The 1996 US presidential election saw incumbent President Bill Clinton of the Democratic Party take on Bob Dole of the Republican Party, and Ross Perot of the Reform Party. Clinton and Vice President Al Gore were re-nominated with no significant opposition, however the Republican primaries were much more crowded. Bob Dole was the early favorite for the Party's nomination, however the early primaries saw a strong performance by political commentator Pat Buchanan, throwing Dole's lead into doubt. The Republican leadership then rallied around Dole and campaigned heavily on his behalf, eventually securing the nomination for their preferred candidate, also defeating Steve Forbes, Editor-in-Chief of Forbes Magazine, along the way. Following his strong performance as an independent candidate in the 1992 election, Ross Perot founded the Reform Party and was subsequently nominated as their first presidential candidate. Campaign As the Democratic nomination was practically uncontested, Clinton was able to begin his political attacks against Dole quite early, while Dole was still trying to seal the Republican nomination and not in a position to respond. While both candidates attacked one another's age (Clinton was 50, while Dole was 73), Dole's attacks were direct and he frequently pointed to Clinton dodging the Vietnam War draft while highlighting his distinguished service in the Second World War, while Clinton's attacks were more subtle and targeted his "old-fashioned ideas" and "out of touch" policies. The Clinton campaign also faced controversy regarding their finances, and donations received from foreign and religious organizations; while 17 people were eventually convicted for fraud, this did little to derail Clinton's momentum. Results Clinton won re-election comfortably, after maintaining a healthy lead in the polls throughout the campaign. Although Clinton took just under fifty percent of the popular vote, Dole took just 41 percent, which gave Clinton more than seventy percent of the electoral vote. Ross Perot took more than eight percent of the popular vote, but none of the electoral vote. This election was the first time an incumbent Democratic President won re-election since Roosevelt's victory in 1944, while voter turnout was at it's lowest ever for a presidential election since 1924. Two years into his second term, Clinton became the second President of the United States to be impeached by the House of Representatives, under charges of lying under oath and obstruction of justice, although he was then acquitted by the senate.

Abstract

The Armenian Household Budget Survey (HBS) 1996 was designed to be a nationally representative survey capable of measuring the standard of living in the Republic of Armenia (ROA) through the collection of data on the family, demographic, socio-economic and financial status of households. The survey was conducted in November - December 1996, on the whole territory of the republic by the State Department of Statistics (SDS) of ROA with technical and financial assistance from the World Bank.

The data collected included information on household composition, housing conditions, education level of household members, employment and income, savings, borrowing, as well as details on levels of expenditure including those on food, non-food, health, tourism and business. The survey covered about 100 villages and 28 towns. The size of the sample was 5,040 households of which 4,920 responded which makes the survey the largest carried out in Armenia to date and one with a very high response rate for a transition economy. The expenditure part of the data was collected using two different methods administered for different households. The methods are: recall method in which households were asked, during the interview, about their expenditures made during the last 30 days preceding the date of the interview; and a diary method where households were given a diary they used to record details about their income and expenditure on a daily basis for 30 days during the interview period. About 25% of the total sample of interviewed households used diaries and 75% used the recall method. The unit of study in the survey was the household, defined as a group of co-resident individuals with a common living budget. As will be explained in detail, the AHBS 96 was generally designed as a two stage stratified sampling, but for large urban areas with an almost definite probability of being selected, a one stage sampling was adopted.

The Armenian HBS 1996 is not a standard Living Standards Measurement Study (LSMS) survey - the questionnaire used is more limited in scope and much different in format from a typical LSMS. This survey used no community or price questionnaires; it did not use most of LSMS’ prototypical fieldwork and data quality procedures, and the technical assistance did not come from the LSMS group in the World Bank. Nonetheless, the goals are some what LSMS-like and the data is certainly worth archiving. They are therefore being entered into the LSMS archives to guarantee their future accessibility to World Bank and other users.

Geographic coverage

National

Analysis unit

• Households
• Individuals

Kind of data

Sample survey data [ssd]

Sampling procedure

The State Department of Statistics specified 3 domains of interest for this study. These are Yerevan (the capital of ROA), Other Urban areas and Rural areas. Recent estimates of earthquake zones assigned almost equal populations to these domain zones of interest, and as a result there was no need for special targeting and no particular reason was implied for departing from a proportionate (or self-weighting) design.

A self-weighting sample was derived by selecting Primary Sampling Units (PSUs) with probability proportional to their size (where size is defined as the number of households) and then taking a constant number of households from each selected. The sample, therefore, was designed to be self-weighted and representative at the administrative regions (Marzes) level, for urban and rural areas, and within urban areas by the size of cities, and in rural areas by elevation. The number of households to be selected in each PSU was 20, so 250 PSUs were required to make up 5000 households.

Note: See detailed sample design and sample implementation information in the technical document, which is provided in this documentation.

Mode of data collection

Face-to-face [f2f]

Research instrument

The Armenia HBS 96 questionnaire was designed to collect information on several aspects of household behavior -- demographic composition, housing, health, consumption expenditures as well as income by source and employment. Information was collected about all the household members, not just about the head of the household alone.

Household Questionnaire

The main household questionnaire used in Armenia HBS 96 contained 13 sections, each of which covered a separate aspect of household activity. The various sections of the household questionnaire are described below followed by a brief description of the diary used to record the daily income and expenditure activities of participating households. All households completed sections A through J, L, and M. Households selected to receive the recall method for expenditures completed section K as well; the remainder filled out the diary instead of being interviewed for section K.

A . FAMILY CHARACTERISTICS AND HOUSING: This section collected basic demographic data such as name, age, sex, education, health, marital status and economic status of everyone living in the household, number of people in the household, etc. In addition, information collected included data on the type of educational institutions attended (private/public), special groups (disabled, single parents, orphan...), dwelling amenities and conditions of the household such as type of dwelling (apartment, house, hostel...) and available facilities (electricity, hot water, telephone...)

B. INCOME FROM EMPLOYMENT: This section collected information on income from employment, type of industry each household member is engaged in, type of ownership of the organization where each person works, salary and other cash payments received, employment subsidies in terms of services (e.g. transport and health ). The recall period covers the 30 days prior to the interview date.

C. INCOME FROM SELF EMPLOYMENT: This section collected information about self-employed persons, their income from selfemployment, costs of equipment and raw materials owned by their business, sector in which the individual is self-employed, etc. The recall period covers 30 days prior to the interview.

D. STATE BENEFITS: This section included information on entitlements and receipt of state benefits such as pension, disability, child benefit, unemployment benefit, single-mother benefit, etc. during the last 30 days preceding the date of the interview.

E. OTHER CASH INCOMES: Included in this section are approximate values of the various types of cash incomes such as those from sale of property, valuables, alimony, rent from properties, dividends and interest, help from relatives, etc. the household received during the last 30 days preceding the date of the interview.

F. AID (ASSISTANCE): This section included information on whether food and non-food (e.g. medical help) assistance were received by the household in forms other than cash from friends, relatives, humanitarian organizations, etc. and the values of such assistance received during the last 30 days preceding the date of the interview.

G. SAVINGS, ASSETS AND LOANS: This section collected information on savings, assets and loans made by the household to others, amount of borrowing from others, and the associated interest rates during the past 30 days.

H. GENERAL ECONOMIC SITUATION: This section collected information about the current economic situation as perceived by the household, how it changed over the past 90 days and the household’s future expectations over the next 90 days.

I. LAND OWNERSHIP AND AGRICULTURAL PRODUCE: This section collected information on the amount of land owned by the household in hectares, each crop type harvested and consumed, crop in storage for own household use, home produced food such as diary products, milk, eggs, etc. and animal stock. The recall period for this section generally is the current year, but for the value of household consumption, and crops sold in the market, it uses a recall period of the past 30 days.

J. FOOD IN STOCK (RESERVES): This section collected data on the amount of food in stock the household currently has such as bread, meat, cereals vegetables, etc.

K. EXPENDITURE FOR 30 DAYS (RECALL METHOD): This section collected expenditure information for the last 30 days on food purchases by item; clothing and foot wear for adults; children’s clothes; fabrics; household furniture, cars, carpets, and electrical appliances; household consumables such as soap and stationary; building materials, bathroom appliances and household tools; household utensils; household services; utilities; leisure activities; health; transport; education; domestic animals; land; tourism; and business activities.

L. EMIGRATION: This section collected information on whether anybody in the household worked outside Armenia for more than three months over the past five years; if the emigrating household member is still abroad and his/her final destination country.

M. "PAROS" social program:2 This section collected information on whether the household is in the PAROS program and points the family has in the PAROS system in their social passport.

Z. GUESTS AND EATING OUT This section collected information on how many people ate in the household during the 30 days prior to the interview, how many times the household invited guests for dinner; and was invited; amount of food given to friends and relatives by the household. The codes for these variables are available in the data dictionary.

Diary Questionnaire

The diary questionnaire was used to collect daily income and expenditure activities of the participating households for 30 consecutive days during the interview period. It was administered to 25% of the households in the sample who also completed sections A through J, L and M from the

Abstract copyright UK Data Service and data collection copyright owner.The Opinions and Lifestyle Survey (formerly known as the ONS Opinions Survey or Omnibus) is an omnibus survey that began in 1990, collecting data on a range of subjects commissioned by both the ONS internally and external clients (limited to other government departments, charities, non-profit organisations and academia).Data are collected from one individual aged 16 or over, selected from each sampled private household. Personal data include data on the individual, their family, address, household, income and education, plus responses and opinions on a variety of subjects within commissioned modules. The questionnaire collects timely data for research and policy analysis evaluation on the social impacts of recent topics of national importance, such as the coronavirus (COVID-19) pandemic and the cost of living, on individuals and households in Great Britain. From April 2018 to November 2019, the design of the OPN changed from face-to-face to a mixed-mode design (online first with telephone interviewing where necessary). Mixed-mode collection allows respondents to complete the survey more flexibly and provides a more cost-effective service for customers. In March 2020, the OPN was adapted to become a weekly survey used to collect data on the social impacts of the coronavirus (COVID-19) pandemic on the lives of people of Great Britain. These data are held in the Secure Access study, SN 8635, ONS Opinions and Lifestyle Survey, Covid-19 Module, 2020-2022: Secure Access. From August 2021, as coronavirus (COVID-19) restrictions were lifting across Great Britain, the OPN moved to fortnightly data collection, sampling around 5,000 households in each survey wave to ensure the survey remains sustainable. The OPN has since expanded to include questions on other topics of national importance, such as health and the cost of living. For more information about the survey and its methodology, see the ONS OPN Quality and Methodology Information webpage.Secure Access Opinions and Lifestyle Survey dataOther Secure Access OPN data cover modules run at various points from 1997-2019, on Census religion (SN 8078), cervical cancer screening (SN 8080), contact after separation (SN 8089), contraception (SN 8095), disability (SNs 8680 and 8096), general lifestyle (SN 8092), illness and activity (SN 8094), and non-resident parental contact (SN 8093). See Opinions and Lifestyle Survey: Secure Access for details. Main Topics:Each month's questionnaire consists of two elements: core questions, covering demographic information, are asked each month together with non-core questions that vary from month to month. The non-core questions for this month were: Condom Use (Module 6): this module is concerned with condoms, including female condoms, their use and reasons for non-use. Investment Income (Module 7a): this module was asked to discover how much interest, tax exempt or tax deducted, respondents earn on money kept in building society and bank accounts. National Health Service Opinions (Module 31): this module asks about respondent's state of health, recent use of health services, and their opinions about the NHS generally and on specific aspects. GP Accidents (Module 78n): this module asked about accidents the respondent had had where help was sought that could have involved a doctor e.g. doctor's surgery, hospital. Work Related Accidents (Module 128): this module is asked of respondents who had done any paid work in the last 12 months and collects details about accidents that have occurred to the respondent while at work. Smoking (Module 130): this module assesses people's smoking habits, past and present, attitudes to smoking in different scenarios, and awareness of cigarette advertising. Expectation of House Price Changes (Module 137): this module asks respondents' views on changes to house prices in the next year and next five years. Delay in Moving (Module 152): this module is asked only of those respondents who currently own their home outright or are buying it with the help of a mortgage. It aims to assess the frequency with which a delay of at least a month occurs between completion and the householders moving into the new property. Food Safety (Module 159): this module is concerned with food safety in relation to food preparation in the home and food poisoning. It aims to assess awareness of safe preparation of food and actual habits and also whether or not behaviour has changed in light of recent food safety information and food poisoning scares. Multi-stage stratified random sample Face-to-face interview 1996 ACCIDENTS ADVERTISING ADVICE AGE AIDS DISEASE ASTHMA ATTITUDES BANK ACCOUNTS BRONCHITIS BUILDING SOCIETY AC... CAUSES OF DEATH CHILDREN CHRONIC ILLNESS CLEANING CONDOM USE COOKING COT DEATHS CULTURAL FINANCE DECISION MAKING DIABETES DISEASES DOMESTIC APPLIANCES DOMESTIC RESPONSIBI... ECONOMIC ACTIVITY EDUCATIONAL BACKGROUND EMPLOYEES EMPLOYMENT EMPLOYMENT HISTORY EMPLOYMENT PROGRAMMES ETHNIC GROUPS EXPECTATION Economic conditions... FAMILY MEMBERS FOOD FOOD CONTAMINATION FOOD HAZARDS FOOD POISONING FOOD PREPARATION FOOD SAFETY FOOD STORAGE FULL TIME EMPLOYMENT GENDER GENERAL PRACTITIONERS HEADS OF HOUSEHOLD HEALTH HEALTH ADVICE HEALTH CONSULTATIONS HEALTH PROFESSIONALS HEALTH SERVICES HEART DISEASES HOME BUYING HOME OWNERSHIP HOSPITAL OUTPATIENT... HOSPITAL SERVICES HOUSEHOLD PETS HOUSEHOLDS HOUSES HOUSING TENURE Health behaviour History Housing INCOME INDUSTRIAL INJURIES INDUSTRIES INFLATION INFORMATION INFORMATION SOURCES INJURIES INTEREST FINANCE Income JOB HUNTING LUNG CANCER Labour and employment MANAGERS MARITAL STATUS MEALS MEAT MEDICAL CARE MORTGAGES MOTOR VEHICLES NEWS ITEMS OCCUPATIONAL SAFETY OCCUPATIONS ONE PARENT FAMILIES PAMPHLETS PART TIME EMPLOYMENT PASSIVE SMOKING PATIENTS PHARMACISTS PRESS ADVERTISING PRICES PUBLIC INFORMATION PURCHASING RADIO ADVERTISING RADIO PROGRAMMES RENTED ACCOMMODATION RESIDENTIAL MOBILITY RESPIRATORY TRACT D... RESTAURANTS RETIREMENT RISK ROAD ACCIDENTS SATISFACTION SAVINGS SELF EMPLOYED SENSORY IMPAIRMENTS SEXUAL BEHAVIOUR SHARED HOME OWNERSHIP SHOPPING SICK LEAVE SMOKING SMOKING CESSATION SMOKING RESTRICTIONS SOCIAL HOUSING STUDENTS SUPERVISORS SYMPTOMS Social behaviour an... TAKE AWAY MEALS TAXATION TELEVISION ADVERTISING TELEVISION PROGRAMMES TOBACCO UNEMPLOYED Wounds and injuries property and invest...

This study was undertaken to obtain information on the characteristics of gun ownership, gun-carrying practices, and weapons-related incidents in the United States -- specifically, gun use and other weapons used in self-defense against humans and animals. Data were gathered using a national random-digit-dial telephone survey. The respondents were comprised of 1,905 randomly-selected adults aged 18 and older living in the 50 United States. All interviews were completed between May 28 and July 2, 1996. The sample was designed to be a representative sample of households, not of individuals, so researchers did not interview more than one adult from each household. To start the interview, six qualifying questions were asked, dealing with (1) gun ownership, (2) gun-carrying practices, (3) gun display against the respondent, (4) gun use in self-defense against animals, (5) gun use in self-defense against people, and (6) other weapons used in self-defense. A "yes" response to a qualifying question led to a series of additional questions on the same topic as the qualifying question. Part 1, Survey Data, contains the coded data obtained during the interviews, and Part 2, Open-Ended-Verbatim Responses, consists of the answers to open-ended questions provided by the respondents. Information collected for Part 1 covers how many firearms were owned by household members, types of firearms owned (handguns, revolvers, pistols, fully automatic weapons, and assault weapons), whether the respondent personally owned a gun, reasons for owning a gun, type of gun carried, whether the gun was ever kept loaded, kept concealed, used for personal protection, or used for work, and whether the respondent had a permit to carry the gun. Additional questions focused on incidents in which a gun was displayed in a hostile manner against the respondent, including the number of times such an incident took place, the location of the event in which the gun was displayed against the respondent, whether the police were contacted, whether the individual displaying the gun was known to the respondent, whether the incident was a burglary, robbery, or other planned assault, and the number of shots fired during the incident. Variables concerning gun use by the respondent in self-defense against an animal include the number of times the respondent used a gun in this manner and whether the respondent was hunting at the time of the incident. Other variables in Part 1 deal with gun use in self-defense against people, such as the location of the event, if the other individual knew the respondent had a gun, the type of gun used, any injuries to the respondent or to the individual that required medical attention or hospitalization, whether the incident was reported to the police, whether there were any arrests, whether other weapons were used in self-defense, the type of other weapon used, location of the incident in which the other weapon was used, and whether the respondent was working as a police officer or security guard or was in the military at the time of the event. Demographic variables in Part 1 include the gender, race, age, household income, and type of community (city, suburb, or rural) in which the respondent lived. Open-ended questions asked during the interview comprise the variables in Part 2. Responses include descriptions of where the respondent was when he or she displayed a gun (in self-defense or otherwise), specific reasons why the respondent displayed a gun, how the other individual reacted when the respondent displayed the gun, how the individual knew the respondent had a gun, whether the police were contacted for specific self-defense events, and if not, why not.

Abstract

The Human Sciences Research Council (HSRC) carried out the Migration and Remittances Survey in South Africa for the World Bank in collaboration with the African Development Bank. The primary mandate of the HSRC in this project was to come up with a migration database that includes both immigrants and emigrants. The specific activities included: · A household survey with a view of producing a detailed demographic/economic database of immigrants, emigrants and non migrants · The collation and preparation of a data set based on the survey · The production of basic primary statistics for the analysis of migration and remittance behaviour in South Africa.

Like many other African countries, South Africa lacks reliable census or other data on migrants (immigrants and emigrants), and on flows of resources that accompanies movement of people. This is so because a large proportion of African immigrants are in the country undocumented. A special effort was therefore made to design a household survey that would cover sufficient numbers and proportions of immigrants, and still conform to the principles of probability sampling. The approach that was followed gives a representative picture of migration in 2 provinces, Limpopo and Gauteng, which should be reflective of migration behaviour and its impacts in South Africa.

Geographic coverage

Two provinces: Gauteng and Limpopo

Limpopo is the main corridor for migration from African countries to the north of South Africa while Gauteng is the main port of entry as it has the largest airport in Africa. Gauteng is a destination for internal and international migrants because it has three large metropolitan cities with a great economic potential and reputation for offering employment, accommodations and access to many different opportunities within a distance of 56 km. These two provinces therefore were expected to accommodate most African migrants in South Africa, co-existing with a large host population.

Analysis unit

• Household
• Individual

Universe

The target group consists of households in all communities. The survey will be conducted among metro and non-metro households. Non-metro households include those in: - small towns, - secondary cities, - peri-urban settlements and - deep rural areas. From each selected household, one adult respondent will be selected to participate in the study.

Kind of data

Sample survey data [ssd]

Sampling procedure

Migration data for South Africa are available for 2007 only at the level of local governments or municipalities from the 2007 Census; for smaller areas called "sub places" (SPs) only as recently as the 2001 census, and for the desired EAs only back so far as the Census of 1996. In sum, there was no single source that provided recent data on the five types of migrants of principal interest at the level of the Enumeration Area, which was the area for which data were needed to draw the sample since it was going to be necessary to identify migrant and non-migrant households in the sample areas in order to oversample those with migrants for interview.

In an attempt to overcome the data limitations referred to above, it was necessary to adopt a novel approach to the design of the sample for the World Bank's household migration survey in South Africa, to identify EAs with a high probability of finding immigrants and those with a low probability. This required the combined use of the three sources of data described above. The starting point was the CS 2007 survey, which provided data on migration at a local government level, classifying each local government cluster in terms of migration level, taking into account the types of migrants identified. The researchers then spatially zoomed in from these clusters to the so-called sub-places (SPs) from the 2001 Census to classifying SP clusters by migration level. Finally, the 1996 Census data were used to zoom in even further down to the EA level, using the 1996 census data on migration levels of various typed, to identify the final level of clusters for the survey, namely the spatially small EAs (each typically containing about 200 households, and hence amenable to the listing operation in the field).

A higher score or weight was attached to the 2007 Community Survey municipality-level (MN) data than to the Census 2001 sub-place (SP) data, which in turn was given a greater weight than the 1996 enumerator area (EA) data. The latter was derived exclusively from the Census 1996 EA data, but has then been reallocated to the 2001 EAs proportional to geographical size. Although these weights are purely arbitrary since it was composed from different sources, they give an indication of the relevant importance attached to the different migrant categories. These weighted migrant proportions (secondary strata), therefore constituted the second level of clusters for sampling purposes.

In addition, a system of weighting or scoring the different persons by migrant type was applied to ensure that the likelihood of finding migrants would be optimised. As part of this procedure, recent migrants (who had migrated in the preceding five years) received a higher score than lifetime migrants (who had not migrated during the preceding five years). Similarly, a higher score was attached to international immigrants (both recent and lifetime, who had come to SA from abroad) than to internal migrants (who had only moved within SA's borders). A greater weight also applied to inter-provincial (internal) than to intra-provincial migrants (who only moved within the same South African province).

How the three data sources were combined to provide overall scores for EA can be briefly described. First, in each of the two provinces, all local government units were given migration scores according to the numbers or relative proportions of the population classified in the various categories of migrants (with non-migrants given a score of 1.0. Migrants were assigned higher scores according to their priority, with international migrants given higher scores than internal migrants and recent migrants higher scores than lifetime migrants. Then within the local governments, sub-places were assigned scores assigned on the basis of inter vs. intra-provincial migrants using the 2001 census data. Each SP area in a local government was thus assigned a value which was the product of its local government score (the same for all SPs in the local government) and its own SP score. The third and final stage was to develop relative migration scores for all the EAs from the 1996 census by similarly weighting the proportions of migrants (and non-migrants, assigned always 1.0) of each type. The the final migration score for an EA is the product of its own EA score from 1996, the SP score of which it is a part (assigned to all the EAs within the SP), and the local government score from the 2007 survey.

Based on all the above principles the set of weights or scores was developed.

In sum, we multiplied the proportion of populations of each migrant type, or their incidence, by the appropriate final corresponding EA scores for persons of each type in the EA (based on multiplying the three weights together), to obtain the overall score for each EA. This takes into account the distribution of persons in the EA according to migration status in 1996, the SP score of the EA in 2001, and the local government score (in which the EA is located) from 2007. Finally, all EAs in each province were then classified into quartiles, prior to sampling from the quartiles.

From the EAs so classified, the sampling took the form of selecting EAs, i.e., primary sampling units (PSUs, which in this case are also Ultimate Sampling Units, since this is a single stage sample), according to their classification into quartiles. The proportions selected from each quartile are based on the range of EA-level scores which are assumed to reflect weighted probabilities of finding desired migrants in each EA. To enhance the likelihood of finding migrants, much higher proportions of EAs were selected into the sample from the quartiles with the higher scores compared to the lower scores (disproportionate sampling). The decision on the most appropriate categorisations was informed by the observed migration levels in the two provinces of the study area during 2007, 2001 and 1996, analysed at the lowest spatial level for which migration data was available in each case.

Because of the differences in their characteristics it was decided that the provinces of Gauteng and Limpopo should each be regarded as an explicit stratum for sampling purposes. These two provinces therefore represented the primary explicit strata. It was decided to select an equal number of EAs from these two primary strata.

The migration-level categories referred to above were treated as secondary explicit strata to ensure optimal coverage of each in the sample. The distribution of migration levels was then used to draw EAs in such a way that greater preference could be given to areas with higher proportions of migrants in general, but especially immigrants (note the relative scores assigned to each type of person above). The proportion of EAs selected into the sample from the quartiles draws upon the relative mean weighted migrant scores (referred to as proportions) found below the table, but this is a coincidence and not necessary, as any disproportionate sampling of EAs from the quartiles could be done, since it would be rectified in the weighting at the end for the analysis.

The resultant proportions of migrants then led to the following proportional allocation of sampled EAs (Quartile 1: 5 per cent (instead of 25% as in an equal distribution), Quartile 2: 15 per cent (instead

The segment of the population between 35 and 64 years of age are considered the population in the latter half of their working life. They have, for the most part, finished having children, are in the upper end of their earning potential, children are leaving the nest, mortgages are paid and assets are increasing. This map exhibits a few interesting patterns when compared with other maps in the age structure. Compared to the early working years group, the later working years segment is less concentrated in the inner parts of the city. Higher proportions are evident on the census subdivision layer in areas outside of cities reflecting past suburban migration patterns. In the north the area outside the populated places is dominated by a high proportion of people in their later working years. Note that very small populations exist in many large census divisions and subdivisions in the North.

Kevään 1996 nuorisobarometrin pääteemoja olivat työttömyys ja työllistyminen. Nuorille esitettiin kysymyksiä myös liittyen tiedonvälitykseen, tuloihin ja mielipidevaikuttamiseen. Ensin esitettiin taustakysymyksiä vastaajan koulutuksesta ja pääasiallisesta toiminnasta. Töissäkäyviltä kysyttiin lisää työsuhteen laadusta ja kestosta. Työttömiltä ja lomautetuilta puolestaan tiedusteltiin kauanko nämä ovat olleet työttöminä ja millaisten tekijöiden he uskovat estävän omaa työllistymistään ja nuorten työllistymistä yleensä. Kysyttiin myös, olisivatko työttömät vastaajat valmiita lähtemään oppisopimuskoulutukseen työttömyyden vaihtoehtona, ja ovatko nämä kuulleet työttömille nuorille tarkoitetuista kunnallisista työpajoista tai osallistuneet niiden toimintaan. Vastaajilta haluttiin myös mielipiteitä työpajojen kehittämisestä. Nuorille esitettiin myös erilaisia väittämiä työelämästä, ja kysyttiin ovatko nämä väittämistä samaa vai eri mieltä. Väittämiä olivat muun muassa "koulutus parantaa olennaisesti työnsaantia", "työllisyystilanne paranee selvästi lähimmän viiden vuoden aikana" ja "työurallani tulen saavuttamaan paremman yhteiskunnallisen aseman kuin mitä vanhemmillani on". Kartoitettiin myös vastaajien tulevaisuudensuunnitelmia kysymällä, aikovatko nämä lähimmän viiden vuoden aikana hakeutua ulkomaille töihin tai opiskelemaan, perustaa oman yrityksen tai mennä ammatilliseen koulutukseen. Nuorilta kysyttiin myös mikä heidän mielestään on suurin este työttömien yrittäjäksi ryhtymiselle. Nuorisobarometrissa kartoitettiin myös tuloihin ja sosiaaliturvaan liittyviä asioita. Kysyttiin mikä on vastaajien tärkein käyttövarojen lähde, ja tiedusteltiin ovatko nämä saaneet viimeisen 12 kuukauden aikana erilaisia tukia (esim. opintoraha, toimeentulotuki, kotihoidontuki tai asumistuki). Kysyttiin myös kansalaispalkasta ja pyydettiin vastaajia arvioimaan, mikä heidän mielestään on vähimmäissumma, jolla tulee kuukauden toimeen. Lopuksi selvitettiin vastaajien mielipiteisiin vaikuttaneita tahoja ja tiedonvälityskanavien käyttöä. Kysyttiin miten paljon eri tahot (esim. vanhemmat, lehdistö, poliitikot tai opettajat) ovat vaikuttaneet vastaajien mielipiteisiin. Tiedusteltiin myös, mitä kautta vastaajat pääasiassa seuraavat Suomen ja maailman ajankohtaisia tapahtumia ja mistä lähteistä he kokevat saavansa luotettavimman kuvan maailmasta. Vastaajat saivat nimetä mielestään mielenkiintoisimman tiedonvälityksen kanavan ja kertoa, millaisia ohjelmia seuraavat televisiosta eniten. Lopuksi kysyttiin, mistä vastaajat pääasiassa kuuntelevat musiikkia (esim. Radio Mafia, äänitteet tai Music Television). Taustamuuttujia tutkimuksessa olivat muun muassa vastaajien ikä, sukupuoli, kunta ja pääasiallinen toiminta. The main themes of the 1996 youth survey were employment and unemployment in Finland. Other topics included education, working life, entrpreneurship, income sources, social security benefits, and mass media. The respondents were asked whether they were studying at that moment and whether they were satisfied with their education in terms of gaining employment. Those in employment were asked about their job contract and whether the job was commensurate with their qualifications. The unemployed or the laid-off were asked about the spells and duration of unemployment, willingness to enter apprenticeship training or participate in a youth workshop. Opinions on the most important obstacles to employment in their case and for young people in general were charted. The respondents were asked to what extent they agreed with a number of statements relating to employment opportunities, unemployment benefits, employment situation, means of increasing employment opportunities and racism. The statements included, for instance, whether education improved one's chances of getting a job, whether the respondents would rather take temporary work than remain unemployed if income were the same, whether they expected to gain better social status than their parents had, whether they would accept a person from a different ethnic background as their work colleague. Future plans were charted by asking whether the respondents planned to work or study abroad, set up a business or acquire vocational education within the next five years. Views were probed on obstacles preventing young people from becoming entrepreneurs/self-employed. Regarding income and social security benefits, the respondents were asked what was their most important source of income and whether they received certain income transfers during the past 12 months (social assistance, study grant, study loan, unemployment allowance or other unemployment benefits, maternal or paternal allowance, housing allowance or sickness allowance). Further themes covered interpersonal influence and mass media. The respondents were asked how much certain persons or bodies had affected the way they think (parents, relatives, teachers, the press, friends, television/radio, politicians, authorities, church or religion). Main information sources for current affairs (television, radio, the press, the Internet etc) were surveyed. Views were also probed on the reliability of information sources. Some questions covered what the respondents thought were the most interesting sources of communication, what kind of television programmes they watched and how they listened to the music (radio, Internet, music TV, albums/tracks). Background variables included the respondent's age, gender, basic education, vocational education, economic activity, municipality of residence, and parents' vocational education.

This dataset contains information on: · Estimated resident population (ERP) at 30 June 1996, 2001, 2006, 2013, and 2018 for total population · ERP at 30 June 2018 by ethnic groups (European or Other (including New Zealander), Māori, Pacific, Asian, and Middle Eastern/Latin American/African) – estimates and percentage · Sex ratio – number of males per 100 females · ERP at 30 June 2018 by broad age groups and median age · Geographies available are regional council areas, territorial authority and Auckland local board areas, Statistical Area 2, and urban rural. Note: The geography corresponds to 2020 boundaries Note: -999 indicates data are not available. ​ About the estimated resident population The estimated resident population at 30 June in the census year is based on the census usually resident population count, with updates for: · net census undercount (as measured by a post-enumeration survey) · residents temporarily overseas on census night · births, deaths and net migration between census night and 30 June · reconciliation with demographic estimates at the youngest ages. The estimated resident population is not directly comparable with the census usually resident population count because of these adjustments. For more detailed information about the methods used to calculate each base population, see DataInfo+ Demographic estimates. ​ Ethnic groups It is important to note that these ethnic groups are not mutually exclusive because people can and do identify with more than one ethnicity. People who identify with more than one ethnicity have been included in each ethnic group. The 'Māori', 'Pacific', 'Asian' and 'Middle Eastern/Latin American/African' ethnic groups are defined in level 1 of the Ethnicity New Zealand Standard Classification 2005. The estimates for the 'European or Other (including New Zealander)' group include people who belong to the 'European' or 'Other ethnicity' groups defined in level 1 of the standard classification. If a person belongs to both the 'European' and 'Other ethnicity' groups they have only been counted once. Almost all people in the 'Other ethnicity' group belong to the 'New Zealander' sub-group. ​ Time series This time series is irregular. Because the 2011 Census was cancelled after the Canterbury earthquake on 22 February 2011, the gap between the 2006-base and 2013-base estimated resident population is seven years. The change in data between 2006 and 2013 may be greater than in the usual five-year gap between censuses. Be careful when comparing trends. ​ Rounding Individual figures may not sum to stated totals due to rounding. ​ More information See Estimated resident population (2018-base): At 30 June 2018 for commentary about the 2018 ERP. Subnational population estimates concepts – DataInfo+ provides definitions of terms used in the map. Access more population estimates data in NZ.Stat: Theme: Population estimates.

Inflation Rate in Nigeria decreased to 23.18 percent in February from 24.48 percent in January of 2025. This dataset provides - Nigeria Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Abstract

The Survey of Activities of Young People was conducted by Statistics South Africa and commissioned by the Department of Labour, primarily to gather information necessary for formulating an effective programme of action to address the issue of harmful work done by children in South Africa. Technical assistance for the survey was provided by the International Labour Organisation (ILO) and a consultant appointed by the Department of Labour. Stats SA also worked with an advisory committee, consisting of representatives from national government departments most directly concerned with child labour (the Departments of Labour,Welfare,Education and Health), non-governmental organisations, and the United Nations Children's Fund (Unicef).

Geographic coverage

The survey has national coverage

Analysis unit

Households and individuals

Universe

The sampled population was household members in South Africa. The survey excluded all people in prison, patients in hospitals, people residing in boarding houses and hotels, and boarding schools. Any single person households were screened out in all areas before the sample was drawn. Families living in hostels were treated as households.

Kind of data

Sample survey data

Sampling procedure

The sample frame was based on the 1996 Population Census Enumerator Areas (EA) and the number of households counted in 1996 Population Census. The sampled population excluded all prisoners in prison, patients in hospitals, people residing in boarding houses and hotels (whether temporary or semi-permanent), and boarding schools. Any single person households were screened out in all areas before the sample was drawn. Families living in hostels were treated as households. Coverage rules for the survey were that all children of usual residents were to be included even if they were not present. This means that most boarding school pupils were included in their parents’ household. The 16 EA types from the 1996 Population Census were condensed into four area types. The four area types were Formal Urban, Informal Urban, Tribal, and Commercial Farms. A decision was made to drop the Institution type EAs.

The EAs were stratified by province, and within a province by the four area types defined above. The sample size (6110 households) was disproportionately allocated to strata by using the square root method. Within the strata the EAs were ordered by magisterial district and the EA-types included in the area type (implicit stratification). PSUs consisted of ONE or more EAs of size 100 households to ensure sufficient numbers for screening. Statistics SA was advised by child labour experts that there was a likelihood of high rates of child labour in the Urban Informal and Rural Farm areas. The sample allocation to Rural Commercial Farms was therefore increased to a minimum of 20 PSUs.

Mode of data collection

Face-to-face [f2f]

Research instrument

The Phase one questionnaire covered the following topics: Living conditions of the household, including the type of dwelling, fuels used for cooking, lighting and heating,water source for domestic use, land ownership,tenure and cultivation; demographic information on members of the household, both adults and children. Questions covered the age, gender and population group of each household member, their marital status, their relationships to each other, and their levels of education; migration details; household income; school attendance of children aged 5 -17 years; information on economic and non-economic activities of children aged 5-17 years in the 12 months prior to the survey

Phase two questionnaire The second phase questionnaire was administered to the sampled sub-set of households in which at least one child was involved in some form of work in the year prior to the interview. It covered activities of children in much more detail than in phase one, and the work situation of related adults in the household. Both adults and children were asked to respond.

The data files contain data from sections of the questionnaires as follows:

PERSON: Data from Section 1, 2 and 3 of the questionnaire HHOLD : Data from Section 4 ADULT : Data from Section 5 YOUNGP: Data from Section 6, 7, 8 and 9

Abstract

The Beijing Platform for Action which emerged from the 1995 Fourth United Nations World Conference on Women called for the development of 'suitable statistical means to recognise and make visible the full extent of the work of women and all their contributions to the national economy, including their contribution in the unremunerated and domestic sectors'. During 2000, Statistics South Africa (Stats SA) conducted the fieldwork for the first national time use study in the country. The aim of the survey was to provide information on the way in which different individuals in South Africa spend their time. Such information contributes to greater understanding of policymakers on the economic and social well-being of different societal groups. In particular, the study was intended to provide new information on the division of both paid and unpaid labour between women and men, and greater insight into less well understood productive activities such as subsistence work,casual work and work in the informal sector.

The survey thus had dual objectives: (1) improvement of concepts, methodology and measurement of all types of work and work-related activity, and (2) the feeding of information into better policy-making, with a particular focus on gender equity.

Geographic coverage

The survey had national coverage

Analysis unit

Units of analysis for the survey include households and individuals

Universe

The survey covered household members in South Africa, ten years old and above

Kind of data

Sample survey data [ssd]

Sampling procedure

The time use study sample frame was based on the frame prepared for the 1999 Survey of activities of young people (SAYP). This sample frame was based on the 1996 population census enumerator areas (EAs) and the number of households counted in the 1996 population census. The sampled population excluded all prisoners in prison, patients in hospital, people residing in boarding houses and hotels (whether temporary or semi-permanent), and boarding schools. The 16 EA types from the 1996 Population Census were condensed into four area types, or strata. The four strata were formal urban, informal urban, non-commercial farming rural, and commercial farming areas. Institution type EAs were excluded from the sample.

The EAs were explicitly stratified by province, and within a province by the four strata. The sample size (10 800 dwelling units, with 3 600 units in each of the three tranches) was disproportionately allocated to the explicit strata using the square root method. Within the strata, the EAs were ordered by magisterial district and the EA-types included in the area type (implicit stratification). Primary sampling units (PSUs) consisted of an EA of at least 100 dwelling units. Where an EA contained less than 100 dwelling units, EAs were pooled (using Kish's method of pooling) to meet this requirement. Most EAs had fewer than 100 dwelling units. The dwelling unit was taken as the ultimate sampling unit (USU).

Firstly, a two stage sampling procedure was applied. The allocated number of PSUs was systematically selected with probability proportional to size in each explicit stratum (with the measure of size being the number of dwelling units in a PSU). In each PSU, a systematic sample of 12 households was drawn.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire for the time use survey was comprised of three sections. Section one covered details of the household. Section two covered demographic details of the first person selected as a respondent in that household. Section three consisted of a Background and methodology diary in which to record the activities performed by the first person selected during the 24 hours between 4 am on the day preceding the interview and 4 am on the day of the interview. Sections four and five were for the second selected person in the household but were otherwise identical to sections two and three respectively.

The household and demographic sections of the questionnaire contained many of the standard questions of Stats SA household surveys. This was done so as to facilitate comparison across surveys. These sections also contained some additional questions on issues that would be likely to affect time use. For the household section, for example, there were questions on access to household aids such as washing machines and vacuum cleaners. In the demographic section there were questions about the presence of the respondent's young children in the household.

The diary, which forms the core instrument of a time use study, was divided into half-hour slots. Respondents were asked an open-ended question as to the activities performed during a given half-hour. These activities were then post-coded by the fieldworker according to the activity classification system (see below). The respondent could report up to three activities for each time slot. Where there was more than one activity reported for a half hour, the respondent was asked whether these activities were conducted simultaneously, or one after the other. For each recorded activity, the questionnaire also included two location codes. The first code provides for eight broadly defined locations plus the mobile activity of travel. Where the location of a particular activity could be classified as more than one of the given options, the option highest on the list took precedence. For example, a domestic worker was classified as working in someone else's dwelling rather than in a workplace. The second code distinguished between interior (inside) and exterior (outside) for the eight broadly-defined locations, and distinguished the mode of travel for all travel activity.

Cleaning operations

The data from the diary were captured in Sybase at Stats SA head office through a custom-designed data capture programme. The programme contained some in-built checks. Further checks were done manually prior to and after capture. The data were subsequently downloaded into SAS format, and the SAS programme was used for analysis.

Abstract copyright UK Data Service and data collection copyright owner.