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Edukrish

Method

How we project a career, and what we won't do.

A student in Class 8 won't start work for years. So we start from the year they could realistically begin, use official pay data, project it forward with stated assumptions, and show how uncertain that is. When the data isn't good enough, we say so instead of guessing.

In short

  1. We start from the year your child could realistically begin work, from their class and the usual route.
  2. We use official pay data only. Today that means Indian government pay scales and US national data.
  3. We project pay forward with stated assumptions, shown in today's money by default, with a range.
  4. Where we don't have trustworthy data, we show no number at all.
  5. These are scenarios, not promises. Projections for India haven't been tested against history yet.

1. When you could start working

The Indian school year runs April to March, so October 2026 is in the 2026–27 session. A student in Class N finishes Class 12 in the spring of 2027 + (12 − N), with results around May. Each route then adds its stages at their usual intake months: most degrees start in August, MBBS in mid-September, master's courses around July. Compulsory internships, articleship, academy training or flying hours are counted where they apply.

Example: on a four-year B.Tech, a Class 8 student today could start work around 2035 and a Class 12 student around 2031. Preparation years, a master's, a repeated year or extra exam attempts move the date, and you can change each of these.

Route durations follow the regulators (NMC, VCI, INC, NCAHP, PCI, CoA, BCI, ICAI, DGCA, UPSC, NCTE, UGC).

2. Where pay figures come from

We only use data we're allowed to use commercially, and we never scrape sites that forbid it. Today that means official US pay data (the Bureau of Labor Statistics' 2025 occupational wage estimates) and official Indian government pay scales (the 7th Pay Commission pay matrix). For private-sector jobs in India there is no public, reusable source of pay by occupation: the national survey's person-level data needs a commercial licence from the statistics ministry, and salary websites prohibit reuse. Until we license better data, those careers show “no reliable pay data yet” rather than a made-up number.

3. How future pay is projected

Every projected figure is built from three visible parts:

  1. Today's pay at your career stage. Official data mixes all experience levels, so a typical person is placed in the lower part of today's range when they start (10th–25th percentile) and moves towards the middle over about 15 years. A high earner reaches the top 10%. These are stated assumptions, not observations, and many people stay specialists.
  2. Real pay growth, in three scenarios. US: 0.53%, 1.13% and 1.73% a year, from the US Social Security Trustees' official long-range assumptions. Indian government pay: 0.0%, 1.3% and 2.0%, where the base case repeats the 7th Pay Commission's real rise spread over ten years.
  3. Prices. US 2.4% a year (Trustees' intermediate assumption); India 4.0% (the Reserve Bank of India's target).

Future money and today's value. A salary in 2035 is shown in the money of that year. “Today's value” divides it by the expected rise in prices, so you can compare it with what money buys now. A bigger number later is not automatically a better life.

No hidden tilts. We don't push the central estimate up or down for AI or job demand, because we haven't shown that doing so improves accuracy. We show demand and AI exposure as separate evidence instead.

4. How sure we are

Every projection has a shaded range that widens with time: ±3.79% per square-root year for US figures. It covers one thing only: overall pay growing faster or slower than our rates. It does not cover the much bigger differences between people in the same job, which we show separately from today's published pay range.

We checked the growth rates against real US wage history: 12 Bureau of Labor Statistics series of average hourly earnings (all private-sector workers and 11 industry groups, data from 1964 to 2025). From every year between 1984 and 2024, we projected each series forward with the same fixed rates and compared the result with what happened. The rates are today's official assumptions, which were set knowing this history, so this is a check of how far constant rates like these can drift, not a clean forecasting record.

Average error of past projections of average pay (all starting years, run 2026-10-17)
Method1 year ahead5 years ahead10 years ahead15 years ahead
Our growth rates (fixed)1.2%4.7%7.3%9.7%
Recent inflation + long-run trend1.1%5.3%7.5%7.1%
Past growth continues1.1%5.0%8.1%9.5%
Inflation only1.2%5.9%8.3%8.0%
  • At 5 and 10 years our fixed rates had the smallest average error, by a small margin (7.3% against 7.5%–8.3% at 10 years). At 15 years they did worst (9.7%). The differences are small, the test periods overlap, and we haven't tested whether they are significant.
  • The range held 89.8% of 5-year and 80.8% of 10-year outcomes. That width was fitted on all of these years, so it is bound to look good on them. The stricter test: a width fitted only on outcomes up to 2004 would have held just 31.8% of 5-year and 39.4% of 10-year outcomes after that, mainly because 2021–23 inflation was unlike the calm years before. Treat the range as a guide that can be too narrow when conditions change.
  • This tests average pay across whole industries. It does not test pay for a single occupation, or our assumption about where a person sits in the pay range at each career stage, and there is no long Indian series to test against. That is why every career projection today is labelled “limited evidence” or “rough projection”.

5. The evidence labels

  • Strong evidence: official data for this exact occupation, no more than two years old, a range checked against history, a career-stage model tested against real pay histories, and a first job within five years from now. No projection meets all of these yet.
  • Limited evidence: any one of those is missing.
  • Rough projection: a first job more than ten years from now. These are scenarios, not forecasts.
  • No reliable pay data yet: no usable data, or no standard occupation matches the career closely enough. No number is shown.

6. Sources and their licences

Terms reviewed 2026-10-17. Only approved sources are ever switched on for automatic updates.

See every source we assessed and its licence
SourceLicenceStatus
Occupational Employment and Wage Statistics (OEWS)U.S. Bureau of Labor StatisticsUS public domainApproved
Employment Projections 2025–35U.S. Bureau of Labor StatisticsUS public domainApproved
Indeed Job Postings IndexIndeed Hiring LabCC BY 4.0Approved
Generative AI and jobs: refined global index of occupational exposureInternational Labour Organization (Working Paper 140, 2025)CC BY 4.0Approved
7th Central Pay Commission pay matrixGovernment of India, Ministry of FinanceOfficial government publication (facts)Approved
Social Security Trustees Report 2025 (economic assumptions)US Social Security AdministrationUS public domainApproved
Flexible inflation target, April 2026 – March 2031Government of India / Reserve Bank of IndiaOfficial government publication (facts)Approved
Average hourly earnings by industry and CPI (back-test data)U.S. Bureau of Labor Statistics, via FRED (Federal Reserve Bank of St. Louis)US public domain (BLS data)Approved
O*NET® 31.0 DatabaseNational Center for O*NET Development (USDOL/ETA)CC BY 4.0Approved
ILOSTAT earnings and labour statisticsInternational Labour OrganizationCC BY 4.0Approved
World Development IndicatorsWorld BankCC BY 4.0Approved
Periodic Labour Force Survey reports and bulletinsMinistry of Statistics and Programme Implementation (MoSPI)Government statistics; aggregates free under GSDD 2026Within limits
PLFS unit-level data (2025 calendar year)MoSPI (microdata.gov.in)GSDD 2026: free for non-commercial use; commercial use needs MoSPI authorisation and a feeNeeds a licence
Adzuna API (salary histograms and history)AdzunaAdzuna terms of serviceNeeds a licence
Payscale / Payfactors market dataPayscaleCommercial licence; data confidential by defaultNeeds a licence
Levels.fyi compensation dataLevels.fyiTerms bar automated access and commercial use without a signed agreementNeeds a licence
Lightcast job postings and salary analyticsLightcastCommercial licenceNeeds a licence
LinkedIn (Talent Insights / Economic Graph)LinkedInUser Agreement prohibits scrapingNeeds a licence
NIRF median salaries of graduatesInstitutions, under the National Institutional Ranking FrameworkNo reuse licence statedNeeds a licence
Salary increase surveys (Aon, Mercer, WTW, Deloitte)Consultancies (press releases)No reuse licence; headline figures may be cited with attributionWithin limits
Future of Jobs Report 2025World Economic ForumCC BY-NC-ND 4.0Needs a licence
GlassdoorGlassdoorTerms prohibit scraping and data miningNot allowed
Naukri.com (and JobSpeak index)Info EdgeTerms prohibit crawling, scraping and commercial reuseNot allowed
AmbitionBoxInfo EdgeTreated as prohibited (sister site bans scraping)Not allowed
Indeed website salary pagesIndeedTerms prohibit scraping and reuseNot allowed
foundit (formerly Monster India)founditPersonal, non-commercial use onlyNot allowed
Talent.com salary pagesTalent.comTerms ban scraping; salary data confidentialNot allowed
Salary.com CompAnalystSalary.comCommercial licenceNeeds a licence

Versions

Forecast engine forecast-1.1, timeline engine timeline-1.1; assumption sets US-2026.10-2 and IN-2026.10-1. Every published projection keeps the versions it was made with, so we can check later how close it came. See also how career matching works.