The Vehicle Inventory and Use Survey (VIUS) is conducted in partnership with the Bureau of Transportation Statistics, Federal Highway Administration, and the U.S. Department of Energy to better understand the characteristics and use of trucks on our nation's roads. The survey universe for the VIUS includes all private and commercial trucks registered (or licensed) in the United States. This includes: pickups; minivans, other light vans, and sport utility vehicles; other light single-unit trucks (GVW = 26,000 lbs.); and truck tractors. The VIUS sample excludes vehicles owned by federal, state, and local governments; ambulances; buses; motor homes; farm tractors; unpowered trailer units; and trucks reported to have been disposed of prior to January 1 of the survey year. VIUS provides data on the physical and operational characteristics of the nation's truck population. Its primary goal is to produce estimates of the total number of trucks and truck miles. This dataset provides national and state-level summary statistics for in-scope vehicles, excluding pickups, SUVs, minivans, and other light vans, that were in use.

The Economic Survey is an annual publication of the Kenya National Bureau of Statistics (KNBS). It presents socio-economic highlights of the economy for the last five years. The report forms an important source of input into the budgeting process, planning, monitoring and policy formulation processes.

Abstract

A comprehensive and detailed statistical database of any economic activity is a prerequisite for planning and policy making and this applies to economic activities that play a major role in most modern world economies.

The Palestinian Central Bureau of Statistics is pleased to issue the eighteenth volume of economic surveys for the Palestine, including statistical tables of findings. This edition presents the findings of the surveys conducted for 2013 as the reference year and covers most of the economic activities operating in the Palestine since 1994.

Economic surveys of various fields constitute the basic foundations for the compilation of National Accounts for Palestine. It is hoped that they will also fulfill the various needs and expectations of users in both the public and private sectors.

Geographic coverage

Palestine

Analysis unit

Enterprises

Universe

The eighteenth round of the economic survey series was conducted based on the Establishments Census of 2012. The economic surveys series cover activities in accordance with ISIC-4.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample of the economic surveys series is a single-stage stratified random-systematic sample in which the enterprise constitutes the primary sampling unit (PSU). Three levels of strata were used to draw up an efficient representative sample (i.e. economic activity, size of workforce and geographical location). The sample size in 2012 was 9,425 enterprises out of the 126,309 enterprises comprising the survey frame.

Mode of data collection

Face-to-face [f2f]

Research instrument

All of the economic surveys series used the same questionnaire, with a few different characteristics for each survey. The design of the 2013 questionnaire takes into account the major economic variables pertaining to the sector examined and the needs to be met to compile the National Accounts for Palestine.

The questionnaire included these variables: 1. The persons engaged in enterprise and compensation of these employees. 2. Value of output from the main activity and secondary activity. 3. Production inputs of goods and services. 4. Payments and transfers. 5. Taxes on production. 6. Assets and capital formation.

Cleaning operations

To ensure the quality and consistency of data, a set of measures was introduced as follows: - Creation of a data entry program prior to the collection of data to ensure this would be ready. - A set of validation rules were applied to the program to check the consistency of data. - The efficiency of the program was pre-tested by entering a few questionnaires, including incorrect information, and checking its efficiency in capturing the incorrect information. - Well-trained data entry personnel were selected and trained for main data entry. - Weekly data files were received by project management to be checked for accuracy and consistency: correction notes were provided to data entry management for implementation.

Response rate

Response rate: 85.2%

Sampling error estimates

Statistical Errors: - Statistical Errors: The findings of the survey are affected by statistical errors due to using sampling in conducting the survey for the units of the target population, which increases the chances of having variances from the actual values we expect to obtain from the data had we conducted the survey using comprehensive enumeration. The variance of the key goods in the survey was computed and dissemination was carried out on the level of the Palestinian Territory for reasons related to sample design and computation of the variance of the different indicators.

Non-Statistical Errors These types of errors could appear on one or all the survey stages that include data collection and data entry. - Response errors: these types of errors are related to, responders, fieldworkers, and data entry personnel's. And to avoid mistakes and reduce the impact has been a series of actions that would enhance the accuracy of the data through a process of data collection from the field and the data processing.

Saudi Arabia Economic Survey of Establishments: ER: ow Oil and Gas Extraction data was reported at 665,325,998.000 SAR th in 2016. This records a decrease from the previous number of 747,668,545.000 SAR th for 2015. Saudi Arabia Economic Survey of Establishments: ER: ow Oil and Gas Extraction data is updated yearly, averaging 824,639,180.500 SAR th from Dec 2005 (Median) to 2016, with 12 observations. The data reached an all-time high of 1,355,124,781.000 SAR th in 2013 and a record low of 654,937,072.000 SAR th in 2009. Saudi Arabia Economic Survey of Establishments: ER: ow Oil and Gas Extraction data remains active status in CEIC and is reported by General Authority for Statistics. The data is categorized under Global Database’s Saudi Arabia – Table SA.S001: Economic Survey of Establishments: Enterprise Revenues and Expenditures.

Abstract

The Iraq Household Socio-Economic Survey conducted in 2006-2007 (IHSES 2007), was Iraq's first nationwide income and expenditure survey since 1988. Based on the model of the Living Standards Measurement Surveys, it covered more than 18,000 households, collected detailed data on all aspects of household income and expenditure and generated information on a wide variety of socio-economic indicators. It also formed the basis for updating the Consumer Price Index (CPI), from an outdated index based in 1990 to a revised index with the base year of 2007. Detailed analysis of poverty, its incidence, characteristics, determinants and consequences, was undertaken using this comprehensive survey. Under the overall guidance of the Poverty Reduction Strategy High Committee (PRSHC) and a technical sub-committee, a poverty line was defined and adopted by the Council of Ministers.

Six years later, in 2012, the second round of the IHSES was completed. Learning from past and international experience on survey design, implementation and sampling, IHSES 2012 also incorporated additional modules on areas of evolving interest. It is the most comprehensive socio-economic survey as yet undertaken in Iraq.

Objectives of the survey: 1) to provide data to help measure and analyze poverty and monitor the implementation of the national strategy to alleviate poverty (issued in 2009) and update it with a new strategy, 2) to provide an integrated system of data to assess the social and economic situation of families and develop indicators related to human development, 3) to provide data meeting the requirements and needs of the national accounts, 4) to provide detailed indicators of consumer spending and the impact of various changes in it to serve the production, consumption, export and import decision-making, 5) to provide detailed indicators of the incomes of individuals and families by source, 6) to provide the data required for creating a new index record of consumer prices beyond 2012.

Geographic coverage

National coverage

Analysis unit

Households and individuals

Kind of data

Sample survey data [ssd]

Sampling procedure

The IHSES intends to provide estimators of comparable quality for each of Iraq's 118 gadahs (districts). This implies that the sample should be explicitly stratified by gadah, with a similar sample size allocated to each gadah, regardless of its size. A sample size of 216 households per gadah is proposed, equivalent to a total sample of 25,488 households for the country.

Within each gadah, the sample will be selected in two stages, as follows:

• First, using Census Enumeration Areas (EAs) as Primary Sampling Units (PSUs), select 24 EAs with Probability Proportional to Size (PPS), using the number of households as a Measure of Size (MoS), and with implicit stratification by urban/rural and the subsequent geographical codes (nahya, mahala, village, mukataa and census block).

• Second, using households as secondary Sampling Units (SSUs), select a cluster of 9 households by systematic, equal probability sampling (SEPS) in each of the selected EAs.

The sample frames for both stages can be developed from the 2010 Census enumeration, with no updating of the household lists.

In some of the smallest gadahs, the standard PPS procedure may result in the selection of fewer than 24 EAs, with some of the larger EAs selected more than once. In those cases, two or more clusters will be taken in the EA, as needed. 2,832 EAs were selected in total. 33 of them had less than the 9 households nominally required in the second stage and were merged ex-post with neighboring EAs.

Mode of data collection

The data were collected using paper questionnaires with concurrent data entry in the field using Computer Assisted Field Entry (CAFE)

Research instrument

The survey questionnaire has four parts: Part 1 - Socio Economic Part 2 - Expenditure Part 3 - Income and other Data Part 4 - Household Diary

Saudi Arabia Economic Survey of Establishments: ER: ow Apparel and Fur Dyeing data was reported at 9,796,746.000 SAR th in 2016. This records an increase from the previous number of 9,656,152.000 SAR th for 2015. Saudi Arabia Economic Survey of Establishments: ER: ow Apparel and Fur Dyeing data is updated yearly, averaging 7,033,267.000 SAR th from Dec 2005 (Median) to 2016, with 12 observations. The data reached an all-time high of 9,796,746.000 SAR th in 2016 and a record low of 3,674,241.000 SAR th in 2005. Saudi Arabia Economic Survey of Establishments: ER: ow Apparel and Fur Dyeing data remains active status in CEIC and is reported by General Authority for Statistics. The data is categorized under Global Database’s Saudi Arabia – Table SA.S001: Economic Survey of Establishments: Enterprise Revenues and Expenditures.

Abstract

Susenas (National Socio-economic Survey) was held for the first time in year 1963. In the last two decades, up to year 2010, Susenas was conducted every year. Susenas was designed to have 3 modules (Module of Household Consumption/Expenditure, Module of Education and Socio-culture, and also Module of Health and Housing) and each module should be conducted every 3 years. Household Consumption/ Expenditure Module of Susenas shall be conducted in year 2011 .

To improve the accuracy of data result and in line with the increased frequency of household consumption/expenditure data request for quarterly GDP/GRDP and poverty calculation, data collection of household consumption/expenditure, it is planned that starting in 2011 it should be held quarterly. Each year, collecting data shall be conducted in March, June, September, and December.

In accordance with the 5-year cycle, in year 2012, BPS (Central Statistical Agency) shall have planned Survei Biaya Hidup-SBH (Cost of Living Survey) with the aim to generate a commodity package and a weigh diagram in the calculation of Consumer Price Index (CPI). Data of food and non-food consumption expenditures as well as household characteristics collected in SBH and Susenas has the same concept/definition, but different implementation time. In order to be more efficient in the utilization of resources of the two surveys and to have a better quality of results achieved, in year 2011 a trial of Susenas and SBH integration shall be conducted in 7 cities (Medan, Sampit, Denpasar, Kudus, Bulukumba, Tual, and South Jakarta).

Poverty data, CPI/Inflation data, GDP/GRDP are BPS strategic data that have to be released on time. Therefore, planning, field preparation, processing, and presentation of data Susenas 2011 activities and trial of integrating Susenas and SBH must be in accordance with the set schedule.

Activities of Susenas 2011 preparation shall be conducted in year 2010, covering activities of workshop/training of chief instructor with the aim to synchronize the perception toward the concept/definition as well as procedure and protocol of survey implementation. National instructor training will also be conducted in year 2010.

Geographic coverage

National coverage, representative to the district level

Analysis unit

Household Members (Individual) and Household

Universe

Susenas 2011 cover 300,000 household sample spread all over Indonesia where each quarter distribute about 75,000 household sample (including 500 households additional sample for Survey in Maluku Province). The result from each quarter can produce national and provincial level estimates. Meanwhile from the cummulative four quarter, the data can be presented until the district/municipality level.

Kind of data

Sample survey data [ssd]

Sampling procedure

From the master sampling frame (Nh enumeration areas) were retractable sample enumeration areas in a probability proportional to size (pps) method, nh acquired 30,000 enumeration areas. Then divided into 4 quarters so that each quarter 7,500 enumeration areas. The next stage selected one census block (BS) in a probability proportional to size (pps) method, whereas size is the number of households from SP 2010 RBL1. The last stage, of each BS Susenas been selected for a number of common household (m = 10) based on the results of systematic updating of listing of households using SP 2010 C1 VSEN2011 List - P. Then do the enumeration of 75,000 households.

Mode of data collection

Face-to-face

This statistic shows the Economic Confidence Index, created by Gallup, on a monthly basis for the ongoing year. The survey is conducted doing weekly telephone interviews among approx. 2,499 adults in the U.S. The graph shows the results for the first update each month to depict an annual trend. The Index is computed by adding the percentage of Americans rating current economic conditions to the percentage saying the economy is (getting better minus getting worse), and then dividing that sum by 2. The Index has a value between null and +100. In December 2017, the U.S. Economic Confidence Index stood at 8.

The World Bank-UNHCR Joint Data Center (JDC) provided his support for a household survey in the Great Kasai area in the Democratic Republic of Congo (DRC) conducted by the UNHCR Sub Office Kananga in collaboration with the National Institute of Statistics (INS). The main objective of the survey was to generate high-quality socioeconomic data to inform decision making and programming of humanitarian and development interventions and policy including UNHCR DRC’s core programing and multi-year strategy implementation as well as UNHCR Angola’s planning of voluntary repatriation. A wide range of stakeholders were consulted and involved from the design stage of the survey tools, including (but not limited to) the World Bank, UNDP, UNICEF, IOM, WFP, FAO, UNFPA, the National Institute of Statistics (INS), the Provincial Ministries of planning, the Protection, Shelter and Health Clusters members and CRIs actors the Grand-Kasai-level.

The data covers the following areas: land ownership, documentation, agro-pastoral activities, conflicts, employment and sources of income, household assets, consumption, savings, and credit, right to housing and habitat, access to basic social services and information, peace, security and peaceful cohabitation, physical and mental health, food insecurity, inclusion, and access to legal resources of the people for whom and with whom UNHCR works.

Abstract

IPUMS-International is an effort to inventory, preserve, harmonize, and disseminate census microdata from around the world. The project has collected the world's largest archive of publicly available census samples. The data are coded and documented consistently across countries and over time to facillitate comparative research. IPUMS-International makes these data available to qualified researchers free of charge through a web dissemination system.

The IPUMS project is a collaboration of the Minnesota Population Center, National Statistical Offices, and international data archives. Major funding is provided by the U.S. National Science Foundation and the Demographic and Behavioral Sciences Branch of the National Institute of Child Health and Human Development. Additional support is provided by the University of Minnesota Office of the Vice President for Research, the Minnesota Population Center, and Sun Microsystems.

Geographic coverage

National coverage

Analysis unit

Household

UNITS IDENTIFIED: - Dwellings: Yes - Vacant units: No - Households: Yes - Individuals: Yes - Group quarters: No - Special populations: Persons without any normal residence, foreign nationals, and people in orphanages, rescue homes, ashram and vagrant houses are not covered by survey.

UNIT DESCRIPTIONS: - Households: A group of persons normally living together and taking food from a common kitchen will constitute a household. The members of a household may or may not be related by blood to one another.

Universe

All population in India, except for foreigners, the homeless, or people in orphanages, rescue homes, ashram, and vagrant houses.

Kind of data

Census/enumeration data [cen]

Sampling procedure

MICRODATA SOURCE: National Sample Survey Organization, Government of India

SAMPLE DESIGN: Two-staged, stratified systematic samples drawn by the country. Stage 1: In rural sector, regions are stratified based on population and crop pattern. Census villages (primary sampling units) are selected from region strata circular systematically with probability proportional to population. In urban sector, districts are stratified by population. Urban frame survey (UFS) blocks are the primary sampling units and selected from district strata circular systematically with equal probability. Stage 2: Selected large villages/blocks are split into hamlet-groups (rural) or sub-blocks (urban), some of which are randomly selected and they form the strata for Stage II, together with small villages/blocks selected in Stage I. Households are selected from those Stage II strata by circular systematically with a random start. Affluent households are over-sampled. The ratio of affluent to other households is 2:8 in rural sector and 4:6 in urban sector. In total, the central sample includes 7,284 villages and 4,792 urban blocks; the state sample includes 7,964 villages and 5,880 urban blocks.

SAMPLE UNIT: Household

SAMPLE FRACTION: .07%

SAMPLE SIZE (person records): 564,740

Mode of data collection

Face-to-face [f2f]

Research instrument

A single form that consists of 8 sections: 1) identification of sample household, 2) household characteristics, 3) demographic particulars and principal usual activity, 4) current work activity during the preceding week, 5) follow-up questions for the unemployed, 6) questions for working persons, 7) questions for children 5-14 years, and 8) questions for persons who attended domestic duties.

Response rate

COVERAGE: Entire country, in both rural and urban sectors

The project will produce a valuation function that depends on factors related to Steller sea lion (SSL) protection measures, and may include some combination of the expected aggregate size of the population and improvements to the ESA listing status resulting from protection measures, cost of the protection measures, and effects of protection measures on local economies, fishery participants, and consumer fish prices. This function can be used to identify non-consumptive use values for SSLs and how these values are affected by protection measures, thereby providing valuable information to policy makers.

Saudi Arabia Economic Survey of Establishments: ER: ow Agriculture, Hunting and Related Services data was reported at 92,540,192.000 SAR th in 2016. This records an increase from the previous number of 91,710,533.000 SAR th for 2015. Saudi Arabia Economic Survey of Establishments: ER: ow Agriculture, Hunting and Related Services data is updated yearly, averaging 70,133,347.500 SAR th from Dec 2005 (Median) to 2016, with 12 observations. The data reached an all-time high of 92,540,192.000 SAR th in 2016 and a record low of 53,527,672.000 SAR th in 2005. Saudi Arabia Economic Survey of Establishments: ER: ow Agriculture, Hunting and Related Services data remains active status in CEIC and is reported by General Authority for Statistics. The data is categorized under Global Database’s Saudi Arabia – Table SA.S001: Economic Survey of Establishments: Enterprise Revenues and Expenditures.

Saudi Arabia Economic Survey of Establishments: ER: ow Education data was reported at 15,540,762.000 SAR th in 2016. This records an increase from the previous number of 15,143,765.000 SAR th for 2015. Saudi Arabia Economic Survey of Establishments: ER: ow Education data is updated yearly, averaging 7,031,290.000 SAR th from Dec 1995 (Median) to 2016, with 19 observations. The data reached an all-time high of 15,540,762.000 SAR th in 2016 and a record low of 1,520,859.000 SAR th in 1995. Saudi Arabia Economic Survey of Establishments: ER: ow Education data remains active status in CEIC and is reported by General Authority for Statistics. The data is categorized under Global Database’s Saudi Arabia – Table SA.S001: Economic Survey of Establishments: Enterprise Revenues and Expenditures.

The Annual Business Survey (ABS) provides information on selected economic and demographic characteristics for businesses and business owners by sex, ethnicity, race, and veteran status. Further, the survey measures research and development (for microbusinesses), new business topics such as innovation and technology, as well as other business characteristics. The U.S. Census Bureau and the National Center conduct the ABS jointly for Science and Engineering Statistics within the National Science Foundation. The ABS replaces the five-year Survey of Business Owners (SBO) for employer businesses, the Annual Survey of Entrepreneurs (ASE), the Business R&D and Innovation for Microbusinesses survey (BRDI-M), and the innovation section of the Business R&D and Innovation Survey (BRDI-S). https://www.census.gov/programs-surveys/abs.html

Saudi Arabia Economic Survey of Establishments: ER: ow Electricity, Gas and Water data was reported at 58,854,933.000 SAR th in 2016. This records an increase from the previous number of 56,106,522.000 SAR th for 2015. Saudi Arabia Economic Survey of Establishments: ER: ow Electricity, Gas and Water data is updated yearly, averaging 29,255,059.000 SAR th from Dec 1995 (Median) to 2016, with 19 observations. The data reached an all-time high of 58,854,933.000 SAR th in 2016 and a record low of 10,573,486.000 SAR th in 1995. Saudi Arabia Economic Survey of Establishments: ER: ow Electricity, Gas and Water data remains active status in CEIC and is reported by General Authority for Statistics. The data is categorized under Global Database’s Saudi Arabia – Table SA.S001: Economic Survey of Establishments: Enterprise Revenues and Expenditures.

Abstract

The Cambodia Socio-Economic Survey (CSES) asks questions to a country wide sample of households and household members about housing conditions, education, economic activities, household production and income, household level and structure of consumption, health, victimization, etc. There are also questions related to people in the labour force, e.g. labour force participation.

Poverty reduction is a major commitment by the Royal Government of Cambodia. Accurate statistical information about the living standards of the population and the extent of poverty is an essential instrument to assist the Government in diagnosing the problems, in designing effective policies for reducing poverty and in monitoring and evaluating the progress of poverty reduction. The Millennium Development Goals (MDG) has been adopted by the Royal Government of Cambodia and a National Strategic Development Plan (NSDP) has been developed. The MDGs are also incorporated into the "Rectangular Strategy of Cambodia".

Cambodia is still a predominantly rural and agricultural society. The vast majority of the population get their subsistence in households as self-employed in agriculture. The level of living is determined by the household's command over labour and resources for own-production in terms of land and livestock for agricultural activities, equipments and tools for fishing, forestry and construction activities and income-earning activities in the informal and formal sector. The CSES aims to estimate household income and consumption/expenditure as well as a number of other household and individual characteristics.

The main objective of the survey is to collect statistical information about living conditions of the Cambodian population and the extent of poverty. The survey can be used for identifying problems and making decisions based on statistical data. They would also prove useful for the production of National Accounts in Cambodia.

A long-term objective of the entire project is to build national capability in NIS for conducting socio-economic surveys and for utilizing survey data for planning for national development and social welfare.

Among specific objectives, the following deserve special mention: - Obtain data on infrastructural facilities in villages, especially facilities for schooling and health care and associated problems. - Obtain data on retail prices of selected food, non-food and medicine items prevailing in the villages. - Collect data on migration - Collect data on utilization of education, housing and land ownership - Collect data on household assets and outstanding loans. - Collect data on household's construction activities. - Collect information on maternal health, child health/care. - Collect information on health of the household members related to illness, injury and disability. - Collect information on economic activities including the economic activities for children aged between 5 and 17 years. - Collect information on victimization by the household - Collect information on the presence of the household members. - Collect information on household income and receipts, expenditure and consumption of own production (also in diaries).

The main user is the Royal Government of Cambodia (RGC) as the survey supports monitoring the National Strategic Development Plan (NSDP) by different socio-economic indicators. Other users are university researchers, analysts, international organizations e.g. the World Bank and NGO's. The World Bank has published a report on poverty profile and social indicators using CSES 2007 data . In this regard, the CSES continues to serve all stakeholders involved as essential instruments in order to assist in diagnosing the problems and designing their most effective policies. The CSES micro data at NIS is available for research and analysis by external researchers after approval by Senior Minister of Planning. The interesting research questions that could be put to the data are many; NIS welcomes new research based on CSES data

Geographic coverage

National Phnom Penh / Other Urban / Other Rural

Analysis unit

Households Individuals

Universe

The target population for CSES is all “normal” households in Cambodia. The term normal is defined in the Population Census 2008 as households that are not institutional households, homeless households, boat population households or households of transient population. (Institutional households are boarding houses, military barracks, prisons, student dormitories, etc.).

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample design

The sample of villages for CSES 2011 is just a simple random 50 % subsample from the CSES 2009 sample of villages, just like for 2010. Consequently, the description of the CSES 2011 sample design will by necessity begin with a description of the CSES 2009 design.

The sample design for CSES 2010 is basically the same as the CSES 2009 design. For the 2010 and 2011 survey a subsample of 360 EAs (stage 2 units) was selected from the CSES 2009 sample of 720 EAs. The selection was done by simple random sampling within strata. The selection resulted in 136 urban EAs and 224 rural EAs.

Households were selected in the same way as in CSES 2009. For CSES 2010 and 2011 only 10 households are selected in each rural EA, as compared to 20 households in 2009. In urban areas 10 households were selected, just as in 2009.

The sampling resulted in a sample of 3,600 households, 1,360 urban households and 2,240 rural households.

Mode of data collection

Face-to-face [f2f]

Research instrument

Four different questionnaires or forms were used in the survey:

Form 1: Household listing sheets to be used in the sampling procedure in the enumeration areas.

Form 2: Village questionnaire answered by the village leader about economy and infrastructure, crop production, health, education, retail prices and sales prices of agriculture, employment and wages, and recruitment of children for work outside the village.

Form 3: Household questionnaire with questions for each household member, including modules on migration, education and literacy, housing conditions, crop production, household liabilities, durable goods, construction activities, nutrition, fertility and child care, child feeding and vaccination, health of children, mortality, current economic activity, health and illness, smoking, HIV/AIDS awareness, and victimization.

Form 4: Diary form on daily household expenditure and income

Cleaning operations

The NIS team commenced their work of checking and coding in begining of February after the first month of fieldwork was completed. Supervisors from the field delivered questionaires to NIS. SIDA project expert and NIS Survey Manager helped in solving relevant matters that become apparent when reviewing questionnaires on delivery.

Response rate

The CSES 2011 enjoyed almost a 100 percent response rate. The high response rate together with close and systematic fieldwork supervision by the core group members were a major contribution for achieving high quality survey results.

The coastal component of the Pacific Regional Oceanic and Coastal Fisheries Development Programme (PROCFish/C) conducted fieldwork in four locations around Papua New Guinea in June to November 2006. Papua New Guinea is one of 17 Pacific Island countries and territories being surveyed over a 5–6 year period by PROCFish or its associated programme CoFish (Pacific Regional Coastal Fisheries Development Programme). The aim of the survey work was to provide baseline information on the status of reef fisheries, and to help fill the massive information gap that hinders the effective management of reef fisheries. Other programme outputs include: • implementation of the first comprehensive multi-country comparative assessment of reef fisheries (finfish, invertebrates and socioeconomics) ever undertaken in the Pacific Islands region using identical methodologies at each site; • dissemination of country reports that comprise a set of ‘reef fisheries profiles’ for the sites in each country in order to provide information for coastal fisheries development and management planning; • development of a set of indicators (or reference points to fishery status) to provide guidance when developing local and national reef fishery management plans and monitoring programmes; and • development of data and information management systems, including regional and national databases.

Survey work in Papua New Guinea covered three disciplines (finfish, invertebrate and socioeconomic) in each site, with two sites surveyed on each trip by a team of five programme scientists and many local attachments from the National Fisheries Authority, the Nature Conservancy, and the Conservation International. The fieldwork included capacity building for the local counterparts through instruction on survey methodologies in all three disciplines, including the collection of data and inputting the data into the programme’s database.

In Papua New Guinea, the four sites selected for the survey were: Andra, Tsoilaunung, Sideia and Panapompom.

Version 01: This is the final, clean, labelled and anonymized version of the Master file.

-HOUSEHOLD: Household size and composition; Agriculture, Ranked sources of income and average household expenditure level; Average household consumption patterns and sources; Average number of fishers and boats per household.
-INDIVIDUAL: Education level of adult members of the household; When, how often and during which months of the year fishers go out to particulat habitats; Average catch size; Catch composition; Fishing techniques; Proportion of the catch targeted for subsistence, gift and sale, and preservation; How finfish and invertebrates are preserved; Community's fishing grounds; Management rules; Major problems relating to the use/management of the community's marine resources; Quantities by species or groups marketed; Quality and processing level of species marketed; Price in local currency/USD; Client groups; Quantitative and qualitative changes in marketing perceived over a period of time.

• Collection start: 2006
• Collection end: 2006

New Zealand Household Economic Survey: Average Weekly Household Expenditure: Clothing and Footwear data was reported at 37.900 NZD in 2016. This records an increase from the previous number of 31.900 NZD for 2013. New Zealand Household Economic Survey: Average Weekly Household Expenditure: Clothing and Footwear data is updated yearly, averaging 31.250 NZD from Jun 2001 (Median) to 2016, with 6 observations. The data reached an all-time high of 37.900 NZD in 2016 and a record low of 24.800 NZD in 2001. New Zealand Household Economic Survey: Average Weekly Household Expenditure: Clothing and Footwear data remains active status in CEIC and is reported by Statistics New Zealand. The data is categorized under Global Database’s New Zealand – Table NZ.H010: Household Economic Survey: Average Weekly Household Expenditure.

Abstract

The Indonesia Social and Economic Survey (SUSENAS) is designed in order to collect social population data, which is relatively in the wide scope. In 1992, SUSENAS data collecting system was renewed. Information which is used to arrange population welfare indicator in module (questionnaire is collected every three year) is joined in to core (questionnaire is collected every year). At that time being, SUSENAS provides tools that can be used to supervise population welfare level, formula government program, and analyze population welfare improvement programs impact.

Questionnaire core, consist some questions asking about condition and member of population attitude, which have tight relationship with welfare aspects. Here are some example question “are you still attend school”, “are you in health disruption”, “how do you take care your health”, “who was the birth helper”, “how long the baby got the wet nursing” and immunization to the children be asked. Beside all question above, also been collected education info, household economic activity, and especially for the ever- married women have been asked about age when she got married, number of child, and Family Planning attitude.

Questionnaire module has taken turns to be collected in 3 years. At the first year, household income and expenditure were collected, at the second year household welfare socio-culture, trips and criminality module were collected, and finally at the last year health, nutrition, education and housing were collected. Information is module is more detail and comprehensive question if it is compared to the same topic question in the core.

Questionnaire core are collected in order to get important information to anticipate some changes that could be happened every year. They are also helpful for short- term planning, and the questions could be related to module's questions such as expenditures. Questionnaire module is useful to analyze problems, which are unneeded to be supervised every year or to analyze government intervention, such as poverty and malnutrition.

Since 1993, sample size of SUSENAS core is enlarged to produce simple statistic in Regency/ Municipality level. This-new progress gave data analyzers a new dimension. At that time being, some Regencies have been arranged their people welfare statistic/ indicator.

Geographic coverage

National coverage, representative to the district level

Analysis unit

Household Members (Individual) and Household

Universe

Susenas 2012 cover 300,000 household sample spread all over Indonesia where each quarter distribute about 75,000 household sample (including 500 households additional sample for Survey in Maluku Province). The result from each quarter can produce national and provincial level estimates. Meanwhile from the cummulative four quarter, the data can be presented until the district/municipality level.

Kind of data

Sample survey data [ssd]

Sampling procedure

From the master sampling frame (Nh enumeration areas) were retractable sample enumeration areas in a probability proportional to size (pps) method, nh acquired 30,000 enumeration areas. Then divided into 4 quarters so that each quarter 7,500 enumeration areas. The next stage selected one census block (BS) in a probability proportional to size (pps) method, whereas size is the number of households from SP 2010 RBL1. The last stage, of each BS Susenas been selected for a number of common household (m = 10) based on the results of systematic updating of listing of households using SP 2010 C1 VSEN2011 List - P. Then do the enumeration of 75,000 households.

Mode of data collection

Face-to-face [f2f]

Geographic coverage

National coverage

Analysis unit

households/individuals

Kind of data

survey

Frequency of data collection

Yearly

Sampling procedure

Sample size: