Executive Summary

This study assesses how the demographic and study-related characteristics of a person impacts on their earnings three years after completing tertiary study. The analysis drew on information gathered from about 98,000 students who attended tertiary education institutions, had used the Student Loan Scheme and left study in the years 1997 to 1999. The study used student information from the integrated student loan scheme dataset, which is maintained and managed by Statistics New Zealand.

This report assumes that financial returns to education are an important indicator of tertiary education outcomes. The earnings an employee can command in the labour market reflects the person's skill. The qualification level is used as a proxy measure of the person's skill level, which is an outcome of education. In other words, differences in earnings between different people are a proxy measure for differences in the human capital they possess. Implicit in this is an income-based model of human capital¹.

The relationships between a person's earnings three years post study (the outcome variable), demographic characteristics and study-related factors (the explanatory variables) were established using a statistical model known as "Generalised logistic regression analysis". This model isolates the independent relationship of each explanatory variable to student earnings after accounting for the relationship of other relevant variables. The individual effect of each explanatory variable is estimated by keeping all other factors constant.This study reinforces some of the findings of earlier studies and highlights the impact of some variables - such as industry - and the interaction effects of study-linked variables, that have not been studied in the previous works.

Key Findings

• The most important factors which significantly influenced earnings were industry of employment, qualification level, field of study and the tertiary education provider type.

• The level of a person's earnings was generally not as strongly related to demographic variables. Age group did show a relatively moderate relationship to post-study earnings. Earnings increased with the age up to the age of 50 years. When age and qualification level were looked at in combination, there was also an effect on earnings.

• The interaction of variables such as qualification level with industry, qualification level with provider, field of study with industry and age-group with qualification level, had a greater influence on graduate earnings than when these factors were considered individually.

• People with a qualification below degree level earned about 20 percent lower than those with a bachelors degree. People with a post-graduate qualification earned about 60 percent more than those with only a bachelors degree (keeping all other factors constant)

• For any given level of study, students who complete a qualification earn more than those that don't complete. However, when considered independently of level of study, the premium for completing a qualification is only marginal.

• Students who studied in the fields of Health, Engineering, Management and Commerce and Education were likely to earn more than students studying in other fields, when adjusted for other relevant factors.

• People holding post-graduate qualifications in Management and Commerce or Health were likely to have the highest earnings, after taking other factors into account.

• Among bachelors degree holders, studies in Engineering and related technology studies, Health and Education resulted in higher predicted earnings. Individuals holding qualifications below degree level in the fields of Engineering and related technology, Health and Education also were likely to earn higher incomes relative to other fields of study at the same level.

• Among industries of employment, Engineering, Mining, Telecommunication services, Finance and Insurance, Property and Business Services and Health and Community services, provides higher returns to tertiary study.

• Although Engineering, Mining and Telecommunication services provided the highest returns to tertiary qualifications, the number of people in these two industries is very small.

• Individuals attaining qualifications in industry-specific fields such as Education, Health, Management and Commerce, Agriculture, Engineering etc. were very likely to be employed in industries that match their fields of study.

Footnote

1. Trinh L, J Gibson and L Oxley, (2005) Measures of Human Capital: A Review of the Literature.