The circular economy is no end point; it is rather a process of transformation. By following circular strategies, organizations and businesses can render their processes increasingly circular and attain the highest level of economic and societal value.

A piece of work by Circle Economy, Making Sense of the Circular Economy: The 7 key elements,2 conducted a literature review and mapped the various terms and definitions used by over 20 organizations – NGOs, government agencies, academia, consultancies, etc. – working on the circular economy. From this work emerged a framework for the circular economy – the DISRUPT Framework – and from this framework the description of a circular job was formulated.

The DISRUPT Framework presented below describes the full breadth of relevant strategies that give direction to this transformative process.

There are three core circular strategies (in light blue), which directly intervene in material cycles, and four enabling strategies (in dark blue), which serve to mainstream, accelerate and scale up the core circular strategies.

2. Definition of a circular job

Employment in the circular economy reflects the broad nature of the system, and can equally be defined according to the DISRUPT Framework. The circular labor market, much like its linear counterpart, comprises all kinds of jobs in different sectors, ranging from manufacturing and creative industries to waste and resource management. Jobs in the circular economy, shortly “circular jobs,” are all jobs that contribute to one of the strategies of the DISRUPT Framework.

There are three types of circular job:

• Core circular jobs. These jobs ensure that raw material cycles are closed and thus form the core of the circular economy. They include jobs in renewable energy, repair, and waste and resource management sectors. Examples of core circular jobs are displayed in light blue in the framework below.

• Enabling circular jobs. These jobs enable the acceleration and upscaling of core circular activities and thus form the supporting shell of the circular economy. They include jobs in leasing, engineering and digital technology – albeit only those that actually contribute to circularity. Examples of enabling circular jobs are displayed in dark blue in the framework below.

• Indirectly circular jobs. These jobs provide services to the primary circular activities above and thus form the activities that indirectly uphold the circular economy. They include, for example, jobs in education, logistics and the public sector. Examples of indirectly circular jobs are displayed in grey in the framework below.

The architect designs buildings to enable resource recovery after the building’s use phase and so designs for the future.

The data analyst makes sense of large amounts of information to connect supply and demand of secondary materials by means of digital technology.

The appliance technician repairs appliances, machines or vehicles and so extends the lifetime of things already made.

The leasing process manager coordinates service providers across market segments to enable the new business model.

The recycling operative separates waste into materials that can and cannot be recovered, allowing for waste to be used as a resource.

The solar panel installer builds solar panels and so contributes to the use of solar energy as a regenerative resource.

The director of a trade organization manages the membership organization that facilitates collaboration for joint value creation.

Indirectly circular jobs
These jobs provide services to the primary circular activities above and thus form the activities that indirectly uphold the circular economy.

The courier brings packages to and from consumers as part of a reverse logistics scheme that enables new business models.

The teacher transfers knowledge and skills to the (future) workforce so as to equip workers with the skills for all circular economy strategies.

Using this definition, the sectors of economic activity as defined by NAICS (level 6) are classified as core, enabling or indirectly circular, based on how well the sectors are connected to the DISRUPT Framework. An indication is provided in the table below, followed by a full extract of NAICS level 6 sectors mapped to the DISRUPT Framework.

Table 1: An indication of how sectors are mapped to the DISRUPT Framework

Table 2: NAICS Codes mapped to the DISRUPT Framework

3. Employment in New York City

Employment data for New York City, 2017, was obtained from the New York Economic Development Corporation, and details the number of employees at NAICS level 6 granularity. The employment data was mapped to our core and enabling circular sector definitions, as described above.

4. Quantifying circularity

For the core circular sectors, it is assumed that 100 percent of the jobs are circular. For the enabling and indirectly circular sectors, however, not all jobs are circular, and it was necessary to analyze what percentage of the jobs within these sectors can be considered circular. This analysis is done through the use of input-output (IO) tables.

IO tables describe the flow of economic activity between different sectors in the economy, with rows representing the “source” of activity and columns representing the “destination.” The sectors in the rows and columns are classified using the NAICS mapping indicated above.

However, the sectors in IO tables are specified at a higher level than NAICS level 6 as per the classification table. Because this higher order classification is often a combination of core, enabling and indirectly circular sectors, corresponding proportions must be applied to every row and every column. We calculate the proportions using the granular employment figures and apply them to each NAICS IO sector grouping. This effectively distributes the value of one cell into nine cells and more clearly specifies the relationships between core, enabling and indirectly circular sectors. This transformation is displayed in the image below: Table 3 is transformed into Table 4.

Table 3: Subset of original IO table

Table 4: Subset of original IO table with circular proportions applied

In order to determine the share of circular activity within a particular enabling circular sector, we take the monetary value of core and enabling circular sectors supplying that enabling circular sector, and the monetary value of that enabling circular sector supplying core and enabling sectors, all as a proportion of the total input and output activity in that sector. With reference to the below table, mathematically, the following calculation was performed:

{(C+D) + (B+D)} / {K + Y} = % enabling circular activity

Table 5: Illustration of enabling and indirectly circular jobs

In order to determine the percentage of circular activity within a particular indirectly circular sector, the monetary value of indirectly circular sector products used by core circular sectors and by enabling circular sectors was taken into consideration. With reference to the above table, mathematically, the following calculation was performed:

{(E+F) / (X+Y)} = % indirectly circular activity

In order to then accurately represent circular jobs, we must consider the intermediate supply of services through the sectors that is not directly represented in the IO table. We calculate final “circular” demand by summing the core, enabling and indirect proportions of circular activity per row in the adjusted IO table, and then dot multiply this onto the Leontief inverse of the IO table. This is mathematically represented by:

d.*((I-A)-1)

Here, d represents circular final demand, A represents the IO table and I represents the identity matrix. This result is the final circular input that is our indirect adjustment to each sector code.

At this point, we know for each sector the share of core, enabling and indirectly circular jobs, and we are able to apply these proportions onto the original employment data at zip code level.

For this calculation, IO data for USA 2016 was sourced from the US Bureau of Economic Analysis3. In the absence of city level IO data, national IO data is scaled using city level employment data.