Hidden Cost Index
Methodology · hiddencostindex.co.za
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Methodology

The Hidden Cost Index (HCI) is a descriptive model. It is not a financial product, tax calculator or investment tool. It is designed to make visible the "survival costs" paid by households to compensate for systemic failures in South Africa.

Version 0.1 · Prototype

1. Core definitions

1.1 Income concepts

  • Gross income: total monthly income before PAYE, UIF and other deductions.
  • Net income: monthly take-home after statutory deductions.
  • Basic life cost: minimum recurring spend on rent/bond, basic groceries, utilities and essential communication.
  • True disposable income: net income minus hidden costs.

1.2 Hidden cost

Hidden costs are recurring monthly amounts paid not to upgrade lifestyle, but to buy safety, stability and basic functionality that should exist by default in a working system.

1.3 Categories

  • Security tax – armed response, electric fencing, cameras, guard levies and crime-loaded premiums.
  • Infrastructure failure – inverters, batteries, generators, backup ISP, water storage, surge damage.
  • Health system gap – medical aid, gap cover, out-of-pocket private healthcare.
  • Transport penalty – car instalments, fuel, maintenance, insurance due to weak public transport.
  • Education uplift – private/semi-private schooling and supplemental lessons.
  • Crime & risk premium – higher excesses, recurring loss and self-insurance from crime exposure.

2. Mathematical structure

2.1 Category sums

SECURITY_COST = armed_response + security_levies + security_capex / 60 ``` INFRA_COST = backup_power_fuel + backup_connectivity + infra_capex / 60 + appliance_damage / 12 HEALTH_COST = medical_aid + gap_cover + health_out_of_pocket TRANSPORT_COST = Σ(installment + fuel + maintenance + insurance) EDU_COST = Σ(school_fees + extra_lessons) CRIME_COST = crime_insurance_uplift + crime_self_insured / 12
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2.2 Aggregate hidden cost

HIDDEN_COST_TOTAL = SECURITY_COST ``` - INFRA_COST - HEALTH_COST - TRANSPORT_COST - EDU_COST - CRIME_COST
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2.3 Derived metrics

TRUE_DISPOSABLE = ``` NET_INCOME - HIDDEN_COST_TOTAL SHADOW_TAX_RATE = (HIDDEN_COST_TOTAL / GROSS_INCOME) × 100 HCI (Hidden Cost Index) = (HIDDEN_COST_TOTAL / BASIC_LIFE_COST) × 100
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Amortisation periods (60 months for capex, 12 months for average replacement / damage) are configurable and documented per release.

3. Data inputs

3.1 User-provided inputs

  • Household gross and net income.
  • Rent or bond, basic groceries and utilities.
  • Security contracts and recurring security-related levies.
  • Medical aid, gap cover, out-of-pocket healthcare.
  • Vehicle instalments, fuel, insurance and maintenance.
  • Education and tutoring costs, where applicable.
  • Self-insurance / recurring crime-related losses.

3.2 Baseline / external inputs (planned)

  • Fuel price indices for transport cost defaults.
  • Electricity tariffs and load-shedding severity indices for infrastructure assumptions.
  • Stats SA CPI, with sub-indices for health, transport and insurance.
  • City-level cost-of-living baselines (rent, utilities, groceries) from third-party datasets.
  • Crime statistics at city / metro level for risk multipliers.

In the current prototype, these are represented as static scenario assumptions, documented in the dashboard's city comparison tab.

4. Interpretation and limitations

4.1 What HCI does and does not claim

Descriptive: HCI describes cost structure; it does not give advice.
Household-level: It works at the household level, not macroeconomic modelling.
Comparative: It is designed for city-to-city and scenario comparison.

The model does not attempt to calculate "optimal" spending, poverty thresholds or tax incidence in a formal economic sense. It simply quantifies the proportion of income allocated to compensating for systemic failure.

4.2 Known limitations

  • Excludes non-monetary burdens (time lost to outages, stress, health effects).
  • Relies on honest and accurate user input; no external validation is attempted.
  • Scenario profiles use rounded, stylised values to illustrate relative pressure, not exact budgets.
  • External data sources may have lags, coverage limitations or sampling bias.

5. Roadmap

  • Integrate periodic fuel price and load-shedding indices into default assumptions.
  • Publish city-level HCI benchmarks with methodology notes per release.
  • Add export tools for anonymised aggregates (for researchers, journalists and policymakers).
  • Extend comparison sets to additional South African and global cities.

Feedback on the methodology is welcome. The goal is transparency: any index that claims to describe lived reality should be inspectable and falsifiable.

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