Cost of Cultivation
This dataset compiles cost statistics for cultivating various crops across the state Himachal Pradesh, detailing expenses from seeds to labor. It's a valuable resource for agriculture research and policymaking, aiding in crop selection, resource allocation, and policy decisions.
Data Dictionary
Column | Type | Label | Description |
---|---|---|---|
id | int4 | index | |
year | text | Year | |
state_name | text | State Name | |
state_code | text | State Code | |
crop_type | text | Crop type | |
crop | text | Crop name | |
crop_code | text | Crop code | |
cultivationcosta1 | numeric | Cultivation Cost A1 | |
cultivationcosta2 | numeric | Cultivation Cost A2 | |
cultivationcostb1 | numeric | Cultivation Cost B1 | |
cultivationcostb2 | numeric | Cultivation Cost B2 | |
cultivationcostc1 | numeric | Cultivation Cost C1 | |
cultivationcostc2 | numeric | Cultivation Cost C2 | |
cultivationcostc2revised | numeric | Cultivation Cost C2 Revised | |
productioncosta1 | numeric | Production Cost A1 | |
productioncosta2 | numeric | Production Cost A2 | |
productioncostb1 | numeric | Production Cost B1 | |
productioncostb2 | numeric | Production Cost B2 | |
productioncostc1 | numeric | Production Cost C1 | |
productioncostc2 | numeric | Production Cost C2 | |
productioncostc2revised | numeric | Production Cost C2 Revised | |
productioncostc3 | numeric | Production Cost C3 | |
mainproductvalue | numeric | Value of Main Product | |
byproductvalue | numeric | Value of By-Product | |
materialinputseed | numeric | Material Input of Seed | |
materialinputfertilizer | numeric | Material Input of Fertilizer | |
materialinputmanure | numeric | Material Input of Manure | |
labourinputhuman | numeric | Labour Input of Human | |
labourinputanimal | numeric | Labout Input of Animal | |
materialinputseedrate | numeric | Rate per Unit of Seed | |
materialinputfertilizerrate | numeric | Rate per Unit of Fertilizer | |
materialinputmanurerate | numeric | Rate per Unit of Manure | |
labourinputhumanrate | numeric | Rate per Unit of Human Labour | |
labourinputanimalrate | numeric | Rate per Unit of Animal Labour | |
implicitrate | numeric | Implicit Rate | |
holdingsnumber | numeric | Number of Holdings in Sample | |
tehsilsnumber | numeric | Number of Tehsils in Sample | |
cropderivedyield | numeric | Derived Yield of Crop | |
humanlabourhoursfamily | numeric | Family Human Labour Hours | |
humanlabourhoursattached | numeric | Attached Human Labour Hours | |
humanlabourhourscasual | numeric | Casual Human Labour Hours | |
humanlabourhourstotal | numeric | Total Human Labour Hours | |
operationalcosthumanlabourfamily | numeric | Operational Cost of Family Human Labour | |
operationalcosthumanlabourattach | numeric | Operational Cost of Attached Human Labour | |
operationalcosthumanlabourcasual | numeric | Operational Cost of Casual Human Labour | |
operationalcosthumanlabourtotal | numeric | Operational Cost of Total Human Labour | |
operationalcostanimallabourhired | numeric | Operational Cost of Hired Animal Labour | |
operationalcostanimallabourowned | numeric | Operational Cost of Owned Animal Labour | |
operationalcostanimallabourtotal | numeric | Operational Cost of Total Animal Labour | |
operationalcostmachlabourhired | numeric | Operational Cost of Hired Machine Labour | |
operationalcostmachlabourownd | numeric | Operational Cost of Owned Machine Labour | |
operationalcostmachlabourtot | numeric | Operational Cost of Total Machine Labour | |
operationalcostseed | numeric | Operational Cost of Seed | |
operationalcostfertilizer | numeric | Operational Cost of Fertilizer | |
operationalcostmanure | numeric | Operational Cost of Manure | |
operationalcostfertilizermanure | numeric | Operational Cost of Fertilizer & Manure | |
operationalcostinsecticides | numeric | Operational Cost of Insecticides | |
operationalcostirrigationcharges | numeric | Operational Cost of Irrigation Charges | |
operationalcostmiscellaneous | numeric | Miscellaneous Operational Cost | |
operationalcostworkingcapitalint | numeric | Operational Cost of Interest on Working Capital | |
operationalcost | numeric | Operational Cost | |
fixedcostownlandrentvalue | numeric | Fixed Cost on Rental Value of Owned Land | |
fixedcostleasedlandrentpaid | numeric | Fixed Cost on Rent Paid for Leased-in-Land | |
fixedcostlandrevenue | numeric | Fixed Cost on Land Revenue, Taxes & Cesses | |
fixedcostdepreciation | numeric | Fixed Cost of Depreciation on Implements & Farm Building | |
fixedcostfixedcapitalinterest | numeric | Fixed Cost of Interest on Fixed Capital | |
fixedcost | numeric | Fixed Cost | |
totalcost | numeric | Total Cost |
Additional Information
Field | Value |
---|---|
Data last updated | June 25, 2024 |
Metadata last updated | June 25, 2024 |
Created | June 25, 2024 |
Format | CSV |
License | Open Data Commons Attribution License |
Additional info | * NA - Data not available^ 0 in (Constant Unit/Changing Unit) cloumns denotes it is constant.^^ 1 in (Constant Unit/Changing Unit) cloumns denotes it is changing respective to the dimension. |
Data extraction page | https://eands.dacnet.nic.in/Cost_of_Cultivation.htm |
Data insights | The dataset provides intriguing insights into the agricultural dynamics of Himachal Pradesh. It highlighting regional disparities and economic trends within the state. Additionally, it distinguishes between cultivation costs and production costs, offering valuable insights for financial planning and efficiency assessments tailored to Himachal Pradesh. By examining variations in labor utilization, the dataset allows for compelling analyses of workforce patterns and their implications for agricultural productivity. This makes it an invaluable resource for understanding and optimizing farming practices in Himachal Pradesh. |
Data last updated | 2015-16 |
Data retreival date | 2023-03-27 00:00:00 |
Datastore active | True |
Frequency | Yearly |
Granularity | State |
Has views | True |
Id | 1f1a5ae3-c750-4f98-b910-c427f8eb4e21 |
Idp ready | True |
Methodology | The methodology used by DES involves collecting data from a sample of farmers in each state, who are selected through a stratified random sampling technique. The sample size is determined based on the number of operational holdings in the state, and the sample is selected from different size classes of holdings to ensure representation of all types of farmers. |
No indicators | 61 |
Package id | 95113323-1036-49ed-97e8-336e9294bb2b |
Position | 0 |
Size | 46.1 KiB |
Sku | moafw-cost_of_cultivation-st-yr-him |
State | active |
States uts no | 1 |
Url type | upload |
Years covered | 1996-2019 |
Methodology | The methodology used by DES involves collecting data from a sample of farmers in each state, who are selected through a stratified random sampling technique. The sample size is determined based on the number of operational holdings in the state, and the sample is selected from different size classes of holdings to ensure representation of all types of farmers. |
Similar Resources | |
Granularity Level | State |
Data Extraction Page | https://eands.dacnet.nic.in/Cost_of_Cultivation.htm |
Data Retreival Date | 2023-03-27 00:00:00 |
Data Last Updated | 2015-16 |
Sku | moafw-cost_of_cultivation-st-yr-him |
Dataset Frequency | Yearly |
Years Covered | 1996-2019 |
No of States/UT(s) | 1 |
No of Districts | |
No of Tehsils/blocks | |
No of Gram Panchayats | |
Additional Information | * NA - Data not available^ 0 in (Constant Unit/Changing Unit) cloumns denotes it is constant.^^ 1 in (Constant Unit/Changing Unit) cloumns denotes it is changing respective to the dimension. |
Number of Indicators | 61 |
Insights from the dataset | The dataset provides intriguing insights into the agricultural dynamics of Himachal Pradesh. It highlighting regional disparities and economic trends within the state. Additionally, it distinguishes between cultivation costs and production costs, offering valuable insights for financial planning and efficiency assessments tailored to Himachal Pradesh. By examining variations in labor utilization, the dataset allows for compelling analyses of workforce patterns and their implications for agricultural productivity. This makes it an invaluable resource for understanding and optimizing farming practices in Himachal Pradesh. |
IDP Ready | Yes |