Training Opportunities: Exploring what happens two months later

Introduction

This paper builds on previous statistical analysis published by the Ministry of Education on Training Opportunities, a programme designed to help people get into the labour force through providing training and foundation skills. ¹

Training Opportunities is funded by the government and is targeted at MSD beneficiaries at risk of long-term unemployment. It aims to help them to move into sustainable employment and/or higher levels of tertiary education.

This paper describes the results of statistical modelling that sets out to predict the factors associated with outcomes for trainees two months after they leave placements, using the Training Opportunities administrative dataset.² This data is collected by the TEC to assess the performance of training delivered by training providers. Training providers are generally required by TEC to ensure that at a certain proportion of placements result in a ‘positive’ outcome, which includes either employment, further training or a return to Training Opportunities within two months of leaving a placement. The complement is a ‘negative’ outcome, meaning further labour market inactivity (i.e. unemployment or having ‘out of the labour force’ status) within two months of leaving a placement.

The logic of this contract management approach is that funds provided by TEC are used to purchase quality training, which results in a ‘positive’ outcome for the learner. This paper looks at the factors associated with two month labour market outcomes, and provides a non-exclusive hierarchy of the factors associated with each type outcomes.

In previous analyses (Mahoney, 2009a) we have shown the observed labour market outcomes of Training Opportunities. However, these observations are not likely to show the full picture of what happens for each category of trainee because of the cumulative effects of different variables. This is where statistical modelling becomes useful. It enables us to determine the strength of the relationship between individual variables and the labour market outcome while controlling for all the other variables.

Footnotes