2 1 Sampling fame eaae aaa eaha ra ea Pedanta Reita aa e ia deae 11 2 22 Sampling Pla N eminii einen 12 2 23 COVOTAG EE 13 2 3 FONOWING TUES erie e er il 14 2 3 1 Initial rules governing contact with bousebolde 040 14 2 3 2 Initial rules governing the follow up of mdividuals renere 14 E En EE 15 2 4 1 Content of the questionnaires nn 15 2 4 2 Oe EU e e WE 17 2 4 3 Revised modules in Wave 14 and new constructed variables 18 2 4 4 Forthcoming new variables nn 18 2 4 5 The use of 11 point scales ern 19 CHAPTER3 FIEEDWORK ee rare ne 21 3 1 Approaching the participating householdS ernennen nn 21 3 2 Selection and training of interviewers and supervlsors 21 3 3 Measures to increase response nenn 22 3 3 1 Incentives for the Imterviewers nn 22 3 3 2 Incentives for the participating householdS nennen een 22 3 3 3 Refusal conversion E 22 3 3 4 Contacting respondents ann 23 3 4 Qu lity Conftrdls rsss Hemer Riem ee lg 23 CHAPTER A DATA QUALITY nn 24 4 1 Response rates and atton nennen 24 4 1 1 RESPONSE rate Snin ieee iiae orana a arena ae re een 24 AT ZAWOR EE 27 4 2 The weighting scheme of the GHP 30 4 2 1 Overview of fechnioues 31 4 2 1a Adjustments for non response ran 31 4 2 1b Generalized weight share method nn 32 4 2 1c Combination of multipl
36. Mayer K U 1991 Soziale Ungleichheit und die Differenzierung von Lebensverlaufen in W Zapf Ed Die Modernisierung moderner Gesellschaften Verhandlung des 25 Deutschen Soziologentages 1990 pp 667 687 Frankfurt am Main Westdeutscher Verlag McCrae R R and Costa P T 2003 Personality in adulthood A five Factor theory perspective NewYork The Guilford Press Merkouris T 2001 Cross sectional Estimation in Multiple Panel Household Surveys Survey Methodology 27 2 171 181 M ller H P and Schmid M 1995 Sozialer Wandel Modellbildung und theoretische Ans tze Frankfurt am Main Suhrkamp Noll H H 1998 Die Perspektive der Sozialberichterstattung in P Flora and H H Noll Eds Sozialberichterstattung und Sozialstaatbeobachtung pp 13 28 Frankfurt Cam pus Verlag Oesch D 2003 Labour market trends and the Goldthorpe class schema A conceptual reassessment Swiss Journal of Sociology 292 241 262 Oesch D 2006a Redrawing the Class Map Stratification and Institutions in Britain Germany Sweden and Switzerland Basingstoke Palgrave Macmillan 75 Oesch D 2006b Coming to grips with a changing class structure International Soci ology 21 2 263 288 Oesch D 2008 The changing shape of class voting An individual level analysis of party support in Britain Germany and Switzerland European Societies 10 3 329 355 Paugam S 2000 Le salari de la pr carit Les
37. SM initially absent L Once the weight sharing is done it is adjusted for non response to the individual ques tionnaire using segmentation The sample includes all individuals older than 14 living in households having responded to the grid and containing at least one longitudinal re spondent Finally the weight is calibrated on the estimated totals of sex by age national ity civil status and region for the year under consideration using data from ES POP STATPOP 4 2 2c Household cross sectional weights All members of a household are given the same weight The way the weights are shared is the same as in equation 2 where P may be equal to 0 Next this weight is adjusted by segmentation for non response to the household questionnaire Finally a calibration is done under the restriction that all members of the same household must have the same weight again using data from ESPOP STATPOP 4 2 2c Individual transitional factors Whereas the current longitudinal weights always refer to the first wave the transitional factors are useful for the development of custom made longitudinal samples It also allows for the longitudinal weighting of non OSMs One takes the waves of interest t t k Then the longitudinal weight for the sample of interest is longitudinal x cross sectional w transitional f transitional f x 34 Determining these factors is a two step process First segmentation is used to m
38. Table 5 4 13 Self perception Variable Question Available in waves P C70 Often it is not worthwhile to make plans because too W 11 W14 much is unpredictable P C71 feel like have little influence on the events of my life W 11 W14 P C72 easily overcome unexpected problems W 11 W14 P C73 In general have no difficulty choosing between two pos W 11 W14 sibilities P C74 At times think am no good at all W 11 W14 P C75 On the whole am satisfied with myself W 11 W14 Note PO9C72 P09C73 and PO9C75 are reversed in valence 5 4 4 Gender role attitudes A number of items measure gender role attitudes and perceived equality between men and women Both direct and indirect measures of attitudes are present in the SHP with measures at the individual and at the intergroup level 1 One item assesses the attitude toward traditional gender roles legitimacy in society Table 5 4 14 Opinion on family Variable Label Available in waves P D92 Opinion on family child suffers W04 W 13 with working mother 2 One item takes into account if an individual perceives work as a possibility to remain independent Table 5 4 15 Opinion on family Variable Label Available in waves P D91 Job preserves independence W04 W 13 3 Additionally the data include an item measured annually from 2002 till 2005 on how individuals perceive childbearing within cohabitation Table 5 4 16 Opinion on family Variable Label Availab
39. able 5 3 3 Table 5 3 1 Constructed household typology variables in household file Variable Description Information used for construction name ss HLDTYP Type of household Classification Relationship to other persons in house adopted from European Community hold civil status number of persons and Household Panel Eurostat 2003 children in household and PACO HLDFFS Household typology adopted from the Relationship to other persons in house Fertility and Family Survey FFS hold civil status number of persons and The FFS was launched by the United children in household Nations Economic Commission for Europe and was commissioned by the Swiss Federal Statistical Office for Switzerland www bfs admin ch HLDCEN Household typology Swiss Census Relationship to other persons in house Swiss Federal Statistical Office hold civil status number of persons and www bfs admin ch children in household 48 Table 5 3 2 Constructed household composition variables in household file Variable name Description MAXCOH Maximum duration of existence of NBADUL NBKID AOLDKI AYOUKI ADUK1_ ADUK2_ NBB_ household in years Number of adults in hld gt 18 Number of children in hid 0 17 Age of oldest coresident child max 17 Age of youngest coresident child max 17 Number of adult children in bid gt 18 amp lt 30 Number of adult children in bid gt 30 Ne
40. al security contributions de ducted I INDMG gross Income from self employment monthly amount I INDMN net social se curity contributions de ducted ISSOASIY State pension for old age first pillar widow er s or orphans annual amount Includes additional benefits AIY Disability pension annual amount Includes additional benefits I PENY Income from pension schemes second pillar old age pension annual amount Includes additional benefits I UNEY Income from unemployment social insurance annual amount IS WELY Income from welfare benefits social assistance annual amount 58 IS GRAY ISSINSY I FAMY I PNHY I PIHY IS OSY IS STPY IS STFY I AVSY I PTOTG gross I PTOTN net social security contributions on employment income de ducted I WYG gross I WYN net social secu rity contributions deduct ed IS WMG gross I WMN net Income from scholarships grants annual amount Income from private or public institution Income from any another private or public institution annual amount Family or child allowances annual amount Might additionally be included in income from employment Payments received from individuals not in household annual amount Payments received from individuals in household annual amount Other income annual amount Might include Ki pillar inheritance income from capital such as income from wealth letting sub letting Yearly total personal income annua
41. angements ji Family Household Composition Tasks Migration Minorities Mobility Gender Social Stratification Social Participation Networks Social Support Values Religions Lifestyle Leisure Internet Marketing Environment Housing Housing Market Region f Ind Behav Consumpt Emotions Coping Deviance Social Reporting Since the start of the SHP in 1999 a great variety of issues of social and economic sig nificance have been studied using the SHP data and many more questions can be ad dressed with the wealth of information the SHP contains For example e Evolving patterns in changing living conditions quality of life and life satisfaction Who is progressively better or worse off and why What are the necessary living conditions for warranting a good quality of life Which objective and subjective factors most strongly determine life satisfaction e Family life and interaction with society at large What are the consequences of various forms of living together in terms of social support and solidarity Which services are produced and consumed within the family unit obtained from the outside or provided by external bodies e g care for children and the elderly e Labour market participation work and life satisfaction What are the different forms of labour market participation full time vs part time employment precari ous and insecure employment sub employment vs over employment under and over
42. ation weight for each unit surveyed in the target popula tion U cohabitants This estimation weight corresponds to the average of the sampling weights of the population U original sample members from which the sample is se lected We calculate the weight wa for each non original sample member as follows vi 5 U kai ik WA ik M2 S TB st 9 where the denominator represents the sum of the initial weights w for all original sam ple members k the in each household and the nominator is the total number of links for that household with the population of reference U that is the number of original sample members in each household 4 2 1 Combination of multiple panels Because we have multiple panels we have to consider the way the panels are combined in order to enable valuable cross sectional estimations The combination of the two pan els from 2004 on is performed using the method of Merkouris 2001 His method consists of associating to each unit an allocation factor p 0 lt p lt 1 when unit is part of the first sample and 7 p when unit is selected in the second sample The combination of the two panels occurs at the level of the seven regions The combi nation is a so called convex combination as the allocation factor defines the relative importance of the two samples according to their size As the sample size of the SHP is larger this method gives more importance to the first panel The fa
43. b communes outside large central regions 13 Suburban residential communes outside large central 14 Peripheral urban communes outside large central regions 15 Net immigration communes moderate or 7 Rural commuter communes 15 16 high proportion 16 Native resident communes moderate or high proportion 17 Communes with industrial and tertiary sec 6 Industrial and tertiary sector communes tor employment 4 8 17 18 18 Communes with industrial employment 19 Communes with agricultural and industrial 8 Mixed agricultural communes 19 20 employment 20 Communes with agricultural and tertiary sector employment 21 Communes with agricultural employment 9 Peripheral agricultural communes 21 22 population 22 Communes with strongly shrinking popula tion The municipality codes themselves are not included in the user file to guarantee the an onymity of the respondents Under certain conditions are the codes available for users of the data This requires special authorization and is only possible when anonymity of the households can be guaranteed Other constructed variables in the household file related to socio geographical charac teristics of the household are HHMOVE whether the household moved since the last interview Table 5 3 14 Household moved since last interview HHMOVE Variable Label Constructed from HHMOVE moved since last interview grid and M I S Trend information 62 5 4 References for psychosocial variables
44. bers to their opinions thus creating interval level measures The best alternative to category scales within the class of magnitude estimation scales that can be used in CATI is the number production scales It is essential that a magnitude estimation scale has fixed anchors or reference points The 11 point number scale used in the panel questionnaire has for example two refer ence points 0 and 10 These reference points have been given labels that clearly indi cate the end point of the scale for example completely satisfied and not for example very satisfied Scales with two or more reference points and clear labels that fix the end points have proven to decrease the measurement error that can result from variation in response functions Saris and De Rooij 1988 3 Reliability of the data less measurement error Another argument is the effect of measurement error or the reliability of the data Scales with more response alternatives will be more reliable than those with fewer It is often stated that the reliability of scales increases with the number of points used There is probably a limit to the benefit of adding response categories or scale points An interna tional study of satisfaction across 10 different countries showed that the 11 point scale 4 This section is a summary See www swisspanel ch under Documentation for the complete version 19 was the most valid and reliable scale of all scales included in
45. ceptions and analyses of social dynamics Budowski et al 2001 Berthoud and Gershuny 2000 Rose 1995 The dynamics at the macrosocial level do not directly belong to the field of obser vation covered by a panel survey What panel surveys are intended to investigate how ever are the effects of changes at the macrosocial level on the living conditions of households and individuals the manner in which these changes affect the individuals and households and how they produce social change on a microsocial level The main purpose of household panels is therefore to understand the processes causes and ef fects of the social changes currently occurring Of course panel surveys are not the only 1 Panel data is data collected about the same units at more than one point in time It allows for insights into dynamic transformations social processes and changes across time Menard 1991 Instead of simply tak ing a snapshot of people and households at one given point in time by interviewing the same households and their members annually panel data enables the following the observation of changes for the same enti ties the reconstruction of the nature and development of their actions the examination of precedents con current dynamics and the consequences of alternative strategies tools used to measure social change A repeated cross sectional survey makes it possi ble to calculate for example net transitions between two dates e g a drop
46. ch as anxiety irritation and depression Scherer Wranik Sangsue Tran and Scherer 2004 64 The SHP contains one item assessing a very general negative emotional state Table 5 4 9 Negative feelings Variable Label Available in waves Do you often have negative feelings P C17 depression blues anxiety wo1 W14 The construct of positive feelings is measured with an item which assesses a feeling of energy and strength as well as general expectancies concerning future events Table 5 4 10 Positive feelings Variable Label Available in waves Are you often P C18 full of strength energy and optimism WO2 W14 Additionally since 2006 the frequency of four of the most important emotional traits is considered Scherer Wranik Sangsue Tran and Scherer 2004 Table 5 4 11 Positive and negative affects Variable Label Available in waves How frequently do you generally expe rience the following emotions P C47 joy WO8 W14 P C48 anger WO W14 P C49 sadness Wo8 W14 P C50 WOITY Wo8 W14 5 4 2 Personality traits Big Five Inventory 10 BFI 10 This ten item scale is designed to provide information about the differences between in dividuals on five principal personality dimensions Extraversion Neuroticism Agreeable ness Conscientiousness and Openness to Experience Each item goes from zero dis agree strongly to ten agree strongly and measure how an individual posi
47. considers necessary or an eval uation of how the household s financial situation has evolved 5 the household and the family collecting information on any external help available to the household for housework or child care the sharing of tasks and decision making within the household The individual questionnaires cover the following topics 1 the household and the family comprising objective elements such as the existence of children living outside the household the sharing of housework and childcare as well as subjective elements such as satisfaction with private life and with the sharing of the housework 2 health and victimisation covering objective elements such as general illness and health problems visits to the doctor and hospitalisation long term handicaps threats or attacks endured together with subjective elements such as the self perceived state of health the estimated evolution of the state of health or satisfaction with one s own health 3 social origins asked at first interview only referring to information related to profes sion professional position educational level political positioning and the nationality of both parents together with possible financial difficulties in the family of origin 4 education covering the various levels of achieved education education currently be ing pursued fluency in foreign languages and participation in on the job training 5 em
48. conversion attempts those who move away from Switzerland and those who are fully and permanently institutional ized 2 3 2 Initial rules governing the follow up of individuals 4 Respondents OSM Original Sample Member and their children are continuously followed whereas cohabitants are only re interviewed as long as they live with an OSM From 2007 onwards also cohabitants are followed 5 The minimum age of eligibility is 14 years 6 As a general rule respondents OSM are followed until they die or are permanently institutionalized or leave the target population for another reason 7 Individuals who send us a written refusal are dropped from the sample 2 3 3 Measures against attrition The following measures were taken to reduce attrition from 2006 to 2009 waves 8 to 11 of SHP_I and waves 3 to 6 of GHP Ir 14 recontacting all SHP_I households that had refused to participate between 2000 and 2003 that is at waves 2 3 4 and 5 recontacting past final refusal households that participated again after being re contacted in 2006 and 2007 recontacting refusing SHP_I households in 2006 2007 2008 and 2009 waves 8 to 11 recontacting refusing SHP_II households in 2005 2006 2007 2008 and 2009 waves 2 to 6 of SHP_II follow up of non original sample members After wave 11 2009 virtually all past final refusals had been contacted and often in terviewed again Since then considering t
49. ction with working atmosphere W01 W14 P W229 en with the level of interest in W01 W14 P W230 Satisfaction with the amount of work W01 W14 P W228 Satisfaction with job in general W01 W14 6 Four items assess the perception of the social environment of the individual Table 5 4 6 Satisfaction with living arrangements and personal relationships Variable Label Available in waves P F01 Satisfaction with living alone W01 W14 P F02 Satisfaction with living together W01 W14 P F04 Satisfaction with way housework is shared W01 W14 P QL04 Satisfaction with personal relationships Wo3 W14 7 Two items measure the satisfaction with leisure time Table 5 4 7 Satisfaction with leisure Variable Label Available in waves P A05 Satisfaction with free time W01 W14 P A06 Satisfaction with leisure activities WO W14 8 One item takes account of the satisfaction with the political system and particularly the perception of democracy Table 5 4 8 Satisfaction with democracy Variable Label Available in waves P P02 Satisfaction with democracy WO W11 W13 The second dimension of subjective well being the affective dimension is also pre sent in the SHP Generally affective traits are conceptualized as two dimensions of mood Watson Clark and Tellegen 1988 positive affect PA which groups together emotions such as joy hope and optimism and negative affect NA which groups to gether a set of negative emotions su
50. ctor of combination is p where n is the number of responding units n TtM from the first panel and nz is the number of responding units from the second panel The unit is either the person in the case of the individual weights or the household in the case of the household weight If the unit is a member of SHP I the weight is then multi plied by the factor p If the unit is a member of the SHP II the weight is multiplied by the factor 7 p This means that each sample is multiplied by the ratio of units in the sample 32 4 2 1d Calibrations to known population totals After the adjustment for non response and the combination of the two panels the weights are softly calibrated Guggemos and Tille 2010 using population totals coming from ESPOP until 2010 and STATPOP since 2011 There were two different calibration total classes depending on the information available and memory restraints The first is the classical version with totals on e sex age category 0 13 14 24 25 34 35 44 45 54 55 e the number of individuals living in the seven major statistical regions Lake Gene va VD VS and GE Middleland BE FR SO NE and JU North West Switzer land BS BL AG Zurich East Switzerland GL SH AR Al SG Central Swit zerland LU UR SZ OW NW and Ticino e the number of individuals with Swiss nationality and e the number of married individuals The second uses the same variables but breaks all totals up by
51. dint in the Interviewer data files have been coded in order to protect the identity of the Interviewers Consequently the merging of the Interviewer data with the Household and Individual level files is only possible after de coding Please contact Oliver Lipps for more details oliver lipps fors unil ch Note further that in 2008 Wave 9 the interviewer ID changed Because three digits to identify interviewers were not enough all interviewers located in the Lausanne studio were added a value of 10 000 and all interviewers located in the Bern studio were added a value of 50 000 This is important for longitudinal interviewer analyses 5 2 Variable naming conventions The variable names are coherent over time The only change is found in the year indica tor In order to assure consistency the following conventions were adapted Year related variables _yydnn Non year related variables individual number sex _dnn Where _ depends on the level of information P Person H Household G Grid X Proxy Where yy denotes the year 99 1999 00 2000 01 2001 Where d denotes the domain a Hobbies leisure free time lifestyle holidays etc b Biography c Health constitution d Demographic variables e Education f Family climate relationships work repartition g Grid 46 h Housing Income financial situation and living condition variables Life events m Geographical mobility n Social networ
52. distinguish between large and small part time jobs From wave 6 onwards this distinction is no longer made but separate response categories for self employed respondents and employees are introduced instead Because the calendar file contains information from all waves some detail present in the separate waves has been lost The calendar file does not include a distinction between small and large part time jobs nor does it have a distinction between self employed indi viduals and employees Users of the data interested in analysing these distinctions are advised to use the calendar questions in the personal files of the appropriate waves In the calendar file the following codes are used 1 Employed full time 2 Employed part time 3 Unemployed 4 Inactive 5 Unemployed or inactive relevant for inactive respondents in W2 and W3 only Table 5 1 1 shows the different versions of the calendar questions in the individual inter views and the corresponding codes in the calendar file 40 Table 5 1 1 Questions in the personal questionnaire related to the activity calendar and the corresponding codes in the calendar file W2 and W3 W4 and W5 W6 to present Original question Cal Original question Cal Original question Cal Original question Calen Employed respondents endar Inactive respondents endar endar dar value value value value We are going to review the We are going to review the We are going to review the We are going to review t
53. dividuals with the 2001 and 2002 sur veys combined Therefore some variables only exist for one of the survey years e g education history only for 2002 or only in an aggregated form e g living arrangement for 2001 The overall participation rate was 53 but over 80 among fully longitudinal panel survey respondents years 1999 2004 participated in the biography survey Budowski and Wernli 2004 The Biographical files include a two horizontal files with lines representing individuals Biography Master File SHPO_MBI and Biography Data File SHPO_BH_ USER and b vertical files for each of the eight domains with lines representing events and not individuals if appropriate SHPO_BV amp amp _ USER SHPO_MBI The Biography master file contains the identification numbers idpers of all individuals who answered the biographical questionnaire in 2001 or 2002 The master file further includes individual population weights wp00tbgp and sample weights wpOOtbgs For methodological reasons weights of zero had to be attributed to 199 persons SHPO_BH_USER In the horizontal file each row represents one respondent It contains in total 281 varia bles representing for each domain per episode the beginning end and description For example for every employment starting date end date and several characteristics of the job are included all as separate variables Also individual population weights wpO0Otbgp and
54. e 4 2 A the drop in participation was as at the household level particularly significant in the second wave 28 compared to the 2 Contrary to the SHP_ starting in 1999 the household recruited in 2004 were not explicitly asked to commit themselves for several years According to the interviewers many households were surprised to be called one year later to be interviewed again in the ongoing panel study 24 other waves in the 2004 2007 period when the drop in participation was between 2 and 6 In 2008 the number of persons validly interviewed increased slightly due to 1 re newal of contacts with past refusal households and 2 efforts made by the interviewers of M I S Trend to enrol all eligible household members for an individual interview In 2008 and 2012 however there was a slight decrease in participation on the individual level too It should be noted that drop in participation is quite similar for both panels after five waves SHP_I 2003 and SHP_II 2008 Table 4 1 Number of households validly interviewed in SHP_I and SHP_II 1999 2012 Year Wave SHP_In D SHP_II SHP_I II A B n A B n 1999 1 5 074 100 100 2000 2 4 425 87 87 2001 3 4 139 82 94 2002 4 3 582 71 87 2003 5 3 227 64 90 2004 6 1 2 837 56 88 2 538 100 100 5 375 2005 7 2 2 457 48 87 1 799 71 71 4 256 2006 8 3 2 537 50 103 1 684 66 94 4 221 2007 9 4 2 817 56 111 1 494 58 89 4 311 2008 10 5 2 718 54 96 1 546 61 103 4 264 2009
55. e following domains in the respondent s life course Trajectory of residence Residence permit information Cohabitation trajectory Couple relationships and civil status Family events Educational trajectory Professional activities Health CONDON BQ INS The SHP_III_pilot study contains biographical data of 505 individuals It includes two types of data files a Two horizontal files the individual master file in which lines represent individuals and the household master file with lines representing households b Eleven vertical files eight files for the eight domains of life with lines representing events or episodes three files containing the individual s perception about three domains of life couple relationships family and education professional activi ties The SHP_III_pilot_MASTERFILE_user sav file contains the identification numbers idpers of all individuals who answered the biographical calendar questionnaire The master file further includes two types of individual weights The SHP_III_pilot_HH_user sav file contains general information about household char acteristics such as the composition of the household the overall quality of the accom modation and the financial situation of the household at the time of the interview In the eight vertical life domain files a row represents one episode Respondents experi encing different episodes in a given domain for example they have held several jobs take up multiple
56. e in waves P C44 Satisfaction with life in general wo2 W14 2 A general measure of well being concerning health In this perspective self reported health is an independent predictor of longevity Table 5 4 2 Satisfaction with health Variable Label Available in waves P C02 Satisfaction with health status WO W14 3 Five items assess the satisfaction with the educational environment and its quality Table 5 4 3 Satisfaction with the educational environment Variable Label Available in waves P YTH01 Satisfaction with current studies W03 W14 P YTHO5 Satisfaction with things learned during studies W03 W14 P YTHO6 Satisfaction with relationship with the teaching staff W03 W14 P YTHO7 Satisfaction with the atmosphere with fellow pu W03 W14 pils students P YTHO8 Satisfaction with the support from parents Wo3 W14 19 Eor an exact wording of the questions presented in this section we refer to www swisspanel ch under Documentation Questionnaires PDF 63 4 Two items assess satisfaction with the overall financial situation Table 5 4 4 Satisfaction with financial situation Variable Label P W92 Satisfaction with income W01 W 14 P 101 Satisfaction with financial situation WO W 14 5 Satisfaction with working conditions is measured with five items Table 5 4 5 Satisfaction with working condition Variable Label Available in waves P W93 Satisfaction with working conditions W01 W14 P W94 Satisfa
57. e panels nn 32 4 2 1d Calibrations to known population totale 33 4 2 2 Overview of current weights and their construction ssseesesssessreeneerererreeee 33 4 2 2a Individual longitudinal weights nsseseeeeeneeeneeeeeetttrtsrernrrnetsrerrnnrererrrneseerene 33 4 2 2b Individual longitudinal weights sseesesnenneeeeenrneeteertntrtereertrrnreetrrnrneerennenn 34 4 2 2c Household cross sectional weight 34 4 2 2c Individual transitional factors nennen nennen 34 4 2 3 Selection of the appropriate weight 35 4 2 4 Addressing the complex sample structure in analvses nn 37 4 3 Data cleaning Consistency checks and Corrections 2 cccceeeeeeeceeeeeeeeeeeeeees 37 CHAPTER 5 DATA DOCUMENTATION teere neren renren nenen 38 5 1 Data RUE 38 5 1 1 Master files households and mdivduals 38 5 1 2 Annual files households and individuals sneneeeeennneeeeeeeennreeeeerrrerresrerrre 38 5 1 3 Calendar file ae ara ek 38 51 4 bast job Tegel tetas nalen ehe 42 5 1 5 Social origin file 42 5 1 6 Biographical files nn en ern aiaa 43 5 1 7 Interviewer MeS arri er Den 46 5 2 Variable naming conventions nn 46 5 3 Constructed vartables EE 48 5 3 1 Socio demographic variables cccccccsececeeeeeeeeceeeeeeeeeeeeeeeeeeeeseeaeaeeeeeeeenaes 48 5 32 ue E 50 5 3 3 Work status occupation and social position 50 5 3 4 Professional integration PAUG R4 nennen 57 0 90 INCOME eege A NERE
58. e satisfaction etc Since spring 2008 the SHP data are also distributed as part of the Cross National Equivalent File CNEF So far 46 special contracts for CNEF data have been signed with the SHP Figure 3 shows the continuous increase of SHP data users since the first wave Figure 3 Number of users who ever received a SHP CD or password Final version SHP Data CD received or password received 1600 1400 1200 CD received or 1000 eft password 800 600 400 200 Wave Wave Jave Jave fave Lave gave Have gave gave ave ave 138 Among the SHP data users sociology 33 and economics 30 are by far the most prevalent disciplines followed by political science 8 public health 4 psychology 4 statistics 3 and education 2 A few scientists from technical sciences ge ography theology and media science are also present indicating that spatially related topics are also being analysed using the SHP data The data users belong to the following institutions Swiss academic institutions 72 international academic institutions 17 public administrations 6 and private insti tutes 5 Academic communities clearly dominate but the statistical use by public administrations and private research facilities is certainly not negligible The data use by foreigners is continuously increasing nowadays almost 20 of the researchers come from abroad Within Switz
59. ed with the release of the W14 SHP data Biographical files 2001 2002 In 2001 and 2002 to obtain additional information about the respondents life course pri or to the panel study a retrospective biographical questionnaire was developed with questions regarding educational working and family history SHP Questionnaires Biography under Documentation Questionnaires PDF SHP Biography This paper and pencil questionnaire was sent to the respondents by mail and was self administered Biographical information was gathered in the following domains 1 Living arrangements LA Periods outside of Switzerland SA Changes in civil status CS Learned professions LP Educational trajectory ED Work life WL Family events FE Retirement RE ONAABRWN In order to assess the potentially negative impact of the self administered biographical questionnaire on the participation in subsequent waves of the yearly CATI a test sur vey was conducted in 2001 The results showed that the drop out rates did not increase substantially as a result of the questionnaire sent in between two waves Scherpenzeel 8 The paper and pencil questionnaire is not available in English but only in the interview languages German French and Italian 43 et al 2002 Consequently the main survey was carried out in 2002 with those partici pants that had not been part of the test survey SHP_I biographical data are available for 5 560 in
60. ehaviour and values social participation psychological scales religion and lei sure and culture For 2012 the modules religion and psychological scales were evaluated and revised Hence these new modules are available for wave 14 see also 2 4 3 The rotation calendar is the following Tab 2 3 Rotation calendar of the SHP modules from 2010 to 2020 Module 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 Social network X X x x Religion x x x Social participa X x x X tion Political behav X x x X iour and values Leisure and cul X X x X ture Psychological x x x scales X Administration of the module 17 2 4 3 Revised modules in Wave 14 and new constructed variables Module religion The revised module contains in addition to questions of the original module new questions on attitudes toward religions religious socialization and two centrality spirituality scales see Lebert and Tillmann 2011 Module psychological scales This module is dedicated to topics such as life satis faction self mastery worry domains and life goals see Ryser et al 2012 New variable Original Sample Member OSM The variable Original Sample Member OSM indicates whether a respondent was present in the sample at the first wave 1999 for the SHP_I sample and 2004 for the SHP_II sample People who join the panel after the first wave are so called cohabitants
61. eholds or individuals in the case of the SHP_Ill per stratum see Graf 2009 This means that for the SHP_I and the SHP_II the selection was proportional to the number of households per major region without overrepresentation of smaller regions For the GHP IL the number of addresses was proportional to the number of individuals per major region In both cases the selection did not take into account the average number of persons in the households per region Within one major region each household or individual had the same inclusion probabil ity independent of the size of the household The addresses of the gross sample are distributed according to the following proportions GHP TI census 1990 SHP_II 2000 census GHP It STATPOP 2012 Table 2 1 Stratification of gross sample Strata Cantons Proportion of Proportion of Proportion of addresses addresses addresses SHP_1 GHP H GHP II Lake Geneva region VD VS GE 18 45 18 22 18 90 Mittelland BE FR SO NE 23 25 22 92 22 25 JU North west Switzerland BS BL AG 13 44 13 86 13 57 Zurich ZH 17 51 18 22 17 52 Eastern Switzerland GL SH AR Al 15 68 13 70 13 98 SG GR TG Central Switzerland LU UR SZ OW 7 20 8 75 9 53 NW ZG Ticino Tl 4 47 4 33 4 25 Total 100 100 100 a See Appendix A for a list of cantons and their abbreviations The size of the strata at the moment of the selection for SHP_I SHP_II and SHP_III were as follows 12 Table 2 2 Sizes of strata at the mo
62. ence Difference with without weight weight Not compared either because of insuffi u 7 cient response too high of modality or it 187 did not make sense to test the variable No difference with or without weights No No 475 85 The variable considered does not appear to be biased from attrition No difference without the weights but No Yes the weighted results are different The 8 1 4 weighting introduces bias We observe a difference without Y N weights but it disappears when the re 42 7 5 re sults are weighted The variable is there fore touched by attrition but the weighting corrects the phenomena We observe a difference without the weight and it persists even with weighting The variable is therefore 34 61 touched by attrition without the possibility of correction by weighting Mainly leisure and politics variables Yes Yes 4 2 The weighting scheme of the SHP Compared to cross sectional surveys longitudinal household panels face some addi tional methodological challenges One of them is the complex weighting scheme On one side the objective of longitudinal surveys is to analyse the evolution of a population over a given year This is done using longitudinal weights On the other side longitudinal surveys are also used for cross sectional analyses referring to the population in any given year For this purpose there is also a need for cross sectional weights Furthe
63. er they show that the phenomenon of attrition can certainly not be ignored The researcher must account for this in his analyses and if necessary in the given interpre tation For the first panel there are 1108 variables that appear in at least one wave of the per sonal files and are thus eligible for testing Out of these there are 306 deemed unfit to be tested The following groups of variables were excluded e proxy variables as it concerns reports on other household members e variables with the same response in all waves considered such as status e variables with too few respondents for categorical variables if no category has at least 30 respondents and for numeric if the total number of respondents is less than 30 e variables of which the modality is too high this is for categorical variables with more than 100 distinct responses such as the 4 digit isco job classification e variables for which testing does not make sense such as id variables dates and weights Table 4 3 gives a summary of the results If a variable has bias detected for any year without weight then it falls into the category of Difference without weight If a variable has bias detected for any year with weights then it falls into the category of Difference with weight 28 Table 4 3 Composite results for the first panel Difference without weight Difference with weight Explanation Occurrences out ofthe 1107 variables in the pers
64. er use The syntax to construct the schema with the SHP can be found at http www swisspanel ch spip php rubrique264 amp lang en 5 3 4 Professional integration PAUG R4 Paugam s typology is based on a distinction between conditions of employment and conditions of work The typology distinguishes four types of professional integration see Paugam 2000 Secure integration integration assur e is defined as the combination of job stability and quality of work measured objectively and subjectively Three forms of integration deviate from this model insecure integration integration incertaine is the result of unstable job but good working conditions and satisfaction at work constrained integration integration laborieuse is the product of a stable job but with work con 57 straints leading to dissatisfaction and disqualifying integration integration disqualifi ante corresponds to the combination of job instability and poor working conditions Paugam 2000 5 3 5 Income Respondents are asked about various income sources and total income both in the indi vidual and in the household questionnaire They are free to report gross or net amounts after deduction of social security contributions and to report monthly or annual income Based on these questions variables on yearly income amounts are constructed Both net and gross incomes are constructed using standard assumptions on social security contributions
65. eristics and social involvement attitudes and behaviour by response pattern SHP II 2004 2012 Always Responding Dropped out responding irregularly n 1418 n 1475 n 1899 3 UN T Sex men 44 4 47 7 47 0 women 55 6 52 3 53 0 Age nn 17 2 21 6 16 9 20t0 29 8 8 12 2 18 6 30 to 39 19 8 17 8 16 8 40 to 49 21 9 18 6 17 7 50 to 59 14 3 14 3 12 5 60 17 9 15 5 17 5 Education compulsory school 23 1 30 7 29 1 upper secondary level vocational 35 8 38 5 37 2 upper secondary level matura 10 6 7 9 10 7 tertiary level vocational 16 9 13 5 13 6 tertiary level university 13 6 9 4 9 3 Swiss nationality 93 9 90 9 84 9 Region Lake Geneva 16 8 17 9 19 4 Middleland 27 0 23 5 23 4 North west Switzerland 14 0 12 5 14 0 Zurich 19 0 17 0 18 7 East Switzerland 11 9 13 6 12 9 Central Switzerland 8 5 11 6 8 4 Ticino 2 8 3 9 3 1 Urbanization highly and moderately urbanized centres 63 4 63 5 63 5 small urban centres 9 5 9 7 9 8 communes of urbanized centres 10 8 9 8 9 5 communes of small urban centres 7 8 6 3 6 6 communes remote from urbanized centres 8 5 10 6 10 6 Civil status ft single never married 37 5 40 7 43 6 married 48 9 49 0 42 2 separated 1 8 1 4 2 1 divorced 7 5 6 0 6 8 widower widow 4 3 2 9 5 3 2 Differences between groups are not significant Cramer s V dropped out p 15 irregularly re sponding
66. erland all universities and many universities of applied science Fachhochschule HES are represented among the data users Figure 4 Disciplines and their distributions among SHP data users CD from any wave or passw ord n 1179 Sociology Economics Political Science Public Health Psychology Statistics Education Demography Techn Science Geography Theology Media Science Ethnology Law Hse 1 7 Getting more information Questions Please visit our website www swisspanel ch or contact the SHP at swisspanel fors unil ch Phone 41 21 692 37 30 Fax 41 21 692 37 35 Contact persons for specific topics Topics Information by E mail and phone Registration data contract secretariat research net work conferences Data methods income and simulated taxes CNEF programming in Stata Data communication with the households instruction of interviewers monitoring of the survey programming in SPSS Interviewer data contact data methods program ming in Stata Weighting survey method ology programming in SAS Data methods communi cation with the households programming in SPSS and HLM Data questionnaires main tenance www swisspanel ch Project information ques tionnaires and documenta tion preparation and moni toring of the survey data dissemination including use of SHP data in a teach ing context Methods attrition analysis programming i
67. ers can be viewed here http www swisspanel ch spip php rubrique161 amp lang en Second respondents are asked to leave their mobile number and or their e mail ad dress If respondents are not willing to give this information or do not have a mobile number or e mail address they are asked to leave the address of an auxiliary e g a family member living outside of the household or a close friend who can help in case of losing track of the respondent Third households are called on different days of the week and on different times during the day in order to minimize noncontact And fourth a bilingual interviewer responsible for administration and tracking of the addresses is specifically briefed on how to find re located respondents The following measures are taken by this interviewer in case the advance letter is returned to sender e Checking whether phone number is still valid e Contacting mobile phone e mail address or auxiliary e Searching directories and the local inhabitant register e Request the dcl data care a service of the Swiss post mandated to seek cur rently valid household addresses and the corresponding phone numbers e f no phone number can be found a form is sent to the address provided by the dcl data care asking to complete contact details 3 4 Quality control Prior to each wave extensive pre tests are carried out checking correct technical func tioning of filters and new items and running different scenarios Af
68. es communes of urbanized centres communes of small urban centres communes remote from urbanized centres Civil status fw single never married married separated divorced widower widow Children in household at Employment active occupied unemployed not in labour force Owner residence eu Mean satisfaction with health 0 10 Participate in clubs Mean general trust in people 0 10 Mean interest in politics 0 10 3 6 61 6 8 5 11 6 8 9 9 5 41 3 48 0 1 4 6 6 2 7 59 5 60 5 1 1 38 4 51 2 59 9 6 00 5 41 3 8 58 4 10 4 10 6 9 3 11 4 41 8 48 7 1 1 5 9 2 4 63 3 63 7 1 8 34 4 51 4 54 0 5 54 4 88 4 4 61 0 10 6 10 2 7 6 10 6 45 1 44 4 1 1 6 0 3 4 60 3 64 4 2 2 33 5 44 4 47 4 5 39 4 63 Region Lake Geneva VD VS GE Middleland BE FR SO NE JU North west Switzerland BS BL AG Z rich East Switzerland GL SH AR Al SG GR TG Central Switzerland LU UR SZ OW NW ZG Ticino See Appendix A for a list of cantons P Asked from 2002 onwards 21 Difference between always and irregularly participating is not significant Cramers V p 64 Difference between always participating and dropped out is not significant Cramers V p 49 3 Difference between always and irregularly participating is not significant Cramers V p 83 22 2 82 Table 2 Demographic charact
69. es and then aggregated to the household level The detailed procedures to simu late taxes are described in SHP working paper 4_09 Tax simulation in the SHP http aresoas unil ch workingpapers WP4_09 pdf 5 3 6 Geographical information In addition to the region REGION 7 regions and the canton CANTON 26 can tons in which the household resides two community typologies are constructed This variable is based on the political municipality codes provided by the Swiss Federal Sta tistical Office see Schuler Dessemontet and Joye 2005 116f and recoded into 22 codes based on the municipality in which the household is located communes or Ge meinden An aggregated version of this variable in 9 categories is provided as well Ta ble 5 3 13 provides the names and labels of these variables as well as how COM1_ is aggregated into COM2_ 61 Table 5 3 13 Coding of the community typology variables COM1_ COM2_ 1 Great urban centres 1 Centres 1 2 3 2 Median sized urban centres 3 Small centres 4 Centre of peripheral region 5 Wealthy communes 3 Wealthy communes 5 6 Tourist communes 5 Tourist communes 6 7 7 Semi tourist commune 8 Communes with homes and asylums 9 Labour job communes in large central re 2 Suburban communes 9 10 12 13 gions 10 Suburban residential communes in large central regions 11 Peripheral urban communes in large central 4 Peripheral urban communes 11 14 regions 12 Labour jo
70. evious annual individual files More information on how to merge files can be found here http Awww swisspanel ch spip php rubrique223 amp lang en 5 1 5 Social origin file The social origin file contains information on the employment status of the parents when the respondent was 15 years old All individuals who were personally interviewed in any of the waves are included Unique information about a person s social origin is collected during the first interview It mainly relates to the composition of the household in which the person lived at the age of 15 and to the level of education and professional activities of both parents Persons who are not yet 20 years old and still living with their parents are not asked about their parents employment status Note that individuals who have had their first interview be fore they turned 20 are not in the social origin file Given the uniqueness of this information it doesn t make sense to attach it to each of the consecutive yearly waves Therefore the social origin module constitutes a specific file containing variable names in which the usual two digit number showing the year of the data collection is replaced by SPSS or__ Stata SAS A separate variable OSYY indicates the wave during which the data on the person s social origin have been collect ed The questions corresponding to the variables P 060 to P 065 have only been asked in the first wave 1999 P 060 At age 15 Wor
71. f the Swiss Centre of Expertise in the Social Sciences FORS hosted by the University of Lausanne The creation of the SHP was one of the key structural measures implemented by the Swiss Priority Program Switzerland Towards the Future during the period 1998 2003 for the following two main purposes Farago 1996 Joye and Scherpenzeel 1997 1 To ensure a solid database for social reporting on stability and changes in living ar rangements and well being in Switzerland that complements data collected by the Swiss Federal Statistical Office 2 To promote opportunities for quantitative social science research by making high quality data available to Swiss social scientists and to the international social science research community The structure of the SHP was developed using insights from the social sciences and the experiences made by various panel surveys in Europe and North America Budowski et al 1998 Budowski et al 2001 Joye and Scherpenzeel 1997 It was based on theoreti cal work related to the structure and development of contemporary societies Beck 1986 Eisenstadt 1990 Haferkamp 1990 Konietzka 1995 Leisering and Walker 1998 Mayer 1991 Muller and Schmid 1995 recent analyses of Swiss society and the way it func tions H pflinger et al 1991 Leu et al 1997 Levy et al 1997 and on literature about social monitoring Davies 1994 Noll 1998 Like other households panels the SHP is a tool for fine tuning our con
72. g SHP DATA Download data new variables File is OCCUPATION_ISCO_08 xls 50 G The Oesch Class Schema For a comprehensive description of the different classifications we refer to Bergman and Joye 2001 which can be downloaded from www swisspanel ch under Documentation Tables 5 3 5 to 5 3 7 show the variables used to construct the different classifications The classification of respondent s last job is4laj father s occupation and mother s occupation is done in the same way The following explanation of the construction of the classification for respondent s current occupation is therefore also applicable to re spondent s last occupation and father s and mother s occupation Table 5 3 5 Variables used to construct classifications for respondent s current occupation WRIGHT3 GOLDTHORP E ESeC CSP TREIMAN CAMSIS OESCH Table 5 3 6 Variables used to construct classifications for respondent s last occupation Profession and sectors WRIGHT3 GOLDTHORP E ESeC CSP TREIMAN CAMSIS OESCH Variable name WR3MAJ GLDMAJ ESECMJ CSPMAJ TR1MAJ CAIMAJ OESCH Variable name WR3LAJ GLDLAJ ESECLJ CSPLAJ TR1LAJ CAILAJ OESCH profession and sectors ISAMAJ IS4MAJ IS3MAJ P W28 IS4MAJ P W28 IS4MAJ NOGA2M ISALAJ IS4LAJ IS3LAJj P W111 IS4LAJ P W111 IS4LAJ NOGA2L education EDUCAT EDUCAT EDUCAT
73. gaux De la stratification aux repr sentations pp 495 538 Zurich Seismo Leu R E Burri S and Priester T 1997 Lebensqualitat und Armut in der Schweiz Bern Haupt 74 Levy R 2002 Meso social structures and stratification analysis A missing link Revue suisse de sociologie 28 193 215 Levy R Joye D Guye O and Kaufmann V 1997 Tous gaux De la stratification aux repr sentations Zurich Seismo Lipps O 2007 Attrition in the Swiss Household Panel Methoden Daten Analysen 1 1 45 68 Lipps O 2009 Attrition of Households and Individuals in Panel Surveys SOEPpapers 164 Lipps O 2011 Refusal Conversion in telephone panels Is it worth it SHP Working Paper 3 11 Lausanne Swiss Household Panel Lipps O and Kissau K 2012 Nonresponse in an Individual Register Sample Tele phone Survey in Lucerne Switzerland in Telephone Surveys in Europe Research and Practice Editors Michael H der Sabine H der Mike K hne Springer Lipps O Lagana F Pollien A and Gianettoni L 2011 National minorities and their representation in Swiss surveys I Providing evidence and analysing causes for their under representation FORS Working Paper Series paper 2011 2 Lausanne FORS Lodge M 1981 Magnitude scaling Quantitative measurement of opinions Sage University Paper series on Quantitative Application in the Social Sciences 07 025 Beverly Hills Sage
74. hat we had somehow reconstituted some kind of original sample we defined five categories of household level responses for a giv en wave wave t full response grid household at least one individual questionnaire household level response grid and household questionnaires grid level response grid questionnaire only non contacted households blocked addresses and full nonresponse On this basis the follow up rules are wave t 1 we contact all full re sponse we contact all household level response grid level response and non contacted households but with a procedure of refusal conversion we do not contact full nonresponse This system is being extended from year to year 2 4 Questionnaires 2 4 1 Content of the questionnaires The Living in Switzerland survey is a comprehensive survey The questionnaires household and individual cover a broad range of social fields and topics They are also designed to collect both objective resources social position participation etc and subjective data satisfaction values evaluation etc The whole constitutes an opera tionalisation of the different elements of the microsocial level living conditions life events attitudes and perceptions and lifestyles ways of life Budowski et al 1998 A household panel collects data at two levels the household and the individual In the case of the SHP sur
75. he Swiss Socio Professional Categories CSP CH The Swiss Socio Professional Categories CSP CH Joye and Schuler 1995 are based on the occupational coding of the Swiss Federal Office of Statistics as well as educa tional achievement The logic of the CSP CH is as follows Table 5 3 9 Swiss Socio Professional Categories University Technical and Apprenticeship Compulsory Professional Education or Less Top Executives 1 top executives Self Employed 2 liberal 3 self employed professions Wage Earners 4 intellectuals 5 middle skilled 8 unskilled and managers employees 6 non manual 7 manual The significance of an educational attainment may vary according to the details and title of an occupation which has been taken into account in this schema For example a par ticular employee could be classified as being part of the intellectual professions based on her degree of managerial responsibility without necessarily having a university edu cation E Treiman s Prestige Scale Treiman proposes a very general stratification model for modern complex societies based on occupational prestige ratings that are supposedly independent of locality and invariant to national social and cultural settings His work in this area culminates in the construction and validation of the Standard International Occupational Prestige Scale Using the four nested levels of the International Standard Classification of Occupations ISCO Treiman
76. he months months between now and months between now and months between now and since month year and for each month year and for each month year and for each month year and for each month you should tell me whether month would like you to tell month would like you to month would like you to tell your main activity was full time me if you have worked full tell me if you have worked me if you have worked full time employee part time employee full time or part time or if you full time or part time or part time or if you have not time self employed part time self have not worked due to a worked due to a period of un employed unemployed retired period of unemployment employment training or other training education housework or training or other reason reason any other situation 1 fulltime job gt 37h 1 1 fulltime paid job gt 37h 1 1 fulltime paid job gt 37h 1 1 Employee fulltime 1 2 part time job 19 36h 2 2 part time paid job 19 36h 2 2 part time paid job 19 36h 2 2 Employee part time 2 3 small part time job 1 18h 2 3 small part time job 1 18h 2 3 small part time job 1 18h 2 3 Self employed fulltime 1 4 unemployed 3 4 no job 5 4 unemployed 3 4 Self employed part time 2 5 continued education voca 4 5 continued education voca 4 5 Unemployed 3 tional retraining tional retraining 6 other 4 6 retired 4 6 Retired 4 7 other 4 7 Student 4 8 student 4 8 At home domestic work chil 4 dren 9 Other inactive 4
77. ion schemas we set the minimum qualification criteria to ten employees c Competence derived from educational attainment are qualified in several ways i Directly relating to the occupation ISCO 88 includes in its occupational classification an explicit reflection on the relations between educational attainment and occupational titles ii According to educational and training trajectories normally followed by those with a particular occupation as established from the Swiss Popula tion Census of 1990 iii Based on the respondents attained educational and professional qualifi cations whatever the relevance to their occupation 15 This recodification differs slightly from that of Levy et al 1997 52 Technically the following rules apply a Owners Employers self employed and at least 10 employees b Petty bourgeoisie self employed and less than 10 employees c Managers Experts professional leading or supervisory role as well as an ad vanced educational attainment d Managers salaried with supervisory position and not yet classified in any of the above categories e Professionals salaried with advanced educational attainment but without su pervisory functions f Semi Professionals salaried with either advanced or middling educational at tainment and with middling professional requirements g Worker other workers B Erikson Goldthorpe and Portocarero s Compa
78. ions are highly valuable for the formu lation and implementation of new policies since they facilitate evidence based political decision making The release of each consecutive wave of SHP data and the synergies between researchers working with the data make the SHP data increasingly rich lead ing to a steadily increasing number of high level scientific publications All SHP data users are contractually required to report back any publication based on the SHP data be it journal articles books working papers etc but also unpublished work such as diploma or doctoral theses or seminar work Figure 2 shows the evolution of the number of publications by type since 1999 Figure 2 Evolution of publications by types since 1999 OThesis Master PhD Report and Working Paper Book Chapters Journal Articles 1 4 SHP and CNEF Since 2008 the SHP participates in the Cross National Equivalent File CNEF The CNEF contains equivalently defined variables for the US Panel Study of Income Dy namics PSID the German Socio Economic Panel GSOEP the British Household Panel Study BHPS the Household Income and Labour Dynamics in Australia HILDA the Canadian Survey of Labour and Income Dynamics SLID the Korea Labor and In come Panel Study KLIPS the Swiss Household Panel SHP and the Russia Longitu dinal Monitoring Survey RLMS The data are designed to allow cross national re searchers access to harmonized vers
79. ions of these panels For acquiring the data see http www swisspanel ch doc PSM_CNEF index php lang en 1 5 Access to the data and data protection rules The SHP data are available at no charge Users must sign a contract available on the SHP website http www swisspanel ch shpdata contract php lang en amp pid 23 Once the contract is signed users will have access to the most recent SHP Data The SHP data are available to researchers signing in person the data contract at no charge and exclusively for non commercial use It is strictly forbidden to attempt to iden a For more information see www human cornell edu PAM Research Centers Programs German Panel cnef cfm or Frick et al 2007 tify particular households or individuals and to make parts or all of the data available to a third party In a research team all users are to sign the contract individually SHP data users commit themselves to personally send a copy of all working papers final reports or publications to the SHP swisspanel fors unil ch 1 6 Research network Living in Switzerland In June 2013 the research network Living in Switzerland had some 1404 registered members which represents an increase of 19 since June 2012 The SHP data users analyse a large number of topics household composition and families poverty health living conditions of elderly people living conditions of first and second generation immi grants political participation lif
80. ipal cantonal and federal level Additional income variables The constructed annualised income variables of the SHP user files have been imputed if the amount was missing don t know no answer implausible value These imputed val 60 ues can be downloaded from www swisspanel ch under SHP Data supplementary da ta The SHP cross national equivalent file CNEF contains income sources defined slightly differently than in the SHP user file The CNEF variables with the exception of profes sional income report income on the household level Missing values have been imput ed The CNEF variables can be downloaded from www swisspanel ch under SHP Data supplementary data from December 2011 To access CNEF variables of other household panels see the CNEF homepage http www human cornell edu pam research centers programs german panel cnef cfm Original responses on the questionnaire are available from the SHP team upon request email to ursina kuhn fors unil ch Simulated taxes The variable IS HTAX simulates the direct taxes paid by the household at the municipal cantonal and federal level To assign the percentage of the household income which has to be paid as taxes we use tax levels in municipalities published by the Swiss Federal Tax administration and take account of household specific deductions that can be ap plied to the income Taxes are calculated at the level of tax units individuals or married coupl
81. ire Also the variable related to re sponse status is checked Finally demographical variables are checked for consistency with earlier waves This is done for gender date of birth and civil status For other variables the general rule is not to make changes retrospectively i e when in a later wave of data collection an error is found in an earlier wave this is not corrected for the earlier wave 37 CHAPTER 5 DATA DOCUMENTATION 5 1 Data files For every wave every year a household and an individual file are released In addition to these annual files there are several other files a household master file an individual master file a calendar file a file containing information on respondents last paid jobs and a social origin file All files are available in SAS Stata and SPSS format See for a table with an overview of the different files the document Getting started with the Swiss Household Panel data downloadable from www swisspanel ch under Documenta tion user guide PDF 5 1 1 Master files households and individuals The master files of households and of individuals include all households and individual respondents that are in the panel or have been in the panel in the past The files contain an overview of response statuses for all waves The household master file SHP_MH contains all households of both samples of the panel For every wave it is documented who the reference person is what interviews have bee
82. ity and Social Psychology Bulletin 21 8 842 849 Treiman D J 1977 Occupational prestige in comparative perspective New York Academic Press Van Doorn L Saris W E and Lodge M 1983 Discrete or continuous measurement What difference does it make Kwantitatieve Methoden 10 104 120 Voorpostel M 2009 Attrition in the Swiss Household Panel by demographic character istics and levels of social involvement SHP Working Paper 1 09 Lausanne Swiss Household Panel Voorpostel M 2010 Attrition patterns in the Swiss Household Panel An analysis of demographic characteristics and social involvement Swiss Journal of Sociology 36 2 359 377 Watson D Clark L A and Tellegen A 1988 Development and validation of brief measures of positive and negative affect The PANAS scales Journal of Personality and Social Psychology 54 6 1063 1070 Weaver B 2010 Attrition and Bias in the Personal Files of the Swiss Household Pan el SHP Working Paper 1 10 Lausanne Swiss Household Panel 77 Appendix A List of cantons in Switzerland Aargau AG Appenzell Ausserrhoden AR Appenzell Innerrrhoden Al Basel Stadt BS Basel Landschaft BL Bern BE Fribourg FR Geneva GE Glarus GL Graub nden GR Jura JU Lucerne LU Neuch tel NE Nidwalden NW Obwalden OW Schaffhausen SH Schwyz SZ Solothurn SO St Gallen SG Thurgau TG Ticino TI Uri UR Valais VS Vaud V
83. k in private households Employer Father 42 P 061 At age 15 Public Company status Father P 062 At age 15 Work in private households Employer mother P 063 At age 15 Public Company status Mother P 064 At age 15 Work in private households Employer Other person P 065 At age 15 Public Company status Other person Therefore valid values are only available for the persons interviewed for the first time in wave 1 For all the others theses values are labelled missing The questions regarding the parents political orientation are asked since wave 4 2002 P P46 Political position Left Right Father P P47 Political position Left Right Mother In wave 4 every person responding to the individual questionnaire was asked these two questions in order to obtain this information also from persons having already been in terviewed in previous waves in which the questions were not asked Since wave 5 these two questions are part of the social origin module and are addressed only to persons who are interviewed for the first time Consequently the information is missing for per sons who answered the social origin module before wave 4 and who did not participate in wave 4 5 1 6 Biographical files Two sets of biographical data files are available to the SHP users First the SHP_I bio graphical data which were collected 2001 and 2002 can be downloaded Second the GHP II pilot survey launched in 2012 2013 will be distribut
84. ks o Social origin p Politics r Religion v Values aspirations other than politic w Labour force work social status y Violence yth Youth z Other variables Where nn is a two digit number which refers to the number of the question normally the position in a block dedicated to a specific topic Two examples year of interview number of variable here 1999 here 01 ONE P99D01 IN source of questionnaire domain here Personal individual here demography year of Interview number of varlable here 2000 here 17 HOGH17 I source of questlonnalre domain here Household here housing 47 Constructed variables do not follow the convention of variable naming and codification These variables have a name corresponding to their contents for example wstat00 for working status in 2000 They are classified by their respective domains in the codebook and are found in the module to which they belong see 5 3 5 3 Constructed variables This paragraph presents background information on the construction of socio demographic variables education labour market participation and income socio geographical information and weights For all other constructed variables we refer to www swisspanel ch under Documentation Variables 5 3 1 Socio demographic variables Tables 5 3 1 to 5 3 3 present the constructed socio demographic variables in the house hold file Table 5 3 1 and 5 3 2 and the individual file T
85. l Pro gramme Prioritaire Demain la Suisse Bern Fonds national suisse de la recherche scientifique Joye D and Schuler M 1995 Stratification sociale en Suisse cat gories socio professionnelle Bern Office f d ral de la statistique Kahn R L and Juster T E 2002 Well being Concepts and measures Journal of Social Issues 58 4 627 644 Kalton G and Brick M 2000 Weighting in household panel surveys In Rose David Researching Social and Economic Change The Uses of Household Panel Studies p 96 112 London Routledge Kass G V 1980 An Exploratory Technique for Investigating Large Quantities of Cat egorical Data Journal of the Royal Statistical Society Series C Applied Statistics 2 2 119 127 Konietzka D 1995 Lebensstile im sozialstrukturellen Kontext Ein theoretischer und empirischer Beitrag zu Analyse soziokultureller Ungleichheiten Opladen Westdeutscher Verlag Kuhn U 2009 Attrition analysis of income data SHP Working Paper 2 09 Lausanne Swiss Household Panel Lavall e P 2007 Indirect Sampling Springer Lebert F and Tillmann R 2011 Panel suisse de m nages revision du module reli gion questionnaire individuel Lausanne FORS Leisering L and Walker R 1998 The dynamics of modern society Briston The Poli cy Press Levy R Joye D andGuye O and Kaufmann V 1997 Repr sentations In R Levy D Joye and O Guye Eds Tous
86. l amount In most cases total income has been calculated by adding the different income sources In case of non response in any of the income sources and in some other cases in waves 1 to 5 total income refers to a global assessment of income Amounts of income sources which represent one off payments over 12 000 CHF are not considered in total income Income from employment or self employment annual amount Takes account of 13 and 14 month salary bonuses or gratifi cations if applicable From 2002 on sum of I EMPY I INDY Income from employment or self employment monthly amount see www swisspanel ch Social public transfers annual amount From 2002 on sum of I UNEY I WELY I GRAY I INSY Income from private persons informal transfers annual amount From 2002 on sum of I PNHY I PIHY Income from old age or disability pension annual amount From 2002 on sum of I OASIY I AIY ISSPENY The questions on income have changed over the duration of the panel cf Table 5 3 11 With the exception of family allowances only asked from 2004 onward as well as old age pension and other income sources in 1999 old age pension not asked in 1999 these changes should not influence comparisons across waves The variables collected from 1999 2001 can be constructed for all years by aggregating different income sources as shown in the table Table 5 3 11 Collection of individual income by wave 1999 2000 2001 2002 200
87. le in waves P D93 A child develops equally well whether his her parents are mar W 04 W 07 ried or not 4 Two items are adapted from Roux 1999 These items measure the perception of in equality at two levels at the individual level which concerns the private sphere and at the intergroup level concerning society at large This scale is important because it allows making a distinction between two kinds of discrimination in this sense this scale gives 67 information whether it is the group and or the individual which is perceived as a target for discrimination Table 5 4 17 Equality Variable Question Available in waves Do you have the feeling that in Switzerland women WO2 W 11 W13 are penalized compared with men in certain areas Do you in your everyday life feel penalized com E FS pared with the opposite sex VORAN TNTS P P20 5 Measuring attitudes toward measures promoting gender equality is another way to measure gender role attitudes Such a scale is much more subtle and provides an indi rect measure of gender role attitudes Two items assess the propensity to behave in a way to improve equality between men and women One item is a global measure at the group level and one item measures the possibility to act at the individual level Such items are inspired by the neo sexism scale Tougas Brown and Joly 1995 a scale which assesses the attitude toward gender roles in society instead of measuring atti tudes towa
88. ment of selection number of households for SHP_I and SHP_II and numbers of individuals for SHP_III Strata Cantons SHP_I N SHP_II N SHP_II N households households Individuals Lake Geneva region VD VS GE 714725 648 590 1519189 Mittelland BE FR SO NE 837452 784266 1788791 JU North west Switzerland BS BL AG 484 667 455 833 1 091 302 Zurich ZH 646 469 587 850 1408575 Eastern Switzerland GL SH AR Al 531731 493606 1 123 672 SG GR TG Central Switzerland LU UR SZ OW 313548 306605 765879 NW ZG Ticino Tl 180 623 160 123 341 652 Total 3 709 215 3 436 873 8 039 060 2 2 3 Coverage Because of the different sampling frames the population of reference differs slightly ac cording to the sample For the SHP_I and the SHP_II the population of reference con sists of all individuals living in private households in Switzerland who had a telephone connection registered in the telephone directory landline or mobile In case of the GHP IL the sampling frame includes all individuals living in privates households in Swit zerland independent of the availability of a telephone connection For all three samples individuals living in old peoples homes institutions collective households or prison are not part of the population of reference An estimated 98 5 of private households had a telephone connection at the time of the selection of the sample for the SHP_II in 2004 The SRH covered about 9
89. method Calibrations are then used to adjust all the weights so that certain popula tion sums are correct equal to the sums of the non institutionalized Swiss population The adjustments due to calibration are chosen to be as small as possible so that the in troduction of bias for non correlated variables is minimized 4 2 1a Adjustments for non response Modelling of non response in the SHP is done by the process of segmentation Kass 1980 The goal of segmentation is to determine the response probability of the panel members or households and is thus used for modelling non response either to the grid the household questionnaire or the individual questionnaire The method proposed by Kass is the Chi squared Automatic Interaction Detector CHAID procedure When mod eling the non response the dependent variable consists of the response status whereas socio demographic information is used as independent variables As one needs infor mation that is available also for non respondents the choice of the variables used to ad just non response is limited CHAID proceeds in consecutive steps and represents a kind of classification tree that shows at each intersection the auxiliary variable that best models the non response The algorithm first chooses the variable for the partition of the data that is most highly asso ciated with the response status according to the highest Pearson Chi squared The data is then divided into two groups according
90. munities and cantons The entries are thus not based on the entry of a phone directory but on the register in the municipal ity or the canton Although undercoverage or overcoverage can still occur they are neg ligible However only 60 of the households selected in the SHP_III have an available phone number associated with them This lack of phone numbers might lead to a certain level of undercoverage as well 2 3 Following rules 2 3 1 Initial rules governing contact with households The general rule is to interview all households that completed at least the grid during the previous wave We proceed with interviews as long as members of these households agree to fill in the household questionnaire and his or her individual questionnaire it is always possible to catch up with the other individuals in a future wave However 1 We permanently drop for following waves households that were not contacted at all during the 1st wave or those that did not supply any information at the time of the 1st wave not even a grid or those who only completed a non response questionnaire for wave 1 2 For SHP_I we also permanently dropped all households that only replied to the grid at wave 1 For SHP_Il we changed this rule and only dropped households that had com pleted just a grid for wave 1 and wave 2 3 We dropped households that gave a final refusal households where no one is will ing to respond to a household interview even after refusal
91. n SPSS and Stata Data data sets communal data programming in SPSS Denise Bloch Ursina Kuhn Florence Lebert Oliver Lipps Erika Antal Val rie Anne Ryser Flurina Schmid Robin Tillmann Marieke Voorpostel Boris Wernli swisspanel fors unil ch 41 0 21 692 3730 ursina kuhn fors unil ch 41 0 21 692 3722 florence lebert fors unil ch 41 0 21 692 3715 oliver lipps fors unil ch 41 0 21 692 3724 erika antal fors unil ch 41 0 21 692 3746 valerie anne ryser fors unil ch 41 0 21 692 3740 flurina schmid fors unil ch 41 0 21 692 3716 robin tillmann fors unil ch 41 0 21 692 3721 marieke voorpostel fors unil ch 41 0 21 692 3727 boris wernli fors unil ch 41 0 21 692 3723 10 CHAPTER 2 STUDY DESIGN 2 1 General design of the SHP Since its origin in 1999 the SHP survey Living in Switzerland has covered a broad range of topics and approaches in the area of social sciences The survey is conducted annually from September to February by M I S Trend in Lausanne and Bern using the computer assisted telephone interview technique CATI From 2010 onwards CAPI and CAWI are used for refusal conversion The SHP is a panel i e the same persons and households are interviewed year after year and answer with a few exceptions the same questions In contrast to a rotating panel it is an indefinite life simple panel There are therefore no continuous refresh ments of the sample
92. n carried out and when they have taken place The individual master file SHP_MP contains all individuals who have resided in the par ticipating households in any of the waves This file includes the time invariant variables gender date of birth month and year and identification number of father and mother as well as response statuses and interview dates for all waves 1 2 Annual files households and individuals The annual household files SHP99_H_USER SHPOO_H_USER etc contain infor mation from the household interviews complemented by information from the grid ques tionnaire For the constructed variables see 5 3 The information from the yearly individual interviews SHP99 _P_USER SHPOO_P_USER etc is included in the annual individual files For the constructed var iables in these files see 5 3 For the complete questionnaires see Questionnaires under Documentation on www swisspanel ch 5 1 3 Calendar file Using the answers in the individual questionnaire the calendar file contains for every Please not that Stata is case sensitive and that Stata data file names are in lower case 38 person the activity status in each month If the person has answered the individual questionnaire in wave x information on his her activity is contained for the last 12 months if the person has not answered the individual questionnaire in the preceding wave the period between the individual interview in wave
93. nal varia tions and is sensitive to gender Other dimensions can be easily accommodated e g ethnicity geographic region in order to incorporate specific research interests and hy potheses and to improve the correspondence between this measure and the social cat egories within their context See for more information Bergman et al 2002 and Bergman and Joye 2001 18 For more details see Bergman Lambert Prandy and Joye 2002 56 G The Oesch Class Schema This schema tries to capture social stratification in modern service societies More pre cisely it aims at reflecting increasing occupational heterogeneity stemming from trends in the employment structure such as e Deindustrialization and service sector expansion e Women s growing participation in paid employment e Massive expansion in educational attainment and occupational upgrading The schema s particularity lies in its focus on both hierarchical and horizontal class divi sions Hence according to Oesch 2003 2006a 2006b the salaried middle class should not be taken as a unitary grouping nor should the manual non manual divide be considered as the decisive division line Based on earlier contributions by John Goldthorpe Gasta Esping Andersen Hanspeter Kriesi and Walter Muller Oesch 2003 the schema combines two dimensions A first vertical dimension separates class positions based on the advantage in their employ ment relationship this distinction
94. ned by verbal labels This type of scale is often called a number production scale The main arguments in favour of this type of scale are 1 Minimisation of categorisation effects We assume that attitudes fall along a single latent continuum ranging from positive to negative The larger the number of points on a response scale the better it represents this underlying latent continuum and the more accurate it reflects the variation Scales with relatively few response alternatives force respondents to categorise their reaction towards an attitude object instead of directly mapping it onto the response continuum thus causing information loss Early research has already shown that respondents dif ferentiate more between objects when offered response scales with greater numbers of categories Bendig 1954 Garner 1960 The larger the number of points the more pow erful the scale is in discriminating but at a certain point respondents become unable to make fine distinctions and thus round off 2 Improvement of data analysis Improving the measurement procedures is one way to improve the quality of data analy sis In their investigation of the possibilities to optimise measurement procedures in so cial science Van Doorn Saris and Lodge 1983 did not simply enlarge the number of scale points but used psychophysical scaling see also Lodge 1981 Respondents ex pressed their answers on continuous scales by drawing lines or assigning num
95. ng noncontact 3 3 1 Incentives for the interviewers To increase the interviewers motivation they can earn two collective bonuses One bo nus is based on the general response rate all interviewers together have to accomplish at least 95 of last year s individual interviews The second bonus is only oriented to wards interviewers who are engaged in refusal calls and is based on the refusal conver sion rate Additionally there are regular briefings of all interviewers and supervisors on the progression of the fieldwork 3 3 2 Incentives for the participating households To enhance survey participation an unconditional incentive is offered to each eligible re spondent In wave 12 we introduced an unconditional incentive sent to the households with the preliminary letter asking them to participate in the new wave An additional incentive is offered to complete households A household is called com plete if all members of the household of 14 years of age or more participate at the indi vidual interview and if the household reference person completes the grid and the household questionnaire Thus this additional incentive is only offered to household consisting of at least two members The general unconditional incentive is sent to the respondents with the preliminary letter asking the household to participate in the new wave of the SHP The additional incentive for complete households is given to the participants at the end of the
96. nouvelles formes de l int gration pro fessionnelle Paris Presses Universitaires de France Plaza S and Graf E 2007 Recommandations et exemples pratiques concernant application des pond rations Neuchatel Swiss Household Panel Rammstedt B and John O P 2007 Measuring personality in one minute or less A ten item short version of Big Five Inventory in English and German Journal of Research in Personality 41 203 212 Rosenberg M 1965 Society and the adolescent self image Princeton NJ Princeton University Press Roux P 1999 Couple et galit Un m nage impossible Lausanne R alit sociales Ryser V A Lebert F and Tillmann R 2012 Proposition d instruments psycholo giques a ins rer dans le questionnaire individuel du Panel suisse de m nages Lau sanne FORS Saris W E and De Rooij K 1988 What kind of terms should be used for reference points In Saris W E Ed Variation in response functions A source of measurement error in attitude research Amsterdam Sociometric Research Foundation Scherer K R Wranik T Sangsue J Tran V and Scherer U 2004 Emotions in everyday life probability of occurrence risk factors appraisal and reaction patterns So cial Science Information 43 499 570 Scherpenzeel A C and Saris W E 1995 The quality of indicators of satisfaction across Europe A meta analysis of multitrait multimethod studies In A C Scherpenzeel Ed A
97. o compute equivalised household income the household income is divided by an equivalence scale Two different equiva lence scales are used in the SHP Firstly the modified OECD scale variables I EQON and I EQOG attributes a weight of 1 to the first adult a weight of 0 5 to all other household members from 14 years on and a weight of 0 3 to children up to 14 years The sum of these weights gives the modified OECD scale Secondly the SKOS equiva lence scale Swiss Conference of social assistance variables IS EQSN and I EQSG attributes a weight of 1 to a 1 person household 1 53 to a two person household 1 86 to a three person household 2 14 to a four person household 2 42 to a five person household 2 70 to a six person household 2 98 to a seven person household and in creases by 0 28 to each additional person Table 5 3 12 List of constructed income variables of households Variable Gross net Description I HTYG gross Yearly income from all members ISSHTYN net Taxes not deducted social security taken account of where possible I EQSG gross Yearly household income equivalised ac I EQON net cording to SKOS scale 1998 see social security taken account of www swisspanel ch where possible Taxes not deducted I EQOG gross Yearly household income equivalised ac I EQON net cording to modified OECD scale social security taken account of Taxes not deducted where possible I HTAX Simulated direct taxes at the munic
98. odel response to the grid at wave t given response to the individual questionnaire in wave t 1 Second response to the individual questionnaire in wave t is modelled given response at the grid at the same wave In the development of these factors certain theoretical weaknesses were uncovered This comes into play if many waves are strung together Because of this we recommend not to use more than three consecutive years see http www swisspanel ch IMG pdf SHP_Transitional_Factors pdf 4 2 3 Selection of the appropriate weight It is essential to use weights in order to have estimates that are representative of the un derlying population Cross sectional weights always refer to the year analysed both for households and for individuals whereas longitudinal weights individuals always ex trapolate to the population resident in Switzerland in 1999 for SHP_I and to the popula tion resident in Switzerland in 2004 for the combined panel SHP_I and SHP_II The transitional factors allow weighting respondents to a selection of consecutive waves and refer to the first year of the sequence Therefore in the selection of a weight one needs to know whether the study concerns only one year i e is cross sectional or considers multiple years and is longitudinal in nature For each of the four types of delivered weights there are two weights produced One is to give the weighted size of the sample the size of the relevant Swiss population These are
99. ome can be found here as well Kuhn 2009 We also refer to other studies on attrition in the SHP Lipps 2007 including a comparison to attrition in other panel stud ies Lipps 2009 Effects of attrition on variables of interest This is an overview of the results and methods of analysis to study the effect of attrition on a large number of variables for a detailed description see Weaver 2010 The goal is to describe the consequences in terms of bias caused by the continuing and selective loss of individual participants to the survey over the course of time One statistical solu tion to attrition is the use of weights Weights attempt to correct non response at all lev els personal household and grid As we will see some variables in the SHP are touched by attrition and we can verify an appearance of bias in the statistics The weights often correct for attrition and therefore compensate for the bias but sometimes the bias persists even after weighting or in rare cases is a result of weighting itself In order to identify the variables touched by attrition we examine all variables that were included in the latest wave and in the previous waves Attrition from both the first sample of the Swiss Household Panel SHP_I and the first and second SHP_II sample com bined is considered We then compare means and frequencies calculated with the value 27 of the first year of the variable in 99 12 on the sub populations of resp
100. on political positioning and subjective elements such as satisfaction with the political system the evaluation of issues or even political values and finally 9 leisure and media comprising objective elements such as leisure activities and the use of the media as well as subjective elements such as satisfaction with leisure and free time 10 psychological scales in 2009 six items were added measuring two dimensions of self perception self mastery and self esteem as well as the Big Five personality traits measured by means of a 10 item short scale see also chapter 5 4 From the second wave on the questionnaire also includes a life events module and an occupational calendar module covering the 12 months prior to the interview More information on the content of the questionnaires is available here http www swisspanel ch codebook cblgre php lang en amp pid 207 And here as pdf http www swisspanel ch doc q_pdf php lang en amp pid 20 2 4 2 Modular design In 2009 the SHP has introduced a new system of modularization of the individual ques tionnaire similar to other panels such as the GSOEP BHPS and HILDA The SHP now contains three different types of questions 1 questions asked only once usually in the first interview 2 questions asked each wave and 3 questions asked regularly but not each year The latter are arranged in different modules i e social network political b
101. onal Labour Office Users interested in ISCO 08 codes can transform swiss specific occupation codes P W28 X W01 P W111 X WO06 P 012 P 029 P 046 with the xls table provided on our website The use of stratification schemas based on occupational titles traditional in this field has as a consequence that only people who report an occupational title can be classi fied The following classifications were constructed A The Wright class structure Wright III B Erikson Goldthorpe and Portocarero s Comparative Analysis of Social Mobili ty in Industrial Nations schema CASMIN The European Socio economic Classification ESeC The Swiss Socio Professional Categories CSP CH Treiman s Prestige Scale The Cambridge Social Interaction and Stratification Scale CAMSIS Amon 11 Cf Joye and Schuler 1995 For a discussion on how occupations are to some extent reflections of their national and temporal context see Levy 2002 12 If some minor adjustments are made in order to adapt it to the European context the label ISCO 88 COM is used Cf International Labour Office 1990 International Standard Classification of Occupations ISCO 88 Geneva ILO Following the ISCO 88 classification armed forces occupations are classified 0 in ISCO 88 1 digit code major group 1 in ISCO 88 2 digit sub major group 10 in ISCO 88 3 digit minor group and 100 in ISCO 88 4 digit unit group 13 Under the headin
102. onal files all waves percent out ofthe 802 variables tested in paren theses Not compared either because of insuffi cient response too high of modality or it did not make sense to test the variable 306 No No No difference with or without weights The variable considered does not appear to be biased from attrition 644 80 3 No Yes No difference without the weights but the weighted results are different The weighting introduces bias 9 1 1 Yes No We observe a difference without weights but it disappears when the re sults are weighted The variable is there fore touched by attrition but the weighting corrects the phenomena 85 10 6 Yes Yes We observe a difference without the weight and it persists even with weighting The variable is therefore touched by attrition without the possibility of correction by weighting Mainly leisure and politics variables 64 8 For the combined panel there are 746 variables that appear in at least one wave of the personal files from 2004 on Out of these 187 are deemed unable to be tested The reasons are the same as those above Table 4 4 gives a summation of these results The categories work as above 29 Table 4 4 Composite results for the combined panel Occurrences out ofthe 746 variables in the personal files Explanation all waves percent out ofthe 564 variables tested in paren theses Differ
103. ondents still present in the latest wave as follows R SE sh sL sL NsL sL Se RE E where st are the longitudinal respondents original sample members in 1999 for the SHP_I and 2004 for the combined panel SHP_I and SHP_II and st are the longitudi nal respondents in year 20 Basically we test to see if samples that still respond in a later year are representative of the same individuals that responded in the first year The tests run through the most recent released version wave 14 One has to be cautious with the results presented below because the variables are compared from their first year of appearance So it is possible that there is left hand bias already introduced in the sample That is to say that a selective process may have already occurred before the appearance of the variable introducing bias This is unde tectable by this method Moreover the calculations are done on the entire sample of longitudinal respondents and there are no comparisons on sub populations by sex age class nationality etc Such comparisons could reveal differences which are not ob served at the aggregate level Of course the inverse is also possible The variables having been identified as being biased by attrition in particular variables related to leisure and politics need to be studied with care by the researchers who use them in their analyses These results do not mean that these variables are unusable Howev
104. or Switzerland Swiss Journal of Sociology 28 7 25 Budowski M Niklowitz M Scherpenzeel A Tillmann R Wernli B and Zimmer mann E 1998 Description of life domains and indicators of the Swiss Household Panel SHP Working Paper 2 98 Neuchatel Swiss Household Panel Budowski M Tillmann R Zimmermann E Wernli B Scherpenzeel A and Gabadi nho A 2001 The Swiss Household Panel 1999 2003 Data for research on micro social change ZUMA Nachrichten 50 100 125 Budowski M and Wernli B 2004 Echantillon et taux de r ponse de l exp rience m thodologique 2001 et du questionnaire biographique 2002 SHP Working Paper 2 04 Neuch tel Swiss Household Panel Cauchon C and Latouche M 2006 Weighting of the Swiss Household Panel SHP I Wave 6 SHP II Wave 1 SHP I and SHP II combined Statistique Canada Davies R B 1994 From Cross Sectional to Longitudinal Analysis In A Dale and R B Davies Eds Analyzing Social and Political Change pp 20 40 London SAGE Diener E 2000 Subjective well being American Psychologist 55 1 34 43 and Diener E Suh M E Lucas R E and Smith H L 1999 Subjective well being Three decades of progress Psychogical Bulletin 125 2 276 302 Eisenstadt S 1990 Kultur und Sozialstruktur in der neueren soziologischen Analyse In H Haferkamp Ed Sozialstruktur und Kultur pp 7 20 Frankfurt am Main Suhr kamp 72 Eurostat
105. p 08 Differences between always participating and dropped out is not significant Cramer s V p 23 2 Differences between groups are not significant Cramers V dropped out p 14 irregularly re sponding p 16 Difference between always and irregularly participating is not significant Cramer s V p 06 83 Children in household 72 50 9 59 5 52 2 Employment active occupied 67 1 63 7 67 1 unemployed 1 4 2 7 3 3 not in labour force 31 5 33 6 29 6 f 2 Owner residence a 49 9 52 2 44 6 Mean satisfaction with health 0 10 8 29 8 15 8 20 Participate in clubs 54 5 49 2 43 3 Mean general trust in people 0 10 5 69 5 30 4 98 Mean interest in politics 0 10 5 74 5 06 4 87 Region Lake Geneva VD VS GE Middleland BE FR SO NE JU North west Switzerland BS BL AG Zurich East Switzerland GL SH AR Al SG GR TG Central Switzerland LU UR SZ OW NW ZG Ticino 8 Difference between always participating and dropped out is not significant Cramer s V p 48 9 Difference between always and irregularly participating is not significant Cramer s V p 21 0 Difference between always participating and dropped out is not significant T test dropped out p 16 84
106. permits to distinguish occupations according to inter linked characteristics such as their marketable skills their earnings or their mobility pro spects A second horizontal dimension distinguishes occupations according to their pre dominating work logic Four work logics are differentiated e an interpersonal logic typical for service occupations based on face to face ex change occupations in health care education or welfare e a technical logic where the work process is determined by technical production parameters occupations in IT craft or assembling e an organizational logic where primary orientation goes towards the employing or ganization occupations in management administration and the back office e an independent logic where entrepreneurial principles of self employed dominate entrepreneurs self employed professionals shopkeepers and farmers The schema s central argument is that depending on whether an occupation involves the face to face attendance to people s personal demands the deployment of technical ex pertise and craft or the administration of organizational power the work logic and prima ry orientation differ in fundamental ways Hence the schema has been developed among others to come to grips with changes in class voting Oesch 2008 Both a 16 class and 8 class version of the schema are available Depending on the re search question under study the detailed or simplified version may be of great
107. pervisors for their roles as contact per sons organizers of the interviews and supervisors of the interviewers The supervisors who are experienced interviewers are responsible for the performance of the inter viewers The aim of the interviewers training is to become familiar with the SHP in general with its longitudinal design and the specific difficulties Complex items are discussed and the interviewers learn how to convince respondents to participate at the survey They work through the questionnaires and study the training manual as well as the advance letters and newsletters which the participating households received The training sessions are conducted by M I S Trend in Lausanne and Bern with the as sistance of the supervisors and a member of the SHP Team 21 For the refusal conversion M I S Trend uses only the most successful interviewers measured by their individual response rates and the quality of their interviewing perfor mance They receive extra training to be well prepared M I S Trend ensures a strict selection of only the most experienced interviewers and guarantees that all interviews are conducted by native speakers 3 3 Measures to increase response Over the past years the SHP has taken several measures to fight attrition These measures concern incentives for the interviewers incentives for the participating households refusal conversion maintaining contact with the households and minimizi
108. ployment considering different aspects firstly the collection of information neces sary to determine the status of the interviewee in the labour market secondly infor mation covering the current main employment thirdly details about the last main job held These modules also comprise objective elements such as profession status of the profession the number of hours worked work schedule atypical work as well as subjective elements such as satisfaction with various aspects of the job the evaluation of promotion prospects or of personal qualifications 6 income including objective elements such as total personal income total profes sional income received social transfers received private transfers and other income and subjective elements such as satisfaction with the financial situation and an evalua tion of changes concerning the personal financial situation 7 participation integration networks taking into account objective elements such as frequency of social contacts non remunerated work outside home participation in asso ciations membership of and participation in religious groups and subjective elements 16 such as the assessment of social capital by means of evaluation of potential practical help and emotional support from various social networks 8 politics and values referring to objective elements such as political participation membership party identificati
109. qualification etc and their relationship to work and life satisfaction How do people especially women with small children manage conflicting de mands from the workplace and from home e Poverty and social exclusion What kinds of living conditions are associated with poverty and social exclusion What are the family and individual characteristics of the poor and what is the mechanism which leads them out of poverty Who remains poor despite policy measures for support What are the complex rela tionships between poverty social isolation and externally induced social exclu sion e Gender social and economic participation How do life trajectories diverge ac cording to gender Why do professional careers of men and women with similar educational resources still diverge e Social determinants of health How is the life course of individuals and families of widely different origins and facing different social conditions related to health be haviour and outcomes What are the consequences of worsening living condi tions on health What impact does ill health have on living conditions employ ment and quality of life later in time e Emotional trait stability over time How do changes in living conditions and or health affect negative anxiety irritation depressions and positive emotional states joy hope optimism Does a negative emotional state cause illness and low life satisfaction Evidence based answers to these and other quest
110. r 5 6 Imputation procedures Apart from the consistency checks and corrections see 4 3 no values are changed or imputed with the exception of income variables see 5 3 5 5 7 Combining data files Table 5 6 1 shows the identification numbers that are available in the different data files The personal ID idpers can be found in all files on the individual level always referring to the same individual The interviewer ID is available in the interviewer files see 5 1 7 and the annual individual and household files As the composition of households can change over time their identification number is wave specific Identification numbers of parents and spouses refer to their personal ID For example to match parents and children one can attach the info of the parent to the info of the child by matching idmoth and idfath idmoth__ and idfath__ in Stata and SAS to idpers To combine information from the household reference person with the household refper needs to be matched to idpers in the individual file To add information from the partner to this file rpspou needs to be matched to idpers 69 Table 5 7 1 Identification numbers variable in files description idint P H V ID of interviewer Idpers P MP SO CA LJ BH ID of person BV Idhous P H MP MH BH ID of household Idfath MP ID of father Idmoth MP ID of mother Idspou P ID of partner Refper H MH ID of reference person in hd Rpspou H ID of
111. r more in a household panel survey there are not only individuals to weight both in a lon gitudinal and cross sectional fashion for every wave but also households In this chapter we describe the current weighting scheme and the construction of each of the weights We then discuss the purpose of and potential for incorporating different advancements and we outline the time frame required to implement them This discus sion is designed to give an idea of how the weights are produced and what techniques are used If one is interested in a detailed exposition on the production of the weights for a given year one should examine the documentation at 30 http Awww swisspanel ch spip php rubrique199 amp lang en 4 2 1 Overview of techniques In this section we present four major techniques used for the construction of weights in the SHP The process of segmentation is used to determine the probability of being in the panel the inverse of which is the basis of the weights and thus represents an ad justment for non response The generalized weight share method GWSM is used for both the cross sectional individual and household weights in order to allocate a weight to cohabitants of whom the inclusion probability is not known The third approach concerns the combination of the two panels that is done according to a factor allocating a relative importance to each of the sample due to its size Finally we shortly present the calibra tion
112. rative Analysis of Social Mobility in In dustrial Nations schema CASMIN The first Goldthorpe class schema was based on occupation and occupational status self employed salaried Originating from Goldthorpe and Hope s prestige scale 1974 and Goldthorpe s subsequent class schema 1987 two levels of classification were de veloped that included 7 or 36 categories Further development in conjunction with the CASMIN Comparative Analysis of Social Mobility in Industrial Countries project makes the seven category schema more suitable for comparative investigations and it has es tablished itself as the most prominent schema for comparative intergenerational mobility studies Contrary to earlier versions the current schema requires information on the re spondents number of employees and supervisory function As a class schema that is primarily used in comparative research it is most frequently based on ISCO 88 Ganzeboom and Treiman 2003 have adapted the most recent Goldthorpe class sche ma into the following codes 1 Higher controllers 2 Lower controllers 3 Routine non manual employees 4 Self employed with employees 5 Self employed without employees 7 Manual supervisor 8 Skilled manual employees 9 Semi and unskilled manual employees 10 Farm labour 11 Self employed farmers It is more difficult than with other schemas presented here to assess how respondents are classified because several dimension
113. rd women directly Such measures are supposed to be less threatening com pared to direct measures and emphasizes attitudes that are generally hidden Table 5 4 18 In favour of equality measures Variable Question Available in waves Are you in favour of Switzerland taking more steps to WO2 W11 W13 ensure the promotion of women In your own relationships with the opposite sex does P P23 it seem possible to you that something can be done W02 W 11 to increase equality between men and women P P22 5 4 5 Risk aversion scale A single item rated on an eleven point scale from 0 avoid taking risks to 10 fully pre pared to take risks assesses the global individual attitude toward taking risks in gen eral For more information Grund and Sliwka 2006 give a general overview of the theo retical background of this scale Table 5 4 19 Risk aversion Variable Label Available in waves P P48 Are you generally a person who is fully pre pared to take risk or do you try to avoid taking W11 W 12 risks 5 5 Missing value conventions The following missing value labels are used 1 does not know 2 no answer 3 inapplicable This means either 68 a the specific question was not asked because it was not applicable to the respondent b the respondent did not participate in this particular wave c the entire household did not respond was not contacted 7 filter error a question should have been asked but was not 8 other erro
114. rily or permanently New variable on children own_kids Until now the SHP provided variables con taining the information of the number of children living in the same household A fre quently recurring question from SHP data users was however how many children someone has or has had in total Therefore we constructed a variable measuring the entire number of own biological and adopted children per person This information plays a key role in the research of fertility and is often used as a control variable for ex ample when measuring the causal effect of income on child achievement or women s labor participation 2 4 4 Forthcoming new variables Wave 15 will contain new variables concerning social networks These variables will be come available in November 2014 Module social networks The module will be enlarged to include new topics such as relationship quality with network members basic demographic information on central network ties and online social networking 18 2 4 5 The use of 11 point scales For many questions of the Swiss Household Panel questionnaire the 11 point scale has been chosen instead of a category scale The 11 point scale is used in many other on going surveys for example the GSOEP and World Value Study and seems to be well handled by respondents Respondents are asked to indicate the strength of their attitude or opinion in a number between 0 and 10 with the endpoints 0 and 10 being defi
115. rom within the same group than from without 18 CAMSIS has been developed initially from friendship networks and subsequently from cohabiting couples Stewart Prandy and Blackburn 1980 For Switzerland the Popula tion Census of 1990 was used to examine the probability of co occurrence of occupa tional titles between cohabiting couples In the simplest model the distances between occupations of couples are calculated on the basis of the contribution of the cell toward the x of a contingency table The x con tribution for each cell is entered into a traditional correspondence analysis which repre sents the best possible solution in a two dimensional space The first dimension repre sents the combination of occupations among couples who have the same occupational title typical examples are couples who both work together on a farm or a restaurant The second dimension represents the social distance that is reflected in the dis similarity between couples occupations It should be added that the scores of a di mensional analysis do not have sociological significance in themselves but only in rela tion to each other Here the value allotted to each occupation i e the score of the di mensional analysis indicates its position on this hypothetical social axis and conse quently its distance to others Subsequently each occupation of the 4 digit ISCO 88 classification is allotted a CAMSIS score The current version adjusts for natio
116. s are integrated in complex and unspecified ways See Bergman and Joye 2001 for a more detailed discussion 53 C The European Socio economic Classification ESeC The European Socio economic Classification ESeC is a European occupationally based classification based on the Erikson Goldthorpe Portocarero EGP Schema The information required to create ESeC is e occupation coded to the minor groups i e 3 digit groups of EU variant of the In ternational Standard Classification of Occupations 1988 ISCO88 COM e details of employment status i e whether an employer self employed or em ployee e number of employees at the workplace e whether a worker is a Supervisor Table 5 3 8 The European Socio economic Classification ESeC Class Common Term 1 Large employers higher grade professional Higher salariat administrative and managerial occupations 2 Lower grade professional administrative Lower salariat and managerial occupations and higher grade technician and supervisory occupa tions 3 Intermediate occupations Higher grade white collar workers 4 Small employer and self employed occupa Petit bourgeoisie or independents tions excluding agriculture etc 5 Self employed occupations agriculture etc Petit bourgeoisie or independents 6 Lower supervisory and lower technician oc Higher grade blue collar workers cupations 7 Lower services sales and clerical occupa Lower grade white collar workers tions
117. s might impact variables of inter est and research findings The common distinction made in the literature on nonresponse and attrition is between attrition that is completely at random attrition that is selective on variables unobserved in the data and attrition that is selective on variables observed in the data Alderman et al 2001 In the analyses presented in this section we will consider attrition on observed variables This kind of attrition may introduce bias in the estimates of interest but this bias is amenable to statistical solutions Two analyses are performed on the impact of attrition in the SHP on an annual basis one focusing on group representativeness the other on potential bias in variables of interest Additionally we present an on going anal ysis focusing on the impact attrition has on the relationship between variables We refer to Appendix C for a general impression of how respondents with various re sponse patterns differ from each other on demographic characteristics and several measures of social involvement A comparison is made between respondents who are in the panel every wave respondents with an irregular response pattern and respondents who have dropped out of the panel Note that calculations are based on unweighted data For the complete study we refer to the SHP Working Paper 1 09 Voorpostel 2009 on the website www swisspanel ch and Voorpostel 2010 A comparable study on attrition in relation to inc
118. s occupational prestige scores for each occupation within an ISCO lev el are averaged to produce a score for occupational groups as summarized by ISCO 55 The subjectively attributed prestige of a specific occupation is a linked to the privilege and power which individuals enjoy based on their occupational titles b invariant across social and cultural groupings and c similar across all complex modern societies The Treiman Prestige Scale differs from Wright and Goldthorpe s class schema not only in that it measures subjectively attributed prestige as an indicator of access to structural and functional power but also because it explicitiy models a prestige hierarchy The prestige scores range between 0 lowest prestige and 100 highest prestige Treiman 1977 F The Cambridge Social Interaction and Stratification Scale CAMSIS The Cambridge Social Interaction and Stratification Scale CAMSIS is based on the idea that social structure can be expressed by the social distance between individuals for instance through the co occurrence of occupations that individuals hold and the rela tionships that they form with each other Persons sharing a similar social position in terms of social class or status group membership are more likely to socially interact in an equal way with members of the same group than with members of other groups So acquaintances friends and marriage partners will all tend to be chosen much more fre quently f
119. sample weights wpOOtbgs are included in this file The vertical files 1 Living arrangements SHPO_BVLA_USER 2 Periods outside of Switzerland SHPO_BVSA_USER 3 Changes in civil status SHPO_BVCS_USER 4 Learned professions SHPO_BVLP_USER 5 Educational trajectory SHPO_BVED_USER 6 Work life SHPO_BVWL_USER 7 Family events SHPO_BVFE_USER 8 Retirement SHPO_BVRE_USER In the eight vertical files one file per domain a row represents one episode Respond ents experiencing different episodes in a given domain for example they have held several jobs take up multiple rows in the file one for every job An index variable is included to preserve the order of the episodes of respondents Biographical files 2012 2013 3 amp amp stands for the domain 12 The information of these respondents was of poor quality or information needed to construct weights was lacking 44 In 2012 2013 the SHP_III_pilot study preceded the first wave of the second refresher sample the GHP IL of which the field work began in September 2013 parallel to the fieldwork of the SHP_I and the SHP_II The questioning in the first wave of this second refresher sample takes the form of a biographical questionnaire a life calendar The aim of the SHP_III_pilot study was to test the biographical calendar questionnaire for a detailed evaluation of the SHP_III_pilot study see Morselli et al 2013 The life calendar of the SHP_III pilot study included th
120. swiss foundation for research Swiss Household Panel in social sciences O F S Schweizer Haushalt Panel Panel suisse de m nages A Swiss Household Panel User Guide 1999 2012 Wave 14 November 2013 By Marieke Voorpostel Robin Tillmann Florence Lebert Ursina Kuhn Oliver Lipps Val rie Anne Ryser Flurina Schmid Martina Rothenb hler Boris Wernli Acknowledgements The Swiss Household Panel data are collected within the framework of the research program Living in Switzerland financed by the Swiss National Science Foundation The SHP is based at the Swiss Centre of Expertise in the Social Sciences FORS in Lausanne This guide is also based on the work of past members of tne SHP Team How to cite this document Voorpostel M Tillmann R Lebert F Kuhn U Lipps O Ryser V A Schmid F Rothenb hler M amp Wernli B 2013 Swiss Household Panel Userguide 1999 2012 Wave 14 November 2013 Lausanne FORS Correspondence to Swiss Household Panel FORS c o University of Lausanne B timent G opolis CH 1015 Lausanne swisspanel fors unil ch 2013 FORS User Guide SHP Table of Contents CHAPTER 1 INTRODUCTION nennen 3 1 1 Aims and Analytic Potential 3 1 2 Institutional Setting irri ireren ranie digen 4 1 3 Use OF IME EE 4 1 4 SHR and CNEF EE 7 1 5 Access to the data and data protection rules ccccccceeeceeeeeeceeeeeeeeeeaeeeeeetesneees 7 1 6 Research network
121. ted due to various measures taken to convert households who were abandoned earlier because of double refusals into respondents see for more information the Swiss Household Panel Scientific Report 2008 downloadable from www swisspanel ch under Project Evaluation and Scientific Report At the individual level see Table 4 2 A the drop in participation was particularly high in the fourth 12 wave as compared to the other waves in the 1999 2005 period be tween 6 and 10 From 2006 onward the number of persons validly interviewed in creases in general but note again the slight drop in 2008 due to 1 various measures taken to convert households who were abandoned earlier because of double refusals into respondents and 2 efforts made by the interviewers of M I S Trend to enrol all eligible household members for an individual interview SHP_II With regard to the SHP_II waves 1 to 5 2 538 households and 3 654 individuals were first interviewed in 2004 In the eighth wave 1 520 households and 2 481 persons were answering At the household level see Table 4 1 A the drop in participation was highly significant in the second wave 29 as compared to 5 to 8 for the three other waves in the 2004 2007 period In 2008 the number of households validly interviewed increased due to renewal of contacts with households who were abandoned earlier be cause of double refusal like for the SHP_I At the individual level see Tabl
122. ted or ended an activity or even been unemployed wave 2 to wave 5 Since month year have you changed your professional status employee self employed changed the amount of hours you work full time part time started or stopped work or been unemployed wave 6 and after In case the answer is no to this question the activity status by the time of the interview is assumed to hold for every month that elapsed since the preceding interview or for the last 12 months if the respondent did not respond to the individual questionnaire in the preceding wave For these cases the appropriate value is imputed for all months since the last wave 7 In terms of labour market situation Here the term activity is used 39 In case the answer is yes to one of the questions above i e if the person reported any changes in his her status during the period considered the calendar questions are asked and the employment situation is assessed for every month since the previous wave The calendar questions changed twice since the start of the survey First in wave 2 and 3 different questions were asked depending on whether or not the respondent had a paid job Response categories differed between these two questions see Table 5 1 1 In wave 4 and 5 both active and inactive respondents answered the same questions in the calendar with slightly adapted response categories compared to earlier waves Up to wave 5 it is possible to
123. ter the training of su pervisors and interviewers for more details see 3 2 the fieldwork agency monitors the interviewer performance during the fieldwork supervisors listen in to the interviews evaluate interviewers on several criteria e g accurateness and pace of reading argu mentation document performance and give feedback to the interviewers M I S Trend carries out the training and monitoring of interviewers in collaboration with the SHP Team 23 CHAPTER 4 DATA QUALITY 4 1 Response rates and attrition 4 1 1 Response rates Tables 4 1 and 4 2 indicate the number of validly interviewed households and persons for the years 1999 2011 See Appendix A for further detail on response figures SHP_I With respect to the first sample SHP_I waves 1 to 13 5 074 households were first in terviewed in 1999 In the thirteenth wave 2 977 households and 5 103 persons re sponded Out of the 7 799 persons interviewed for the first time in 1999 23 n 1 811 responded to their personal interview in each of the following waves including the thir teenth wave conducted in 2011 At the household level see Table 4 1 A the drop in participation was particularly high in the second 13 and the fourth 11 waves compared to the other waves in the 1999 2005 period 5 to 8 From 2006 onward the number of households validly interviewed increases in general but note the slight tem porary drop in 2008 in the number of interviews conduc
124. ting Cramers V for all the categorical variables and by t tests for the continuous variables and the variables measured on an 11 point scale Table 1 Demographic characteristics and social involvement attitudes and behaviour by response pattern SHP I 1999 2012 Always Irregularly Dropped out responding responding n 2606 n 3196 n 4878 Sex men 42 7 46 2 47 8 women 57 3 53 8 52 2 Age 14 to 19 23 4 23 8 21 1 20 to 29 10 4 13 7 19 9 30 to 39 22 6 19 1 19 7 40 to 49 17 1 18 6 16 6 50 to 59 14 9 13 7 10 6 60 11 7 11 0 12 2 Education compulsory school 32 2 35 3 34 3 upper secondary level vocational 33 3 36 7 38 0 upper secondary level matura 9 9 9 2 10 3 tertiary level vocational 12 0 10 4 8 9 tertiary level university 12 5 8 5 8 5 Swiss nationality 95 4 92 6 87 4 Region Lake Geneva 17 0 18 3 17 6 Middleland 27 1 25 1 24 7 North west Switzerland 14 9 15 1 13 7 Zurich 17 4 15 0 16 3 East Switzerland 10 2 13 6 14 5 Central Switzerland 9 8 9 0 8 8 Following a matching procedure with the Swiss National Cohort a database containing all residents in Swit zerland matched with the mortality register see Spoerri et al 2010 we were able to identify additional de ceased respondents who until now were erroneously included in the dropped out group 81 Ticino Urbanization highly and moderately urbanized centres small urban centr
125. tions himself relative to a list of ten statements This scale developed by Rammstedt and John 2007 is an abbreviated version of the 44 items Big Five Inventory BFI 44 The Big Five Inventory includes two items per per sonality trait Commonly a trait is defined as temporally stable heritable or at least in part and considered as universal Rammstedt and John 2007 have assessed the psy chometric properties of this short scale For a general overview about the theoretical assumption behind this personality traits scale John Naumann and Soto 2008 give information about the history and the con struction of the Big Five inventory taxonomy For the general five factor theory see also McCrea and Costa 2003 Srivastava Gosling and Potter 2003 provide information about the relative stability of personality traits during adulthood and put forward that not all the personality traits are equally stable In the SHP this information related to the BFI 10 is collected once at the first interview 65 Table 5 4 11 Big Five 10 Variable Label Available in wave see myself as someone who P C60 iS reserved W 11 W13 P C61 Is generally trusting W 11 W13 P C62 does a thorough job W 11 W13 P C63 Is relaxed handles stress well W 11 W13 P C64 has an active imagination W 11 W13 P C65 is outgoing sociable W 11 W13 P C66 tends to find fault with others W 11 W13 P C67 tends to be la
126. to this chosen predictor Each of these sub groups is then analyzed separately and independently of the other to produce further subdivisions Kass 1980 It doesn t have to be the same variable in each of the two subsamples and the predictors can be used several times to partition the data Kalton and Brick 2000 The partitioning process goes so on until each sub group satisfies one of the following conditions 1 none of the remaining variables is found to be significant on response rate 2 the number of members of the sub group including non respondents would fall below a given level 30 if the sub group were divided and 3 the response rate would fall below a given level 3 if the sub group were divided The resulting subsets repre sent homogenous response groups HRG Adjustment for non response is based on these HRG the adjustment factor corresponds to the inverse of the response rate of a given HRG 31 4 2 1b Generalized weight share method Because the inclusion probabilities of new household entrants cohabitants are not known we apply an alternative strategy in order to allocate them a cross sectional indi vidual weight This strategy consists of using only the known inclusion probabilities of the original sample members and allocating parts of these weights within a household to cohabitants The strategy used in the SHP is the Generalized Weight Share Method GWSM of Lavall e 2007 The GWSM produces an estim
127. useholds The syntax SPSS and STATA for this correction can be found in the syntax example for the file creations that are released to gether with the data Second the household weights can also be used at the individual level In order to do so one needs to merge the household files with the individual files Then each individual gets the household weight An extrapolation using the household weights would then correspond to the population totals of the respective year In general we recommend using the individual weights for analyses on the individual level The use of the house hold weights for analyses on individual level makes however sense if one wishes to have a larger sample as some information on the individuals is coming from the household questionnaire or the grid and is thus available also for non respondents of a specific year 36 4 2 4 Addressing the complex sample structure in analyses Weighting provides estimates that are representative of the national population Another issue has to be considered when using the SHP the complex sample structure of the data The standard procedures of common statistical software packages e g SAS SPSS STATA underestimate variance Plaza and Graf 2007 because they assume a simple random sample As with most surveys the SHP sample selection is more com plex as it has stratification clustering and adjustments due to non response Such com plex sample needs to be taken into account in
128. vey the questionnaire at the household level covers the following areas 1 composition of the household containing basic information collected in the grid ques tionnaire about all the members of the household such as age sex relations between the members of the household nationality level of education and occupational status 2 accommodation containing objective elements such as the type and size of the ac commodation home ownership or tenancy the cost of and or the subsidies received for housing as well as subjective elements such as satisfaction with the accommodation evaluation of the state of the accommodation and assessment of perceived nuisances 3 Out of the 1 520 asked again SHP_I households in 2006 and 2007 580 completed at least the grid inter view 15 3 standard of living referring to a list of goods owned by the household or activities that its members can carry out together with the reason financial or otherwise why goods are not owned or activities not carried out 4 the household s financial situation containing objective information such as the ex istence of financial difficulties and the household s reactions to different situations in debtedness and the reasons for it the total household income the amount of tax paid and the social and private transfers as well as subjective elements such as satisfac tion an estimate of the minimum income the household
129. vidual H Household X Proxy CA Activities calendar LJ Last Job MP Individual Masterfile MH Household Masterfile OS Social Origin LANGUAGES is to be replaced by E English F Frangais D Deutch Italiano For SPSS labels To label a SPSS data file open the files located in the LABELS SPSS WAVES LANGUAGES directory in a syntax editor and run the syn tax For Stata labels To label a Stata data file open the files located in the LABELS STATA WAVES LANGUAGES directory in a do file editor and run the syn tax Note that all Stata file names variable names use lower case letters 71 References Beck U 1986 Risikogesellschaft Auf dem Weg in eine andere Moderne Frankfurt am Main Suhrkamp Verlag Behr A Bellgardt E and Rendtel U 2005 Extent and determinants of panel attrition in the European Community Household Panel European Sociological Review 21 489 512 Bendig A W 1954 Transmitted information and the length of rating scales Journal of Experimental Psychology 47 303 308 Bergman M M and Joye D 2001 Comparing Social Stratifications Schemas CAMSIS CSP CH Goldthorpe ISCO 88 Treiman and Wright Cambridge Studies in Social Research 9 1 37 Bergman M M Lambert P Prandy K and Joye D 2002 Theorization Construc tion and Validation of a Social Stratification Scale Cambridge Social Interaction and Stratification Scale CAMSIS f
130. w born baby birth between two consecu Information used for construction Longest time of two members living together in years information from grid Information from grid Information from grid Information from grid Information from grid Information from grid and individual questionnaire Information from grid and individual questionnaire Information from household and indi tive grid interviews or within last 12 months if vidual master file no previous year grid interview Table 5 3 3 Constructed socio demographic variables in individual files Variable Description Information used for construction name AGE Age in year of interview Collected once confirmed next waves Difference from the year of birth and the official year of interview official means the year of the beginning of the wave in question even when interview took place beginning of following cal endar year SEX Gender of respondent Collected once confirmed next waves CIVSTA Civil status in year of interview Information from household grid and personal interview Equivalent to question P D13 Individual infor mation is considered more reliable than from reference person MAXCOP Max time in years of person living with Information from grid someone else in household NAT_1_ First nationality Grid and individual questionnaire NAT_2_ Second nationality Grid and individual questionnaire NAT_3_ Third nationality Grid and individual questionnaire HAB_
131. x 1 and the individual inter view in wave x if the person has answered the individual interview both in wave x and in the preceding wave The activity calendar is empty for waves in which a respondent did not answer the indi vidual questionnaire The variable names in the calendar file are as follows JAN activity status in January in the year FEB activity status in February in the year MAR activity status in March in the year etc The calendar questions in the questionnaire have changed twice over the course of the years Three periods can be distinguished wave 2 and 3 wave 4 and 5 and wave 6 and thereafter For all waves however the professional status at the time of the survey is determined by the variables P WO1 to P WO03 to distinguish between working for pay and not working for pay P W39 and P W42 to distinguish between fulltime and part time employ ment P WO6 to distinguish between unemployment and inactivity The respondents who did not work during the week preceding the survey or did not have a job are asked the following question variable P W154 You are not currently in paid employment However since month year have you had a paid job also be it casual or on an irregular basis Respondents who worked at the time of the survey were asked the following question variable P W177 Since month year has there been a change in the number of hours you work have you star
132. zy W 11 W13 P C68 gets nervous easily W 11 W13 P C69 has artistic interests W 11 W13 Note 1 Only asked after W11 if this was the respondents first interview Scoring the BFI 10 scales P C60 P C66 P C67 and P C68 are reversed in valence items Each trait is measured with two items Extraversion P C60 R P C65 Agreeableness P C61 P C66 R Conscientiousness P C62 P C67 R Neuroticism P C63 P C68 R Openness P C64 P C69 R means reversed item 5 4 3 Self perception Six items measure a very general personal perception of the self Some items measure in how far respondents believe that their destiny is controlled by themselves and their own decisions or by external forces over which they do not have any power Individuals who believe more strongly that they control their own destiny are more likely develop a feeling of self efficacy The items are rated on an eleven point scale from O I completely disagree to 10 I completely agree The first four questions are adapted by Levy Joye Guye and Kauf mann p 510 1997 from Strodtbeck 1958 These items are directly related to the per ception of the level of self mastery and self efficacy toward the environment The last two items come from the self esteem scale by Rosenberg 1965 and reflect the ap praisal of one s own worth These questions are asked at regular intervals and were in cluded for the second time in W 14 66

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