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

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 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.

Abstract

The National Institute of Statistics and Census (INEC), through the Directorate of Agricultural and Economic Statistics (DEAGA) executed the Annual Agricultural Area and Production Survey (ESPAC), 2010.

This survey was carried out in Ecuador at the national level, in all provinces, except for the Galapagos and unassigned areas such as Las Golondrinas, Manga del Cura and El Piedrero. It covered all properties with total or partial agricultural activity, called Agricultural Production Units (UPAs), selected by the Area Sampling and List Sampling, a methodology that is applied in this survey.

The main objective of the survey is to provide information on the agricultural sector, referring to planted and/ or sown, harvested areas, to the production and sales of permanent and transient crops, as well as the existence and movement of Cattle, Pigs, Sheeps, Other Species , existence of Field Birds, and Poultry Plants and Employment of Workforce.

This was done in order to have information for formulating crop plans and diversification of agricultural production, formulating price rules and incentives to improve agricultural production, establish a system of equitable distribution of production in the different areas of the country, contribute to the sectoral economic analysis, as well as, the preparation and execution of import and export policies for agricultural products so that the country, through the national government, can promote policies that strengthen the agricultural sector.

Geographic coverage

Regional Coverage (Data only available for one region: Azuay).

Analysis unit

Agricultural holdings

Universe

All properties with total or partial agricultural activity called Agricultural Production Units (UPAs), selected in the sample.

The survey covers the rural area of continental Ecuador. However, populated centers, the province of Galapagos and areas not assigned to the provinces such as Las Golondrinas, Manga del Cura and El Piedrero are excluded.

Kind of data

Sample survey data [ssd]

Sampling procedure

The Annual Agricultural Area and Production Survey (ESPAC) 2010 uses the multi-frame sampling methodology, which consists of a combination of Sample Area Frame (MMA) and a Sample List Frame (MML). The sample frames of each of the provinces of the territory used in the III National Agricultural Census of the year 2000 are applied.

The MMA sampling consists of dividing the total area of the country into small areas without over position or omission, called Primary Sampling Units (UPMs). A UPM is an area of 10 km2 on average and is delimited by natural and/ or cultural accidents easily identifiable on the ground. For the operation of the survey, these areas were outlined on an aerial photograph and a map. A second division is made as each Primary Sampling Unit (UPM) is divided into a specific number of Sampling Segment (SM). An SM is an extension of land with an area of approximately 2 km2 or 200 hectares, delimited by natural and/ or cultural accidents easily identifiable on the ground. The set of all SMs constitutes the area frame (MMA) and covers the continental territory excluding the province of Galapagos and the areas not assigned to the provinces. The SMs are clearly marked and delineated on an aerial photograph and generally contain one or more UPAs or one or several non-UPAs.

The MML is a statistical procedure that consists of extracting information from all or a sample of the elements found in the list frame (MML). The MML is a Directory prepared by the INEC where the UPAs that meet certain pre-established criteria are recorded. In the MML are the main UPAs, identified by INEC, the Ministry of Agriculture and Livestock (MAG) and the private sector, based on their importance in the contribution to production.

The sample size consists of randomly selecting a subsample of 2,115 Sample Segments and the list frames from the set of the MMA. In total, a sample of 4000 Agricultural Production Units were obtained, corresponding to 17.23% and 26.25% respectively, in relation to the one investigated in the III National Agricultural Census.

Mode of data collection

Face-to-face paper [f2f]

Cleaning operations

In the Annual Agricultural Area and Production Survey 2010, the Expert System is used. This is a computer system that allows the coding, validation and individual criticism of the data collected.

The person conducting the survey collects the information in the questionnaires, during the day, and at night it is delivered to the digitizer/ operator who enters the information into the computer in the Expert System. Once the information is entered, it is encrypted, validated and verified. In certain cases, the questionnaire is delivered to the field staff so that the information is verified again, and the data is re-entered.

Once the information of the segments and list is collected, a database is created.

It involves the following steps:

1.- Criticism - Information coding: The critical coding process is included in the computer system prior to the delivery of the updated validation manual by the Agricultural Statistical Unit of the Economic Statistics Production Department (DECON).

2.- Digitizing: At this stage of data entry, the following processes are considered: Questionnaire Entry, Coverage Control, Validation (Consistency of Questions, Associates, Vegetative Cycles that are the life periods of a crop, Intersections of the Area Framework and List Framework ), Analysis of yields and backups,

3.- Validation and debugging: In the system validations are implemented in order to stop the capture when the information captured in the questionnaire is inconsistent and then be able to take the necessary measures to correct the information. It consists of analyzing and debugging the information contained in the file so that it is left without errors, omissions, inconsistencies or inconsistencies. The information is validated in an automated way in order to guarantee congruence between variables and generating a database file and the different publications generated by the National Institute of Statistics and Census, (INEC).

4.- Tabulation: The final step is the tabulation of the obtained survey results.

Response rate

In the Annual Agricultural Area and Production Survey of the year 2010, the non-response rate as other rejection indicators go hand in hand with the sample design implemented, so this rate is not unique or general.

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 makes it possible to provide information on the physical characteristics of cultivated plots (geo-location, area) and major investments made at their level (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 2021-2022 edition of the EAA is characterized by the integration of the ILP (Revenue, Labor and Productivity) module. The introduction of this module makes it possible to collect the information necessary for the calculation of SDGs 2.3.1 and 2.3.2. In addition, the basic module of the 50x2030 questionnaire allows the collection of data for the calculation of SDG 5.a.1 and CAADP indicators (3.1i, 3.1ii, 3.2i, 3.2ii, 3.2iii and 4.1i) .

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

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 EAA was built on a two-stage survey, with enumeration districts (DRs) as primary units (PU) and agricultural households as secondary units (US), 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, the sampling plan has integrated from this campaign , a first-degree stratification, induced by that of the second degree, to better reflect the different 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. 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.

Four strata were thus formed as follows: - the “rain-fed only” stratum which groups together all the households practicing only rain-fed 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 “Rain-fed-breeding” stratum made up of households that practice both rain-fed 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 method of Bankier (1988) developed in the methodological guide on the Practices of Master Sampling Bases (pp. 79-81) of the Global Strategy (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.

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, labor and agricultural productivity.

Response rate

The overall response rate is 94% for the first phase of the survey while it is 89% for the second phase.

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 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

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 questionnaire

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. 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

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

In this regard, the National Institute of Statistics of Rwanda conducted the Seasonal Agriculture Survey (SAS) from November 2017 to October 2018 to gather up-to-date information for monitoring progress on agriculture programs and policies in Rwanda, including the Second Economic Development and Poverty Reduction Strategy (EDPRS II) and Vision 2020. This 2018 RSAS covered three agricultural seasons (A, B and C) and provides data on background characteristics of the agricultural operators, farm characteristics (area, yield and production), agricultural practices, agricultural equipments, use of crop production by agricultural operators and by large scale farmers.

Geographic coverage

National coverage allowing district-level estimation of key indicators

Analysis unit

This seasonal agriculture survey focused on the following units of analysis: Agricultural Operators and Large Scale Farmers

Universe

The RSAS 2018 targeted potential agriicultural land and large scale farmers

Kind of data

Sample survey data [ssd]

Sampling procedure

In order to provide the basis for conducting probability surveys based on complete coverage of the farm level, and as a better way of collecting agricultural data and finding better precise survey estimates, SAS used a Multiple-Frame Sampling (MFS) methodology by which, area frame was constructed and survey sample was drawn from it. Apart from that, a list frame of large-scale farmers (LSF), with at least 10 hectares of agricultural holdings, was done to complement the area frame just to cover crops mostly grown by large scale farmers and that cannot be easily covered in area frame.For detailed information regarding the sampling procedures, refer to the component of Methodology in the report.

Mode of data collection

Face-to-face [f2f]

Research instrument

There were two types of questionnaires used for this survey namely Screening questionnaire and plot questionnaires. A Screening questionnaire was used to collect information that enabled identification of a plot and its land use using the plot questionnaire. For point-sampling , the plot questionnaire is concerned with the collection of data on characteristics of crop identification, inputs (seeds, fertilizers, labor …), agricultural practices, crop production and use of production. All the surveys questionnaires used were published in English.

Cleaning operations

The CAPI method of data collection allows the enumerators in the field to collect and enter data with their tablets and then synchronize to the server at headquarters where data are received by NISR staff, checked for consistency at NISR and thereafter transmitted to analysts for tabulation using STATA software, and reporting using office Excel and word as well.

Response rate

Data collection was done in 780 segments and 222 large scale farmers holdings for Season A, whereas in Season C data was collected in 232 segments, response rate was 100% of the sample.

Data appraisal

All Farm questionnaires were subjected to two/three rounds of data quality checking. The first round was conducted by the enumerator and the second round was conducted by the team leader to check if questionnaires had been well completed by enumerators. And in most cases, questionnaires completed by one enumerator were peer-reviewed by another enumerator before being checked by the Team leader.

Abstract

Lesotho has been undertaking Agricultural Production Survey (APS) annually since 1973/1974 Agricultural Year. The APS estimates are usually available by the end of October for summer and winter crops. In addition to APS, the Bureau of Statistics (BOS) conducts Crop Forecasting Survey (CFS) as early as April every year. The main purpose of the forecasts is to inform the planners and policy makers about the expected crop production to make effective decisions concerning availability of food in the country and to make necessary preparations if there is shortage of food.

Crop forecasting is a process of estimating the most likely yield and production of cereals based on known facts at the time of making the forecast. Assumptions used for forecast are based on conditions such as weather and damage by pests. Forecasts assume that there is no change in production of crops between date of forecasting and final harvest.

Geographic coverage

Rural settlement

Analysis unit

Agricultural household and crop type

Universe

The survey covers all selected sample agricultural households.

Kind of data

Sample survey data [ssd]

Sampling procedure

A stratified multi-stage sampling scheme was adopted for the selection of the sample for the APS. Large enumeration areas constituted Primary Sampling Units (PSUs) and individual agricultural holdings (farming households) constituted Secondary Sampling Units (SSUs) for the estimation of land use, crop areas and livestock population. Fields under Maize, Sorghum and wheat formed the third sampling unit for the estimation of crop yield. Two sub-plots for crop cutting in each selected field formed the ultimate units for yield estimation. About 100 PSUs in the rural areas that covered about 2,000 farming households were selected. A maximum of five fields, each for Maize, Sorghum and their mixtures per PSU constituted the sample for the crop forecasting exercise that covered summer season only. Wheat which had already reached its maturity stage covers 10 fields per PSU following the APS sampling procedure. The PSUs have been selected with probability proportional to size, the size estimate being the number of households being obtained from the 2016 Population and Housing Census. In each PSU, an average of 20 agricultural households was selected through systematic sampling from a list of all agricultural households.

Mode of data collection

Face-to-face [f2f]

Research instrument

The 2018-2019 APS questionnaire comprises of the following sections: - The demographic characteristics - Income Level - Contribution to farming - Livestock ownership - Field ownership - Loans access - Decision maker

Abstract

The main target of the FSS 2007 was to obtain information about structure and typology of the agricultural farms and their agricultural activities in Latvia in accordance with EU and national requirements.

Geographic coverage

National

Analysis unit

Farms

Universe

All economically active farms - farms, which produce agricultural production, were involved in the target population for the FSS 2007. The definition of a holding is in line with the EU Farm Structure Survey definition. Agricultural holding is a single unit both technically and economically, which has a single management and the output of which is agricultural production. The holding may also provide other supplementary (non-agricultural) products and services.

Kind of data

Sample survey data [ssd]

Sampling procedure

The Latvian farm structure survey 2007 was made as combination of exhaustive enumeration and sample. All units were sampled in the part of sampling frame where exhaustive enumeration was done. Stratified simple random sampling was done in the sampling part of the frame. For more details see 3.3.2 of the Methodological Report available as external resources.. For each farm structure survey new sample is drawn. Procedure for sample selection is self-made using SPSS®. In 2007 total sample size comprised 58.0 thousand holdings.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire form of FSS 2007 was developed in co-operation with the Ministry of Agriculture and other State institutions concerned. The list of characteristics included in the survey was compliant with EU requirements concerning the Farm Structure Survey 2007 (Commission Regulation (EC) No 204/2006 of February 6, 2006 adapting Council Regulation (EEC) No 571/88 and amending Commission Decision No 2000/115/EC with a view to the organization of Community surveys on the structure of agriculture holdings in 2007).

For all types of farms (private farms, state farms and statutory companies) Latvia has only one type of questionnaire form. The questionnaire form of FSS 2007 was developed in co-operation with the Ministry of Agriculture and other State institutions concerned.The questionnaire form was designed so that later it can easily be processed on scanners. The size of the questionnaire form is 8 pages. The following parts are included: · General description of the farm and holder (user) · Land use · Utilisation of arable land · Number of livestock and poultry · Stock of agricultural machines · Farm storage facilities of manure and irrigation devices · Farm labour force, permanent and temporary · Rural development

Cleaning operations

Data Control of the FSS 2007 was carried out as follows: Manual Control: The first visual control of questionnaire forms was done in regional offices. Regional supervisory stuff and other staff in regional offices carried out a preliminary verification to see if the forms were filled in correctly and completely. Verification and Logical Control: For data entering scanners were used. After scanning the verification of the logical and arithmetical control was done in the CSB in accordance with specially developed verification programme. There were approximately 200 different logical and arithmetical controls. After interviewers or farmers were contacted by phone the re-addressing of errors was done. Due to the error shown by logical control program, if necessary, land users were contacted by phone in, e.g., to find out volume of sown areas, number of livestock, etc. thus needed information was obtained, and there non-response in such cases does not exist. Comparison of the FSS with other data sources: After logical control was finished, the FSS data were compared with information from Statistical Farm Register (information on holder (user) of farm, land areas belonging to farm and other), with information from other statistical surveys (previous livestock survey), with Animal Register information (Agricultural Data Centre) on June 1, 2007, and with the list of Organic farms received from Ministry of Agriculture and Integrated Administration an Control System – IACS (Rural Support Service)

Response rate

Details on non-response are available in section 3.4.5 of the Methodological Report available as external resources.

Sampling error estimates

Please see section 3.5.2 of the Methodological Report (available as external resources) for a detailed explanation procedure used to estimate sampling errors.

Data appraisal

Comparison of the FSS with other data sources: After logical control was finished, the FSS data were compared with information from Statistical Farm Register (information on holder (user) of farm, land areas belonging to farm and other), with information from other statistical surveys (previous livestock survey), with Animal Register information (Agricultural Data Centre) on June 1, 2007, and with the list of Organic farms received from Ministry of Agriculture and Integrated Administration an Control System - IACS (Rural Support Service).

International comparability Eurostat Statistical Office of the European Union (Eurostat) on its homepage published information on agriculture on EU-27 and on each country separately. Main indicators are available in section: Main tables/ Agriculture, forestry and fisheries/ Agriculture/ Structure of agricultural holdings. More detailed Farm Structure Data: Database/ Agriculture, forestry and fisheries/ Agriculture/ Structure of agricultural holdings. Eurostat has published reports on agriculture in EU countries on its webpage: Publications/ Collections/ Statistics in focus.

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 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 AGRIS Ghana Pilot test was implemented in 4 districts of the Ashanti Region (Ahafo Ano South, Asante Akim North, Ejura Sekye Dumase, and Sekyere Afram Plains) in February 2018, to collect information on: - Crop and livestock production as well as data on farm characteristics, diversification and structures; - Farm revenues and expenses; - Type of labour used by the agricultural holding; - Farming practices and their linkages with the natural environment; - Farm machinery, equipment and assets.

The general objective of the pilot was to customize AGRIS instruments and methodologies for adoption as a standard tool to efficiently gather relevant and reliable agricultural data for policy making and monitoring the Sustainable Development Goals (SDGs).

The specific objectives of the AGRIS Ghana pilot were as follows: - Elaborate the overall set up of AGRIS in Ghana; - Customize the content of the AGRIS questionnaire to the Ghanaian context; - Assess the overall efficiency of the customized, integrated questionnaires and their feasibility in terms of length, flow, use of Computer Assisted Personal Interviewing (CAPI), and integration of core and rotating modules; - Assess the difficulty and relevance of each question, each section and each generic questionnaire for different types of holdings; - Test the use of Survey Solutions software to implement CAPI data collection, and the current version of the CAPI questionnaires; - Assess the relevance of the training material developed to train survey enumerators and supervisors.

Geographic coverage

District level coverage. The 4 district covered by the survey were: - Ahafo Ano South (CORE+PME) - Asante Akim North (CORE+MEA) - Ejura Sekye Dumase (CORE+LABOUR) - Sekyere Afram Plains (CORE+ECO)

Analysis unit

Agricultural holdings in the household sector

Universe

All households, agricultural or not, in the 4 surveyed districts.

Kind of data

Sample survey data [ssd]

Sampling procedure

Definition of Agricultural Holding As stated in the manual of the World Programme for the Census of Agriculture (FAO, 2015), an agricultural holding is defined as an economic unit of agricultural production under single management comprising all livestock and poultry kept, and all land used wholly or partly for agricultural production purposes, without regards to title, legal form, or size. Single management may be exercised by an individual or household, jointly by two or more individuals or households, by a clan or tribe, or by a juridical person such as a corporation, cooperative or government agency (FAO, 2015).

1. The Sampling Frame The initial plan for the pilot survey was to consider as statistical units, agricultural holdings covering both the household and the non-household sectors, as proposed in the AGRIS methodology. For holdings in the household sector, no updated list of agricultural households in the country was available, and therefore a sampling frame needed to be established. To do so, the 2010 Population and Housing Census (PHC) was used to build a frame of EAs which were the primary sampling units (PSUs) of the adopted sampling design. After selecting the sample of PSUs in the four districts of interest, a complete list of holdings in the selected EAs was built. All households, agricultural or not, present in the selected EAs were listed.

Holdings in the non-household sector are by definition, economic units such as commercial farms and government institutions engaged in agricultural production. GSS and MoFA provided a list of these holdings to be used as sampling frame. Therefore, the plan was to use as the overall sampling frame a multiple frame composed of the two lists described above (one for the household sector and one for the non-household sector). However, after further discussion and evaluation, it was determined that the list of holdings in the non-household sector could not be considered as a reliable sampling frame for the targeted units. As a consequence, the data collected for the 80 non-household units could not be analysed to represent holdings in the nonhousehold sector.

1. The Sampling design A stratified two-stage sampling design was used for the holdings in the household sector. The PSUs were the EAs and the secondary sampling units (SSU) were the agricultural households.

2. The Sampling Size For holdings in the household sector, the calculation of sample size was performed fixing the minimum degree of precision required for the final estimates of main variables of interest. The variable considered to determine the sample size was the area of the agricultural land owned by the households. This information had been collected during the 2012-2013 Ghana Living Standards Survey 6 (GLSS6). Therefore, data from this survey was used to estimate the coefficient of variation (CV) of the variable of interest in the chosen four districts. It should be noted that the estimation domain of the GLSS6 was the region. For that survey, a two-stage sampling design was used and the PSUs (EAs) were selected in each region with the probability proportional to size (PPS). The measure of size was given by the number of individuals in each region, provided for the chosen districts for the AGRIS-Ghana pilot survey by the GLSS6. For the estimation of the CV of the households' agricultural land, it was assumed that the EAs sampled in GLSS6 and located in the target districts were selected in these districts with the same method of selection (PPS). Thus, the households included in the sample were supposed to have been selected with a two-stage sampling design.

The formula for the computation of the sampling size can be consulted in the final report of the survey.

The number of households to be surveyed in each PSU is fixed to 10. Therefore, the size of the sample of PSU is the size of the sample of the households divided by 10.

1. Agricultural holding definition As stated in the manual of the World Programme for the Census of Agriculture (FAO, 2015), an agricultural holding is defined as an economic unit of agricultural production under single management comprising all livestock and poultry kept, and all land used wholly or partly for agricultural production purposes, without regards to title, legal form, or size. Single management may be exercised by an individual or household, jointly by two or more individuals or households, by a clan or tribe, or by a juridical person such as a corporation, cooperative or government agency (FAO, 2015).

Sampling deviation

As mentioned in the sampling procedure section, holdings in the non-household sector were not included in the survey, as per initial plan, due to a problem in the listing frame provided by the Ghana Statistical Service.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The AGRIS Core module integrates with the Production Methods and Environment module (Core+Pme) collected information on household and holding characteristics, agricultural production and practices used for agricultural production by holdings.

A full appraisal of the contents of the questionnaires can be get by downloading the questionnaires in the documentation section.

Cleaning operations

The first level of data quality checks was implemented through Survey Solutions, which allows the programmer to develop a questionnaire containing skips and validation rules to minimize errors and inconsistencies in the collected data.

After data collection, data editing and preparation was performed using STATA.

Response rate

Out of 370 households planned for interview, 366 were interviewed (98.91% response rate).

Sampling error estimates

Details on the estimates of sampling error are provided in the final survey report.

Abstract

• The agricultural integrated survey is conducted to collect statistical information on the agriculture in the Republic of Armenia.

• AGRIS is based on FAO International Statistical Experience

• AGRIS questionnaires and tools (CAPI application, manual, other documents) were developed to collect internationally comparable statistics

• AGRIS content and tools are adapted to reflect the nature and policy of Armenia's agriculture

• The survey on agricultural production in Armenia in 2020 has in total 5 waves of data collection (visits).

The potential of AGRIS 1. AGRIS data - will be the basis for the development, implementation and evaluation of agricultural policy - will improve market efficiency - will support research implementation 2. AGRIS can be the base for an effective agricultural statistical system 3. AGRIS is available and manageable

Geographic coverage

Kotayk Armavir Tavush Shirak

Analysis unit

Agricultural households

Universe

Farm holdings

Kind of data

Sample survey data [ssd]

Sampling procedure

The design followed the principles and recommendations of the Handbook on the Agricultural Integrated Survey (AGRIS). A link tothe Handbook is provided under Technical Documents.

Framing: The sampling strategy is based on the Multiple Frame Sampling (MSF) approach using the two agricultural frames of the Agricultural Census 2014: · List Frame 1: Agricultural holdings of the household sector · List Frame 2: Agricultural holdings of the non-household sector

For details of the sampling design please refer to the Sampling Strategy and Plan attached as a Technical Document.

Sampling deviation

Terms of using replacement list:

Addresses from replacement list should be used only in sequential order and in the following cases: The household cannot be found at a given address. The enumerator visited the address at least 3 times and was unable to meet with members of the household. The household refuses to take participate the survey. For large holdings no replacement is available.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The Agricultural Integrated Survey is conducted by the interviewers via Computer Assisted Personal Interviewing (Survey Solutions, SuSo) using exclusively the following digital questionnaires:

Inception questionnaire Quarterly questionnaire Annual questionnaire

The questionnaires were completed by interviewer during the visits to holdings in the course of the year, through direct interviews with the holder of the holding or another adult (at least 18 years old) member of the holding who is well-informed of the holding's agricultural activities.

The inception questionnaire consists of a cover page, survey preparation and the following 6 sections: - General information on the holding - Land use by parcels as of 1st January, 2020 - Stocks of agricultural products produced on the holding (as of 1st January, 2020 - Livestock numbers - Buildings on the holding - Agricultural cooperatives

The quarterly questionnaire consists of a cover sheet, general information on the holding and the following 6 sections: - Crop area sown and production during the last two quarters (1st of January - 30th of June 2020) - Use of Fertilizers and Pesticides/Herbicides - Livestock and Poultry - Production and processing of crop and animal products during the last two quarters (1st of January - 30th of June 2020) - Labour on the holding - Economic information about expenditures of agricultural holdings for agricultural production carried out during the last two quarters (1st of January - 30th of June 2020)

The annual questionnaire consists of a cover sheet, general information on the holding and the following 10 sections: - Crop area sown and production during the last two quarters (1st of July - 31st of December 2020) - Use of crop product durinig the last year - Use of Fertilizers and Pesticides/Herbicides - Livestock and Poultry - Production and processing of crop and animal products during the last two quarters - Use of pasture during 2020 (1 Jan - 31 Dec 2020) - Labour on the holding - Economic information about expenditures of agricultural holdings for agricultural production carried out during the last two quarters - Access to agricultural production warehouses (From January 1st to December 31st 2020) - Economic profiles of the holding (From January 1st to December 31st 2020)

The questionnaires were jointly developed by ARMSTAT, FAO and ICARE. Discussions were aimed at matching indicators available in the sections to the national peculiarities, particularly crop list and farm animals' gender and age group.

Cleaning operations

Supervisors and controllers checked and edited the filled questionnaires.

The computer software helped in checking arithmetic and logic of the responses.

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.

Abstract

The CrPS is conducted quarterly to generate production estimates for crops other than cereals at the national, regional and provincial levels.

Of the 230 crops covered, the individual estimates of the 19 crops highlighted in the Quarterly Report on the Production in Agriculture are released at the national level while the rest were lumped as Other Crops. Provincial level estimates are available on an annual basis.

The survey aims to support the data needs of planners, policy and decision makers and other stakeholders in the agricultural sector, and to provide periodic updates on crop related developments.

The survey adopts two-stage sampling with the municipality as the primary sampling unit and the households as the secondary sampling unit.

Geographic coverage

Provinces covered for Crops Production Survey are the following: CAR: Abra Apayao Benguet Ifugao Kalinga Mt. Province ILOCOS REGION:
Ilocos Norte Ilocos Sur La Union Pangasinan CAGAYAN VALLEY: Cagayan Isabela Nueva Vizcaya Quirino CENTRAL LUZON: Aurora Bataan Bulacan Nueva Ecija Pampanga Tarlac Zambales CALABARZON: Batangas Cavite Laguna Quezon Rizal MIMAROPA: Marinduque Mindoro Occidental Mindoro Oriental Palawan Romblon BICOL: Albay Camarines Norte Camarines Sur Catanduanes Masbate Sorsogon WESTERN VISAYAS: Aklan Antique Capiz Guimaras Iloilo Negros Occidental CENTRAL VISAYAS: Bohol Cebu Negros Oriental Siquijor EASTERN VISAYAS: Biliran Eastern Samar Leyte Northern Samar Southern Leyte Samar ZAMBOANGA PENINSULA: Zamboanga City Zamboanga del Norte Zamboanga del Sur Zamboanga Sibugay NORTHERN MINDANAO: Bukidnon Camiguin Lanao del Norte Misamis Occidental Misamis Oriental DAVAO REGION: Compostela Valley Davao City Davao Norte Davao Oriental Davao del Sur SOCCSKSARGEN: North Cotabato Saranggani South Cotabato Sultan Kudarat CARAGA: Agusan del Norte Agusan del Sur Surigao del Norte Surigao del Sur ARMM: Basilan Lanao Del Sur Maguindanao Sulu Tawi-Tawi

Analysis unit

An agricultural production-related survey with a household-level questionnaire which would have provincial unit of analysis.

Universe

The survey covers all small farm producers and plantation farms of all agricultural crops, other than palay and corn, nationwide.

Kind of data

Sample survey data [ssd]

Sampling procedure

The survey employs two-stage sampling design with municipality as the primary sampling unit (psu) and farmer-producer as the secondary sampling unit (ssu).

Farms are classified as small farms and plantation farms. For small farms, crops are classified based on coverage of the Farm Price Survey, e.i. Farm Price Survey and non-Farm Price Survey. For crops under Farm Price Survey, the top five producing municipalities based on the volume of production were chosen as psu. In each municipality, five sample farmer-producers as ssu were enumerated.

For small farms of all other crops not covered under Farm Price Survey, top two to three producing municipalities were chosen as psus. In each municipality, three sample farmer-producers as ssu were enumerated.

This scheme is applied to each of the crops being covered every survey round. It is possible for a farmer-producer to be a respondent for several crops, which he plants and harvests during the reference quarter.

Classification for plantation farms is based on the cut-off on area planted. Each survey round covers a maximum of 5 plantations by crop.

The above scheme was adopted since 2005 to date.

The sampling design for CrPS has undergone several changes. In 1988 until 2000, the survey adopted three stage sampling or 5x5x5. This is intended to represent the five (5) municipalities as the primary sampling unit, five barangays as the secondary sampling unit and five (5) households as the ultimate sampling unit. In May 2000, a two stage sampling was adopted with the five (5) top producing municipalities as the primary sampling unit and five farmers-producers as the secondary sampling unit.

For coconut, the sampling procedure was in collaboration with the PCA which was developed in 1996. The Bureau was responsible for the survey methodology and data processing while the PCA was responsible for the data collection.

A three-stage sampling is being employed. The domain of the survey is the municipality, classified as coastal flat, coastal upland, inland flat, and inland upland. The barangays, also classified according to the classification used for the municipalities, serve as the first stage. The second stage is the two coconut farmers from each sample barangay drawn using simple random sampling. The third stage is the 10 sample coconut trees lying along the longest diagonal line bisecting the parcel. The sampling design cut across the small and plantation farms and remain the same until the frame is updated or the sampling design is changed.

The survey was piloted in Davao Region provinces which started on the fourth quarter of 1996. This was replicated in the Western Visayas provinces in the first quarter of the following year. The provinces in the rest of the regions conducted this survey beginning in June 1997. The PASOs and the Provincial Coconut Development Managers jointly validate the results. The PASOs forward the result to the region for further joint review by the RASOs and the Regional Managers.

Mode of data collection

Face-to-face [f2f]

Research instrument

The title of the questionnaire is Crops Production Survey, and is in the English language. This captures production, area, and bearing trees for the current quarter and last year same period. A remaks column is also provided for the explanation on the changes this year versus last year.

The questionnaire also serves as summary worksheet for the small farms and plantation farms and provinvial summary.

The instrument is a one-page questionnaire which could accommodate as many as five crops. The number of sheets may vary depending on the number of crops covered in the province.

Cleaning operations

Editing is done in four stages during the data review. The initial stage is at the collection point while with the respondent. This starts with the completeness and correctness of the entries in the answer grid. The yield per unit area, or kilograms per bearing tree and planting density were computed and verified with the respondents when these are out of range. The range varies by crop and reference period. The farmer-respondents are asked on the climatic condition a quarter ago up to the prevailing quarter and explanations on the change in the level against the same period a year ago. During the Provincial Data Review, Regional Data Review and National Data Review, data editing is done after encoding and data transfer from one form or system to another during the generation of estimates.

Sampling error estimates

Not estimated.

Data appraisal

The estimates are subjected to three levels of data review and validation. These are the Provincial Data Review (PDR), Regional Data Review (RDR) and National Data Review (NDR).

Accross all data validation levels, a set of parameters is being used as guideposts and the available data from other agencies.

The existing indicators also accounts for the situation in the province. At the RDR, the data is assessed to reflect the situation of the region and the levels in comparison between and among the provinces in the region. At the NDR, the data are validated in comparison to national level data and the data between and among the regions.

To some extent and for valid reasons, this involves adjustment of the levels of the data generated.

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.

Abstract

The Nepal Agriculture and Food Security Project (AFSP) aims to improve the livelihood of poor farmers by increasing agricultural output and improving nutritional practices. AFSP is funded by the Global Agriculture and Food Security Project (GAFSP), supervised by the World Bank, and implemented by the Ministries of Agricultural Development (MoAD) and Health (MoH). AFSP includes 19 districts1 of the mid- and far-western development regions of Nepal. It intends to benet 162,000 people living in hill and mountain areas of the country.

According to the Project Appraisal Document (PAD), the Project Development Objective (PDO) is to enhance food and nutritional security of the targeted communities in select locations of Nepal. The project hypothesizes a link between this food security/nutrition and increased productivity of on-farm income from both cultivation of crops and rearing of livestock. Additional Results indicators for the project include: - Increase in the productivity of targeted crops - Increase in the yield of targeted livestock products - Increase in the proportion of pregnant and nursing mothers and children between 6-24 months' age adopting appropriate feeding practices.

Following from these objectives, and the indicators laid out in the PAD, the IE was designed in order to capture both the direct targets of the project, as well as its envisioned mechanism pathways. These form the core outcomes measured and described in this report.

In order to achieve its targets, AFSP consists of four components: 1. Technology Development and Adaptation 2. Technology Dissemination and Adoption (TDA) 3. Food and Nutrition Status Enhancement (FNSE) 4. Project Management

The Impact Evaluation (IE) of AFSP concentrates on components 2 and 3. Component 2, TDA, aims to introduce farmers to new production and management methods for both crops and livestock in order to improve their yields and income using a Farmer Field Schools (FFS) approach. Component 3, FNSE, aims to improve feeding practices of young children and of pregnant women, primarily through Behavior Change Communication (BCC).

Geographic coverage

AFSP is being implemented in 19 districts of the Mid- and Far-Western development region of Nepal, and adapted to three agro-climactic zones: hills, low mountains, and high mountains. It is expected to reach about 162,000 beneficiaries.

Analysis unit

Household

Kind of data

Sample survey data [ssd]

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The questionnaire used across rounds was nearly identical - outside of a few minor changes to language and increased options for some of the multiple-choice questions. The questionnaire is available for download under the Documentation tab.

Cleaning operations

Data was edited only minimally - to cater for outliers. Even so, the original data for all these variables are still in the dataset.