<?xml version='1.0' encoding='UTF-8'?>
<codeBook version="1.2.2" ID="PAK_2024_AC_v01_M_v01_A_ESS" xml-lang="en" xmlns="http://www.icpsr.umich.edu/DDI" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.icpsr.umich.edu/DDI http://www.icpsr.umich.edu/DDI/Version1-2-2.xsd">
  <docDscr>
    <citation>
      <titlStmt>
        <titl>
          PAK_2024_AC_v01_M_v01_A_ESS
        </titl>
        <IDNo>
          DDI_PAK_2024_AC_v01_M_v01_A_ESS_FAO
        </IDNo>
      </titlStmt>
      <prodStmt>
        <producer role="Metadata producer">
          Pakistan Bureau of Statistics
        </producer>
        <producer abbr="ESS" affiliation="Food and Agriculture Organization of the United Nations" role="Metadata adapted for FAM">
          Statistics Division
        </producer>
        <software version="4.0.10" date="2018-05-02">
          Nesstar Publisher
        </software>
      </prodStmt>
    </citation>
  </docDscr>
  <stdyDscr>
    <citation>
      <titlStmt>
        <titl>
          Agricultural Census 2024
        </titl>
        <IDNo>
          PAK_2024_AC_v01_M_v01_A_ESS
        </IDNo>
      </titlStmt>
      <rspStmt>
        <AuthEnty>
          Pakistan Bureau of Statistics
        </AuthEnty>
      </rspStmt>
      <prodStmt>
        <producer role="Technical assistance">
          Food and Agriculture Organization of the United Nations
        </producer>
        <software version="4.0.10" date="2018-05-02">
          Nesstar Publisher
        </software>
      </prodStmt>
      <distStmt>
        <contact URI="https://www.pbs.gov.pk/content/agriculture-census" email="naveedeqbal@gmail.com ">
          Pakistan Bureau of Statistics
        </contact>
      </distStmt>
      <serStmt>
        <serName>
          Agricultural Census [ag/census]
        </serName>
        <serInfo>
          Seven agricultural censuses were conducted in Pakistan, the first in 1960, followed by the ones conducted in 1972, 1980, 1990, 2000 and 2010. The most recent agricultural census was conducted in 2024, and it was the first to integrate the domains of agriculture, livestock, and agricultural machinery, previously conducted as separate censuses.
        </serInfo>
      </serStmt>
    </citation>
    <stdyInfo>
      <subject>
        <keyword>
          Structure of Agriculture
        </keyword>
        <keyword>
          Land use
        </keyword>
        <keyword>
          Crops
        </keyword>
        <keyword>
          Livestock and Poultry
        </keyword>
        <keyword>
          Labour in the Agricultural Sector
        </keyword>
        <keyword>
          Machinery and Equipment
        </keyword>
      </subject>
      <abstract>
        <![CDATA[The Agricultural Census 2024 collected key information on farm holdings, land tenure patterns, cropping practices, agricultural credit, irrigation methods, livestock ownership, and the use of modern machinery. Such data are critical to devising evidence-informed policies for raising productivity, enhancing climate resilience, increasing rural incomes, and aligning with our  international commitments including the Sustainable Development Goals (SDGs).]]>
      </abstract>
      <sumDscr>
        <collDate date="2024-09-01" event="start" cycle="Phase 1: cold and mountain areas"/>
        <collDate date="2024-09-30" event="end" cycle="Phase 1: cold and mountain areas"/>
        <collDate date="2025-01-01" event="start" cycle="Phase 2: remaining areas"/>
        <collDate date="2025-02-10" event="end" cycle="Phase 2: remaining areas"/>
        <nation abbr="PAK">
          Pakistan
        </nation>
        <geogCover>
          The Agricultural Census 2024 covered the entire country.
        </geogCover>
        <anlyUnit>
          Agricultural holdings
        </anlyUnit>
        <universe>
          <![CDATA[The statistical unit was the agricultural holding held and/or operated by the Government or by households, individually or collectively or under corporate arrangement during the time of census enumeration, normally used for crop production, rearing livestock, or having agricultural machinery. 

Urban blocks with no agricultural activity and defence related areas were excluded from the census enumeration.]]>
        </universe>
        <dataKind>
          Census/enumeration data [cen]
        </dataKind>
      </sumDscr>
      <notes>
        <![CDATA[The census scope covered agricultural activities (crops and livestock) and agricultural machinery. 

The questionnaire collected information on:
1. Identification & basic information
2. Agricultural land details
3. Land use
4. Irrigation
5. Orchard area, fruit & non fruit trees
6. Crops in the current year
7. Ownership and use of agricultural machinery
8. Cattle, buffaloes
9. Sheep, goats
10. Camels, horses, mules & asses
11. Yak/Dzo/Dzomo
12. Changes & veterinary treatment of animals during last 12 months
13. Agricultural loan and sources of income
14. Attestation]]>
      </notes>
    </stdyInfo>
    <method>
      <dataColl>
        <timeMeth>
          <![CDATA[Reference day: 
- Day of enumeration, for various variables including agricultural land, livestock, milk production, machinery ownership, orchard area, fruit and non-fruit trees and stock variables. 

Reference periods: 
- Crop year, for land use, irrigation and soil management.
- Last 12 months, for use of machinery, crops (Rabi-Winter/Spring and Kharif-Monsoon/Autumn Seasons), crops under protective cover, veterinary services, slaughtered animals, dynamics of livestock herds, loans and sources of income.]]>
        </timeMeth>
        <sampProc>
          <![CDATA[The sampling frame for the Agricultural Census 2024 was based on the Mouza Census 2020. Each mouza contains one or more Enumeration Blocks (EBs). In urban areas, the blocks were the enumeration areas. This frame was updated using information from the Population and Housing Census 2023, which was also used to update the geospatial mapping of the Mouza Census Frame 2020. The sampling frame consisted of 45 753 mouzas and 103 972 urban blocks. A list of National Certainty Holdings (NCH) was constructed including big agricultural holdings and agricultural holdings in the household sector with at least 100 acres (40.5 ha) of agricultural land, 50 cows/buffaloes, 200 goats/sheep, or 25 camels. 

The census was conducted using sample enumeration. A total of 9037 Mouzas and 2046 urban blocks were selected and allocated within strata using proportional allocation. There were a total of 1 052 956 agricultural holdings enumerated, with a response rate of 99 percent. 

The sample design of the census differed in each stratum.  
- For the stratum of NCH, complete enumeration was used.  
- In the rural area, Mouzas were stratified using variables related to cultivated land and livestock.  
- In urban areas, strata were based on livestock rearing and self-agriculture activities.  

In the first stage, Mouzas were allocated to stratum using proportional allocation, then selected using probability proportional to size with cultivated area as the measure of size. For selected big Mouzas, which had two or more blocks already identified through the Population and Housing Census 2023, a single block was selected through probability proportional to size. Urban blocks were selected using simple random sampling.  

A complete listing of all households having agricultural land, livestock, and agricultural machinery was carried out in selected Mouzas and/or Blocks. Those units in Mouzas with at least 20 acres (8.1 ha) of agricultural land, 20 cows/buffaloes, 50 goats/sheep or 20 camels were identified as Mouza Certainty Holdings (MCH) and were completely enumerated. Also, households with only agricultural machinery, nomads and Roma households were fully enumerated.  In the rest of the holdings, a systematic random sampling was used. ]]>
        </sampProc>
        <collMode>
          <![CDATA[Computer Assisted Personal Interview [capi]]]>
        </collMode>
        <collMode>
          <![CDATA[Computer Assisted Web Interview [cawi]]]>
        </collMode>
        <resInstru>
          <![CDATA[Three questionnaires were used in the census. 
- Form-1 was used for household listing in the selected mouzas or urban blocks for further selection. 
- Form-2 was used to collect data in agricultural holdings in the household sector and National and Mouza Certainty Holdings.
- Form-3A collected information regarding slaughtered animals in recognized slaughterhouses. 

The questionnaires covered 18 out of the 23 essential items recommended in the WCA 2020. 


The Mouza Census 2020 collected data at the mouza-level regarding facilities available to the farming community living in rural areas: roads, electricity, education and health facilities, veterinary facilities, markets for vegetable, fruit and grain market, seed shop, pesticide shop, government procurement centre, cold storage, livestock market, community pasture, police station, disaster during last five years, banks and sources of credit, industries and employment.]]>
        </resInstru>
        <sources/>
        <collSitu>
          <![CDATA[The Agricultural Census 2024 involved 352 Lead Census Trainers, 7686 enumerators and supervisors from Provincial Governments, 25 technical officers and officials working in Agricultural Census Project Management Unit before and after field operations, 15 Geographic Information System (GIS) staff and 20 IT experts working on the development of software and digital solutions during the field operation and on data processing afterward. 

**QUALITY ASSURANCE**
As part of its strategic planning, the Pakistan Bureau of Statistics launched a pilot census in July 2024 to evaluate the functionality and practicality of census technologies and processes, to identify potential implementation challenges, and to ensure system readiness. 

The Agricultural Census 2024 used advanced technologies: tablets for data collection, geo-tagging of agricultural holdings in the household sector, a real-time online dashboard for monitoring, digital maps, a task management system, social media advertising campaigns and a hotline complaint system. These digital tools improved data accuracy, reduced errors, time and costs, and improved efficient processing and analysis. A call centre was established at the headquarters of the Pakistan Bureau of Statistics to address all complaints, provide IT support and ensure data collection quality during the census process. However, the centre's main task was to handle complaints and the non-response from large agricultural holdings. The Pakistan Bureau of Statistics integrated a centralized SMS Gateway into its operational framework to facilitate rapid and reliable information exchange between the headquarters, regional offices, supervisors, and enumerators, enabling rapid dissemination of updates, technical instructions, operational alerts, and critical deadlines, streamlining field operations and supporting urgent decision-making. 

At each Census District Level, 157 dedicated Census Support Centres were established to support and facilitate the census field operation. These Census Support Centres were responsible for managing a variety of tasks, including distributing and retrieving tablet devices, installing and configuring software applications, acting as control rooms, and handling complaints at the district level. For hard-to-reach areas and some specific areas where complete enumeration of agricultural holdings in the household sector was required, listing and enumeration were completed together, reducing costs and non-response. An in-house GIS dashboard was used to monitor data collection in real time, geotagging households and automatically flagging completed and missing data, which supported immediate quality checks and corrections.]]>
        </collSitu>
        <cleanOps>
          Direct data capture was ensured by the CAPI using software developed by the Pakistan Bureau of Statistics. The questionnaires completed with the PAPI method were digitized through tablets and transferred to the main server. For data editing and imputation, the Data Cleaning Module developed by the Pakistan Bureau of Statistics was used. This app is a query-based automated data cleaning tool that replaced the traditional manual review methods, enabling faster, repeatable, and scalable error correction. AI-assisted cleaning features were used at initial scale to detect data anomalies. A tabulation plan with specifications was prepared for proper data representation for different themes of the Census. Final Tabulated data was processed digitally through Data Quality and Validation application developed and processed by trained technical staff.
        </cleanOps>
      </dataColl>
    </method>
    <dataAccs>
      <useStmt>
        <conditions>
          <![CDATA[For additional information on data access and use, please contact the Pakistan Bureau of Statistics.
E-mail: naveedeqbal@gmail.com 
Website: https://www.pbs.gov.pk/content/agriculture-census]]>
        </conditions>
      </useStmt>
    </dataAccs>
  </stdyDscr>
  <dataDscr/>
</codeBook>
