This source did not publish a separate summary. Review SKILL.md before using the skill.
SKILL.md
Only stop to ask the user when: the project description, counterfactual, or sponsor is missing.
Never stop to ask about: sector detection, lens choice, formatting, table layout, output filename, or which methods to use. Pick sensible defaults and keep moving.
Before starting, run this silently. If it outputs UPDATE_AVAILABLE, tell the user:
"A new version of econstack is available. Run cd ~/.claude/skills/econstack && git pull to update."
Then continue with the skill normally.
Types: framework (preferred appraisal framework), parameter (custom overrides), data-source (preferred data), output (past report references), operational (tool/env quirks), preference (formatting/style). Confidence: 9-10 observed/stated, 6-8 strong inference, 4-5 weak. User-stated never decays; observed/inferred lose 1 point per 30 days. All data stored locally. Nothing transmitted.
After the update check, verify the parameter database is available and check staleness:
PARAMS_DIR="$HOME/econstack-data/parameters"
if [ -d "$PARAMS_DIR" ]; then
PARAM_COUNT=$(find "$PARAMS_DIR" -name "*.json" 2>/dev/null | wc -l | tr -d ' ')
echo "PARAMS: $PARAM_COUNT files loaded from $PARAMS_DIR"
# Check for stale files (last_verified > 2 years ago)
STALE=$(find "$PARAMS_DIR" -name "*.json" -mtime +730 2>/dev/null | wc -l | tr -d ' ')
if [ "$STALE" -gt 0 ]; then
echo "PARAMS_WARNING: $STALE file(s) not updated in 2+ years. Run: cd ~/econstack-data && git pull"
fi
else
echo "PARAMS: not found. Using built-in defaults. For full parameter support: git clone https://github.com/charlescoverdale/econstack-data.git ~/econstack-data"
fi
If PARAMS_WARNING appears, tell the user which parameter files may be stale and recommend updating. Continue with the skill normally using whatever parameters are available.
Safety rules for this skill:
Parameter database is read-only. Never write to, modify, or delete files in ~/econstack-data/parameters/. These are shared, versioned parameters maintained separately. If a parameter needs updating, tell the user to update the econstack-data repo.
Confirm before overwriting. Before writing an output file, check if a file with the same name already exists. If it does, ask the user: "A file named [filename] already exists. Overwrite it, or save with a new name?" Do not silently overwrite.
At the end of every skill run, report one of these statuses:
DONE: Analysis complete, output generated, all sections finished.
DONE_WITH_CONCERNS: Output generated but with caveats (e.g., data gaps, assumptions that need review, sections below expected depth).
NEEDS_CONTEXT: Need more information from the user before continuing.
Format: STATUS: [status] | [one-line reason]
/longlist: Benefits and Costs Longlist
The pre-CBA brainstorming skill. Produces a single clean longlist of benefits and costs for a project, with materiality (H/M/L), how to quantify each item, and how to monetise it. Designed to hand straight off to any downstream CBA or business case workflow.
The output is two tables. That is the whole skill.
Arguments
/longlist [project description] [options]
Examples:
/longlist "New secondary school in Leeds"
/longlist "Climate adaptation via city greening, Milan"
/longlist "Mandatory climate disclosure for large EU firms" --framework eu-brg
/longlist "Victorian level crossing removal" --framework au-vic
/longlist "Rural water supply project, Indonesia" --framework adb
/longlist "Urban transport upgrade, Nairobi" --framework wb
/longlist "Rural broadband rollout" --benefits-only
Options:
--framework <name> : uk-gb (default), eu-brg, wb, adb, or au-vic. Auto-detected from context if not set.
--sponsor <type> : government (default), private, blended, philanthropic. Drives the Cash flow column. Anchors what counts as cash on whose books. See Step 1.
--section <name> : Emit only one sub-component. Options: full (default), benefits (benefits table only), costs (costs table only), summary (cash flow summary only). Combinable with commas.
--benefits-only / --costs-only : Legacy aliases. Equivalent to --section benefits and --section costs.
--format <type> : Output format(s). Options: markdown (default, always generated), xlsx, word, pptx, pdf, or all. Comma-separate for multiple.
--client "Name" : Add "Prepared for" metadata to the output.
Supported frameworks
Flag
Framework
Use when
uk-gb
UK HM Treasury Green Book (2022, with Wellbeing supplementary 2021)
EU Better Regulation Guidelines (2021, SWD(2021) 305)
Regulations and EU-level interventions. Categories: economic, social, environmental, fundamental rights, SMEs, competitiveness. Compliance costs via Standard Cost Model. Companion methodology in the Better Regulation Toolbox.
wb
World Bank Economic Analysis of Investment Operations (OP 10.04; 2023 Technical Note)
World Bank-financed projects in low and middle income countries. Economic rate of return (ERR), economic NPV at country-specific discount rate, distributional incidence, poverty impact, incremental approach. Standard shadow pricing for tradables, non-tradables, labour.
adb
Asian Development Bank Guidelines for the Economic Analysis of Projects (2017 revision)
ADB-financed projects in Asia and the Pacific. Economic internal rate of return (EIRR), 9% hurdle rate (reducible to 6% for climate, health, education), poverty and distributional analysis, willingness-to-pay for non-traded outputs.
au-vic
Victorian Treasury High Value High Risk (HVHR) framework
Victorian Government projects above the HVHR threshold (typically AUD 100m capital, or otherwise designated high risk). Six-gate assurance process. Benefits expressed against an Investment Logic Map (ILM) and a Benefit Management Plan with named owners, KPIs, baselines, targets, and realisation timeframes. Disbenefits captured explicitly. ATAP M1 applies for transport sub-cases.
Auto-detection rules:
Mentions of "HVHR", "Investment Logic Map", "ILM", "Victorian Government", "Victoria", "Melbourne", "Geelong", or AUD with Victorian context -> au-vic
Mentions of "ADB", "Asian Development Bank", or Asian DMC context (Pakistan, Bangladesh, Indonesia, Philippines, Vietnam, Nepal, Sri Lanka, Pacific Islands) with project finance framing -> adb
Mentions of "World Bank", "IBRD", "IDA", "IFC project", or Africa / Latin America public investment context -> wb
Step 1: Get project description, counterfactual, and sponsor
Ask the user in ONE AskUserQuestion batch. If the project description was given on the command line, only ask for the remaining items.
Required questions:
Project description (free text, 2-3 sentences). What is it, where, what is it trying to achieve.
Counterfactual (free text). What happens if the project does NOT go ahead? This must be dynamic: what evolves over time without intervention (deterioration, demand growth, committed policies in the pipeline).
Sponsor (multiple choice, default = Government / municipality). Who is the named funder whose books we are tracking for cash flow? Options:
Government / municipality (default)
Private investor (equity or debt)
Blended (government + private + grants)
Philanthropic / grant-funded
The sponsor anchors the Cash flow column. An item is cash in when real money moves onto the sponsor's books, cash out when real money moves off, and non-cash when the social value has no money attached to the sponsor. Same item can be cash to a municipality and non-cash to a private investor, so the sponsor choice matters.
If --sponsor was passed on the command line, skip the sponsor question. Default is government.
Do NOT ask sector, scale, type, lens, materiality thresholds, or anything else. Detect them from the description.
If project description or counterfactual is missing or vague, ask once more for clarification, then proceed with best guess.
Step 2: Brainstorm internally (do NOT narrate to the user)
Silently walk through these lenses to surface candidates. Do not show the working. The output is the table, not the brainstorm.
Stakeholders: who is the direct beneficiary, who is indirectly affected (supply chain, neighbours, community, government, future generations, environment), who loses?
Causal chain (compressed ToC): inputs -> activities -> outputs -> outcomes -> impacts. Benefits sit mostly at outcomes/impacts. Costs sit mostly at inputs/activities.
Framework taxonomy: walk through every category for the chosen framework (see below). This catches benefits invisible through stakeholder mapping alone.
Sector trap check: for the detected sector, what is commonly missed and what is commonly double-counted?
Disbenefits (HVHR requires negative impacts to be captured explicitly alongside benefits)
Each HVHR benefit MUST have: a named owner, a measurable KPI, a baseline, a target, a measurement method, and a realisation timeframe. The longlist captures the KPI and measurement method in the quantification column. The owner, baseline, target, and timeframe are added downstream in the CBA or business case.
Target longlist size: 8-15 benefits and 5-10 costs. Do not pad. Do not produce 30 items.
Step 3: Apply filters before tabulating
Drop or downgrade items that violate any of these rules. If something is dropped, list it once in the "Excluded" section below the table with a one-line reason. Do not put excluded items in the main table.
Always exclude:
Sunk costs. Resources already committed that cannot be recovered. Green Book 2022 §5.17.
Transfers (in social CBA). Tax revenue on new earnings, council tax from new residents, welfare payments — these move money between parties without creating real resources. Note them as fiscal effects, not social benefits.
Always flag and downgrade (move to Excluded with reason):
Construction employment when capital cost is already on the cost side. The labour is paid for inside the capex line. Only include if there is genuine local labour market slack and the user explicitly asks.
Land value uplift when journey time savings (or any direct accessibility benefit) is already counted. Land values capitalise the same effect.
Tax receipts on earnings when gross individual earnings are already on the benefits side.
Step 4: Build the two tables
Each table has seven columns. Use H/M/L for materiality based on expected share of total NPV (H = top 3-5 items / >20% each; M = 5-20%; L = <5%).
For the Cash flow column, tag each item from the sponsor's perspective (set in Step 1):
Cash in : real money moves onto the sponsor's books. Examples: user fees, ticket sales, grant receipts, avoided opex the sponsor would otherwise pay, avoided capex the sponsor would otherwise fund, lease or rental income.
Cash out : real money moves off the sponsor's books. Examples: construction capex, operating expenditure, irrigation water bills, debt interest, maintenance, contractor payments.
Non-cash : social value with no money attached to the sponsor. Examples: heat deaths avoided, WELLBYs, biodiversity net gain, air quality improvements, carbon sequestration (unless the sponsor can actually sell credits).
Rules for tagging:
Avoided municipal costs (e.g. avoided stormwater grey infrastructure) are Cash in when the sponsor is the municipality: the sponsor would otherwise have paid them.
Avoided healthcare costs are Cash in when the sponsor is the healthcare system (NHS, SSN, Medicare) and Non-cash when the sponsor is a local municipality or a private investor.
Carbon sequestration is Non-cash by default. Mark it Cash in only if the sponsor can actually monetise the carbon (registered offset credits in a functioning market).
Property value uplift is Non-cash to a public sponsor (it accrues to private landowners), and already flagged as a likely double-count anyway.
Construction capex and annual O&M are always Cash out.
Embodied construction carbon is Non-cash (social cost, no money to anyone).
Transfers go to Excluded (as today). They are neither cash flow nor social value.
If the sponsor is blended, tag the item from the perspective of whoever bears or receives the dominant share.
For the quantification method, write a short concrete approach: how to measure the item in physical units. Examples: "tCO2e sequestered per ha × ha planted × decay curve", "heat-related deaths avoided estimated from EuroHEAT exposure-response × heat days × population in catchment", "compliance hours per business × number of affected businesses × frequency".
For the monetisation method, write the route from physical units to money: a published unit value, an analytical approach, or "qualitative only - narrative treatment". Cite the specific source. Examples: "DESNZ shadow carbon price (Italy: EU ETS price as proxy)", "Italian VSL ~ EUR 1.6m per fatality avoided", "Standard Cost Model: hours × median wage × frequency".
If no method exists for an item, write "Qualitative only - narrative treatment" in the monetisation column. Do not leave blank.
Step 5: Write the output
Save longlist-[slug]-[YYYY-MM-DD].md with this exact structure. Nothing more, nothing less.
# Longlist: [Project Name]
**Framework**: [uk-gb | eu-brg | au-vic] · **Sponsor**: [government | private | blended | philanthropic] · **Date**: [YYYY-MM-DD]
**Project**: [1-2 sentence project description]
**Counterfactual**: [1-2 sentence dynamic baseline]
## Benefits
Table 1: Benefits longlist.
| # | Benefit | Description | Materiality | Cash flow | Quantification method | Monetisation method |
|---|---------|-------------|:-----------:|:---------:|----------------------|---------------------|
| 1 | [name] | [one sentence] | H | Cash in / Non-cash | [physical-unit method] | [unit value or approach with source] |
| 2 | ... | ... | M | ... | ... | ... |
| ... | | | | | | |
Source: Authors' analysis using [framework name].
## Costs
Table 2: Costs longlist.
| # | Cost | Description | Materiality | Cash flow | Quantification method | Monetisation method |
|---|------|-------------|:-----------:|:---------:|----------------------|---------------------|
| 1 | [name] | [one sentence] | H | Cash out / Non-cash | ... | ... |
| ... | | | | | | |
Source: Authors' analysis.
## Excluded
- **[Item name]**: [reason — sunk cost / double-counts row N / transfer / etc.]
- ... (omit this section entirely if no exclusions)
## Cash flow summary
| Side | Cash items (count) | Non-cash items (count) | Note |
|------|:------------------:|:----------------------:|------|
| Benefits | [n_cash_in] | [n_non_cash_benefits] | [one line, e.g. "Most benefits are non-cash social value; requires public or philanthropic funding"] |
| Costs | [n_cash_out] | [n_non_cash_costs] | [one line, e.g. "All costs are cash out from the sponsor"] |
## Next step
Hand this to a downstream CBA or business case workflow to monetise and compute both economic and financial NPV.
<!-- KEY NUMBERS
type: longlist
project: [name]
framework: [framework]
sponsor: [sponsor]
n_benefits: [count]
n_costs: [count]
n_h_benefits: [count]
n_h_costs: [count]
n_cash_in_benefits: [count]
n_non_cash_benefits: [count]
n_cash_out_costs: [count]
n_non_cash_costs: [count]
date: [YYYY-MM-DD]
-->
That is the entire output. No methodology section. No shortlist section. No detail tables. No JSON companion.
Sub-component selection (via --section): if the user wants only part of the output, emit only those parts. In all modes include the header block.
full (default): header + both tables + Excluded + Cash flow summary + next step
benefits: header + benefits table only
costs: header + costs table only
summary: header + cash flow summary only
benefits,costs: both tables without summary / excluded / next step
Always include the KEY NUMBERS comment at the bottom.
Format-specific output structure (only produce formats explicitly requested; see dispatcher below):
Markdown (.md): longlist-[slug]-[date].md with the structure shown above.
Excel (.xlsx): invoke the xlsx skill. Two sheets: Benefits and Costs, seven columns each. Conditional formatting on the materiality column (green H, amber M, grey L) and on the Cash flow column (green "Cash in", red "Cash out", grey "Non-cash"). Save as longlist-[slug]-[date].xlsx.
Word (.docx): invoke the docx skill. One document: header block, benefits table, costs table, excluded list, cash flow summary. Save as longlist-[slug]-[date].docx.
PowerPoint (.pptx): invoke the pptx skill. Four slides: title / counterfactual, benefits table, costs table, cash flow summary. Action titles. Save as longlist-[slug]-[date].pptx.
PDF: render markdown through the econstack Quarto template. Save as longlist-[slug]-[date].pdf.
Output formats
The user requests format(s) via --format. Default: md. Comma-separated lists are allowed (e.g. --format md,pdf); all expands to every supported format.
For each format explicitly requested, produce that file and only that file:
md: write the markdown inline (only when md is in the requested set).
docx: invoke the docx skill with the rendered content.
pdf: render via the econstack Quarto template (or invoke the pdf skill if no template exists for this skill).
xlsx: invoke the xlsx skill with the structured tables.
pptx: invoke the pptx skill with the briefing as a deck.
Do NOT produce formats that were not requested. This is the v0.4 fix for the multi-format leak that previously caused --format pdf to also write .md and .docx files alongside the PDF. Any intermediate files needed during rendering must go to a temp directory and be cleaned up before the skill returns.
When you finish, the file listing in your "Saved:" message must contain exactly the files the user asked for, no extras.
Tell the user:
Longlist complete. [N] benefits, [M] costs.
Saved: longlist-[slug]-[date].md
[Other formats listed only if generated]
Citation discipline
Every numerical claim in the output must be followed by an inline citation in the form [SOURCE_CODE, vintage]. SOURCE_CODE is a short tag (e.g. ONS_PSF, OBR_EFO, BoE_MPR, Fed_FOMC, ECB_EB, RBA_SoMP, IMF_WEO, OECD_EO, Eurostat, BLS, BEA, FRED, ABS, Comtrade) matching an entry in the References footer. vintage is the publication date of the source data (e.g. Mar 2026, Q4 2025, Jan 2026).
Examples:
CPI was 3.4% YoY in March 2026 [ONS_CPI, Mar 2026].
The OBR forecasts borrowing falling to 1.6% of GDP by 2028-29 [OBR_EFO, Mar 2026].
Industry concentration is moderate: HHI is 1,820 across the top 8 firms [Companies_House, Q4 2025].
Numbers that cannot be sourced to a primary publication must NOT appear in the output. No exceptions: do not estimate, infer from training data, interpolate, or recall from memory. If a needed number isn't in fetched data, state it explicitly:
[Source] has not yet published this measure for [period].
Self-check before output: scan the draft for every number. If any number lacks an inline citation, either add the citation or remove the number. Citation density should be roughly even across sections; a section with no citations is a red flag that the section was generated rather than sourced.
Factuality
When citing parameter values (carbon prices, QALY values, VTTS, optimism bias percentages, distributional weights), use values from ~/econstack-data/parameters/ rather than recall. The parameter database is the source of truth and is dated. If a parameter is not in the database, state that and use a built-in default with an explicit "fallback" annotation. Do not invent or interpolate parameter values from memory.
Common gotchas: HMT Green Book STPR is currently 3.5% with a declining schedule for long horizons (Annex 6); DESNZ shadow carbon price varies by year and is published annually; QALY GBP 70k is the Green Book wellbeing supplement value, not the NICE HTA threshold (GBP 20k to 30k). Cite which is which.
Out of scope (unless explicitly requested)
A longlist is a brainstorm, not a CBA. Do NOT:
Recommend which benefits or costs to pursue. That is a downstream judgement.
Compute NPV, BCR, or rank-order options.
Apply optimism bias or sensitivity analysis here. Those belong in CBA.
Pre-quantify items as "M" or "L" without explaining the materiality reasoning in one line.
Skip items because they are likely to be small. Materiality is L, not zero.
If the user asks for any of the above, route to /cba or /business-case (downstream CBA / business-case skills) rather than expanding longlist scope.
Method library (for filling in the quantification + monetisation + cash flow columns)
This is a lookup the skill uses internally. Do not show it to the user. Pick the closest match for each item; if nothing fits, fall back to "primary research" or "qualitative only". The Cash flow column assumes a government sponsor. Adjust for other sponsors per Step 4 rules (e.g. avoided NHS costs are Cash in to the NHS as sponsor but Non-cash to a municipality).
UK Green Book defaults (uk-gb)
Item type
Quantification
Monetisation
Cash flow (gov sponsor)
Travel time savings
Minutes saved × annual trips
DfT TAG values per minute by purpose. TAG Data Book.
Non-cash
Accidents avoided
Casualties avoided by severity
TAG A4.1 casualty unit costs
Non-cash
Carbon (operational)
tCO2e by year
DESNZ shadow carbon price
Non-cash
Carbon (embodied)
RICS Whole Life Carbon × capex
DESNZ shadow carbon price
Non-cash
QALYs
Cohort × per-person QALY gain
GBP 70k/QALY (Green Book wellbeing supp.); cite NICE GBP 20-30k for HTA
Non-cash
Avoided NHS admissions
Admissions avoided
NHS Reference Costs (HRG)
Cash in (NHS) or Non-cash (other sponsor)
Wellbeing
WELLBYs gained
GBP 13k per WELLBY
Non-cash
Earnings uplift
Cohort × wage premium × deadweight discount
DfE returns to qualifications
Non-cash
Avoided welfare spend
Person-years unemployed avoided
GMCA Unit Cost Database
Cash in (central government)
Land value uplift
Hectares × uplift factor
MHCLG Land Value Estimates (only if not double-counting)
Non-cash to public sponsor
Air quality
tonnes of pollutant reduced
Defra air quality damage costs
Non-cash
Flood risk reduction
Properties protected × probability
EA Flood Damage Costs
Non-cash (unless sponsor owns protected assets)
Biodiversity
BNG units
Natural England BNG metric, Defra ENCA
Non-cash (unless credits are sold)
Recreation / amenity
Visits, hectares
Defra ENCA values, or hedonic pricing
Non-cash (unless fees charged)
User fees / charges / tickets
Users × tariff
Market tariff schedule
Cash in
Grant receipts
Award amount × draw-down profile
Grant agreement
Cash in
Construction (capital)
GIA × £/sqm or BoQ
BCIS, SPON's
Cash out
Operating and maintenance
Annual estimate
2-5% of capex (BCIS FM benchmarks)
Cash out
Optimism bias
% uplift on capex
HMT Supplementary Green Book Table 1
Cash out
EU Better Regulation defaults (eu-brg)
Item type
Quantification
Monetisation
Cash flow (gov sponsor)
Compliance cost (business)
Affected firms × hours × frequency
Standard Cost Model: hours × median EU/national wage
Non-cash to government; cash out to regulated firms
Familiarisation cost
One-off hours per firm × firms
SCM, one-off
Non-cash to government
Direct business benefits
Cost or time saved per firm
SCM applied to savings side
Non-cash to government
Consumer benefit (prices)
Price change × market size
Price elasticity × price × volume
Non-cash
Consumer benefit (info, choice)
Affected consumers
Stated preference WTP, or "qualitative only"
Non-cash
Safety / fatalities avoided
Fatalities avoided
EU Reference VSL (~ EUR 3.6m, EC 2021); national VSL where available
Non-cash
Carbon (operational)
tCO2e
EU ETS price, or EC Better Regulation shadow carbon price
Non-cash
Air quality
Pollutant tonnes reduced
EEA / NEEDS damage cost values
Non-cash
SME impact
Number of SMEs affected, costs
SCM with separate SME cost share
Non-cash to government
Fundamental rights
Affected rights and groups
Qualitative only - narrative treatment
Non-cash
Environmental (biodiversity, water)
Affected hectares / volumes
EC Natural Capital Accounting where available, otherwise qualitative
Non-cash
Compliance and enforcement (public sector)
FTEs × annual cost
Eurostat labour costs
Cash out
EU grant / structural funds inflow
Award × draw-down profile
Grant agreement (e.g. NextGenerationEU, ERDF, LIFE)
Cash in
World Bank defaults (wb)
Item type
Quantification
Monetisation
Cash flow (gov sponsor)
Travel time savings (transport)
Hours saved × users × trips per year
Shadow wage rate (typically 30-50% of market wage for non-working time in low-income contexts); or local VOT study
Non-cash
Yield uplift (agriculture)
Δ yield (t/ha) × area × farmgate price
FAO price database or country MAFF farmgate prices
Cash in (to farmers, or farmer-owned cooperatives)
Reduced water fetching time
Hours saved × affected population
Shadow wage for women / children (often 0.5x adult wage)
Non-cash
Health outcomes (DALYs / reduced morbidity)
DALYs avoided
GDP per capita × DALYs × 1.0-3.0 GDP multiplier (WHO CHOICE), or country-specific cost-per-DALY
Willingness-to-pay studies, or cost of next-best alternative (kerosene, diesel)
Cash in if tariff revenue; else Non-cash
Avoided emissions
tCO2e
World Bank shadow carbon price (USD 40-80/t, rising to USD 50-100 by 2030)
Non-cash
Avoided environmental damage
Physical units × damage cost
World Bank Environmental Economics values, or benefit transfer from peer studies
Non-cash
Operational and maintenance costs
Annual by project type
Country-specific unit costs, or %-of-capex benchmarks
Cash out
Capital costs
BoQ × unit rates
Country construction cost databases, or regional comparables
Cash out
ADB defaults (adb)
Item type
Quantification
Monetisation
Cash flow (gov sponsor)
Transport: travel time savings
Hours saved × users × trips per year
ADB shadow wage rate by country and skill level
Non-cash
Transport: VOC savings
Vehicle-km by type
ADB Transport Appraisal Note VOC formulae, or HDM-4 output
Non-cash
Irrigation yield uplift
Δ yield (t/ha) × area × farmgate price
ADB Economic Analysis reference values; FAO prices adjusted for distortions
Cash in (farmers)
Power generation
kWh produced × net
Willingness-to-pay; or avoided cost of next-best plant; or tariff revenue
Cash in (if tariff revenue retained by sponsor)
Water supply
m³ delivered × consumers
Willingness-to-pay studies (ADB Compendium); or avoided cost of private water vendors
Cash in (if tariff revenue); else Non-cash
Health: DALYs avoided
Cohort × per-person DALY gain
1-3x GDP per capita per DALY, country-specific
Non-cash
Education: wage premium
Graduates × wage premium × deadweight discount
Country-specific Mincerian returns
Non-cash
Carbon benefits
tCO2e
ADB shadow carbon price (USD 36.30/t from 2017, rising)
Non-cash
Gender-specific benefits
Women / girls affected × benefit per person
Same as above, disaggregated and reported separately
Non-cash
Capital costs
BoQ × country construction rates
ADB country construction cost benchmarks, Rawlinsons (regional)
Cash out
Operating and maintenance
Whole-of-life annual estimate
Country-specific benchmarks; typically 2-5% of capex per year
Cash out
Sensitivity and switching values
Required by ADB for all major variables
ADB guidelines specify +/-20% scenarios and switching value computation
n/a
Victoria HVHR defaults (au-vic)
For HVHR projects, every benefit needs a KPI and a measurement method. The "quantification" column captures the KPI; the "monetisation" column cites the unit value or pricing source.
Item type
Quantification (KPI)
Monetisation
Cash flow (gov sponsor)
Travel time savings (transport)
Vehicle-hours saved by mode and purpose
ATAP PV5 unit values per hour by purpose
Non-cash
Vehicle operating cost savings
Vehicle-km by vehicle type
ATAP PV5 VOC formulae
Non-cash (users save; not sponsor)
Road safety improvements
Crashes avoided by severity (fatal / serious / minor)
BITRE crash unit costs; or AUD ~5.4m per fatality (OBPR 2024)
Non-cash
Carbon (operational)
tCO2e by year
Australian shadow carbon price
Non-cash
Carbon (embodied)
RICS WLCA × capex intensity
Same shadow carbon price as operational
Non-cash
Health and wellbeing
QALYs / DALYs gained
AUD 250k/QALY (PBAC reference)
Non-cash
Reliability improvements
Standard deviation of journey time × trips
ATAP PV5 reliability ratio
Non-cash
Accessibility (jobs / services within X minutes)
Population catchment increase
Hedonic property values, or qualitative
Non-cash
Agglomeration / WEBs
Effective density × elasticity
ATAP M1 WEBs methodology (supplementary only)
Non-cash
Service delivery (health, education, justice)
Patient visits, student-years, case throughput
Vic Department service unit costs
Non-cash (unless fees charged)
Asset condition uplift
Asset condition score improvement; renewal years deferred
Avoided renewal capex, discounted to PV
Cash in (avoided future capex by the same sponsor)
Risk reduction
Probability × consequence reduction
Expected value of avoided loss
Cash in if avoided payout is on sponsor's books; else Non-cash
Indigenous and equity outcomes
Specific KPI (e.g. Aboriginal Victorians employed)
Often qualitative; supplement with distributional weights
Non-cash
Disbenefits (HVHR requires explicit capture)
KPI describing the harm
Same source as the analogous benefit; or qualitative
Non-cash (use Cash out only if a real sponsor payout)
User fares / tolls / fees
Users × tariff
Published tariff schedule
Cash in
Commonwealth grant receipts
Award × draw-down profile
Federal funding agreement
Cash in
Construction (capital)
Bill of quantities × Rawlinsons / Cordell rates
Rawlinsons Australian Construction Handbook; Cordell
Cash out
Operating and maintenance
Annual cost estimate
Whole-of-life model; typically 1.5-3% of capex per year
No published unit value: state "Primary research: [survey | interviews | Delphi panel | revealed preference]" with rough sample/scope.
No quantification possible: "Qualitative only - narrative treatment".
Construction employment: do NOT include unless slack exists; even then, flag and put in Excluded.
Tax receipts on new earnings: Excluded (transfer).
Important rules
Counterfactual is mandatory. If the user does not give one, ask once. If still missing, refuse to produce a longlist - the comparison has no meaning without it.
Sponsor is mandatory for the Cash flow column. Default is government. A non-government sponsor (private investor, blended, philanthropic) changes the tagging significantly for items like avoided public expenditure, user fees, and grant receipts. If the sponsor is genuinely unclear, default to government and note the assumption in the header.
Cash flow ≠ materiality. A Cash in item is not automatically more important than a Non-cash item. A park project is dominated by Non-cash benefits that still make it worth doing. Cash flow is a separate lens for financial viability, not a ranking.
Every row must have a Cash flow tag. No blank cells. If unsure, default to Non-cash and explain the tagging in a footnote. Transfers still go to Excluded.
The brainstorm is internal. Do not show stakeholder lists, ToC steps, or lens-by-lens working in the output. The user wanted a table. Give them a table.
Maximum three interactive questions. Project description, counterfactual, and sponsor. That is it. Do not pepper the user with sector / scale / lens / materiality questions.
Materiality is a judgement call. H = top 3-5 items, expected to dominate NPV. M = meaningful but not headline. L = small or speculative.
Quantification ≠ monetisation. Quantification gives you physical units (tonnes, lives, hours). Monetisation converts to money. Both columns are required for every row.
Drop, do not bury. Items that fail filters go to the Excluded section, not into the main table greyed out. Keep the main table clean.
No sunk costs. No transfers in social CBA. No double counts. See the filter rules in Step 3.
Do not narrate the methodology. No "Methodology" section. No "Lenses applied" footer. No shortlist recommendation. The next-step line is the only metadata that survives.
Em dashes: never use em dashes in any output. Use commas, colons, parentheses, or "and".
Integration with other skills
The two tables are designed to hand off directly to any downstream CBA, business case, or RIA workflow. The Cash flow column supports both an Economic NPV (all items at shadow prices) and a Financial NPV (cash items only, at the sponsor's cost of capital).
/econ-audit can audit a longlist for double counting, transfer inclusion, and filter compliance.
