Survey Combining Multi-mode Data Collection and Big Data Extracts - PowerPoint PPT Presentation

Towards an integrated Consumer Expenditure Survey Combining Multi-mode Data Collection and Big Data Extracts Gustav Haraldsen, Sverre Amdam, Li-Chun Zhang

CES 2012 • The diary is the most burdensome and costly part of the design. • Response burden affect both quality and actual cost in a negative way • The diary information cover a rather small part of the consumption 2

2017 Mixed Mode Survey Design Inputs: (1) E-receipts (2) Web Diary & Questionnaire

2017 Survey Quality Challenges Willingness to disclose • Challenges card transactions – Recruitment 1 60 50 • Peoples willingness to 40 30 disclose card 20 10 transactions 0 Yes No Not sure • Recruitment 2 – Limited share of shops have yet adopted the e-receipt technology (e.g. grocery retail chains) – Loyalty programs are an alternative

Register Assisted Survey Survey Assisted Register Data Audit sampling Sampling Integration Editing Sampling Unit = Person/HH Unit = Transaction Variable = Characteristics Variable = Card

Extended TSE Model Representation Measurement Groves et al. revisited Transformation and Integration

Strategic Perspective Relevance Extended Monetary Cost TSE Model Perceived Response burden Ethical  Legal Technical  Competence GSBPM  Reorganization Thank you Gustav Haraldsen: GHa@ssb.no Sverre Amdam: Sad@ssb.no Li-Chun Zhang: LCZ@ssb.no