After a final application has been submitted and the final ROI values have been calculated. The Impact Measurement team will conduct a living wage analysis.

Step 1

1. Go to the Living Wage Analysis tab in the grantee’s final ROI spreadsheet (which originates from the North Star ROI Model TEMPLATE)
2. Type in the information that already exists from the ROI model
   1. Number of people impacted
   2. Post-program avg income
   3. Counterfactual post-program income

Step 2

1. Determine the living wage threshold.

   1. For U.S. grants, use the MIT Living Wage Calculator
      1. Look up the geographic area that best fits the grantee’s focus population
         1. If a national program, use the national living wage threshold (2023 = $41,000)
         2. If based in a metropolitan area look at the relevant area (e.g. Seattle, Tacoma, Bellevue here)
         3. Take the hourly wage (e.g. $24.03) and multiply by 2,080 hours (40 hours a week for 52 weeks) to get annual income ($24.03 * 2,080 = $49,982)
   2. We use the threshold set at two working adults and one child.
      1. This line is set to be a midpoint between one adult and zero children and two adults with two children.
      2. We don’t use the single-parent thresholds, as just 15% of households have children under 18 without a partner present. Census source in Key Stats section.
      3. We don’t use the two-child assumption, as the expected births per woman is 1.73.
      4. We are assuming two working adults as 65% of married-couple families have two working adults.
   3. Adjusting the household assumptions:
      1. If a grantee is explicitly working with single parents, a higher living wage threshold should be used. Absent of specific household size details, the general two working adults and one child line should be used.
      2. This line could be adjusted as we learn more about average demographics in the United States.
         1. Percent of single parents (table here)
            1. 15% of households with children under 18 have no partner present.
            2. 76% of households with children under 18 are married with the spouse present.
            3. 85% of households with children under 18 are either married with the spouse present or cohabitating with a partner present.
         2. The average number of children
            1. The expected births per woman is 1.73 (CDC source, 2018)
         3. Average working couples statistics (BLS source, 2022)
            1. Among married-couple families with children, 97.4 percent had at least one employed parent in 2022, and in 65.0 percent of these families, both parents were employed.

2. For non-U.S. grants, use data from the Global Living Wage Coalition.

   1. There are 3 types of living wage thresholds
      1. Urban (Example)
      2. Semi-Urban (Example)
      3. Rural (Example)
   2. Determine if the grantee’s population is focused in urban, semi-urban, or rural areas and lookup the latest living wage threshold for the country and area on the global living wage website.
      1. As of Feb 2024 the latest datapoints for Kenya and Colombia are below:
         1. Colombia
            1. Bogota, Colombia
            2. Rural Areas, Colombia
         2. Kenya
            1. Lake Naivasha, Kenya
            2. Rural Kericho, Kenya
   3. The living wage thresholds are at the household level so divide the monthly living wage by the number of workers per household.
   4. Then translate that threshold per person into USD based on the most recent exchange rate.
   5. Multiply that monthly wage by 12 to get the annual living wage.

   Step 3

   1. Use a normal distribution online calculator to determine the percentage of the program participants and counterfactual participants that would earn above the living wage threshold.
   2. Take a screenshot of the two normal distributions, the counterfactual, and the post-program outcomes and paste the two images in the living wage analysis tab

   

   Step 4

   1. Use R Studio to create a more detailed comparison of the before and after effect of the grantee’s programs.
   2. Use the R script code here
   3. Paste the combine counterfactual and program-effect distributions in the living wage analysis tab

   

Step 5

1. If the wage distributions are not assumed to be normally distributed, use the distribution of wages according to the BLS gov website, such as for Computer Network Support Specialists.

1. Input the distribution values into the R script code to create more customized and tailored predictions on the percentage of participants that would earn above living wages

Appendix

Colombia Living Wage Data