Israel Employment: 2008 Census: Agriculture, Forestry & Fishing data was reported at 39.752 Person th in Sep 2018. This records an increase from the previous number of 34.366 Person th for Jun 2018. Israel Employment: 2008 Census: Agriculture, Forestry & Fishing data is updated quarterly, averaging 38.561 Person th from Mar 2012 (Median) to Sep 2018, with 27 observations. The data reached an all-time high of 47.526 Person th in Mar 2013 and a record low of 34.227 Person th in Dec 2015. Israel Employment: 2008 Census: Agriculture, Forestry & Fishing data remains active status in CEIC and is reported by Central Bureau of Statistics. The data is categorized under Global Database’s Israel – Table IL.G009: Employment: 2008 Census: 2011 Classification: by Industry.

Israel Employment: 2008 Census: sa: Agriculture, Forestry & Fishing data was reported at 36.648 Person th in Mar 2018. This records a decrease from the previous number of 41.193 Person th for Dec 2017. Israel Employment: 2008 Census: sa: Agriculture, Forestry & Fishing data is updated quarterly, averaging 38.328 Person th from Mar 2012 (Median) to Mar 2018, with 25 observations. The data reached an all-time high of 46.136 Person th in Jun 2013 and a record low of 35.992 Person th in Dec 2015. Israel Employment: 2008 Census: sa: Agriculture, Forestry & Fishing data remains active status in CEIC and is reported by Central Bureau of Statistics. The data is categorized under Global Database’s Israel – Table IL.G009: Employment: 2008 Census: 2011 Classification: by Industry.

Israel Employment: 2008 Census: Male: Skilled Agricultural, Forestry and Fishery Workers data was reported at 29.869 Person th in Mar 2018. This records an increase from the previous number of 27.935 Person th for Dec 2017. Israel Employment: 2008 Census: Male: Skilled Agricultural, Forestry and Fishery Workers data is updated quarterly, averaging 29.869 Person th from Mar 2012 (Median) to Mar 2018, with 25 observations. The data reached an all-time high of 34.595 Person th in Jun 2013 and a record low of 25.591 Person th in Dec 2012. Israel Employment: 2008 Census: Male: Skilled Agricultural, Forestry and Fishery Workers data remains active status in CEIC and is reported by Central Bureau of Statistics. The data is categorized under Global Database’s Israel – Table IL.G010: Employment: 2008 Census: 2011 Classification: by Occupation.

Israel Employment: 2008 Census: sa: Skilled Agricultural, Forestry and Fishery Workers data was reported at 35.526 Person th in Mar 2018. This records an increase from the previous number of 33.860 Person th for Dec 2017. Israel Employment: 2008 Census: sa: Skilled Agricultural, Forestry and Fishery Workers data is updated quarterly, averaging 33.474 Person th from Mar 2012 (Median) to Mar 2018, with 25 observations. The data reached an all-time high of 40.343 Person th in Jun 2013 and a record low of 29.646 Person th in Jun 2015. Israel Employment: 2008 Census: sa: Skilled Agricultural, Forestry and Fishery Workers data remains active status in CEIC and is reported by Central Bureau of Statistics. The data is categorized under Global Database’s Israel – Table IL.G010: Employment: 2008 Census: 2011 Classification: by Occupation.

Abstract

Nigeria was among the first few countries in Sub-Saharan Africa to identify cases of COVID-19. Reported cases and fatalities have been increasing since it was first identified. The government implemented strict measures to contain the spread of this virus (such as travel restrictions, school closures and home-based work). While the Government is implementing these containment measures, it is important to understand how households in the country are affected and responding to the evolving crises, so that policy responses can be designed well and targeted effectively to reduce the negative impacts on household welfare.

The objective of Nigeria COVID-19 NLPS is to monitor the socio-economic effects of this evolving COVID-19 pandemic in real time. These data will contribute to filling critical gaps in information that could be used by the Nigerian government and stakeholders to help design policies to mitigate the negative impacts on its population. The Nigeria COVID-19 NLPS is designed to accommodate the evolving nature of the crises, including revision of the questionnaire on a monthly basis.

The households were drawn from the sample of households interviewed in 2018/2019 for Wave 4 of the General Household Survey—Panel (GHS-Panel). The extensive information collected in the GHS-Panel just over a year prior to the pandemic provides a rich set of background information on the Nigeria COVID-19 NLPS households which can be leveraged to assess the differential impacts of the pandemic in the country.

Each month, the households will be asked a set of core questions on the key channels through which individuals and households are expected to be affected by the COVID-19-related restrictions. Food security, employment, access to basic services, coping strategies, and non-labour sources of income are channels likely to be impacted. The core questionnaire is complemented by questions on selected topics that rotate each month. This provides data to the government and development partners in near real-time, supporting an evidence-based response to the crisis.

Geographic coverage

National

Analysis unit

• Households
• Individuals

Universe

The survey covered all de jure households excluding prisons, hospitals, military barracks, and school dormitories.

Kind of data

Sample survey data [ssd]

Sampling procedure

Wave 4 of the GHS-Panel conducted in 2018/19 served as the frame for the Nigeria COVID-19 NLPS survey. The GHS-Panel sample includes 4,976 households that were interviewed in the post-harvest visit of the fourth wave in January/February 2019. This sample of households is representative nationally as well as across the 6 geopolitical Zones that divide up the country. In every visit of the GHS-Panel, phone numbers are collected from interviewed households for up to 4 household members and 2 reference persons who are in close contact with the household in order to assist in locating and interviewing households who may have moved in subsequent waves of the survey. This comprehensive set of phone numbers as well as the already well-established relationship between NBS and the GHS-Panel households made this an ideal frame from which to conduct the COVID-19 monitoring survey in Nigeria.

Among the 4,976 households interviewed in the post-harvest visit of the GHS-Panel in 2019, 4,934 (99.2%) provided at least one phone number. Around 90 percent of these households provided a phone number for at least one household member while the remaining 10 percent only provided a phone number for a reference person. Households with only the phone number of a reference person were expected to be more difficult to reach but were nonetheless included in the frame and deemed eligible for selection for the Nigeria COVID-19 NLPS.

To obtain a nationally representative sample for the Nigeria COVID-19 NLPS, a sample size of approximately 1,800 successfully interviewed households was targeted. However, to reach that target, a larger pool of households needed to be selected from the frame due to non-contact and non-response common for telephone surveys. Drawing from prior telephone surveys in Nigeria, a final contact plus response rate of 60% was assumed, implying that the required sample households to contact in order to reach the target is 3,000.

3,000 households were selected from the frame of 4,934 households with contact details. Given the large amount of auxiliary information available in the GHS-Panel for these households, a balanced sampling approach (using the cube method) was adopted. The balanced sampling approach enables selection of a random sample that still retains the properties of the frame across selected covariates. Balancing on these variables results in a reduction of the variance of the resulting estimates, assuming that the chosen covariates are correlated with the target variable. Calibration to the balancing variables after the data collection further reduces this variance (Tille, 2006). The sample was balanced across several important dimensions: state, sector (urban/rural), household size, per capita consumption expenditure, household head sex and education, and household ownership of a mobile phone.

Mode of data collection

Computer Assisted Telephone Interview [cati]

Research instrument

BASELINE (ROUND 1): One questionnaire, the Household Questionnaire, was administered to all households in the sample. The Household Questionnaire provides information on demographics; knowledge regarding the spread of COVID-19; behaviour and social distancing; access to basic services; employment; income loss; food security; concerns; coping/shocks; and social safety nets.

ROUND 2: One questionnaire, the Household Questionnaire, was administered to all households in the sample. The Household Questionnaire provides information on demographics; access to basic goods and services; employment (including non-farm enterprise and agricultural activity); other income; food security; and social safety nets.

ROUND 3: One questionnaire, the Household Questionnaire, was administered to all households in the sample. The Household Questionnaire provides information on demographics; access to basic goods and services; housing; employment (including non-farm enterprise and agricultural activity); other income; coping/shocks; and social safety nets.

ROUND 4: One questionnaire, the Household Questionnaire, was administered to all households in the sample. The Household Questionnaire provides information on demographics; access to basic goods and services; credit; employment (including non-farm enterprise, crop farming and livestock); food security; income changes; concerns; and social safety nets.

ROUND 5: One questionnaire, the Household Questionnaire, was administered to all households in the sample. The Household Questionnaire provides information on demographics; education; employment (including non-farm enterprise and agricultural activity); and other income.

ROUND 6: One questionnaire, the Household Questionnaire, was administered to all households in the sample. The Household Questionnaire provides information on demographics; education; employment (including non-farm enterprise); COVID testing and vaccination; and other income.

ROUND 7: One questionnaire, the Household Questionnaire, was administered to all households in the sample. The Household Questionnaire provides information on demographics; access to basic services; employment (including non-farm enterprise); food security; concerns; and safety nets.

ROUND 8: One questionnaire, the Household Questionnaire, was administered to all households in the sample. The Household Questionnaire provides information on demographics; education; employment (including non-farm enterprise and agriculture); and coping/shocks.

ROUND 9: One questionnaire, the Household Questionnaire, was administered to all households in the sample. The Household Questionnaire provides information on demographics; education; early childhood development, access to basic services, employment (including non-farm enterprise and agriculture); and income changes.

ROUND 10: One questionnaire, the Household Questionnaire, was administered to all households in the sample. The Household Questionnaire provides information on demographics; access to basic services; employment (including non-farm enterprise and agricultural activity); concerns and COVID testing and vaccination.

Cleaning operations

COMUPTER ASSISTED TELEPHONE INTERVIEW (CATI): The Nigeria COVID-19 NLPS exercise was conducted using Computer Assisted Telephone Interview (CATI) techniques. The household questionnaire was implemented using the CATI software, Survey Solutions. The Survey Solutions software was developed and maintained by the Data Analytics and Tools Unit within the Development Economics Data Group (DECDG) at the World Bank. Each interviewer was given two tablets, which they used to conduct the interviews. Overall, implementation of survey using Survey Solutions CATI was highly successful, as it allowed for timely availability of the data from completed interviews.

DATA COMMUNICATION SYSTEM: The data communication system used in the Nigeria COVID-19 NLPS was highly automated. Each interviewer was given a mobile modem allowing for internet connectivity and daily synchronization of their tablet. This ensured that head office in Abuja has access to the data in real-time. Once the interview is completed and uploaded to the server, the data is first reviewed by the Supervisors, and then routed for call back or audio audit if selected. A feedback questionnaire was also designed in Survey Solutions where interviewers receive respective

Israel Employment: 2008 Census: Female: Skilled Agricultural, Forestry and Fishery Workers data was reported at 4.432 Person th in Mar 2018. This records an increase from the previous number of 3.497 Person th for Dec 2017. Israel Employment: 2008 Census: Female: Skilled Agricultural, Forestry and Fishery Workers data is updated quarterly, averaging 3.581 Person th from Mar 2012 (Median) to Mar 2018, with 25 observations. The data reached an all-time high of 5.178 Person th in Jun 2013 and a record low of 1.858 Person th in Sep 2016. Israel Employment: 2008 Census: Female: Skilled Agricultural, Forestry and Fishery Workers data remains active status in CEIC and is reported by Central Bureau of Statistics. The data is categorized under Global Database’s Israel – Table IL.G010: Employment: 2008 Census: 2011 Classification: by Occupation.

Sri Lanka Employment: Major Group: Agriculture data was reported at 2,159,496.000 Person in Dec 2024. This records an increase from the previous number of 2,066,789.000 Person for Sep 2024. Sri Lanka Employment: Major Group: Agriculture data is updated quarterly, averaging 2,127,523.500 Person from Mar 2015 (Median) to Dec 2024, with 40 observations. The data reached an all-time high of 2,390,849.000 Person in Sep 2021 and a record low of 1,927,886.000 Person in Jun 2018. Sri Lanka Employment: Major Group: Agriculture data remains active status in CEIC and is reported by Department of Census and Statistics. The data is categorized under Global Database’s Sri Lanka – Table LK.G011: Labour Force Survey: MYPE 2012: Employment: by Industry and Occupation Group. The Labour Force Survey (LFS) is re-weighted using the rebased mid-year population estimate of 2012. This is to keep the LFS estimates in line with the latest population data after the Census of Population & Housing 2012.

Malaysia Payroll: Wholesale: Agri Raw Meterials & Live Animals data was reported at 216.722 MYR mn in Sep 2018. This records an increase from the previous number of 216.609 MYR mn for Jun 2018. Malaysia Payroll: Wholesale: Agri Raw Meterials & Live Animals data is updated quarterly, averaging 169.721 MYR mn from Mar 2010 (Median) to Sep 2018, with 35 observations. The data reached an all-time high of 219.109 MYR mn in Mar 2018 and a record low of 146.464 MYR mn in Mar 2010. Malaysia Payroll: Wholesale: Agri Raw Meterials & Live Animals data remains active status in CEIC and is reported by Department of Statistics. The data is categorized under Global Database’s Malaysia – Table MY.G019: Employment & Payroll: Wholesale & Retail Trade: MSIC 2008: Census of Distributive Trade 2009.

就业：2008年人口普查：男性：熟练的农业、林业和渔业工人在03-01-2018达29.869千人，相较于12-01-2017的27.935千人有所增长。就业：2008年人口普查：男性：熟练的农业、林业和渔业工人数据按季更新，03-01-2012至03-01-2018期间平均值为29.869千人，共25份观测结果。该数据的历史最高值出现于06-01-2013，达34.595千人，而历史最低值则出现于12-01-2012，为25.591千人。CEIC提供的就业：2008年人口普查：男性：熟练的农业、林业和渔业工人数据处于定期更新的状态，数据来源于Central Bureau of Statistics，数据归类于Global Database的以色列 – 表 IL.G010：就业：2008年人口普查：2011年分类：按职业。