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  <citation>
    <titlStmt>
      <IDNo>DDI_PER_2016_ENA_v01_EN_M_v01_A_OCS_FAO</IDNo>
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    <prodStmt>
      <producer abbr="OCS" affiliation="Food and Agriculture Organization" role="Metadata adapted for FAM">Office of Chief Statistician</producer>
      <producer abbr="INEI" affiliation="Government of Peru" role="">National Institute of Statistics and Informatics</producer>
      <producer abbr="DNCE" affiliation="National Institute of Statistics and Informatics" role="Statistical research producer">National Directorate of Censuses and Surveys</producer>
      <producer abbr="CIDE" affiliation="National Institute of Statistics and Informatics" role="Documentation, review and validation of the metadata">Research and Development Centre</producer>
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<stdyDscr>
  <citation>
    <titlStmt>
      <titl>National Agricultural Survey 2016</titl>
      <subTitl/>
      <altTitl>ENA 2016</altTitl>
      <parTitl/>
      <IDNo>PER_2016_ENA_v01_EN_M_v01_A_OCS</IDNo>
    </titlStmt>
    <rspStmt>
      <AuthEnty affiliation="Government of Peru">National Institute of Statistics and Informatics</AuthEnty>
      <AuthEnty affiliation="National Institute of Statistics and Informatics">National Directorate of Censuses and Surveys</AuthEnty>
    </rspStmt>
    <prodStmt>
      <producer abbr="" affiliation="Government of Peru" role="Technical Assistance">Ministry of Agriculture and Irrigation</producer>
      <producer abbr="" affiliation="Government of Peru" role="Technical Assistance">Ministry of Economy and Finance</producer>
      <copyright/>
      <software version="5.0" date="2023-02-16">NADA</software>
      <fundAg abbr="MEF" role="Financing">Ministry of Economic anad Financing</fundAg>
      <grantNo/>
    </prodStmt>
    <distStmt>
      <contact affiliation="National Institute of Statistics and Informatics" URI="https://www.inei.gob.pe/" email="gisella.canote@inei.gob.pe">Gisella Cañote Fajardo</contact>
      <depDate date=""/>
      <distDate date=""/>
    </distStmt>
    <serStmt>
      <serName>Agricultural Survey [ag/oth]</serName>
      <serInfo>This is the third survey of its kind, following the National Agricultural Survey in 2014 and 2015.</serInfo>
    </serStmt>
    <verStmt>
      <version date=""/>
      <verResp/>
      <notes/>
    </verStmt>
    <biblCit format=""/>
    <notes/>
  </citation>
  <stdyInfo>
    <studyBudget/>
    <subject>
      <keyword vocab="" vocabURI="">Agricultural holding</keyword>
      <keyword vocab="" vocabURI="">Plot</keyword>
      <keyword vocab="" vocabURI="">Agricultural producer</keyword>
      <keyword vocab="" vocabURI="">Agricultural practices</keyword>
      <keyword vocab="" vocabURI="">Livestock activity</keyword>
      <keyword vocab="" vocabURI="">Food safety</keyword>
      <keyword vocab="" vocabURI="">Enumeration area</keyword>
      <keyword vocab="" vocabURI="">Agricultural district</keyword>
    </subject>
    <abstract>The National Institute of Statistics and Informatics (INEI), the governing body of the National Statistical System, in a strategic alliance with the Ministry of Economy and Finance (MEF) and in coordination with the Ministry of Agriculture and Irrigation (MINAGRI), executed for the third consecutive time the National Agricultural Survey (ENA), in the 24 regions of the country.

The National Agricultural Survey 2016 is a statistical research that will have the fundamental purpose of generating updated information for the construction of indicators that will facilitate the follow-up and evaluation of the different budgetary programs, within the framework of a results-based budget, that the Ministry of Economy and Finance has been implementing in the public sector. In this way,it will contribute to the design and orientation of public policies for the improvement of the living conditions of agricultural producers.

The survey had the following objectives:

General objectives:
- Estimate land uses, planted area, harvested area, production and yield of the main transitory and permanent crops, milk production and livestock inventory in regions of the national territory.
- Generate information for the construction of indicators of the agricultural sector, within the framework of a results-based budget, that allow for the continuous evaluation of the evolution of said indicators and contribute to the design and orientation of public policies for the improvement of the living conditions of the population.

Specific objectives:
- Identify and quantify land use (land uses).
- Estimate the planted area of the transitory and permanent crops.
- Estimate the harvested area, production and yield of the main crops, at the regional level.
- Produce information that supports the estimation of the gross value of agricultural production.
- Determine the national livestock inventory.
- Identify the primary destinations of production, marketing channels and points of sale.
- Determine the percentage of agricultural producers that carry out adequate agricultural and livestock practices.
- Obtain information from agricultural producers who carry out an appropriate sowing orientation.
- Determine the percentage of agricultural producers who have carried out soil analysis and received technical assistance to implement the results of said analysis in the last three years.
- Determine the percentage of agricultural producers who were trained in water quality standards for irrigation in the last three years.
- Determine the percentage of agricultural producers who have received technical assistance on the installation and management of pastures and apply it, in the last three years.
- Determine the percentage of agricultural producers who have been trained in pasture installation and management in the last three years.
- Obtain the percentage of agricultural producers that apply technical irrigation.
- Estimate the agricultural area with technical irrigation.
- Determine the percentage of agricultural producers informed on safety issues.
- Determine the percentage increase in the annual average value of sales of small agricultural producers.
- Determine the percentage increase in the average gross annual profit of the sales of small producers.
- Determine the percentage of agricultural producers organized and managing their organizations business.
- Percentage of small agricultural producers and organizations that access storage infrastructure and equipment for marketing.
- Investigate and estimate other study variables.</abstract>
    <sumDscr>
      <collDate date="2016-05-15" event="start" cycle=""/>
      <collDate date="2016-10-31" event="end" cycle=""/>
      <nation abbr="PER">Peru</nation>
      <geogCover>National Coverage</geogCover>
      <geogUnit/>
      <anlyUnit>Agricultural holdings</anlyUnit>
      <universe>The survey covers all the agricultural units of the country with less than 50 ha and the agricultural units that are agricultural or farming enterprises.</universe>
      <dataKind>Sample survey data [ssd]</dataKind>
    </sumDscr>
    <!-- qualityStatement - ddi2.5 - complex type
     
     This structure consists of two parts, standardsCompliance and otherQualityStatements. 
     In standardsCompliance list all specific standards complied with during the execution of this 
     study. Note the standard name and producer and how the study complied with the standard. 
     Enter any additional quality statements in otherQualityStatements.
     
     -->
    <qualityStatement>
      <standardsCompliance>
        <standard>
          <standardName/>
          <producer/>
        </standard>
        <complianceDescription/>
      </standardsCompliance>
      <otherQualityStatement/>
    </qualityStatement>
    <notes>The description of the scope includes:

1. Characteristics of the agricultural holding
2. Crop area - planting and harvesting
3. Agricultural practices
4. Livestock production
5. Good livestock practices
6. Food safety
7. Agricultural extension services
8. Organization/Association membership
9. Access to financial services
10. Production costs
11. Socio-economic characteristics of household</notes>
    <!-- exPostEvaluation ddi2.5
      Use this section to describe evaluation procedures not address in data evaluation processes. 
      These may include issues such as timing of the study, sequencing issues, cost/budget issues, 
      relevance, instituional or legal arrangments etc. of the study. 
      
      The completionDate attribute holds the date the evaluation was completed. 
      The type attribute is an optional type to identify the type of evaluation with or without 
      the use of a controlled vocabulary.
    -->
    <exPostEvaluation completionDate="" type="">
      <evaluationProcess/>
      <outcomes/>
    </exPostEvaluation>
  </stdyInfo>
  <method>
    <dataColl>
      <timeMeth/>
      <!-- collectorTraining - DDI2.5
        
        Collector Training

        Describes the training provided to data collectors including internviewer training, process testing, 
        compliance with standards etc. This is repeatable for language and to capture different aspects of the 
        training process. The type attribute allows specification of the type of training being described.
        
        -->
      <collectorTraining type=""/>
      <frequenc/>
      <sampProc>The basic sampling framework for the selection of the survey sample is constituted by the statistical information of the master framework of agricultural units, using information from the IV National Agricultural Census 2012 (IV CENAGRO 2012).
The total sample of the National Agricultural Survey is 30,710 agricultural units, comprising of 29,218 agricultural units for medium and small producers; and 1,492 agricultural units for large agricultural producers (special stratum).</sampProc>
      <sampleFrame>
        <sampleFrameName/>
        <custodian/>
        <universe/>
        <frameUnit isPrimary="">
          <unitType numberOfUnits=""/>
        </frameUnit>
        <updateProcedure/>
      </sampleFrame>
      <deviat>In the National Agricultural Survey 2016, out of a total of 2,260,973 agricultural units programmed, 2,244,679 are small and medium and 16,294 belong to the large units (enterprises, individuals, poultry farms, farms, stables, among others).
The sample executed was 30,710 of which 29,218 are small and medium agricultural units and 1,492 belong to the large units.</deviat>
      <collMode>Computer Assisted Personal Interview [capi]</collMode>
      <resInstru/>
      <!-- instrumentDevelopment - DDI2.5             
        Describe any development work on the data collection instrument. Type attribute allows for the optional use of a defined development type with or without use of a controlled vocabulary.
        -->
      <instrumentDevelopment type=""/>
      <collSitu/>
      <actMin/>
      <ConOps/>
      <weight/>
      <cleanOps>The use of mobile technology to capture data online, ensured basic consistency of information and possible corrections in a timely manner. Also, the use of GPS for measuring the surface of the plots, helped to guarantee the correct location of the interviewers in the field and served as a mechanism of supervision and control.

The methodological documents of the survey were also validated; including questionnaires, manuals and auxiliary documents, in coordination with the technical areas of the Ministry of Agriculture and Irrigation (MINAGRI) and the Ministry of Economy and Finance (MEF). The collection instruments were further validated through pilot tests.

Quality control procedures (re-interview application, face-to-face supervision application, coverage monitoring, information quality monitoring, online consistency reports, mainly) were also applied in the field in order to ensure the quality of the information collected, especially of the main variables, such as: agricultural activity, number of plots, area, production, yields, among others.

Other tasks were also performed. They include:

1. Development of an integrated data entry system, which contained all the modules (segmentation, monitoring, data transfer, basic consistency checks, and reporting modules).
2. Analysis of the information: This task consists of evaluating, identifying and correcting errors and omissions in the variables of the database, as a result of processing, to obtain a consistent and reliable data for the generation of indicators.
This task was carried out by the national supervisor and was monitored by a team installed in the data processing and methodology area at the headquarters.
3. Elaboration and analysis of quality indicators: Through the monitoring and data entry system, product indicators were generated, after the information had been consolidated.
4. Export of data to SPSS or STATA format: Finally, an export module was created which allowed the database to be exported to SPSS or STATA format.</cleanOps>
    </dataColl>
    <notes/>
    <anlyInfo>
      <respRate>1. The non-response rate of small and medium agricultural units is 0.61%.

- The non-response rate of small and medium agricultural units in the coastal region is 0.63%
- The non-response rate of small and medium medium agricultural units in the sierra region is 0.50%
- The non-response rate of small and medium agricultural units in the jungle region is 0.91%

2. The non-response rate of large agricultural units is 0.58%.</respRate>
      <EstSmpErr/>
      <dataAppr/>
    </anlyInfo>
    <stdyClas/>
    <dataProcessing type=""/>
    <codingInstructions relatedProcesses="" type="">
      <txt/>
      <command formalLanguage=""/>
    </codingInstructions>
  </method>
  <dataAccs>
    <setAvail>
      <accsPlac URI=""/>
      <origArch/>
      <avlStatus/>
      <collSize/>
      <complete/>
      <fileQnty/>
      <notes/>
    </setAvail>
    <useStmt>
      <confDec required="yes" formNo="" URI="">The National Agricultural Survey 2016, maintains the confidentiality of the information collected, protected by Supreme Decree 043-2001-PCM that mentions that the information provided by the sources is secret and cannot be revealed individually, even if there is an administrative or judicial order.

STATISTICAL CONFIDENTIALITY AND DATA PRIVACY.
Supreme Decree No. 043-2001-PCM Art. 97.
The information provided by the sources is of a secret nature and may not be disclosed individually, even by administrative or judicial order. It may only be disclosed or published in an unnamed form. The information provided may not be used for tax or police purposes either.</confDec>
      <restrctn/>
      <citReq>The INEI authorizes the use of the information whenever the source is cited. (Source: National Institute of Statistics and Informatics - National Agricultural Survey 2016). 
Therefore, the copying or reproduction of the information contained in any electronic medium (networks, databases or electronic publications) that allows the availability of this information to multiple users without the prior written consent of INEI is totally prohibited.</citReq>
      <deposReq/>
      <conditions>The INEI makes all the information contained on the web site available to users, on an individual basis, as an end-user licence. Any commercialisation of this right of access is therefore prohibited. The INEI does not undertake to update the information immediately and reserves the right to modify, increase, update, change or correct any omission or information contained on this website at any time.</conditions>
      <disclaimer>1. Supreme Decree No. 043-2001-PCM: Regulations on the Organisation and Functions of the INEI and R.J. No. 108-94 /INEI approving Directive No. 006-94-INEI/DNEB "Regulations on the application of fines, for failure to provide statistical information, requested by the bodies of the National Statistics System".

Mandatory:
Supreme Decree No. 043-2001-PCM Art. 81
The sources of statistical information of the National System of Statistics are the natural or legal persons that are in the country, which are obliged to provide the information of statistical use to the organs of the System, in the form, terms and deadlines that are set, in forms approved by the Head of the INEI and published in the official newspaper "El Peruano". Likewise, the administrative records of the Public Sector are sources of information. This obligation does not apply to sources whose information is considered classified and affects national security.

Sanctions:
Supreme Decree No. 043-2001-PCM Art. 87.
Natural or legal persons who refuse to provide data, maliciously falsify the truth, or unjustifiably delay the established terms, will be liable for the fines established in Article 89, without prejudice to any civil or criminal liability.

Supreme Decree No. 043-2001-PCM Article 88.
Fines will be applied by the governing body of the National System of Statistics and Information Technology for the purpose of improving statistical production.

Supreme Decree No. 043-2001-PCM Article 89.
In order to sanction the non-compliance with the requested information, the following fines are established:
a) Natural persons: from 1% to 50% of the ITU in force at the date of cancellation
b) Legal entities: from 10 % of the ITU to 10 ITU at the date of cancellation Art. 93
The payment of the fine does not exempt the sources from the obligation to provide the requested information. Consequently, whether or not payment of the fine has been made, it may be applied as often as the obligation is not fulfilled.

Supreme Decree No. 043-2001-PCM Article 91
The INEI, by means of a Sub-Jefatural Resolution published in the official newspaper El Peruano, will make known the list of natural and legal persons affected by the fine; by means of a Jefatural Resolution the appeal is determined in the last instance.

Supreme Decree No. 043-2001-PCM Article 93
The payment of the fine does not exempt the sources from the obligation to provide the requested information. Consequently, whether or not payment of the fine has been made, it may be applied as often as the obligation is not fulfilled.

Supreme Decree No. 043-2001-PCM Article 94
The fines will be paid at the Banco de la Nación, in the current account No. 20131369981 that the INEI has opened for this purpose.

2. Supreme Decree No. 043-2001-PCM on Statistical Secrecy and Confidentiality of Information
The INEI does not guarantee the operation of the communications network and therefore does not assume responsibility for the availability of this service. The data server may be disconnected without prior notice. Every effort will be made to keep the impact of maintenance tasks to a minimum. Likewise, it is not responsible for any damage or harm suffered by the user derived from the access to this server or from the use of information or applications contained in it.</disclaimer>
    </useStmt>
    <notes/>
  </dataAccs>
  <notes/>
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