Abstract

The main purpose of the Survey of Agricultural Holdings is to produce official indicators in line with agricultural sector. The survey allows the compilation of statistics on crops and animal husbandry, of which information annual and permanent crops, sown area, average yield of annual crops and etc. Statistical tables are accessible through the following link: https://www.geostat.ge/en/modules/categories/196/agriculture.

One round of the survey (reference year) includes 5 inquiries: The Inception interview is carried out using the inception questionnaire during the period of January-February of the reference year. During this interview the sampled holdings are identified and situation existing at the holding as of first January is recorded. I, II and III quarter interviews are conducted by means of quarterly questionnaire at the beginning of the following month of the corresponding quarter of the reference year. Based on these surveys, the information about agricultural activities during the corresponding quarter is collected. The final interview is conducted by means of final questionnaire in January of the following year of the reference year. During this interview, the information about agricultural activities at the holding during IV quarter of the reference year and the summary information about agricultural activities at the holding during the whole reference year (from 1 January to 31 December of the previous year) are collected. During all five interviews, the same agricultural holdings (about 12 000) are interviewed which are selected by a two-stage stratified cluster random sampling procedure out of about 642 000 agricultural holdings operated in Georgia. On the first stage, clusters (settlements) are selected. On the second stage, holdings are selected within the selected clusters.

The survey completely covers the territory of Georgia, excluding the occupied territories of Autonomous Republic of Abkhazia and Tskhinvali region. Each year a new sample is selected based on a rotational design (on a 3-year basis). In particular, every year approximately 4000 holdings out of the 12000 sampled holdings are replaced by new holdings. Sampled holdings participate in the survey for 3 years. Large agricultural holdings are sampled every year with complete coverage. The statistical unit of the survey is the agricultural holding (family holdings and agricultural enterprises) – which is defined as an economic unit of agricultural production under single management comprising all livestock kept and all land used wholly or partly for agricultural production purposes, without regard to title, legal form or size. Agricultural activities are conducted under the supervision of a holder (in case of households - a member of household, in case of agricultural enterprises - director or authorized person), who is responsible for making decisions and takes all economic risks and expenses related to agricultural activities.

More than 270 interviewers participated in the survey fieldwork. For the Data collection, computer-assisted personal interviewing method (CAPI) was used in the family holdings. In case of agricultural enterprises, the authorized persons of the enterprises (respondent) fill the electronic (online) questionnaires by themselves (CAWI). Coordination of the interviewers and the primary control of the collected data during the field is carried out by coordinators. Their working area covers several municipalities. The function of the coordinators also includes consultation for agricultural enterprises on methodological and technical issues related to the survey.

Geographic coverage

Entire country (Georgia), excluding occupied regions (Abkhazia and Tskhinvali region)

Analysis unit

Agricultural holding – economic unit of agricultural production under single management comprising all livestock kept and all land used wholly or partly for agricultural production purposes, without regard to title, legal form or size in which agricultural activities are conducted under the supervision of a holder, who is responsible for making decisions and takes all economic risks and expenses related to agricultural activities.

Universe

Survey sampling frame includes about 642,000 agriculture holdings (households and agricultural enterprises) operated in country. The Agricultural Census 2014 is the main source of the sample frame. Sampling frame is updated on a permanent basis in according to the results of survey of agricultural holdings, business register and different administrative sources.

Kind of data

Sample survey data [ssd]

Sampling procedure

• Main Source of the sample frame since 2016 - Agricultural Census 2014; • Sample frame contained 642,000 holding - sample size 12,000 (1.9%); • Sample Design: two-stage stratified cluster random sampling; - First stage - selection of cluster (Settlement); - Second stage - Selection of holdings within the selected clusters; • Each year a new sample is selected based on a rotational design; - Every year 1/3 of holdings (4,000) selected a year before are replaced (Sampled holdings participate in the survey during 3 years); • Extremely large agricultural holdings are sampled every year with complete coverage; • Additional Sources for updating sample frame: Sample Survey of Agricultural Holdings, Statistical Business Register, Administrative data existing in MEPA (large agricultural holdings); Sampling error of main indicators do not exceed 5% for a country level and 10% for a regional level.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Detailed information on structure, and sections of questionnaires used in the survey of agricultural holdings are available in following link: https://www.geostat.ge/en/modules/categories/564/questionnaires-Agricultural-Statistics

Cleaning operations

After the field work, cleaning and harmonization of all inquiries are established at the Geostat head office - logical and arithmetical inconsistencies, as well as non-typical and suspicious data are detected, checked and corrected. Verification of the data is performed by contacting the respondents by phone. If verification with respondent is impossible, different imputation methods are used. Finally, indicators are calculated using weighted data. The obtained results are compared with corresponding results of the previous periods. In case of significant differences, the possible causes are identified and analyzed.

Response rate

In the 2022 fourth quarter, 1,349 holdings were not surveyed, due to the fact that some holdings refused to be interviewed or were not found during the fieldwork despite its existence. This is about 10.7% of the total sampled holdings of 12,589 holdings involved in the sample 2022 fourth quarter.

The STRIVE project, funded by USAID's Displaced Children and Orphans Fund (DCOF) and managed by FHI 360, used market-led economic strengthening initiatives to improve the well-being of vulnerable children. Through STRIVE, ACDI/VOCA implemented the Agriculture for Children’s Empowerment (ACE) Project in Liberia, which is founded on the premise that increased household economic security will stimulate more consistent investments in children’s well being via longer term social investments in education and nutrition. ACE’s primary focus was on the horticulture value chain (VC) — the production and marketing of vegetables by smallholder farmers in Montserrado, Bong, and Nimba counties of Liberia. ACE also strengthened smallholder rice farming to increase household food security using a market-sensitive approach to rice seed lending and cultivation. This dataset contains baseline information about each plot the household owns.

Abstract

The sample design of the Production Methods and the Environment module survey is based on the sample of the current Survey of Agricultural Holdings, so firstly given the design of the current Survey. The main purpose of the Survey of Agricultural Holdings as well as Production Methods and the Environment module is to produce official indicators in line with agricultural sector. The survey allows the compilation of statistics on crops and animal husbandry, of which information annual and permanent crops, sown area, average yield of annual crops, farming practices and their linkages with the natural environment, crop and livestock production methods, access to and use of information services, infrastructure and communal resources and etc. Statistical tables are accessible through the following link: https://www.geostat.ge/en/modules/categories/196/agriculture. Production Methods and the Environment Module is part of main Survey of Agricultural Holdings. One round of the main survey (reference year) includes 5 inquiries: The Inception interview is carried out using the inception questionnaire during the period of January-February of the reference year. During this interview the sampled holdings are identified and situation existing at the holding as of first January is recorded. I, II and III quarter interviews are conducted by means of quarterly questionnaire at the beginning of the following month of the corresponding quarter of the reference year. Based on these surveys, the information about agricultural activities during the corresponding quarter is collected. The final interview is conducted by means of final questionnaire in January of the following year of the reference year. During this interview, the information about agricultural activities at the holding during IV quarter of the reference year and the summery information about agricultural activities at the holding during the whole reference year (from 1 January to 31 December of the previous year) are collected. During all five interviews, the same agricultural holdings (about 12000) are interviewed which are selected by a two-stage stratified cluster random sampling procedure out of about 642 000 agricultural holdings operated in Georgia. On the first stage, clusters (settlements) are selected. On the second stage, holdings are selected within the selected clusters. The survey completely covers the territory of Georgia, excluding the occupied territories of Autonomous Republic of Abkhazia and Tskhinvali region. Each year a new sample is selected based on a rotational design (on a 3-year basis). In particular, every year approximately 4000 holdings out of the 12000 sampled holdings are replaced by new holdings. Sampled holdings participate in the survey for 3 years. Large agricultural holdings are sampled every year with complete coverage. The statistical unit of the survey is the agricultural holding (family holdings and agricultural enterprises) - which is defined as an economic unit of agricultural production under single management comprising all livestock kept and all land used wholly or partly for agricultural production purposes, without regard to title, legal form or size. Agricultural activities are conducted under the supervision of a holder (in case of households - a member of household, in case of agricultural enterprises - director or authorized person), who is responsible for making decisions and takes all economic risks and expenses related to agricultural activities. More than 270 interviewers participate in the survey fieldwork. For the Data collection, computer-assisted personal interviewing method (CAPI) is used in the family holdings. In case of agricultural enterprises, the authorized persons of the enterprises (respondent) fill the electronic (online) questionnaires by themselves (CAWI). Coordination of the interviewers and the primary control of the collected data during the field is carried out by coordinators. Their working area covers several municipalities. The function of the coordinators also includes consultation for agricultural enterprises on methodological and technical issues related to the survey. Production Methods and Environment module field work was carried out from May 5th to May 20th of 2022. 200 field staff participated in the survey, 22 of which were field supervisors. In total 5,880 agricultural holdings were selected for the PME survey. Such are the extra-large farms that are continuously participating in the survey and the third rotation farms that have been participating in the survey since 2019. Currently 943 extra-large farms and 3,899 third rotation farms are participating in the survey. Therefore, we have a total of 4,842 farm data for the last three years. The rest of the holdings will be selected from the first rotation clusters where interviews have been conducted for two years. In particular, using simple random sampling approximately 30% of the working clusters of the first rotation are selected in each stratum. This will give us about 1,038 farms. A total of about 5,880 farms will be selected.

Geographic coverage

Entire country (Georgia), excluding occupied regions (Abkhazia and Tskhinvali region)

Analysis unit

Agricultural holding – economic unit of agricultural production under single management comprising all livestock kept and all land used wholly or partly for agricultural production purposes, without regard to title, legal form or size in which agricultural activities are conducted under the supervision of a holder, who is responsible for making decisions and takes all economic risks and expenses related to agricultural activities.

Universe

Survey sampling frame includes about 642 000 agriculture holdings (households and agricultural enterprises) operated in country. The Agricultural Census 2014 is the main source of the sample frame. Sampling frame is updated on a permanent basis in according to the results of survey of agricultural holdings, business register and different administrative sources.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample design of the Production Methods and the Environment module survey is based on the sample of the current Survey of Agricultural Holdings, so firstly given the design of the current Survey. • Main Source of the sample frame since 2016 - Agricultural Census 2014; • Sample frame contained 642 000 holding - sample size 12 000 (1.9%); • Sample Design: two-stage stratified cluster random sampling; - First stage - selection of cluster (Settlement); - Second stage - Selection of holdings within the selected clusters; • Each year a new sample is selected based on a rotational design; - Every year 1/3 of holdings (4 000) selected a year before are replaced (Sampled holdings participate in the survey during 3 years); • Extremely large agricultural holdings are sampled every year with complete coverage; • Additional Sources for updating sample frame: Sample Survey of Agricultural Holdings, Statistical Business Register, Administrative data existing in MEPA (large agricultural holdings); Sampling error of main indicators do not exceed 5% for a country level and 10% for a regional level; The sample design of the Production Methods and the Environment module survey: • Sample Design:Two-stage cluster sampling was used for the survey. -Sample is formed separately in each stratum. At first, clusters are selected in every stratum, and then holdings from selected clusters are selected for survey. -Extra-large holdings will be in the sample by probability 1. That is, all clusters of extra-large holdings and all extra-large holdings from these clusters fall into sample. -Primary sampling unit in the rest of the strata is the cluster. The same number of holdings will be interviewed in all the selected clusters of a stratum. Specifically, in small holding strata, 12 holdings will be interviewed in each selected cluster. This number is 8 for medium-sized strata and 4 for large strata. -In each stratum the number of clusters that have to be selected is calculated by dividing the number of holdings to be selected in the stratum by the number of holdings to be interviewed in each cluster of the stratum. -In each stratum selection of clusters is done by the PPS method (Probability Proportionally to Size). -The selection of holdings in each selected cluster is made using a random systematic sample. • Rotational design: Survey has a panel design. Holdings, which will get into the sample, will stay there for three years. After this, they will be substituted by holdings from the same stratum. -The database lists 943 extra-large holdings. All of them will constantly participate in the survey. Their rotation group number will be "0". Of the remaining holdings each of them will belong to one of the three rotation groups. Holdings selected from the same cluster will fall in the same rotation group. Each rotation group will have more or less the same number of holdings. Each rotation group represents an independent random sample. -When holdings change by rotation , holding from the sample will be substituted by the new one from the same cluster. If the cluster does not have enough holdings to make the full rotation, then the cluster is deemed exhausted and is substituted by a randomly selected cluster from the same stratum. -Newly introduced holdings will belong to the same rotation group which its predecessor belonged to

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Detailed information on structure, and sections of questionnaires used in the survey of agricultural holdings available in following link:

Abstract

The agricultural survey in its current form covers all regions of the country and all 45 departments of Senegal. The agricultural survey is an annual statistical operation whose general objective is to estimate the level of the main agricultural output of family-type agricultural holdings. It also provides information on the physical characteristics of cultivated plots (geo-location, area) and major investments made in them (agricultural inputs, cultivation operations, soil management and restoration). The main indicators relate to yield levels, areas sown, production and means of production.

Following a modular approach, the 2022-2023 edition of the annual agricultural survey is characterized by the integration of the MEA module (Machines, Equipment and other Agricultural Assets). In addition, the basic module of the 50x2030 questionnaire allows the collection of data for the calculation of SDG 5.a.1.

Geographic coverage

The annual agricultural survey covers all 45 departments of Senegal. However, for reasons related to anonymization, the variable "Department" has been replaced by the variable "Agroecological Zone" which constitutes groupings in relation to the departments. The variable "Region" remains in the anonymized version of the data.

Analysis unit

Households and agricultural plots

Universe

The agricultural survey covers all households and plots in the 45 departments of Senegal.

Kind of data

Sample survey data [ssd]

Sampling procedure

The AAS was built on a two-stage survey, with census districts (CDs) as primary units (PUs) and agricultural households as secondary units (SUs), as defined during the general census of population and l'Habitat, de l'Agriculture et de l'Élevage (RGPHAE) of 2013. In line with the broadening of the scope of the survey recommended by the AGRIS approach, from this campaign onwards the sample design incorporated a first-stage stratification, induced by the second-stage stratification, to better reflect the various agricultural activities and improve the efficiency of the estimates. The choice of a first-degree stratification induced by that of the second degree, although less efficient than an independent first-degree stratification, was guided by the constraint of non-existence of relevant variables of interest in the sampling frame of the RGPHAE to discriminate against the CDs. The stratification took into account the relative importance of the main agricultural activities (in terms of household size) identified during the 2013 RGPHAE, namely rainfed agriculture, livestock and horticulture.

Thus, four strata were formed as follows: - the "rainfed only" stratum which groups together all the households practicing only rainfed crops; - the "livestock only" stratum for households that practice animal husbandry only; - the "Horticulture and other crops" stratum, which includes households that mainly practice horticulture and secondarily other crops (forestry, fruit growing, etc.); - the "Rainfed-livestock" stratum made up of households that practice both rainfed agriculture and livestock breeding.

The size of the sample of agricultural households to be surveyed was calculated by department (area of study) by setting a relative error of 10% on the variable of interest. The distribution of the sample of each department in the strata was made using the Bankier method (1988) developed in the methodological guide to the main sampling frame practices (pp. 79-81) of the Global Strategy for Agricultural and Rural Statistics (GSARS).

At the national level, the total theoretical sample is equal to 7,450 households, spread over 1,460 physical CDs, with 5 households per CD. At the end of the enumeration operation carried out in the physical sample CDs, adjustments were made to take into account the actual updated size of the CDs, which led to a final size of 7,378 households, or 1,382 CDs.

Sampling deviation

Compared to the survey plan, adjustments were made based on the response rate at each phase.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The first questionnaire collected information on census and characteristics of agricultural household plots. The second questionnaire collected information on agricultural production, machinery, equipment and agricultural productivity.

Response rate

First phase: sample of 7378 households, including 6360 surveyed, i.e. a coverage rate of 86%.

Second phase: sample of 7218 households, including 6,834 surveyed, i.e. a coverage rate of 95%.

Abstract

The Annual Agricultural Sample Survey (AASS) for the year 2022/23 aimed to enhance the understanding of agricultural activities across the United Republic of Tanzania by collecting comprehensive data on various aspects of the agricultural sector. This survey is crucial for policy formulation, development planning, and service delivery, providing reliable data to monitor and evaluate national and international development frameworks.

The 2022/23 survey is particularly significant as it informs the monitoring and evaluation of key agricultural development strategies and frameworks. The collected data will contribute to the Tanzania Development Vision 2025, Zanzibar Development Vision 2020, the Five-Year Development Plan 2021/22–2025/26, the National Strategy for Growth and Reduction of Poverty (NSGRP) known as MKUKUTA, and the Zanzibar Strategy for Growth and Reduction of Poverty (ZSGRP) known as MKUZA. The survey data also supports the evaluation of Sustainable Development Goals (SDGs) and Comprehensive Africa Agriculture Development Programme (CAADP). Key indicators for agricultural performance and poverty monitoring are directly measured from the survey data.

The 2022/23 AASS provides a detailed descriptive analysis and related tables on the main thematic areas. These areas include household members and holder identification, field roster, seasonal plot and crop rosters (Vuli, Masika, and Dry Season), permanent crop production, crop harvest use, seed and seedling acquisition, input use and acquisition (fertilizers and pesticides), livestock inventory and changes, livestock production costs, milk and eggs production, other livestock products, aquaculture production, and labor dynamics. The 2022/23 AASS offers an extensive dataset essential for understanding the current state of agriculture in Tanzania. The insights gained will support the development of policies and interventions aimed at enhancing agricultural productivity, sustainability, and the livelihoods of farming communities. This data is indispensable for stakeholders addressing challenges in the agricultural sector and promoting sustainable agricultural development.

Statistical Disclosure Control (SDC) methods have been applied to the microdata, to protect the confidentiality of the individual data collected. Users must be aware that these anonymization or SDC methods modify the data, including suppression of some data points. This affects the aggregated values derived from the anonymized microdata, and may have other unwanted consequences, such as sampling error and bias. Additional details about the SDC methods and data access conditions are provided in the data processing and data access conditions below.

Geographic coverage

National, Mainland Tanzania and Zanzibar, Regions

Analysis unit

Households for Smallholder Farmers and Farm for Large Scale Farms

Universe

The survey covered agricultural households and large-scale farms.

Agricultural households are those that meet one or more of the following two conditions: a) Have or operate at least 25 square meters of arable land, b) Own or keep at least one head of cattle or five goats/sheep/pigs or fifty chicken/ducks/turkeys during the agriculture year.

Large-scale farms are those farms with at least 20 hectares of cultivated land, or 50 herds of cattle, or 100 goats/sheep/pigs, or 1,000 chickens. In addition to this, they should fulfill all of the following four conditions: i) The greater part of the produce should go to the market, ii) Operation of farm should be continuous, iii) There should be application of machinery / implements on the farm, and iv) There should be at least one permanent employee.

Kind of data

Sample survey data [ssd]

Sampling procedure

The frame used to extract the sample for the Annual Agricultural Sample Survey (AASS-2022/23) in Tanzania was derived from the 2022 Population and Housing Census (PHC-2022) Frame that lists all the Enumeration Areas (EAs/Hamlets) of the country. The AASS 2022/23 used a stratified two-stage sampling design which allows to produce reliable estimates at regional level for both Mainland Tanzania and Zanzibar.

In the first stage, the EAs (primary sampling units) were stratified into 2-3 strata within each region and then selected by using a systematic sampling procedure with probability proportional to size (PPS), where the measure of size is the number of agricultural households in the EA. Before the selection, within each stratum and domain (region), the Enumeration Areas (EAs) were ordered according to the codes of District and Council which reflect the geographical proximity, and then ordered according to the codes of Constituency, Division, Wards, and Village. An implicit stratification was also performed, ordering by Urban/Rural type at Ward level.

In the second stage, a simple random sampling selection was conducted . In hamlets with more than 200 households, twelve (12) agricultural households were drawn from the PHC 2022 list with a simple random sampling without replacement procedure in each sampled hamlet. In hamlets with 200 households or less, a listing exercise was carried out in each sampled hamlet, and twelve (12) agricultural households were selected with a simple random sampling without replacement procedure. A total of 1,352 PSUs were selected from the 2022 Population and Housing Census frame, of which 1,234 PSUs were from Mainland Tanzania and 118 from Zanzibar. A total number of 16,224 agricultural households were sampled (14,808 households from Mainland Tanzania and 1,416 from Zanzibar).

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The 2022/23 Annual Agricultural Survey used two main questionnaires consolidated into a single questionnaire within the CAPIthe CAPI System, Smallholder Farmers and Large-Scale Farms Questionnaire. Smallholder Farmers questionnaire captured information at household level while Large Scale Farms questionnaire captured information at establishment/holding level. These questionnaires were used for data collection that covered core agricultural activities (crops, livestock, and fish farming) in both short and long rainy seasons. The 2022/23 AASS questionnaire covered 23 sections which are:

1. COVER; The cover page included the title of the survey, survey year (2022/23), general instructions for both the interviewers and respondents. It sets the context for the survey and also it shows the survey covers the United Republic of Tanzania.

2. SCREENING: Included preliminary questions designed to determine if the respondent or household is eligible to participate in the survey. It checks for core criteria such as involvement in agricultural activities.

3. START INTERVIEW: The introductory section where basic details about the interview are recorded, such as the date, location, and interviewer’s information. This helped in the identification and tracking of the interview process.

4. HOUSEHOLD MEMBERS AND HOLDER IDENTIFICATION: Collected information about all household members, including age, gender, relationship to the household head, and the identification of the main agricultural holder. This section helped in understanding the demographic composition of the agriculture household.

5. FIELD ROSTER: Provided the details of the various agricultural fields operated by the agriculture household. Information includes the size, location, and identification of each field. This section provided a comprehensive overview of the land resources available to the household.

6. VULI PLOT ROSTER: Focused on plots used during the Vuli season (short rainy season). It includes details on the crops planted, plot sizes, and any specific characteristics of these plots. This helps in assessing seasonal agricultural activities.

7. VULI CROP ROSTER: Provided detailed information on the types of crops grown during the Vuli season, including quantities produced and intended use (e.g., consumption, sale, storage). This section captures the output of short rainy season farming.

8. MASIKA PLOT ROSTER: Similar to Section 4 but focuses on the Masika season (long rainy season). It collects data on plot usage, crop types, and sizes. This helps in understanding the agricultural practices during the primary growing season.

9. MASIKA CROP ROSTER: Provided detailed information on crops grown during the Masika season, including production quantities and uses. This section captures the output from the main agricultural season.

10. PERMANENT CROP PRODUCTION: Focuses on perennial or permanent crops (e.g., fruit trees, tea, coffee). It includes data on the types of permanent crops, area under cultivation, production volumes, and uses. This section tracks long-term agricultural investments.

11. CROP HARVEST USE: In this, provided the details how harvested crops are utilized within the household. Categories included consumption, sale, storage, and other uses. This section helps in understanding food security and market engagement.

12. SEED AND SEEDLINGS ACQUISITION: Collected information on how the agriculture household acquires seeds and seedlings, including sources (e.g., purchased, saved, gifted) and types (local, improved, etc). This section provided insights into input supply chains and planting decisions based on the households, or head.

13. INPUT USE AND ACQUISITION (FERTILIZERS AND PESTICIDES): It provided the details of the use and acquisition of agricultural inputs such as fertilizers and pesticides. It included information on quantities used, sources, and types of inputs. This section assessed the input dependency and agricultural practices.

14. LIVESTOCK IN STOCK AND CHANGE IN STOCK: The

Abstract

The Ministry of Agriculture and Livestock Development (MoALD), and the Central Bureau of Statistics (CBS), with technical and financial assistance of FAO, have jointly conducted a pilot survey in the framework of AGRIS Program in Chitwan district with its affluence of agricultural diversity. It has adopted Production Method and Environment (PME) Module as rotating module along with Core Module for the pilot study as developed by FAO. Along with the piloting of the AGRISurvey Program initiated by FAO, the objective of the survey is to measure key indicators related to area and volume of agriculture production capturing the social, economic and technical dimensions of the holdings as well as providing data to monitor some farm-based indicators of Sustainable Development Goals. The statistical unit of the survey is agriculture holdings satisfying the certain specified conditions. The survey has adopted a dual approach of taking both types of agriculture activities-registered (as commercial farming) and non-registered activities operated in household and non-household sectors. Information on the household sector is collected through a representative sample of agricultural households selected with a stratified two-stage sampling design whereas a stratified simple random sample of non-household farms is selected and interviewed. The result is the outcome of collaborative efforts of all the stakeholders involved in the survey. The AGRISurvey program promotes the adoption of an integrated and modular approach, namely the AGRIS method, developed under the Global Strategy for the Improvement of Agricultural and Rural Statistics (GSARS).

Geographic coverage

The survey provides representative data at distrit and municipality level for Chitwan district and Khairahani municipality of the Chitwan district.

Analysis unit

Agricultural holdings

Universe

The survey covers both commercial and non-commercial algriculture holdings in Chitwan district.

Kind of data

Sample survey data [ssd]

Sampling procedure

In the framework of the Agriculture Integrated Survey (AGRISurvey) programme, the pilot agricultural survey covers agricultural holdings in both household and non-household sectors in the district of Chitwan. At the same time, one of the local units (Khairahani Municipality) is also taken as a separate domain to produce estimates at local level. The Khairahani Municipality is one of the seven Palikas (local Governments) in the Chitwan district.

Information on the household sector was collected through a representative sample of agricultural households selected with a stratified two-stage sampling design. The sampling frame of the primary sampling units (enumeration areas) was developed with stratification information using data from the Nepal Population Census 2011. Listing operations were implemented in the selected EAs for selecting a sample of agricultural households (secondary sampling units).

The survey also has interest on commercial agricultural holdings that comprise by definition all non-household farms. As most of these farms are registered in professional and government agencies, related registers were used as primary source to build a sampling frame that was further updated through field operations. A stratified simple random sample of commercial farms were selected and interviewed.

The pilot survey was aimed to produce reliable estimations at the district level as well as for Khairahani municipality in particular at local level. The observations are the agricultural holdings as recommended and defined by FAO. The final sampling units are the agricultural households in the households' sector and the registered commercial farms in the non-household sector.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Listing Form containing structured items with preliminary information such as name of holder, address, contact number, area cultivated, number of livestock and poultry raised and so on was administered for listing the agriculture holdings within the predefined criteria. Questionnaire in Nepali Language comprising Core Module and Production Method and Environment (PME) Module was administered for capturing the detailed information on agricultural activities of the both commercial and non-commercial holdings. The questionnaire is based on the standard model recommended by AGRISurvey Program of the Food and Agriculture Organization (FAO). It was modified to address the Nepalese context as per the series of stakeholders' meetings.

The questionnaire has eight sections: seven under Core Module and one under PME Module. The Survey Questionnaire with Core Module contains the items like holding identification, demographic information (for non-commercial holding), land use and land tenure, area of cultivation and crop production, status of irrigation, use of agricultural inputs, employment status, current and capital expenses of holding and source of information for agricultural activities and so on. The PME Module contains the items like source of energy used by holding, livestock production method, organic manure management practices, access and use of information, infrastructure and public resources by the holding, solid waste management practices, strategies to cope with the effect of natural disasters and climate change and so on. The questionnaire and the listing forms administered in the survey are provided as external resources in the documentation section.

Cleaning operations

The enumeration of the Pilot Agriculture Integrated Survey was conducted by CBS using tablets with CSPro version as a CAPI method of choice. The supervisors were collected the filled-up questionnaires from enumerators using CAPIs in a flash drive in every second day and send to CBS through email and Dropbox. The IT staff in CBS was responsible for compiling and managing the filled-up questionnaires received from the supervisors from the field. The supervisors were allowed to send the collected information to the IT staff in CBS after ensuring the completion of the questionnaires and thoroughly reviewing all the information captured in the tablet. Data processing system was centralized in this survey. In this survey, IT staff in CBS had more advantage of accessing the data immediately. If any inconsistencies were found in data it was informed immediately to the field team so that field staff could confirm the issues before leaving the EA.

Abstract

The 2007/08 Agricultural Sample Census was designed to meet the data needs of a wide range of users down to district level including policy makers at local, regional and national levels, rural development agencies, funding institutions, researchers, NGOs, farmers' organizations, and others. The dataset is both more numerous in its sample and detailed in its scope and coverage so as to meet the user demand.

The census was carried out in order to:

• Identify any structural changes,in the size of farm household holdings, crop and livestock production, farm input and implement use. It also seeks to determine if there are any improvements in the rural infrastructure and the level of agricultural households living conditions;

-Provide benchmark data on productivity, production and agricultural practices in relation to policies and interventions promoted by the Ministry of Agriculture and Food Security and other stakeholders; and

• Obtain data that will be used to address specific issues such as: food security, rural poverty, gender, agro-processing, marketing and service delivery.

Geographic coverage

Tanzania Mainland and Zanzibar

Analysis unit

Community, Household, Individual

Universe

Small scale farmers, Large Scale Farmers, Community

Kind of data

Sample survey data [ssd]

Sampling procedure

The Mainland sample consisted of 3,192 villages. The total Mainland sample was 47,880 agricultural households while in Zanzibar, a total of 317 EAs were selected and 4,755 agricultural households were covered.

The villages were drawn from the National Master Sample (NMS) developed by the National Bureau of Statistics (NBS) to serve as a national framework for the conduct of household based surveys in the country. The National Master Sample was developed from the previous 2002 Population and Housing Census.

The numbers of villages/Enumeration Areas (EAs) were selected for the first stage with a probability proportional to the number of villages/EAs in each district. In the second stage, 15 households were selected from a list of agricultural households in each village/EA using systematic random sampling.

Mode of data collection

Face-to-face [f2f]

Research instrument

The census used three different questionnaires: - Small scale farm questionnaire - Community level questionnaire - Large scale farm questionnaire

The small scale farm questionnaire was the main census instrument and it included questions related to crop and livestock production and practices; population demographics; access to services, community resources and infrastructure; issues on poverty and gender. The main topics covered were:

• Household demographics and activities of the household members
• Land access, ownership, tenure and use
• Crop and livestock production and productivity
• Access to inputs and farming implements
• Access and use of credit
• Access to infrastructure (roads, district and regional headquarters, markets, advisory services, schools, hospitals).
• Crop marketing, storage and agro processing
• Tree farming, agro-forestry, and fish farming
• Access and use of communal resources (grazing land, communal forests, water for humans and livestock, beekeeping)
• Investment activities ( irrigation structures, water harvesting, erosion control, fencing)
• Off farm income and non agricultural related activities
• Households living conditions (housing, sanitary facilities )
• Livelihood constraints
• Poverty Indicators

The community level questionnaire was designed to collect village level data such as access and use of common resources, community tree plantation and seasonal farm gate prices.

The Large Scale Farm questionnaire was administered to large farms either privately or corporately managed.

Cleaning operations

Data editing took place at a number of stages throughout the processing, including: - Manual cleaning exercisePrior to scanning. (Questionnaires found dirty or damaged and generally unsuitable for scanning were put aside for manual data entry ) - CSPro was used for data entry of all Large Scale Farms and Community based questionnaires - Scanning and ICR data capture technology for the smallholder questionnaire - There was an Interactive validation during the ICR extraction process. - The use of a batch validation program developed in CSPro. This was used in order to identify inconsistencies within a questionnaire. - Statistical Package for Social Sciences (SPSS) was used to produce the Census tabulations - Microsoft Excel was used to organize the tables, charts and compute additional indicators -Arc GIS (Geographical Information System) was used in producing the maps. - Microsoft Word was used in compiling and writing up the reports

Abstract

Niger is part of the Living Standards Measurement Study - Integrated Surveys on Agriculture (LSMS-ISA) program. This program has developed a household level survey with a view to enhancing our knowledge of agriculture in Sub-Saharan Africa, in particular, its role in poverty reduction and the techniques for promoting efficiency and innovation in this sector. To achieve this objective, an innovative model for agricultural data collection in this region will need to be developed and implemented. To this end, activities conducted in the future will be supported by four main pillars: a multisectoral framework, institutional integration, analytical capacity building, and active dissemination.

First, agricultural statistical data collection must be part of an expanded and multisectoral framework that goes beyond the rural area. This will facilitate generation of the data needed to formulate effective agricultural policies throughout Niger and in the broader framework of the rural economy.

Second, agricultural statistical data collection must be supported by a well-adapted institutional framework suited to fostering collaboration and the integration of data sources. By supporting a multi-pronged approach to data collection, this project seeks to foster intersectoral collaboration and overcome a number of the current institutional constraints.

Third, national capacity building needs to be strengthened in order to enhance the reliability of the data produced and strengthen the link between the producers and users of data. This entails having the capacity to analyze data and to produce appropriate public data sets in a timely manner. The lack of analytical expertise in developing countries perpetuates weak demand for statistical data.

Consequently, the foregoing has a negative impact on the quality and availability of policy-related analyses. Scant dissemination of statistics and available results has compounded this problem.

In all countries where the LSMS-ISA project will be executed, the process envisioned for data collection will be a national household survey, based on models of LSMS surveys to be conducted every three years for a panel of households. The sampling method to be adopted should ensure the quality of the data, taking into account the depth/complexity of the questionnaire and panel size, while ensuring that samples are representative.

The main objectives of the ECVMA are to:

• Gauge the progress made with achievement of the Millennium Development Goals (MDGs);
• Facilitate the updating of the social indicators used in formulating the policies aimed at improving the living conditions of the population;
• Provide data related to several areas that are important to Niger without conducting specific surveys on individual topics ;
• Provide data on several important areas for Niger that are not necessarily collected in other more specific surveys.

Geographic coverage

National Coverage

Analysis unit

Households

Kind of data

Sample survey data [ssd]

Mode of data collection

Face-to-face paper [f2f]

Cleaning operations

The data entry was done in the field simultaneously with the data collection. Each data collection team included a data entry operator who key entered the data soon after it was collected. The data entry program was designed in CSPro, a data entry package developed by the US Census Bureau. This program allows three types of data checks: (1) range checks; (2) intra-record checks to verify inconsistencies pertinent to the particular module of the questionnaire; and (3) inter-record checks to determine inconsistencies between the different modules of the questionnaire.

The data as distributed represent the best effort to provide complete information. The data were collected and cleaned prior to the construction of the consumption aggregate. Using the same guidelines as were used in 2011, the households that are provided in the data set should have consumption data for both visits. This may not be the case. During the cleaning process, it was found that households had been misidentified which allowed more households to be included in the final consumption aggregate file (see below). The raw data that contains household/item level data that was used to calculate the consumption aggregate has been included in the distribution file.There are 3,614 households and 26,579 individuals in the data.

Surveys for more than 9,500 households were conducted in the growing seasons 2002/2003 or 2003/2004 in eleven African countries: Burkina Faso, Cameroon, Ghana, Niger and Senegal in western Africa; Egypt in northern Africa; Ethiopia and Kenya in eastern Africa; South Africa, Zambia and Zimbabwe in southern Africa. Households were chosen randomly in districts that are representative for key agro-climatic zones and farming systems. The data set specifies farming systems characteristics that can help inform about the importance of each system for a country’s agricultural production and its ability to cope with short- and long-term climate changes or extreme weather events. Further it informs about the location of smallholders and systems at highest risk and permits benchmarking agricultural systems characteristics.

This dataset contains India Economic Survey Agriculture Production Index Numbers. Follow datasource.kapsarc.org for timely data to advance energy economics research.

The web survey was completed in 2017 by over 900 hosts, implementing staff and volunteers engaged in the current Farmer-to-Farmer program cycle (FY14-FY18). The sample for this web survey was created in collaboration with the program implementation team, as no central database of contacts existed. In total, over 1,800 contacts were shared by the implementing partners. In order to receive the web survey, individuals were required to have a unique and valid email address. In the event that an email address was shared by more than one individual, only one copy of the web survey was distributed so as to prevent any individual from responding more than once. The web survey was available to respondents in English, French and Spanish and the data was collected to supplement a program evaluation of the project.

Abstract

The main objective of the Seasonal Agricultural Survey is to provide timely, accurate, reliable and comprehensive agricultural statistics that describe the structure of agriculture in Rwanda mainly in terms of land use, crop area, yield and crop production to monitor current agricultural and food supply conditions and to facilitate evidence-based decision making for the development of the agricultural sector.

The National Institute of Statistics of Rwanda (NISR) has been conducting seasonal agricultural survey since 2012 for the estimation of the national agricultural crop area and production estimates. In 2022/2023 agricultural year, the NISR conducted Seasonal Agricultural Survey (SAS) covering the three agricultural seasons. The SAS provides information used as a tool to assist in addressing key agricultural issues and information needs that will inform policymakers and other stakeholders and allow more effective identification of priority intervention needs.

Geographic coverage

National coverage allowing district-level estimation of key indicators

Analysis unit

Small scale agricultural farms and large scale farms

Universe

The SAS 2023 targeted potential agricultural land and large-scale farmers

Kind of data

Sample survey data [ssd]

Sampling procedure

The total country land was classified into five strata, of which four are agricultural, while the remaining stratum is designated for land not suitable for agriculture. The four agricultural strata are: dominant hill crop land, dominant wetland crops, dominant rangeland, and mixed stratum, all considered suitable for agriculture. The fifth stratum comprises non-agricultural land, including areas occupied by water bodies, forestry plantations, settlements, parks, and protected marshland not utilized for agriculture. The sampling frame excludes land areas covered by tea plantation farms. In 2023 agricultural year, the total sample used was 1200 segments. At first stage,1200 segments were selected and allocated at district level based on the power allocation approach (Bankier, 1988). Sampled segments inside each district were distributed among strata with a proportional-to-size criterion.

At the second stage, 25 sample points were systematically selected, following a special distance of 60 meters between points. For every sample point, a corresponding farm or plot is identified, and the operator is interviewed. The farms therefore constitute the sampling units within each segment. Enumerators locate every sample point, delineate plots in which the sample points fall using high accurate GPS devices and then collect information on land use and other related information. Sampling weights are calculated and applied to the sample data to obtain stratum-level estimates. District estimates are then derived by aggregating the estimates from all strata within the district.

Data collection was done in 1200 segments and 345 large scale farmers holdings for Season A and B, whereas in Season C data was collected in 1769 sites potential to grow season C crops in addition to 513 segments, response rate was 100% of the sample.

During the SAS 2023 exercise, data collection covered three main agricultural seasons A, B and C and was conducted into two separate phases in each season: A. The first phase, known as screening activity (post-planting phase), consists of visiting all sampled segments and demarcating all plots with sampled points with the aim of covering the information related to land area, planted crops and land use.

B. The second phase involves capturing of production data by visiting sampled agricultural plots identified from screening activity as well as all large-scale farmers. To ensure the smooth completion of the SAS workload, NISR employed 137 Enumerators and 23 Team Leaders. All fieldwork staff hold a degree in agriculture sciences and were consistently trained by NISR headquarter staff before starting data collection in each season. Moreover, higher-level supervision was organized and done by staff from NISR who frequently visited the field teams during each phase of data collection to ensure the quality of collected data. For Season A, data collection started on 4th December 2022 and ended on 16th February 2023. For Season B, data collection started on 2nd May 2023 and ended on 30th June 2023. For Season C, data collection started on 10th September 2023 and ended on 30th September 2023.

Mode of data collection

Computer Assisted Personal Interview [capi]

Abstract

The Ministry of Agriculture and Livestock Development (MoALD), and the Central Bureau of Statistics (CBS), with technical and financial assistance of FAO, have jointly conducted a pilot survey in the framework of AGRIS Program in Chitwan district with its affluence of agricultural diversity. It has adopted Production Method and Environment (PME) Module as rotating module along with Core Module for the pilot study as developed by FAO. Along with the piloting of the AGRISurvey Program initiated by FAO, the objective of the survey is to measure key indicators related to area and volume of agriculture production capturing the social, economic and technical dimensions of the holdings as well as providing data to monitor some farm-based indicators of Sustainable Development Goals. The statistical unit of the survey is agriculture holdings satisfying the certain specified conditions. The survey has adopted a dual approach of taking both types of agriculture activities-registered (as commercial farming) and non-registered activities operated in household and non-household sectors. Information on the household sector is collected through a representative sample of agricultural households selected with a stratified two-stage sampling design whereas a stratified simple random sample of non-household farms is selected and interviewed. The result is the outcome of collaborative efforts of all the stakeholders involved in the survey. The successful completion of the survey has also paved the way for the full-fledged implementation of AGRISurvey Program in Nepal. The results from the survey will be useful to planners, policy makers, researchers and other users.

Geographic coverage

The survey provides representative data at distrit and municipality level for Chitwan district and Khairahani municipality of the Chitwan district.

Analysis unit

Non-commercial holdings, Commercial holdings

Universe

The survey covers both commercial and non-commercial algriculture holdings in Chitwan district.

Kind of data

Sample survey data [ssd]

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Listing Form containing structured items with preliminary information such as name of holder, address, contact number, area cultivated, number of livestock and poultry raised and so on was administered for listing the agriculture holdings within the predefined criteria. Questionnaire in Nepali Language comprising Core Module and Production Method and Environment (PME) Module was administered for capturing the deatailed information on agricultural activities of the both commercial and non-commercial holdings. The questionniare is based on the standard model recommendated by AGRISurvey Program of the Food and Agricuture Organization (FAO) It was modified to address the Nepalese context as per the series of stakeholders' meetings. The questionnaire has eight sections: seven under Core Module and one under PME Module. The Survey Questionnaire with Core Module contains the items like holding identification, demografic information (for non-commercial holding), land use and land tenure, area of cultivation and crop production, status of irrigation, use of agricultural inputs, employment status, current and capital expenses of holding and source of information for agricutural activities and so on. The PME Module contains the items like source of energy used by holding, livestock production method, organic manure management practices, acess and use of information, infrastructure and public resources by the holding, solid waste management practices, strategies to cope with the effect of natural disasters and climate change and so on.

The questionnaire and the listing forms administered in the survey are provided as external resources.

Cleaning operations

The enumeration of the Pilot Agriculture Integrated Survey was conducted by CBS using tablets with CSPro version as a CAPI method of choice. The supervisors were collected the filled-up questionnaires from enumerators using CAPIs in a flash drive in every second day and send to CBS through email and dropbox. The IT staff in CBS was responsible for compiling and managing the filled-up questionnaires received from the supervisors from the field. The supervisors were allowed to send the collected information to the IT staff in CBS after ensuring the completion of the questionnaires and thoroughly reviewing all the information captured in the tablet. Data processing system was centralized in this survey. In this survey, IT staff in CBS had more advantage of accessing the data immediately. If any inconsistences were found in data it was informed immediately to the field team so that field staff could confirm the issues before leaving the EA.

Abstract

The Sierra Leone Annual Agricultural Survey (SLAASS 2023) is a key component of Stats SL's efforts to provide up-to-date information on the agricultural sector. The 2023 SLAASS builds upon the successes of previous surveys and aligns with the best international practices. The primary objective of the SLAASS was to collect comprehensive data on crop and livestock production, as well as other relevant agricultural indicators. This information is essential for policymakers, researchers, and other stakeholders to assess the performance of the agricultural sector, identify opportunities for improvement, and inform evidence-based interventions. Specifically, it involved: · Collection of timely data on agricultural production and productivity at both national regional and district levels; · Gathering core data to help develop and review agricultural policies and to guide the implementation of agricultural plans at national and regional levels between agricultural sub-sectors; · Compilation of fundamental statistics that facilitate comparisons in the development of the agriculture sector across the country.

Geographic coverage

National coverage, with the exception of the Western Urban district.

Analysis unit

Agricultural households

Universe

Households involved in agricultural production and livestock rearing, in all the fifteen agricultural districts of the country, were considered for this study.

Kind of data

Sample survey data [ssd]

Sampling procedure

The survey employed a stratified random sampling technique to ensure a representative sample of agricultural households across all five regions and fifteen districts of Sierra Leone with the exception of the Western Urban district. A two-stage sampling method was employed to select households.Both stages of sampling employed probabilistic methods.

The country was divided into districts and within each district, areas called Enumeration Areas (EAs) were identified. A sample of EAs was then selected, followed by a sample of agricultural households (Ag HHs) within each chosen EA. The total number of EAs selected for the survey was 520, with 5,200 households interviewed in total. For each EA, the field team had a list of 10 households.

The survey included households engaged in crop cultivation and/or livestock rearing, regardless of the scale of their operations. However, it did not cover non-household holdings, such as large-scale commercial farms, or sectors like aquaculture, forestry, and fisheries.

The survey generated national, regional, and sub-regional estimates.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

For this survey, two questionnaires were used: the Post Planting (PP) questionnaire and the Post Harvesting (PH) questionnaire. They were administered in each household, preferably to the head of household. They cover two modules, the CORE module and the ILP (Income, Labor and Productivity) module, split into several topics such as household demographics, land ownership, agricultural activities, livestock rearing, labor force composition, and participation in off-farm activities.

The questionnaires are provided as external resources.

Cleaning operations

The PP and PH questionnaire were implemented using CAPI with CSPRO. During data collection, some validation controls were integrated into the app to minimize mistakes when typing households’ answers. After data collection, a processing program designed with SPSS software allowed for cleaning both cases and variables. Duplicated cases were deleted and then the sampling weights were adjusted to take the two non-covered EAs into account (out of the 520 EAs originally planned, 518 were actually completed). Missing, illegal, unlike and incoherent values were detected and then locally imputed objectively in respecting filters. Finally, the necessary tabulation variables were created and then tables were produced according to the tabulation plan designed earlier.

Sampling error estimates

To appreciate the data quality, some tables were supported by sampling errors estimates. Especially, coefficients of variations and standard errors were estimated for a set of indicators for open data publishing purposes.

Abstract

In a country where the economy is predominantly agrarian, agricultural information is essential for policy makers and other users. In this regards, the Central Statistical Agency (CSA) has exerted every effort to provide users and decision makers with reliable and timely agricultural data. The general objectives of CSA's annual Agricultural Sample Survey are: - To collect basic quantitative information on the country's agriculture that is considered essential for development planning, socio-economic policy formulation, food assistance, etc. - To estimates of the total cultivated land area and yield per hectare of major crops (temporary) and estimates of land utilization and quantity of agricultural inputs applied by type for main season. - To estimate the total farm inputs applied area and quantity of inputs by type for major temporary and permanent crops.

Geographic coverage

The 1997-1998 (1990 E.C.) annual Agricultural Sample Survey was designed to cover sedentary rural agricultural population in all regions of the country except urban and nomadic areas of the country.

Analysis unit

Agricultural household/ Holde/ Crop

Universe

Agricultural households

Kind of data

Sample survey data [ssd]

Sampling procedure

SAMPLE DESIGN A two stage stratified sample design was used for the 1997-1998 (1990 E.C) annual Agricultural Sample Survey. All regions except Harari, Addis Ababa, Dire Dawa and Gambella were broken into zones and treated as strata/reporting levels for survey summarization purposes, but for the four mentioned regions, the reporting levels are the regions themselves. The sample design first-stage consists of primary sampling units (PSUs) in all strata which were enumeration areas (EAs). The second-stage sampling units were agricultural households selected as the secondary level sampling units. The survey questionnaires were administered to all agricultural holders in the sampled agricultural households. Based on cost and field enumeration considerations, a fixed number of sample EAs were allocated to each stratum/reporting level taking into consideration the desired precision of the estimates and number of households per stratum. The overall sample number of EAs in a stratum was proportionately allocated to zones/special wereda within stratum based on their number of households. From within each zones/special weredas sample EAs were selected with probability proportional to size, size being the total number of households identified for EAs as obtained from the 1994 Population Census. From each sample EA, 40 agricultural households were sampled systematically without replacement from a newly enumerated list of agricultural households of which the first 25 agricultural households were used to obtain information on crop planted area and crop production of both the “Meher” and “Belg” seasons. However, livestock information was collected from the full sample of 40 selected agricultural households. Information was collected from all twenty five households except for crop-cutting data which was collected form only the last 15 agricultural households, starting from the 11th selected agricultural households. Data was collected on separate questionnaires form each holder within these twenty-five sampled households.

Note: Distribution of number of sampling units by stratum is given in Appendix III of the 1997-1998 annual Agricultural Sample Survey, Volume I report which is provided as external resource.

Mode of data collection

Face-to-face [f2f]

Research instrument

The 1997-1998 annual Agricultural Sample Survey used structured questionnaires to collect agricultural information from selected sample households. List of forms in the questionnaire:
- AgSS Form 90/0: Used to list all agricultural households and holders in the sample enumeration areas. - AgSS Form 90/1: Used to list selected households and agricultural holders in the sample enumeration areas. - AgSS Form 90/2: Used to collect information about crop condition. - AgSS Form 90/3A: Used to list fields and agricultural practices only pure stand temporary and permanent crops, list of fields and agricultural practices for mixed crops, other land use, quantity of improved and local seeds by type of crop and type and quantity of crop protection chemicals. - AgSS Form 90/3B: Used to collect information about quantity of production of crops. - AgSS Form 90/4A: Used to collect information about results of area measurement and field area measurement. - AgSS Form 90/4B: Used to collect information about results of area measurement and field area measurement. - AgSS Form 90/5: Used to list fields for selecting fields for crop cuttings and collect information about details of crop cutting. - AgSS Form 90/6: Used to collect information about cattle by sex, age and purpose.

Note: The questionnaires are provided as external resource.

Cleaning operations

Editing, Coding and Verification: To insure the quality of colleted survey data an editing, coding and verification instruction manual was prepared, and sixty-five editors, coders and verifiers were trained for two days to edit, code and verify the data using the aforementioned manual as a reference and teaching aid. The filled-in questionnaires were edited, coded and later verified by supervisors on a 100% basis before the questionnaires were sent to the data processing unit for data entry. The editing, coding and verification of all questionnaires was completed in thirty-eight days.

Data Entry, Cleaning and Tabulation: Before starting data entry professional staffs of Agricultural Statistics Department of Central Statistical Authority prepared edit specification that used to developed data entry and cleaning computer programs by data processing staffs using Integrated Microcomputer Processing System (IMPS). The edited and coded questionnaires were captured into computers and later cleaned using cleaning program that was developed for this purpose earlier. Thirty data encoders were involved in this process and it took thirty-three days to complete the job. Finally, using tabulations format provided by the subject matter specialist computer program was developed and survey results were produced accordingly.

Sampling error estimates

Estimation procedures of totals and ratios of agricultural variables and the measure of precision of area and production are given in Appendix I and II of the 1997-1998 annual Agricultural Sample Survey, Volume I report which is provided as external resource.

The Input Survey dataset, managed by the Department of Agriculture, Cooperation & Farmers Welfare (DAC&FW), is an essential tool that captures data related to agricultural inputs across India. This survey delves into various aspects of farming, detailing the usage of seeds, fertilizers, pesticides, machinery, irrigation methods, and other critical agricultural resources. By collecting this data periodically, the dataset offers insights into the evolving patterns of input utilization, facilitating the identification of trends, gaps, and potential areas of improvement. Policymakers, researchers, and agricultural stakeholders rely on the Input Survey dataset to devise strategies, frame policies, and implement interventions that aim to enhance the efficiency and sustainability of the Indian agricultural sector.

Abstract

The objective of the GAPS is to strengthen the Multi-Round Annual Crop and Livestock Surveys (MRACLS) that the ministry implements through SRID. The MRACLS is the national agricultural survey on the basis of which SRID releases information on agricultural production and yields of important crops. The ultimate goal of GAPS is to provide more accurate and timely agricultural production estimates at the district, regional, and national levels. The survey is also to offer an opportunity for SRID to experiment with a number of potential improvements with a view to developing the required skills and competencies before scaling up, over time, to all the districts in the country.

As part of the terms of implementing GAPS, MoFA agreed to assign four Agriculture Extension Agents (AEAs) per district for data collection. The Agents were relieved from all extension duties. To distinguish these field data collection officers from other extension agents, they were referred to as District Agricultural Statistical Assistants (DASAs). One officer per district was designated as a District Management Information System (MIS) officer and was given additional responsibility as field supervisor and referred to as District Agricultural Statistical Officer (DASO). A total of 100 DASAs and DASOs were successfully trained and deployed to their districts for GAPS implementation and given the task of collecting and processing datafrom the field.

Geographic coverage

National Level Regions Districts

Analysis unit

Household

Universe

Agricultural household and holder

Kind of data

Census/enumeration data [cen]

Sampling procedure

The GAPS employed a three stage multi-sampling design in response to the Government of Ghana's requirement for reliable agricultural statistics at the national, regional and district levels.

· First Stage Sampling- Selection of 2 Districts from each of the 10 Regions. A total of 20 districts, 2 from each of the 10 regions were randomly selected with probability proportional to size, using districts' population in year 2000 as a measure of size.1. Eleven Metropolitan and Municipal Assemblies (Kumasi, Sunyani, Cape Coast, New Juaben, Accra, Tema, Tamale, Bolgatanga, Wa, Ho and Shama Ahanta East) were excluded from the study, given their urban predominance.

· Second Stage Sampling - Selection of 40 Enumeration Areas (EAs) from each of the 20 Districts. A total of 800 EAs was selected; 40 EAs were randomly selected with probability proportional to size in each district, using the list of EAs compiled by the 2010 Census as a sample frame, and projected total population as a measure of size.2 In the Kassena-Nankana East district, 53 of the 187 EAs compiled by the 2010 census were excluded from the study because of the land disputes prevalent in the area earlier in 2011.

· Third Stage Sampling - Selection of 5 holders At the third stage, five holders were randomly chosen in each EA, using as a sample frame; the full list of all holders, compiled from the Household and Holders Listing questionnaire. This provides a total sample of 4000 holders, consisting of 200 holders per district.

Sampling deviation

Not reported

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The questionnaires used in the minor season survey include the followings:-

(a) The Household and Holding Inquiry - Pre-Harvest questionnaire, also known as the form 2a. This was used to make enquiries on the general characteristics of households and holdings for pre-harvest farming activities during the minor season. Information sought included changes in the household composition, detailed information on livestock, poultry and other animals owned by the selected holders, detailed information on tree crops grown by the selected holders, information on aquaculture practices, inputs, outputs and assets.

(b) The Household and Holding Inquiry - Post-Harvest questionnaire, also known as form 2b. This was used to make enquiries on field practices, inputs and outputs. The following information were sought: inventory of fields, inputs and expenses, Remaining major season production and marketing of crops, minor season crop production and marketing, holding information, shocks and adaptation to shocks, other income generating activities and household health status.

(c) The Household and Holding Inquiry - Pre-harvest field measurements questionnaire known as the form 3. This questionnaire was used to gather data on the nature and characteristics of crop fields and area measurements for individual crop fields for all selected holdings.

(d) Crop Yield Measurement questionnaire also known as the form 4. This was used to seek for data on the yields of food crops such as the cereals, root and tubers, plantain, legumes and nuts, and vegetables.

Cleaning operations

The set of questionnaires used in the minor season survey include:-

(a) The Household and Holding Inquiry – Pre-Harvest questionnaire, also known as the form 2a. This was used to make enquiries on the general characteristics of households and holdings for pre-harvest farming activities during the minor season. Information sought included changes in the household composition, detailed information on livestock, poultry and other animals owned by the selected holders, detailed information on tree crops grown by the selected holders, information on aquaculture practices, inputs, outputs and assets.

(b) The Household and Holding Inquiry – Post-Harvest questionnaire, also known as form 2b. This was used to make enquiries on field practices, inputs and outputs. The following information were sought: inventory of fields, inputs and expenses, Remaining major season production and marketing of crops, minor season crop production and marketing, holding information, shocks and adaptation to shocks, other income generating activities and household health status.

(c) The Household and Holding Inquiry – Pre-harvest field measurements questionnaire known as the form 3. This questionnaire was used to gather data on the nature and characteristics of crop fields and area measurements for individual crop fields for all selected holdings.

(d) Crop Yield Measurement questionnaire also known as the form 4. This was used to seek for data on the yields of food crops such as the cereals, root and tubers, plantain, legumes and nuts, and vegetables.

Response rate

The repond rate reported was 70%

Sampling error estimates

No estimates of sampling error given

Data appraisal

District information and communication infrastructure was upgraded in the 20 districts to improve data collection and management. Each office was provided with a computer, printer, voltage stabilizers, an internet modem, 5 GPS units, and other field equipment. Motorbikes were also provided to the DASAs to enhance mobility.

Similarly, the SRID head office was also upgraded with ICT equipment to facilitate work.To oversee the implementation of the pilot survey a cross-sectoral steering committee was established.

At the end of each phase of implementation, a team was put together to assess the institutional and financial feasibility of scaling up GAPS, and both assessment reports are available at SRID.

Abstract

NASC is an exercise designed to fill the existing data gap in the agricultural landscape in Nigeria. It is a comprehensive enumeration of all agricultural activities in the country, including crop production, fisheries, forestry, and livestock activities. The implementation of NASC was done in two phases, the first being the Listing Phase, and the second is the Sample Survey Phase. Under the first phase, enumerators visited all the selected Enumeration Areas (EAs) across the Local Government Areas (LGAs) and listed all the farming households in the selected enumeration areas and collected the required information. The scope of information collected under this phase includes demographic details of the holders, type of agricultural activity (crop production, fishery, poultry, or livestock), the type of produce or product (for example: rice, maize, sorghum, chicken, or cow), and the details of the contact persons. The listing exercise was conducted concurrently with the administration of a Community Questionnaire, to gather information about the general views of the communities on the agricultural and non-agricultural activities through focus group discussions.

The main objective of the listing exercise is to collect information on agricultural activities at household level in order to provide a comprehensive frame for agricultural surveys. The main objective of the community questionnaire is to obtain information about the perceptions of the community members on the agricultural and non-agricultural activities in the community.

Additional objectives of the overall NASC program include the following: · To provide data to help the government at different levels in formulating policies on agriculture aimed at attaining food security and poverty alleviation · To provide data for the proposed Gross Domestic Product (GDP) rebasing

Geographic coverage

Communities (in Enumerated Areas).

Analysis unit

Community

Universe

The population units are communities encompassing the designated enumeration areas, where household listing was performed.

Kind of data

Census/enumeration data [cen]

Sampling procedure

Focus group interviews were performed in communities overlapping with in the EAs selected for the extended listing operation. Accordingly, a focus group discussion in a total of 26,555 communities were undertaken to administer the community level questionnaire. It is important to note here that the results from the community survey are unweighted results and all the tables produced from the community level data are only from the 26,555 communities interviewed.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The NASC community listing questionnaire served as a meticulously designed instrument administered within every community selected to gather comprehensive data. It encompassed various aspects such as agricultural activities in the community, infrastructures, disaster, etc. The questionnaire was structured into the following sections:

• Identification of the community • Respondent Characteristics (Name, Sex, age) • Agricultural Activities in the Community • Disasters and Shocks • Community Infrastructure and Transportation • Community Organizations • Community Resources Management • Land Prices and Credit • Community Key Events • Labour

Cleaning operations

Data processing of the NASC household listing survey included checking for inconsistencies, incompleteness, and outliers. Data editing and cleaning was carried out electronically using the Stata software package. In some cases where data inconsistencies were found a call back to the household was carried out. A pre-analysis tabulation plan was developed and the final tables for publication were created using the Stata software package.