Livelihoods is a component of the Livelihoods and Economies goal. This subgoal describes the quantity and quality of marine related employment available to people. Livelihoods includes two equally important sub-components, the number of jobs, which is a proxy for livelihood quantity, and the per capita average annual wages, which is a proxy for job quality.
A score of 100 indicates that a coastal region has maximized the quantity and quality of jobs in the marine sector.
Before embarking on the Livelihoods subgoal, consider how you want to structure the larger goal. The global assessment is composed of two equally important sub-goals, livelihoods and economies, which are assessed across as many marine-related sectors as possible. Livelihoods includes two equally important sub-components, the number of jobs, which is a proxy for livelihood quantity, and the per capita average annual wages, which is a proxy for job quality. Economies is composed of a single component, revenue. We track the two halves of this goal separately because the number and quality of jobs and the amount of revenue produced are both of considerable interest to stakeholders and governments, and could show very different patterns in some cases (e.g., high revenue sectors do not necessarily provide large employment opportunities). The status of the livelihoods and economies goal is the average of the livelihoods and economies subgoals.
The marine-related industries that provide jobs and revenue often provide multiple benefits which are accounted for in different OHI goals. For example, the quantity of food from wild-caught fisheries and mariculture is included in the Food Provision goal; participation in tourism activities is accounted for in the Tourism and Recreation goal. The quantity and quality of jobs is captured in the Livelihoods subgoal.
STEP 1: Determine the sectors
The first step of this goal is to identify the marine-related employment sectors in your area. Some sectors are directly connected to the marine environment, such as shipping, fishing, longshore workers, but some are connected indirectly, such as suppliers and supporting industries. For example, the sectors included in global assessments included tourism, commercial fishing, marine mammal watching, aquarium fishing, water and tidal energy jobs, mariculture, transportation and shipping, ports and harbors, ship and boatbuilding.
You will need to determine whether to include industries that are not considered sustainable, such as oil and gas extraction. It is also important to determine whether to include industries that do not rely on healthy oceans to thrive, such as wind/wave energy, shipping, and boat-building. However, these industries may employ many people and generate large revenue for a region. Ultimately, whether and how to include these industries is a decision that should be made on a case-by-case basis by the individual OHI+ group. For the global assessment we excluded sectors that are not considered sustainable, but decided to include sectors that do not depend on a healthy ocean.
STEP 2: Find the data
After you have identified which jobs are in your area, you will want to find some measure of their direct and indirect benefits. Direct benefits of jobs include the number of jobs in each area, and the wages or income for such jobs. You could find such information from you local national statistical office, or economics bureaus, for example. Indirect benefits of these jobs to the local communities are calculated through the use of economic multipliers, that can be used to more broadly estimate the revenue generated by marine sector jobs. It’s encouraged to use economic multipliers from the literature.
For example, the number of fishermen can be multiplied by a multiplier to estimate larger economic effects, ranging from gear manufacturing companies to restaurants and movie theaters where the fishermen spend their income.
In addition to the quantity of marine jobs in an area, this sub-goal should incorporate the quality of the jobs. The global assessment uses wages as a metric of quality, but other information is also relevant such as the sustainability of different sectors as well as working conditions and job satisfaction.
STEP 3: Identify the reference point
The reference point for this sub-goal is often a temporal reference point that compares current livelihoods to past livelihoods in the same region. In this case, the goal is to maintain the quantity and quality of marine-related jobs year after year. Another approach would be to use a locally established target for growth.
STEP 4: Other helpful information
Studying the behavior of economic trends in your area can provide useful insights. For example, time-series data can be used to identify general economic cycles specific to your area that can be used to scale reference points or identify the more persistent patterns amid the noise. This may be useful if there is a lot of uncertainty or high variation in the data. For example, a sporadic event such as a large storm may negatively impact a year’s revenue, but this may not accurately reflect longer term patterns.
It may be advisable to adjust the reference point to track the overall job market, such that the Livelihoods goal will not be penalized if the number of jobs lost is consistent with the number of jobs lost throughout the country.
| Assessment | Developing the Model | Setting the Reference Point | Other Considerations |
|---|---|---|---|
| Global 2012 | This was measured as the number of direct and indirect jobs across sectors within a region plus the average purchasing power parity (PPP)-adjusted wages within each sector. Jobs were summed across sectors and wages were averages across sectors within each region. | The reference point for jobs was a temporal comparison using a moving-window value. The reference point for wages was the highest average annual wage observed across all reporting units. A score of 100 indicated that the number of marine jobs had not reduced relative to the number five years previously, and that the wages in the area were the highest anywhere. | The goal model assumed there was no-net-loss of jobs in order to account for broader economic trends. The economic multipliers were used for jobs and revenue but not wages. |
| Global 2013 - 2015 | The model was similar to Global 2012, with some simplifications. | The reference point was the same as Global 2012. | The approach was the same as Global 2012 except for a few simplifications in multipliers, wage data, and jobs data. This was done because of data availability and in order to correct for national macroeconomic events across all sectors. |
| Brazil 2014 | The method was the same as Global 2012. | The reference point was the same as Global 2012. | The approach was the same as Global 2012. |
| U.S. West Coast 2014 | This goal follows the same model as in Global 2012, using local data for the sectors of living resources, tourism and recreation, shipping and transport, marine related construction, and ship and boat building or repair. Data and sector-specific multipliers came from the National Ocean Economics Program (NOEP). | The reference point was the same as in Global 2012. | This study followed the Global 2012 approach but used local data. It recognized that sectors and economic activity within a region can be influenced by activities outside the region. |
| Israel 2014 | See Global 2012 assessment. | No-net-loss reference point. | N/A |
| Ecuador-Gulf of Guayaquil 2015 | The approach is the same as the Global assessment. | A temporal reference points was used for both the number of jobs and salaries. 2009 values were used as the reference point for jobs, and values of 2010 for salaries. | Data for jobs, wages, and unemployment were gap-filled. |
| China 2015 | Status model is the based on the number of direct jobs across marine sectors and the average disposable income among rural and urban inhabitants within a region. | Both jobs and wages have a spatial reference point of the maximum value among all provinces across all years. | Eleven marine sectors are assessed. The number of jobs per sector is not readily available and is extenuated from the nation-wide number of employments for each sector and the total number of marine-related jobs per province. There is not enough information on indirect jobs and is thus left out of the calculation. Due to unavailability of wage information per sector, wage is substituted by disposable income. |