RDP 2024-06: Examining the Macroeconomic Costs of Occupational Entry Regulations 3 Measuring the stringency of OER

OER encompass a range of factors such as qualification pathways, licensing requirements and recognition of interjurisdictional requirements. Creating a single metric to quantify the stringency of OER is helpful in being able to readily compare OER across occupations and jurisdictions.

We adopt the approach laid out by the OECD in von Rueden and Bambalaite (2020) to create a single index to measure the stringency of OER. This provides a simple, single indicator of the stringency of OER that we can compare to other countries. The following sections describe the construction of the measures in more detail, as well as outlining the range of occupations to which we apply the index.

The OER indicator is constructed in two steps (see Box 1 for more details). First, we assess the burden imposed by the restriction on an occupation. The index captures three areas of the burden: the administrative burdens that need to be met, the qualification requirements, and any mobility restrictions across states or countries associated with the OER (e.g. Queensland licences are not automatically recognised in New South Wales, or vice versa). Each of these indicators is scored, then combined with an equal weight to construct an aggregate indicator for the occupation. This takes on a value between 0 (no regulation) and 6 (fully regulated).

In the second step, we scale the burden by a factor to reflect the type of OER used, as these differ in how binding they are. For example, licences are required to undertake certain protected activities, while certification is only needed to use a protected title. We scale down the OER indicator for the less binding types of OER.

3.1 OER indicator estimated for a range of occupations in Australia's largest states

We calculate the OECD's OER measure for a range of occupation groups in New South Wales, Queensland, and Victoria. We start by focusing on the set of 15 OECD occupations considered in von Rueden and Bambalaite (2020) and Bambalaite et al. (2020) for New South Wales, Queensland, and Victoria (Table 3). This enables direct comparison of OER across Australia's largest states and with other OECD countries.

We extend the analysis, measuring regulatory stringency for the top 100 most common occupations in New South Wales (see appendix B for the full list). This provides a broader view of the coverage and stringency of OER throughout the New South Wales economy, as well as the key components that feed into OER.

Finally, we conducted industry-specific analysis by measuring the regulatory stringency of 14 select occupations in the building and construction industry in New South Wales, Queensland, and Victoria. We do a deep dive into this sector given it consistently reports acute skill shortages, which has important implications for our ability to meet growing demand for housing and infrastructure (Housing Industry Association 2023). Moreover, it is a highly cyclical industry, meaning that OER may be particularly binding, preventing new workers from entering and exiting the construction sector as demand ebbs and flows.

A summary of the occupation groupings and states covered in the analysis is contained in Table 4. We use data available as at 2023.

The OER indicator rates the stringency of OER on a scale of 1 to 6, which enables us to assess how regulatory stringency compares across states and internationally. Table 5 provides an example of how the OER indicator was used to measure the stringency of occupational requirements for registered nurses across Australia under the nationally harmonised registration scheme. The scoring criteria and weighting for each regulated area and sub-indicator is outlined in appendix A. The scores reveal that registered nurses have an overall OER score of 2.33, with qualification requirements being the main contributed to this score.

3.2 OER indicator has some innate limitations

The OER indicator also has several limitations:

1. Simplification: The regulatory areas are weighed equally, in line with the OECD method, to enable comparison. In reality, one might be a bigger constraint on another, and their relative importance might vary between occupations and jurisdictions.
2. Coverage: OER measure does not consider the number of specific tasks that are restricted to each occupation, which means the actual stringency of regulations may not be accurate where reserved activities differ.
3. Data quality and availability: Construction of the OER indicator is time-consuming and data availability issues may limit the extent to which the indicator can be estimated over time and across jurisdictions. The OER indicator may be mismeasured if data is limited or outdated.

For example, the typical four-year apprenticeship to become an electrician in New South Wales may present a bigger barrier for potential entrants than the mobility restrictions, such as the process for recognising qualifications gained abroad. The scope of work allowed for electricians can also vary across jurisdictions. Some areas may combine electrical and air conditioning and refrigeration work under a single licence, while others may require separate licences for each activity. Further, it can be challenging to find information on how mobility restrictions on electricians have changed over time.

In addition, the OER indicator cannot be used in isolation to determine whether certain requirements should be kept or removed. This assessment requires an evaluation of the costs and benefits, which is beyond the scope of a single indicator.

Footnote

Where registrations or licences are not automatically recognised between jurisdictions, these are considered to be territorial restrictions. [2]