Why Wrongful Death Damages results differ in Brazil

The top 5 reasons results differ

When DocketMath runs the wrongful-death-damages calculator for Brazil (BR), different outputs usually trace back to a few jurisdiction-aware inputs and rule assumptions. Because wrongful-death damages are typically built from economic loss concepts plus how facts are modeled and documented, seemingly small changes can create noticeable swings.

Here are the top 5 reasons results differ in Brazil:

1. Different assumptions about income and “loss of support”

   • DocketMath needs a starting point for the deceased’s earnings (for example: formal salary vs. an estimated income measure, depending on what you enter).
   • If you input documented wage income in one run and estimated/averaged income in another, the calculated loss of support can change substantially—then the rest of the total updates from that foundation.

2. **Time horizon differences (life expectancy / remaining working years)

   • The projected duration of loss is a key multiplier.
   • Even a modest change—e.g., 10 years remaining vs. 12 years remaining—can increase the present-value damage figure because more future periods are being brought into the calculation.

3. Age and dependency profile of claimants

   • Results can depend on who depended on the deceased and for how long (for instance: spouse vs. children, and their ages).
   • If claimant counts, claimant ages, or dependency duration assumptions differ, DocketMath will allocate the economic loss differently and totals can move.

4. Discounting and present-value methodology

   • DocketMath converts future economic loss into a present-value number using the tool’s Brazil-specific modeling approach.
   • If your inputs imply a different forecast length (time horizon) or change the mechanics behind the present-value conversion, the final number can shift even if annual loss appears similar.

5. Document quality and how uncertainty is handled

   • In practice, outcomes vary based on what’s supported by evidence: payslips, contracts, tax filings, employment terms, and dependency proof.
   • DocketMath can’t “verify” missing documents, so analysts often substitute assumptions. Those substitutions are a common reason two runs produce different totals.

Pitfall to avoid: If two DocketMath runs differ in only one field (for example, claimant age or income basis), the final number can still diverge meaningfully. Always compare the inputs first, not just the output totals.

How to isolate the variable

To find the driver behind a difference, use a controlled approach: change one variable at a time, while keeping everything else identical. The goal is to identify which input category is causing the swing.

• Freeze the jurisdiction and tool settings so both runs use the same rule set.
• Compare one input at a time (dates, rates, amounts) and re-run after each change.
• Review the breakdown to see which segment or assumption drives the difference.

A repeatable isolation workflow

• Step 1: Freeze a “baseline” run

  • Use your best-supported inputs: income amount and basis, claimant list, claimant ages, and any horizon-related inputs available in the interface.

• Step 2: Run a “delta” test

  • Change only one input category per run, such as:

    • Income baseline / income basis (documented vs. estimated measure)
    • Claimant ages or dependency status/allocation
    • Remaining time horizon parameters
    • Any discounting-related or present-value controls (only if the interface allows you to adjust them)

• Step 3: Compute the impact

  • Track both:

    • Absolute change in total damages
    • Percent change vs. baseline
      This helps you distinguish “small modeling drift” from true sensitivity.

Quick checklist (what to change first)

Diagnostic reading of results (symptoms → likely driver)

If you’re working interactively, run the same case facts twice and only toggle the input you suspect. This is the fastest way to separate modeling assumptions from factual differences.

For quick access to the calculator, use: /tools/wrongful-death-damages.

Next steps

1. Create an input “fact sheet” for the run

   • Write down the exact values you used (income amount/basis, claimant list and ages, and horizon parameters). This reduces accidental drift between runs.

2. Confirm both runs use the same claimant set

   • Many “mystery differences” come from including/excluding a dependent or updating an age.

3. Run three scenario bands to measure sensitivity

   • Conservative: lower documented income + shorter effective horizon
   • Baseline: best-supported income + standard horizon
   • Upside: higher documented income (or higher income basis) + longer horizon
     Comparing the spread shows how sensitive the model is to your assumptions.

4. Lock your comparison rules before re-running

   • Decide what remains fixed (e.g., claimant list) and what you intentionally vary (e.g., income basis). That consistency is what makes DocketMath comparisons diagnostic instead of confusing.

Related reading

• Wrongful Death Damages Estimator Guide for Alabama
• Wrongful Death Damages Estimator Guide for Arizona
• Wrongful Death Damages Estimator Guide for Colorado