Geographic coverage

National coverage

Analysis unit

households/individuals

Kind of data

survey

Frequency of data collection

Yearly

Sampling procedure

Sample size:

Abstract

The major aim of the survey was to collect a set of comprehensive statistics on the various dimensions of country’s civilian labour force. The results from the survey provide information required for skill development and planning, for employment generation, for assessing the role and importance of the informal sector, and for identifying the volume and characteristics of the unemployed and underemployed. The specific objectives of the survey are as follows:

• To collect data on the socio-demographic characteristics of the total population i.e. age, sex, marital status, level of education, current enrolment and migration etc;
• To collect current information on the dimensions of Pakistan’s labour force; that is, how many persons are employed, unemployed, underemployed or for some reasons not in the labour market for gainful employment;
• To collect descriptive facts on the nature of work they are engaged in i.e. the occupations the people performed and the nature of work undertaken by the institution/organization, where they work;
• To collect data on employment status of the individuals, i.e. whether they are employers, own account workers, unpaid family workers or paid employees (regular/casual);
• To classify non-agriculture enterprises employing a household member as formal and informal;
• To provide information on the hours worked at main/subsidiary occupations;
• To provide data on wages and mode of payment for paid employees;
• To collect occupational health and safety information of employed persons by causes, type of injuries/diseases occurred, parts of body injured, type of treatment received and period of absence from work; and
• To collect data on the characteristics of unemployed persons i.e. age, sex, level of education, previous experience if any, occupation, industry, employment status related to previous job, how long they have been looking for work, their availability for work and expectations for future employment.

Geographic coverage

The survey covered all urban and rural areas of the four provinces of Pakistan defined as such by 1998 Population Census, excluding Federally Administered Tribal Areas (FATA), military restricted areas, and protected areas of NWFP. The population of excluded areas constitutes about 3% of the total population.

Analysis unit

• Household
• Individual

Kind of data

Sample survey data [ssd]

Sampling procedure

Sampling Frame: Federal Bureau of Statistics (FBS) has developed its own sampling frame for urban areas. Each city/town has been divided into a number of enumeration blocks. Each enumeration block is based on 200 to 250 households on the average with well-defined boundaries and maps. The list of enumeration blocks as updated during 1995 and the list of villages/mouzas/dehs of 1998 Population Census have been taken as sampling frame. Enumeration blocks and villages have been considered as Primary Sampling Units (PSUs) from urban and rural domains respectively.

Stratification Plan Urban Domain: Large size cities i.e. Karachi, Lahore, Gujranwala, Faisalabad, Rawalpindi, Multan, Sialkot, Sargodha, Bahawalpur, Hyderabad, Sukkur, Peshawar, Quetta and Islamabad have been considered as self-representing cities (SRC). Each of these cities constitutes a separate stratum which has been further substratified according to low, middle and high income groups based on the information collected in respect of each Enumeration Block at the time of demarcation/ updating of urban area sampling frame.

Remaining Urban Areas: After excluding the population of self-representing cities from the population of respective defuncted administrative division, the remaining urban population in each administrative division of a province has been grouped together to form another stratum called other urban. Thus each defuncted administrative division in remaining urban areas in all the four provinces constitutes a stratum.

Rural Domain: In rural domain, each administrative district in the Punjab, Sindh and NWFP has been considered an independent and explicit stratum whereas in Balochistan province each defuncted administrative division constitutes a stratum.

Sample Design: A stratified two-stage sample design has been adopted for the survey. i) Selection of primary sampling units (PSUs): Enumeration Blocks in urban domain and mouzas/dehs/villages in rural domain have been taken as Primary Sampling Units (PSUs). In the urban domain, sample PSUs from each ultimate stratum/sub-stratum have been selected with probability proportional to size (PPS) method of sampling scheme. In urban domain, the number of households in an enumeration block as per Quick Count Record Survey, 1995 and population of village/deh/mouza according to Population Census, 1998 have been considered as measure of size. ii) Selection of secondary sampling units (SSUs): Households within sample PSUs have been taken as Secondary Sampling Units (SSUs). A specified number of households i.e. 12 from each urban sample PSU, 16 from rural sample PSU have been selected with equal probability using systematic sampling (with random start) technique.

Sample Size and Its Allocation: Considering the variability of characteristics for which estimates are to be prepared, population distribution and field resources available, a sample size of 18928 sample households have been considered appropriate to provide reliable estimates of key labour force characteristics at the desired level. The entire sample of households (SSUs) has been drawn from 1348 Primary Sampling Units (PSUs) out of which 660 are urban and 688 are rural. As urban population is more heterogeneous therefore, a higher proportion of sample size has been allocated to urban domain. Similarly, NWFP and Balochistan being the smaller provinces and to get reliable estimates, a higher proportion of sample has been assigned to these provinces. After fixing the sample size at provincial level, further distribution of sample PSUs to different strata/sub-strata in rural and urban domains in each province has been made proportionately.

Sample Covered: All enumeration Blocks in urban areas and mouzas/dehs/villages in rural areas were enumerated. The number of sample households (18,890) enumerated is less than the estimated sample size (18,928) due to non-contact and refusal cases in urban and rural areas.

Mode of data collection

Face-to-face [f2f]

Cleaning operations

Further editing had been done at headquarter by the subject matter section. Also during data entry, further editing of computer identified errors by applying computer edit checks, data ranges in numerical values were used to eliminate erroneous data as result of mistakes made during coding. The survey records were edited and corrected through a series of computer processing stages.

Pakistan Labour Force Participation Rate: Urban data was reported at 29.010 % in 2015. This records a decrease from the previous number of 29.350 % for 2014. Pakistan Labour Force Participation Rate: Urban data is updated yearly, averaging 27.540 % from Jun 1990 (Median) to 2015, with 26 observations. The data reached an all-time high of 35.210 % in 1995 and a record low of 25.610 % in 2011. Pakistan Labour Force Participation Rate: Urban data remains active status in CEIC and is reported by Pakistan Bureau of Statistics. The data is categorized under Global Database’s Pakistan – Table PK.G002: Labour Force Survey: Population, Labour Force, Employment and Unemployment.

Abstract

The major aim of the survey is to collect a set of comprehensive statistics on the various dimensions of country’s civilian labour force as a means to pave the way for skill development, planning, employment generation, assessing the role and importance of the informal sector and, sizing up the volume, characteristics and contours of employment. The broad objectives of the survey are as follows: - To collect data on the socio-demographic characteristics of the total population i.e. age, sex, marital status, level of education, current enrolment and migration etc; - To acquire current information on the dimensions of national labour force; i.e. number of persons employed, unemployed, and underemployed or out of labour market; - To gather descriptive facts on the engagement in major occupational trades and the nature of work undertaken by the institutions/organizations; - To profile statistics on employment status of the individuals, i.e. whether they are employers, own account workers, contributing family workers or paid employees (regular/casual); - To classify non-agricultural enterprises employing household member(s) as formal and informal; - To quantify the hours worked at main/subsidiary occupations; - To provide data on wages and mode of payment for paid employees; - To make an assessment of occupational health and safety of employed persons by causes, type of treatment, conditions that caused the accident/injury and time of recovery; and To collect data on the characteristics of unemployed persons i.e. age, sex, level of education, previous experience if any, occupation, industry, employment status related to previous job, waiting time invested in the quest for work, their availability for work and expectations for future employment.

Geographic coverage

National Coverage

The survey covers all urban and rural areas of the four provinces of Pakistan defined as such by 1998 Population Census, excluding Federally Administered Tribal Areas (FATA) and military restricted areas. The population of excluded areas constitutes about 2% of the total population.

All sample enumeration blocks in urban areas and mouzas/dehs/villages in rural areas were enumerated except 184 households due to non contact and refusal cases in urban and rural areas. However, the number of sample households (42,108) enumerated as compared to total sample size (42,292) is high as response rate is (99.56). Province wise detail of dropped sample areas (PSUs) are shown in the table on p4 of the survey report provided a a related document.

Analysis unit

Household/Individual

Universe

The universe for Labour Force Survey consists of all urban and rural areas of the four provinces of Pakistan defined as such by 1998 Population Census excluding FATA and military restricted areas. The population of excluded areas constitutes about 2% of the total population.

Frequency of data collection

Quarterly: average based on 3 monthly data points

Sampling procedure

Sample Design: A stratified two-stage sample design is adopted for the survey.

Stratification Plan Urban Domain: Large cities Karachi, Lahore, Gujranwala, Faisalabad, Rawalpindi, Multan, Sialkot, Sargodha, Bahawalpur, Hyderabad, Sukkur, Peshawar, Quetta and Islamabad are considered as large cities. Each of these cities constitutes a separate stratum, further sub-stratified according to low, middle and high income groups based on the information collected in respect of each enumeration block at the time of demarcation/ updating of urban area sampling frame.

Remaining Urban Areas: In all the four provinces after excluding the population of large cities from the population of an administrative division, the remaining urban population is grouped together to form a stratum.

Rural Domain: Each administrative district in the Punjab, Sindh and Khyber Pakhtunkhwa (KP) is considered an independent stratum whereas in Balochistan, each administrative division constitutes a stratum.

Selection of primary sampling units (PSUs): Enumeration blocks in urban and rural domain are taken as Primary Sampling Units (PSUs). In the urban domain, sample PSUs from each ultimate stratum/sub-stratum are selected with probability proportional to size (PPS) method of sampling scheme. In urban domain, the number of households in an enumeration block by Quick Count technique in 2013 and village or its part (block), updated during House listing in 2011 for conduct of Population Census are taken as sampling frames for rural domain is considered as measure of size.

Selection of secondary sampling units (SSUs): The listed households of sample PSUs are taken as Secondary Sampling Units (SSUs). A specified number of households i.e. 12 from each urban sample PSU, 16 from rural sample PSU are selected with equal probability using systematic sampling technique with a random start.

Sample Size and Its Allocation: A sample of 42,292 households is considered appropriate to provide reliable estimates of key labour force characteristics at National/Provincial level. The entire sample of households (SSUs) is drawn from 2949 Primary Sampling Units (PSUs) out of which 1726 are rural and 1223 are urban. The overall sample has been distributed evenly over four quarters independently. As urban population is more heterogeneous therefore, a higher proportion of sample size is allocated to urban domain. To produce reliable estimates, a higher proportion of sample is assigned to Khyber Pakhtunkhwa and Balochistan in consideration to their smallness. After fixing the sample size at provincial level, further distribution of sample PSUs to different strata in rural and urban domains in each province is made proportionately. The distribution of sample PSUs and SSUs in the urban and rural domain of the four provinces is provided on page 3 the survey report provided under Related documents.

Mode of data collection

Face-to-face [f2f]

Research instrument

Structured

Data appraisal

Reliability of Estimate: Notwithstanding complete observance of the requisite codes to ensure reliability of data, co-efficient of variations and confidence intervals computed in the backdrop of 5% margin of error exercised for determining sample size, are also given in Section II of the survey report to affirm the reliability of estimates.

Pakistan Labour Force Participation Rate: Rural data was reported at 34.010 % in 2015. This records an increase from the previous number of 33.840 % for 2014. Pakistan Labour Force Participation Rate: Rural data is updated yearly, averaging 30.535 % from Jun 1990 (Median) to 2015, with 26 observations. The data reached an all-time high of 37.500 % in 2011 and a record low of 25.040 % in 1995. Pakistan Labour Force Participation Rate: Rural data remains active status in CEIC and is reported by Pakistan Bureau of Statistics. The data is categorized under Global Database’s Pakistan – Table PK.G002: Labour Force Survey: Population, Labour Force, Employment and Unemployment.

Labor force, total in Pakistan was reported at 83643815 in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. Pakistan - Labor force, total - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

Pakistan Unemployment Rate: Urban data was reported at 7.230 % in 2018. This records a decrease from the previous number of 7.980 % for 2015. Pakistan Unemployment Rate: Urban data is updated yearly, averaging 7.950 % from Jun 1990 (Median) to 2018, with 27 observations. The data reached an all-time high of 9.920 % in 2001 and a record low of 4.580 % in 1990. Pakistan Unemployment Rate: Urban data remains active status in CEIC and is reported by Pakistan Bureau of Statistics. The data is categorized under Global Database’s Pakistan – Table PK.G002: Labour Force Survey: Population, Labour Force, Employment and Unemployment. No data for 2016-2017 as per source. Labour Force Survey has not been conducted for these two years due to Population Census.

Pakistan Employment: Urban data was reported at 20.960 Person mn in 2018. This records an increase from the previous number of 17.570 Person mn for 2015. Pakistan Employment: Urban data is updated yearly, averaging 12.730 Person mn from Jun 1990 (Median) to 2018, with 27 observations. The data reached an all-time high of 20.960 Person mn in 2018 and a record low of 8.250 Person mn in 1991. Pakistan Employment: Urban data remains active status in CEIC and is reported by Pakistan Bureau of Statistics. The data is categorized under Global Database’s Pakistan – Table PK.G002: Labour Force Survey: Population, Labour Force, Employment and Unemployment. No data for 2016-2017 as per source. Labour Force Survey has not been conducted for these two years due to Population Census.

Pakistan Employment: Transport data was reported at 3.110 Person mn in 2015. This records an increase from the previous number of 3.070 Person mn for 2014. Pakistan Employment: Transport data is updated yearly, averaging 2.365 Person mn from Jun 1990 (Median) to 2015, with 26 observations. The data reached an all-time high of 3.110 Person mn in 2015 and a record low of 1.500 Person mn in 1990. Pakistan Employment: Transport data remains active status in CEIC and is reported by Pakistan Bureau of Statistics. The data is categorized under Global Database’s Pakistan – Table PK.G002: Labour Force Survey: Population, Labour Force, Employment and Unemployment.

Labor force, female (% of total labor force) in Pakistan was reported at 22.85 % in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. Pakistan - Labor force, female - actual values, historical data, forecasts and projections were sourced from the World Bank on June of 2025.

Analysis unit

Households Individuals

Mode of data collection

Face-to-face [f2f]

Pakistan Employment: Rural data was reported at 40.750 Person mn in 2018. This records an increase from the previous number of 39.850 Person mn for 2015. Pakistan Employment: Rural data is updated yearly, averaging 27.740 Person mn from Jun 1990 (Median) to 2018, with 27 observations. The data reached an all-time high of 40.750 Person mn in 2018 and a record low of 21.270 Person mn in 1991. Pakistan Employment: Rural data remains active status in CEIC and is reported by Pakistan Bureau of Statistics. The data is categorized under Global Database’s Pakistan – Table PK.G002: Labour Force Survey: Population, Labour Force, Employment and Unemployment. No data for 2016-2017 as per source. Labour Force Survey has not been conducted for these two years due to Population Census.

Pakistan Employment: Electricity and Gas Distribution data was reported at 0.450 Person mn in 2015. This records an increase from the previous number of 0.270 Person mn for 2014. Pakistan Employment: Electricity and Gas Distribution data is updated yearly, averaging 0.275 Person mn from Jun 1990 (Median) to 2015, with 26 observations. The data reached an all-time high of 0.450 Person mn in 2015 and a record low of 0.180 Person mn in 1990. Pakistan Employment: Electricity and Gas Distribution data remains active status in CEIC and is reported by Pakistan Bureau of Statistics. The data is categorized under Global Database’s Pakistan – Table PK.G002: Labour Force Survey: Population, Labour Force, Employment and Unemployment.

Pakistan Unemployment Rate: Rural data was reported at 5.030 % in 2018. This records an increase from the previous number of 5.010 % for 2015. Pakistan Unemployment Rate: Rural data is updated yearly, averaging 5.010 % from Jun 1990 (Median) to 2018, with 27 observations. The data reached an all-time high of 7.550 % in 2003 and a record low of 2.600 % in 1990. Pakistan Unemployment Rate: Rural data remains active status in CEIC and is reported by Pakistan Bureau of Statistics. The data is categorized under Global Database’s Pakistan – Table PK.G002: Labour Force Survey: Population, Labour Force, Employment and Unemployment. No data for 2016-2017 as per source. Labour Force Survey has not been conducted for these two years due to Population Census.

In 2023, 36.1 percent of the workforce in Pakistan worked in the agricultural sector, about a quarter worked in industry, and 38.31 percent in the services sector. The primary sectorThe most common breakdown of a country’s economy is into three sectors; the primary sector, which includes agriculture, raw materials, fishing, and hunting, the secondary sector, which is also called the industrial sector and includes manufacturing, and the tertiary sector, which encompasses intangible goods and services, like financial services, tourism, or telecommunications. Usually, an advanced economy focuses on the services sector, while in a developing economy, the primary sector is still prevalent. In Pakistan, agriculture plays an important role in trade and production, and most Pakistanis are employed in the agricultural sector – however, the services sector generates the lion’s share of GDP Is Pakistan on the verge of being a developed country?Typically, a developed country shifts GDP generation and employment to intangible goods, which also often means that its citizens move to the city, away from rural areas. In Pakistan, urbanization progresses slowly, and most inhabitants live in rural areas. One reason for this is Pakistan’s vast arable land area, which allows for the production and export of raw materials. To be a developed country, Pakistan still needs to put in some work and improve the standard of living and infrastructure, among other factors.

In 2024, the unemployment rate in Pakistan was at approximately 5.47 percent, a slight increase from 5.41 percent the previous year. Unemployment as an economic key indicatorThe unemployment rate of a country represents the share of people without a job in the country’s labor force, i.e. unemployed persons among those who are able and/or willing to work. Among other factors, it takes population growth into account, and thus increases in the labor force, as well as the age of the population. A high unemployment rate usually indicates economic troubles, with a popular example being Greece, where the unemployment rate skyrocketed from 7.76 percent in 2008 to 27.5 percent as a result of the Great Recession. From plowshares to keyboardsWhile Pakistan’s unemployment slumped below the one percent mark in 2010, it is now on the rise again and currently standing at just over four percent. Traditionally, most Pakistanis work in agriculture however, the lion’s share of the country’s GDP is generated by services, like tourism, banking, and IT. While agriculture is still important for Pakistan’s economy, the services sector is gaining ground in the country, and more and more people are moving to urban areas from the countryside to find jobs in the cities.

The youth unemployment rate in Pakistan increased by 0.2 percentage points (+2.06 percent) compared to the previous year. In total, the youth unemployment rate amounted to 9.86 percent in 2024. This increase was preceded by a declining youth unemployment rate.The youth unemployment rate refers to the share of the economically active population aged 15 to 24 currently without work but in search of employment. The youth unemployment rate does not include economically inactive persons such as the long-term unemployed or full-time students.Find more key insights for the youth unemployment rate in countries like Nepal and Afghanistan.

Abstract

South Asia Regional Flagship: More and Better Jobs in South Asia

Employment is a major issue throughout the world. To enjoy life, people need productive jobs that remove them from the daily struggle of making ends meet. According to the International Labour Organization (ILO), as many as 30 million people lost their jobs as a result of the 2008 crisis. Youth unemployment is especially high and inequality has increased. As recent events in the Middle East and North Africa demonstrate, joblessness and inequality can trigger political instability and unrest.

When the World Bank South Asia Region decided to initiate a yearly Flagship Report series, it was clear that the very first report needed to concentrate on the important topic of More and Better Jobs in South Asia. Although one of the fastest growing regions, South Asia is still home to the largest number of the world's poor and the pace of creating productive jobs has lagged behind economic growth. Conflict and social and gender issues also increase the challenge of generating more and more productive jobs. Without urgent action, the potential for the demographic dividend from about 150 million entrants to the labor force over the next decade may not be realized.

The Flagship seeks to answer four questions, which could have implications beyond South Asia. - How is South Asia performing in creating more and better jobs? - Where are the better jobs? - What are constraints in supply and demand in moving towards better jobs? - How does conflict affect job creation?

Kind of data

Sample survey data [ssd]

Mode of data collection

Face-to-face [f2f]

Abstract

The major aim of the survey is to collect a set of comprehensive statistics on the various dimensions of country’s civilian labour force. The survey profiles information to pave the way for skill development, planning, employment generation, assessing the role and importance of the informal sector and, sizing up the volume, characteristics and contours of employment. The specific objectives of the survey are as follows:

• To collect data on the socio-demographic characteristics of the total population i.e. age, sex, marital status, level of education, current enrolment and migration etc;
• To acquire current information on the dimensions of Pakistan’s labour force; i.e. number of persons employed, unemployed, underemployed or out of labour market;
• To gather descriptive facts on the engagement in major occupational traits and the nature of work undertaken by the institution/organization;
• To profile statistics on employment status of the individuals, i.e.,whether they are employers, own account workers, unpaid family workers or paid employees (regular/casual);
• To classify non-agricultural enterprises employing household member(s) as formal and informal;
• To put figure on the hours worked at main/subsidiary occupations;
• To provide data on wages and mode of payment for paid employees;
• To quantify occupational health and safety of employed persons by causes, type of injuries/diseases occurred, parts of body injured, type of treatment received and period of absence from work; and
• To collect data on the characteristics of unemployed persons i.e. age, sex, level of education, previous experience if any, occupation, industry, employment status related to previous job, waiting time invested in the quest for work, their availability for work and expectations for future employment.

Geographic coverage

The universe for Labour Force Survey consists of all urban and rural areas of the four provinces of Pakistan defined as such by 1998 Population Census, excluding Azad Jammu and Kashmir, Northern Areas, Federally Administered Tribal Areas (FATA) and military restricted areas and protected areas of NWFP. The Population of excluded areas constitute about 3% of the total population.

Sampling procedure

Sample Design Sampling Frame: Federal Bureau of Statistics (FBS) has developed its own sampling frame for urban areas. Each city/town is divided into a number of enumeration blocks. Each enumeration block is based on 200 to 250 households on the average with well defined boundaries and maps. The list of enumeration blocks as updated through Economic Census 2003-04 and the list of villages/mouzas/dehs of 1998 Population Census have been taken as sampling frame. Enumeration blocks and villages are considered as Primary Sampling Units (PSUs) from urban and rural domains respectively.

Stratification Plan Urban Domain: Karachi, Lahore, Gujranwala, Faisalabad, Rawalpindi, Multan, Sialkot, Sargodha, Bahawalpur, Hyderabad, Sukkur, Peshawar, Quetta and Islamabad are considered as large cities. Each of these cities constitutes a separate stratum, further sub-stratified according to low, middle and high income groups based on the information collected in respect of each Enumeration Block at the time of demarcation/ updating of urban area sampling frame.

Remaining Urban Areas: After excluding the population of large cities from the population of respective ex-administrative division, the remaining urban population of exadministrative division from provinces is grouped together to form another stratum called other urban. Thus each ex-division in remaining urban areas in the four provinces constitutes a stratum.

Rural Domain: Each administrative district in the Punjab, Sindh and NWFP is considered an independent stratum whereas in Balochistan, each ex-administrative division constitutes a stratum.

Sample Design: A stratified two-stage sample design has been adopted for the survey. i) Selection of primary sampling units (PSUs): Enumeration Blocks in urban domain and mouzas/dehs/villages in rural are taken as Primary Sampling Units (PSUs). Sample PSUs are drawn with probability proportional to size (PPS) method. In urban domain, the number of households in an enumeration block as updated in 2003-04 through Economic Census and respective population of 1998 Census for a stratum is considered as measure of size. ii) Selection of secondary sampling units (SSUs): The constituent households of sample PSUs are taken as Secondary Sampling Units (SSUs). A specified number of households i.e. 12 from each urban sample PSU, 16 from rural sample PSU have been selected with equal probability using systematic sampling technique with random a start.

Sample Size and Its Allocation: Keeping in view the variability of characteristics, population distribution and availability of field resources, a sample of 18912 households have been considered appropriate to provide reliable estimates of key labour force characteristics. The entire sample of households (SSUs) has been drawn from 1347 Primary Sampling Units (PSUs) out of which 660 are urban and 687 are rural. As urban population is more heterogeneous therefore, a higher proportion of sample size is allocated to urban domain. In order to get reliable estimates, a higher proportion of sample has been assigned to NWFP and Balochistan in consideration to their smallness. After fixing the sample size at provincial level, further distribution of sample PSUs to different strata in rural and urban domains in each province is made proportionately.

Sample Covered: All enumeration Blocks in urban areas and mouzas/dehs/villages in rural areas have been enumerated. The number of sample households (18,858) enumerated is less than the estimated sample size (18,912) due to non-contact and refusal cases in urban and rural areas.

Mode of data collection

Face-to-face [f2f]

Research instrument

The LFS 2003-04 Questionnaire is divided into the following 11 sections: Section 1: Identification Section 2: Field operations Section 3: Editing/coding at headquarter Section 4: Household composition and demographic information Section 5: Current activity Section 6: Underemployment Section 7: For paid employees only Section 8: Occupational injuries/diseases (all employed persons) Section 9: Questions to be addressed to head of household or his/her proxy Section 10: Unemployment Section 11: Work activity

Cleaning operations

Editing is done at headquarter by the subject matter section. Computer edit checks are applied to get even with errors identified at the stage of data entry. Data ranges in numerical values are used to eliminate erroneous data resulting from mistakes made during coding. The survey records are further edited and rectified through a series of computer processing stages.

Tingkat Pengangguran Pakistan dilaporkan sebesar 6.30 % pada 2021. Rekor ini turun dibanding sebelumnya yaitu 6.90 % untuk 2019. Data Tingkat Pengangguran Pakistan diperbarui tahunan, dengan rata-rata 5.80 % dari 1980 sampai 2021, dengan 39 observasi. Data ini mencapai angka tertinggi sebesar 8.27 % pada 2003 dan rekor terendah sebesar 3.04 % pada 1986. Data Tingkat Pengangguran Pakistan tetap berstatus aktif di CEIC dan dilaporkan oleh Pakistan Bureau of Statistics. Data dikategorikan dalam Pakistan Global Database – Table PK.G002: Labour Force Survey: Population, Labour Force, Employment and Unemployment.