TransparentSource-firstValue-year aware

Methodology

Transparent by design.

PathLens is built to be explainable: every score is traceable to indicator values, normalization rules, and weights — with value years visible when datasets are lagged.

Browse indicators Compare Example country

Quick guide

Strict year: use only values from the selected year.
Latest ≤ year: carry forward the most recent datapoint at or before the selected year (value year shown).
Confidence reflects coverage after missing-data adjustment.

Tip

Searching for FINDEX_ highlights Global Findex indicators.

Dimensions & scenario weights

Scenarios are simple weight presets for the four dimensions.

Default

{
  "affordability": 0.25,
  "skills_capacity": 0.15,
  "governance_policy": 0.25,
  "access_infrastructure": 0.35
}

Governance-first

{
  "affordability": 0.2,
  "skills_capacity": 0.15,
  "governance_policy": 0.4,
  "access_infrastructure": 0.25
}

Inclusion-first

{
  "affordability": 0.35,
  "skills_capacity": 0.2,
  "governance_policy": 0.2,
  "access_infrastructure": 0.25
}

Infrastructure-first

{
  "affordability": 0.2,
  "skills_capacity": 0.1,
  "governance_policy": 0.25,
  "access_infrastructure": 0.45
}

How scores are computed

Normalization, missing data, confidence, and value years.

PathLens combines many indicators into a single 0–100 score. The key idea is: compare each country to the global distribution of that indicator for the relevant year, then aggregate with weights.

Winsorization: per indicator/year, values are clamped to the 2nd–98th percentile to reduce outlier distortion.
Scale to 0–100: min-max scaling using the winsorized min/max across countries for that year.
Directionality: indicators where “lower is better” are inverted after scaling.
Missing values: dimension scores compute from remaining indicators. If coverage is below 60% in a dimension, that dimension’s weight is reduced proportionally and the result is marked lower confidence.
Confidence badge: reflects the “effective weight sum” after missing-data down-weighting. Higher means more complete coverage.
Value year & staleness (Strict vs Latest ≤ year): some datasets are lagged or non-annual (notably Global Findex). In Latest ≤ year mode, we use the most recent available datapoint at or before the selected year and surface the underlyingvalue year.

Important: the “Scenario weighting (custom)” panel computes a score client-side from normalized indicators (and supports Latest ≤ year). The headline score on the Country Lens page is a precomputed scores row for the selected scenario/year.

Data sources (high level)

What we ingest and what to expect.

World Bank (WDI)

Macro + infrastructure context (e.g., Internet use, broadband, electricity, poverty, GDP).
Annual(ish) series; latest year varies by indicator.

World Bank (WGI)

Governance estimates (e.g., Rule of Law, Government Effectiveness).
Not always updated every year for all countries.

World Bank (Global Findex)

Survey-based adoption/usage (accounts, digital payments, mobile money).
Not an annual series; in “Latest ≤ year” mode values may be carried forward (and we show the value year).

UNESCO UIS

Education/skills proxies (literacy, enrolment, completion, schools with computers).
Coverage can be uneven; expect missing values for some countries/years.

A4AI / ITU-A4AI pricing DB

Affordability indicators (policy/driver score + mobile broadband price as % of income).
Often lagged; “Latest ≤ year” is recommended for comparisons across years.

How to interpret changes over time

Why “latest≤year” matters.

If an indicator is updated irregularly, strict-year comparisons can look “missing” even when a country has a recent datapoint.
Use Latest ≤ year for a stable view when combining datasets with different update cadences.
Always check the value year badge to understand how current the underlying data is.

Indicators

Filtered by VA.EST. Clear filter

Code

Indicator

Dimension

Direction

Source

VA.EST

Voice & Accountability (estimate)

Unit: estimate · Default weight: 1

Governance & policy

higher_is_better

World Bank (WGI)