This statistic shows the biggest cities in Pakistan as of 2023. In 2023, approximately 18.87 million people lived in Karāchi, making it the biggest city in Pakistan.

Population in largest city in Pakistan was reported at 17236230 in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. Pakistan - Population in largest city - actual values, historical data, forecasts and projections were sourced from the World Bank on March of 2025.

Pakistan PK: Population in Largest City data was reported at 15,020,931.000 Person in 2017. This records an increase from the previous number of 14,650,981.000 Person for 2016. Pakistan PK: Population in Largest City data is updated yearly, averaging 6,793,799.000 Person from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 15,020,931.000 Person in 2017 and a record low of 1,853,325.000 Person in 1960. Pakistan PK: Population in Largest City data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Pakistan – Table PK.World Bank.WDI: Population and Urbanization Statistics. Population in largest city is the urban population living in the country's largest metropolitan area.; ; United Nations, World Urbanization Prospects.; ;

The regional cities accessibility dataset is modelled as raster-based travel time/cost analysis. Individual cumulative travel time/cost maps were produced for major regional cities (>850k habitants) less than 500 km from the border. The following values were assumed: City - Country Delhi 16,349,831 Ahmedabad 5,633,927 Surat 4,591,246 Kabul 4,434,550 Jaipur 3,046,163 Vadodara 1,752,371 Ludhiana 1,618,879 Meerut 1,571,434 Jammu 1,529,958 Rajkot 1,390,640 Srinagar 1,264,202 Amritsar 1,183,549 Jodhpur 1,138,300 Chandigarh 1,026,459 Kota 1,001,694 Moradabad 889,810 Aligarh 874,408 Dushanbe 863,400 This 500m resolution raster dataset is part of FAO’s Hand-in-Hand Initiative, Geographical Information Systems - Multicriteria Decision Analysis (GIS-MCDA) aimed at the identification of value chain infrastructure sites (optimal location).

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 421 households due to non contact and refusal cases in urban and rural areas. However, the number of sample households (35067) enumerated as compared to total sample size (35488) is high as response rate is 98.8%.

Analysis unit

• Household
• Individuals aged 10 years and above

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.

Kind of data

Sample survey data [ssd]

Frequency of data collection

Quarterly

Sampling procedure

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

Sampling Frame: Pakistan Bureau of Statistics (PBS) has developed its own sampling frame for urban areas. Each city/town is divided into enumeration blocks. Each enumeration block is comprised of 200 to 250 households on the average with well-defined boundaries and maps.

The list of enumeration blocks as updated through Economic Census 2003 and the list of villages/mouzas/dehs of 1998 Population Census are taken as sampling frames. Enumeration blocks & villages are considered as Primary Sampling Units (PSUs) for urban and rural domains respectively.

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 domain and mouzas/dehs/villages in rural 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 as updated through Economic Census 2003 and village population of 1998 Census 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 35,488 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 2548 Primary Sampling Units (PSUs) out of which 1228 are rural and 1320 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.

Mode of data collection

Face-to-face [f2f]

Research instrument

Structured questionnaire.

Cleaning operations

Editing and coding 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. The relevant numerical techniques 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.

Response rate

98.8%

Data appraisal

Notwithstanding complete observance of the requisite codes to ensure reliability of data, co-efficient of variations, computed in the backdrop of 5% margin of error exercised for determining sample size, are also given below to affirm the reliability of estimates.

There were 43 764 900 Facebook users in Pakistan in January 2023, which accounted for 18.9% of its entire population. The majority of them were men - 77%. People aged 18 to 24 were the largest user group (15 900 000). The highest difference between men and women occurs within people aged 25 to 34, where men lead by 12 100 000.

PK：最大城市人口在12-01-2017达15,020,931.000人，相较于12-01-2016的14,650,981.000人有所增长。PK：最大城市人口数据按年更新，12-01-1960至12-01-2017期间平均值为6,793,799.000人，共58份观测结果。该数据的历史最高值出现于12-01-2017，达15,020,931.000人，而历史最低值则出现于12-01-1960，为1,853,325.000人。CEIC提供的PK：最大城市人口数据处于定期更新的状态，数据来源于World Bank，数据归类于全球数据库的巴基斯坦 – Table PK.World Bank.WDI：人口和城市化进程统计。