AUTNES Comparative Study of Electoral Systems Post-Election Survey 2013 - Documentation (Edition 2.0.0) Page 1 AUTNES Comparative Study of Electoral Systems Post-Election Survey 2013 Sylvia Kritzinger, Kathrin Thomas, Christian Glantschnigg, Julian Aichholzer, Konstantin Glinitzer, David Johann, Markus Wagner, Eva Zeglovits. (Edition 2.0.0, 2016) [email protected] http://www.autnes.at 2 Page Contents 1. Introduction 4 1.1 How to cite these data 4 1.2 Changes in Edition 2.0.0 4 2. Conditions of Use 5 2.1 Restrictions 5 2.2 Confidentiality 5 2.3 Deposit Requirement 5 3. Study Description 6 3.1 Title 6 3.2 Principal Investigators 6 3.3 Funding / Acknowledgments 6 3.4 Fieldwork 6 3.5 File Name 7 3.6 Keywords 7 4. Study Design 8 4.1 Fieldwork 8 4.2 Sampling Procedure 8 4.3 Quality control 8 4.4 Response Rate 11 4.5 Post Stratification Weight 11 5. Questionnaire 14 5.1 Questionnaire Development and Quality Assessment 14 5.2 Language 15 5.3 Deviation Notes 15 6. Codebook 34 3 Page 1. Introduction The Documentation of the Austrian National Election Study (AUTNES) Comparative Study of Electoral Systems Post Election Survey 2013 accompanies the data files and provides useful information about the data, coding and any related issues. The Austrian National Parliamentary Elections were held on 29 September 2013. 1.1 How to cite these data Data users are kindly asked to acknowledge the data and the accompanying release document. Please refer to the GESIS data catalogue (www.gesis.org) for a recommendation on how to cite the data and the documentation. 1.2 Changes in Edition 2.0.0 For an overview of changes between the first version of this data (Edition 1.0.0; 2014) and the current version 2.0.0, please look at the document “ZA5856_changes_in_v2-0-0.pdf” available on the GESIS website. 4 Page 2. Conditions of Use 2.1 Restrictions The data are available for non-profit use without any restrictions. 2.2 Confidentiality AUTNES, the Principal Investigators and the funding institutions are neither responsible for the use of the data or for interpretations or inferences based on their use, nor do they accept liability for indirect, consequential or incidental damages or losses arising from use of the data. 2.3 Deposit Requirement In order to facilitate exchange within the scientific community and to provide the funding agencies with the essential information about the use of the archival resources, users of the AUTNES data are requested to notify the AUTNES team of all forms of publications based on the AUTNES data. 5 Page 3. Study Description 3.1 Title The Comparative Study of Electoral Systems Post-Election Survey 2013. 3.2 Principal Investigators Wolfgang C. Müller, University of Vienna (AUTNES Supply Side) Sylvia Kritzinger, University of Vienna (AUTNES Demand Side) Klaus Schönbach, University of Vienna (AUTNES Media Side) 3.3 Funding / Acknowledgments The survey was carried out under the auspices of the Austrian National Election Study (AUTNES) and the National Research Network (NFN). It was sponsored by the Austrian Research Fund (FWF) (S10902-G11). FWF Austrian Science Fund. 3.4 Fieldwork Jaksch & Partner Schillerstraße 8 4020 Linz Austria Email: [email protected] http://www.jaksch-partner.at/ 6 Page 3.5 File Name The AUTNES provides a German and an English version of the data as well as two different formats. A SPSS readable data file (.sav), and a Stata format (.dta). ZA5856_de_v2-0-0.sav ZA5856_en_v2-0-0.sav ZA5856_de_v2-0-0.dat ZA5856_en_v2-0-0.dat 3.6 Keywords Distributional politics and social protection, mobilization, political knowledge 7 Page 4. Study Design 4.1 Fieldwork Fieldwork was carried out by the field institute Jaksch & Partner between 1 October 2013 and 29 October 2013 using Computer Assisted Telephone Interviewing (CATI). In total, 1000 interviews were completed. 4.2 Sampling Procedure The sampling method employed was stratified random sampling. The stratification characteristics were the nine Austrian provinces (“Bundesländer”). Within the Austrian provinces an unlimited random sample was drawn and respondents were sampled proportional to the population size. Phone numbers were randomly selected using a dual sampling frame (Random Digit Dialling: 89.1% and Randomised Last Digits: 10.9%). Within each household, the last-birthday method was used to randomly select the respondent. The last birthday method is a quick and easy method of selecting respondents within a sampled household in random-digit dialling surveys. It asks for the eligible person within the sampling unit who had the most recent birthday. The sample is representative of the eligible Austrian voters. These are citizens aged 16 and older. Please see also Section 4.5. 4.3 Quality control In order to ensure the quality of the data, several quality checks were conducted throughout the data gathering process: 1) Quality control of the questionnaire 2) interviewer training, 3) quality control during the field period, 4) post-field work interview verification, and 5) data cleaning. 8 Page (1) Quality control of the questionnaire was conducted by trained members of staff at Jaksch & Parter with regard to the completeness, plausibility, and formal correctness of the questionnaire. (2) Prior to the interviewing process, a training session for the interviewers was held at the field institute under the supervision of senior researchers at Jaksch & Partner as well as a member of the AUTNES team. The training included: Intensive interviewer briefing by the project leader at Jaksch & Partner Presentation and practice of the questionnaire Group as well as individual exercises Observation and control by the senior researchers The senior investigators at Jaksch & Partner as well as an AUTNES team member were available to answer questions about any component of the survey throughout the training session. (3) During the field period, respondents were contacted up to five times until a non-sample was declared. In addition, several techniques were employed to persuade those respondents who indicated at first contact that they were undecided whether or not they wanted to participate. For instance, the household was passed on to a more experienced interviewer and they re- contacted the household up to three times in order to persuade them to participate in the survey. Individual interviews and interviewer feedback were recorded for quality control in the call centre. Jaksch & Partner also established a daily quality control process of the field work by the project leader. 9 Page (4) After the interview, some respondents were re-contacted by Jaksch & Partner in order to verify the data and assess their quality. In total, 10% of the interviews were evaluated and respondents asked about their personal interview situation. (5) Team members at Jaksch & Partner also did the data cleaning, which included checking the completeness, plausibility and consistency of the data. If applicable, missing or incorrect information were re-collected or corrected. The data cleaning was conducted manually as well as computer assisted. In addition, members of the AUTNES team double checked for duplicates, removed typographical errors as well as validated and corrected values against a known list of entries, whenever possible. The latter predominantly applied to contextual data that could be inferred from the postal code. 10 Page 4.4 Response Rate The response rate for the CSES post-election survey is 52.1%. Please see Table 1 for a detailed account. Table 1: Response Rate Total % of Total % of Number of the overall the net Cases sample sample No response after 5 contact attempts/non-contact 4238 28.2% No contact/incorrect number 6721 44.8% No private household 1765 11.8% Housing units with no eligible respondents 356 2.4% Completed interviews 1000 52.1% Interrupted interviews 0 0.0% Target respondent identified, but refused 739 38.5% Target respondent identified, but unable to participate 78 4.1% Target respondent identified, but language problems 84 4.4% Other reasons for non-response 19 1.0% Total 15000 100.0% 4.5 Post Stratification Weight The dataset includes a post-stratification weight (gew). The weight variables were computed on the basis of the following socio-demographic characteristics: Gender Age Education Household size Provinces (‘Bundesländer’) Employment status 11 Page The weight’s values range from a minimum of 0.51 to a maximum value of 3.57. The target distributions are based on StatCube Micro Census data 2012 (Statistics Austria, StatCube, last accessed in September 2013). StatCube data refers to all Austrian citizens aged ≥ 15, a total of 6325600 residents. Table 2 displays the actual estimates of the total Austrian target population as well as the weighted values in the sample: Table 2: Expected Socio-Demographic Characteristics and Weighted Values Expected Values after Socio-Demographics values weighting Gender male 48.6% 48.4% female 51.4% 51.6% Age 15 to 17 years old 4.3% 3.8% 18 to 21 years old 5.7% 5.2% 22 to 24 years old 4.3% 4.1% 25 to 34 years old 13.8% 14.2% 35 to 44 years old 17.2% 17.7% 45 to 54 years old 19.1% 19.2% 55 to 64 years old 14.1% 14.7% 65+ years old 21.6% 21.0% Education no school/primary school/lower secondary level 24.5% 23.9% vocational training/vocational school 36.6% 36.3% higher vocational school (BMS) 13.8% 13.4% secondary school leaving certificate (=Matura) 14.4% 15.0% university-related institution/tertiary education 10.7% 11.3% Household size single person household 19.2% 19.8% 2 person household 29.5% 30.2% 3 person household