Longitudinal Data Recent Experience and Future Direction August 2012

Content Survey of Family, Income and Employment Linked Employer–Employee Data (LEED) Future direction: Integrated Data Infrastructure Linked Census Data Administrative and Survey Data linking 20 August 20122

Survey of Family Income and Employment Longitudinal Study that ran for 8 waves from Wave 1 Sample: 11,500 households 29,700 individuals(22,200 adults and 7,500 children ) 20 August 20123

Survey of Family Income and Employment Topics covered in all waves: Demographics Education Family Labour market Income 20 August 20124

Survey of Family Income and Employment Additional topics: In waves 2,4,6 and 8: Assets and Liabilities In waves 3,5 and 7:Health 20 August 20125

Survey of Family Income and Employment 20 August 20126

Strengths Investigating causal processes Identifying important transitions Assessing the effects of policies Wide coverage of topics Flexibility of content 20 August 20127

Limitations Intermediate length Incomplete coverage of subpopulations Limited scope for analysis of subpopulations Recall error 20 August 20128

Successes High retention rate Large sample Rich dataset Broad group of users 20 August 20129

Challenges Respondent Burden Less representative over time Attrition across subgroups High Cost to Statistics NZ Complex data Confidentiality and Data Access 20 August

Longitudinal Data after SoFIE 11

LEED Combines: Employer Monthly Schedule (EMS) payroll data from Inland Revenue Statistics NZ Business Frame Ministry of Social Development's Benefit Dynamics Dataset (BDD) Annual tax returns (self-employment data) 20 August

Strengths High coverage of specific groups Longitudinal Indefinite observation period Enables the study of rare phenomena Enables the study of small subpopulations More detailed than survey data 20 August

Limitations Not representative of the entire population Administrative data is collected for administrative purposes No unique Identifier for exact matching 20 August

Integrated Data Infrastructure (IDI) Prototype Includes data from: LEED Ministry of Education Ministry of Social Development Ministry of Business, Innovation and Employment Household Labour Force Survey (HLFS) 20 August

Additional Benefits Greater number of variables Greater coverage Greater number of topics 20 August

Linked Census Data Feasibility studies into linking together data from past censuses Enables the study of long term phenomena and intergenerational mobility Can be used to study social and geographic mobility Potential for wide use 20 August

Administrative and Survey Data Linking Administrative data adds a longitudinal dimension to survey data Survey data adds a broad range of variables to administrative data Reduced respondent burden Better use of existing data 20 August

Examples SoFIE – IRD data SoFIE – Health data Census – Cancer Register Census – Mortality Records 20 August

Future Direction Maximising the use of Administrative data Maximising the use of SoFIE data Maximising the benefits from linking administrative and survey data 20 August