Graph and download economic data for All Employees, Manufacturing (MANEMP) from Jan 1939 to Jun 2025 about headline figure, establishment survey, manufacturing, employment, and USA.

Graph and download economic data for All Employees, Retail Trade (USTRADE) from Jan 1939 to Jun 2025 about establishment survey, retail trade, sales, retail, employment, and USA.

Definition: The volume of work includes the hours worked (actual hours worked) of all workers. Hours worked are also those of persons with several simultaneous employment relationships. On the other hand, hours worked but not paid, such as annual leave, parental leave, public holidays, short-time work or sick leave, are not included in the volume of work. Also not included are the unpaid breaks for taking meals as well as the time for the trips from the apartment to the workplace and back. Neither the intensity nor the quality of the work done is taken into account. Employed persons include all persons who, as employees or self-employed persons or family workers, carry out an activity aimed at economic gain within an economic territory. Note: A general revision was carried out in 2014. The main purpose of this was to introduce the new European System of Accounts (ESA 2010) across Europe. For its part, ESA 2010 is based on the globally valid new System of National Accounts (SNA 2008) and replaced the previous ESA 1995. As a result of this revision, the base year for the calculations changed from 2005 to 2010. Data source: Working Group "National Accounts of the Länder"

Employment statistics on the Flat Glass Manufacturing industry in the UK

The 2018 edition of Woods and Poole Complete U.S. Database provides annual historical data from 1970 (some variables begin in 1990) and annual projections to 2050 of population by race, sex, and age, employment by industry, earnings of employees by industry, personal income by source, households by income bracket and retail sales by kind of business. The Complete U.S. Database contains annual data for all economic and demographic variables for all geographic areas in the Woods & Poole database (the U.S. total, and all regions, states, counties, and CBSAs). The Complete U.S. Database has following components: Demographic & Economic Desktop Data Files: There are 122 files covering demographic and economic data. The first 31 files (WP001.csv – WP031.csv) cover demographic data. The remaining files (WP032.csv – WP122.csv) cover economic data. Demographic DDFs: Provide population data for the U.S., regions, states, Combined Statistical Areas (CSAs), Metropolitan Statistical Areas (MSAs), Micropolitan Statistical Areas (MICROs), Metropolitan Divisions (MDIVs), and counties. Each variable is in a separate .csv file. Variables: Total Population Population Age (breakdown: 0-4, 5-9, 10-15 etc. all the way to 85 & over) Median Age of Population White Population Population Native American Population Asian & Pacific Islander Population Hispanic Population, any Race Total Population Age (breakdown: 0-17, 15-17, 18-24, 65 & over) Male Population Female Population Economic DDFs: The other files (WP032.csv – WP122.csv) provide employment and income data on: Total Employment (by industry) Total Earnings of Employees (by industry) Total Personal Income (by source) Household income (by brackets) Total Retail & Food Services Sales ( by industry) Net Earnings Gross Regional Product Retail Sales per Household Economic & Demographic Flat File: A single file for total number of people by single year of age (from 0 to 85 and over), race, and gender. It covers all U.S., regions, states, CSAs, MSAs and counties. Years of coverage: 1990 - 2050 Single Year of Age by Race and Gender: Separate files for number of people by single year of age (from 0 years to 85 years and over), race (White, Black, Native American, Asian American & Pacific Islander and Hispanic) and gender. Years of coverage: 1990 through 2050. DATA AVAILABLE FOR 1970-2019; FORECASTS THROUGH 2050

The following are a selection of annual outcomes of services provided by the Pennsylvania's Department of Labor & Industry's Office of Vocational Rehabilitation. Outcomes include applicants and case outcomes including employment and wages.

Key Footnotes: 1) Employed in Competitive Labor Market means employment at or above the minimum wage in settings where most employees do not have disabilities. 2) Estimated Taxes Paid are based on a standard deduction for the year, annual tax brackets and rates established by the IRS, and flat-rate FICA, state, and local taxes. 3) Estimated Total Government Savings are estimated federal, state, and local taxes paid plus annualized public support dollars at closure. 4) Average per Person Cost for a Competitive Employment Placement is the average individual "life of case" cost for all persons having a competitive employment outcome regardless of total number of years receiving services. 5) Average per Person Cost of Services is the average individual "life of case" cost for all persons having an employment outcome regardless of total number of years receiving services. 6) Source: U.S. Department of Labor, Bureau of Labor Statistics, May 2016 State Occupational Employment and Wage Estimates, Pennsylvania, https://www.bls.gov/oes/current/oes_pa.htm#00-0000.

The following are a selection of annual outcomes of services provided by the Pennsylvania's Department of Labor & Industry's Office of Vocational Rehabilitation. Outcomes include applicants and case outcomes including employment and wages.

Key Footnotes: 1) Employed in Competitive Labor Market means employment at or above the minimum wage in settings where most employees do not have disabilities. 2) Estimated Taxes Paid are based on a standard deduction for the year, annual tax brackets and rates established by the IRS, and flat-rate FICA, state, and local taxes. 3) Estimated Total Government Savings are estimated federal, state, and local taxes paid plus annualized public support dollars at closure. 4) Average per Person Cost for a Competitive Employment Placement is the average individual "life of case" cost for all persons having a competitive employment outcome regardless of total number of years receiving services. 5) Average per Person Cost of Services is the average individual "life of case" cost for all persons having an employment outcome regardless of total number of years receiving services. 6) Source: U.S. Department of Labor, Bureau of Labor Statistics, May 2016 State Occupational Employment and Wage Estimates, Pennsylvania, https://www.bls.gov/oes/current/oes_pa.htm#00-0000.

ABSTRACTWe discuss historic trends in large metropolitan areas in Brazil showing that manufacturing has decreased its share in the country but the movement was, in general, more intense in large metropolitan areas and particularly in the São Paulo Metropolitan Area (SPMA). This movement was more intense in the 1980s and in the first half of the 1990s. From mid 1990s up to the end of the 2000s, the manufacturing share trend became flat. We speculate that the first period reflects the exhaustion of the process of import substitution that took place in the previous three decades (1950 to 1980). The second period, from 1993 to 2009, is representative of a new model of growth and the evidence that manufacturing share became flat is reinforcing the idea of a new period in terms of manufacturing employment. While concentration has risen from 1996 to 2005, it decreased again in the second half of the first decade of the 2000s. The SPMA reinvented itself very quickly from late 1970s to mid-2000s.

Global spending on telecom services is expected to reach 1.595 trillion U.S. dollars by 2024, slightly higher than the 1.575 trillion U.S. dollars spent on telecom services during 2019. The overall growth forecast is largely driven by increased spending in the Americas, as the Asia Pacific and Europe, Middle East and Africa regions are expected to remain flat. The stagnation in growth seen between 2019 and 2022 is attributable to the effects of the coronavirus (COVID-19) pandemic, with the increase in services from more people working at home offset by the slowdown in travel and tourism, and prevailing economic conditions.

Telecoms: a capital-intensive industry

Developing, maintaining and building new telecommunications infrastructure is part and parcel of operating a major telcos. Ageing infrastructure and technological advancements drive capital expenditure, while challenges such as gaining access to remote locations are expensive problems to solve.​ While the global median revenue sat at 201 million U.S. dollars in 2019, median expenses came in at 180 million U.S. dollars.

The equipment contained in the network can also provide telcos with a huge asset base. United States based AT&T generated 181.27 billion U.S. dollars in revenue during 2019, holding assets worth 551.67 billion U.S. dollars.

Economic contribution through employment

Telecommunications companies play a vital role in the economy, not only as operators of essential infrastructure, but as providers of millions of jobs worldwide. The effect of this contribution is even greater given the industry’s relative stability during uncertain economic times. AT&T alone employs 246,000 people in the United States, while Deutsche Telekom AG provides 210,530 jobs in Europe.

In June 2025, the surveyed unemployment rate in urban areas of China ranged at *** percent, remaining flat from the previous month. The annual unemployment rate in China was *** percent in 2024. Surveyed versus registered unemployment Figures on surveyed unemployment were published by the National Bureau of Statistics of China in 2018 for the first time. The use of surveys was initiated to get a more accurate picture of actual unemployment in urban areas of China. The surveys cover all permanent residents between the age of 16 and retirement age living in cities. In contrast, registered unemployment figures take only those people into account that have actively reported their unemployment. As most migrant workers and other groups that do not qualify for unemployment compensations in China normally do not report their unemployment status, the figures for registered unemployment are considerably lower than those for surveyed unemployment. Youth unemployment in China Youth unemployment has become a growing problem in China in recent years. Unemployment figures for young people fluctuate over the year and normally peak in July and August in China, when the largest number of graduates enter the job market. The youth unemployment rate increased from 13.9 percent in July 2019 to 16.8 percent in July 2020, 19.9 percent in July 2022, and 21.3 percent in June 2023. This is mainly due to difficult economic conditions and rising numbers of college graduates who often do not fit the demand for more practically skilled work in the job market.

DOI Housing and housing status. Residential area and social structure. Mobility and economic situation. Employment. Election decision and participation. Topics: 1. Housing and housing status: Size of the place (degree of urbanisation); location; duration of residence; satisfaction with the place of residence; duration of residence in the apartment; previous location; status of the previous apartment; status of the current apartment; one or more households in the house; monthly contribution costs; type of purchase of the house/flat; amount of the monthly charge for mortgage repayment and interest; amount of monthly ancillary costs; amount of maintenance costs in the last calendar year; residence entitlement certificate required; owner of the apartment; rent amount; rent including costs for heating and hot water; amount of the lump sum for heating and hot water (or for heating and hot water separately); average costs for heating and hot water and payment period; rent includes modernisation levy; amount of modernisation levy overall or per sqm; adequacy of rental costs; withdrawal of housing benefit; amount of monthly housing benefit; living space; number of rooms; assessment of apartment size; apartment equipment; apartment equipment meets needs; modem or Internet connection; garden or weekend property outside the immediate residential environment; year of construction of the house; assessment of the structural condition of the house; satisfaction with the apartment. 2. Residential area and social structure: satisfaction with the immediate living environment; satisfaction with the environmental conditions at the place of residence; walking distance to selected facilities (e.g. public transport stops, shopping facilities, doctors, kindergarten, primary school, etc.); frequency of contact with relatives and friends or acquaintances (visiting relatives or friends, visits of relatives or friends, meet elsewhere, phone or write); relatives in the residential area; friends in the residential area; shopping frequency in larger shopping centres more than 5 km away from home; frequency of leisure activities at a distance of more than 20-30 km; social differences in the immediate residential environment; relationship with neighbours; change in social composition in the residential environment; foreigners in the residential area; proportion of foreigners in residential area compared to other residential areas; attitude to the spatial separation of Germans and foreigners; personal contacts with foreigners or Germans in the family, at work, in the neighbourhood or among friends and acquaintances. 3. Mobility: intention to move; most important reason for moving; preference of moving (target area); assessment of current and future personal economic situation; change in personal economic situation since one year. 4. Employment: employment status; job security; distance to work in minutes; distance to work in kilometers; problems with reconciling work and family life. 5. Election decision and participation: eligibility to vote in the last federal election; participation in the last federal election and election decision (second vote); party preference (Sunday question) or party most likely to be considered. Demography: sex; age (month of birth and year of birth); highest school leaving certificate or targeted school leaving certificate; age at school leaving certificate; vocational education or training certificate; current or former employment; full-time or part-time employment; current or last employment position; current or last employment; current or last employment; employment in the public sector; marital status; cohabitation with a partner; employment status of the partner; former employment of the partner; professional activity of the partner; self-assessment of class affiliation; denomination; closeness to the church; church attendance frequency; union member in the household; closeness to the union; household size; net income of the respondent; number of children in the household and age of these children; number of persons in the household aged 18 years and older with German citizenship and persons with foreign citizenship; number of persons in the household contributing to household income; number of persons employed in the household; net household income; place of residence before 1989; German citizenship; telephone in the household with or without answering machine; computers in the household and computer equipment; Internet connection. Interviewer rating: residential house type; residential area type; interview is conducted in the old or new federal states. Additionally coded: ID BBSR; split; respondent-ID; state; government district; city size (political community size, BIK/Boustedt); interview date; interview duration; weighting factors; West/East. Wohnung und Wohnstatus. Wohngebiet und Sozialstruktur. Mobilität und Wirtschaftliche Lage. Erwerbstätigkeit. Wahlentscheidung und Wahlbeteiligung. Themen: 1. Wohnen und Wohnstatus: Ortsgröße (Urbanisierungsgrad); Wohnlage; Wohndauer am Wohnort; Zufriedenheit mit dem Wohnort; Wohndauer in der Wohnung; vorherig Wohnlage; Wohnstatus der vorherigen Wohnung; Wohnstatus der jetzigen Wohnung; ein Haushalt oder mehrere Haushalte im Haus; Umlagekosten pro Monat; Art des Erwerbs des Hauses/der Wohnung; Höhe der monatlichen Belastung für Hypotheken-Tilgung und Zinsen; Höhe der monatlichen Nebenkosten; Höhe der Instandhaltungskosten im letzten Kalenderjahr; Wohnberechtigungsschein erforderlich; Eigentümer der Wohnung; Miethöhe; Miete inklusive Kosten für Heizung und Warmwasser; Höhe der Pauschale für Heizung und Warmwasser (bzw. für Heizung und Warmwasser getrennt); durchschnittliche Kosten für Heizung und Warmwasser und Zahlungszeitraum; Miete enthält Modernisierungsumlage; Höhe der Modernisierungsumlage insgesamt oder pro qm; Angemessenheit der Mietkosten; Bezug von Wohngeld; Höhe des monatlichen Wohngelds; Wohnfläche; Anzahl der Wohnräume; Beurteilung der Wohnungsgröße; Wohnungsausstattung; Wohnungsausstattung entspricht den Bedürfnissen; Modem bzw. Internetanschluss; Garten oder Wochenendgrundstück außerhalb der unmittelbaren Wohnumgebung; Baujahr des Wohnhauses; Beurteilung des baulichen Zustands des Hauses; Zufriedenheit mit der Wohnung. 2. Wohngebiet und Sozialstruktur: Zufriedenheit mit der unmittelbaren Wohnumgebung; Zufriedenheit mit den Umweltbedingungen am Wohnort; fußläufige Erreichbarkeit ausgewählter Einrichtungen (z.B. Haltestellen für öffentliche Verkehrsmittel, Einkaufsmöglichkeiten, Ärzte, Kindergarten, Grundschule, etc.); Kontakthäufigkeit mit Verwandten und mit Freunden bzw. Bekannten (Verwandte bzw. Freunde besuchen, von Verwandten bzw. Freunden besucht werden, Treffen woanders, telefonieren oder schreiben); Verwandte im Wohngebiet; Freunde im Wohngebiet; Einkaufshäufigkeit in größeren Einkaufszentren in mehr als 5 km Entfernung von der Wohnung; Häufigkeit von Freizeitaktivitäten in einer Entfernung von mehr als 20-30 km; soziale Unterschiede in der unmittelbaren Wohnumgebung; Verhältnis zu den Nachbarn; Veränderung der sozialen Zusammensetzung in der Wohnumgebung; Ausländer in der Wohnumgebung; Ausländeranteil im eigenen Wohngebiet im Vergleich zu anderen Wohngebieten; Einstellung zur räumlichen Trennung von Deutschen und Ausländern; persönliche Kontakte zu Ausländern bzw. Deutschen in der Familie, am Arbeitsplatz, in der Nachbarschaft bzw. im Freundes- und Bekanntenkreis. 3. Mobilität: Umzugsabsicht; wichtigster Umzugsgrund; Umzugspräferenz (Zielgebiet); Beurteilung der derzeitigen und zukünftigen persönlichen wirtschaftlichen Lage; Veränderung der persönlichen wirtschaftlichen Lage seit einem Jahr. 4. Erwerbstätigkeit: Erwerbsstatus; Sicherheit des eigenen Arbeitsplatzes; Länge des Arbeitsweges; Entfernung des Arbeitsplatzes in Kilometern; Probleme mit der Vereinbarkeit von Familie und Beruf. 5. Wahlentscheidung und Wahlbeteiligung: Wahlberechtigung bei der letzten Bundestagswahl; Teilnahme an der letzten Bundestagswahl und Wahlentscheidung (Zweitstimme); Parteipräferenz (Sonntagsfrage) bzw. Partei, die am ehesten in Frage käme. Demographie: Geschlecht; Alter (Geburtsmonat und Geburtsjahr); höchster Schulabschluss bzw. angestrebter Schulabschluss; Alter bei Schulabschluss; Berufsausbildung bzw. Ausbildungsabschluss; derzeitige bzw. frühere Erwerbstätigkeit; Vollzeit- bzw. Teilzeiterwerbstätigkeit; derzeitige bzw. letzte berufliche Stellung; derzeitige bzw. letzte berufliche Tätigkeit; Tätigkeit im öffentlichen Dienst; Familienstand; Zusammenleben mit einem Partner; Erwerbsstatus des Partners; frühere Erwerbstätigkeit des Partners; berufliche Tätigkeit des Partners; Selbsteinstufung der Schichtzugehörigkeit; Konfession bzw. Religionsgemeinschaft; Kirchenverbundenheit; Kirchgangshäufigkeit; Gewerkschaftsmitglied im Haushalt; Gewerkschaftsverbundenheit; Haushaltsgröße; Nettoeinkommen des Befragten; Anzahl der Kinder im Haushalt und Alter dieser Kinder; Anzahl der Personen im Haushalt ab 18 Jahren mit deutscher Staatsangehörigkeit und der Personen mit ausländischer Staatsangehörigkeit; Anzahl der Personen im Haushalt, die zum Haushaltseinkommen beitragen; Anzahl der Erwerbstätigen im Haushalt; Haushaltsnettoeinkommen; Wohnort vor 1989; deutsche Staatsangehörigkeit; Telefon im Haushalt mit oder ohne Anrufbeantworter; Computer im Haushalt und Computerausstattung; Internetanschluss. Interviewerrating: Wohnhaustyp; Wohngegendtyp; Interview wird durchgeführt in den alten oder in den neuen Bundesländern. Zusätzlich verkodet wurde: ID BBSR; Split; Befragten-ID; Bundesland; Regierungsbezirk; Ortsgröße (politische Gemeindegröße, BIK/Boustedt); Interviewdatum; Interviewdauer; Gewichtungsfaktoren; West/Ost. Probability Sample: Multistage Sample Wahrscheinlichkeitsauswahl: Mehrstufige Zufallsauswahl

The Global Alternative Legal Services Providers (ALSP) Market size is expected to reach $44.69 billion by 2032, rising at a market growth of 8.2% CAGR during the forecast period. Due to the high demand from companies looking for help with governance, mergers and acquisitions, regulatory compliance,

This paper employs a computable general equilibrium model (CGE) to analyse how a carbon tax and/or a national Emissions Trading System (ETS) would affect macroeconomic parameters in Turkey. The modelling work is based on three main policy options for the government by 2030, in the context of Turkey’s mitigation target under its Intended Nationally Determined Contribution (INDC), that is, reducing greenhouse gas (GHG) emissions by up to 21% from its Business as Usual (BAU) scenario in 2030: (i) improving the productivity of renewable energy by 1% per annum, a target already included in the INDC, (ii) introducing a new flat rate tax of 15% per ton of CO2 (of a reference carbon price in world markets) imposed on emissions originating from carbon-intensive sectors, and (iii) introducing a new ETS with caps on emission permits. Our base path scenario projects that GHG emissions in 2030 will be much lower than Turkey’s BAU trajectory of growth from 430 Mt CO2-eq in 2013 to 1.175 Mt CO2-eq by 2030, implying that the government’s commitment is largely redundant. On the other hand, if the official target is assumed to be only a simple reduction percentage in 2030 (by 21%), but based on our more realistic base path, the government’s current renewable energy plans will not be sufficient to reach it. Turkey’s official INDC is based on over-optimistic assumptions of GDP growth and a highly carbon-intensive development pathway;A carbon tax and/or an ETS would be required to reach the 21% reduction target over a realistic base path scenario for 2030;The policy options considered in this paper have some effects on major sectors’ shares in total value-added. Yet the reduction in the shares of agriculture, industry, and transportation does not go beyond 1%, while the service sector seems to benefit from most of the policy options;Overall employment would be affected positively by the renewable energy target, carbon tax, and ETS through the creation of new jobs;Unemployment rates are lower, economic growth is stronger, and households become better off to a larger extent under an ETS than carbon taxation. Turkey’s official INDC is based on over-optimistic assumptions of GDP growth and a highly carbon-intensive development pathway; A carbon tax and/or an ETS would be required to reach the 21% reduction target over a realistic base path scenario for 2030; The policy options considered in this paper have some effects on major sectors’ shares in total value-added. Yet the reduction in the shares of agriculture, industry, and transportation does not go beyond 1%, while the service sector seems to benefit from most of the policy options; Overall employment would be affected positively by the renewable energy target, carbon tax, and ETS through the creation of new jobs; Unemployment rates are lower, economic growth is stronger, and households become better off to a larger extent under an ETS than carbon taxation.

Housing and residential status. Residential area and social structure. Mobility and economic situation. Employment. Election decision and participation.

Topics: 1. Housing and residential status: size of place (degree of urbanisation); location; duration of residence; satisfaction with the place of residence; duration of residence in the apartment; distance before moving into the current apartment; previous place of residence; previous location; residential status of the previous apartment and reasons for moving; main reason for moving; current apartment itself sought, obtained by exchange or assignment; residential status of the current apartment; social housing; owner of the apartment; only one family in the house or several households; rent amount; rent including costs for heating and hot water; amount of the flat rate for heating and hot water; average costs for heating and hot water and payment period; rent includes modernization levy; amount of the modernization levy in total or per sqm; adequacy of rental costs; receipt of housing allowance; amount of monthly housing allowance; living space; number of rooms; assessment of the apartment size; apartment equipment; apartment equipment corresponds to the needs; year of construction of the house; assessment of the structural condition of the house; satisfaction with the apartment.

1. Residential area and social structure: satisfaction with the immediate residential environment; satisfaction with the environmental conditions in the residential environment; relationship with neighbours; social structure: foreigners in the residential environment; percentage of foreigners in the residential environment; assessment of the relationship between foreigners and Germans in the residential environment; attitude towards the spatial separation of Germans and foreigners; personal contacts with foreigners in the family, at work, in the neighbourhood or among friends and acquaintances.

2. Mobility: intention to move; reasons for the intention to move; main reason for the intention to move; preference for moving (target area); preference for old or new federal states; assessment of current and future personal economic situation; change in personal economic situation since one year.

3. Employment: employment status; job security; commute; life satisfaction.

4. Electoral decision and participation: eligibility to vote in the last federal election; participation in the last federal election and election decision (second vote); party preference (Sunday question) or party most likely to be considered.

Demography: sex: age (month of birth and year of birth); highest school leaving certificate or targeted school leaving certificate; age at school leaving certificate; vocational education or training certificate; current or former employment; full-time or part-time employment; current or last employment position; current or last employment activity; employment in the public sector; marital status; cohabitation with a partner; self-assessment of class; religious denomination; church affiliation of the respondent and parents; participation in religious education; household size; net income of the respondent; number of children in the household and age of these children; number of persons in the household over 18 years with German citizenship; number of persons in the household who contribute to the household income; number of persons employed in the household; household net income; telephone connection in the household.

Interviewer rating: residential house type; residential area type; presence of other persons during the interview; intervention of persons present in the interview; willingness of the respondent to cooperate; reliability of respondent’s information.

Additionally coded was: ID BBSR; split; respondent-ID; serial no.; state; government district; city size (political community size); interview date; interviewer sex; interviewer age; interviewer-ID.

The selected non-financial assets data are sourced from the RBA. These data relate to households only. ‘Consumer durables’ are tangible assets, other than dwellings, that generally have a life of a year or more. These include motor vehicles, furnishings and other household equipment. The quarterly estimates of the market value of consumer durables owned by households are interpolated from annual data sourced from the ABS. The latest data are extrapolated from the most recent observation. ‘Dwellings’ are considered to be private dwellings owned by households in all areas of Australia. These include houses, semi-detached dwellings, townhouses, terrace houses, flats, units and apartments. The market value of the stock of household dwellings is estimated by multiplying the dwelling stock by an Australia-wide mean dwelling price series. The dwelling stock is estimated by combining Census data and the number of new dwellings completed each quarter (sourced from the ABS) with an adjustment for estimated demolitions. The dwelling price series is constructed from a number of sources including RP Data/Rismark. The financial assets and liabilities data are derived from ABS Cat No 5232.0, Tables 4 and 20. The sectoral classification is on a national accounts basis and differs slightly from that in the preceding tables. In particular, the household sector includes unincorporated enterprises and non-profit institutions serving households. Identified claims between transactors in the same sector are excluded. The data were upgraded in 2009 to comply with SNA08 standards and are only available back to June 1988. ‘Reserves of life offices and pension funds’ are equal to total assets of life offices, superannuation funds and friendly societies, less liabilities of these institutions other than to policyholders and fund members. Ownership of these net assets is imputed to the household sector. ‘Unfunded superannuation claims’ are liabilities of state, local and national governments to public sector employees in respect of unfunded retirement benefits. ‘Loans from banks’ are taken directly from the asset side of Table 8 in the above ABS catalogue and exclude bills of exchange etc.

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

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This data is based on data collected as part of the national data collection operation on the professional integration of Master’s graduates.

This investigation has been carried out

in December 2013, 30 months after graduation, with 59,600 Master graduates from the 2011 session. in December 2012, 30 months after graduation, with 47,500 Master graduates from the 2010 session. The integration rate is defined as the percentage of graduates in any job, of all graduates present in the labour market. It is calculated on graduates of French nationality, from initial training, who entered the labour market immediately and sustainably after graduation in 2011. Graduates verifying these conditions represent 38 % of all Master’s graduates (39 % for the 2010 session). The information collected on the salary relates to the net salary, including bonuses. The posted wages correspond to the median values on full-time jobs. Based on these values, an annual gross salary is estimated, based on a flat rate of change from net to gross of 1.3 (average data on private sector wages).

The survey was conducted by universities in the framework of a charter whose provisions are designed to ensure comparability of results between institutions. The overall coordination and operation of the survey is carried out by the Ministry in charge of Higher Education and Research.

In 2011, the rate of actionable responses across universities was 71 % (70 % for the 2010 session), but this rate varies significantly from one university to another (from 92 % to 28 % for the 2011 session, from 93 % to 9 % for the 2010 session). Given the response rate and the number of respondents working on data quality, it was decided not to disseminate the results of universities with too low numbers of respondents (less than 30) or a response rate of less than 30 % and to report by the words “fragile results” those with a response rate of less than 50 %.

Sources of additional data:

% of scholarship graduates: data observed on the population of the occupational integration survey.

Regional unemployment rate: INSEE — 4th quarter 2012 for the 2010 session, 4th quarter 2013 for the 2011 session.

Regional median net monthly salary: INSEE DADS 2010 for the 2010 session and INSEE DADS 2011 for the 2010 session — for 25-29 year olds employed full-time in the socio-professional categories “Senior intellectual frameworks and professions” and “Intermediate Professions”.

Legend: nd = not available (no respondent) ns = insignificant (number of respondents less than 30).

— Denominations of variables of exported files (for year N):

number_of_responses: Number of responses

rate_of_response: Response rate

weight_of_discipline: Weight of discipline

jobs_frame_or_professions_intermediaires: Share of middle-level or middle-level jobs

jobs_stables: Share of stable jobs

jobs_a_time_full: Share of full-time jobs

salary_net_median_jobs_a_time_full: Median monthly net salary of full-time jobs

salary_gross_annual_estimates: Estimated median annual gross salary

de_diplomes_Scholars: Share of fellow graduates in the institution

rate_of_chomage_regional: Regional unemployment rate (INSEE: Fourth quarter N+ 2)

salary_net_mensuel_median_regional: Median net monthly salary of 25-29 year olds employed full-time in the framework and intermediate occupation categories (INSEE: DADS N)

insertion rate: Insertion rate

jobs_Framework: Share of senior level jobs (In some sectors of activity, not all jobs corresponding to the diploma are of a framework level. Access to the framework level may require prior professional experience.)

employment_external_a_la_region_de_luniversite Share of jobs located outside the region of the establishment (including abroad)

women: Share of women

Data on 2011 graduates can be found on the website of MENESR

Data by institution is also available.

Graph and download economic data for Nonfarm Business Sector: Real Hourly Compensation for All Workers (COMPRNFB) from Q1 1947 to Q1 2025 about per hour, compensation, sector, nonfarm, business, real, and USA.

Abstract

Objective of the Enterprise Survey: The main aim of the survey on unorganised service sector enterprises was to estimate size in terms of the total number enterprises, employment, fixed assets, operating expenses, receipts, value added, loans, gross value added per worker, etc. Information on other attributes like type of ownership, type of operation, number of months of operation, whether carrying out mixed/multiple activity, whether accounts maintained, etc. was also collected. The results pertaining to size, employment and economic indicators of the enterprises have been brought out in the first report*. This report, second in the series, presents the size and employment in brief, and the characteristics of the enterprises in terms of ownership, social group of owner, type of operation, months of operation, whether accounts maintained, nature of problems faced, etc.

Geographic coverage

National, State, Urban and Rural

Analysis unit

Enterprises and Households

Universe

All enterprises belonging to the service sector excluding the service sector enterprises pursuing the activities of wholesale and retail trade, repair of motor vehicles, motorcycles and personal and household goods (G); financial intermediation (J); public administration and defence (L); private households with employed persons (P) and extra-territorial organisations and bodies (Q).

Kind of data

Sample survey data [ssd]

Sampling procedure

Outline of sample design: Two frames have been used for the 63rd round survey viz. List frame and Area frame.

List frame: A list of 1000 service sector companies distributed all over India has been used as list frame. The list of financial sector enterprises has been supplied by RBI. For the other service sector enterprises the list has been supplied by the Ministry of Company Affairs. For all the companies in the list frame, information will be collected considering all the branch offices. A combined schedule 2.345 is to be filled up for the list frame companies covering all the branches.All these companies in the list frame will be surveyed. However, these companies and their branch offices will be excluded from the coverage of the area frame survey to avoid duplication.There is no sub-round restriction for the list frame units. All the enterprises in the list frame are common to both central and state samples.The list frame units will be surveyed by the central agency only. Validated data regarding list frame units will besupplied by DPD to the respective State agencies.

Area frame: A stratified multi-stage design has been adopted for the 63rd round survey. The first stage units (FSU) will be the 2001 census villages (Panchayat wards in case of Kerala) in the rural sector and Urban Frame Survey (UFS) blocks in the urban sector. In addition, for the newly declared towns and out growths (OGs) in census 2001 for which UFS has not yet been done, a separate list has been prepared and these list has been used as a frame for such towns and OGs in urban sector. For these towns and OGs the whole town/ OG will be considered as FSU. The ultimate stage units (USU) will be households/ service sector enterprises, in both the sectors. In the case of large villages/ towns/ blocks requiring hamlet-group (hg)/ sub-block (sb) formation, one intermediate stage will be the selection of hgs/ sbs from each FSU.

The list of villages as per census 2001 has been used as frame for the rural sector. In the urban sector, three kinds of frames have been used: (a) For the 27 towns with population 10 lakhs or more (as per Census 2001), EC-98 has been used as frame. (b) For other UFS towns, the latest available list of UFS blocks has been used as frame. (c) For non-UFS towns list of such towns/ OGs has been used as frame.

Stratification: Within each district of a State/ UT, two basic strata have been formed: i) rural stratum comprising of all rural areas of the district and (ii) urban stratum comprising of all the urban areas of the district. However, if there are one or more towns with population 10 lakhs or more as per population census 2001 in a district, each of them will also form a separate basic stratum and the remaining urban areas of the district will be considered as another basic stratum. There are 27 towns with population 10 lakhs or more at all- India level as per census 2001. Sub-stratification for area frame:

Total sample size: 13997 FSUs for area frame and 1000 service sector companies for list frame have been allocated at all-India level for central sample on the basis of investigator strength. For state sample, 16892 FSUs have been allocated for area frame.

For Detailed on Sampling procedure refereed to External Resource , page number A5 of Note on Sample Design and Estimation Procedure

Sampling deviation

There was no deviation from the original sampling design

Mode of data collection

Face-to-face [f2f]

Research instrument

Schedule 3.1 consists of the following 7 blocks: [0] descriptive identification of sample enterprise [1] identification of sample enterprise / establishment [2] particulars of operation and background information [3] selected important operating expenses during the reference month (Rs. in whole number) other operating expenses during the reference month: all activities (Rs. in whole number)

(blocks 3 and 3.1 together will give total expenses of the enterprise. If some of the items have already been covered under specific activities in block 3, they should not be reported here again)

[4] selected important receipts during the reference month (Rs. in whole number) [4.1] other receipts during the reference month : all activities (Rs. in whole number) (blocks 4 and 4.1 together will give total receipts of the enterprise. If some of the items have already been covered under specific activities in block 4, they should not be reported here again) [5] calculation of gross value added for the reference month (Rs. in whole number) [6] employment particulars of the enterprise during the reference month [7] compensation to workers during the reference month [8] fixed assets owned and hired [9] loans outstanding as on the date of survey (only loans taken for enterprise to be considered) [10] particulars of field operation

Blocks 3 and 4 are the main blocks of this schedule. Block 3 is meant for recording the information relating to availability of some facilities to the villagers. Block 4 is for recording the information relating to distance of specified facilities from the centre of the sample village.

Blocks 0 & 1 are meant for recording the identification particulars of the sample village. Block 2, 5 and 6 are used for recording the particulars relating to field operations, Remarks of the investigators and those of the supervisory officer(s) respectively.

Cleaning operations

Data was collected as per the Questionnaire 2.3453. But for processing purposes, two flat files were created using the identification particulars from Block 1 and 2. Other data for these two data sets have been derived from Block 3 to 10. Data editing, scrutiny and validation were carried out as per the scrutiny checks and corrected manually.

Data appraisal

Comparison of results with earlier survey for Unorganised service sector.