In 1990, the unemployment rate of the United States stood at 5.6 percent. Since then there have been many significant fluctuations to this number - the 2008 financial crisis left millions of people without work, as did the COVID-19 pandemic. By the end of 2022 and throughout 2023, the unemployment rate came to 3.6 percent, the lowest rate seen for decades. However, 2024 saw an increase up to four percent. For monthly updates on unemployment in the United States visit either the monthly national unemployment rate here, or the monthly state unemployment rate here. Both are seasonally adjusted. UnemploymentUnemployment is defined as a situation when an employed person is laid off, fired or quits his work and is still actively looking for a job. Unemployment can be found even in the healthiest economies, and many economists consider an unemployment rate at or below five percent to mean there is 'full employment' within an economy. If former employed persons go back to school or leave the job to take care of children they are no longer part of the active labor force and therefore not counted among the unemployed. Unemployment can also be the effect of events that are not part of the normal dynamics of an economy. Layoffs can be the result of technological progress, for example when robots replace workers in automobile production. Sometimes unemployment is caused by job outsourcing, due to the fact that employers often search for cheap labor around the globe and not only domestically. In 2022, the tech sector in the U.S. experienced significant lay-offs amid growing economic uncertainty. In the fourth quarter of 2022, more than 70,000 workers were laid off, despite low unemployment nationwide. The unemployment rate in the United States varies from state to state. In 2021, California had the highest number of unemployed persons with 1.38 million out of work.

In August 2025, the agriculture and related private wage and salary workers industry had the highest unemployment rate in the United States, at seven percent. In comparison, financial activities workers had the lowest unemployment rate, at 1.6 percent. The average for all industries was 4.5 percent. U.S. unemployment There are several factors that impact unemployment, as it fluctuates with the state of the economy. Unfortunately, the forecasted unemployment rate in the United States is expected to increase as we head into the latter half of the decade. Those with a bachelor’s degree or higher saw the lowest unemployment rate from 1992 to 2022 in the United States, which is attributed to the fact that higher levels of education are seen as more desirable in the workforce. Nevada unemployment Nevada is one of the states with the highest unemployment rates in the country and Vermont typically has one of the lowest unemployment rates. These are seasonally adjusted rates, which means that seasonal factors such as holiday periods and weather events that influence employment periods are removed. Nevada's economy consists of industries that are currently suffering high unemployment rates such as tourism. As of May 2023, about 5.4 percent of Nevada's population was unemployed, possibly due to the lingering impact of the coronavirus pandemic.

Unemployment Rate in the United States increased to 4.40 percent in September from 4.30 percent in August of 2025. This dataset provides the latest reported value for - United States Unemployment Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

In the fourth quarter of 2024, the unemployment rate in the information industry in the United States stood at *** percent, increasing from *** percent in the same quarter of 2023. In 2020, the tech industry was hit hard by the economic recession brought about by the COVID-19 pandemic, registering a record ** percent unemployment rate during the second quarter. Information industry in the U.S. The U.S. information industry consists of those businesses involved in the production or distribution of information, those involved in providing a means to distribute information and data, and those involved in data processing. More specifically, the sector is comprised of * segments: publishing industries (except internet), motion picture and sound recording industries, broadcasting (except internet), telecommunications, data processing/hosting, and other information services. Employment in the U.S. information industry As a whole, the sector employs nearly ************* people around the United States and accounts for a significant portion of the country’s entertainment industry. As unemployment has fallen, average hourly earnings within the sector have also risen sharply within the past decade, now amounting to almost ** dollars per hour. This trend towards more favorable employment conditions comes at a time when union membership within the industry declined to *** percent in 2022.

Unemployment Rate in South Africa decreased to 31.90 percent in the third quarter of 2025 from 33.20 percent in the second quarter of 2025. This dataset provides - South Africa Unemployment Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Unemployment Rate in Philippines decreased to 3.80 percent in September from 3.90 percent in August of 2025. This dataset provides - Philippines Unemployment Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

View monthly updates and historical trends for Ontario Unemployment Rate. Source: Statistics Canada. Track economic data with YCharts analytics.

Number of persons in the labour force (employment and unemployment) and not in the labour force, unemployment rate, participation rate, and employment rate, by census metropolitan area, sex and age group, last 5 months.

The Labour Force Survey provides estimates of employment and unemployment which are among the timeliest and important measures of performance of the Canadian economy. With the release of the survey results only 10 days after the completion of data collection, the LFS estimates are the first of the major monthly economic data series to be released. The Canadian Labour Force Survey was developed following the Second World War to satisfy a need for reliable and timely data on the labour market. Information was urgently required on the massive labour market changes involved in the transition from a war to a peace-time economy. The main objective of the LFS is to divide the working-age population into three mutually exclusive classifications - employed, unemployed, and not in the labour force - and to provide descriptive and explanatory data on each of these. LFS data are used to produce the well-known unemployment rate as well as other standard labour market indicators such as the employment rate and the participation rate. The LFS also provides employment estimates by industry, occupation, public and private sector, hours worked and much more, all cross-classifiable by a variety of demographic characteristics. Estimates are produced for Canada, the provinces, the territories and a large number of sub-provincial regions. For employees, wage rates, union status, job permanency and workplace size are also produced. These data are used by different levels of government for evaluation and planning of employment programs in Canada. Regional unemployment rates are used by Employment and Social Development Canada to determine eligibility, level and duration of insurance benefits for persons living within a particular employment insurance region. The data are also used by labour market analysts, economists, consultants, planners, forecasters and academics in both the private and public sector.This public use microdata file contains non-aggregated data for a wide variety of variables collected from the Labour Force Survey (LFS). It contains both personal characteristics for all individuals in the household and detailed labour force characteristics for household members 15 years of age and over. The personal characteristics include age, sex, marital status, educational attainment, and family characteristics. Detailed labour force characteristics include employment information such as class of worker, usual and actual hours of work, employee hourly and weekly wages, industry and occupation of current or most recent job, public and private sector, union status, paid or unpaid overtime hours, job permanency, hours of work lost, job tenure, and unemployment information such as duration of unemployment, methods of job search and type of job sought. Labour force characteristics are also available for students during the school year and during the summer months as well as school attendance whether full or part-time and the type of institution.LFS revisions: Labour force surveys are revised on a periodic basis, either to adopt the most recent geography, industry and occupation classifications; to use new observations to fine-tune seasonal adjustment factors; or to introduce methodological enhancement. Prior LFS revisions were conducted in 2011, 2015 and 2021. The most recent revisions to the LFS were conducted in 2023. The first major change was a transition to the National Occupational Classification (NOC) 2021 V1.0, with all LFS series from 1987 onwards having been revised to the new classification. The second major change were methodological enhancements to LFS data processing, applied to all LFS series beginning Jan 2006. The third major change was a revision of seasonal adjustment factors, applied to LFS series Jan 2002 onward. A list of prior versions of this LFS dataset can be found under the ‘Versions’ tab.

Movie Scores vs. Unemployment Rate

Examining the Correlation between Cinema Popularity and Economic Stability

By [source]

About this dataset

This dataset examines the potential correlation between US unemployment rates and movie scores in order to explore how difficult economic times can influence how viewers rate films. With data spanning from 2009-2018, this dataset contains information on the yearly unemployment rate as well as the average movie score on a scale from 1-10 for that same year. Our goal is to investigate whether economic unrest and hardship have any effect on film ratings in order to shed light both on an often overlooked part of moviegoers' opinions, and also on our society's attitudes towards certain topics during times of crisis

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Research Ideas

• Predicting the success of a movie, given the economic conditions for that year.
• Determining how a year's unemployment rate affects viewers' overall opinion of movies from that same period.
• Analyzing whether people rate movies differently in times of economic difficulty than when the economy is booming

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

Columns

File: result.csv | Column name | Description | |:-------------------|:-----------------------------------------------------------------------------------------------------------------------------------------------------| | year | The year in which the movie was released. (Integer) | | UnEmployeeRate | The unemployment rate in the country during the year the movie was released. (Float) | | movieScore | The average score of the movie based on reviews from critic websites such as Rotten Tomatoes, IMDb etc., with 10 being highest rated movies. (Float) |

Acknowledgements

If you use this dataset in your research, please credit the original authors. If you use this dataset in your research, please credit .

Abstract

The 2004-05 Household Survey of Employment and Unemployment aimed to meet the data requirements of planners working towards improving the quality and productivity of Fiji's human resources.

The principal objective of the survey was to obtain comprehensive statistical data on the economically active population, comprising employed and unemployed persons, as well as on the inactive population of working age. From the data, the size and structure of the country's workforce have been determined. When compared to figures of previous years, changes in the labour market and in the employment situation can be obtained.

Geographic coverage

National

Analysis unit

Household Individual

Kind of data

Sample survey data [ssd]

Sampling procedure

Sampling Design The survey included all householders in conventional dwellings distributed in localities within the urban and urban sectors of the four administrative divisions namely Central, Eastern, Western and Northern.

The target population was Fiji Citizens and permit holders in conventional dwellings excluding those found in households of non-Fiji citizens, hospitals, prisons, hotels, temporary construction sites, boarding schools and similar institutions.

A sampling frame was constructed using the count of conventional households gather from the listing stage for HIES 2002-2003 and information gathered from updates to EAs identified to have had significant changes in household numbers. In previous surveys the sample was drawn from a sampling frame taken from the immediate past census. This would not have been suitable for this survey, as the last census was taken almost 10 years ago. Since then, there has been considerable rural: urban drift, while the urban boundaries have extended significantly in many areas, for example, along the Nadi and lautoka corridor.

A sample of 3000 households was targeted using a two stage stratified systematic sampling. The first stage involved the selection of 300 EAs in proportion to the number of households in each stratum. In the second stage, a random sample of 10 households within each identified EA was selected. This sample, including a reserve pool, was drawn from a list of households in EA stratified by household size and ethnicity.

Mode of data collection

Face-to-face [f2f]

Cleaning operations

Coding and Data Entry Once the schedules were returned, coders tallied counts of population and households by ethnicity. Written responses were standardized. These tasks include coding the main occupation and industry of the employed and those involved in any economic activity including responses of those not in the labour force. Separate data entry screens were used for the Schedule 1- Listing, and Schedule 2- Main schedule using CSPro, a survey data processing software. The data entry screens had built in skip patterns derived from the questionnaire, simplifying data entry and editing.

Editing Some editing were done in the field and verified at coding stages. However a more thorough check involved printing all entered information and the verifying against field records item by item. This ensured that data gathered from the field was not lost in transition during data entry through to output. Consistency and structural checks on the data were part of the tasks carried out at the compilation stages of the final database. The calculated weight was assigned to each record at this edit stage. Data frequencies on variables also provided an indication of the effectiveness of the data collection exercise, particularly in checking the required number of households to be visited per EA. Weighted frequencies further provided an indication of the accuracy of the data collection and monitoring survey processes as a whole.

Verification Verification of information was done by enumerator on repeat household visits during the week allocated for completion of the main questionnaire. Checks on age and relationship of members of the household to the head were some of the initial tasks in making sure that respondents provided information with a highest acceptable degree of accuracy and consistency. For working employees. enumerators were able to access statements of emoluments and at times balance sheets for those involved in sale of goods and services.

Response rate

Response rate is 100%.

Key information about Turkey Unemployment Rate

• Turkey Unemployment Rate dropped to 8.50% in Oct 2025, from the previously reported figure of 8.60% in Sep 2025.
• Turkey Unemployment Rate is updated monthly, available from Jan 2005 to Oct 2025, with an average rate of 10.20%.
• The data reached an all-time high of 14.10% in Jul 2020 and a record low of 8.00% in Mar 2025.
• The data is reported by reported by Turkish Statistical Institute.
• In the latest reports, Turkey Population reached 85.66 million people in Dec 2024.

This dataset provides information on the unemployment rates for different demographic groups in the United States.

The data is sourced from the Economic Policy Institute’s State of Working America Data Library and economic research conducted by the Federal Reserve Bank of St. Louis.

The dataset contains unemployment rates for various age groups, education levels, genders, races, and more.

Interesting Task Ideas:

1. See how unemployment rates have changed for different groups of people over time.
2. Look into how education levels can affect unemployment rates.
3. Compare unemployment rates between different races / genders.
4. Check out how unemployment rates can vary across different age groups and genders.
5. Find out if there's a connection between education levels and unemployment rates within specific racial or gender groups.
6. Explore how economic downturns can impact unemployment rates for specific groups of people.
7. Use the data to create visuals that show how unemployment rates differ across all sorts of factors.

Don't forget to upvote this dataset if you find it useful! 😊💝

Checkout my other datasets

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Column Descriptions

The IZA Evaluation Dataset Survey (IZA ED) was developed in order to obtain reliable longitudinal estimates for the impact of Active Labor Market Policies (ALMP). Moreover, it is suitable for studying the processes of job search and labor market reintegration. The data allow analyzing dynamics with respect to a rich set of individual and labor market characteristics. It covers the initial period of unemployment as well as long-term outcomes, for a total period of up to 3 years after unemployment entry. A longitudinal questionnaire records monthly labor market activities and their duration in detail for the mentioned period. These activities are, for example, employment, unemployment, ALMP, other training etc. Available information covers employment status, occupation, sector, and related earnings, hours, unemployment benefits or other transfer payments. A cross-sectional questionnaire contains all basic information including the process of entering into unemployment, and demographics. The entry into unemployment describes detailed job search behavior such as search intensity, search channels and the role of the Employment Agency. Moreover, reservation wages and individual expectations about leaving unemployment or participating in ALMP programs are recorded. The available demographic information covers employment status, occupation and sector, as well as specifics about citizenship and ethnic background, educational levels, number and age of children, household structure and income, family background, health status, and workplace as well as place of residence regions. The survey provides as well detailed information about the treatment by the unemployment insurance authorities, imposed labor market policies, benefit receipt and sanctions. The survey focuses additionally on individual characteristics and behavior. Such co-variates of individuals comprise social networks, ethnic and migration background, relations and identity, personality traits, cognitive and non-cognitive skills, life and job satisfaction, risky behavior, attitudes and preferences. The main advantages of the IZA ED are the large sample size of unemployed individuals, the accuracy of employment histories, the innovative and rich set of individual co-variates and the fact that the survey measures important characteristics shortly after entry into unemployment.

Abstract

Statistical information on all aspects of the population is vital for the design, implementation, monitoring and evaluation of economic and social development plan and policy issues. Labour force survey is one of the most important sources of data for assessing the role of the population of the country in the economic and social development process. It is useful to indicate the extent of available and unutilized human resources that must be absorbed by the national economy to ensure full employment and economic well being of the population. Statistics on the labour force further present the measurement of economic activity status and its relationship to other social and economic characteristics of the population. Seasonal and other variations as well as changes over time in the size and characteristics of employed and unemployed populations that can be monitored using up-to-date information from labour force surveys. It serves as an input for assessing the meeting of the Millennium Development Goals (MDGs). Furthermore, labour force datais also used as a springboard for monitoring and evaluation of the five years growth and transformation plan of a country.

Despite the significance of the labopur force data, the availability of reliable and timely labour force data were inadequate. The lack of reliable and timely data on different aspects of the population hinders the monitoring and evaluation of changes of developmental activities.

In order to fill the gap in data requirement for the purpose of socio-economic development planning, monitoring and evaluation, the Central Statistical Agency (CSA) has been providing labour force and related data at different levels with various contents and details. These include the 1976 Addis Ababa Manpower and Housing Sample Survey, the 1978 Survey on Population and Housing Characteristics of Seventeen Major Towns, the 1980/81 and 1987/88 Rural Labour Force Surveys (RLFS). Also, the 1984, 1994 and 2007 Population and Housing Censuses and the 1999 and 2005 National Labour Force Surveys provided a comprehensive national labour force data representing both urban and rural areas.

The survey results mainly provide data on the main characteristics of employed and unemployed population, that is, the work force engaged or available to be engaged in the production of economic goods and services and its distribution in the various sectors of the economy during a given reference period.

In addition, data on economic activities of children were also collected to measure child labour in urban areas. For this purpose, the former minimum age limit 10 years was lower down to 5 years since May 2009. Therefore, the data in this survey were collected from those persons aged five years and over. However, for the purpose of measuring the economic activity status based on Ethiopian situation, the lower age limit was fixed in to ten years. This is because children in rural and urban areas used to work at their early age such as collection of fire wood, looking after cattle, shoeshine, street vendor, petty trading…etc. Thus, the May 2011 Urban Employment and Unemployment Survey statistical report is mainly aimed at provide information on the economic characteristics of the population aged ten years and over.

Furthermore, the 2011 UEUS provide data on employment on the informal sector, their spatial distribution and problem in the sector.

Geographic coverage

The 2011 Urban Employment and Unemployment Survey (UEUS) covered all urban parts of the country except three zones of Afar, Six zones of Somali, where the residents are pastoralists.

Analysis unit

• Household
• Individual aged 10 years and above

Universe

The survey follows household approach and covers households residing in conventional households and thus, population residing in the collective quarters such as universities/colleges, hotel/hostel, monasteries and homeless population etc., are not covered by this survey.

Kind of data

Sample survey data [ssd]

Sampling procedure

SAMPLING FRAME The list of households obtained from the 2007 population and housing census is used to select EAs. A fresh list of households from each EA was prepared at the beginning of the survey period. The list was then used as a frame in order to select 30 households from sample EAs.

SAMPLE DESIGN For the purpose of the survey the country was divided into two broad categories. That is major urban center and other urban center categories. Category I:- Major urban centers:- In this category all regional capitals and five other major urban centers that have a high population size as compared to others were included. Each urban center in this category was considered as a reporting level. The category has a total of 16 reporting levels. In this category, in order to select the sample, a stratified two-stage cluster sample design was implemented. The primary sampling units were EAs of each reporting level. From each sample EA 30 households were then selected as a Second Stage Unit (SSU).

Category II:- Other urban centers: Urban centers in the country other than those under category I were grouped into this category. A domain of other urban centers is formed for each region. Consequently 8 reporting levels were formed in this category. Harari, Addis Ababa and Dire Dawa do not have urban centers other than that grouped in category I. Hence, no domain was formed for these regions under this category.

A stratified three stage cluster sample design was also adopted to select samples from this category. The primary sampling units were urban centers and the second stage sampling units were EAs. From each EA 30 households were selected at the third stage and the survey questionnaires administered for all of them.

Mode of data collection

Face-to-face [f2f]

Research instrument

The survey questionnaire is organized into six sections; Section - 1: Area identification of the selected household: this section deals with area identification of respondents such as region, zone, wereda, etc. Section - 2: Particulars of household members: it consists of the general socio-demographic characteristics of the population such as age, sex, educational status, types of training and marital status. Section - 3: Economic activity during the last seven days: this section deal with whether persons were engaged in productive activities or not during the last seven days prior to date of interview, the status and characteristics of employed persons such as occupation, industry, employment status, hours of work, employment sector /formal and informal employment/ and earnings from paid employment. Section - 4: Unemployment rate and characteristics of unemployed persons: this section focuses on the size, distribution and characteristics of the unemployed population and unemployment rate only for those aged 10 years and over. Section - 5: Economic activity during the last six months: this section contains information on the economic activity status of the population in the long reference period or during the last six months.
Section - 6: Economic activity of children aged 5-17 years: this section consists of information on the participation of children aged 5-17 years in the economic activities, whether attending education, reason for not attending education…etc.

Cleaning operations

The filled-in questionnaires that were retrieved from the field were first subjected to manual editing and coding. During the fieldwork the field supervisors and the heads of branch statistical offices have checked the filled-in questionnaires and carried out some editing. However, the major editing and coding operation was carried out at the head office. All the edited questionnaires were again fully verified and checked for consistency before they were submitted to the data entry by the subject matter experts.

Using the computer edit specifications prepared earlier for this purpose, the entered data were checked for consistencies and then computer editing or data cleaning was made by referring back to the filled-in questionnaire. This is an important part of data processing operation in attaining the required level of data quality. Consistency checks and re-checks were also made based on frequency and tabulation results. This was done by senior programmers using CSPro software in collaboration with the senior subject experts from Manpower Statistics Team of the CSA.

Response rate

It was initially planned to cover 660 EAs and 19,800 households in the survey, but ultimately 100% of EAs and 99.68% of households were successfully covered.

Key information about Indonesia Unemployment Rate

• Indonesia Unemployment Rate dropped to 4.85% in Aug 2025, from the previously reported figure of 4.91% in Aug 2024.
• Indonesia Unemployment Rate is updated yearly, available from Aug 1984 to Aug 2025, with an average rate of 9.86%.
• The data reached an all-time high of 11.24% in Aug 2005 and a record low of 1.62% in Aug 1984.
• The data is reported by reported by Statistics Indonesia.
• In the latest reports, Indonesia Population reached 281.60 million people in Dec 2024.

Abstract

Objective of the survey on employment and unemployment:

The basic objective of the employment-unemployment surveys of NSSO is to get estimates of the employment and unemployment characteristics at national and State level. The statistical indicators on labour market are required for planning, policy and decision making at various levels, both within government and outside. Some of the important uses of these indicators include use by the Planning Commission in evolving employment strategy, use by National Accounts Division in estimating gross domestic product using sector wise workforce participation, and use by various researchers to analyse the condition of the labour market. In this context, it may be mentioned that data collected in NSS employment-unemployment surveys was widely used by the National Commission for Enterprises in the Unorganised Sector (NCEUS), 2009. In NSS 68th round, information on various facets of employment and unemployment will be collected in Schedule 10 (Employment and Unemployment) from all the members of the selected households.

The critical issues in the context of labour force enquiries pertain to defining the labour force and measuring participation of labour force in different economic activities. The activity participation of the people is not only dynamic but also multidimensional; it varies with region, age, education, gender, industry and occupational category. These aspects of the labour force will be captured in detail in the present survey on employment and unemployment. Major types of information that will be collected in this round relate to activity status, industry, occupation and earning from employment for the employees along with education particulars, etc. Besides, the survey will also provide insight into the informal sector and informal employment. Information will be collected from the workers about the type of enterprises in which they were engaged and conditions of employment for the employees. Using the data collected from employment and unemployment surveys, indicators will be generated on labour force participation rate, worker population ratio, unemployment rates, employment in the informal sector, informal employment, wages of employees, etc.

Description:

The survey on employment and unemployment is the prime source of estimates of various parameters of labour force and activity participation of the population. The first quinquennial survey on employment - unemployment, carried out by the NSSO in the 27th round (September 1972 - October 1973), made a marked departure from the earlier employment surveys of NSSO in procedure and content. The concepts and procedures followed in this survey were primarily based on the recommendations of the 'Expert Committee on Unemployment Estimates' (1970). Since then, the seven successive quinquennial surveys conducted in the 32nd, 38th, 43rd, 50th, 55th, 61st and 66th rounds have, more or less, followed an identical approach in the measurement of employment and unemployment. The basic approach (in all these seven quinquennial surveys) had been the collection of data to generate the estimates of employment and unemployment according to the 'usual status' based on a reference period of one year, the 'current weekly status' based on a reference period of one week, and the 'current daily status' based on each day of the seven days preceding the date of survey. In order to reveal the multi-dimensional aspects of the employment-unemployment situation in India, information on several correlates were also gathered in these surveys. Sets of probing questions on some of these aspects had also been one of the basic features of these surveys. In NSS 68th round (July 2011- June 2012), detailed information on employment-unemployment was collected in the same way as was done in the last quinquennial survey, i.e., in NSS 66th round.

A Working Group was set up for the purpose of finalising the survey methodology and schedules of enquiry of the 68th round. Considering all the aspects of current data demand and usefulness of the survey results, the Group has suggested a few improvisations, additions and deletions in the content of the schedule of enquiry for the present survey. The major changes made in the schedule for employment and unemployment survey vis-à-vis the previous quinquennial survey (NSS 66th round) are given below:

a) Block 3: 1) In NSS 66th round survey, along with the information on 'whether the household has NREG job card', information was collected on 'whether got work in NREG works during the last 365 days', 'number of days worked' and 'mode of payment'. In NSS 68th round for rural households, information on Mahatma Gandhi National Rural Employment Guarantee (MGNREG) works was collected on the following: i. whether the household has MGNREG job card ii. number of MGNREG job cards issued to the household iii. whether any member of the household has any bank/post office account Information on the last two items (viz., ii & iii) will be collected from the households which have got MGNREG job card. 2) Household type codes and procedure for determination of household type codes in rural areas have been modified.

b) Block 3.1: In this block information on indebtedness of rural labour households was collected in NSS 66th round. This Block was not canvassed in NSS 68th round.

c) Block 4: i. Instead of collecting information on 'whether currently registered with employment exchange' for persons of age 15-45 years as was done in NSS 66th round, information was collected for the same age group on 'whether currently registered with any placement agency'. ii. In NSS 66th round, for vocational training, detailed information was collected on 'duration of training', 'source from which degree/diploma/certificate received' and 'whether the vocational training was ever helpful in getting a job'. In NSS 68th round, collection of information on vocational training was restricted only to 'whether receiving/received any vocational training' and 'field of training'. iii. For persons of age 18 years and above in rural households with MGNREG job card, information was collected on 'whether registered in any MGNREG job card' and, for those who were registered in any MGNREG job card 'whether worked in MGNREG work during last 365 days'. Such information was not collected in NSS 66th round.

d) Block 5.1/5.2: i. Information on 'seeking or available or suitable for the type of occupation' which was collected in NSS 66th round in Block 5.1 from the non-workers of age below 75 years, was not collected. ii. The probing questions to the self-employed persons in the usual status (Block 5.1/5.2) to identify Home Based Workers have been deleted.

e) Block 5.3: i. In this block, for those who were unemployed on all the 7 days of the week, information was also collected on 'duration of present spell of unemployment'. In NSS 66th round, this question was placed in Block 6. Except retaining this item in Block 5.3, Block 6 of NSS 66th round on follow-up questions for persons unemployed on all the 7 days of the week has been deleted.

f) Block 6 (Block 7.1/7.2 of NSS 66th round): i. Block 7.1 and Block 7.2 have been restructured by deleting some of the items and a new block (Block 6) has been formed in NSS 68th round. ii. Questions on remunerativeness of the earning from self-employment which were asked in NSS 66th round in Block 7.1 to the self-employed persons in principal status and/or subsidiary status have been deleted. These were, 'do you regard the current earning from self-employment as remunerative?' and 'what amount per month would you regard as remunerative?'. iii. Information was collected in NSS 66th round in Block 7.2 on some aspects of labour mobility, such as, whether changed establishment, status, industry, occupation during the period of last two years. Information on these items was not collected in NSS 68th round. iv. The three items of Block 7.2 of NSS 66th round which have been retained in NSS 68th round are placed in Block 6. These are: 1. Is there any union/association in your activity? 2. Whether a member of union/association 3. Nature of employment

Geographic coverage

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

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample design

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

Sampling Frame for First Stage Units: For the rural sector, the list of 2001 census villages (henceforth the term 'village' would include also Panchayat wards for Kerala) constitutes the sampling frame. For the urban sector, the list of UFS blocks (2007-12) is considered as the sampling frame.

Stratification: Within each district of a State/ UT, generally speaking, 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, within the urban areas of a district, if there are one or more towns with population 10 lakhs or more as per population census 2001 in a district, each of them forms a separate basic stratum and the remaining urban areas of the district are considered as another

"Listening to Canadians" is a public opinion survey, which was conducted three times a year. These surveys measure Canadians' views on public policy priorities and their assessment of how the Government of Canada serves Canadians in responding to those priorities. The surveys were conducted by Communications Canada. The questions ask opinions on Governemnt of Canada priorities, the internet, access to Government information and the ability to access Government services. The respondents were also asked questions so that they could be grouped according to geographic and social variables. Topics of interest include: Canada's economy; Contact with the Government; How to contact the Government; Feelings toward the Government of Canada; First Nations People; Living on a reserve; Future of Canada; Information from the Government; Preferred way to get information from Government; Primary to get information from Government; Performance of the Government of Canada; Government ratings; Reasons for good Government performance; Reasons for poor Government performance; Highest Government priority issues; Unemployment; Money given to provincial Governments; Impact of Sept 11th/01 on survey responses; Shaping the impression of the Government; The internet. Basic demographic variables are also included.

Key information about Brazil Unemployment Rate

• Brazil Unemployment Rate dropped to 5.40% in Oct 2025, from the previously reported figure of 5.60% in Sep 2025.
• Brazil Unemployment Rate is updated monthly, available from Mar 2012 to Oct 2025, with an average rate of 11.70%.
• The data reached an all-time high of 14.90% in Mar 2021 and a record low of 5.40% in Oct 2025.
• The data is reported by reported by Brazilian Institute of Geography and Statistics.
• In the latest reports, Brazil Population reached 213.42 million people in Jun 2025.

Abstract

An all-India survey on the situation of employment and unemployment in India during the period July, 2005 to June, 2006 was carried out as part of the annual series in the 62nd round of the National Sample Survey Organisation (NSSO). In this survey, a nation-wide enquiry was conducted in a moderately large sample of households to provide estimates on various characteristics pertaining to employment and unemployment in India and some characteristics associated with them at the national and state levels. Information on various facets of employment and unemployment in India were collected through a schedule of enquiry (Schedule 10).

In terms of subject coverage for employment and unemployment (Schedule 10), this survey is broadly similar to the NSS 60th round. On the request of the Planning Commission, additional information regarding the possession of different types of ‘ration cards’ by the households and the participation of the household members in the rural areas in various public works programmes were also collected. Further, to meet the requirements of the Ministry of Human Resource Development, information on current attendance in educational institutions by persons of age below 30 years and the type of educational institutions being attended by the persons currently attending educational institutions was also collected. Instead of collecting detailed particulars on formal vocational training, as was done in NSS 60th round, it was enquired from the household members, of age 15 – 29 years, whether they received or receiving‘formal’ or ‘non-formal’ vocational training. Besides, information was collected on whether the household members ( of age 15 – 29 years) were receiving formal vocational training. For the purpose of collection of information on industry of activity, National Industrial Classification (NIC), 2004 was used in this survey.

Geographic coverage

The survey covered the whole of the Indian Union except (i) Leh (Ladakh) and Kargil districts of Jammu & Kashmir, (ii) interior villages of Nagaland situated beyond 5 kilometres of the bus route and (iii) villages in Andaman and Nicobar Islands which remain inaccessible throughout the year. All the sample first-stage units of the districts Poonch and Rajouri of Jammu & Kashmir, became casualty and therefore, the districts Poonch and Rajouri of Jammu & Kashmir, are outside the survey coverage. . Thus, the estimates of Jammu and Kashmir and all-India estimates do not include these two districts.

Analysis unit

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

Universe

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

Kind of data

Sample survey data [ssd]

Sampling procedure

An outline of the sampling design: The 62nd round (July 2005 - June 2006) of NSS was earmarked for survey on unorganised manufacturing enterprises, annual survey of consumer expenditure and survey on employment – unemployment. The sampling design adopted for the survey was essentially a stratified multi-stage one for both rural and urban areas. Two frames were used for this survey viz. List frame and Area frame. List frame was used only for urban sector and that too for selection of manufacturing enterprises only and thus is not relevant for discussion. Area frame was adopted for both rural and urban sectors for selection of First Stage Units (FSU) . For the area frame, the list of villages as per census 2001 (for Manipur, 1991 census was used since 2001 census list was not available) was used as frame for the rural sector and the latest available list of UFS blocks was used as frame in the urban sector. However, EC-98 was used as frame for the 27 towns with population 10 lakhs or more (as per Census 2001). The ultimate stage units (USU) were households, in both the sectors. In the case of large villages/ blocks requiring hamlet-group (hg)/ sub-block (sb) formation, one intermediate stage was the selection of two hgs/ sbs from each FSU.

Sample Size – first stage units: At the all-India level, a total number of 9997 FSUs (4847 villages in the rural areas and 5150 UFS blocks in the urban areas) for area frame were allocated on the basis of investigator strength. The allocation between rural and urban sectors was made in proportion to the number of unorganised non-agricultural workers as per EC-98. The total (all-India) rural/ urban sample FSUs were allocated to different States and U.Ts. in proportion to number of unorganised non-agriculture workers as per EC-98 subject to the availability of investigators ensuring more or less uniform work-load. Within each sector of a State/ U.T, the respective sample sizes were allocated to the different strata in proportion to the stratum population as per census 2001.Out of these 9997 FSUs allotted for survey, 9923 FSUs could be surveyed - 4798 in rural and 5125 in urban. Note that in the 62nd round, a sample of 10706 FSUs (4962 villages and 5744 urban blocks) was also selected for survey by the state agencies (State sample) at the all-India level.

Sample size – second stage units: For Schedule 10, a sample of 8 households was planned to be surveyed from each selected village and urban block. In the Central sample, 78879 households were actually surveyed – 37975 in rural areas and 40904 in urban areas.
As regards the actual number of persons surveyed, it was 186571 in the rural sector and 190806 in the urban sector.

Sampling deviation

There was no deviation from the original sample deviation.

Mode of data collection

Face-to-face [f2f]

Research instrument

Summary description of the schedule : The schedule 10 on employment-unemployment for NSS62nd round consisted of 9 blocks as given below.

Block 0: Descriptive identification of sample household Block 1: Identification of sample household Block 2: Particulars of field operations Block 3 - Household Characteristics. Block 4: Demographic particulars of household members Block 5: Usual activity particulars of household member Block 6: Time disposition of household members during the week Block 7: Remarks by investigator/ senior investigators Block 8: Comments by supervisory officer(s).

Cleaning operations

System design document giving details of Receipt of schedule,data entry,verification and updation of data is attached as an external resource document