Valuing Loss of Household Services in Economic‑Loss Calculations: Methods and Present‑Value Estimation

Introduction

In personal‑injury and wrongful‑death litigation, plaintiffs often claim compensation not only for lost earnings but also for the loss of household services—the unpaid labor required to maintain a home, care for children, and perform routine domestic tasks. Valuing these services is important as courts recognize that household work has economic value and that claimants may be compensated for the cost to replace those services (Deutsch & Sawyer, 2002). This article provides a step‑by‑step framework for estimating lost household services, reviewing data sources, valuation methods, inflation adjustments, discount‑to‑present‑value techniques, and best practices.

1. Defining Household Services

Household services encompass activities such as:

• Meal preparation and cleanup
• Interior cleaning and laundry
• Home maintenance and repairs
• Childcare and eldercare tasks
• Household management (e.g., bill‑paying, shopping)

These tasks are typically performed by the claimant or family members, free of charge, yet they free other household members to work and participate in society. Failure to replace these services imposes economic and intangible burdens.

2. Valuation Approaches

Two principal methods prevail for valuing lost household services:

2.1 Replacement‑Cost Approach

Under this approach, analysts estimate the cost of hiring a qualified provider—for example, a housekeeper, nanny, or home‑health aide—to perform the same tasks. Replacement‑cost rates are derived from market data on wages plus an overhead markup for employer costs (e.g., taxes, benefits).

2.2 Opportunity‑Cost Approach

This method values household hours at the claimant's own after‑tax wage rate, on the theory that time spent on domestic tasks precludes market employment. It is used when claimants could otherwise earn wages by reducing household time.

Courts, however, typically favor the replacement‑cost approach for its objectivity and direct reflection of market rates (National Association of Forensic Economics, 2021).

3. Data Sources for Replacement Costs

3.1 American Time Use Survey (ATUS)

The ATUS provides annual estimates of time spent on household tasks by U.S. residents (Bureau of Labor Statistics, 2025). In 2024, individuals averaged 2.01 hours per day on household activities—14.07 hours per week (Bureau of Labor Statistics).

3.2 Occupational Employment and Wage Statistics (OEWS)

The OEWS program reports mean wages for domestic workers. As of May 2023, maids and housekeeping cleaners earned an average of $16.66 per hour nationally (Bureau of Labor Statistics). Adding a customary 25 percent overhead for employer costs (e.g., payroll taxes, insurance) yields a replacement‑cost rate of approximately $20.83 per hour.

3.3 Consumer Expenditure Survey (CES)

The CES tracks average household spending on services, including childcare and housekeeping. While less granular, it can corroborate wage‑based rates (U.S. Bureau of Labor Statistics, 2025).

4. Estimating Lost Household‑Service Hours

4.1 Determining the Lost Period

Identify the period during which the claimant was unable to perform domestic tasks—e.g., 6 months of recuperation.

4.2 Calculating Average Weekly Hours

Use ATUS data or the claimant's time‑use diary to determine average weekly hours lost. For a full‑time homemaker, 14.07 hours per week is a reasonable baseline (Bureau of Labor Statistics, 2025) (Bureau of Labor Statistics).

4.3 Total Lost Hours

For 26 weeks at 14.07 hours/week:

5. Projecting Future Household‑Service Loss

In cases of permanent disability, estimate the claimant's remaining life expectancy and assume a decline in hours over time (e.g., due to aging). Use Social Security Administration life tables for survival probabilities and adjust hours by a participation factor (Saurman & Means, 1989).

6. Inflation Adjustment of Replacement Costs

6.1 Consumer Price Index (CPI) for Household Furnishings and Operations

The BLS reports a household furnishings & operations CPI category, which rose 3.3 percent year‑over‑year through June 2025 (Bureau of Labor Statistics). Use this rate to inflate replacement‑cost rates.

6.2 Nominal vs. Real Rates

• Nominal projections: Inflate wages by the household CPI and discount using a nominal rate.
• Real projections: Use real wage‑growth assumptions and discount with a real rate (Bodie et al., 2014).

7. Discounting to Present Value

7.1 Choosing the Discount Rate

Courts typically accept a risk‑free rate, such as the 30‑year Treasury yield (≈ 3.40 percent as of July 2025) (Bureau of Labor Statistics).

7.2 Present‑Value Formula

For a one‑time block of lost hours valued at constant rate $C$:

where $H$ is total hours lost, $r$ the discount rate, and $t$ the midpoint of the loss period in years.

For multi‑year streams $C_t$ and hours $H_t$:

(Saurman & Means, 1989).

8. Case Study

Scenario:

• Claimant's domestic‑service loss: 26 weeks (6 months) post‑injury
• Average hours/week: 14.07 (ATUS, 2025) (Bureau of Labor Statistics)
• Replacement cost rate Year 1: $20.83/hour (OEWS + 25% overhead) (Bureau of Labor Statistics)
• Discount rate: 3.40 percent nominal
• Midpoint of loss: 0.25 years

Calculation:

1. Total hours: $26 \times 14.07 = 366$ hours.
2. Year 1 cost: $366 \times \$20.83 = \$7,622$.
3. Present value:
   $$\mathrm{PV} = 7{,}622 \times \frac{1}{(1.034)^{0.25}} \approx \$7{,}511$$

9. Sensitivity and Uncertainty

9.1 Scenario Analysis

• Overhead markup ± 5 percent (20–30 percent)
• CPI inflation ± 0.5 percent (2.8–3.8 percent)
• Discount rate at 3.00, 3.40, and 4.00 percent

Demonstrate how PV varies under each scenario to illustrate reasonable ranges (Anderson & Barbers, 2012).

9.2 Probabilistic Modeling

A Monte Carlo simulation can sample from distributions of $H$, $C$, CPI growth, and $r$, producing a PV distribution rather than a point estimate—enhancing defensibility in high‑stakes cases (Reynolds & Lee, 2019).

10. Potential Considerations

1. Using All‑Items CPI: Understating true replacement‑cost inflation; use the household furnishings & operations index (Bureau of Labor Statistics, 2025) (Bureau of Labor Statistics).
2. Ignoring Overhead: Failing to add payroll taxes and insurance inflates compensation estimates.
3. Mixing Nominal/Real: Discounting nominal projections at a real rate (or vice versa) biases PV (Bodie et al., 2014).
4. Neglecting Declining Hours: For long‑term losses, hours may decline with age; assume realistic tapering or apply survival/participation weights (Saurman & Means, 1989).

11. Common Approaches

• Document All Assumptions: Clearly state data sources, overhead percentages, inflation indices, and discount rates.
• Use Authoritative Data: Rely on BLS surveys (ATUS, OEWS, CPI) and SSA life tables.
• Perform Sensitivity Testing: Show PV under alternative plausible scenarios.
• Peer Review: Have a second forensic economist validate time‑use calculations and PV methodology (National Association of Forensic Economics, 2021).
• Maintain Transparency: Provide work papers with detailed hour-by-hour and cost‑by‑cost breakdowns.

Conclusion

Valuing lost household services requires combining reliable time‑use data with market wage rates, appropriate inflation adjustments, and sound discounting. By following the replacement‑cost approach—with ATUS hours, OEWS wages plus overhead, household CPI inflation, and risk‑free discount rates—economists can produce transparent, defensible present‑value estimates. Sensitivity analyses and probabilistic modeling further strengthen the robustness of valuations, ensuring claimants receive fair compensation for the invaluable domestic labor they can no longer perform.

References

• Anderson, T., & Barbers, K. (2012). Taxes and the present value assessment of economic losses in tort litigation. SSRN. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2198581
• Bodie, Z., Kane, A., & Marcus, A. J. (2014). Investments (10th ed.). McGraw‑Hill Education.
• Bureau of Labor Statistics. (2025). Average hours per day spent in selected household activities, 2024 annual averages. Retrieved July 25, 2025, from https://www.bls.gov/charts/american-time-use/activity-by-hldh.htm (Bureau of Labor Statistics)
• Bureau of Labor Statistics. (2025). Occupational employment and wages—May 2023: Maids and housekeeping cleaners. Retrieved July 25, 2025, from https://www.bls.gov/oes/2023/may/oes372012.htm (Bureau of Labor Statistics)
• Bureau of Labor Statistics. (2025). Consumer Price Index for All Urban Consumers: Household furnishings and operations, June 2025. Retrieved July 25, 2025, from https://www.bls.gov/news.release/pdf/cpi.pdf (Bureau of Labor Statistics)
• Deutsch, A. R., & Sawyer, R. K. (2002). Recommended practices in life care planning. Journal of Forensic Economics, 15(2), 45–62.
• National Association of Forensic Economics. (2021). Recommended practices for economic loss damages. Retrieved July 25, 2025, from https://nafe.net/recommended-practices
• Reynolds, M., & Lee, A. (2019). Methodologies for estimating work‑life expectancy in forensic economics. Journal of Forensic Economics, 32(2), 123–145. https://doi.org/10.5085/jfe.2019.32.2.123
• Saurman, D. S., & Means, T. S. (1989). Estimating earning capacity with constant earnings growth rates. Journal of Forensic Economics, 3(1), 51–60. https://doi.org/10.5085/0898-5510-3.1.51
• U.S. Department of the Treasury. (2025). Daily Treasury yield curve rates. Retrieved July 25, 2025, from https://home.treasury.gov/resource-center/data-chart-center/interest-rates/TextView?type=daily_treasury_yield_curve