- Raw value
- 1590.74articles per million people
- Year
- 2023. The rail runs from 1960 to 2026.
- Normalized
- Source
- World Bank (IP.JRN.ARTC.SC)
- History
Nepal
Strongest usable evidence: Adaptability, at 57.0. Raise Anticipation first, at 20.5. Experimentation needs more evidence: confidence is 0.23.
Raise, lowest first
| Dimension | Confidence | Score |
|---|---|---|
| Anticipation | 0.46 | 20.5 |
| Learning | 0.54 | 24.7 |
| Building | 0.54 | 24.9 |
Measure before managing
| Dimension | Confidence | Score |
|---|---|---|
| Experimentation | 0.23 | 5.2 |
| Shared Purpose | 0.28 | 60.3 |
| Trust | 0.29 | 69.5 |
| Agency | 0.35 | 45.8 |
| Coordination | 0.41 | 78.3 |
These lists are the country's capability agenda, computed from the scores. Read the full agenda. It names comparable evidence from other countries and the 18 gaps in the registry.
Why this country is included: Added in the 9.0.0 completion, which takes every country of a million people or more that is measurable in all nine capabilities.
Read Nepal beside up to three other countries, down to the indicator behind every row.
- Usable or good evidence
- Thin evidence, hollow point. The dashes open further as confidence falls.
- The point still sits at the score, because confidence never moves it.
- Click any axis to see every country on that dimension.
A score from 0 to 100 is a position inside the frame that all the benchmark countries set: zero is the weakest on a dimension and 100 is the strongest. A score of 10 puts a country near the floor of that frame and does not mean 10 percent of a capability.
| Coordination | 0.41 | 3 of 5 | 0.86 | no trend | no data | no estimate | |
| Trust | 0.29 | 3 of 7 | 0.83 | no trend | 44.0 | -25.5 | |
| Shared Purpose | 0.28 | 2 of 6 | 0.88 | +26.9(2) | 42.0 | -18.3 | |
| Adaptability | 0.53 | 4 of 6 | 0.85 | no trend | no data | no estimate | |
| Agency | 0.35 | 3 of 5 | 0.61 | no trend | no data | no estimate | |
| Building | 0.54 | 4 of 6 | 0.85 | 0.0(3) | no data | no estimate | |
| Learning | 0.54 | 3 of 4 | 0.78 | no trend | no data | no estimate | |
| Anticipation | 0.46 | 2 of 4 | 0.96 | +11.6(2) | 24.0 | +3.5 | |
| Experimentation | 0.23 | 4 of 9 | 0.56 | no trend | 12.0 | +6.8 |
How to read this page
Each dimension has a score from 0 to 100. It shows where this country sits among all 125 countries in the comparison frame, not a percentage. Confidence sits beside the score. A dashed radar edge and hollow point mean the evidence is thin. The records below show each indicator, its raw value, year and source.
A panel estimate, when present, is a separate judgment about what the indicators miss. It does not change the score or confidence. The panel's provenance is shown beside the estimate.
- direct capability measuredirect capability measure Measures the thing itself.
- capability inputcapability input Measures something that supports the capability.
- downstream outcomedownstream outcome Measures a result that usually follows from the capability.
- perception proxyperception proxy Records what people or experts say, not what they did.
Confidence
- very thin0.00 to 0.25
The score rests on one or two indicators. Do not quote it on its own.
- thin0.25 to 0.45
A minority of indicators, or evidence old enough to have moved. Read with care.
- usable0.45 to 0.65
Enough evidence to compare countries, with known holes.
- good0.65 and above
Most indicators observed, recent, from official or intergovernmental sources.
A row marked no dataset exists is a gap: the benchmark wants data that nobody publishes. A retired row has a source this project chose not to use. Both reduce confidence. The glossary defines each term, and the limits page lists where these numbers are known to be wrong about the world.
Anticipation
How capable is the country of identifying and preparing for emerging change?
+11.6 over 10 years, from 8.9 in 2016 to 20.5 on 2 indicators seen in both years.
Trends use fewer indicators than the current score and use today's frame. A longer span reaches further back.
- Raw value
- 60.368index 0-100
- Year
- 2024. The rail runs from 1960 to 2026.
- Normalized
- Source
- World Bank (IQ.SPI.OVRL)
- History
Government foresight capacity
direct capability measureno dataset exists- Raw value
- no dataindex 0-100
- Year
- no data
- Normalized
- no data
- Source
- none
- History
- no data
Note: No comparable international dataset. OECD and UN work is descriptive, not scored. Envisioning would have to build this.
Long-horizon research commitments
direct capability measureno dataset exists- Raw value
- no data% of new grants
- Year
- no data
- Normalized
- no data
- Source
- none
- History
- no data
Note: Redefined 2026-10-02 (D152). The row asked for the share of R&D spending classed as basic research, which is the make-up of a spending stock, the construct D142 retired business R&D share for. OECD MSTI publishes that share for its members only, and UNESCO UIS no longer serves R&D by type of research (construct audit, 2026-10-02). The behaviour behind it is a funder committing to a horizon: a grant awarded for five years or more is a decision to wait for a result. Untried: no memo has triaged a grant register. National funders publish award lists one by one with their own durations, and commercial grant aggregators fail the inspectability rule. Wireable on a grant-level register with award and end dates, on one definition of a competitive public grant, for half the frame or more.
Conditions, not scored
What the country has to work with on this capability. The values are shown as the source published them and are not part of the score, the confidence or the trend. The rank counts the countries with a value, best first.
R&D expenditureWorld Bank (GB.XPD.RSDV.GD.ZS), 2010
0.3 % of GDP, rank 73 of 118. Gross domestic expenditure on research and development as a share of GDP.
The value is from 2010, more than 15 years old.
A condition, not scored: money committed to research is what a country spends, and spending it does not show the country reads the future well (D122).
Researchers in R&DWorld Bank (SP.POP.SCIE.RD.P6), 2002
59.7 per million people, rank 95 of 114. Full-time-equivalent researchers per million people.
The value is from 2002, more than 15 years old.
A condition, not scored: a standing stock of people who could investigate is what a country has, not a record of what they found (D122). Correlates with income but survives size normalization.
Secure internet serversWorld Bank (IT.NET.SECR.P6), 2024
541 per million people, rank 73 of 125. Servers using encryption in internet transactions, per million people.
A condition, not scored: a diffusion stock of digital adoption that money buys, not an act of anticipation (D122). Spans four orders of magnitude, so its rank is read on the published value and its correlations on the logged one.
Panel estimate, round 2, how this layer works
- 23.0 institutionalist@claude-opus-5-5, self-confidence 0.40
I move up three points: the post-2015 building code reform and the community flood early-warning systems on the Karnali and Koshi are institutionalised, as the others argue. Chronic government turnover and weak central planning keep me below them, and code enforcement remains patchy.
- 25.0 bottom_up@claude-opus-5-5, self-confidence 0.40
A's point on chronic government turnover blocking sustained planning is fair and I trim a point; C and I agree that community flood early warning on the Karnali and Koshi and post-2015 code reform are learned preparation the indicators miss, so I stay above A.
- 24.0 wealth_sceptic@claude-sonnet-5-5, self-confidence 0.40
Little research and a below-middle statistical score. Community-based flood early warning and post-2015 building-code reform are learned preparation beyond income, but implementation is patchy and governments turn over, so I move down slightly.
Agency
How able are individuals and organizations to turn an intention into action?
No trend is shown because too few indicators have values at both ends. The rows below still show the available history.
- Raw value
- 1.398per 1,000 aged 15-64
- Year
- 2020. The rail runs from 1960 to 2026.
- Normalized
- Source
- World Bank (IC.BUS.NDNS.ZS)
- History
- Raw value
- 22.5days
- Year
- 2019. The rail runs from 1960 to 2026.
- Normalized
- Source
- World Bank (IC.REG.DURS.MA.DY)
- History
- Raw value
- 8count
- Year
- 2019. The rail runs from 1960 to 2026.
- Normalized
- Source
- World Bank (IC.REG.PROC.MA.NO)
- History
Adults doing digital tasks
direct capability measureno dataset exists- Raw value
- no data% of adults
- Year
- no data
- Normalized
- no data
- Source
- ITU / UNESCO UIS (SDG 4.4.1, ICT skills by type)
- History
- no data
Note: Redefined 2026-10-02 (D152). The row asked whether adults can perform standard digital tasks, which reads a skill level, the kind of stock D122 moved out of the scores with internet users. It now counts the act: a person who did the task. It is not the internet users condition beside it, which counts access. Candidate: ITU ICT skills by type (SDG 4.4.1) through the UNESCO UIS API, probed 2026-10-02. Sent a message with an attached file reaches 33 of the 53 countries then in the frame, 25 at 2018 or later, with no United States, India or China and most of Africa and Central America missing; two other task items reach 31 and 16. The items are self-reported and the task list has changed between rounds. Wireable on one task observed for half the frame or more at 2018 or later.
Perceived control over life
perception proxymissing- Raw value
- no datamean 1-10
- Year
- no data
- Normalized
- no data
- Source
- Joint EVS/WVS (A173)
- History
- no data
Note: A perception: the publisher-weighted mean, on a 1 to 10 scale, of how much freedom of choice and control respondents feel they have over the way their life turns out, from the official Joint EVS/WVS 2017-2022 results table, release 5.0.0. It observes the felt capacity to act, not action. The table prints the mean to one decimal and no top-box share, so the row stores the mean and ties are common. Fieldwork years differ by up to six years: the 37 countries emitted were surveyed between 2017 (eight, the US among them) and 2023 (India), and every value is stamped with the release year 2022. Response style on 10-point scales differs across cultures, and a closed autocracy can read high: Vietnam and Nicaragua sit near the top of the frame. Countries with separate EVS and WVS samples (Germany, the United Kingdom, the Netherlands) are held, as for interpersonal trust. See D127 and A15.
Conditions, not scored
What the country has to work with on this capability. The values are shown as the source published them and are not part of the score, the confidence or the trend. The rank counts the countries with a value, best first.
Individuals using the internetWorld Bank (IT.NET.USER.ZS), 2024
46.3 % of population, rank 103 of 125. Share of the population that used the internet in the last three months.
A condition, not scored: access to the basic tool of modern agency is what people have to act with, not a record of them acting (D122). Saturates near 95%, which compresses the top of the range.
Financial account ownershipWorld Bank (FX.OWN.TOTL.ZS), 2024
60 % aged 15+, rank 79 of 122. Adults with an account at a bank or mobile money provider.
A condition, not scored: holding an account is the precondition for almost any economic action, not the action (D122). Global Findex, published every three years.
Credit to the private sectorWorld Bank (FS.AST.PRVT.GD.ZS), 2025
90.5 % of GDP, rank 22 of 124. Domestic credit provided to the private sector by financial corporations.
A condition, not scored: financial depth is a stock of money available to actors, not what they do with it (D122). High values can also signal a credit bubble, so more is not always better.
Coordination
How effectively can independent actors organize around shared objectives?
No trend is shown because too few indicators have values at both ends. The rows below still show the available history.
Government effectiveness
perception proxyretired, see notes- Raw value
- no dataz-score -2.5 to 2.5
- Year
- no data
- Normalized
- no data
- Source
- World Bank (GOV_WGI_GE.EST)
- History
- no data
Note: Retired 2026-08-26. The WGI aggregate the opinions of experts and firms, and in this set the four WGI series correlate with each other between 0.93 and 0.98 while correlating with log GDP per capita at 0.91. That is one perception of national wealth counted in three dimensions. Cross-agency delivery records are the replacement and they are a declared gap. See D23 and A4.
Regulatory quality
perception proxyretired, see notes- Raw value
- no dataz-score -2.5 to 2.5
- Year
- no data
- Normalized
- no data
- Source
- World Bank (GOV_WGI_RQ.EST)
- History
- no data
Note: Retired 2026-08-26. Same measurement as government effectiveness, filed under a different name, correlating with it above 0.93. See D23 and A4.
Logistics performance
perception proxyretired, see notes- Raw value
- no dataindex 1-5
- Year
- no data
- Normalized
- no data
- Source
- World Bank (LP.LPI.OVRL.XQ)
- History
- no data
Note: Retired 2026-08-26. The LPI is a survey of international freight forwarders, so it records how a country looks to global logistics firms. A small country with a small port scores low whatever its state can organise, which is artefact A9. Container throughput and border time are observable and stay. See D23.
- Raw value
- 11hours
- Year
- 2019. The rail runs from 1960 to 2026.
- Normalized
- Source
- World Bank (TRD.ACRS.BRDR.EXPT.BRDR.COMP.HR.DB1619)
- History
- Raw value
- 77.652percentage points from approved budget
- Year
- 2024. The rail runs from 1960 to 2026.
- Normalized
- Source
- World Bank (GF.XPD.BUDG.ZS)
- History
University-industry collaboration
direct capability measureno dataset exists- Raw value
- no dataindex 0-100
- Year
- no data
- Normalized
- no data
- Source
- Global Innovation Index
- History
- no data
Note: GII carries it, but the underlying item is a WEF executive opinion survey whose microdata is not inspectable. Excluded on principle 4.
- Raw value
- 0.858index 0-1
- Year
- 2025. The rail runs from 1960 to 2026.
- Normalized
- Source
- V-Dem (v2x_cspart)
- History
- one year
Public-private collaboration
direct capability measureno dataset exists- Raw value
- no dataindex 0-100
- Year
- no data
- Normalized
- no data
- Source
- none
- History
- no data
Note: No comparable dataset. PPP investment databases measure infrastructure finance, not collaboration capacity.
Behavioral check, not scored
Each number below is published beside the score and stays out of it. It is not in the frame, the average, the indicator count or the confidence.
Customs clearance time for exportsWorld Bank (IC.CUS.DURS.EX), 2023
2.903 days, lower is better. Average number of days to clear direct exports through customs, as reported by manufacturing firms that export directly, in the World Bank Enterprise Surveys.
Days a manufacturer that exports directly says its goods took to clear customs, from the World Bank Enterprise Surveys. It is the time the border took on firms' own shipments, current where the Doing Business border time this capability scores is frozen at 2019. It is not scored for two reasons. The number of firms behind each country's figure is published only in the survey microdata, and on a proxy from the published tables 37 of the 53 countries in the frame when it was checked clear 30 exporting firms; Mexico, the Philippines, Israel and nine others may not. And the question changed: surveys fielded from 2024 also ask how long release took across all border agencies, and drop an answer where customs alone took longer, so a country surveyed on both sides of the change can move severalfold with nothing at its border changing. India reads 17.3 days in 2022 and 2.5 in 2025, on more than 9,000 firms each time. No country in the frame has two surveys on the new questionnaire yet. Income is not why it is left out: it barely tracks log GDP per capita.
Trust
How much cooperation is possible beyond immediate personal networks?
No trend is shown because too few indicators have values at both ends. The rows below still show the available history.
Rule of law
perception proxyretired, see notes- Raw value
- no dataz-score -2.5 to 2.5
- Year
- no data
- Normalized
- no data
- Source
- World Bank (GOV_WGI_RL.EST)
- History
- no data
Note: Retired 2026-08-26. A WGI perception composite correlating with control of corruption above 0.95 and with log GDP per capita at 0.83. Court throughput and case clearance rates are the observable replacement and are a declared gap. See D23 and A4.
Control of corruption
perception proxyretired, see notes- Raw value
- no dataz-score -2.5 to 2.5
- Year
- no data
- Normalized
- no data
- Source
- World Bank (GOV_WGI_CC.EST)
- History
- no data
Note: Retired 2026-08-26. A WGI perception composite. It measures reputation for corruption, which is not the same thing as corruption, and it tracks income closely. Prosecution and audit records are the observable replacement and are a declared gap. See D23 and A4.
- Raw value
- 910days
- Year
- 2019. The rail runs from 1960 to 2026.
- Normalized
- Source
- World Bank (ENF.CONT.DURS.DY)
- History
- Raw value
- 6.168% of firms
- Year
- 2023. The rail runs from 1960 to 2026.
- Normalized
- Source
- World Bank (IC.FRM.BRIB.ZS)
- History
- Raw value
- 2.645scale 0-4 (never to always)
- Year
- 2025. The rail runs from 1960 to 2026.
- Normalized
- Source
- V-Dem (v2jucomp_osp)
- History
- one year
Intentional homicide rate
downstream outcomeretired, see notes- Raw value
- no dataper 100,000 people
- Year
- no data
- Normalized
- no data
- Source
- World Bank (VC.IHR.PSRC.P5)
- History
- no data
Note: Added 2026-08-26 by D23 as the observable replacement for two retired WGI perception composites, and retired 2026-08-27 by D44 when the diagnostic built in D42 measured what it was doing. It raised this dimension's correlation with log GDP per capita by 0.288, from 0.096 to 0.385, the largest single wealth contribution anywhere in the model. It was added to fix wealth contamination and it was the wealth contamination. The dataset is sound and the objection is to what it measures here: homicide is driven heavily by organised crime, a society can be physically safe while trusting very little, and across this country set the variation it carries is mostly income. Behavioural trust measures remain a gap.
Generalised interpersonal trust
perception proxymissing- Raw value
- no data% agreeing
- Year
- no data
- Normalized
- no data
- Source
- Joint EVS/WVS (A165)
- History
- no data
Note: Share answering that most people can be trusted in the official Joint EVS/WVS 2017-2022 results table, release 5.0.0. The adapter uses the publisher-weighted country results, emits only countries with one survey row, and holds countries with separate EVS and WVS samples until the respondent-level weights can be pooled reproducibly. See D57 and D64.
Trust in public institutions
perception proxyno dataset exists- Raw value
- no data% expressing confidence
- Year
- no data
- Normalized
- no data
- Source
- OECD Trust Survey / WVS
- History
- no data
Note: The OECD survey covers members only. Mixing it with WVS items for India and South Africa would break comparability. The Joint EVS/WVS confidence battery (E069) reaches 37 countries from one release, and confidence in the courts (E069_17) is published beside Trust as a check under this id rather than scored: every item of the battery tested (courts, civil service, police, parliament and government) reads higher in the closed and electoral autocracies of the frame than in its democracies, which is deference as much as confidence (A13). The gap stays open for a measure that does not reward a court that cannot rule against the state. See D132.
Cooperation beyond the in-group
perception proxymissing- Raw value
- no data% expressing trust
- Year
- no data
- Normalized
- no data
- Source
- Joint EVS/WVS (G007_34_B)
- History
- no data
Note: The distinction that makes this dimension worth measuring: whether trust reaches a person with no tie to the respondent. Generalised trust asks about "most people", which a respondent can fill with their own circle; this item names the stranger. China is the clearest case, high on most people and low on a person met for the first time. The value is the publisher-weighted share answering trust completely plus the share answering trust somewhat, the one sum of two printed columns the adapter stores, exact to about 0.1, over all respondents including don't know and no answer. EVS and WVS ask the same question on the same four-point scale; where one country has both samples, the WVS share is a median 2.2 points higher. Trust in people of another nationality (G007_36_B), which the row once also named, is left out because it reads attitudes to foreigners as much as trust. Fieldwork runs from 2017 to 2023 and every value carries the release year 2022. Germany, the United Kingdom and the Netherlands are held, as for interpersonal trust. See D140.
Court case clearance rate
downstream outcomeno dataset exists- Raw value
- no data% of incoming cases
- Year
- no data
- Normalized
- no data
- Source
- CEPEJ / OECD / national court statistics
- History
- no data
Note: Whether a court finishes what it starts, counted from case records rather than asked in a survey. D23 named it as the observable replacement for the two retired WGI composites and it has stayed unfilled since. CEPEJ publishes it for Council of Europe members and OECD for its own members, so no single publisher reaches this country set, and a harmonised series needs the project second source adapter. See D57.
Panel estimate, round 2, how this layer works
- 44.0 institutionalist@claude-opus-5-5, self-confidence 0.35
I move up four points: the community forest user groups are legally recognised bodies, numbering in the thousands and lasting three decades, which is cooperation beyond kin carried by institutions. Slow contract enforcement, politicised judicial appointment and the 2025 uprising against elite corruption keep me well below the indicator score.
- 47.0 bottom_up@claude-opus-5-5, self-confidence 0.35
A and C convincingly argue the 2025 uprising signals deep distrust of the political class, so I come down three points; forest user groups, guthi and savings cooperatives still carry cooperation beyond kin, which keeps me above A.
- 44.0 wealth_sceptic@claude-sonnet-5-5, self-confidence 0.30
Low firm bribery sits oddly with procurement corruption reports and slow contract enforcement, and the 2025 uprising shows low trust in elites. Community forest user groups and guthi are real beyond-kin cooperation, so I stay between panelists A and B.
Learning
How effectively does the country acquire, distribute, and update knowledge?
No trend is shown because too few indicators have values at both ends. The rows below still show the available history.
- Raw value
- 0.505index 0-1
- Year
- 2020. The rail runs from 1960 to 2026.
- Normalized
- Source
- World Bank (HD.HCI.OVRL)
- History
- Raw value
- 14.052% of firms
- Year
- 2023. The rail runs from 1960 to 2026.
- Normalized
- Source
- World Bank (IC.FRM.TRNG.ZS)
- History
Adult learning participation
direct capability measureno dataset exists, 1 record- Raw value
- no data% of adults
- Year
- no data
- Normalized
- no data
- Source
- Eurostat / OECD PIAAC
- History
- no data
Note: The best available measure of continuous learning capacity, and it exists only for European and OECD members.
- Raw value
- 0.683ratio to world average
- Year
- 2021. The rail runs from 1960 to 2026.
- Normalized
- Source
- OpenAlex (citation_normalized_percentile.is_in_top_10_percent)
- History
- one year
Conditions, not scored
What the country has to work with on this capability. The values are shown as the source published them and are not part of the score, the confidence or the trend. The rank counts the countries with a value, best first.
Tertiary enrolmentWorld Bank (SE.TER.ENRR), 2024
21.3 % gross, rank 94 of 124. Gross enrolment ratio in tertiary education.
A condition, not scored: enrolment counts people in formal education and records nothing learned (D122).
Public education expenditureWorld Bank (SE.XPD.TOTL.GD.ZS), 2024
3.7 % of GDP, rank 76 of 125. Government expenditure on education as a share of GDP.
A condition, not scored: public spending on education is a pure input, and learning is what the dimension asks about (D122).
Vocational share of secondaryWorld Bank (SE.SEC.ENRL.VO.ZS), 2019
1.2 % of secondary, rank 114 of 125. Vocational pupils as a share of total secondary enrolment.
A condition, not scored: the share of secondary pupils on a vocational track describes how a school system is built, not what anyone learns in it, and higher is not unambiguously better (D141). It marks a route into skilled work that does not run through university. Learning reads research citation impact, firm training and the human capital index instead.
Evidence for missing indicators
Each record describes a case the indicators above cannot see. It does not affect the score or confidence because one case is not comparable across countries. A gap can become an indicator when a comparable series covers at least two countries.
Enhanced Vocational Education and Training (EVENT II) short-term training
Nepal's Ministry of Education, Science and Technology, through the EVENT II project secretariat, put 111,062 people aged 16 to 40 through market-relevant short-term vocational training between 2018 and 2023, delivered by 142 private and public training providers in 68 of the 77 districts and paid partly on trainees' employment six months after completion.
111,062 trainees, youth (16 to 40) who enrolled in and completed project-supported short-term training, 2018-02/2023-07 (project period). 23,735 trainees, of which trained with vouchers redeemed at a provider of their choice, 2018-02/2023-07. World Bank, Implementation Completion and Results Report, Nepal Second Enhanced Vocational Education and Training Project (EVENT II), 26 February 2024, retrieved 2026-10-02.
How it worked: The education ministry bought short courses from accredited private and public providers and paid them per trainee, with part of the payment withheld until the trainee was verified as employed six months later, and paid more for women, disadvantaged youth and the poorest districts.
Limits: The figure is in a PDF completion report written by the World Bank about its own project, from data supplied by the ministry's project secretariat and checked by a joint monitoring team of local education officers, CTEVT, the ministry and SDC-Helvetas, which is not fully independent of the delivery; the Bank rated its own outcome. It counts trainees over a five-year project, not participation in the last 12 months, and amounts to roughly 22,000 a year against a labour force in the millions. The project defined youth as 16 to 40, so the count mixes recent school leavers with older adults and gives no age split. The total was 96.5 percent of a 115,000 target and training stopped for about 18 months during the pandemic. The training was financed by IDA credit, not the national budget, and the report does not say whether the government continued the results-based short-term training after the July 2023 closing, so 'concluded' describes the project window, not a measured end of the model. Employment rates of 70 to 83 percent six months after training are from the project's own tracer verification.
Experimentation
How easily can new approaches be attempted, tested, abandoned, and improved?
No trend is shown because too few indicators have values at both ends. The rows below still show the available history.
- Raw value
- 20per million people
- Year
- 2017. The rail runs from 1960 to 2026.
- Normalized
- Source
- World Bank (IP.PAT.RESD)
- History
- Raw value
- 4005per million people
- Year
- 2017. The rail runs from 1960 to 2026.
- Normalized
- Source
- World Bank (IP.TMK.RSCT)
- History
- Raw value
- 15per million people
- Year
- 2017. The rail runs from 1960 to 2026.
- Normalized
- Source
- World Bank (IP.IDS.RSCT)
- History
- Raw value
- 306434per million people
- Year
- 2026. The rail runs from 1960 to 2026.
- Normalized
- Source
- GitHub Innovation Graph (data/repositories.csv)
- History
- no data
Venture deals
direct capability measureno dataset exists- Raw value
- no dataper million people
- Year
- no data
- Normalized
- no data
- Source
- OECD / national VC associations
- History
- no data
Note: Redefined 2026-10-02 (D152). The id keeps its first name so evidence records, links and published files still resolve. The row asked for venture capital deployed as a share of GDP, a level of financial depth of the kind private credit is (D122). A count of first rounds counts attempts started with outside risk money, which is what this capability asks about, and a large round counts once. Candidates, none wireable: the OECD SME and Entrepreneurship Financing scoreboard carried venture capital for 6 of the 16 countries the frame held on 2026-08-26, as amounts in national currency, latest year 2022, with Brazil, India, South Africa and Singapore absent (D21); national venture capital associations publish counts on their own definitions; commercial deal databases cover the world and are not inspectable (D10). Wireable on an inspectable deal count with one definition of a first round for half the frame or more. Read A1 before treating this dimension as measured.
Early-stage entrepreneurial activity
direct capability measuremissing- Raw value
- no data% aged 18-64
- Year
- no data
- Normalized
- no data
- Source
- Global Entrepreneurship Monitor (APS key indicators, TEA rate)
- History
- no data
Note: From the GEM Adult Population Survey, entered by hand because GEM has no open API. TEA counts every new business, so necessity self-employment scores the same as a funded startup, which is why Chile and Argentina sit above the United States here. Read it as how many people are trying, not as how much value the attempts create. GEM does not run every economy every year: Singapore last took part in 2014 and the recency term marks that value down hard.
Tolerance of entrepreneurial failure
perception proxymissing- Raw value
- no data% not deterred
- Year
- no data
- Normalized
- no data
- Source
- Global Entrepreneurship Monitor (APS key indicators, fear of failure rate)
- History
- no data
Note: Stored as 100 minus the published GEM fear of failure rate, so the direction matches the rest of the registry. GEM measures that rate among adults who already see good opportunities, not among all adults, so the denominator differs from the label. Attitudinal: bankruptcy law and time to discharge would be the observable substitute and are still worth wiring beside it.
Firms through regulatory sandboxes
direct capability measureno dataset exists- Raw value
- no datafirms per million people
- Year
- no data
- Normalized
- no data
- Source
- national regulators
- History
- no data
Note: Redefined 2026-10-02 (D152). The row asked for the number and breadth of live sandboxes, which is a policy stock: a regime can exist with nobody in it. It now counts what passes through: firms a regulator let test under relaxed rules, and firms that came out, authorised, withdrawn or failed. Regulators publish cohort lists and exit reports one by one. The evidence corpus holds 22 records against this row, most of them counts of firms admitted or exited, each on the definition and window of its own regulator, and no register assembles them on one definition (O1 triage sweep, 2026-10-01). A realistic candidate for Envisioning to build from those lists. Wireable on a register that counts admissions and completions on one definition for half the frame or more.
University spinouts
direct capability measureno dataset exists- Raw value
- no dataper million people
- Year
- no data
- Normalized
- no data
- Source
- national TTO associations
- History
- no data
Note: Reported nationally with incompatible definitions of what counts as a spinout.
Business share of R&D
capability inputretired, see notes- Raw value
- no data% of R&D
- Year
- no data
- Normalized
- no data
- Source
- OECD MSTI / RICYT
- History
- no data
Note: Retired 2026-10-02. The only working source, OECD MSTI joined with RICYT for Latin America, covers 34 of the 53 countries then in the frame, but the row reads the make-up of a spending stock: who performs the R&D a country pays for. R&D spending itself is a condition since D122, and the share is high both where business research is large (Israel) and where total research is tiny and one firm dominates it (Thailand). State enterprises count as business, so China and Vietnam read their ownership model. UIS stopped publishing the series in 2023. Firms trying new things are read through patents, trademarks, designs and entrepreneurship instead. See D142.
Panel estimate, round 2, how this layer works
- 11.0 institutionalist@claude-opus-5-5, self-confidence 0.35
I move up three points: licensed mobile wallets scaled quickly under Nepal Rastra Bank rules, which shows a regulatory channel that let new approaches in. Panelist B's remittance microenterprise and community hydropower are real, but stale IP data, weak insolvency law and emigration as the main outlet keep me low.
- 24.0 bottom_up@claude-opus-5-5, self-confidence 0.30
A and C note weak testing and exit institutions and emigration as the main outlet, which costs four points; I stay well above them because a repository count high for the income level, eSewa and Khalti scaling, community hydropower and remittance microenterprise are trial the stale filings cannot see.
- 12.0 wealth_sceptic@claude-sonnet-5-5, self-confidence 0.30
IP filings are near zero and dated 2017. The repository count and mobile wallets are real trial, but labour emigration is the dominant adaptive outlet and institutions for testing and exit are weak, so I move up two points, well short of panelist B's 28.
Adaptability
How effectively can the system respond when circumstances change?
No trend is shown because too few indicators have values at both ends. The rows below still show the available history.
- Raw value
- 10.465% of labour force
- Year
- 2025. The rail runs from 1960 to 2026.
- Normalized
- Source
- World Bank (SL.UEM.TOTL.ZS)
- History
- Raw value
- 29.6% of unemployed
- Year
- 2017. The rail runs from 1960 to 2026.
- Normalized
- Source
- ILOSTAT (DF_UNE_TUNE_SEX_AGE_DUR_NB)
- History
- one year
- Raw value
- 0.194index 0-1, lower = more diversified
- Year
- 2025. The rail runs from 1960 to 2026.
- Normalized
- Source
- UNCTAD (US.ConcentDiversIndices)
- History
- one year
- Raw value
- 1.78% of products not exported competitively at the start
- Year
- 2024. The rail runs from 1960 to 2026.
- Normalized
- Source
- Harvard Growth Lab (hs92_country_product_year_4.csv (doi:10.7910/DVN/T4CHWJ))
- History
- one year
Disaster preparedness and recovery
direct capability measureno dataset exists, 1 record- Raw value
- no dataindex 0-100
- Year
- no data
- Normalized
- no data
- Source
- INFORM / UNDRR
- History
- no data
Note: No source observes a country preparing for or recovering from a real shock. INFORM publishes its lack of coping capacity apart from hazard and exposure, but that dimension averages government self-assessments and governance perception indices with stocks such as roads, phones and physicians, which is the perception layer D23 retired plus conditions money buys (D122). Sendai and WHO reporting are governments grading themselves. A warning-reach survey item is a check candidate. See the disaster preparedness memo.
Institutional responsiveness
direct capability measureno dataset exists, 1 record- Raw value
- no dataindex 0-100
- Year
- no data
- Normalized
- no data
- Source
- none
- History
- no data
Note: No dataset exists. Measurable in principle from legislative and regulatory timestamps, which no one has assembled comparably.
Conditions, not scored
What the country has to work with on this capability. The values are shown as the source published them and are not part of the score, the confidence or the trend. The rank counts the countries with a value, best first.
Labour force participationWorld Bank (SL.TLF.ACTI.ZS), 2025
41.9 % aged 15+, rank 123 of 125. Share of the working-age population in the labour force.
A condition, not scored: how much of the population is in the labor force at all is what a country has to reallocate, a level set by norms, schooling and age, not a record of it reallocating (D141). Participation norms confound it, especially for India. Adaptability reads reallocation through long-term unemployment and export diversification instead.
Fixed broadband subscriptionsWorld Bank (IT.NET.BBND.P2), 2024
10.1 per 100 people, rank 79 of 125. Fixed broadband subscriptions per 100 people.
A condition, not scored: installed infrastructure is what a country has to change with, not a record of it changing (D122). Penalizes mobile-first countries such as India and South Africa.
Electricity transmission lossesWorld Bank (EG.ELC.LOSS.ZS), 2023
14.4 % of output, rank 88 of 117. Power lost in transmission and distribution, including unbilled use.
A condition, not scored: the state of the grid, and whether its operator can bill what it delivers, is infrastructure a country has to change with, not a record of it changing (D141). Read it beside broadband, the other installed network beside Adaptability.
Informal employmentILOSTAT (DF_SDG_0831_SEX_ECO_RT), 2017
81.5 % of employment, rank 73 of 102. Informal employment as a share of total employment, SDG indicator 8.3.1.
A condition, not scored: how much work carries no contract, registration or social protection describes the labor market a country reallocates through, not it reallocating (D150). Read it beside the unemployment rate: where most work is informal, a person who loses a job takes any work within weeks, so a low rate is not a fluid market. Its direction for Adaptability cannot be defended, since informal work is both the slack that absorbs a shock and the precarity that keeps a worker from moving up, so the rank orders values and is not a verdict. Comparability is weak: the European values come from an income survey (EU-SILC) with a proxy definition, and the rest from labor force or household surveys processed by the ILO. ILOSTAT has no value for the United States, Canada, Australia, Japan, Singapore, Israel, Malaysia, China, the Philippines or Cuba, and some values are old (Haiti and Nicaragua 2012).
Evidence for missing indicators
Each record describes a case the indicators above cannot see. It does not affect the score or confidence because one case is not comparable across countries. A gap can become an indicator when a comparable series covers at least two countries.
Earthquake housing reconstruction programme (National Reconstruction Authority)
After the April 2015 Gorkha earthquake, Nepal's National Reconstruction Authority ran an owner-driven housing grant programme that, by 23 September 2021, had paid the third and final tranche of the reconstruction grant to 704,341 of 866,207 eligible households across 32 districts, with the World Bank-financed share revised to 309,335 houses.
704,341 households, eligible beneficiary households that had received the third tranche of the housing reconstruction grant, 2021-09-23. 309,335 houses, houses whose safer reconstruction was supported by the ida-financed earthquake housing reconstruction project, final revised count, 2023-05. World Bank, Implementation Status and Results Report, Earthquake Housing Reconstruction Project (P155969), Sequence No. 13, retrieved 2026-10-02.
How it worked: Parliament created a time-limited National Reconstruction Authority that enrolled every damaged household, paid a flat grant in three tranches, and released each tranche only after engineers verified that the house met a seismic building code, so the payment schedule enforced the standard.
Limits: A grant tranche is a payment, not a finished house: in the programme's rules the third tranche is released on completion of construction up to the roof band, so 704,341 counts households verified to that stage, not occupied, completed homes. The figures are reported by the government agencies to the lender and published by the lender, which financed about $700 million of the programme and rates its own operation; the 309,335 count was itself revised in 2023 after the project clarified that its reported total had included 3,766 houses financed by a trust fund grant (TF0A4783). About 162,000 eligible households had not received the final tranche at the reporting date, and the World Bank's ICR for the MDTF Funding for Earthquake Housing Reconstruction project (P162067, TF0A4783) notes the average rebuilding cost was about three times the NPR 300,000 grant, and one third of households used loans to close the gap. The number shows recovery after one shock; it says nothing about preparedness before the next one, and the NRA was a temporary body dissolved in December 2021, with its residual work passed to the National Disaster Risk Reduction and Management Authority. The record documents the national programme's scale through a single donor's monitoring report; there is no independent national statistical series behind it.
Nepal Rastra Bank COVID-19 refinance and loan relief
Nepal Rastra Bank's monetary policy of 17 July 2020 expanded its subsidised refinance facility to five times the available fund for COVID-19 affected businesses, and by mid-July 2021 Rs 148.75 billion had been approved to 48,890 borrowers, against Rs 7.49 billion of refinance outstanding a year earlier.
148.75 billion Nepalese rupees (48,890 borrowers), covid-19 refinance approved, cumulative, 2021-07. 7.49 billion Nepalese rupees, refinance outstanding before the expansion, 2020-07. Nepal Rastra Bank, Monetary Policy for 2021/22 (unofficial English translation, August 2021), paragraph 54, retrieved 2026-10-02.
How it worked: The central bank turned an existing subsidised refinance window into a pandemic credit programme by multiplying its size, setting sector rates (1 percent special, 2 percent small business, 3 percent general) and letting commercial banks, development banks, finance companies and microfinance institutions on-lend it.
Limits: The URL serves a PDF, which NRB labels an unofficial translation; the 7.49 billion baseline is in the Monetary Policy for 2020/21 (https://www.nrb.org.np/ofg/monetary-policy-2020-21-full-text-english-version/, paragraph 48) and the expansion in paragraphs 100 to 103 of the same document. The central bank reports on its own scheme. 'Approved' is not disbursed, and the two figures are different measures (an annual stock against a cumulative approval), so the comparison shows scale, not a like-for-like increase. The rule changed about four months after the March 2020 lockdown, at the regular annual monetary policy rather than in an emergency statement, so the speed is moderate. Uptake was uneven: under the same document the business continuity loan for tourism and small firms to pay wages reached only Rs 956.7 million, and 30 percent of refinance could go through customer evaluation or microfinance lump sums that the source does not break down. Refinance at 1 to 3 percent with borrowers paying 3 to 5 percent went to borrowers banks chose, and the document gives no count of first-time or small borrowers. Other relief in the same section (repayment extensions for Rs 93.63 billion of loans, restructuring of Rs 129.21 billion) is not added here.
Building
How capable is the country of turning plans and knowledge into functioning systems?
0.0 over 10 years, from 4.3 in 2016 to 4.3 on 3 indicators seen in both years.
Trends use fewer indicators than the current score and use today's frame. A longer span reaches further back.
- Raw value
- 4.982% of GDP
- Year
- 2025. The rail runs from 1960 to 2026.
- Normalized
- Source
- World Bank (NV.IND.MANF.ZS)
- History
- Raw value
- 0.618% of manufactured exports
- Year
- 2022. The rail runs from 1960 to 2026.
- Normalized
- Source
- World Bank (TX.VAL.TECH.MF.ZS)
- History
Logistics infrastructure quality
perception proxyretired, see notes- Raw value
- no dataindex 1-5
- Year
- no data
- Normalized
- no data
- Source
- World Bank (LP.LPI.INFR.XQ)
- History
- no data
Note: Retired 2026-08-26. An LPI sub-index, so the same freight-forwarder survey as logistics performance and the same problem. Electricity connection speed stays as the observable infrastructure measure in this dimension. See D23.
- Raw value
- 86.522score 0-100
- Year
- 2019. The rail runs from 1960 to 2026.
- Normalized
- Source
- World Bank (IC.ELC.TIME.DFRN)
- History
- Raw value
- 0.039index
- Year
- 2024. The rail runs from 1960 to 2026.
- Normalized
- Source
- World Bank (EF.EFM.UNIV.XD)
- History
Large project delivery
direct capability measureno dataset exists, 1 record- Raw value
- no data% overrun
- Year
- no data
- Normalized
- no data
- Source
- none
- History
- no data
Note: The single best measure of execution capability and there is no comparable international dataset. Assembling one is a defensible Envisioning project. Building mixes industrial output with state delivery capacity, and this indicator carries the delivery side: the other six indicators cannot see a national programme that was delivered. Documented deliveries are recorded in data/evidence and never scored, see D20.
Firm scale-up rate
direct capability measureno dataset exists- Raw value
- no data% of firms
- Year
- no data
- Normalized
- no data
- Source
- OECD DynEmp
- History
- no data
Note: OECD business dynamics work covers members irregularly. Nothing comparable for India, Brazil or South Africa.
Conditions, not scored
What the country has to work with on this capability. The values are shown as the source published them and are not part of the score, the confidence or the trend. The rank counts the countries with a value, best first.
Output per workerWorld Bank (SL.GDP.PCAP.EM.KD), 2025
20,874 constant 2021 PPP $, rank 91 of 123. GDP per person employed, constant purchasing power parity.
A condition, not scored: output per worker is income per worker, the wealth the benchmark tests capability against, so it is published beside Building as context (D122).
Evidence for missing indicators
Each record describes a case the indicators above cannot see. It does not affect the score or confidence because one case is not comparable across countries. A gap can become an indicator when a comparable series covers at least two countries.
Melamchi Water Supply Project, and its erosion after the 2021 flood
Nepal's government built the Melamchi River diversion tunnel and headworks to pipe an additional 170 million litres a day into the Kathmandu Valley, closing the project in June 2021, more than 14 years after its original March 2007 closing date; the 2021 flood then damaged the headworks, and water has since been diverted for about eight months a year.
14 years, delay of project closing beyond the originally planned closing date (march 2007 planned, june 2021 actual), 2021-06. 8 months per year, months per year melamchi water could be diverted after the 2021 flood damaged the headworks, 2025-08. Asian Development Bank, Independent Evaluation Department, Validation Report PVR-1165 (Melamchi Water Supply Project and Kathmandu Valley Water Services Sector Development Program), retrieved 2026-10-02.
How it worked: The Ministry of Physical Planning and Works and later the Ministry of Water Supply, with ADB as lead financier, tied a trans-basin water diversion to a reform of Kathmandu's water utility in a single loan. The infrastructure was delivered and the institutional reforms largely were not.
Limits: The 14 years is the gap between two loan closing dates, which is a lender's administrative milestone, not a measured completion date for the tunnel; the source gives no physical completion schedule against a baseline. The cost figure is not usable as an overrun: appraisal was $464 million and completion $345.3 million, but the 2008 scope change and the exit of the World Bank, NORAD and Sida mean the two totals price different projects, and ADB says separately that a 2014 additional loan covered tunnel cost overruns without stating the overrun in percent. The erosion is stated in words and one current number: the source publishes no figure for the year-round flow before the 2021 flood, so the secondMetric holds the post-flood level, not a measured peak. The flood is an exogenous shock, though ADB attributes the vulnerability to design that did not fit the terrain. The validation rests on the project completion report written by the lender and the executing agency, and ADB was itself a party to the project's design. The delay mixes national causes (slow decisions, leadership turnover, poor contractor management) with contractor failure, the cancelled and re-bid contracts of nonperforming contractors.