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Institution
경상북도 상주시
Department
농업정책과

○4월 이상저온피해 중앙지원대상농가 재난복구비

Programme [도]농작물 피해복구비 지원

Amounts and period

Budget amount
515,550,000 KRW
기정액
0 KRW
Change
+515,550,000 KRW

A zero here is what the source recorded. Missing values are never folded into zero.

Changes are calculated only when both amounts are known in full. No percentage is calculated when the comparison amount is zero.

Programme hierarchy and share

The selected item’s share of each parent budget, calculated from amounts in the same source document.

A share is not calculated for missing or partial amounts, non-positive parent amounts, or an item amount greater than its parent.

  1. Department 농업정책과 62,403,813,000 KRW
  2. Policy 친환경 농산물생산 및 소비촉진 37,019,952,000 KRW
  3. Programme 고품질 농산물 생산 8,210,385,000 KRW
  4. Project [도]농작물 피해복구비 지원 515,550,000 KRW
  5. Budget category 이주및재해보상금 515,550,000 KRW
  6. Statistical item 민간인재해및복구활동보상금 515,550,000 KRW
  7. Item ○4월 이상저온피해 중앙지원대상농가 재난복구비 515,550,000 KRW
Category–statistical code
302-02
Group
Not provided in source

Original description

○4월 이상저온피해 중앙지원대상농가 재난복구 비 1,718,500,000원*1식*30%

Institution and programme names are shown as the original Korean source text.

Detailed budget items

1 items
  1. ○4월 이상저온피해 중앙지원대상농가 재난복구비 302-02 Page 3 Selected item 515,550,000 KRW Opens in a new window

Data source

View source document details
Document ID
doc_0g9fa1vd9gg39nptvdh3cmfb26
Source document status
Available
File type
application/pdf
File size
223.714 KiB
Location inside the source
Page 3 Row 10 Line 1 Column level4

Source and reference

FY 2020 release No source record

Fiscal year of record
2020
Fetched from the source
2026-07-29 18:07
Read and interpreted
2026-07-29 18:07
Query snapshot refreshed
2026-11-14 09:03
Item ID
bi_3b5aektp441d1hf4et1b7h6mp0

Similar budgets

Items share the same budget classification and a related name. Different years may be included. The name search uses the keyword without a classification filter.

Keyword “중앙지원대상농가” · classification 302-02

No items with the same classification were found among the candidates checked.

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