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We carried out an harmonization of the Eurobarometer 2004-2021(spring). This dataset includes 35 single standard Eurobarometers, and morethan 140 variables about EU policies, attitudes towards Europe and the EU, identity, cognitive mobilization, political institutions, socio-political characteristics and partisanship, etc.

The harmonization was carried out using existing Eurobarometer datasets published by GESIS. To allow the user to replicate the harmonization and be able to modify some codes if needed, we publish one example of do-file used to pursue the harmonization, as well as the corresponding (harmonized) dataset. The user can find the do-file containing the codes used to modify and clean EB 953 (ZA7783, conducted in spring 2021) according to the harmonization procedure that we followed. Moreover, the user can find the cleaned dataset for EB 953 that was obtained after running the do-file. The files are named "EB 953.do" and "953_new.dta".

We include:
- a harmonized dataset ("harmonised_EB_2004-2021.dta"),
- a technical report ("User Guide Harmonized Eurobarometer 2004-2021"),
- a summary of the original survey questions corresponding to the variables included in the dataset ("Trends_EBs_1970-2021.xlsx"),
- one of the do-files used to carry out the harmonization ("EB 953.do" ),
- one of the datasets used before merging all datasets ("953_new.dta").

This codebook documents the harmonization of the Comparative Study of Electoral Systems Module 3 and the 2010 British Election Study internet data.

Published here is a Stata Do-File in which all data transformations and calculations for the reference publication are included (replication material).

On 21 May 2006, Swiss citizens adopted the revised education articles of the Federal Constitution by a large majority. Since then, the cantons have been obliged to harmonize key parameters of compulsory education at the national level. These include the age when starting school, compulsory schooling, the duration and objectives of educational levels, and the transitions between educational levels (Article 62(4) of the Federal Constitution).
In June 2011, for the first time, the 26 cantons approved national educational objectives for four subject areas and thereby created an important basis for the implementation of the constitutional mandate. These educational objectives define the basic competencies which pupils should acquire in the language of instruction, in a second national language and in English, in mathematics, as well as in natural sciences at defined school levels.
At the starting point of harmonization in 2017, the first nationwide tests were carried out in the framework of the review of the achievement of basic competencies to determine the extent to which Swiss pupils in the respective cantons had already achieved parts of these basic competencies in the language of instruction (reading and spelling) and in the first foreign language (reading and listening comprehension) at the end of primary school. On the one hand, the results were supposed to show the degree of similarity between the cantons at the beginning of the harmonization process and the degree to which the basic competencies were achieved in the assessed areas. On the other hand, this was the first time that such comprehensive data have been collected, which can be used for national educational monitoring and cantonal processes of educational quality development. To this end, the standardized performance tests were supplemented by a questionnaire on individual, school, and family characteristics, which represent key indicators for explaining differences in performance levels.
All 26 cantons participated with a representative sample. Schools and pupils were selected according to a two-stage sampling procedure. A total of 20,177 pupils took part, covering the whole of Switzerland. The tests and surveys took place between April 24 and June 2, 2017. They were administered by trained test managers and carried out according to a standardized procedure on tablets, which were brought to schools by trained test managers.
The results were published in May 2019.

On 21 May 2006, Swiss citizens adopted the revised education articles of the Federal Constitution by a large majority. Since then, the cantons have been obliged to harmonize key parameters of compulsory education at the national level. These include the age when starting school, compulsory schooling, the duration and objectives of educational levels, and the transitions between educational levels (Article 62(4) of the Federal Constitution).
In June 2011, for the first time, the 26 cantons approved national educational objectives for four subject areas and thereby created an important basis for the implementation of the constitutional mandate. These educational objectives define the basic competencies which pupils should acquire in the language of instruction, in a second national language and in English, in mathematics, as well as in natural sciences at defined school levels.
At the starting point of harmonization in 2017, the first nationwide tests were carried out in the framework of the review of the achievement of basic competencies to determine the extent to which Swiss pupils in the respective cantons had already achieved parts of these basic competencies in the language of instruction (reading and spelling) and in the first foreign language (reading and listening comprehension) at the end of primary school. On the one hand, the results were supposed to show the degree of similarity between the cantons at the beginning of the harmonization process and the degree to which the basic competencies were achieved in the assessed areas. On the other hand, this was the first time that such comprehensive data have been collected, which can be used for national educational monitoring and cantonal processes of educational quality development. To this end, the standardized performance tests were supplemented by a questionnaire on individual, school, and family characteristics, which represent key indicators for explaining differences in performance levels.
All 26 cantons participated with a representative sample. Schools and pupils were selected according to a two-stage sampling procedure. A total of 20,177 pupils took part, covering the whole of Switzerland. The tests and surveys took place between April 24 and June 2, 2017. They were administered by trained test managers and carried out according to a standardized procedure on tablets, which were brought to schools by trained test managers.
The results were published in May 2019.

On 21 May 2006, Swiss citizens adopted the revised education articles of the Federal Constitution by a large majority. Since then, the cantons have been obliged to harmonize key parameters of compulsory education at the national level. These include the age when starting school, compulsory schooling, the duration and objectives of educational levels, and the transitions between school levels (Article 62(4) of the Federal Constitution).
In June 2011, for the first time, the 26 cantons approved national educational objectives for four subject areas and thereby created an important basis for the implementation of the constitutional mandate. These educational objectives define the basic competencies which pupils should acquire in the language of instruction, in a second national language and in English, in mathematics, as well as in natural sciences at defined school levels.
In the framework of the review of the achievement of basic competencies, the first nationwide tests were conducted in 2016 to determine the extent to which Swiss pupils have already achieved parts of basic competencies in mathematics in the respective cantons at the end of compulsory schooling. On the one hand, the results were supposed to show the degree of similarity between the cantons at the start of harmonization and the degree to which the basic competencies were achieved in the assessed areas. On the other hand, this was the first time that such comprehensive data have been collected, which can be used for national educational monitoring and cantonal processes of quality development. To this end, the standardized performance tests in mathematics were supplemented by a questionnaire on individual, school, and family aspects, which represent key indicators for explaining differences in performance levels.
All 26 Swiss cantons participated with a representative sample. The schools and pupils were drawn according to a two-stage sampling procedure. A total of 22,423 pupils took part throughout Switzerland. The tests and surveys took place between May 2 and June 10, 2016. They were carried out online and computer-based according to a standardized procedure by trained test managers using the school infrastructure.
The results were published in May 2019.

The responsiveness of democratic institutions is a topic of fundamental importance to researchers, citizens, and decision-makers. The PolicyVotes project aimed to assemble a dataset that facilitates investigation of the responsiveness of political parties and governments to public preferences. The data collection efforts were motivated by the interest to allow researchers to examine, among many others, the following questions: Are governments responsive to citizen demands? Do we see policy changing in response to changing public preferences over time? Is a government's responsiveness to public demands more pronounced in some policy areas than in others and at some points in time than others? What is the mediating role of political institutions such as electoral systems, government types (coalition versus single-party) and executive-legislative structures? How does the degree of responsiveness of national governments compare to responsiveness of European institutions? What are the interdependencies of legislative decision-making between the national and the European level? Do national policies influence the development of European level public policies and vice versa?

The data collection we have assembled facilitates addressing these questions and others. It allows researchers to use large-N statistical methodologies to empirically test theoretical models of dynamic representation in a multilevel system of governance. It allows longitudinal comparative empirical analysis of the triangular relationship between preferences of the electorate, policy positions of parties and governments, and legislative outputs of national governments and the EU. With this data collection we are introducing efficiencies that enable researchers to examine how and under what circumstances responsiveness can be achieved in different institutional settings.

For individual-level data, we have harmonized Eurobarometers from 1970 to the 2011, the ISSP Role of Government surveys, and the EES voter Study. For measurements of party positions, we have harmonized and cross-linked the Chapel Hill Expert Survey, the Party Policy in Modern Democracies Dataset, the Comparative Manifesto Project data, and the EES Euromanifesto Study.
For the measurements of policy output we have collected and cross-linked data for legislative output and budget outlays of 15 EU governments and the European Union.

Please refer to the How-to-Guide and the user guides in the individual trendfile folders (see Downloads/Datasets) for detailed information and citation instructions. Following trendfiles and user guides are available:

- Arnold, Christine, Franklin, Mark, Wlezien, Christopher, Russo, Luana & Palacios, Irene (2023): PolicyVotes Database on Political Responsiveness. PolicyVotes Eurobarometer Trendfile. Data File Version 1.0.0, https://doi.org/10.7802/2618
- Arnold, Christine, Franklin, Mark, Wlezien, Christopher, Russo, Luana & Palacios, Irene (2023): PolicyVotes Database on Political Responsiveness. PolicyVotes Eurobarometer Trendfile User Guide. Version 1.0.0, https://doi.org/10.7802/2618
- Arnold, Christine, Franklin, Mark, Wlezien, Christopher, Sapir, Eliyahu & Williams, Christopher (2023): PolicyVotes Database on Political Responsiveness. PolicyVotes EES Voter Study Trendfile. Data File Version 1.0.0, https://doi.org/10.7802/2618
- Arnold, Christine, Franklin, Mark, Wlezien, Christopher, Sapir, Eliyahu & Williams, Christopher (2023): PolicyVotes Database on Political Responsiveness. PolicyVotes EES Voter Study Trendfile User Guide. Version 1.0.0, https://doi.org/10.7802/2618
- Arnold, Christine, Franklin, Mark, Wlezien, Christopher, Sapir, Eliyahu & Williams, Christopher (2023): PolicyVotes Database on Political Responsiveness. PolicyVotes ISSP Role of Government Trendfile. Data File Version 1.0.0, https://doi.org/10.7802/2618
- Arnold, Christine, Franklin, Mark, Wlezien, Christopher, Sapir, Eliyahu & Williams, Christopher (2023): PolicyVotes Database on Political Responsiveness. PolicyVotes ISSP Role of Government Trendfile User Guide. Version 1.0.0, https://doi.org/10.7802/2618
- Arnold, Christine, Franklin, Mark, Wlezien, Christopher, Sapir, Eliyahu & Williams, Christopher (2023): PolicyVotes Database on Political Responsiveness. PolicyVotes Party Positions Trendfile. Data File Version 1.0.0, https://doi.org/10.7802/2618
- Arnold, Christine, Franklin, Mark, Wlezien, Christopher, Sapir, Eliyahu & Williams, Christopher (2023): PolicyVotes Database on Political Responsiveness. PolicyVotes Party Positions Trendfile User Guide. Version 1.0.0, https://doi.org/10.7802/2618
- Arnold, Christine, Franklin, Mark, & Wlezien, Christopher (2023): PolicyVotes Database on Political Responsiveness. PolicyVotes National Budgets Trendfile. Data File Version 1.0.0, https://doi.org/10.7802/2618
- Arnold, Christine, Franklin, Mark, & Wlezien, Christopher (2023): PolicyVotes Database on Political Responsiveness. PolicyVotes National Budgets Trendfile User Guide. Version 1.0.0, https://doi.org/10.7802/2618
- Arnold, Christine, Franklin, Mark, & Wlezien, Christopher (2023): PolicyVotes Database on Political Responsiveness. PolicyVotes European Union Budget Trendfile. Data File Version 1.0.0, https://doi.org/10.7802/2618
- Arnold, Christine, Franklin, Mark, & Wlezien, Christopher (2023): PolicyVotes Database on Political Responsiveness. PolicyVotes European Union Budget Trendfile User Guide. Version 1.0.0, https://doi.org/10.7802/2618
- Arnold, Christine, Franklin, Mark, & Wlezien, Christopher (2023): PolicyVotes Database on Political Responsiveness. PolicyVotes European Union Legislation Trendfile. Data File Version 1.0.0, https://doi.org/10.7802/2618
- Arnold, Christine, Franklin, Mark, & Wlezien, Christopher (2023): PolicyVotes Database on Political Responsiveness. PolicyVotes European Union Legislation Trendfile User Guide. Version 1.0.0, https://doi.org/10.7802/2618
- Arnold, Christine, Franklin, Mark, Wlezien, Christopher, & Rahmani, Hossein (2023): PolicyVotes Database on Political Responsiveness. PolicyVotes National Legislation Trendfile. Data File Version 1.0.0, https://doi.org/10.7802/2618
- Arnold, Christine, Franklin, Mark, Wlezien, Christopher, & Rahmani, Hossein (2023): PolicyVotes Database on Political Responsiveness. PolicyVotes National Legislation Trendfile User Guide. Version 1.0.0, https://doi.org/10.7802/2618

Mandated by the Federal Chancellery, the research project VOTO analyses after each federal ballot the voting decisions of Swiss citizens. For this purpose, VOTO surveys about 1500 eligible voters all over Switzerland. VOTO is a joint project of the Swiss Centre of Competence in the Social Sciences FORS, the Centre for Democracy Studies Aarau (ZDA) and the Survey Institute LINK.

The standardized post-vote surveys are the result of the harmonization of the VOTO surveys. A standardization work has been necessary to make a comparison between two items possible. Since the surveys have renamed as "VOTO" instead of "VOX" with the vote of autumn 2016, the standardized surveys start with the VOTO survey no. 1 on the vote of 25.09.2016 and include between 2 and 4 surveys per year, depending on the number of ballots.

The VOTO data combines information from several sources into one file. First, the data integrates and harmonises the most significant variables in the post-vote surveys VOTO. A second type of variable includes specific characteristics of votes and items (i.e. popular initiatives or referendums) such as the date of the vote, the results of each item, participation rates, and the slogans of the federal government. The slogans of the main political parties are also integrated, according to information provided by the database Swissvotes, which is a project from the Année Politique Suisse of the Institute of Political Science of the University of Bern. Finally, the standardized surveys include a third type of variable, created specifically to synthesize certain data and/or to allow comparisons from across the whole range of the available surveys.

In the context of standardized surveys, all data related to a federal vote (that is, a federal voting weekend) is called a "scrutin". The term "projet", meanwhile, refers to a subset of these data, organized in relation to a to one of the specific items of this vote (initiative, referendum, etc.). As a general rule, a "scrutin" will therefore include as many "projects" as there were proposals in the vote data. More specifically, the VOTO surveys offer, for each vote, data in two forms: a "scrutin" file dedicated to the vote as a whole and an individual "project" file for each item submitted for a vote. The cumulative scrutin and project files are also available. The choice of file type is dependent on the analyses which the user would like to carry out.

A whole series of additional information about the VOTO Studies are available on the website https://www.voto.swiss.

Since 1977, a survey is carried out after each federal vote, offering insight into the voting of Swiss citizens. Up until June 2016 these surveys were carried out under the name of VOX. Beginning with the vote of autumn 2016 the surveys have renamed as "VOTO" and are also integrated into VoxIt.

The standardized post-vote surveys are the result of the harmonization of the VOX surveys. Indeed, the long history of these surveys has resulted in quite some changes over time, so much that a lot of standardization work has been necessary to make a comparison involving two very distant Vox surveys possible. Since the data from the first 14 surveys are no longer readable by current software, the standardized surveys start with the Vox survey no. 15 on the vote of 14.06.1981 and include between 2 and 4 surveys per year, depending on the number of votes.
The VoxIt data combines information from several sources into one file. First, the data integrates and harmonises the most significant variables in the post-vote surveys (VOX and VOTO). A second type of variable includes specific characteristics of votes and items (i.e. popular initiatives or referendums) such as the date of the vote, the results of each item, participation rates, and the slogans of the federal government. The slogans of the main political parties are also integrated, according to information provided by a database of the Institute of Political Science of the University of Bern. Finally, the standardized surveys include a third type of variable, created specifically to synthesize certain data and/or to allow comparisons from across the whole range of the available surveys.

In the context of standardized surveys, all data related to a federal vote (that is, a federal voting weekend) is called a "scrutin". The term "projet", meanwhile, refers to a subset of these data, organized in relation to a to one of the specific items of this vote (initiative, referendum, etc.). As a general rule, a "scrutin" will therefore include as many "projets" as there were items in the vote data, but it is possible that some "projets" will only be partially covered. More specifically, the VoxIt offer, for each vote, data in two forms: a "scrutin" file dedicated to the vote as a whole and an individual "projet" file for each item submitted for a vote. The choice of file type is dependent on the analyses which the user would like to carry out. The cumulative scrutin and projet files are also available. The choice of file type is dependent on the analyses which the user would like to carry out.

A whole series of additional information about the Voxit project and the standardized data are available on the website http://forscenter.ch/en/data-and-research-information-services/2221-2/special-projects/vox-voxit/ where you can also find information on accessing the cumulative files.

Since 1977, a survey is carried out after each federal vote, offering insight into the voting of Swiss citizens. Up until June 2016 these surveys were carried out under the name of VOX. Beginning with the vote of autumn 2016 the surveys have renamed as "VOTO" and are also integrated into VoxIt.

The standardized post-vote surveys are the result of the harmonization of the VOX surveys. Indeed, the long history of these surveys has resulted in quite some changes over time, so much that a lot of standardization work has been necessary to make a comparison involving two very distant Vox surveys possible. Since the data from the first 14 surveys are no longer readable by current software, the standardized surveys start with the Vox survey no. 15 on the vote of 14.06.1981 and include between 2 and 4 surveys per year, depending on the number of votes.
The VoxIt data combines information from several sources into one file. First, the data integrates and harmonises the most significant variables in the post-vote surveys (VOX and VOTO). A second type of variable includes specific characteristics of votes and items (i.e. popular initiatives or referendums) such as the date of the vote, the results of each item, participation rates, and the slogans of the federal government. The slogans of the main political parties are also integrated, according to information provided by a database of the Institute of Political Science of the University of Bern. Finally, the standardized surveys include a third type of variable, created specifically to synthesize certain data and/or to allow comparisons from across the whole range of the available surveys.

In the context of standardized surveys, all data related to a federal vote (that is, a federal voting weekend) is called a "scrutin". The term "projet", meanwhile, refers to a subset of these data, organized in relation to a to one of the specific items of this vote (initiative, referendum, etc.). As a general rule, a "scrutin" will therefore include as many "projets" as there were items in the vote data, but it is possible that some "projets" will only be partially covered. More specifically, the VoxIt offer, for each vote, data in two forms: a "scrutin" file dedicated to the vote as a whole and an individual "projet" file for each item submitted for a vote. The choice of file type is dependent on the analyses which the user would like to carry out. The cumulative scrutin and projet files are also available. The choice of file type is dependent on the analyses which the user would like to carry out.

A whole series of additional information about the Voxit project and the standardized data are available on the website http://forscenter.ch/en/data-and-research-information-services/2221-2/special-projects/vox-voxit/ where you can also find information on accessing the cumulative files.

Bei dem aufbereiteten Längsschnitt-Datensatzes 2014 bis 2016 handelt es sich um "Big-Data", weshalb der Gesamtdatensatz nur in Form einer Datenbank (MySQL) verfügbar sein wird. In dieser Datenbank liegt die Information verschiedener Variablen eines Befragten untereinander. Die vorliegende Publikation umfasst eine SQL-Datenbank mit den Meta-Daten des Sample des Gesamtdatensatzes, das einen Ausschnitt der verfügbaren Variablen des Gesamtdatensatzes darstellt und die Struktur der aufbereiteten Daten darlegen soll, und eine Datendokumentation des Samples. Für diesen Zweck beinhaltet das Sample alle Variablen der Soziodemographie, dem Freizeitverhalten, der Zusatzinformation zu einem Befragten und dessen Haushalt sowie den interviewspezifischen Variablen und Gewichte. Lediglich bei den Variablen bezüglich der Mediennutzung des Befragten, handelt es sich um eine kleine Auswahl: Für die Onlinemediennutzung wurden die Variablen aller Gesamtangebote sowie der Einzelangebote der Genre Politik und Digital aufgenommen. Die Mediennutzung von Radio, Print und TV wurde im Sample nicht berücksichtigt, da deren Struktur anhand der veröffentlichten Längsschnittdaten der Media-Analyse MA Radio, MA Pressemedien und MA Intermedia nachvollzogen werden kann.

Die Datenbank mit den tatsächlichen Befragungsdaten wäre auf Grund der Größe des Datenmaterials bereits im kritischen Bereich der Dateigröße für den normalen Up- und Download. Die tatsächlichen Befragungsergebnisse, die zur Analyse nötig sind, werden dann 2021 in Form des Gesamtdatensatzes der Media-Analyse-Daten: IntermediaPlus (2014-2016) im DBK bei GESIS veröffentlicht werden.



Die Daten sowie deren Datenaufbereitung sind ein Vorschlag eines Best-Practice Cases für Big-Data Management bzw. den Umgang mit Big-Data in den Sozialwissenschaften und mit sozialwissenschaftlichen Daten. Unter Verwendung der GESIS Software CharmStats, die im Rahmen dieses Projektes um Big-Data Features erweitert wurde, erfolgt die Dokumentation und Herstellung der Transparenz der Harmonisierungsarbeit. Durch ein Python-Skript sowie ein html-Template wurde der Arbeitsprozess um und mit CharmStats zudem stärker automatisiert.



Der aufbereitete Längsschnitt des Gesamtdatensatzes der MA IntermediaPlus für 2014 bis 2016 wird 2021 in Kooperation mit GESIS herausgegeben werden und den FAIR-Prinzipien (Wilkinson et al. 2016) entsprechend verfügbar gemacht werden. Ziel ist es durch die Harmonisierung der einzelnen Querschnitte die Datenquelle der Media-Analyse, die im Rahmen des Dissertationsprojektes "Angebots- und Publikumsfragmentierung online" durch Inga Brentel und Céline Fabienne Kampes erfolgt, für Forschung zum sozialen und medialen Wandel in der Bundesrepublik Deutschland zugänglich zu machen.



Künftige Studiennummer des Gesamtdatensatzes der IndermediaPlus im DBK der GESIS: ZA5769 (Version 1-0-0) und der doi: https://dx.doi.org/10.4232/1.13530



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The prepared Longitudinal IntermediaPlus dataset 2014 to 2016 is a "big data", which is why the entire dataset will only be available in the form of a database (MySQL). In this database, the information of different variables of a respondent is organized in one column, one below the other. The present publication includes a SQL-Database with the meta data of a sample of the full database, which represents a section of the available variables of the total data set and is intended to show the structure of the prepared data and the data-documentation (codebook) of the sample. For this purpose, the sample contains all variables of sociodemography, free-time activities, additional information on a respondent and his household as well as the interview-specific variables and weights. Only the variables concerning the respondent's media use are a small selection: For online media use, the variables of all overall offerings as well as the individual offerings of the genres politics and digital were included. The media use of radio, print and TV was not included in the sample because its structure can be traced using the published longitudinal data of the media analysis MA Radio, MA Pressemedien and MA Intermedia.

Due to the size of the datafile, the database with the actual survey data would already be in the critical range of the file size for the common upload and download. The actual survey results required for analysis will be published in 2021 in the form of the total dataset of the Longitudinal IntermediaPlus (2014-2016) dataset at the GESIS DBK.



The data as well as their data preparation are a proposal for a best practice case for big-data management and/or the handling of big data in the social sciences and with social science data. Using the GESIS software CharmStats, which was extended by big-data features within this project, the documentation and creation of transparency of the harmonization work is carried out. A Python script and an html template have been used to automate the workflow with and within CharmStats.



The full dataset of the Longitudinal IntermediaPlus for 2014 to 2016 will be published in 2021 in cooperation with GESIS and made available in accordance with the FAIR principles (Wilkinson et al. 2016). By harmonizing and pooling the cross-sectional datasets to one longitudinal dataset – which is being carried out by Inga Brentel and Céline Fabienne Kampes as part of the dissertation project "Audience and Market Fragmentation online" –, the aim is to make the data source of the media analysis, accessible for research on social and media change in the Federal Republic of Germany.



The future study number of full the Longitudinal IntermediaPlus (2014-2016) dataset at the GESIS DBK will be: ZA5769 (Version 1.0.0) and doi: https://dx.doi.org/10.4232/1.13530

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Deutsche Version (English version below)

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Das "Occupational Panel on Tasks and Education (OPTE)" beschreibt für die Jahre von 1973 bis 2011 Tätigkeitsprofile, Bildungsinvestitionszeiten und das Ausbildungsverhalten differenziert nach 179 harmonisierten Berufsgruppen. Es wurde für das Dissertationsprojekt "Die Anwendbarkeit des Erlernten in den wandelnden Bildungs- und Arbeitslandschaften der 1970er bis 2000er Jahre" erstellt. Die Dissertationsschrift ist unter https://kops.uni-konstanz.de/handle/123456789/49897 frei zugänglich und beschreibt (im Anhang) ausführlich die Erstellung der mit diesem Panel veröffentlichten Variablen.

Die Datenbasis für das Panel auf Berufsebene bilden die Scientific Use Files (SUF) des deutschen Mikrozensus. Diese erfassen den ausgeübten Beruf bis zum Jahr 1993 nach der Klassifikation der Berufe des Jahres 1975 (KldB75). In den nachfolgenden Erhebungsjahren erfolgt die Erfassung nach der Klassifikation der Berufe des Jahres 1992 (KldB92). Beide Berufsklassifikationen wurden nach dem Prinzip des kleinsten gemeinsamen Nenners so aggregiert, dass über den gesamten Zeitraum von 1973 bis 2011 eine homogene Messung von Berufsordnungen erfolgt. Zudem wurden die Daten auch auf die Klassifikation der Berufe des Jahres 1988 (KldB88) umgeschlüsselt, um ein Zuspielen der Berufsinformationen zu anderen Datensätzen zu ermöglichen, welche den Beruf nach der KldB75, KldB88 oder KldB92 erfassen. Das Excel-Dokument "Transition_key_occupational_groups_KldB75_88_92.xlsx" gibt die Zuordnung der Berufscodes der KldB75, KldB88 oder KldB92 zur harmonisierten KldB88h wieder.



Auf der Ebene der 179 harmonisierten Berufsordnungen werden Veränderungen im Tätigkeitsprofil, in den Bildungsinvestitionen und im Ausbildungsverhalten über die Zeit beschrieben. Diese werden aus folgenden Informationen der Mikrozensus-SUF's erhalten:



Tätigkeitsprofile: In den Jahren 1973, 1976, 1978, 1980, 1982, 1985, 1987, 1989, 1991, 1993, 1995, 1996, 2000, 2004, 2007, 2011 wird jeweils die Frage nach der "überwiegend ausgeübten Tätigkeit" in der Haupterwerbstätigkeit gestellt. Die möglichen Antwortvorgaben unterscheiden sich in den einzelnen Erhebungsjahren. Grob gesagt kann zwischen drei Perioden (1973 bis 1980, 1982 bis 1995 und 1996 bis 2011) der Tätigkeitsmessung unterschieden werden. Die erfassten Haupttätigkeitsschwerpunkte können jedoch harmonisiert werden, so dass für jede harmonisierte Berufsgruppe über die Zeit nachvollziehbar ist, wie hoch der Anteil an Personen in einem Beruf ist, die in einem Jahr folgende elf Haupttätigkeitsschwerpunkte ausgeübt haben:

• taskshare 1: "Maschinen einrichten/einstellen"

• taskshare 2: "Gewinnen/herstellen"

• taskshare 3: "Reparieren/ausbessern"

• taskshare 4: "Verkaufen/beraten/verhandeln"

• taskshare 5: "Schreibarbeiten/kalkulieren"

• taskshare 6: "Analysieren/messen/forschen"

• taskshare 7: "Disponieren/koordinieren"

• taskshare 8: "Bewirten/reinigen/transportieren"

• taskshare 9: "Bewachen/Gesetze anwenden"

• taskshare 10: "Lehren/ausbilden/publizieren/unterhalten"

• taskshare 11: "Pflegen/medizinisch kosmetisch behandeln"



Das Vorgehen zur Harmonisierung wird in der Dissertation ab Seite 299 (Anhang A) und in doi.org/10.1007/s11135-021-01158-y beschrieben. Die Tätigkeitsprofile in den "Zwischenjahren", in welchen keine SUFs des Mikrozensus zur Verfügung stehen, wurden interpoliert. Anschließend wurden die Tätigkeitsanteile mit einem Moving-Average (t-3, t, t+3) geglättet. Die mit diesem Panel veröffentlichten Tätigkeitsanteile unterscheiden sich von der in der Dissertation verwendeten Tätigkeitsanteilen, indem auch Nichtdeutsche und Erwerbstätige mit weniger als zehn Wochenstunden Arbeit berücksichtigt werden. Zudem werden die Tätigkeitsanteile nach den Arbeitsstunden der Erwerbstätigen gewichtet und anonymisiert.



Anonymisierung der Tätigkeitsprofile: Die Fallzahl "N" gibt die hochgerechneten, interpolierten und mit Moving-Average (t-3, t, t+3) geglättete Anzahl an Erwerbstätigen in der Berufsordnung wieder. Wird eine Aggregation der Berufsordnungen angestrebt, kann "N" genutzt werden, um z.B. gewichtete Durchschnitte zu berechnen. Multipliziert man "N" mit den jeweiligen Tätigkeitsanteilen "taskshare_..." erhält man eine "fiktive" Zahl an Erwerbstätigen, die diese Haupttätigkeit im Beruf ausüben. Die Zahl ist fiktiv, weil es sich aufgrund der Harmonisierung um geschätzte Tätigkeitsanteile handelt, die zudem mit der jeweiligen Stundenanzahl der Erwerbstätigen gewichtet sind. Einzelfälle können deshalb sowieso nicht zweifelsfrei identifiziert werden. Um eine mögliche Deanonymisierung faktisch weiter zu erschweren, wurden des Weiteren sichergestellt, dass hinter jeder genannten Tätigkeit mindestens drei "fiktive Personen" stehen. Haupttätigkeiten in einem Beruf wurden deshalb mit ein oder zwei weiteren Haupttätigkeiten zusammengefasst, bis in Summe über drei "fiktive Personen" diese Haupttätigkeiten ausübten. Die ursprüngliche "fiktive Personenanzahl" in diesen Haupttätigkeiten wurden anschließend mit der durchschnittlichen Anzahl der "fiktiven Personen" aus diesen Haupttätigkeiten ersetzt. War eine Zusammenfassung im Querschnitt nicht sinnvoll, weil sich der nächstgrößte Tätigkeitsanteil stärker vom kleinsten Tätigkeitsanteil unterschied (weil dieser mehr als 10 "fiktive Personen" enthielt) wurde eine Aggregation über die Erhebungsjahre gewählt. In diesem Fall wurden die Erhebungsjahre solange zusammengefasst, bis in jeder Tätigkeit des Berufs mindestens drei "fiktive Personen" enthalten waren. Die Tätigkeitsanteile des Berufs wurden anschließend mit den durchschnittlichen Tätigkeitsanteilen der zusammengefassten Erhebungsjahre ersetzt. Zuletzt wurden alle Tätigkeitsanteile gerundet. Aufgrund dieser Rundung ergibt die Summe aller Tätigkeitsanteilen einer Berufsgruppe nicht immer den Wert 1. Ist dies für die weiteren Analysen notwendig, sollten die Tätigkeitsanteile so skaliert werden, dass sie in Summe 1 ergeben.



Die Variable "N_soc" gibt die Anzahl der hochgerechneten, interpolierten und mit einem Moving-Average (t-3, t, t+3) geglätteten abhängig Beschäftigten "Angestellte, Arbeiter, Heimarbeiter" (ohne Auszubildende) aus dem Mikrozensus wieder. Die Variable "taskshare_socsec_..." gibt die dazugehörigen Tätigkeitsanteile der abhängig Beschäftigten wieder. Die Anonymisierung erfolgte in derselben Weise wie bei den Tätigkeitsanteilen "taskshare_..." mit allen Erwerbstätigen. Um Einzelfallidentifikationen durch die Subtraktion von "N_socsec" von "N" zu vermeiden, wurden die Tätigkeitsanteile "taskshare_socsec_..." mit den Tätigkeitsanteilen "taskshare_..." aller Erwerbstätigen ersetzt, sofern N-N_socsecEnglish version
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The "Occupational Panel on Tasks and Education (OPTE)" describes task profiles, education investment periods and training behavior differentiated by 179 harmonized occupational groups for the years from 1973 to 2011. It was prepared for the dissertation project "The Applicability of the Learned in the Changing Educational and Labor Landscapes of the 1970s to 2000s." The dissertation paper (in German) is freely available at https://kops.uni-konstanz.de/handle/123456789/49897 and describes in detail (in the appendix) the creation of the variables published with this panel. The creation of the task variables is also decribed in English in doi.org/10.1007/s11135-021-01158-y



The data basis for the occupation-level panel are the Scientific Use Files (SUF) of the German Microcensus. These record the occupation up to 1993 according to the 1975 classification of occupations (KldB75). In subsequent survey years, the occupation is recorded according to the 1992 classification of occupations (KldB92). Both occupational classifications were aggregated according to the principle of the lowest common denominator in such a way that there is a homogeneous measurement of occupational classifications over the entire period from 1973 to 2011. In addition, the data were also recoded to the 1988 Classification of Occupations (KldB88) to allow matching of occupational information to other datasets that record the occupation according to KldB75, KldB88, or KldB92. The Excel document "Transition_key_occupational_groups_KldB75_88_92.xlsx" shows the mapping of the occupation codes of KldB75, KldB88 or KldB92 to the harmonized KldB88h.



At the level of the 179 harmonized occupational codes, changes in task profile, educational investments and educational behavior over time are described. These are obtained from the following information from the Microcensus SUF's:

Task profiles: In each of the years 1973, 1976, 1978, 1980, 1982, 1985, 1987, 1989, 1991, 1993, 1995, 1996, 2000, 2004, 2007, 2011, the question about the "predominantly performed activity" in the main job is asked. The possible answer specifications differ in the individual survey years. Roughly speaking, a distinction can be made between three periods (1973 to 1980, 1982 to 1995, and 1996 to 2011) of task measurement. However, the main task recorded can be harmonized so that for each harmonized occupational group it is possible to track over time the proportion of people in an occupation who performed the following eleven main activity foci in a given year:

• taskshare 1: "setting up/adjusting machines"

• taskshare 2: "extraction/manufacturing"

• taskshare 3: "repairing/mending"

• taskshare 4: "selling/advising/negotiating"

• taskshare 5: "typewriting/calculating"

• taskshare 6: "analyzing/measuring/researching"

• taskshare 7: "scheduling/coordinating"

• taskshare 8: "serving/accommodating/cleaning/transport"

• taskshare 9: "securing/guarding/applying laws"

• taskshare 10: "teaching/educating/publishing"

• taskshare 11: "nursing/treating medically or cosmetically."



The procedure for harmonization is described in doi.org/10.1007/s11135-021-01158-y .

Anonymization of task profiles: The case number "N" reflects the extrapolated, interpolated and moving-average (t-3, t, t+3) smoothed number of employed persons in the occupational group. If aggregation of occupational groups is desired, "N" can be used to calculate weighted averages, for example. Multiplying "N" by the respective activity shares "taskshare_..." yields a "fictitious" number of employed persons performing this main activity in the occupation. The number is fictitious because, due to harmonization, it is an estimated activity share, which is also weighted with the respective number of hours of the employed persons. Individual cases can therefore not be identified beyond doubt anyway. Furthermore, in order to make deanonymization even more difficult, it was ensured that at least three "fictitious" persons are behind each activity mentioned. Main activities in an occupation were therefore combined with one or two other main activities until a total of more than three "fictitious persons" performed these main activities. The original "notional number of persons" in these main activities were then replaced with the average number of "notional persons" from these main activities. If a cross-sectional aggregation did not make sense because the next largest activity share was more different from the smallest activity share (because the latter contained more than 10 "fictitious persons"), an aggregation over the survey years was chosen. In this case, survey years were aggregated until each activity in the occupation contained at least three "notional persons". The occupation's activity shares were then replaced with the average activity shares of the aggregated survey years. Finally, all task shares were rounded. Due to this rounding, the sum of all task shares of an occupational group does not always add up to 1. If this is necessary for further analyses, the activity shares should be scaled so that they add up to 1.



The variable "N_soc" reflects the number of extrapolated, interpolated and moving-average (t-3, t, t+3) smoothed dependent employees "white-collar workers, blue-collar workers, homeworkers" (without apprentices) from the microcensus. The variable "taskshare_socsec_..." reflects the corresponding activity shares of the dependent employees. Anonymization was carried out in the same way as for the activity shares "taskshare_..." with all employed persons. To avoid individual case identifications by subtracting "N_socsec" from "N", the activity shares "taskshare_socsec_..." were replaced with the activity shares "taskshare_..." of all employed persons, if N-N_socsec<5000. The corresponding cases are labeled with the variable "anonymous_socsec".



Educational investment: For the variable "educ_invest", the education time in months formally required to obtain the general education and last/highest vocational qualification was calculated from the Microcensus SUF's of 1973, 1976, 1978, 1980, 1982, 1985, 1987, 1989, 1991, 1993 and 1995 to 2011 for all employed persons. For example, a secondary general school certificate was measured as 108 months (9 years) and a "completion of apprenticeship training or equivalent vocational school qualification" as 36 months (3 years). A detailed list and justification of the education periods assigned to each by degree can be found in the dissertation beginning on page 308 (Appendix B). The "average formal education time" of an occupation was calculated using the average education time of all employed persons in the harmonized occupational group. The "intermediate years" in which no SUF was available were interpolated. Subsequently, the values were smoothed with a moving average (t-3, t, t+3).



Training behavior (supply-demand relation): The Federal Institute for Vocational Education and Training (BIBB) converted the major field of the highest vocational qualification in combination with the training institution into a learned occupation according to KldB92. The heuristic procedure for this is described in Maier and Helmrich (2012). To calculate the supply-demand relation ("sdr"), the microcensuses (on-site) from 2005 to 2012 are pooled and a relative distribution of vocational degrees according to the harmonized occupational classification KldB88h is calculated for all degree years from 1973 to 2012. This distribution is contrasted with the relative distribution of employment shares according to KldB88h for the respective years. The procedure is described in the dissertation on page 86 and 145-147 and plausibilized starting on page 328 (Appendix D). The variable "ln_sdr" corresponds to ln(sdr).