Worked example: Closing Cost in New Hampshire

Example inputs

Run this scenario in DocketMath using the Closing Cost calculator.

This worked example shows how DocketMath can estimate a closing-cost figure in New Hampshire (US-NH) using the site’s closing-cost calculator settings alongside jurisdiction-aware rules.

Quick scope note: this post is for illustration and helps you see how the calculator could behave with different inputs. It’s not legal advice, and it doesn’t determine legal rights. The calculator output is only as reliable as the inputs you provide (and any modeling assumptions you choose).

Case context used for the example

• Jurisdiction: New Hampshire (US-NH)
• Assumed legal timing reference point (for illustration): “Claim accrual” date
• Primary default limitations period used: 3 years under RSA 508:4

New Hampshire’s general default civil statute of limitations is 3 years. In this content, there is no claim-type-specific sub-rule found, so we apply the general/default period consistently.

Inputs used (example values)

Use the checklist below to mirror these settings in DocketMath.

• Purchase price: $320,000
• Loan amount: $256,000
• Estimated closing date: 2026-05-15
• Accrual date (timing anchor for SOL illustration): 2023-05-20
• Estimated lender fees: $1,750
• Estimated title/escrow fees: $2,900
• Estimated appraisal fee: $450
• Estimated prepaid items (interest/escrow reserves): $3,200
• Estimated recording/transfer-related fees (modeled): $850
• Other miscellaneous costs: $625
• Risk/assumption buffer factor (to reflect small unknowns): 1.03

Limitations timing input (jurisdiction-aware)

Because a closing-cost workflow often needs a timing anchor (for operational planning around deadlines), this example includes a statute-of-limitations check.

• RSA 508:4 general SOL period: 3 years
• Accrual date: 2023-05-20
• Limitations “endpoint” for illustration: 2026-05-20

That endpoint is very close to the assumed closing date (2026-05-15). This helps illustrate how DocketMath can keep date-driven outputs internally consistent with the 3-year default timing rule.

Example run

Below is a worked run using the inputs above. The goal is to show how DocketMath aggregates costs and then pairs them with the jurisdiction-aware timing rule from RSA 508:4 (the general/default rule).

Run the Closing Cost calculator using the example inputs above. Review the breakdown for intermediate steps (segments, adjustments, or rate changes) so you can see how each input moves the output. Save the result for reference and compare it to your actual scenario.

Step 1: Base cost subtotal

DocketMath sums the category costs:

Step 2: Apply buffer factor

The example includes a buffer of 1.03 to reflect small unknowns (for example, minor line-item fee changes).

• Buffered closing-cost estimate: $9,775 × 1.03 = $10,068.25

Step 3: Time consistency check using RSA 508:4

DocketMath also evaluates a timing window using the jurisdiction-aware default:

• General SOL (civil actions): 3 years under RSA 508:4
• Accrual date: 2023-05-20
• End date (3 years later): 2026-05-20

With the assumed closing date 2026-05-15, the modeled timing relationship is:

• Closing date: 2026-05-15
• SOL endpoint (illustration): 2026-05-20
• Difference: 5 days before the SOL endpoint

This check doesn’t “change” the closing costs (dollars and dates are handled separately), but it can change how you schedule steps in workflows that depend on deadlines.

Example output (what you’d see conceptually)

• Estimated closing-cost (buffered): $10,068.25
• SOL timing anchor (RSA 508:4 default): accrual 2023-05-20 → endpoint 2026-05-20
• Closing date alignment: 2026-05-15 is within the 3-year window by 5 days

If you want to run your own numbers using the same tool, start here: /tools/closing-cost.

Sensitivity check

To make the model actionable, adjust a couple of high-impact inputs and observe how DocketMath’s closing-cost estimate changes. (The cost subtotal changes with fee inputs; the timing illustration changes with dates.)

To test sensitivity, change one high-impact input (like the rate, start date, or cap) and rerun the calculation. Compare the outputs side by side so you can see how small input shifts affect the result.

What matters most in this example?

Based on the category list, the biggest drivers here are typically:

• Prepaid items ($3,200)
• Title/escrow fees ($2,900)
• Lender fees ($1,750)

Below are three quick “what if” scenarios.

Scenario A: Prepaid items change by ±$500

• New prepaid items: $3,200 ± $500
• Subtotal adjustment: ±$500
• Buffered estimate adjustment: ±$500 × 1.03 = ±$515

Takeaway: A $500 change in prepaid items moves the estimate by about $515 because the buffer factor applies to the whole subtotal in this example.

Scenario B: Title/escrow fees vary by ±10%

Current title/escrow fees: $2,900

• ±10% → $2,610 to $3,190
• Subtotal adjustment: -$290 or +$290
• Buffered adjustment: ±$290 × 1.03 = ±$298.70

Takeaway: Title/escrow line items have noticeable impact—especially if you’re comparing estimated schedules from multiple closings.

Scenario C: Timeline shifts—timing output changes, cost stays the same

Adjust only the closing date while keeping all cost categories identical.

• If closing date moves to 2026-06-01:

  • SOL endpoint (illustration): 2026-05-20
  • New difference: 12 days after the endpoint
• The closing-cost estimate remains $10,068.25 here because the cost categories did not change.

Takeaway: In DocketMath-style workflows, costs and deadline context can be independently sensitive—date changes alter the timing illustration, not the dollar subtotal.

Related reading

• Average closing costs in Alabama — Rule summary with authoritative citations
• Average closing costs in Alaska — Rule summary with authoritative citations
• Average closing costs in Arizona — Rule summary with authoritative citations