ESRA 2019 Draft Programme at a Glance
Linked administrative data and applications for evidence building 3
|Session Organisers|| Dr Asaph Young Chun (U.S. Census Bureau)
Dr Manfred Antoni (Institute for Employment Research (IAB), Germany)
|Time||Thursday 18th July, 16:00 - 17:30|
The survey data linked to multiple data sources, such as administrative records and big data, are increasingly at the heart of evidence-based policy making across continents. We call the multiply linked data as "pandata" (Chun and Scheuren, 2011). This session presents papers that demonstrate how multiple sources of data linked together are instrumental to evidence-based policy making. In the vein of papers published in a Wiley book (Chun, Larsen, Durant, and Reiter, forthcoming 2019), "Administrative Records for Survey Methodology," this session will discuss linked administrative data papers that address the following topics of substantive applications or methodological research:
- Papers demonstrating the use of administrative records linked to survey data in developing or evaluating public policy. For example, how administrative data linked to survey data have informed the policy making process to bring about social and economic benefits that were not possible to research by relying on traditional survey data alone?
- Substantive census applications where administrative data are linked and transformed into information that is useful and relevant to policy making.
- Papers utilizing dynamic data visualization involving the data linked by multiple data sources to communicate the public policy issues.
- Papers involving experimental design, such as randomized controlled trials, to advance evidence-based policy making with case studies in economics, education, and public health.
- Recent methodological advancements in linking administrative data with survey data (one-to-one) or with multiple sources of data (one-to-many).
- Papers applying Bayesian approaches to using linked administrative data in order to produce information that is useful and relevant to key sectors of health, economy and education.
Keywords: administrative records, evidence-based policymaking, linked data, multiple data sources
Foot-in-the-door or door-in-the-face? A survey experiment on multiple requests for consent to data linkage
Ms Sandra Walzenbach (ISER, University of Essex) - Presenting Author
Mrs Annette Jäckle (ISER, University of Essex)
Mr Jon Burton (ISER, University of Essex)
Mr Mick P. Couper (University of Michigan)
Mr Tom Crossley (ISER, University of Essex)
To fill information gaps or avoid cognitively demanding recall questions, it is increasingly common for researchers to link survey data to administrative data. If several administrative data sources are of interest, respondents are required to give consent to each of them, meaning that multiple consent questions must be included in one survey. Researchers face the challenge of maximising consent rates, but also of ensuring that consent is informed by presenting relevant information in an accessible way.
So far, very little is known about how respondents process information and make decisions when asked for consent. The existing literature suggests that individual consent varies widely between administrative data sources and also over time.
Using an online access panel, we collected survey data from 5,500 respondents in Great Britain to shed light on how people process linkage requests and which question features help them to undergo an informed decision process, particularly when asked for multiple consents at the same time.
The collected data comprises consent decisions with regard to five different administrative data sources (records on income and taxes, unemployment benefits, energy use, education, and health) as well as information on the respondents’ perceived sensitivity of these consent domains. In addition, participants answered several objective and subjective questions to ascertain their understanding of the consent process and their confidence in the decision made. We experimentally varied the order of the requests (from most to least sensitive, or vice versa) and the format of the question (each consent asked on a separate page or all consents presented together on a single page). This allows us to estimate to what extent consent and understanding are influenced by question order and variations in question wording and page sequencing.
Young people’s consent and data linkage between survey data to multiple data sources
Ms Dinusha Bandara (Australian Institute of Family Studies) - Presenting Author
Dr Galina Daraganova (Australian Institute of Family Studies)
There is established recognition of the value of data linkage to inform policy, research and service delivery to improve health and quality of life. While there have been notable developments in data linkage, the administrative data is collected for specific purposes, rarely include reference population, and lack information on individual-level and contextual variables. Linking key administrative datasets to the existing longitudinal studies will provide the opportunity to transform data into valuable data assets that would be used to enable, enhance and inform research and policy development.
The Longitudinal Study of Australian Children (LSAC) is Australia’s first nationally-representative longitudinal study of child development. Since 2004, two cohorts of 5,000 children and their parents have been interviewed every two years. Over the years, multiple data linkage in LSAC has been undertaken using consent, to enhance insight and broadens the range of research questions that can be explored. Depending on participant age, either parental consent (on behalf of their children) or participant consent was obtained. As data linkage can add new dimensions, enrich detail and reduce respondent burden, LSAC data has been linked to different types of national administrative data from multiple data sources. These include Medicare Benefits Schedule, Pharmaceutical Benefits Scheme, Repatriation Pharmaceutical Benefits Scheme, Australian Childhood Immunisation Register, National Assessment Program – Literacy and Numeracy, Australian Early Development Census, Australian Curriculum Assessment and Reporting Authority (also known as MySchool), and Centrelink. These linkages permit a range of research possibilities, including the capacity to inform and develop evidence-based policies.
This paper will focus on current LSAC data linkage landscape, challenges of LSAC data linkage (such as biases introduced by linked data and analytical issues) and future of LSAC data linkage which will be instrumental for the development of evidence-based policies.
Theatregoers’ choice of seat and performance: combined revealed-stated preference approach
Mrs Alina Ozhegova (National Research University Higher School of Economics) - Presenting Author
Mr Evgeniy Ozhegov (National Research University Higher School of Economics)
Theatrical productions are supposed to be perishable good, since the tickets for a particular play cannot be inventoried and sold after a time of play. In the revenue management of a perishable good price discrimination is widely used. Since the theatre audience is heterogeneous in terms of visit purpose, ability to perceive quality, willingness-to-pay, the strategy of price discrimination should be developed in the context of theatre segments. In this paper, we segment consumers of Perm Opera and Ballet Theatre, that allows to propose marketing instruments to increase theatre revenue. Since development of detailed price discrimination strategy requires data on consumer's purchase history, his behavioral and socio-demographic characteristics, we combine two data sources: data on ticket purchases and data obtained from survey. Having a database with consumer emails, we conduct email-based online survey. The part of survey is devoted to the discrete choice experiment, that permits to imitate the real choice of ticket in the theatre with induced variation in the price. Using modication of latent class logit model for joint revealed and stated preferences data we identify four segments of the theater's audience. The study proves that the representatives of segments have different willingness to pay for performance and seat location characteristics, which allows developing detailed recommendations on the pricing
strategy for various theater audiences. The availability of the survey data also allows obtaining a meaningful interpretation of the results and describing the resulting segments in terms of sociodemographic characteristics.
The ODISSEI Data Facility
Dr Tom Emery (ODISSEI) - Presenting Author
The Open Data Infrastructure for Social Science and Economic Innovations (ODISSEI, http://www.odissei-data.nl/) is the Dutch national infrastructure for the social sciences. The aim of the infrastructure is to coordinate social science data collection efforts within the Netherlands and ensure their integration with e-infrastructures and alignment with the research aims of the scientific and policy making communities.
At the heart of ODISSEI is the development of the ODISSEI data platform which brings together three crucial components that are required for cutting edge research in the social sciences. Firstly, the platform provides researchers with secure remote access to depersonalized administrative data on every individual in the country, held by Statistics Netherlands. Secondly, social scientists can import their own data from surveys or other sources and link these to administrative data, enriching it with diverse and complex data forms that are necessary for scientific research. The Netherlands has high quality persistent identifiers for persons and entities that make this process very straight forward and reliable. Finally, the platform is situated within a high-performance computing environment provided by SURFsara (https://www.surf.nl/en/about-surf/subsidiaries/surfsara/), which is the Dutch high-performance computing facility for science and industry.
In this presentation we provide a technical overview of the ODISSEI data platform and its development through its initial prototype and piloting stages. We will also introduce several use cases drawn from a broad range of disciplines. For example, the first project to conduct analysis using the ODISSEI data platform combined administrative records with detailed genetic data to examine the contextual determinants of depression. In this new HPC environment a first record linkage project of administrative and genetic variant data has been carried out to run genome wide association studies (GWAS). This is only possible with a secure high-performance data platform.