Session 2d, Social Data

This session will be held in the Erskine Building, Room 031

15:40 — 16:00

A new New Zealand static microsimulation model – challenges with data

Rissa Ota
Ministry of Social Development

Helen Stott
Ministry of Social Development

The New Zealand Ministry of Social Development has been developing a new static microsimulation model of the national tax and transfer system. The survey data used for the simulation is Survey of Family, Income and Employment (SoFIE), which has a rich source of information about income, employment, benefits and family structure changes along the interview year. The 2002/3 survey data is the first wave of a longitudinal survey which will be carried out for eight years.

As the primary use of the database will be modelling changes to the income support system, the primary focus is on benefit recipients and low income families. This paper gives an overview of the development of the database, with emphasis on the data synthesis, imputation and calibration of the beneficiary population. Calibration using generalised regression estimators has enabled a wide range of benchmarks to be used. However, there have been a range of challenges encountered along the way, including issues around updating the data as the benefit system has been undergoing major changes, and the representativeness of the data as the number of unemployed has dropped significantly since the first wave was collected.

16:00 — 16:20

Text Mining of Te Puni Kokiri Project Data

Paul J. Bracewell
Offlode Ltd.

This presentation outlines the findings from a text mining proof of concept performed for Te Puni Kokiri (Ministry of Maori Development) by Offlode Ltd using SAS Enterprise Miner.

Almost 2,500 bilingual documents relating to Te Puni K okiri's Whanau Development Action and Research projects were provided for analysis. These documents relate to approximately 100 projects conducted under the Ministry's direction over a two year period. The aim was to identify and supply evidence of the actual and implied outcomes of the projects using a cost-effective methodology.

Analyses revealed that among the success indicators of the Whanau Development Action and Research Projects is the implementation of communal infrastructure targeting local communities. Plans for sustainability rely on the community with specialist assistance from external agencies.

Additionally, based on interpretation and consultation with domain experts it was possible to quantify the quality of the final reports. This is particularly useful for determining which parties may need assistance communicating their results effectively. Additionally, it is possible to predict the quality of a final report based on preliminary documentation, such as proposals and e-mails. Preliminary documents that are not overly reworked and have an action theme tend to result in better quality documents.

16:20 — 16:40

Small Area Estimation for ILO-Unemployment

Stephen Haslett
Massey University

Alasdair Noble
Massey University

Felibel Zabala
Statistics New Zealand

This research fits hierarchical Bayes models under a superpopulation structure to provide sound Territorial Local Authority level estimates of International Labour Organisation (ILO) unemployment. The models are fitted via R and WinBUGS using Markov Chain Monte Carlo techniques and are based on strong priors developed from extensive historical information. Unemployed count models combine survey information on ILO unemployment from the quarterly Household Labour Force Survey (HLFS) with monthly Ministry of Social Development (MSD) information on registered unemployed for the period first quarter 2001 to first quarter 2006. The accuracy of estimates is good for levels at which sample sizes in HLFS are otherwise too small, and the method also allows monitoring of changes of model parameters over time. Relative risk models, which incorporate census population projections, are also fitted. The outcome is improved and potentially publishable ILO based estimates of unemployment at a finer geographic level than is currently possible from the HLFS alone. The research was funded under the Statistics New Zealand OSRDAC Official Statistics Research programme.

16:40 — 17:00

Measuring Labour Mobility in New Zealand

Walter Davis
Statistics New Zealand

Statistics New Zealand’s Linked Employer-Employee Database (LEED) links employer payroll data with Statistics New Zealand’s Business Frame to create a view of the labour market which includes nearly every business and employee in the economy. This database provides the opportunity to investigate the dynamics of the labour market. This presentation looks at the possibilities and challenges of using LEED to measure geographic labour mobility in 58 labour market areas (LMAs) as defined by the Department of Labour (Newell & Papps 2001). Preliminary analysis will investigate inter-regional labour flows and mobility by various firm and worker characteristics.

Presentation Program