Critical Limitations
Please read before using this data for research or journalism.
This page documents what data we DON'T have and the known limitations of what we do have. Radical transparency about limitations is core to our mission. We believe you need this context to use the data responsibly.
Critical Impact
High Impact
Medium Impact
Low Impact
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Critical1. No Jammu vs Kashmir Disaggregation
What: The budget data covers all of J&K UT as a single entity. We cannot separate spending in the Jammu division from spending in the Kashmir division.
Why: The official budget documents are published at the UT level, not region level. The government does not publish region-wise breakdowns in its budget documents.
Impact: You cannot use this data to compare Jammu vs Kashmir allocations or identify regional disparities.
Workaround: District-level data might be available through RTI requests or CAG audit reports, but is not part of this dataset.
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Critical2. No District-Level Data
What: We do not have district-wise spending breakdowns. You cannot see how much was spent in, say, Kupwara vs Jammu district.
Why: Budget documents classify spending by department and programme, not by geography.
Impact: Geographic analysis of spending distribution is not possible with this dataset.
Workaround: Some scheme-level data (like MGNREGA) has district breakdowns available separately from the Planning Department.
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High3. Budget ≠ Actual Spending
What: This dataset primarily contains Budget Estimates (BE) — what the government planned to spend. Actual expenditure can differ significantly.
Why: We have Revised Estimates for most years, but Actuals (from the Annual Accounts) are only partially available in our dataset.
Impact: A department with a large budget allocation may have spent far less (or more). Comparing across years using BE can be misleading.
Workaround: Check the Revised Estimates column where available. For critical analysis, verify against CAG reports or the Finance Accounts.
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High4. No Project Outcomes
What: We show money allocated and spent — but not what was achieved. You cannot see how many schools were built, roads constructed, or beneficiaries reached.
Why: Outcome data is not published in budget documents. It exists in various departmental reports but is not standardised or machine-readable.
Impact: Budget allocations do not tell you whether the money was spent effectively.
Workaround: Combine budget data with annual reports, CAG performance audits, and news coverage for a fuller picture.
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Medium5. No Beneficiary Data
What: We cannot tell you who received the money — which households, villages, or communities benefited from specific programmes.
Why: Beneficiary data is collected at the implementation level, not published in budget documents.
Impact: You cannot use this dataset to study equity or targeting of government programmes.
Workaround: Social audit reports, PFMS data, and scheme-level portals (like MGNREGA MIS) may have beneficiary information.
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Medium6. Pre-2013 Data Not Available
What: Our dataset begins from 2013-14. We do not have budget data for years before this.
Why: Earlier budget documents either don't exist in digital form, are in formats too degraded to extract, or have not yet been processed.
Impact: Long-term trend analysis going back before 2013 is not possible with this dataset.
Workaround: We plan to extend coverage backwards when resources allow. Some data may be available through the Finance Department's own archives.
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Low7. Limited Quarterly/Monthly Breakdown
What: Budget data is annual. We don't have month-by-month or quarter-by-quarter spending data.
Why: Monthly expenditure data is reported internally but not published in the budget documents we process.
Impact: You cannot see seasonal spending patterns or how quickly funds were utilised within a year.
Workaround: Controller of Accounts data might be available through RTI for quarterly breakdowns.
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Medium8. Post-2019 Structural Changes
What: In October 2019, J&K was reorganised into two Union Territories (J&K UT and Ladakh UT). Our data before 2019-20 includes Ladakh, while post-2019 data does not.
Why: This is a fundamental administrative change with no simple adjustment possible.
Impact: Direct year-on-year comparisons before and after 2019 require adjustment for the Ladakh separation. Total budget figures are not directly comparable across this break.
Workaround: When making long-term comparisons, note the 2019 reorganisation. Add a footnote to any analysis crossing this boundary.
Data Quality Issues
For OCR errors, label variations, and extraction accuracy, see the Data Quality page.
View Data Quality →Found a new limitation?
If you discover a limitation we haven't documented, please tell us. We'll add it here.
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Despite these limitations, this dataset is the most comprehensive publicly available source of J&K budget data.
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