National Agricultural Survey 2017 - Peru

Abstract
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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), has been executing the National Agricultural Survey (ENA), in the 24 regions of the country.

The fundamental purpose of the survey is to obtain statistical information that allows the characterizing of small, medium, and large agricultural units of the country. The survey is also used to generate updated information for the construction of indicators that facilitate the monitoring and evaluation of the different budgetary programs, within the framework of the budget for results that the MEF has been developing in the public sector. In this way, it contributes to the design and orientation of public policies for the improvement of the living conditions of this sector of the population, especially the small and medium-sized agricultural producers.

The survey had the following objectives:

General objectives:
- To have statistical information that allows characterizing the small, medium and large agricultural units of the country.
- To 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, especially small and medium-sized agricultural producers.

Specific objectives:
- Determine the percentage of agricultural producers who 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 analyzes and received technical assistance to implement the results of said analysis in the last three years.
- Percentage of agricultural producers who have received technical assistance on the installation and management of pastures and apply it, in the last three years.
- 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 issues of agri-food safety.
- Obtain a baseline to measure the percentage increase in gross profit from sales of small producers.
- Determine the percentage of agricultural producers organized and managing their organizations business.
- Obtain a baseline to measure the percentage increase in the sales value of small subsistence agricultural producers.
- Obtain the percentage of organized small-scale agricultural producers that access storage infrastructure and equipment for commercialization.

Geographic coverage
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National Coverage

Analysis unit
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Agricultural holdings

Universe
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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.

Kind of data
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Sample survey data [ssd]

Sampling procedure
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The sampling frame for the selection of the survey sample is made up of statistical and cartographic information from the IV National Census of Agriculture 2012 (IV CENAGRO 2012).
The total sample of the National Agricultural Survey is 30,755 agricultural units, comprising of 29,218 agricultural units for medium and small producers; and 1,537 agricultural units for large agricultural producers and enterprises.

Mode of data collection
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Computer Assisted Personal Interview [capi]

Response rate
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The non-response rate of the 2017 National Agricultural Survey of small and medium producers is 0.43%, while that of large producers is 1.69%.

Data appraisal
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The tasks carried out in the information processing are described below.

1. DATA CAPTURE
The data capture in the National Agricultural Survey 2017 was through the digital form captured in a tablet application which was validated by a team of consistency analysts to ensure that they do not present difficulties during the field operation.
With this process, the survey official first filled out the digital form, then at the end of the interview he was instructed to export the database of the agricultural unit and send it to the central headquarters servers after reviewing the information completed, to which was directed to look for an internet booth, from where using the address, username and password, he proceeded to send said information through an integrated information system via the web.
For the daily income it was not necessary that the questionnaire be complete, so the application allowed him to modify the information as many times as necessary, but only until the information is completed, at which time he should save the information by placing the agricultural unit in "Closed" status so that the system can proceed with its consistency.
If once closed, it was necessary to modify the information, this process was only possible, through the computer team, who coordinated the cases with the consistency area and, according to their need, proceeded to correct them.

2. BASIC CONSISTENCY
Coverage: The coverage process is carried out by the INEI Consistency staff, consisting of the crossing of information between the framework and what was actually found in the field. In the case of the National Agricultural Survey, we worked in two stages according to the natural region; First stage: Sierra; Second stage: Costa-Selva. The progress of coverage at the national level was monitored from the Lima headquarters through a series of reports, which guaranteed that the agricultural units are covered and consistent according to their natural region.

Structure: The structure process is carried out by INEI's OTIN staff. This process consisted of ensuring the integrity of the chapters that correspond to each agricultural unit according to their agricultural activity carried out by that agricultural producer in the reference period.

Basic consistency: Basic consistency is performed by the ENA and OTIN consistency staff together. The consistency analyst defines a set of flow rules, default values, etc. that apply to the database. The OTIN programmer implements and incorporates these rules into the basic consistency application. The process operators execute the basic consistency application and the consistency analyst verifies the obtained result.

3. CODING
The coding process is automatic in the tablet application, however there are cases in which the interviewer was unable to determine the name and / or type of the crop, sub product and / or derivative, in these cases the coding is carried out by INEI's coding analysts and OTIN process operators using an interface to assign their corresponding codes in the database.

4. CONSISTENCY
Consistency is performed by ENA and OTIN Consistency staff together. The consistency analyst defines a set of consistency rules that apply to the database. The OTIN developer implements and incorporates these rules into the consistency application. The process operators execute the consistency application and the consistency analyst verifies the obtained result. To facilitate the work of process operators, the process application for data processing was implemented, which consolidates in a single application all the processes involved in this task. Consistency was also a parallel action with the collection of information because, when entered into the survey database in a timely manner, it was immediately reviewed, consistent, verified and if errors or omissions were detected, they were gradually delivered to the operational headquarters for their timely recovery, correction and / or verification in the field and, if necessary, the information was returned to the headquarters.

5. RESULTS
Generation of results: 23 data tables were generated according to each chapter of the form, each identified with a unique identifier (ID) in each table.

6. PRODUCTS
From the database of the definitive results of the National Agricultural Survey, the microdata is generated as a product in the SPSS Database, which includes all the chapters and sections of the virtual form.

摘要
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国家统计局与信息研究所（INEI），作为国家统计系统的管理机构，与经济财政部（MEF）建立战略联盟，并与农业灌溉部（MINAGRI）协调，正在执行全国农业普查（ENA），涵盖国家24个地区。
普查的基本目的是获取统计信息，以描述国家的小型、中型和大型农业单位。普查还用于生成更新信息，构建促进不同预算项目监控和评估的指标，这些项目是在MEF在公共部门开发的结果导向预算框架内进行的。因此，它有助于设计并指导旨在改善该人口群体生活条件的公共政策，特别是小型和中型农业生产商。
普查具有以下目标：

总体目标：
- 获取统计信息，以描述国家的小型、中型和大型农业单位。
- 在结果导向预算框架内，生成构建农业部门指标的信息，这些指标允许对指标演变进行持续评估，并有助于设计和发展旨在改善该人口群体生活条件的公共政策，特别是小型和中型农业生产商。

具体目标：
- 确定实施适当农业和畜牧业实践的农业生产商的比例。
- 获取实施适当播种方向的农业生产商的信息。
- 确定在过去三年内实施土壤分析并收到技术援助以实施分析结果的农业生产商的比例。
- 过去三年内接受技术援助进行牧场安装和管理并将其应用的农业生产商的比例。
- 过去三年内接受牧场安装和管理培训的农业生产商的比例。
- 获取应用技术灌溉的农业生产商的比例。
- 估算具有技术灌溉的农业面积。
- 确定了解农业食品安全问题的农业生产商的比例。
- 获取基线，以衡量小型生产商销售总收入增长的百分比。
- 确定组织并管理其组织业务的农业生产商的比例。
- 获取基线，以衡量小规模自给自足农业生产商销售价值增长的百分比。
- 获取能够访问存储基础设施和设备以进行商业化的有组织的小规模农业生产商的比例。

地理覆盖范围
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全国覆盖

分析单元
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农业经营

总体
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该调查涵盖所有国家少于50公顷的农业单位和农业企业。

数据类型
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样本调查数据 [ssd]

抽样程序
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用于选择调查样本的抽样框架由IV次全国农业普查2012年（IV CENAGRO 2012）的统计和制图信息组成。
全国农业普查的总样本量为30,755个农业单位，包括29,218个中、小规模生产商的农业单位；以及1,537个大规模农业生产商和企业的农业单位。

数据收集方式
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计算机辅助个人访谈 [capi]

响应率
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2017年小规模和中规模生产商的全国农业调查的非响应率为0.43%，而大规模生产商的非响应率为1.69%。

数据评估
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以下是对信息处理中执行的任务的描述。

1. 数据捕获
全国农业普查2017年的数据捕获是通过平板应用程序中的数字表单完成的，该表单由一致性分析团队验证，以确保在实地操作中不会出现困难。
通过此过程，调查官员首先填写了数字表单，然后在访谈结束时，他被告知在审查完完成的信息后，将农业单位数据库导出并发送到中央总部服务器，然后被指示寻找互联网摊位，从那里使用地址、用户名和密码，他通过互联网集成信息系统发送了信息。
对于日常收入，无需问卷完整，因此应用程序允许他根据需要多次修改信息，但仅限于信息完成之前，在此之后，他应通过将农业单位置于“关闭”状态来保存信息，以便系统可以继续其一致性。
如果一旦关闭，需要修改信息，则此过程只能通过计算机团队进行，该团队协调与一致性区域的案例，并根据他们的需要进行了纠正。

2. 基本一致性
覆盖范围：覆盖过程由INEI一致性工作人员执行，包括框架与实地发现之间的信息交叉。在农业普查的情况下，我们根据自然区域分两个阶段进行工作；第一阶段：山区；第二阶段：海岸-森林区。通过一系列报告从利马总部监控国家层面的覆盖进度，这保证了农业单位在其自然区域内的覆盖和一致性。
结构：结构过程由INEI的OTIN工作人员执行。该过程包括确保与每个农业单位相对应的章节的完整性，这些章节根据农业生产商在参考期间进行的农业活动。
基本一致性：基本一致性由ENA和OTIN一致性工作人员共同执行。一致性分析师定义一组适用于数据库的流规则、默认值等。OTIN程序员实现并将这些规则纳入基本一致性应用程序。流程操作员执行基本一致性应用程序，一致性分析师验证获得的结果。

3. 编码
编码过程在平板应用程序中是自动的，但是在某些情况下，访谈员无法确定作物、副产品或衍生物的名称和/或类型，在这些情况下，编码由INEI的编码分析师和OTIN流程操作员使用一个界面完成，在该界面中分配数据库中的相应代码。

4. 一致性
一致性由ENA和OTIN一致性工作人员共同执行。一致性分析师定义一组适用于数据库的一致性规则。OTIN开发者实现并将这些规则纳入一致性应用程序。流程操作员执行一致性应用程序，一致性分析师验证获得的结果。为了方便流程操作员的工作，实施了数据处理的流程应用程序，该应用程序在单个应用程序中巩固了涉及此任务的所有流程。一致性也是与信息收集并行进行的行动，因为，当及时输入调查数据库时，它立即被审查、核实、验证，如果发现错误或遗漏，则逐步将其交付给运营总部以进行及时恢复、纠正/验证，如果需要，则将信息返回到总部。

5. 结果
结果生成：根据表单的每个章节生成了23个数据表，每个表都有一个唯一的标识符（ID）。

6. 产品
从全国农业普查最终结果的数据库中，生成了SPSS数据库中的微观数据作为产品，该数据库包括虚拟表单的所有章节和部分。