blockgroupspending Opportunity US Consumers express their behavior in a number of ways, but critically in their spending decisions. The US Bureau of Labor Statistics is charged with publishing spending activity and provides its Consumer Expenditure Survey (CEX) annually with US totals, with selected states (40) and cities (23). Limited to aggregates, the survey only needs 10s of thousands of observations in the original collection. While this is sufficient for macroeconomic use, the volume gives a weak basis for estimating lower levels of geography. In addition, the CEX includes demographic measurements that are similar, but not directly related, to Census variables. So, the CEX does not integtate well with the American Commuity Survey or other Census publications. This blockgroupspending publication by Open Environments attempts to address this problem by using the BLS' Public Microdata (PUMD) sample to allocate CEX spending categories across 220,000 US Census block group geographies. For each block group, the effort applies two models to estimate: total consumer spending (regression) distribution of spending across spending categories (penetration) including Food, Transportation, Housing and Health costs. Ultimately, these project spending on block groups that can be joined to US Census publications for additional demographics. Understanding the results requires awareness of the BLS' CEX data structures. This is available in the markdown file named oe_bls_cex_EDA.md The publication is made together with the source python code and notebooks used for repeatability. The materials are maintained under version control at https://github.com/OpenEnvironments/blockgroupspending. All feedback and development requests are welcome. Model details -- The CEX publication includes many files reflecting detailed 'diary' surveys capturing spend on thousands of items every two weeks family 'interviews' collecting household spending over the previous 3 months The models are trained upon the latter, 'FMLI' files. The regression model uses extreme gradient boosting, or XGBoost methods that apply many decision trees to iteratively correct prediction error. The subcategory models also use tree based methods, trained upon a the family interview details. The spending variables are named, following the BLS' CEX convention: |Variable|Definition|2023|pct| |---|---|---|---| |TOTEXP|Average annual expenditures|77280|| |FOOD|Food|9985|0.129| |ALCBEV|Alcoholic beverages|637|0.008| |HOUS|Housing|25436|0.329| |APPAR|Apparel and services|2041|0.026| |TRANS|Transportation|13174|0.17| |HEALTH|Healthcare|6159|0.08| |ENTERT|Entertainment|3635|0.047| |PERSCA|Personal care products and services|950|0.012| |READ|Reading|117|0.002| |EDUCA|Education|1656|0.021| |TOBACC|Tobacco products and smoking supplies|370|0.005| |MISC|Miscellaneous|1184|0.015| |CASHCO|Cash contributions|2378|0.031| |RETPEN|Personal insurance and pensions|9556|0.124| During the exploratory phase of this effort, ensemble modelling was evaluated finding that different groupings of income did not appreciably change model estimates while racial and ethnic categories did. As a result, the models are case for major races (White, African American, Asian, Other) and Hispanic. The ACS is collected by API at the block group level. Block group geographies are the lowest level of Census ACS detail and consolidate into Census tracts which in turn consolidate into counties. The FMLI responses are recorded in nominal dollars throughout the year, while total expenditure and ACS data represent year end states. As a result, the models' prediction for total expenditure is cast up using monthly inflation, weighted by monthly expenditure. Additional Caveats It is import to note, analytically, that the results are a stretch for credibility. CEX Consumer Units (people sharing financial decisions) are not exactly Census households (people in a housing unit) CEX demographics are not exactly Census demographics, with the CEX imputing incomes differenly than the Census medians. The CEX applies population weightings to the microdata while the Census primarily aggregates from respondents. The CEX observations are from 1 household (race is a 0/1 indicator) while Census demographics are many households (races are proportions) Models are trained upon repeated measures from a Consumer unit but not revised for ANOVA. Several of the CEX subcategories are very small, as spending has changed over the years. Reading, Alcohol and Tobacco use are still top level subcategories, for example as those have declined significantly since the CEX was first designed. So, this model is limited to the major subcategories of food, housing, transportation, health and retirement spending.* The model apply machine learning to large datasets so significance is not a consideration. However, in practice, those very small subcategories should be avoided. Difference in spending across racial categories also have different...

The Consumer Expenditure Estimates dataset was created by SimplyAnalytics using small area estimation techniques. The Consumer Expenditure (CE) Public Use Microdata (PUMD) samples thousands of respondents (referred to as consumer units, or "CUs") across Texas. Each CU is assigned a weight that reflects the relative proportion of all American CUs that they represent. To estimate expenditures at the Census block group and ZCTA5 levels, we use data from the American Community Survey 5-Year Estimates as a proxy for how CUs are distributed over small areas, and use this information to derive expenditure estimates for all CE spending categories. Due to limitations on the PUMD sample size, and to account for national-level weighting of all CUs, the estimates are further adjusted to account for regional fluctuations in cost of living.

VITAL SIGNS INDICATOR Population (LU1)

FULL MEASURE NAME Population estimates

LAST UPDATED October 2019

DESCRIPTION Population is a measurement of the number of residents that live in a given geographical area, be it a neighborhood, city, county or region.

DATA SOURCES U.S Census Bureau: Decennial Census No link available (1960-1990) http://factfinder.census.gov (2000-2010)

California Department of Finance: Population and Housing Estimates Table E-6: County Population Estimates (1961-1969) Table E-4: Population Estimates for Counties and State (1971-1989) Table E-8: Historical Population and Housing Estimates (2001-2018) Table E-5: Population and Housing Estimates (2011-2019) http://www.dof.ca.gov/Forecasting/Demographics/Estimates/

U.S. Census Bureau: Decennial Census - via Longitudinal Tract Database Spatial Structures in the Social Sciences, Brown University Population Estimates (1970 - 2010) http://www.s4.brown.edu/us2010/index.htm

U.S. Census Bureau: American Community Survey 5-Year Population Estimates (2011-2017) http://factfinder.census.gov

U.S. Census Bureau: Intercensal Estimates Estimates of the Intercensal Population of Counties (1970-1979) Intercensal Estimates of the Resident Population (1980-1989) Population Estimates (1990-1999) Annual Estimates of the Population (2000-2009) Annual Estimates of the Population (2010-2017) No link available (1970-1989) http://www.census.gov/popest/data/metro/totals/1990s/tables/MA-99-03b.txt http://www.census.gov/popest/data/historical/2000s/vintage_2009/metro.html https://www.census.gov/data/datasets/time-series/demo/popest/2010s-total-metro-and-micro-statistical-areas.html

CONTACT INFORMATION vitalsigns.info@bayareametro.gov

METHODOLOGY NOTES (across all datasets for this indicator) All legal boundaries and names for Census geography (metropolitan statistical area, county, city, and tract) are as of January 1, 2010, released beginning November 30, 2010, by the U.S. Census Bureau. A Priority Development Area (PDA) is a locally-designated area with frequent transit service, where a jurisdiction has decided to concentrate most of its housing and jobs growth for development in the foreseeable future. PDA boundaries are current as of August 2019. For more information on PDA designation see http://gis.abag.ca.gov/website/PDAShowcase/.

Population estimates for Bay Area counties and cities are from the California Department of Finance, which are as of January 1st of each year. Population estimates for non-Bay Area regions are from the U.S. Census Bureau. Decennial Census years reflect population as of April 1st of each year whereas population estimates for intercensal estimates are as of July 1st of each year. Population estimates for Bay Area tracts are from the decennial Census (1970 -2010) and the American Community Survey (2008-2012 5-year rolling average; 2010-2014 5-year rolling average; 2013-2017 5-year rolling average). Estimates of population density for tracts use gross acres as the denominator.

Population estimates for Bay Area PDAs are from the decennial Census (1970 - 2010) and the American Community Survey (2006-2010 5 year rolling average; 2010-2014 5-year rolling average; 2013-2017 5-year rolling average). Population estimates for PDAs are derived from Census population counts at the tract level for 1970-1990 and at the block group level for 2000-2017. Population from either tracts or block groups are allocated to a PDA using an area ratio. For example, if a quarter of a Census block group lies with in a PDA, a quarter of its population will be allocated to that PDA. Tract-to-PDA and block group-to-PDA area ratios are calculated using gross acres. Estimates of population density for PDAs use gross acres as the denominator.

Annual population estimates for metropolitan areas outside the Bay Area are from the Census and are benchmarked to each decennial Census. The annual estimates in the 1990s were not updated to match the 2000 benchmark.

The following is a list of cities and towns by geographical area: Big Three: San Jose, San Francisco, Oakland Bayside: Alameda, Albany, Atherton, Belmont, Belvedere, Berkeley, Brisbane, Burlingame, Campbell, Colma, Corte Madera, Cupertino, Daly City, East Palo Alto, El Cerrito, Emeryville, Fairfax, Foster City, Fremont, Hayward, Hercules, Hillsborough, Larkspur, Los Altos, Los Altos Hills, Los Gatos, Menlo Park, Mill Valley, Millbrae, Milpitas, Monte Sereno, Mountain View, Newark, Pacifica, Palo Alto, Piedmont, Pinole, Portola Valley, Redwood City, Richmond, Ross, San Anselmo, San Bruno, San Carlos, San Leandro, San Mateo, San Pablo, San Rafael, Santa Clara, Saratoga, Sausalito, South San Francisco, Sunnyvale, Tiburon, Union City, Vallejo, Woodside Inland, Delta and Coastal: American Canyon, Antioch, Benicia, Brentwood, Calistoga, Clayton, Cloverdale, Concord, Cotati, Danville, Dixon, Dublin, Fairfield, Gilroy, Half Moon Bay, Healdsburg, Lafayette, Livermore, Martinez, Moraga, Morgan Hill, Napa, Novato, Oakley, Orinda, Petaluma, Pittsburg, Pleasant Hill, Pleasanton, Rio Vista, Rohnert Park, San Ramon, Santa Rosa, Sebastopol, Sonoma, St. Helena, Suisun City, Vacaville, Walnut Creek, Windsor, Yountville Unincorporated: all unincorporated towns

The Consumer Expenditure Estimates dataset was created by SimplyAnalytics using small area estimation techniques. The Consumer Expenditure (CE) Public Use Microdata (PUMD) samples thousands of respondents (referred to as consumer units, or "CUs") across Texas. Each CU is assigned a weight that reflects the relative proportion of all American CUs that they represent. To estimate expenditures at the Census block group and ZCTA5 levels, we use data from the American Community Survey 5-Year Estimates as a proxy for how CUs are distributed over small areas, and use this information to derive expenditure estimates for all CE spending categories. Due to limitations on the PUMD sample size, and to account for national-level weighting of all CUs, the estimates are further adjusted to account for regional fluctuations in cost of living.

Abstract

The STEP (Skills Toward Employment and Productivity) Measurement program is the first ever initiative to generate internationally comparable data on skills available in developing countries. The program implements standardized surveys to gather information on the supply and distribution of skills and the demand for skills in labor market of low-income countries.

The uniquely-designed Household Survey includes modules that measure the cognitive skills (reading, writing and numeracy), socio-emotional skills (personality, behavior and preferences) and job-specific skills (subset of transversal skills with direct job relevance) of a representative sample of adults aged 15 to 64 living in urban areas, whether they work or not. The cognitive skills module also incorporates a direct assessment of reading literacy based on the Survey of Adults Skills instruments. Modules also gather information about family, health and language.

Geographic coverage

13 major metropolitan areas: Bogota, Medellin, Cali, Baranquilla, Bucaramanga, Cucuta, Cartagena, Pasto, Ibague, Pereira, Manizales, Monteira, and Villavicencio.

Analysis unit

The units of analysis are the individual respondents and households. A household roster is undertaken at the start of the survey and the individual respondent is randomly selected among all household members aged 15 to 64 included. The random selection process was designed by the STEP team and compliance with the procedure is carefully monitored during fieldwork.

Universe

The target population for the Colombia STEP survey is all non-institutionalized persons 15 to 64 years old (inclusive) living in private dwellings in urban areas of the country at the time of data collection. This includes all residents except foreign diplomats and non-nationals working for international organizations.

The following groups are excluded from the sample: - residents of institutions (prisons, hospitals, etc.) - residents of senior homes and hospices - residents of other group dwellings such as college dormitories, halfway homes, workers' quarters, etc. - persons living outside the country at the time of data collection.

Kind of data

Sample survey data [ssd]

Sampling procedure

Stratified 7-stage sample design was used in Colombia. The stratification variable is city-size category.

First Stage Sample The primary sample unit (PSU) is a metropolitan area. A sample of 9 metropolitan areas was selected from the 13 metropolitan areas on the sample frame. The metropolitan areas were grouped according to city-size; the five largest metropolitan areas are included in Stratum 1 and the remaining 8 metropolitan areas are included in Stratum 2. The five metropolitan areas in Stratum 1 were selected with certainty; in Stratum 2, four metropolitan areas were selected with probability proportional to size (PPS), where the measure of size was the number of persons aged 15 to 64 in a metropolitan area.

Second Stage Sample The second stage sample unit is a Section. At the second stage of sample selection, a PPS sample of 267 Sections was selected from the sampled metropolitan areas; the measure of size was the number of persons aged 15 to 64 in a Section. The sample of 267 Sections consisted of 243 initial Sections and 24 reserve Sections to be used in the event of complete non-response at the Section level.

Third Stage Sample The third stage sample unit is a Block. Within each selected Section, a PPS sample of 4 blocks was selected; the measure of size was the number of persons aged 15 to 64 in a Block. Two sample Blocks were initially activated while the remaining two sample Blocks were reserved for use in cases where there was a refusal to cooperate at the Block level or cases where the block did not belong to the target population (e.g., parks, and commercial and industrial areas).

Fourth Stage Sample The fourth stage sample unit is a Block Segment. Regarding the Block segmentation strategy, the Colombia document 'FINAL SAMPLING PLAN (ARD-397)' states "According to the 2005 population and housing census conducted by DANE, the average number of dwellings per block in the 13 large cities or metropolitan areas was approximately 42 dwellings. Based on this finding, the defined protocol was to report those cases in which 80 or more dwellings were present in a given block in order to partition block using a random selection algorithm." At the fourth stage of sample selection, 1 Block Segment was selected in each selected Block using a simple random sample (SRS) method.

Fifth Stage Sample The fifth stage sample unit is a dwelling. At the fifth stage of sample selection, 5582 dwellings were selected from the sampled Blocks/Block Segments using a simple random sample (SRS) method. According to the Colombia document 'FINAL SAMPLING PLAN (ARD-397)', the selection of dwellings within a participant Block "was performed differentially amongst the different socioeconomic strata that the Colombian government uses for the generation of cross-subsidies for public utilities (in this case, the socioeconomic stratum used for the electricity bill was used). Given that it is known from previous survey implementations that refusal rates are highest amongst households of higher socioeconomic status, the number of dwellings to be selected increased with the socioeconomic stratum (1 being the poorest and 6 being the richest) that was most prevalent in a given block".

Sixth Stage Sample The sixth stage sample unit is a household. At the sixth stage of sample selection, one household was selected in each selected dwelling using an SRS method.

Seventh Stage Sample The seventh stage sample unit was an individual aged 15-64 (inclusive). The sampling objective was to select one individual with equal probability from each selected household.

Sampling methodologies are described for each country in two documents and are provided as external resources: (i) the National Survey Design Planning Report (NSDPR) (ii) the weighting documentation (available for all countries)

Mode of data collection

Face-to-face [f2f]

Research instrument

The STEP survey instruments include:

• The background questionnaire developed by the World Bank (WB) STEP team
• Reading Literacy Assessment developed by Educational Testing Services (ETS).

All countries adapted and translated both instruments following the STEP technical standards: two independent translators adapted and translated the STEP background questionnaire and Reading Literacy Assessment, while reconciliation was carried out by a third translator.

The survey instruments were piloted as part of the survey pre-test.

The background questionnaire covers such topics as respondents' demographic characteristics, dwelling characteristics, education and training, health, employment, job skill requirements, personality, behavior and preferences, language and family background.

The background questionnaire, the structure of the Reading Literacy Assessment and Reading Literacy Data Codebook are provided in the document "Colombia STEP Skills Measurement Survey Instruments", available in external resources.

Cleaning operations

STEP data management process:

1) Raw data is sent by the survey firm 2) The World Bank (WB) STEP team runs data checks on the background questionnaire data. Educational Testing Services (ETS) runs data checks on the Reading Literacy Assessment data. Comments and questions are sent back to the survey firm. 3) The survey firm reviews comments and questions. When a data entry error is identified, the survey firm corrects the data. 4) The WB STEP team and ETS check if the data files are clean. This might require additional iterations with the survey firm. 5) Once the data has been checked and cleaned, the WB STEP team computes the weights. Weights are computed by the STEP team to ensure consistency across sampling methodologies. 6) ETS scales the Reading Literacy Assessment data. 7) The WB STEP team merges the background questionnaire data with the Reading Literacy Assessment data and computes derived variables.

Detailed information on data processing in STEP surveys is provided in "STEP Guidelines for Data Processing", available in external resources. The template do-file used by the STEP team to check raw background questionnaire data is provided as an external resource, too.`

Response rate

An overall response rate of 48% was achieved in the Colombia STEP Survey.

Abstract

This is the fourth Labor Force Survey of Tonga. The first one was conducted in 1990. Earlier surveys were conducted in 1990, 1993/94, and 2003 and the results of those surveys were published by the Statistics Department.

The objective of the LFS survey is providing information on not only well-known employment and unemployment as well as providing comprehensive information on other standard indicators characterizing the country labour market. It covers those age 10 and over in the whole Kingdom. Information includes age, sex, activity, current and usual employment status, hours worked and wages and in addition included a seperate Food Insecurity Experiences Survey (FIES) questionniare module at the Household Level.

The conceptual framework used in this labour force survey in Tonga aligns closely with the standards and guidelines set out in Resolutions of International Conferences of Labour Statistician.

Geographic coverage

National coverage.

There are six statistical regions known as Division's in Tonga namely Tongatapu urban area, Tongatapu rural area, Vava'u, Ha'pai, Eua and the Niuas.Tongatapu Urban refers to the capital Nuku'alofa is the urban area while the other five divisions are rural areas. Each Division is subdivided into political districts, each district into villages and each village into census enumeration areas known as Census Blocks. The sample for the 2018 Labour Force Survey (LFS) was designed to cover at least 2500 employed population aged 10 years and over from all the regions. This was made mainly to have sufficient cases to provide information on the employed population.

Analysis unit

• Households (for food insecurity module questionnaire)
• Individuals.

Universe

Population living in private households in Tonga. The labour force questionnaire is directed to the population aged 10 and above. Disability short set of questions is directed to all individuals age 2 and above and the food insecurity experience scale is directed to the head of household.

Kind of data

Sample survey data [ssd]

Sampling procedure

2018 Tonga Labour force survey aimed at estimating all the main ILO indicators at the island group level (geographical stratas). The sampling strategy is based on a two stages stratified random survey.

1. Computation of the survey parameters: Total sample size per strata, number of households to interview in each Primary Sampling Unit (PSU = census block) and number of PSUs to select The stratification of the survey is the geographical breakdown by island group (6 stratas Tongatapu urban, Tongatapu rural, Vava'u, Ha'apai, 'Eua, Niuas)
2. The selection strategy is a 2 stages random survey where: Random selection of census blocks within each
3. Census blocks are randomly selected in first place, using probability proportional to size

4. 15 households per block are randomly selected using uniform probability

5. The sampling frame used to select PSUs (census blocks) and household is the 2016 Tonga population census.

The computation of sample size required the use of: - Tonga 2015 HIES dataset (labour force section) - Tonga 2016 population census (distribution of households across the stratas) The resource variable used to compute the sample size is the labour force participation rate from the 2015 HIES. The use of the 2015 labour force section of the Tonga HIES allows the computation of the design effect of the labour force participation rate within each strata. The design effect and sampling errors of the labour force participation rate estimated from the 2015 HIES in combination with the 2016 household population distribution allow to predict the minimum sample size required (per strata) to get a robust estimate from the 2018 LFS.

Total sample size: 2685 households Geographical stratification: 6 island groups Selection process: 2 stages random survey where census blocks are selected using Probability Proportional to Size (Primary Sampling Unit) in the first place and households are randomly selected within each selected blocks (15 households per block) Non response: a 10% increase of the sample happened in all stratas to account for non-response Sampling frame: the household listing from the 2016 population census was used as a sampling frame and the 2015 labour force section of the HIES was used to compute the sample size (using labour force participation rate.

Sampling deviation

No major deviation from the original sample has taken place.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The 2018 Tonga Labour Force Survey questionnaire included 15 sections:

IDENTIFICATION SECTION B: INDIVIDUAL CHARACTERISTICS SECTION C: EDUCATION (AGE 3+) SECTIONS B & C: EMPLOYMENT IDENTIFICATION AND TEMPORARY ABSENCE (AGE 10+) SECTION D: AGRICULTURE WORK AND MARKET DESTINATION SECTION E1: MAIN EMPLOYMENT CHARACTERISTICS SECTION E2: SECOND PAID JOB/ BUSINESS ACTIVITY CHARACTERISTICS SECTION F: INCOME FROM EMPLOYMENT SECTION G: WORKING TIME SECTION H: JOB SEARCH SECTION I: PREVIOUS WORK EXPERIENCE SECTION J: MAIN ACTIVITY SECTION K: OWN USE PRODUCTION WORK FOOD INSECURITY EXPERIENCES GPS + PHOTO

The questionniares were developed and administered in English and were translated into Tongan language. The questionnaire is provided as external resources.

The draft questionnaire was pre-tested during the supervisors training and during the enumerators training and it was finally tested during the pilot test. The pilot testing was undertaken on the 27th of May to the 1st of June 2018 in Tongatapu Urban and Rural areas. The questionnaire was revised rigorously in accordance to the feedback received from each test. At the same time, a field operations manual for supervisors and enumerators was prepared and modified accordingly for field operators to use as a reference during the field work.

Cleaning operations

The World Bank Survey Solutions software was used for Data Processing, STATA software was used for data cleaning, tabulation tabulation and analysis.

Editing and tabulation of the data will be undertaken in February/March 2019 in collaboration with SPC and ILO.

Response rate

A total, 2,685 households were selected for the sample. Of these existing households, 2,584 were successfully interviewed, giving a household response rate of 96.2%.

Response rates were higher in urban areas than in the rural area of Tongatapu.

-1 Tongatapu urban: 97.30%
-2 Tongatapu rural: 93.00%
-3 Vava'u: 100.00% -4 Ha'pai: 100.00% -5 Eua: 95.20% -6 Niuas: 80.00% -Total: 96.20%.

Sampling error estimates

Sampling errors were computed and are presented in the final report.

The sampling error were computed using the survey set package in Stata. The Finite Population Correction was included in the sample design (optional in svy set Stata command) as follow: - Fpc 1: total number of census blocks within the strata (variable toteas) - Fpc 2: Here is a list of some LF indicators presented with sampling error

-RSE: Labour force population: 2.2% Employment - population in employment: 2.2% Labour force participation rate (%): 1.7% Unemployment rate (%): 13.5% Composite rate of labour underutilization (%): 7.3% Youth unemployment rate (%): 18.2% Informal employment rate (%): 2.7% Average monthly wages - employees (TOP): 12%.

-95% Interval: Labour force population: 28,203 => 30,804 Employment - population in employment: 27,341 => 29,855 Labour force participation rate (%): 45.2% => 48.2% Unemployment rate (%): 2.2% => 3.9% Composite rate of labour underutilization (%): 16% => 21.4% Youth unemployment rate (%): 5.7% => 12.1% Informal employment rate (%): 44.3% => 49.4% Average monthly wages - employees (TOP): 1,174 => 1,904.

Abstract

The 2018 Tonga National Disabiltiy Survey was conducted jointly by the Tonga Department of Statistics (TDS) and the Ministry of Internal Affairs, Social Protection and Disability. It is the first population-based comprehensive disability survey in the country. Funding was provided through number of bodies including UNICEF, DFAT and Tonga Government. The Pacific Community provided technical supports through out different stages of the survey.

The main purpose of the survey is to desctibe demographic, social and economic characteristics of persons with disabilities and detemine the prevalence by type of disability in Tonga, and thus help the government and decision makers in formulating more suitable national plans and policies relevant to persons with disabilities.

The other objectives of the Disability survey were collect data that would determine but not limited to the following: a. Disability prevalence rate at the national, urban and rural based on the Washington Group recommendations; b. degree of activity limitations and participation restrictions and societal activities for persons with disability: c. ascertain the specific vulnerabilities that children and adults with disability face in Tonga d. establish the accessibility of health and social services for persons with disability in Tonga e. generate data that guides the development of policies and strategies that ensure equity and opportunities for children and adults with disabilities.

An additional module was included to collect information on people's perception/experiences of service delivery of Goverment to the public.

Geographic coverage

National and island division coverage.

There are six statistical regions known as Divisions in Tonga namely Tongatapu urban area, Tongatapu rural area, Vava'u, Ha'apai, Eua and the Niuas.Tongatapu Urban refers to the capital Nuku'alofa is the urban area while the other five divisions are rural areas. Each Division is subdivided into political districts, each district into villages and each village into census enumeration areas known as Census Blocks.

Analysis unit

• Individuals
• Households.

Universe

The survey covers all usual residents of selected households, all children 2-17 years and adults 18 years and above and undertake comparisons between persons with and without disability.

Kind of data

Sample survey data [ssd]

Sampling procedure

SAMPLE SIZE: the total number of households to interview approximates 5,500 households based on the budget allocation available

SELECTION PROCESS: the selection of the sample is based on different steps (see previous section)

Stratification: this sample design is a stratified multi stage random survey. Stratification happened based on the disability status of the households and their geographical residence.

STAGES OF SELECTION: - the first stage of selection focussed on the selection of Enumeration Areas or Census Blocks as Primary Sampling Unit for households with disability. In total 334 PSUs have to be selected in order to cover the expected sample size. - the stage 2 of the selection concerns only the households with no disability as all households with disability from the selected EA are selected for interview

Level of representation: The survey will provide a comparison of the status between households with and without disability at the island group level.

REPLACEMENT: All non-response have been replaced according to the disability status of the household. Disable households that had to be replaced were replaced by another household with disability from the closest block.

SAMPLING FRAME: The sampling frame used was the 2016 population census. No additional listing were conducted.

The Sampling strategy is designed consistently with the purpose of the survey. The purpose of the 2018 Tonga Disability Survey is not to estimate the prevalence of disability in Tonga, which has been done on a very accurate way in the 2016 Population Census, but to compare the situation of the household with disability with the situation of households with not disability across the 6 geographical zones of Tonga.

The sampling strategy of the 2018 Tonga Disability Survey is based on 2 stages stratified random sample.

The stratification carried out in this survey is based on the disability status of the household: - strata 1: households who declared at least 1 member in disability (according to Washington Group list of question) - strata 2: households who did not report any disability member

The sampling frame used in this survey is the 2016 National Population Census that included the set of question on disability (from the Washington Group). In addition to the first set of stratification, the geographical breakdown of Tonga (by 6 island groups) has to be taken into consideration.

The overall idea is to equally split the total sample in both strata (1 & 2), which has been allocated to approximatively 5,500 households.

A replacement procedure is implemented in case of non -response.

The first step is to identify the households with disability from the population census. Households with disability are the households who reported at least 1 member as disable according to the 6functionning domains recommended by the Washington Group (see, hear, walk, remember, self-care, communicate).

In the strata 1, the sample distribution of approximatively 2,750 households was allocated using the square roots distribution of households across the 6 island groups. The next step consists in determining the number of blocks (Enumeration Areas) to select as Primary Sampling Unit. Again, by getting from the census frame the average number of households with disability in each block by island group will generate the number of blocks to select as PSU. Within each selected block, all households with disability will be selected for interview.

The strategy for strata 2 (non disable households) is to use the same blocks that have been selected for households in strata 1 and interview within those blocks the same number of households as strata 1.

Here is the final sample - after selection: Tongatapu urban: 1336
Tongatapu rural: 1884
Vava'u: 1060
Ha'apai: 550
Eua: 352
Niua: 54
TOTAL: 334

EA SELECTION (Primary Sampling Units labelled as blocks in the 2016 Tonga census): The EA were selected using probability proportional to size (size means number of households with disability within the EA). Within all selected EAs, all households with disability are selected for interview, and the same number of household with no disability. Households with no disability to interview in the EA were randomly selected, using uniform probability of selection.

Sampling deviation

Deviation from the original sampling plan was observed due to challenges in the field: The main fieldwork challenge was to trace the selected households (that were selected from the 2016 census frame) especially after cyclone Gita that hit Tonga before the field operation. Geography and composition of households have changed (and the household listing was not updated).

Under those circumstances, the total number of households interviewed has changed. Here is the percentage of modification between the original sampling plan and the survey achievements for each of the 2 stratas:

-STRATA 1: Tongatapu urban: 5% Tongatapu rural: 3% Vava'u: 6% Ha'apai: 0% Eua: -10% Niua: 103% Total: 4%

-STRATA 2 Tongatapu urban: 6% Tongatapu rural: 5% Vava'u: 2% Ha'apai: 1% Eua: 1% Niua: 133% Total: 5%.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Tonga Disability Survey 2018 used the CAPI system for the interview. However, the questionnaire was developed manually using excel and word software. The questionnaire was then converted to the CAPI using the Survey Solutions software. The questionnaire has two parts - the household and personal questions.

The Household questionnaire containing questions asking about characteristics of all household members of and about the household characteristics. It contains the following parts: · Household schedule/roster - listing all members and recording other social and economic information · Household characteristics - ask about household structure, characteristics, goods, assets and income.

The Personal questionnaire contains questions asking about child functioning among young children (aged 2-4 years) and older children (aged 5-17 years). Questions on adult functioning are also asked of adult aged 18 years and above. The personal questionnaire includes the following sections: · Young Child functioning for children aged 2-4 years old · Older child functioning for children aged 5-17 years old · Adult functioning for persons aged 18 years and older · Tools and service (2 years and above) · Needs and availability (2 years and above) · Transport (2 years and above) · Health care and support (5 years and above) · Education (5 years and above) · Employment and income (15 years and above) · Participation and accessibility (15 years and above) · Other social issues (18 years and above).

The development of the questionnaire went through several consultations and review from key partners and stakeholders within and outside Tonga including Tonga National Statistics Office, Non disability and disability offices in Tonga, UNICEF, WG, PDF, UNESCAP and SPC. Though the questionnaire was originally developped in English, it was also translated to Tongan local language. The first draft of the questionnaire was tested during the Pilot training and fieldwork. The questionnaire is provided as an external resource.

The draft questionnaire was pre-tested during

Abstract

The primary objective of the 2002-2003 Indonesia Young Adult Reproductive Health Survey (IYARHS) is to provide policymakers and program managers with data on knowledge, attitudes, and behavior of young adults about human reproduction, relationships, HIV/AIDS and other sexually transmitted infections. Being the first nationally representative survey of this kind in Indonesia, findings of the survey will also provide program managers with baseline data on these issues.

Specifically, the 2002-2003 IYARHS was designed to: • Measure the level of knowledge of young adults about reproductive health issues • Examine the attitudes of young adults on various issues in reproductive health • Measure the level of tobacco use, alcohol consumption, and drug use • Measure the level of sexual activity among young adults • Explore young adults’ awareness of HIV/AIDS and other sexually transmitted infections.

Geographic coverage

National coverage

Analysis unit

• Household
• Never married woman age 15-24
• Never married man age 15-24

Universe

The survey excluded people who live in institutional households such as dormitories and military barracks.

Kind of data

Sample survey data [ssd]

Sampling procedure

The IYARHS sample covered 1,815 unmarried women and 2,341 unmarried men. The respondents were identified in the 2002-2003 IDHS Household Questionnaire. The IDHS sample was drawn from a frame of census blocks (CBs) developed for the 2002 National Socioeconomic Survey (Susenas), for which a household listing had been conducted. The list includes all private households, which are defined as a person or a group of persons who usually sleep in the same housing unit and have a common arrangement for the preparation and consumption of food.

The IYARHS sample was stratified to yield reliable estimates at the national level. The remaining 26 provinces included in the Susenas are grouped in six strata: two in Sumatera and one each in Java, Nusa Tenggara, Kalimantan, and Sulawesi.

For further details on sample design and implementation, see Appendix A of the final report.

Mode of data collection

Face-to-face [f2f]

Research instrument

The survey data was collected using the Individual Questionnaire. The questionnaire was translated into Indonesian from English.

Cleaning operations

All completed questionnaires, accompanied by the control forms, were returned to the BPS central office in Jakarta for data entry and processing. The data processing consisted of office editing, coding of open-ended questions, data entry, verification, and editing computer-identified errors. Since the IYARHS was implemented in tandem with the 2002-2003 IDHS, census blocks that were selected for both surveys were processed simultaneously. A team of about 40 data entry clerks, data editors, and data entry supervisors processed the data. Census and Survey Processing System (CSPro) software was used to process the survey data.

Response rate

A total of 9,099 households were selected in the sample, of which 8,730 were occupied. Of the households found in the survey, 8,633 were successfully interviewed, yielding a response rate of 99 percent.

In the interviewed households, 2,187 female and 2,929 male respondents were identified for individual interview. Of these, completed interviews were conducted with 1,815 women and 2,341 men, yielding response rates of 83 and 80 percent, respectively.

Sampling error estimates

Detailed description of estimates of sampling errors are presented in Appendix B of the survey report.

VITAL SIGNS INDICATOR Population (LU1)

FULL MEASURE NAME Population estimates

LAST UPDATED October 2019

DESCRIPTION Population is a measurement of the number of residents that live in a given geographical area, be it a neighborhood, city, county or region.

DATA SOURCES U.S Census Bureau: Decennial Census No link available (1960-1990) http://factfinder.census.gov (2000-2010)

California Department of Finance: Population and Housing Estimates Table E-6: County Population Estimates (1961-1969) Table E-4: Population Estimates for Counties and State (1971-1989) Table E-8: Historical Population and Housing Estimates (2001-2018) Table E-5: Population and Housing Estimates (2011-2019) http://www.dof.ca.gov/Forecasting/Demographics/Estimates/

U.S. Census Bureau: Decennial Census - via Longitudinal Tract Database Spatial Structures in the Social Sciences, Brown University Population Estimates (1970 - 2010) http://www.s4.brown.edu/us2010/index.htm

U.S. Census Bureau: American Community Survey 5-Year Population Estimates (2011-2017) http://factfinder.census.gov

U.S. Census Bureau: Intercensal Estimates Estimates of the Intercensal Population of Counties (1970-1979) Intercensal Estimates of the Resident Population (1980-1989) Population Estimates (1990-1999) Annual Estimates of the Population (2000-2009) Annual Estimates of the Population (2010-2017) No link available (1970-1989) http://www.census.gov/popest/data/metro/totals/1990s/tables/MA-99-03b.txt http://www.census.gov/popest/data/historical/2000s/vintage_2009/metro.html https://www.census.gov/data/datasets/time-series/demo/popest/2010s-total-metro-and-micro-statistical-areas.html

CONTACT INFORMATION vitalsigns.info@bayareametro.gov

METHODOLOGY NOTES (across all datasets for this indicator) All legal boundaries and names for Census geography (metropolitan statistical area, county, city, and tract) are as of January 1, 2010, released beginning November 30, 2010, by the U.S. Census Bureau. A Priority Development Area (PDA) is a locally-designated area with frequent transit service, where a jurisdiction has decided to concentrate most of its housing and jobs growth for development in the foreseeable future. PDA boundaries are current as of August 2019. For more information on PDA designation see http://gis.abag.ca.gov/website/PDAShowcase/.

Population estimates for Bay Area counties and cities are from the California Department of Finance, which are as of January 1st of each year. Population estimates for non-Bay Area regions are from the U.S. Census Bureau. Decennial Census years reflect population as of April 1st of each year whereas population estimates for intercensal estimates are as of July 1st of each year. Population estimates for Bay Area tracts are from the decennial Census (1970 -2010) and the American Community Survey (2008-2012 5-year rolling average; 2010-2014 5-year rolling average; 2013-2017 5-year rolling average). Estimates of population density for tracts use gross acres as the denominator.

Population estimates for Bay Area PDAs are from the decennial Census (1970 - 2010) and the American Community Survey (2006-2010 5 year rolling average; 2010-2014 5-year rolling average; 2013-2017 5-year rolling average). Population estimates for PDAs are derived from Census population counts at the tract level for 1970-1990 and at the block group level for 2000-2017. Population from either tracts or block groups are allocated to a PDA using an area ratio. For example, if a quarter of a Census block group lies with in a PDA, a quarter of its population will be allocated to that PDA. Tract-to-PDA and block group-to-PDA area ratios are calculated using gross acres. Estimates of population density for PDAs use gross acres as the denominator.

Annual population estimates for metropolitan areas outside the Bay Area are from the Census and are benchmarked to each decennial Census. The annual estimates in the 1990s were not updated to match the 2000 benchmark.

The following is a list of cities and towns by geographical area: Big Three: San Jose, San Francisco, Oakland Bayside: Alameda, Albany, Atherton, Belmont, Belvedere, Berkeley, Brisbane, Burlingame, Campbell, Colma, Corte Madera, Cupertino, Daly City, East Palo Alto, El Cerrito, Emeryville, Fairfax, Foster City, Fremont, Hayward, Hercules, Hillsborough, Larkspur, Los Altos, Los Altos Hills, Los Gatos, Menlo Park, Mill Valley, Millbrae, Milpitas, Monte Sereno, Mountain View, Newark, Pacifica, Palo Alto, Piedmont, Pinole, Portola Valley, Redwood City, Richmond, Ross, San Anselmo, San Bruno, San Carlos, San Leandro, San Mateo, San Pablo, San Rafael, Santa Clara, Saratoga, Sausalito, South San Francisco, Sunnyvale, Tiburon, Union City, Vallejo, Woodside Inland, Delta and Coastal: American Canyon, Antioch, Benicia, Brentwood, Calistoga, Clayton, Cloverdale, Concord, Cotati, Danville, Dixon, Dublin, Fairfield, Gilroy, Half Moon Bay, Healdsburg, Lafayette, Livermore, Martinez, Moraga, Morgan Hill, Napa, Novato, Oakley, Orinda, Petaluma, Pittsburg, Pleasant Hill, Pleasanton, Rio Vista, Rohnert Park, San Ramon, Santa Rosa, Sebastopol, Sonoma, St. Helena, Suisun City, Vacaville, Walnut Creek, Windsor, Yountville Unincorporated: all unincorporated towns

The Consumer Expenditure Estimates dataset was created by SimplyAnalytics using small area estimation techniques. The Consumer Expenditure (CE) Public Use Microdata (PUMD) samples thousands of respondents (referred to as consumer units, or "CUs") across Texas. Each CU is assigned a weight that reflects the relative proportion of all American CUs that they represent. To estimate expenditures at the Census block group and ZCTA5 levels, we use data from the American Community Survey 5-Year Estimates as a proxy for how CUs are distributed over small areas, and use this information to derive expenditure estimates for all CE spending categories. Due to limitations on the PUMD sample size, and to account for national-level weighting of all CUs, the estimates are further adjusted to account for regional fluctuations in cost of living.

Abstract

Tonga Household Income and Expenditure Survey 2009 (HIES), undertaken by the Tonga Statistics Department during the period from 1 January 2009 to 31 December 2009. This is the second survey of its kind in Tonga. The last one was carried out in 2000/01, and the results were used in November 2002 to rebase the Consumer Price Index (CPI). A report from that survey was produced in December 2002, and where possible, results from this report will be made to be comparable to the previous report.

• To provide updated information for the expenditure item weights for the CPI;

• To provide some data for the components of National Accounts; and

• To provide information on the nature and distribution of household income and expenditure for planners, policy makers, and the general public.

Geographic coverage

National Coverage and Island Division.

Analysis unit

Private Households, individuals, Income and expenditure items.

Universe

The survey covered all members of the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample design was done in such a way that promoted estimates primarily at the national level, but also at the island division level. For that reason a higher sample fraction was selected in the smaller island divisions.

Rural Tongatapu received the smallest sample fraction (8.3%) as it had the highest population. On the other hand the Ongo Niua received the largest sample fraction (21.5%) as their population was the smallest. Overall a sample of roughly 10 per cent was selected for Tonga.

The sample was selected independently within each of the 6 target areas. Firstly, extremely remote areas were removed from the frame (and thus not given a chance of selection) as it was considered too expensive to cover these areas. These areas only represented about 3.5 per cent of the total population for Tonga, so the impact of their removal was considered very minimal.

The sampling in each area was then undertaken using a two-stage process. The first stage involved the selection of census blocks using Probability Proportional to Size (PPS) sampling, where the size measure was the expected number of households in that block. For the second stage, a fixed number (twelve) of households were selected from each selected census block using systematic sampling. The household lists for all selected blocks were updated just prior to the second stage of selection.

Given the sample was spread out over four quarters during the 2009 calendar year, every 4th selected census block was allocated to a respective quarter. To ensure an equally distribution of sample to each quarter, the number of census blocks selected for each of the six target group was made divisible by four. This therefore meant the sample size for each target group was adjusted so that it was divisible by (4*12)=48, as can be seen in Table 1 of Section 1 of the survey report.

Mode of data collection

Face-to-face [f2f]

Research instrument

There were 4 main survey schedules used to collect the information for the survey were published in English: 1) Household Questionnaire 2) Individual Questionnaire - Part 1 3) Individual Questionnaire - Part 2 4) Individual Diary (x2)

Household Questionnaire

This questionnaire is primarily used to collect information on large expenditure items, but also collects information about the dwelling characteristics. In total there are 14 sections to this uestionnaire which cover: 1 Dwelling Characteristics 2 Household Possessions 3 Dwelling Tenure 4 Construction of Dwellings 5 Household Bills 6 Transport Expenses 7 Major Consumer Durables 8 Education/Recreation 9 Medical & Health 10 Overseas Travel 11 Special Events 12 Subsistence Activity Sales 13 Remittances 14 Contributions to Church/Village/School As stated above, the first section is devoted to collecting information about key dwelling characteristics, whereas the second section collects information on household possessions. Sections 3-11, and Section 14, focus on expenses the household incurs, whereas Section 13 focuses on remittances both paid by and received by the household. Finally, Section 12 collects information from households about the income they generate from subsistence activities. This section is the main question collecting income from the household questionnaire, as was included here as it was considered more appropriate to collect this data at the household level. The front page of this Questionnaire is also used for collecting the Roster of Household Members.

Individual Questionnaire - Part 1

This questionnaire collects basic demographic information about each individual in the household, including: • Relationship to Household Head • Sex • Age • Ethnicity • Marital Status

Also collected in this form is information about health problems each individual may have encountered in the last 3 months, followed by education information. For the education section, if a person is currently attending an education institution, then current level is asked, whereas if the person attended an education institution but no longer attends, then the highest level completed is collected. The last main section of this form collects information about labour force and is only asked of individuals aged 10 years and above. These questions aim to classify each person in scope for this section as either: • In the Labour Force - Employed • In the Labour Force - Unemployed • Not in the Labour Force

Individual Questionnaire - Part 2

This questionnaire is focused on collecting information from individuals regarding their income. There are eight sections to this questionnaire of which six are devoted to income. They include: 1 Wages and Salary 2 Self-Employment
3 Previous Jobs
4 Ad-hoc Jobs 5 Pensions/Welfare Benefits 6 Other Income 7 Loan Information 8 Contributions to Benefit Schemes

As stated above, the first six sections of this questionnaire focus on income. Section 7 collects information pertaining to loans for i) households, ii) cars, iii) special events and iv) other, and finally the last question is an expense related question covering contributions to benefit schemes which was considered best covered at an individual level.

Individual Diary

The last form used for the survey was the Individual Diary which each individual aged 10 years and over was required to fill in for two weeks (two one-week diaries).

Each diary had 4 sections covering the following: 1) Items Purchased: This section had a separate page for each day and was for recording all items bought in a store, street vendors, market or any other place (including credit) 2) Home Grown/Produced Items: This section was for recording home grown/produced items consisting of items such as food grown at home or at the family plantation, self caught or gathered fish and homemade handicrafts and other goods grown and produced at home. Information is recorded for these items consumed by the household which they produced themselves, these items they gave away as a gift, and these items they received as a gift. 3) Gifts Given and Received: This section of the diary is for recording gifts given and received including both cash and purchased goods (but not home produced). If any member of the household receives a gift that meets this criteria during the diary keeping period from someone who is not a member of their household it is recorded here. 4) Winnings from Gambling: The last section of the Diary is for recording all winnings from gambling during the diary keeping period.

Cleaning operations

Batch edits in CSPro were performed on the data after data entry was completed. The batch edits were aimed at identifying any values falling outside acceptable ranges, as well as other inconsistencies in the data. As this process was done at the batch level, questionnaires were often referred to and manual changes to the data were performed to amend identified errors.

One significant problem which was identified during this process was the incorrect coding of phone card purchase to the purchase of actual phones. As there were many such cases, an automatic code change was applied to any purchase of phones which was less than $40 - recoding them to purchase of phone cards.

Response rate

The final Response Rates for the survey was high, which will assist in yielding statistically significant estimates. Across all six target groups the response rate was in excess of 95 per cent, with the exception of Ongo Niua who only reported 50 per cent. The reason the number was so low in the Ongo Niua was because this target area was only visited in the 2nd quarter, where half the total sample were enumerated (to make up for the sample loss in the first quarter), and was not visited again in quarter 3 and 4.

The reason behind the high response rates in other areas was due to the updated lists for selected census blocks excluding vacant dwellings. As such, it was mostly refusals that impacted on the final response rates.

Sampling error estimates

Sampling errors refer to those errors that are implicit in any sample survey, where only a portion of the population is covered. Non-sampling errors refer to all other types of error. These can arise at any stage of the survey process. Examples of activities that are likely to increase the level of non-sampling error are: failing to select a proper sample, poor questionnaire design, weak field supervision, inaccurate data entry, insufficient data editing, or failure to analyze or report on the data

The Consumer Expenditure Estimates dataset was created by SimplyAnalytics using small area estimation techniques. The Consumer Expenditure (CE) Public Use Microdata (PUMD) samples thousands of respondents (referred to as consumer units, or "CUs") across Texas. Each CU is assigned a weight that reflects the relative proportion of all American CUs that they represent. To estimate expenditures at the Census block group and ZCTA5 levels, we use data from the American Community Survey 5-Year Estimates as a proxy for how CUs are distributed over small areas, and use this information to derive expenditure estimates for all CE spending categories. Due to limitations on the PUMD sample size, and to account for national-level weighting of all CUs, the estimates are further adjusted to account for regional fluctuations in cost of living.

Abstract

The Annual Survey of Industries (ASI) is the principal source of industrial statistics in India. It provides statistical information to assess changes in the growth, composition and structure of organised manufacturing sector comprising activities related to manufacturing processes, repair services, gas and water supply and cold storage. Industrial sector occupies an important position in the State economy and has a pivotal role to play in the rapid and balanced economic development. The Survey is conducted annually under the statutory provisions of the Collection of Statistics Act 1953, and the Rules framed there-under in 1959, except in the State of Jammu & Kashmir where it is conducted under the State Collection of Statistics Act, 1961 and the rules framed there-under in 1964.

Geographic coverage

The ASI extends its coverage to the entire country upto state level.

Analysis unit

The primary unit of enumeration in the survey is a factory in the case of manufacturing industries, a workshop in the case of repair services, an undertaking or a licensee in the case of electricity, gas & water supply undertakings and an establishment in the case of bidi & cigar industries. The owner of two or more establishments located in the same State and pertaining to the same industry group and belonging to same scheme (census or sample) is, however, permitted to furnish a single consolidated return. Such consolidated returns are common feature in the case of bidi and cigar establishments, electricity and certain public sector undertakings.

Universe

The survey cover factories registered under the Factory Act 1948. Establishments under the control of the Defence Ministry,oil storage and distribution units, restaurants and cafes and technical training institutions not producing anything for sale or exchange were kept outside the coverage of the ASI. The geographical coverage of the Annual Survey of Industries, 2004-2005 has been extended to the entire country except the states of Arunachal Pradesh, Mizoram and Sikkim and Union Territory of Lakshadweep.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sampling Procedure

The sampling design followed in ASI 2004-05 is a stratified circular systematic one. All the factories in the updated frame (universe) are divided into two sectors, viz., Census and Sample.

Census Sector: Census Sector is defined as follows:

a) All industrial units belonging to the six less industrially developed states/ UT's viz. Manipur, Meghalaya, Nagaland, Tripura, Sikkim and Andaman & Nicobar Islands.
b) For the rest of the twenty-six states/ UT's., (i) units having 100 or more workers, and (ii) all factories covered under Joint Returns. c) After excluding the Census Sector units as defined above, all units belonging to the strata (State by 4-digit of NIC-04) having less than or equal to 4 units are also considered as Census Sector units.

Remaining units, excluding those of Census Sector, called the sample sector, are arranged in order of their number of workers and samples are then drawn circular systematically considering sampling fraction of 20% within each stratum (State X Sector X 4-digit NIC) for all the states. An even number of units with a minimum of 4 are selected and evenly distributed in two sub-samples. The sectors considered here are Biri, Manufacturing and Electricity.

Sampling deviation

There was no deviation from sample design in ASI 2004-05

Mode of data collection

Statutory return submitted by factories as well as Face to face

Research instrument

Annual Survey of Industries Questionnaire (in External Resources) is divided into different blocks:

BLOCK A.IDENTIFICATION PARTICULARS BLOCK B. PARTICULARS OF THE FACTORY (TO BE FILLED BY OWNER OF THE FACTORY) BLOCK C: FIXED ASSETS BLOCK D: WORKING CAPITAL & LOANS BLOCK E : EMPLOYMENT AND LABOUR COST BLOCK F : OTHER EXPENSES BLOCK G : OTHER INCOMES BLOCK H: INPUT ITEMS (indigenous items consumed) BLOCK I: INPUT ITEMS – directly imported items only (consumed) BLOCK J: PRODUCTS AND BY-PRODUCTS (manufactured by the unit)

Cleaning operations

Pre-data entry scrutiny was carried out on the schedules for inter and intra block consistency checks. Such editing was mostly manual, although some editing was automatic. But, for major inconsistencies, the schedules were referred back to NSSO (FOD) for clarifications/modifications.

Code list, State code list, Tabulation program and ASICC code are also may be refered in the External Resources which are used for editing and data processing as well..

Tabulation procedure The tabulation procedure by CSO (ISW) includes both the ASI 2004-05 data and the extracted data from ASI 03-04 for all tabulation purpose. For extracted returns, status of unit (Block A, Item 12) would be in the range 17 to 20. To make results comparable, users are requested to follow the same procedure. For calculation of various parameters, users are requested to refer instruction manual/report. Please note that a separate inflation factor (Multiplier) is available for each unit against records belonging to Block-A for ASI 2004-05 data. The multiplier is calculated for each stratum (i.e. State X NIC-04 (4 Digit) after adjusting for non-response cases.

Note that for all processing Status of unit code 17 to 20 should always be considered.

Merging of unit level data As per existing policy to merge unit level data at ultimate digit level of NIC'04 (i.e., 5 digit) for the purpose of dissemination, the data have been merged for industries having less than three units within State, District and NIC-04 (5 Digit) with the adjoining industries within district and then to adjoining districts within a state. There may be some NIC-04 (5 Digit) ending with '9' that do not figure in the book of NIC '04. These may be treated as 'Others' under the corresponding 4-digit group. To suppress the identity of factories data fields corresponding to PSL number, Industry code as per Frame (4-digit level of NIC-04) and RO/SRO code have been filled with '9' in each record.

It may please be noted that, tables generated from the merged data may not tally with the published results for few industries, since the merging for published data has been done at aggregate-level to minimise the loss of information.

Sampling error estimates

Relative Standard Error (RSE) is calculated in terms of worker, wages to worker and GVA using the formula. Programs developed in Visual Foxpro are used to compute the RSE of estimates.

Data appraisal

To check for consistency and reliability of data the same are compared with the NIC-2digit level growth rate at all India Index of Production (IIP) and the growth rates obtained from the National Accounts Statistics at current and constant prices for the registered manufacturing sector.

Abstract

Introduction

The Annual Survey of Industries (ASI) is the principal source of industrial statistics in India. It provides statistical information to assess changes in the growth, composition and structure of organised manufacturing sector comprising activities related to manufacturing processes, repair services, gas and water supply and cold storage. The Survey is conducted annually under the statutory provisions of the Collection of Statistics Act 1953, and the Rules framed there-under in 1959, except in the State of Jammu & Kashmir where it is conducted under the State Collection of Statistics Act, 1961 and the rules framed there-under in 1964.

Geographic coverage

The ASI extends its coverage to the entire country upto state level.

Analysis unit

The primary unit of enumeration in the survey is a factory in the case of manufacturing industries, a workshop in the case of repair services, an undertaking or a licensee in the case of electricity, gas & water supply undertakings and an establishment in the case of bidi & cigar industries. The owner of two or more establishments located in the same State and pertaining to the same industry group and belonging to same scheme (census or sample) is, however, permitted to furnish a single consolidated return. Such consolidated returns are common feature in the case of bidi and cigar establishments, electricity and certain public sector undertakings.

Merging of unit level data As per existing policy to merge unit level data at ultimate digit level of NIC'08 (i.e., 5 digit) for the purpose of dissemination, the data have been merged for industries having less than three units within State, District and NIC-08 (5 Digit) with the adjoining industries within district and then to adjoining districts within a state. There may be some NIC-08 (5 Digit) ending with '9' that do not figure in the book of NIC '08. These may be treated as 'Others' under the corresponding 4-digit group. To suppress the identity of factories data fields corresponding to PSL number, Industry code as per Frame (4-digit level of NIC-09) and RO/SRO code have been filled with '9' in each record.

It may please be noted that, tables generated from the merged data may not tally with the published results for few industries, since the merging for published data has been done at aggregate-level to minimise the loss of information.

Universe

The survey cover factories registered under the Factory Act 1948. Establishments under the control of the Defence Ministry,oil storage and distribution units, restaurants and cafes and technical training institutions not producing anything for sale or exchange were kept outside the coverage of the ASI. The geographical coverage of the Annual Survey of Industries, 2008-2009 has been extended to the entire country except the states of Arunachal Pradesh, Mizoram and Sikkim and Union Territory of Lakshadweep.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sampling Procedure

The sampling design followed in ASI 2008-09 is a stratified circular systematic one. All the factories in the updated frame (universe) are divided into two sectors, viz., Census and Sample.

Census Sector: Census Sector is defined as follows:

a) All industrial units belonging to the six less industrially developed states/ UT's viz. Manipur, Meghalaya, Nagaland, Tripura, Sikkim and Andaman & Nicobar Islands.
b) For the rest of the twenty-six states/ UT's., (i) units having 100 or more workers, and (ii) all factories covered under Joint Returns. c) After excluding the Census Sector units as defined above, all units belonging to the strata (State by 4-digit of NIC-04) having less than or equal to 4 units are also considered as Census Sector units.

Remaining units, excluding those of Census Sector, called the sample sector, are arranged in order of their number of workers and samples are then drawn circular systematically considering sampling fraction of 20% within each stratum (State X Sector X 4-digit NIC) for all the states. An even number of units with a minimum of 4 are selected and evenly distributed in two sub-samples. The sectors considered here are Biri, Manufacturing and Electricity.

Sampling deviation

There was no deviation from sample design in ASI 2008-09.

Mode of data collection

Statutory return submitted by factories as well as Face to face

Research instrument

Annual Survey of Industries Questionnaire (in External Resources) is divided into different blocks:

BLOCK A.IDENTIFICATION PARTICULARS BLOCK B. PARTICULARS OF THE FACTORY (TO BE FILLED BY OWNER OF THE FACTORY) BLOCK C: FIXED ASSETS BLOCK D: WORKING CAPITAL & LOANS BLOCK E : EMPLOYMENT AND LABOUR COST BLOCK F : OTHER EXPENSES BLOCK G : OTHER INCOMES BLOCK H: INPUT ITEMS (indigenous items consumed) BLOCK I: INPUT ITEMS – directly imported items only (consumed) BLOCK J: PRODUCTS AND BY-PRODUCTS (manufactured by the unit)

Cleaning operations

Pre-data entry scrutiny was carried out on the schedules for inter and intra block consistency checks. Such editing was mostly manual, although some editing was automatic. But, for major inconsistencies, the schedules were referred back to NSSO (FOD) for clarifications/modifications.

A list of validation checks carried out on data files is given in External Resources "Validation checks, ASI 2008-09". Code list, State code list, Tabulation program and ASICC code are also may be refered in the External Resources which are used for editing and data processing as well..

Response rate

No. of units to be surveyed No. of units responded No. of units non-responded Response rate (in %)

  58300             52376                  5924             89.84

Sampling error estimates

Relative Standard Error (RSE) is calculated in terms of worker, wages to worker and GVA using the formula (Pl ease refer to Estimation Procedure document in external resources). Programs developed in Visual Foxpro are used to compute the RSE of estimates.

Data appraisal

To check for consistency and reliability of data the same are compared with the NIC-2digit level growth rate at all India Index of Production (IIP) and the growth rates obtained from the National Accounts Statistics at current and constant prices for the registered manufacturing sector.

Abstract

The objective of PLFS is primarily on two aspects. The first is to measure the dynamics in labour force participation and employment status in the short time interval of three months for the urban areas only in the Current Weekly Status (CWS). Thus, in every quarter, PLFS will bring out the level and change estimates of the key labour force indicators in CWS viz. Worker Population Ratio (WPR), Labour Force Participation Rate (LFPR), Unemployment Rate (UR). Secondly, for both rural and urban areas, level estimates of all important parameters in both usual status and CWS will be brought out annually.

Geographic coverage

The survey covers the whole of the Indian Union except the villages in Andaman and Nicobar Islands which remain extremely difficult to access throughout the year. 12800 FSUs (7024 villages and 5776 UFS blocks) are being covered annually at all-India level.

Sampling procedure

Rotational panel design for urban areas i.The initial rotational panel is for two years, where only 25% FSUs of urban annual allocation will be covered in the first quarter (Panel Ptwo-year period of rotation. 11) with detail listing and canvassing of visit 1 schedule in the selected households. ii. Another 25% FSUs will be covered in the second quarter (Panel P12) for taking up visit 1 schedule and revisit schedule will be canvassed in the selected households of Panel P11. iii. A new panel P13 of 25% FSUs will be surveyed in third quarter with visit 1 schedule and revisit schedules will be canvassed in the households of panels P11 & P12. iv. In the fourth quarter, households of panels P11, P12 & P13 will be surveyed with revisit schedule and a new panel P14 with 25% FSUs for visit 1 schedule. v. In the subsequent quarters of second year 75% FSUs (3 panels - P12, P13 & P14) will be common and an earlier panel (P11) will be replaced by a new panel (P15) for canvassing visit 1 schedule. This will continue till 8th quarter. vi. All the FSUs of the panels P11, P12, ...., P18 (each of which is with 25% of FSUs) will be selected before commencement of survey in the first quarter. vii. At the end of the second year of each two-year duration, updated frame will be used for both rural and urban areas. viii. FSUs of another set of panels P21, P22, ..., P28 selected from the updated frame will be made ready before commencement of first quarter of third year (first quarter of the second two-year duration). These panels P21 to P28 will take care of the changes in the urban frame during the intracensal period. ix. In the ninth quarter (first quarter of the second two-year duration), panel P21 selected from the updated frame will be introduced and the panels P16, P17 and P18 of the old frame will be surveyed. x. This scheme will continue for another 2 years with the introduction of panels P22 to P28 each in one quarter for the subsequent 7 quarters till the end of the fourth year (second year of the two-year period). xi. This scheme of rotation of panels will enable generation of estimates of change parameters with 75% matching and 25% of unmatched samples from fifth quarter onwards. xii. One of the main advantages of this plan of rotation is that there will not be any break in the series of estimates of the change parameters starting from 5th quarter. xiii. Since major changes in the rural-urban frame occurs in the Census years (say for the year 2023-24), provision is to be made to generate estimates without break in the series of estimates considering panels from pre and post-census frames.

1.3.3 Rural samples For rural areas, samples for all the 8 quarters have been selected before commencement of survey for each two-year period, while the frame remains same for this duration. In each quarter, only 25% FSUs of annual allocation (as is done in each sub-round of NSS rounds) are being covered in rural areas so that independent estimates can be generated for each quarter. For this purpose, quarterly allocation is multiple of 2 for drawing interpenetrating sub-samples. There will not be any revisit in the rural samples.

Outline of the design: A stratified multi-stage design has been adopted. The first stage units (FSU) are the Urban Frame Survey (UFS) blocks in urban areas and 2011 Population Census villages (Panchayat wards for Kerala) in rural areas. The ultimate stage units (USU) are households. As in usual NSS rounds, in the case of large FSUs one intermediate stage unit, called hamlet group/sub-block, will be formed. Periodic Labour Force Survey 4 Note on sample design and estimation procedure 1.3.7 Sampling Frame for First Stage Units: The list of latest available Urban Frame Survey (UFS) blocks is considered as the urban sampling frame. List of 2011 Population Census villages (Panchayat wards for Kerala) constitutes the rural sampling frame. Since the duration of rotational panel is of two-year, the urban sampling frame once updated incorporating the changes made in the current phase of UFS will remain unchanged for two years. Similarly the rural sampling frame with changes, if any, for urbanisation of village(s) will remain unchanged for two years. After completion of every two-year period, the frames will be updated for incorporating the changes likely to occur during this period. When next Population Census details will be available, the new frame will be used only when UFS blocks for all newly declared Census Towns and Statutory Towns are available for preparation of sampling frame, as the new list of census villages will not include those villages which will be considered as urban areas. ......

Mode of data collection

Face to Face

Abstract

The Employment and Unemployment surveys of National sample Survey (NSS) are primary sources of data on various indicators of labour force at National and State levels. These are used for planning, policy formulation, decision support and as input for further statistical exercises by various Government organizations, academicians, researchers and scholars. NSS surveys on employment and un-employment with large sample size of households have been conducted quinquennially from 27th. round(October'1972 - September'1973) onwards. The NSS 68th. round carried out during July'2011 - June'2012 was the nineth quinquennial round in the series covering subjects of (i) Household Consumer Expenditure and (ii) Employment and Unemployment.

Field work of the survey is carried out by the Field Operation Division ( FOD ) of National Sample Survey Office ( NSSO ) in which the central samples are covered. most of the State Governments also participate in the survey on matching sample size basis.

The National Sample Survey Office (NSSO) during the period July 2011 - June 2012 carried out an all-India household survey on the subject of employment and unemployment in India as a part of 68th round of its survey programme. In this survey, the nation-wide enquiry was conducted to generate estimates of various characteristics pertaining to employment and unemployment and labour force characteristics at the national and State levels. Information on various facets of employment and unemployment in India was collected through a schedule of enquiry (Schedule 10) adopting the established concepts, definitions and procedures. Based on the data collected during the entire period of survey, estimates of some key employment-unemployment characteristics in India and States have been presented in the NSSO published report on Key Indicators of Employment and Unemployment July'2011 - June'2012 ( 68th Round).

The main objective of the employment-unemployment surveys conducted by NSSO at periodic interval is to get estimates of level parameters of various employment and unemployment characteristics at national and State level. These statistical indicators on labour market are required for planning, policy and decision making at various levels, both within the government and outside. The critical issues in the context of labour force enquiries pertain to defining the labour force and measuring participation of labour force in different economic activities. The activity participation of the people is not only dynamic but also multidimensional: it varies with region, age, education, gender, level of living, industry and occupational category. These aspects of the labour force are captured in detail in the NSS survey on employment and unemployment and estimates are generated for labour force participation rate, worker population ratio, unemployment rate, wages of employees, etc. The indicators of the structural aspects of the workforce such as status in employment, industrial distribution and occupational distribution are also derived from the survey. Besides, from the data collected on the particulars of enterprises and conditions of employment, the aspects of employment in the informal sector and informal employment are reflected through the conceptual framework of the survey.

Geographic coverage

The survey covered the whole of the Indian Union except (i) interior villages of Nagaland situated beyond five kilometres of the bus route and (ii) villages in Andaman and Nicobar Islands which remained inaccessible throughout the year.

Analysis unit

Households and Persons

Universe

Households and members of the household

Kind of data

Sample survey data [ssd]

Sampling procedure

The 68th round (July 2011-June 2012) of NSS was earmarked for survey on 'Household Consumer Expenditure' and 'Employment and Unemployment'. The survey covered the whole of the Indian Union except (i) interior villages of Nagaland situated beyond five kilometres of the bus route and (ii) villages in Andaman and Nicobar Islands which remain inaccessible throughout the year. In addition to these, all the sample first stage units of the following areas were casualty in different sub-rounds: in sub-rounds 1, 2,3 and 4. In each of these four sub-rounds equal number of sample villages/ blocks (FSUs) was allotted for survey with a view to ensuring uniform spread of sample FSUs over the entire survey period. Attempt was made to survey each of the FSUs during the sub-round to which it is allotted. Because of the arduous field conditions, this restriction need not be strictly enforced in Andaman and Nicobar Islands, Lakshadweep and rural areas of Arunachal Pradesh and Nagaland.

Sample Design A stratified multi-stage design has been adopted for the 68th round survey. The first stage units (FSU) was the 2001 census villages (Panchayat wards in case of Kerala) in the rural sector and Urban Frame Survey (UFS) blocks in the urban sector. The ultimate stage units (USU) was households in both the sectors. In case of large FSUs, one intermediate stage of sampling was the selection of two hamlet-groups (hgs)/ sub-blocks (sbs) from each rural/ urban FSU.

Selection of the first-stage units: The various steps involved before making the selection of the FSUs are discussed at length in the following few paragraphs before taking up the issue of selection of USUs within FSUs.

Sampling Frame for First Stage Units: For the rural sector, the list of 2001 census villages (Panchayat wards in case of Kerala) constituted the sampling frame. For the urban sector, the list of latest available UFS blocks constituted the sampling frame.

Stratification of the first stage units: Within each district of a State/ UT, two basic strata were formed as follows: Within each sector of a State/ UT, the respective sample size will be allocated to the different strata/ sub-strata in proportion to the population as per census 2001. Allocations at stratum level were adjusted to multiples of 4 with a minimum sample size of 4. Allocation for each sub-stratum was 4. Equal number of samples were allocated among the four sub-rounds.

Selection of first-stage units: For the rural sector, from each stratum/ sub-stratum, required number of sample villages were selected by probability proportional to size with replacement (PPSWR), size being the population of the village as per Census 2001. For urban sector, from each stratum FSUs were selected by using Simple Random Sampling Without Replacement (SRSWOR). Both rural and urban samples were drawn in the form of two independent sub-samples.

Selection of Ultimate Stage Units (USU) within a FSU: The remaining paragraphs of this sub-section outlines the various steps leading to the actual selection of USUs within a FSU.

Criterion for hamlet-group/ sub-block formation: After identification of the boundaries of the FSU, it is to be determined whether listing was done in the whole sample FSU or not. In case the population of the selected FSU is found to be 1200 or more, it should be divided into a suitable number (say, D) of 'hamlet-groups' in the rural sector and 'sub-blocks' in the urban sector by more or less equalising the population as stated below.

approximate present population of the sample FSU no. of hg's/sb's to be formed

less than 1200 (no hamlet-groups/sub-blocks) 1
1200 to 1799 3
1800 to 2399 4
2400 to 2999 5
3000 to 3599 6
…………..and so on

For rural areas of Himachal Pradesh, Sikkim, Uttarakhand (except four districts Dehradun (P), Nainital (P), Hardwar and Udham Singh Nagar), Poonch, Rajouri, Udhampur, Doda, Leh (Ladakh), Kargil districts of Jammu and Kashmir and Idukki district of Kerala, the number of hamlet-groups were formed as follows:

approximate present population of the sample village no. of hg's to be formed

less than 600 (no hamlet-groups) 1 600 to 899 3 900 to 1199 4 1200 to 1499 5 .………..and so on

Formation and selection of hamlet-groups/ sub-blocks: In case hamlet-groups/ sub-blocks are to be formed in the sample FSU, the same should be done by more or less equalizing population.It was ensured that the hamlet-groups/ sub-blocks formed were clearly identifiable in terms of physical landmarks.

Two hamlet-groups (hg)/ sub-blocks (sb) were selected from a large FSU wherever hamlet-groups/ sub-blocks have been formed in the following manner - one hg/ sb with maximum percentage share of population always selected and termed as hg/ sb 1; one more hg/ sb selected from the remaining hg's/ sb's by simple random sampling (SRS) and termed as hg/ sb 2. Listing and selection of the households done independently in the two selected hamlet-groups/ sub-blocks. The FSUs without hg/ sb formation treated as sample hg/ sb number 1. It is to be noted that if more than one hg/ sb have same maximum percentage share of population, the one among them which is listed first in block 4.2 of schedule 0.0 treated as hg/ sb 1.

Listing of households: Having determined the hamlet-groups/ sub-blocks, i.e. area(s) to be considered for listing, the next step is to list all the households (including those found to be temporarily locked after ascertaining the temporariness of locking of households through

Abstract

The National Sample Survey Organisation (NSSO) conducted an integrated survey encompassing various aspects of the socio-economic scenario during July to December 2002. The survey, among others, included the housing condition of all segments of population. Information on the available condition of the structure where the household stays, the amenities available in their houses and details of construction work undertaken by households, were collected in the current survey through household enquiry.

Geographic coverage

The survey covered whole of the Indian Union except (i) Leh and Kargil districts of Jammu & Kashmir, (ii) villages situated beyond 5 kms. of bus route in the state of Nagaland, and (iii) inaccessible villages of Andaman and Nicobar Islands. Thus the corresponding State/UT level estimates and the all-India results presented in this report are based on the areas falling under the coverage of the survey.

Analysis unit

Randomly selected households based on sampling procedure and members of the household

Universe

The survey used the interview method of data collection from a sample of randomly selected households and members of the household

Kind of data

Sample survey data [ssd]

Sampling procedure

A stratified multi-stage sampling design was adopted for selection of the ultimate sample units. The first-stage units (FSUs) for the survey were villages (panchayat wards in Kerala) in the rural areas and the Urban Frame Survey (UFS) blocks in urban areas. If an FSU was quite large, it was divided into smaller areas of equal population, called hamlet-groups, and two hamlet-groups were selected at random and merged, demarcating the area to be used for selection of the households - the ultimate stage units. The households were selected at random from the entire FSU, if the FSU was not large, or from the selected hamlet-groups for larger FSUs. A detailed discussion on the sample design and estimation procedure followed in the survey is given as an ATTACHMENT in external resources.

Sampling deviation

There was no deviation from the original sample deviation.

Mode of data collection

Face-to-face [f2f]

Research instrument

Schedule 1.2 consists of 12 blocks including block 0. The blocks are:

Block 0: descriptive identification of sample household  
Block 1: identification of sample household
Block 2: particulars of field operation

Block 3: household characteristics Block 4: particulars of living facilities Block 5: housing characteristics and micro environment
Block 6: particulars of the dwelling Block 7: particulars of construction and repair for residential purpose Block 8: particulars of dwelling / land owned elsewhere within the country Block 9: some general particulars of slum dwellers Block 10: remarks by investigator Block 11: comments by supervisory officer(s)

Response rate

A total of 8338 first stage units, i.e., villages (panchayat wards for Kerala) in the rural and UFS blocks in the urban were selected for this survey, of which 8307 could be surveyed in the central sample. At the all-India level, a total of 97882 households were captured in the surveyed FSUs.

The Consumer Expenditure Estimates dataset was created by SimplyAnalytics using small area estimation techniques. The Consumer Expenditure (CE) Public Use Microdata (PUMD) samples thousands of respondents (referred to as consumer units, or "CUs") across Texas. Each CU is assigned a weight that reflects the relative proportion of all American CUs that they represent. To estimate expenditures at the Census block group and ZCTA5 levels, we use data from the American Community Survey 5-Year Estimates as a proxy for how CUs are distributed over small areas, and use this information to derive expenditure estimates for all CE spending categories. Due to limitations on the PUMD sample size, and to account for national-level weighting of all CUs, the estimates are further adjusted to account for regional fluctuations in cost of living.

Abstract

Introduction

The Annual Survey of Industries (ASI) is the principal source of industrial statistics in India. It provides statistical information to assess changes in the growth, composition and structure of organised manufacturing sector comprising activities related to manufacturing processes, repair services, gas and water supply and cold storage. Industrial sector occupies an important position in the State economy and has a pivotal role to play in the rapid and balanced economic development. The Survey is conducted annually under the statutory provisions of the Collection of Statistics Act 1953, and the Rules framed there-under in 1959, except in the State of Jammu & Kashmir where it is conducted under the State Collection of Statistics Act, 1961 and the rules framed there-under in 1964.

Geographic coverage

Coverage of the Annual Survey of Industries extends to the entire Factory Sector, comprising industrial units (called factories) registered under section 2(m)(i) and 2(m)(ii) of the Factories Act.1948, wherein a "Factory", which is the primary statistical unit of enumeration for the ASI is defined as:- "Any premises" including the precincts thereof:- (i) wherein ten or more workers are working or were working on any day of the preceding twelve months, and in any part of which a manufacturing process is being carried on with the aid of power or is ordinarily so carried on, or (ii) wherein twenty or more workers are working or were working on any day of the preceding twelve months, and in any part of which a manufacturing process is being carried on without the aid of power. In addition to section 2(m)(i) & 2(m)(ii) of the Factories Act, 1948, electricity units registered with the Central Electricity Authority and Bidi & Cigar units, registered under the Bidi & Cigar Workers (Conditions of Employment) Act,1966 are also covered in ASI.

Analysis unit

The primary unit of enumeration in the survey is a factory in the case of manufacturing industries, a workshop in the case of repair services, an undertaking or a licensee in the case of electricity, gas & water supply undertakings and an establishment in the case of bidi & cigar industries. The owner of two or more establishments located in the same State and pertaining to the same industry group and belonging to same scheme (census or sample) is, however, permitted to furnish a single consolidated return. Such consolidated returns are common feature in the case of bidi and cigar establishments, electricity and certain public sector undertakings.

Universe

The survey cover factories registered under the Factory Act 1948. Establishments under the control of the Defence Ministry,oil storage and distribution units, restaurants and cafes and technical training institutions not producing anything for sale or exchange were kept outside the coverage of the ASI.

Kind of data

Census and Sample survey data [cen/ssd]

Sampling procedure

Sampling Procedure

The sampling design followed in ASI 1988-89 is a circular systematic one. All the factories in the updated frame (universe) are divided into two sectors, viz., Census and Sample.

Census Sector: Census Sector is defined as follows:

a) All industrial units belonging to the 12 less industrially developed states/ UT's viz. Goa, Himachal Pradesh, J & K, Manipur, Meghalaya, Nagaland, Tripura, Andaman & Nicobar Islands, Chandigarh, Dadra & Nagar Haveli, Daman & diu and Pondicherry were completely enumerated.
b) For the rest of the states/ UT's., (i) units having 100 or more workers irrespective of their operation with or without power and all electricity undertakings and (ii) all factories covered under Joint Returns. c) After excluding the Census Sector units as defined above, all units belonging to the strata (State by 4-digit of NIC-04) having less than or equal to 4 units are also considered as Census Sector units.

Remaining units, excluding those of Census Sector, called the sample sector, are covered on sampling basis through an efficient sampling design adopting State X 3 digit industry group as stratum so as to cover all the units in a span of three years. In any stratum, if the number of units was less than 20 , then the entire stratum was enumerated completely along with census factories. In any stratum if the units is between 21 and 60, a minimum sample of size 20 was selected by Circular Systematic Sampling. For all other units a uniform sampling fraction of 1/3 was adopted.

Sampling deviation

There was no deviation from sample design in ASI 1989-90

Mode of data collection

Statutory return submitted by factories as well as Face to face

Research instrument

Annual Survey of Industries 1988-89 Questionnaire is divided into different blocks : (However only Summarised data is available for processing and analysis). The Summary Results are based on the information provided in the Summary block pf ASI survey schedule. Therefore, there is only on data file in ASI Summary 1988-89. Record Layout of the merged file is provided.

Cleaning operations

Pre-data entry scrutiny was carried out on the schedules for inter and intra block consistency checks. Such editing was mostly manual, although some editing was automatic. But, for major inconsistencies, the schedules were referred back to NSSO (FOD) for clarifications/modifications.

Code list, State code list, NIC 70, NIC 87, Concordance Table and ASICC code may be refered in the External Resources which are used for editing and data processing as well..

Sampling error estimates

Relative Standard Error (RSE) is calculated in terms of worker, wages to worker and GVA using the formula. Programs developed in Visual Foxpro are used to compute the RSE of estimates.

Data appraisal

To check for consistency and reliability of data the same are compared with the NIC-2digit level growth rate at all India Index of Production (IIP) and the growth rates obtained from the National Accounts Statistics at current and constant prices for the registered manufacturing sector.

Abstract

The NSS 65th round (July 2008-June 2009) was comprehensively dedicated to the all India survey on housing condition. In this round, a nation-wide survey enquiry was organised to provide estimates on various characteristics of housing amenities, housing condition, cost of construction, etc.

Information on housing condition collected through schedule 1.2 canvassed in the NSS 65th Round is broadly categorised into three groups.

Firstly, information on the particulars of various facilities available to the sample households for decent living such as drinking water, latrine, bathroom, electricity etc. which were collected from all the selected households.

Secondly, information was collected on some of the characteristics of the houses, particulars of the dwelling unit and the micro environment surrounding the dwelling unit from the households who were living in houses. These broadly relate to different aspects of the structure of the houses, number of rooms, floor area, rent of the hired dwellings, use of the house, age of the structure, condition of the structure, drainage arrangement, garbage collection arrangement, etc.

Finally, information regarding number of constructions undertaken, number of constructions completed, type of constructions, cost of constructions, sources of finance, etc. was collected from the households who undertook constructions during the last 365 days, Besides, information was collected on first hand purchase of constructed house/flat by the households during the last 365 days such as number of such purchases, their area and cost.

Geographic coverage

The survey covered the whole of the Indian Union except (i) interior villages of Nagaland situated beyond five kilometres of the bus route and (ii) villages in Andaman and Nicobar Islands which remained inaccessible throughout the year.

Analysis unit

Randomly selected households based on sampling procedure.

Universe

The survey used the interview method of data collection from a sample of randomly selected households and members of the household

Kind of data

Sample survey data [ssd]

Sampling procedure

A stratified multi-stage design was adopted for the 65th round survey. The first stage units (FSU) were the 2001 census villages (Panchayat wards in case of Kerala) in the rural sector and Urban Frame Survey (UFS) blocks in the urban sector. For towns where no UFS frame was available (applicable to Leh and Kargil towns of J & K), each town was treated as an FSU. The ultimate stage units (USU) were households in both the sectors. In case of large FSUs, one intermediate stage of sampling was the selection of two hamlet-groups (hgs)/ sub-blocks (sbs) from each FSU. Details of the sample design and estimation procedure may be found attached as a document in the external resources.

Sampling deviation

There was no deviation from the original sample deviation.

Mode of data collection

Face-to-face [f2f]

Research instrument

Schedule 1.2 consists of 11 blocks including block 0. The blocks are:

Block 0: descriptive identification of sample household  
Block 1: identification of sample household
Block 2: particulars of field operation
      Block 3: household characteristics
Block 4: particulars of living facilities
Block 5: housing characteristics and micro environment  
Block 6: particulars of the dwelling
Block 7: particulars of construction and repair for residential purpose
Block 10: remarks by investigator
      Block 11: comments by supervisory officer(s)

Cleaning operations

In external resources find attached as a document

Response rate

At the all-India level, 12,952 FSUs (8188 villages and 4764 urban blocks) was allocated for survey for the ‘central sample’. Out of these 12,952 FSUs allotted for survey, 12,865 FSUs could be surveyed - 8,130 in rural and 4,735 in urban. In the central sample, 1,53,518 households were actually surveyed – 97,144 in rural areas and 56,374 in urban areas.

In NSS 65th round, a sample of 13,996 FSUs (8,552 villages and 5,444 urban blocks) was also selected for survey by the state agencies (State sample) at the all-India level.